the effect of omega-3 polyunsaturated fatty acids on the ......marc-olivier trépanier doctorate of...

The Effect of Omega-3 Polyunsaturated Fatty Acids on the Resolution of Inflammation in

the Rodent Brain

By

Marc-Olivier Trépanier

A thesis submitted in conformity with the requirements for the degree of Doctor of

Philosophy

Department of Nutritional Sciences

University of Toronto

© Copyright by Marc-Olivier Trépanier 2016

ii

The Effect of Omega-3 Polyunsaturated Fatty Acids on the Resolution of Inflammation in

the Rodent Brain

Marc-Olivier Trépanier

Doctorate of Philosophy

Department of Nutritional Sciences

University of Toronto

2016

Abstract

Resolution of inflammation in the periphery is believed to be mediated by omega-

3 polyunsaturated fatty acids (n-3 PUFA) derived specialized pro-resolving lipid

mediators. However, the resolution of neuroinflammation, and the role of n-3 PUFA and

their specialized pro-resolving lipid mediators in the resolution of neuroinflammation

have yet to be studied. Moreover, while ischemia induces the production of various

mediators in the brain, this effect has yet to be demonstrated for specialized pro-resolving

lipid mediators.

The first objective of this thesis was to develop a lipidomic approach to measure

the rodent neurolipidome without the effect of ischemia using head-focused microwave

fixation. Once a lipidomic approach was developed, we attempted to develop a self-

resolving model of neuroinflammation and to determine the effect of increasing brain

docosahexaenoic acid (DHA) on resolution of neuroinflammation.

We demonstrated that microwave-fixation inhibits ischemia-induced production

of bioactive mediators, including specialized pro-resolving lipid mediators, and changes

in various intact lipid species.

iii

We then developed a self-resolving model of neuroinflammation using

intracerebroventricular injections of lipopolysaccharide (LPS). Following LPS injection,

microglia activation peaked at 5 days and returned to baseline by 21 days. Using a

microarray, we illustrated that various markers had varying time courses of inflammation.

Interestingly, no neutrophil infiltration was detected. Since neutrophils carry the

lipoxygenase enzyme, which produces specialized pro-resolving lipid mediators, we also

did not detect specialized pro-resolving mediator production following LPS injection as

measured by our new lipidomic approach combined with microwave fixation.

In order to increase brain DHA, we compared a wildtype mouse fed a safflower

diet deficient in n-3 PUFA to the fat-1 mouse and a wildtype mouse fed a fish oil diet

high in n-3 PUFA. Increasing brain DHA resulted in modest increases in resolution of

microglia activation and cyclooxygenase (COX)-2 mRNA expression. However, many

other inflammatory markers were unaffected by the increased brain DHA.

In conclusion, we illustrated that microwave fixation inhibits the ischemia-

induced changes on the rodent neurolipidome and that n-3 PUFA have small pro-

resolving properties in a self-resolving model of neuroinflammation. These appear to be

independent of specialized pro-resolving mediator production.

iv

Acknowledgements

First and foremost, I would like to thank my supervisor, Dr. Richard Bazinet,

for mentoring me for the past 7 years. Your guidance throughout my academic

career has been invaluable and I would not have achieved what I have achieved to

this date without it. I do not know what my future career holds, but I am confident

that because of you I am more than ready. Finally, I just wanted to say thank you for

making us feel appreciated. All the dinners and the nights out have created

memories I will not soon forget, and I always enjoy our conversation about food and

drinks. I don’t know where I will end up, but I truly hope we can keep in touch.

I also need to thank my co-supervisor, Dr. Mojgan Masoodi. You have been a

great help throughout my thesis. Moreover, you were a great host during my trip to

Lausanne. I will never forget eating fondue in Gruyere. I also want to thank my

advisory committee, Dr. Ali Salahpour and Dr. Romina Mizrahi. Your guidance

throughout my thesis was much appreciated. Special thanks also need to go to Dr.

W.M. Burnham, my first mentor.

I would also like to thank my lab mates for being such great colleagues over

the past 7 years. I would especially like to thank Katie. You were so generous with

your time and working with you was a pleasure. Anthony, sharing an office with you

and chatting about sports definitely made my day more entertaining. I’d also like to

thank Sarah for training me and helping me get my project off the ground. Vanessa,

it was very enjoyable to train you and you have a bright future ahead of you. To the

rest of you, Chuck, Lauren, Kayla, Lin, Shoug, Scott, Alex, and Adam, I want to thank

v

you for all the help you offered over the years and for making the work place so

great.

The Natural Science and Engineering Research Council should be thanked for

providing me with a studentship over the course of my studies. The Canadian

Institute of Health Research should be acknowledged for funding the project.

Finally, I would like to thank the International Society for the Study of Fatty Acids

and Lipids for awarding me with the International Research Exchange Scholarship

to allow me to travel to Lausanne, Switzerland.

Finally, I want to thank all my family and friends for being there for me over

the years. To Louise and Pierre, thank you for always being there for me and being

my home away from home. Sarah and Clayton, thank you for always making time for

me either by coming to visit or hosting dinner. I can’t wait to meet Raphael. To my

parents, Mario and Francine, words can’t describe the gratitude I have for you. This

thesis would not have been possible if it weren’t for you. I dedicate this thesis to

you. And finally, Claudia, the love of my life, thank you for being in my life and for all

the support you offer. I just can’t wait to start this next chapter in my life with you.

vi

Table of Contents

List of Figures ............................................................................................................................ ix

List of Tables ............................................................................................................................. xi

List of Abbreviations ........................................................................................................... xiii

Chapter 1: Introduction .......................................................................................................... 1 1.1. Polyunsaturated fatty acids .................................................................................................... 2 1.2. Sources of PUFA .......................................................................................................................... 2 1.3. Synthesis ........................................................................................................................................ 3 1.4. Brain uptake ................................................................................................................................. 5 1.5. N-3 PUFA and anti-inflammation .......................................................................................... 6 1.6. Models of neuroinflammation ............................................................................................... 9 1.7 The lipopolysaccharide (LPS) model of neuroinflammation ................................... 10 1.8. The fat-1 mouse........................................................................................................................ 12 1.9. Objectives ................................................................................................................................... 14

Chapter 2: N-3 Polyunsaturated Fatty Acids in Animal Models with Neuroinflammation: An Update ....................................................................................... 16

2.1. Abstract ....................................................................................................................................... 17 2.2. Introduction .............................................................................................................................. 18 2.3. Results ......................................................................................................................................... 24

2.3.1 n-3 PUFA and neuroinflammation in ischemia or ischemia/reperfusion ................ 24 2.3.2. n-3 PUFA and neuroinflammation in spinal cord injury ................................................. 31 2.3.3. n-3 PUFA and neuroinflammation in aging .......................................................................... 37 2.3.4. n-3 PUFA and neuroinflammation in Parkinson’s disease ............................................. 40 2.3.5. n-3 PUFA and neuroinflammation with lipopolysaccharide ......................................... 44 2.3.6. n-3 PUFA and neuroinflammation in i.c.v. IL-1 ................................................................ 48 2.3.7. n-3 PUFA and neuroinflammation in traumatic brain injury ....................................... 50 2.3.8. n-3 PUFA and neuroinflammation in neuropathic pain .................................................. 53 2.3.9. n-3 PUFA and neuroinflammation in diabetes.................................................................... 53 2.3.10. n-3 PUFA and neuroinflammation in other models ....................................................... 56

2.4. Conclusion .................................................................................................................................. 60 2.5. Acknowledgments ................................................................................................................... 63

Chapter 3: Objectives and Hypotheses ........................................................................... 64 3.1 Objectives .................................................................................................................................... 65 3.2. Hypotheses ................................................................................................................................ 65

Chapter 4: High-resolution lipidomics coupled with rapid fixation reveals novel ischemia-induced signaling in the rat neurolipidome ................................. 66

4.1. Abstract ....................................................................................................................................... 67 4.2 Introduction ............................................................................................................................... 68 4.3. Methods ....................................................................................................................................... 71

4.3.1. Subjects ............................................................................................................................................... 71 4.3.2. Treatment groups ........................................................................................................................... 74 4.3.3. Microwave fixation ......................................................................................................................... 74 4.3.4. Brain preparation ........................................................................................................................... 75 4.3.5. Lipid extraction ................................................................................................................................ 75

vii

4.3.6. Mass spectrometry analysis ....................................................................................................... 77 4.3.7. Data analysis ..................................................................................................................................... 79

4.4. Results ......................................................................................................................................... 80 4.5. Discussion .................................................................................................................................. 89 4.6. Acknowledgements................................................................................................................. 94 4.7. Author contributions ............................................................................................................. 95 4.8. Conflict of interest statement .............................................................................................. 95

Chapter 5: N-3 polyunsaturated fatty acids mediate small changes in the resolution of neuroinflammation following intracerebroventricular lipopolysaccharide injection independent of pro-resolving lipid mediators .. 96

5.1. Abstract ....................................................................................................................................... 97 5.2. Introduction .............................................................................................................................. 99 5.3. Methods ..................................................................................................................................... 101

5.3.1. Diets ................................................................................................................................................... 102 5.3.2. Subjects ............................................................................................................................................ 104 5.3.3. Intracerebroventricular LPS injections .............................................................................. 104 5.3.4. Immunohistochemistry ............................................................................................................. 105 5.3.5. Genetic expression analysis ..................................................................................................... 106 5.3.6. Lipidomic analysis ....................................................................................................................... 109 5.3.7. Bioactive mediator extraction ................................................................................................ 109 5.3.8. Extraction of intact lipids from the brain ........................................................................... 110 5.3.9. Mass spectrometry analysis .................................................................................................... 111 5.3.10. Total lipid extraction ................................................................................................................ 112 5.3.11. Fatty acid methyl ester analysis by gas-chromatography for Experiment 2 .... 113 5.3.12. Y-maze............................................................................................................................................ 113 5.3.13. Statistics ........................................................................................................................................ 114

5.4. Results ....................................................................................................................................... 115 5.4.1. Experiment 1 .................................................................................................................................. 115 5.4.1.1. Microglial activation peaked by 5 days and resolved by 21 days, independent of neutrophil and macrophage infiltration ......................................................................................... 115 5.4.1.2. Gene expression of various neuroinflammatory markers have different time courses of expression following LPS injection ............................................................................. 117 5.4.1.3. Neuroinflammation alters some intact lipid species, but does not affect the production of bioactive mediators .................................................................................................... 128 5.4.1.4. Neuroinflammation does not affect cognitive abilities in the Y-maze ................ 128 5.4.2. Experiment 2 .................................................................................................................................. 128 5.4.2.1. The fat-1 gene and fish oil diet increases brain DHA................................................. 128 5.4.2.2. Increased brain DHA increases microglial resolution .............................................. 131 5.4.3.3. Increased brain DHA decreases COX-2 expression but not the expression of other pro-inflammatory markers ...................................................................................................... 134

5.4. Discussion ................................................................................................................................ 136

Chapter 6: Discussion ......................................................................................................... 141 6.1. Overall findings ...................................................................................................................... 142 6.2. Limitations ............................................................................................................................... 143 6.3. Future directions ................................................................................................................... 146 6.4. Significance .............................................................................................................................. 149 6.5. Conclusions .............................................................................................................................. 151

References .............................................................................................................................. 153

viii

Appendix 1: Postmortem evidence of cerebral inflammation in schizophrenia: a systematic review............................................................................................................. 186

ix

List of Figures Figure 1-1. The n-3 and n-6 synthetic pathways ........................................................................ 4

Figure 4-1. Flow of methods in Chapter 4 .................................................................................. 73

Figure 4-2. Microwave fixation inhibits ischemia-induced production of bioactive

lipid mediators ............................................................................................................... 81

Figure 4-3. Microwave fixation inhibits ischemia-induced changes of intact lipids .. 84

Figure 4-4. Correlation network between lipid mediators and intact lipids in the CO2

group. ................................................................................................................................. 90

Figure 5-1. Time course of Iba1 optical density in the hippocampus in the C57Bl/6

mouse following i.c.v. LPS. ....................................................................................... 116

Figure 5-2. Hippocampal microglial M1 markers’ response to i.c.v. LPS over time. 120

Figure 5-3. Hippocampal microglial M2 markers’ response to i.c.v. LPS over time. 121

Figure 5-4. Hippocampal mRNA expression of infiltrating cell markers following

i.c.v. LPS over time. ..................................................................................................... 122

Figure 5-5. Hippocampal mRNA expression of astrocytic markers following i.c.v. LPS

over time. ........................................................................................................................ 124

Figure 5-6. Hippocampal cytokine mRNA response to i.c.v. LPS over time ................ 125

Figure 5-7. Hippocampal NF-B pathways mRNA markers’ response to i.c.v. LPS

over time. ........................................................................................................................ 126

Figure 5-8. Hippocampal arachidonic cascade markers’ response to i.c.v. LPS over

time. .................................................................................................................................. 127

Figure 5-10. Spontaneous alternation performance in the Y-maze 7 days following

i.c.v. LPS injection. ....................................................................................................... 130

x

Figure 5-11. Increased brain DHA in the fat-1 mice and mice fed a fish oil diet at 12

weeks of age. ................................................................................................................. 132

Figure 5-12. Effect of increased brain DHA on the resolution of microglial activation

............................................................................................................................................ 133

Figure 5-13. Effect of increased brain DHA on the time course of mRNA expression

of example pro-inflammatory markers. ............................................................. 135

xi

List of Tables Table 2-1: Summary of studies investigating the effects of n-3 PUFA in ischemia and

ischemia/reperfusion models .................................................................................. 25

Table 2-2: Summary of studies investigating the effects of n-3 PUFA in spinal cord

injury models .................................................................................................................. 33

Table 2-3: Summary of studies investigating the effects of n-3 PUFA in aging and

Alzheimer’s disease models ...................................................................................... 38

Table 2-4: Summary of studies investigating the effects of n-3 PUFA in Parkinson’s

disease models ............................................................................................................... 42

Table 2-5: Summary of studies investigating the effects of n-3 PUFA in

lipopolysaccharide models ........................................................................................ 45

Table 2-6: Summary of studies investigating the effects of n-3 PUFA in IL-1 models

.............................................................................................................................................. 49

Table 2-7: Summary of studies investigating the effects of n-3 PUFA on traumatic

brain injury models ...................................................................................................... 51

Table 2-8: Summary of studies investigating the effects of n-3 PUFA in neuropathic

pain models...................................................................................................................... 54

Table 2-9: Summary of studies investigating the effects of n-3 PUFA in diabetes

models................................................................................................................................ 55

Table 2-10: Summary of studies investigating the effects of n-3 PUFA on other

neuroinflammatory models ....................................................................................... 57

Table 4-1: Confusion matrix for PLS-DA calculated for lipid mediators. ....................... 83

xii

Table 4-2: Class-based prediction statistics for PLS-DA calculated for lipid

meditators. ....................................................................................................................... 83

Table 4-3: Confusion matrix for PLS-DA calculated for intact lipids. .............................. 86

Table 4-4: Class-based prediction statistics for PLS-DA calculated for intact lipids. 86

Table 4-5: Top 20 lipid mediators in PLS-DA discrimination of the four phenotypic

groups ................................................................................................................................ 87

Table 4-6: Top 20 intact lipids in PLS-DA discrimination of the four phenotypic

groups ................................................................................................................................ 88

Table 5-1: Percent of total fatty acids of the 3 experimental diets. ................................ 103

Table 5-2. Top 20 fold change in gene expression at each time point following LPS

injection........................................................................................................................... 118

xiii

List of Abbreviations A – amyloid beta

ANOVA – analysis of variance

ARA – arachidonic acid

BBB – blood-brain barrier

CD – cluster of differentiation

CCL – chemokine (c-c motif) ligand

CO2 – 5 minutes of CO2 asphyxiation (group)

CO2 + MW – 5 minutes of CO2 asphyxiation followed by microwave fixation (group)

COX – cyclooxygenase

CXCL – chemokine (c-x-c motif) ligand

CX3CL – chemokine (c-x3-c motif) ligand

DHA – docosahexaenoic acid

EPA – eicosapentaenoic acid

F1SO – fat-1 mice fed safflower oil (group)

GFAP – glial fibrillary acidic protein

Iba1 – ionized calcium-binding adaptor molecule 1

IFN – interferon

IL – interleukin

i.c.v. – intracerebroventricular

i.p. - intraperitoneal

i.v. – intravenous

LCN - lipocalin

LPS – lipopolysaccharide or LPS injection 3 hr followed by microwave fixation (group)

MHC – major histocompability complex

m/z – mass/charge

n – omega

NF-B – nuclear factor kappa-light-chain-enhancer of activated B cells

PET – positron emission topography

PG – prostaglandin

p.o. - per os

PPAR – peroxisome proliferator-activated receptor

PUFA – polyunsaturated fatty acid or acids

qPCR – quantitative polymerase chain reaction

Ri – resolution index

SAA3 – serum amyloid A3

s.c. – subcutaneous

SERPIN – serpin peptidase inhibitor

SEM – standard error of the mean

TNF – tumor necrosis factor

WT – wildtype

WTFO – wildtype mice fed fish oil (group)

WTSO – wildtype mice fed safflower oil (group)

1

Chapter 1: Introduction

2

1.1. Polyunsaturated fatty acids

Fatty acids are defined as acyl chains containing a carboxylic group at the -

carbon. There are several types of fatty acids, including saturated, monounsaturated, and

polyunsaturated. Saturated fatty acids, which include stearic and palmitic acids, do not

contain any double bonds. Monounsaturated acids, which include oleic acid, contain a

single double bond. Polyunsaturated fatty acids (PUFA), such as docosahexaenoic acid

(DHA) and arachidonic acid (ARA), have more than one double bond. The first double

bond in relation to the methyl end of the fatty acids, known as the omega end, determines

the family of polyunsaturated fatty acids. A double bond 3 carbons removed from the

methyl carbon produces an omega-3 (n-3) fatty acid, such DHA, while a double bond 6

carbons away from the omega end generates an omega-6 (n-6) fatty acid, such as ARA1.

1.2. Sources of PUFA

Shorter chain PUFA cannot be made de novo and must be obtained through the

diet. Although alpha-linolenic acid is most abundant in flaxseed, the major sources of n-3

PUFA in the western diet are soybean and canola oil2. Longer chain n-3 PUFA are found

in marine sources2, 3. Salmon and herring are better sources of n-3 PUFA than other fish

such as cod and catfish3.

Soybean oil is also a major source of n-6 PUFA in the western diet. Other rich

sources of n-6 PUFA include corn and safflower oil3. Since corn is a major source of feed

in agriculture, most of the meat consumed in the western diet is high in n-6 PUFA, with

3

ratios of n-6 to n-3 PUFA that can reach as high as 25 to 14. The n-6/n-3 ratio of animal

meat can return closer to 1 to 1 when animals are raised on grass or pasture5, 6.

1.3. Synthesis

As mentioned above, shorter chain fatty acids obtained from the diet can be

elongated into longer chain PUFA. Alpha-linolenic acid, an 18 carbon omega-3 fatty acid

is the precursor for the longer chain n-3 PUFA, while linoleic acid, an 18 carbon n-6

PUFA, is the precursor for longer n-6 PUFA.

Once obtained from the diet, these precursor molecules can enter the elongation

pathway (Figure 1-1). The fatty acids are desaturated by 5 and 6 desaturases and

elongated by elongases. These enzymes involved in the elongation of longer chain PUFA

are highly expressed in the liver7, 8, representing the major site of DHA and ARA

synthesis de novo. Other organs, such as the brain, have a lower expression of these

enzymes and do not contribute significantly to the production of PUFA synthesis de novo

9.

The synthesis rate of DHA from alpha-linolenic acid in the rat has been estimated

to be approximately 1%10. The rat is said to be a “super converter”, as human studies

have reported much lower synthesis, as low as 0.01%11-13. However, due to

methodological differences between animal and human studies, the conversion rate

between the two species may be more similar than originally thought, with values in

humans closer to 1%14.

4

Figure 1-1. The n-3 and n-6 synthetic pathways

n-3 pathway n-6 pathway

Adapted from 15

Alpha-linolenic acid (18:3)

Octadecatrienoic acid (18:4)

Eicosatetraenoic acid (20:4)

Eicosapentaenoic acid (20:5)

n-3 Docosapentaenoic acid (22:5)

Linoleic acid (18:2)

Gamma-linolenic acid (18:3)

Dihomo-gamma-linolenic acid (20:3)

Arachidonic acid (20:4)

Adrenic Acid (22:4)

Docosahexaenoic acid (22:6) n-6 Docosapentaenoic acid (22:5)

Δ-6-Desaturase

Elongase

Δ-5-Desaturase

Elongase, Δ-6-Desaturase, β-oxidation

Elongase

5

1.4. Brain uptake

Since PUFA synthesis does not occur in a significant quantity in the brain16, 17,

PUFA must be taken up from the periphery. Several mechanisms have been proposed for

the uptake of PUFA by the brain18, including passive diffusion of fatty acids19 or

lysophospholipids20, or by lipoprotein transporters21. Previous studies have demonstrated,

however, that knocking out lipoprotein receptors does not affect PUFA levels, suggesting

these receptors are not necessary for maintaining PUFA concentration22, 23.

Lysophosphatidylcholine has been proposed as the preferred source of PUFA in the

rodent brain. The major facilitator superfamily domain-containing protein 2 (Mfsd2a), a

lysophospholipid transport protein, knockout mouse model, has decreased brain DHA

concentration suggesting lysophosphatidylcholine as the major source of brain DHA24.

Studies injecting either radiolabelled lysophosphatidylcholine DHA or unesterified DHA

have reported more radioactivity entering the brain when DHA is delivered in the

lysophosphatidylcholine form25, 26.

However, one study has demonstrated that the brain is exposed to lower

radioactivity levels when injected with the unesterified form compared to the

lysophosphatidylcholine form. This is explained by the shorter plasma half-life of the

unesterified form compared to the lysophosphatidylcholine form. When correcting for

radioactivity exposure, the brain uptake is higher for the unesterified form26. Moreover,

brain uptake rates of unesterified DHA closely match brain DHA consumption,

suggesting that the unesterified pool is the major source of brain DHA27.

The process of uptake is thought to be passive and not transport facilitated28.

Despite the passive nature of the brain uptake, however, there are certain differences in

6

concentration between PUFA. ARA and DHA are highly concentrated in the brain

(10,000 nmol/g of brain)29, 30, while alpha-linolenic acid, EPA and linoleic acid are found

in much lower concentrations, approximately 500-fold less concentrated31. The low

levels of alpha-linolenic acid17 and EPA32, 33 and linoleic acid16 are due to beta-oxidation

upon entry into the brain, and other redundant mechanisms to maintain the levels of these

fatty acids18, 32.

1.5. N-3 PUFA and anti-inflammation

It has been suggested that n-3 PUFA have anti-inflammatory properties15. In vivo,

for instance, n-3 PUFA reduce inflammation in multiple models including stroke, spinal

cord injury, Alzheimer’s disease, Parkinson’s disease, lipopolysaccharide (LPS),

interleukin (IL)-1, and others. This is reviewed in Chapter 2.

The anti-inflammatory properties of n-3 PUFA appear to be driven by multiple

mechanisms15. In vitro evidence suggests that one mechanism may relate to the action of

n-3 PUFA on the peroxisome proliferator-activated receptor (PPAR)-The downstream

action of n-3 PUFA on the PPAR-leads to a down regulation of the nuclear factor

kappa-light-chain-enhancer of activated B cells (NF-B), resulting in a decrease in

cytokine production34, 35 and a reduction of adhesion molecules on monocytes36. In

microglial culture, n-3 PUFA reduce microglial hypertrophy37, cytokine production38-41,

NF-B signalling40, 41, and induce polarization to the anti-inflammatory M2 phenotype38,

39 following an inflammatory insult. In addition, increasing doses of DHA and EPA

7

Figure 1-2. PUFA-derived mediator synthesis pathway

Adapted from15, 42

PGH2

PGE2

PGF2

2

PGD2

ARA EPA DHA

TXA2

PGI2

8-keto-PGF1

LTA4

15-HETE

LTB4 LTC4

LXA4

17S-H(p)DHA

17S-HDHA

RVE2 RVE1

18-HpEPE

RVE3 RVD1

RVD2

RVD3

RVD5

14-H(p)DHA 12-HETE

20-HETE

5-HpEPE

LTA5

5-HEPE

LTB5

RVD4

RVD6

PD1

MaR1

COX-2

15-LO

5-LO

15-LO

5-LO

15-LO

PGES

12-LO

Cyp450

5-LO

Cyp450

EET

PDX

5-LO

5-LO 5-LO

12-LO

MaR2

ARA, arachidonic acid; COX, cyclooxygenase; DHA, docosahexaenoic acid; EET, epoxyeicosatrienoic acid; EPA, eicosapentaenoic acid; HDHA, hydroxy DHA; HEPE, hydroxy eicosapentaenoic acid; HETE, hydroxyeicosatetraenoic acid; H(p)DHA, hydroperoxy DHA; H(p)EPE, hydroperoxy eicosapentaenoic acid; LO, lipoxygenase; LT, leukotriene; LX, lipoxin; MaR, maresin; PD, protectin D; PG, prostaglandin; RV, resolvin

8

increase phagocytosis of amyloid- (A39. DHA is also suggested to promote anti-

inflammatory properties through its binding to G-coupled receptor 120, which has been

demonstrated to reduce cytokine production43.

Alternatively, it has been proposed that n-3 PUFA may exert their anti-

inflammatory properties through their conversion to specialized pro-resolving lipid

mediators by lipoxygenases, including protectin D1, resolvins and maresins42, 44. The

synthesis pathways of these specialized pro-resolving lipid mediators are illustrated in

Figure 1-2.

In microglial culture, similar to DHA, specialized pro-resolving lipid mediators

reduce cytokine production45, increase Aphagocytosis46, reduce microglial marker

expression46, increase anti-inflammatory M2 phenotype47 and increase neuronal

survival46. These specialized pro-resolving lipid mediators appear to work through

different receptors than G-coupled receptor 120, with different specialized pro-resolving

lipid mediators activating different receptors48. These receptors include G-coupled

receptor 18 (resolvin D2)49, chemerin receptor 23 (resolvin E1)50, G-coupled receptor 32

(resolvin D1, resolvin D3, resolvin D5)51, 52, lipoxin A4 receptor (resolvin D1)53, and

leukotriene B4 receptor (resolvin E1)50.

N-3 PUFA are also thought to have indirect anti-inflammatory properties through

their reduction of n-6 PUFA in the phospholipid membrane. N-6 PUFA, and more

specifically ARA, are located in the sn-2 position of the phospholipid membrane and can

be released by cytosolic calcium-dependent phospholipase A2. Once released by cytosolic

calcium-dependent phospholipase A2, ARA can be metabolized by cyclooxygenase

(COX) and lipoxygenase to form pro-inflammatory mediators such as prostaglandins

9

(PG), thromboxanes, hydroxyeicosatetraenoic acids and leukotrienes. The synthesis of

these mediators is also represented in Figure 1-2. N-3 PUFA also occupy the sn-2

position in the phospholipid membrane. Therefore, by increasing n-3 PUFA

concentration in the phospholipid membrane, n-6 PUFA are displaced which reduces the

substrate availability for pro-inflammatory mediator production15, 54. Moreover, both n-3

and n-6 PUFA use the same enzyme for mediator production. By increasing n-3 PUFA

concentration, these enzymes become saturated which limits the production of pro-

inflammatory mediators by producing more anti-inflammatory mediators54.

1.6. Models of neuroinflammation

Neuroinflammation is present in many common animal models, including

transgenic models, traumatic brain injury models and models involving the injection of

neurotoxic agents.

A number of models of central nervous system disorders, for instance, have a

neuroinflammatory component. For example, Alzheimer’s disease is associated with

neuroinflammation, and many of the Alzheimer’s disease transgenic mouse models,

including the 3xTg and APPsw mice, have a neuroinflammatory phenotype55, 56. This

includes microglial activation57, 58 and the production of cytokines59, 60. It is thought,

however, that the neuroinflammation found in these models is secondary to the beta-

amyloid production56. Similar observations are also seen in Parkinson’s disease

transgenic mice61, 62.

Neuroinflammation is also observed in traumatic injury models. In stroke models,

the ischemia causes activation of microglia in the penumbra shortly after the induction of

10

ischemia-induced cell death63. This induces secondary cell death through the release of

pro-inflammatory cytokines, such as IL-1 and tumor necrosis factor (TNF)-64-66.

Similar increases in microglial activation and cytokine production are observed in

traumatic brain injury67, 68 and spinal cord injury69 models. The inflammatory component

of these models appears to be secondary to the injury itself, and to be induced by

endogenously produced danger-associated molecular patterns secreted by damaged

neurons70. Breakdown of the blood-brain barrier (BBB) also occurs following traumatic

injury, which allows for the movement of inflammatory blood-born immune cells from

the periphery into the brain70, 71. This is important to consider when assessing

neuroinflammation following trauma.

Neurotoxins have also been linked to neuroinflammation. For example, injection

of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine results in the degeneration of

dopaminergic neurons and is associated with increased microglial activation72.

Neurodegeneration in this model occurs independent of microglial activation73, and

neuroinflammation appears to be secondary to cell death74. Other similar models include

6-hydroxydopamine and rotenone75.

1.7 The lipopolysaccharide (LPS) model of neuroinflammation

The LPS model is one of the most common models of neuroinflammation. LPS is

a component the outer wall of Gram-negative bacteria. It causes inflammation through

the activation of the Toll-like receptor 476, 77. These receptors are highly expressed on

microglia, while not present on neurons, astrocytes or oligodendrocytes78-80. Activation of

11

the Toll-like receptor 4 directly activates the NF-B pathway, resulting in increased

production of pro-inflammatory cytokines81, 82.

There are many variations of the LPS model involving different routes of

administration, doses, and durations of infusion. Systemically, LPS has been

administered through a variety of routes, including s.c., i.p., and i.v., and at doses ranging

from 0.002 to 200 mg/kg83. Overall, LPS induces rapid microglial activation within 6

hours of injection, which can last up to 3 days83, 84. By one week, microglial activation

has usually returned to baseline84, 85. However, some studies have reported microglial

activation lasting months86 following LPS injection, or even for up to one year87.

Following microglial activation, cytokine production and astrocyte activation are

observed88, 89. Chronic administration of LPS can result in less severe symptoms

compared to acute administration88.

Systemic delivery of LPS results in peripheral inflammatory effects through the

activation of the Toll-like receptor 4 on macrophages. This can result in increased

circulating cytokines, which in turn can signal to the brain and increase BBB

permeability90. In order to focus on neuroinflammation, without the effects from the

periphery, the present project focuses on neuroinflammation following the

intracerebroventricular (i.c.v.) injection of LPS. This model has been shown to increase

cytokine production, such as TNF- and IL-1, and microglial activation within hours to

1 day of injection91-95. Microglial activation persists up to at least 3 days94, and has been

shown to still be increased at 4 weeks in rats receiving 25 g LPS96. A study using

positron emission topography (PET) imaging has reported that microglial activation

peaks at 3 days post injection97. The inflammatory insult induced by i.c.v. LPS is

12

exacerbated in older (26 month old) rats98. Memory appears to be affected in this model.

Repeated administration of 50 g of LPS in Wistar rats results in decreased spatial

memory in the Morris water maze99. Wistar rats receiving 10 g of i.c.v. LPS show

decreased spontaneous alternating behaviour in the Y-maze100. Depressive-like behaviour

in the forced swim test is also present 24 hr following the injection of 100 ng i.c.v. LPS

95, 101.

1.8. The fat-1 mouse

The fat-1 mouse is a model developed by Dr. Jiang Kang at Harvard

University102. The fat-1 gene from c. elegans codes for a n-3 desaturase that converts n-6

to n-3 PUFA by adding a double bond at the third carbon from the methyl end of the fatty

acid. The introduction of the fat-1 gene into a mouse allows for the endogenous

conversion of n-3 PUFA from n-6 PUFA. When fed an n-3 PUFA deficient diet, fat-1

mice have higher cortical DHA and lower cortical ARA as compared to wildtype (WT)

littermates103, 104. In fact, fat-1 mice fed a diet deficient in n-3 PUFA have brain DHA

concentrations similar to mice on an adequate diet104. The amount of DHA that can

accumulate in the brain appears to have a plateau, the fat-1 mice and WT littermates

consuming fish oil have similar brain DHA concentrations104. Dietary interventions, such

as fish oil, have the potential for confounders, such as having increased vitamin D or the

subtraction of n-6 PUFA for the introduction of n-3 PUFA. The fat-1 model allows us to

isolate the potential effect of increased brain DHA on neuroinflammation.

13

The fat-1 mouse has reduced systemic inflammation in various disease models.

The fat-1 mouse, for instance, displays a lower inflammatory phenotype, with decreased

pro-inflammatory signals such TNF- and IL-6, in models of colitis105, osteoporosis106,

ethanol-induced liver steatosis107 and in the apoE knockout108. Serum IL-6 is also reduced

in the fat-1 mouse in a cerulein-induced pancreatis model109. Similarly, expression of the

NF-B pathway is decreased in the fat-1 mouse in the streptozotocin induced-diabetes

model110, in colon tumorigenesis107 and in the fat-1/apoE knockout mouse fed a western

diet108. The fat-1 gene also appears to enhance the calorie-induced reduction of serum

pro-inflammatory cytokines such as IL-1 and TNF-111.

Aside from increases in n-3 PUFA, bioactive mediators are also elevated in the

fat-1 mouse in inflammatory models. Lipidomic analysis of fat-1 mouse plasma shows a

specific anti-inflammatory signature, with increases in 17-hydroxy DHA, a precursor to

resolvin D1 and resolvin D2, and decreases in pro-inflammatory mediators such as

hydroxyeicosatetraenoic acid112. Increases in 17-hydroxy DHA have also been found in

the fat-1 mouse in a model liver carcinogenesis. This was correlated with decreases in

serum TNF- and COX-2113. In an obesity-linked inflammation model, the fat-1 mouse

has increased protectin D1 in muscle and adipose tissue, which is correlated with

increased macrophage clearance and decreased cytokine production114.

In the brain, it has been reported that COX-2 is lower in fat-1 mice than in WT

littermates, while no differences in cytosolic phospholipase A2 are found between the two

groups103. A microarray analysis has shown a decrease in calcium independent

phospholipase A2 mRNA expression in the fat-1 brain as compared to the brain of a WT

mouse on an n-3 PUFA deficient diet115. These two studies point to a potential lower

14

inflammatory environment in the fat-1 brain as compared to the WT littermate brain.

Several studies have reported lower neuroinflammation in various disease models in the

fat-1 mouse (reviewed in Chapter 2).

1.9. Objectives The goal of this thesis was to define a self-resolving model of neuroinflammation

following the i.c.v. injection of LPS. This model was to be defined based on protein

expression, gene expression and lipidomic profile. Once the model was defined, this

thesis was designed to evaluate whether n-3 PUFA could modulate the resolution of

neuroinflammation.

Chapter 2 is a review of the literature on the effect of n-3 PUFA on

neuroinflammation. This chapter is adapted from a published article that summarizes all

known studies which have measured the effect of n-3 PUFA on neuroinflammatory

markers in a variety of models, including stroke, spinal cord injury, Alzheimer’s disease,

LPS injection, traumatic brain injury and others. This paper is published in the European

Journal of Pharmacology.

Chapter 3 reviews the objectives and hypotheses of this thesis. Chapter 4 and 5

are the experimental chapters of the thesis. Chapter 4 is a “method paper” that attempts to

describe a novel method for measuring the brain neurolipidome. As PUFA-derived

mediators are thought to regulate resolution of inflammation, and these mediators had yet

to be measured in the brain without the artifact of ischemia, a novel method was

developed combining high-energy head-focused microwave fixation with high-resolution

lipidomics.

15

Chapter 5 develops a self-resolving model of neuroinflammation following i.c.v.

LPS injection. It is based on inflammatory markers and lipidomic profile as measured by

our new method to eliminate the ischemia-induce artifact on pro-resolving mediator

production. Once resolution of neuroinflammation is established, Chapter 5 sets out to

determine whether or not increasing brain DHA, utilizing either dietary approaches or the

fat-1 transgenic model, has an effect on the resolution of neuroinflammation.

Chapter 6 summarizes the findings of this thesis, along with the significance and

implications for the field. The chapter concludes that ischemia induces a unique

lipidomic signature which is inhibited by microwave fixation, and that increasing brain

DHA only has subtle effects on the resolution of neuroinflammation. Limitations of the

thesis are also discussed in this chapter.

Appendix 1 is a systematic review of the literature on neuroinflammation in

postmortem schizophrenia brains. Neuroinflammation has been found in most

neurological disorders, and evidence is starting to suggest that neuroinflammation is

associated with psychiatric disorders as well. In particular, in vivo imaging and clinical

trials suggest a possible link between neuroinflammation and schizophrenia. Some

postmortem studies have also demonstrated elevated neuroinflammation in

schizophrenia. However, to date, a review of all of the postmortem data had not yet been

published. This paper is published in Molecular Psychiatry.

16

Chapter 2: N-3 Polyunsaturated Fatty Acids in Animal Models with Neuroinflammation: An Update

Adapted from: Marc-Olivier Trépanier, Kathryn E Hopperton, Sarah K. Orr and Richard

P Bazinet. Eur J Pharmacol. 2015 May 30 [DOI: 10.1016/j.ejphar.2015.05.045] http://www.sciencedirect.com/science/article/pii/S0014299915300431

Contribution: Expanding on our previous article, I found all new published articles published since 2012, along with expanding the scope of research included. I extracted all information and wrote the first draft of the paper.

17

2.1. Abstract

Neuroinflammation is a characteristic of a multitude of neurological and

psychiatric disorders. Modulating inflammatory pathways offers a potential therapeutic

target in these disorders. Omega-3 polyunsaturated fatty acids have anti-inflammatory

and pro-resolving properties in the periphery, however, their effect on neuroinflammation

has been less studied. This review summarizes 61 animal studies that have tested the

effects of omega-3 polyunsaturated fatty acids on neuroinflammatory outcomes in vivo in

various models including models of stroke, spinal cord injury, aging, Alzheimer’s

disease, Parkinson’s disease, lipopolysaccharide injection, IL-1β injection, diabetes,

neuropathic pain, traumatic brain injury, depression, surgically induced cognitive decline,

whole body irradiation, amyotrophic lateral sclerosis, and lupus. The evidence presented

in this review suggests that while there are anti-neuroinflammatory properties of omega-3

polyunsaturated fatty acids, it is not clear by which mechanism omega-3 polyunsaturated

fatty acids exert their effects. Future research should aim to isolate the effects of omega-3

polyunsaturated fatty acids on neuroinflammatory signaling in vivo and to elucidate the

mechanisms underlying these effects.

18

2.2. Introduction

Inflammation is a characteristic of many neurological and psychiatric illnesses,

including Alzheimer’s disease, multiple sclerosis, depression, schizophrenia and

Parkinson’s disease116, 117. While some inflammation is integral to pathogen and debris

clearance, as well as to wound healing, excessive, dysregulated inflammation can

exacerbate tissue injury116, 118, 119. Indeed, inflammation has been suggested as a

mechanism by which Alzheimer’s and Parkinson’s disease pathologies potentiate

neuronal death116, 120.

The brain is an immunologically unique environment, and, as such, knowledge

about inflammation and its resolution in the periphery may not apply directly to the

brain121. The brain is separated from the periphery by the blood-brain-barrier (BBB), and

houses its own population of immune effector cells: astrocytes and microglia. Microglia

are the macrophages of the brain, and, under normal conditions, exist in the M0 resting

phenotype, surveying the neurological environment for insult or injury122. Microglia can

be activated from their resting M0 state to a M1 pro-inflammatory state by cytokines such

as tumor necrosis factor-alpha (TNF-) and interferon gamma (IFN-, produced either

by the microglia themselves or by astrocytes, the major glial cells of the brain, in

response to insult recognition123, 124. Once activated, M1 microglia are characterized by

the production of pro-inflammatory cytokines and chemokines, such as interleukin (IL)-6,

IL-1β, IL-12, IFN-, IL-1α, and chemokine (c-x-c motif) ligand (CXCL) 11. Moreover,

M1 microglia have increased activity of cyclooxygenase (COX)-2 and production of pro-

inflammatory lipid mediators such as prostaglandin (PG) E2. They also exhibit increased

production of reactive oxygen and nitrogen species via activity of inducible nitric oxide

19

synthase and NADPH oxidase119, 122. Pro-inflammatory cytokines also activate

astrocytes, which contribute to cytokine, reactive oxygen species and nitric oxide

production125. Exaggerated innate immune responses, or the failure to clear insults, can

lead to excessive production of cytokines and reactive oxygen species by astrocytes and

microglia, which triggers neuronal death by apoptosis or necrosis, feeding forward to

further activate microglia by releasing ATP and calcium into the extracellular space116, 122,

125. Upon neutralization of the initial insult and/or in response to cytokine IL-4 and

chemokine (c-c motif) ligand (CCL) 2, M1 microglia switch to a M2 anti-inflammatory

phenotype, promoting phagocytosis, wound healing and a return to homeostasis123, 124.

Despite the presence of the BBB, neuroinflammation can also be influenced by

peripheral factors. Pro-inflammatory cytokines such as IL-1α, IL-1β, IL-6 and TNF-α

have all been shown to cross the BBB, seemingly regulated by specific transporters 126.

Permeability of the BBB to these factors increases under some neurological conditions,

allowing peripheral macrophages, neutrophils and T cells to enter the brain121, 122, 126, 127.

Clearly, neuroinflammation is a distinct and complex process that results from interplay

between a variety of cell types and mediators.

As neuroinflammation has been implicated in the pathogenesis of various

neurological disorders, there has been interest in the role of anti-inflammatory drugs for

prevention and treatment. In human observational studies, the use of aspirin and other

non-steroidal anti-inflammatory drugs is associated with a decreased risk of Alzheimer’s

disease, with longer-term users exhibiting the greatest risk reduction128. Ibuprofen use is

also associated with a decreased risk of Parkinson’s disease, although aspirin and other

non-steroidal anti-inflammatory drugs do not seem to exhibit the same protective

20

effects129. Randomized clinical trials, on the other hand, generally do not support the

positive effects of non-steroidal anti-inflammatory drugs in these neurological diseases.

For instance, the only randomized control trial testing non-steroidal anti-inflammatory

drugs in primary prevention of Alzheimer’s disease found that neither celecoxib nor

naproxen reduced the risk of Alzheimer’s Disease onset, although this trial was stopped

with an average of 15 months follow-up, well short of the target 7 years, due to concerns

over increased cardiovascular risk with celecoxib treatment130. Randomized clinical trials

of anti-inflammatory drugs in patients with Alzheimer’s disease or mild cognitive

impairment have also generally failed to show any benefits131, and, in some cases, have

reported serious adverse events, with one trial finding that rofecoxib (selective COX-2

inhibitor) increased the risk of patients with mild cognitive impairment progressing to

Alzheimer’s disease132.

The evidence suggests that, although neuroinflammation is implicated in

neurological disease, blocking inflammation may not be therapeutic. In animal models,

blocking inflammation via reduced activity of microglia exacerbates acute neural injury

to ischemia133, and acute administration of exogenous activated microglia immediately

following ischemia-reperfusion improves recovery134. In mice, deletion or disruption of

the COX-2 gene exacerbates the neuroinflammatory response to lipopolysaccharide

(LPS) and fails to provide any benefit in models of Parkinson’s disease and traumatic

brain injury, while pharmaceutical COX-2 inhibitors have mixed effects in

neuroinflammatory disease models135. In a transgenic model of Alzheimer’s disease, a

mildly pyrogenic agonist of Toll-like receptor 4, a receptor on the surface of microglia,

improved amyloid-β (A) clearance and cognitive measures, while the much more potent

21

Toll-like receptor 4 agonist, LPS, did not136. Thus, interventions that can modulate, as

opposed to block, neuroinflammation may be a useful therapeutic approach.

The resolution of inflammation was historically thought to be a passive process

resulting from the dissipation of pro-inflammatory mediators137. A novel class of

molecules produced from the omega (n)-3 polyunsaturated fatty acids (PUFA)

docosahexaenoic acid and eicosapentaenoic acid (DHA and EPA, respectively),

collectively referred to as specialized pro-resolving lipid mediators, stimulate resolution,

actively returning tissue to homeostasis following inflammation42, 137. Specialized pro-

resolving lipid mediators, comprised of the resolvin, protectin and maresin families, offer

a potential mechanism for the protective effects of n-3 PUFA on neurological diseases

that have been observed in animal models and human observational studies117, 138, 139.

The two main PUFA species in the brain are DHA, an n-3 PUFA, and arachidonic

acid (ARA), an n-6 PUFA. DHA and ARA can be consumed pre-formed from the diet, or

can be synthesized from dietary precursors, α-linolenic (n-3) or linoleic (n-6) fatty acids,

primarily in the liver. While the brain expresses enzymes that can synthesize DHA and

ARA from their dietary precursors, these synthesis rates appear to be much lower than the

rate of brain PUFA uptake from the plasma, suggesting the brain is largely dependent on

preformed DHA and ARA synthesized in the liver, or supplied directly from the diet16, 140,

141.

Brain lipid metabolism is a complex and evolving field (for review see142).

Briefly, upon entry into the brain, DHA and ARA are mostly esterified to phospholipids

at the stereospecifically numbered-2 position. DHA and ARA are both released from the

phospholipid membrane by phospholipase A2, with ARA preferentially cleaved by

22

calcium dependent cytosolic phospholipase A2, and DHA by calcium independent

phospholipase A2143. While over 90% of DHA and ARA released from the phospholipid

membrane are rapidly re-esterified to phospholipids, a process known as the Lands cycle,

a proportion of these unesterified fatty acids can be used as substrates for the synthesis of

pro-inflammatory and pro-resolving lipid mediators140. ARA and DHA are acted upon by

COX and lipoxygenase enzymes, with ARA giving rise to pro-inflammatory mediators

such as PG (notably PGE2) and leukotrienes and DHA giving rise to specialized pro-

resolving lipid mediators 42.

It is generally appreciated that n-3 PUFA have anti-inflammatory properties in the

periphery144, 145. The mechanism by which n-3 PUFA are anti-inflammatory, however,

has yet to be determined. One suggested mechanism includes the increased availability of

n-3 PUFA precursors for specialized pro-resolving mediator production. The potent

actions of specialized pro-resolving lipid mediators have been studied in peripheral

immune cells 42, 48. It has recently been shown that supplementation with fish oil for as

little as 5 days produces significant increases in plasma levels of specialized pro-

resolving lipid mediators and their precursors, suggesting that diet modifies the body’s

inflammatory environment146. It is important to note, however, that there is variation

between studies in the detection of specialized pro-resolving lipid mediators and their

precursors at baseline and following n-3 PUFA supplementation147-149.

While studies of specialized pro-resolving lipid mediators in the brain are limited,

it is known from postmortem brain samples that patients with Alzheimer’s disease have

lower hippocampal levels of protectin D1150. Likewise, lipoxin A4 and resolvin D1 levels

in the cerebrospinal fluid are positively correlated to Mini-Mental State Examination

23

scores151, which supports a protective role for these mediators in human neurological

disease.

In general, in vitro evidence points to immunomodulatory effects of DHA and

EPA in immortalized microglia and astrocyte cultures, with lower levels of inflammatory

markers in response to stimulation with IFN-γ, LPS or A152, 153. EPA and DHA lower

markers of M1 microglial activation and improve phagocytosis of A in microglia

cultures, while DHA also increases M2 microglia markers, pointing to a pro-resolving

effect39. Cultures of human glial cells produce various DHA-derived specialized pro-

resolving lipid mediators in response to stimulation, suggesting that specialized pro-

resolving lipid mediators may play a role in the brain154. Protectin D1 decreases A-

induced apoptosis in human neuronal cell cultures150. In a co-culture of human neuronal

and glial cells, protectin D1 decreases inflammatory markers COX-2 and TNF-α,

increases peroxisome proliferator-activated receptor (PPAR) γ, and protects neurons from

A-induced cell death155. Together, these results support a role for n-3 PUFA and their

associated specialized pro-resolving lipid mediators in modulating elements of the

neuroinflammatory environment.

Given the complexity of the interaction between different cell types in

neuroinflammation, along with the potential modifying role of the peripheral immune

system, animal models provide some advantages over cell culture models to study the

interaction between dietary n-3 PUFA and inflammation in the brain. Diet is capable of

changing the plasma concentrations of n-3 PUFA and specialized pro-resolving lipid

mediators 146, and the levels of these components in the plasma are often used as a basis

to select treatment doses in cell culture systems. It is not clear, however, how much diet,

24

particularly in the short term, can influence brain composition of n-3 PUFA and

specialized pro-resolving lipid mediators, and thus how relevant these doses may be to

the brain. Moreover, a recent paper that established an adult microglial signature based on

expression of 239 genes found that two of the most commonly used microglial cell lines,

Bv2 and N9, do not express this signature, bringing into question the generalizability of

work with these and other cell lines to the brain156.

In this review, we will summarize the evidence for the role of n-3 PUFA in

modulating neuroinflammation in animal models by updating and adding to our previous

review, published in 2013157.

2.3. Results

2.3.1 n-3 PUFA and neuroinflammation in ischemia or ischemia/reperfusion

Inflammation is a key component of stroke injury. We identified 16 studies

(summarized in Table 2-1) that have investigated the role of n-3 PUFA in controlling

inflammation following ischemia and ischemia and reperfusion.

Three studies have investigated chronic effects of n-3 PUFA. Lalancette-Hébert

and colleagues utilized the Toll-like receptor 2-fluc-GFP transgenic mouse, a mouse that

is transgenically modified to be bioluminescent under Toll-like receptor 2 activation,

supplemented with DHA (0.7% of total diet weight) for 12 weeks. Compared to the low

n-3 PUFA control, DHA supplementation decreases infarct size, microglial activation (as

indicated by bioluminescence) and COX-2, IL-6 and IL-1 protein expression following

1 hr middle cerebral artery occlusion. This was correlated with increased striatal DHA158.

25

Table 2-1: Summary of studies investigating the effects of n-3 PUFA in ischemia and ischemia/reperfusion models Authors (year)

Injury Model Species PUFA Treatment(s) Comparison Treatment

Treatment Duration/

Time point

Brain n-3 PUFA

Non-Inflammatory Outcome

Inflammatory Outcome

Black et al. (1984)

Ischemia/ reperfusion

Mongolian Gerbils

a) 0.833 mg EPA i.v. b) 0.167 mg EPA i.v.

0.167 mg LNA i.v.

135 min infusion 5 min prior ischemia

Not reported

a ↑ cerebral blow flow a,b ↔ brain edema

a,b ↔ brain PGF2, PGE2, TXB2,

6-ketoPGF1

Marcheselli et al. (2003)


C57Bl/6 mice

a) 0.4-120 μg 10,17S-dihydroxy-DHA i.c.v. b) 2- 200 μg DHA i.c.v

vehicle i.c.v. 3 or 48 hr continuous infusion post-injury

Not reported

b ↓ infarct size a,b↓ CX and HIP leukocyte/neutrophil accumulation a,b ↓ HIP NF-B protein a,b ↓ HIP COX-2 mRNA

Yang et al. (2007)


Sprague Dawley rats

per kg body weight i.p.: a) 250 nmol (71 μg) STA b) 500 nmol (142 μg) STA c) 250 nmol (76 μg) ARA d) 500 nmol (152 μg) ARA e) 250 nmol (82 μg) DHA f) 500 nmol (164 μg) DHA

saline i.p. 60 min post-reperfusion

Not reported

d,f ↑ infarct size d,f ↑ CX leukocyte/neutrophil accumulation d,f ↑ CX COX-2 mRNA

Pan et al. (2009)


Sprague Dawley rats

per kg body weight i.p.: a) 100 nmol (33 μg) DHA b) 500 nmol (164 μg) DHA

saline i.p. 1 h (single), 3 d (single), or 6 weeks# (daily) prior to ischemia

Not reported

b ↓ infarct size b ↓ BBB permeability b ↓ apoptosis b # ↓ oxidative stress b ↓ lipid peroxidation

b↓ CX leukocyte/neutrophil accumulation b↓ CX IL-6 protein

Belayev et al. (2009)


Sprague Dawley rats

14 mg/kg DHA i.v. saline i.v. 60 min post-reperfusion

Not reported

↓ infarct size

↑ CX GFAP protein

Zhang et al. (2010)

Ischemia (immature

Sprague Dawley

Chow + EPA + DHA (15mg/g of diet)

Low n-3 (0.5%)

From day 2 of pregnancy

↑ CX total DHA and

↑ Sensorimotor

↓CX COX-2, iNOS, TNF-α, IL-

1α, IL-1, IL-6 mRNA

26

brain) rats (pups) to 7 days post surgery (PND 14)

EPA score (FF) ↑ learning and memory (MWM) ↓ infarct size

↓ CX, ST Iba-1 protein

Belayev et al. (2011)


Sprague Dawley rats

5 mg/kg DHA i.v. saline i.v. Time post-ischemia: a) 3h b) 4h c) 5h d) 6h

a ↑ PN NPD1 and 17-HDHA

a,b,c ↓ infarct size a,b,c ↑ sensorimotor score (PRT, FPT)

a ↑ CX and ST GFAP protein a ↓ CX and ST CD68 protein (microglia)

Lalancette-Hébert et al. (2011)


TLR2-fluc-GFP transgenic mice (C57Bl/6)

DHA supplemented (0.7% n-3 PUFA total diet)

low n-3 PUFA (0.03% n-3 PUFA)

12 weeks ↑ ST DHA

↓ infarct size ↓ TLR2 promoter induction (microglial activation) ↓ brain IL-1, IL-6, COX-2 protein ↔ brain TNF- protein

Okabe et al. (2011)


Mongolian Gerbils

500 mg/kg EPA i.p. Saline i.p. 4 weeks prior to surgery

Not reported

↑ CA1 neuronal survival ↓ oxidative stress ↑ Learning and memory (8ARM)

↓ HIP Iba-1 protein

Bazan et al. (2012)


Sprague Dawley rats

333 g/kg AT-NPD1 i.v. saline i.v. 60 min post-reperfusion

Not reported

↓ infarct size

↑ sensorimotor score (PRT, FPT)

↑ CX GFAP protein

↓ CX CD68 protein ↔ SCX GFAP and CD68 protein

Eady et al. (2012)

Ischemia/ Reperfusion

Sprague Dawley rats

5 mg/kg DHA i.v. Saline i.v. 1 hr post reperfusion

Not reported

↓ infarct size

↑ sensorimotor score (PRT, FPT) ↓ pAKT

↑ CX GFAP protein

↓ CX CD68 protein

Eady et al. Ischemia/ Sprague Per kg body weight i.v.: Saline i.v. or 1 hr post Not a,b,c,d ↑ a,b,c,d ↑ CX, ST GFAP protein

27

(2012) Reperfusion Dawley rats

a) 5 mg DHA b) 5 mg DHA + 0.32 g Alb c) 5 mg DHA + 0.63 g Alb d) 5 mg DHA + 1.25 g Alb

0.63 g/kg Alb

reperfusion reported sensorimotor score (PRT, FPT) a,b,c,d ↓ infarct size a,b,c,d ↑ new neurons

c,d ↓ CX, ST CD68 protein

Chang et al. (2013)

Ischemia Sprague Dawley rats

Daily 500 nmol (164 g)/kg i.p. DHA

Saline i.p. 3 days prior to surgery

Not reported

↑ neurological score ↓ infarct size

↓ apoptotic signals ↓ oxidative stress

↓ CX CD68, CD45 (macrophage), Ly6g (neutrophil), CD3 (lymphocyte), CD11 (microglia) protein ↓ CX MPO activity

↓ CX TNF-α, IL-1, CCR2, IL-6, MCP-1 mRNA

Eady et al. (2014)

Ischemia/ Reperfusion in aged rats (18 mo)

Sprague Dawley rats

Per kg body weigh i.v.: a) 5 mg DHA b) 5 mg DHA + 0.63g Alb

Saline or 0.63 g/kg Alb

1 hr post reperfusion

Not reported

a,b↑ sensorimotor score (PRT, FPT) b ↓ edema b ↓ infarct size a,b ↑ new neurons

a,b ↔ CX, b ↑ ST GFAP protein b ↓ CX, ST CD68 protein

Luo et al. (2014)


Fat-1 mice Fat-1 mice were placed on 10% corn oil

WT were placed on 10% corn oil

Not reported ↑HIP total DHA and n-3 DPA ↑ HIP RvD1 (following ischemia)

↑ learning and memory (MWM) ↓ apoptosis

↓ cell death ↔ GPCR 120 expression

↓ HIP NF-κB, TNF-, IL-1β, IL-6, MCP-1, GFAP, Iba-1 protein

Zendedel et al. (2014)


Wistar rats Per kg body weight i.v. 140 mg DHA + 220 mg EPA

saline i.v. or Lipofundin MCT

1 and 12hr post ischemia

Not reported

↓ hypoxic marker ↑axonic,

↓ brain IL-1, TNF-, Arg1, NLRP3 mRNA ↔ brain Trem2 mRNA

28

dendritic marker ↑ neurological score ↓ infarct size

17-HDHA, 17-hydroxy-DHA (DHA derivative); 8ARM, 8-arm radial maze, Aβ, amyloid-β; Alb, albumin; pAKT, phosphorylated protein kinase B; ARA, arachidonic acid; AT-NPD1, aspirin triggered NPD1; BBB, blood brain barrier; C-C motif chemokine; CD, cluster of differentiation; COX, cyclooxygenase; CX, cortex; DHA, docosahexaenoic acid; DPAn-3, docosapentaenoic acid; EPA, eicosapentaenoic acid; FF, foot fault/grid walking; FPT, forelimb placing test; GFAP, glial fibrillary acidic protein; HIP, hippocampus; IL, interleukin; iNOS, nitric oxide synthase; LNA, linoleic acid; Ly6G, lymphocyte antigen 6; MCP, monocyte chemotactic protein; MPO, myeloperoxidase; MWM, Morris water maze; NF-B, nuclear factor-κB; NLRP3, NLR family pyrin domain containing 3; NPD, neuroprotectin D; PG, prostaglandin; PN, penumbra; PND, post natal day; PRT, postural reflex test; PUFA, polyunsaturated fatty acid; STA, stearic acid; ST, striatum; TLR2, Toll-like receptor 2; TNF, tumor necrosis factor; TX, thromboxane; WT, wildtype; a,b,c,d,e,f, indicates treatment group represented in outcome columns (brain n-3 PUFA, primary outcome, inflammatory outcome)

29

experience a lower level of microglial activation and expression of COX-2, TNF-, and

IL-1 mRNA following ischemic brain injury159. Finally, Luo et al. utilized the fat-1

transgenic mouse to test the chronic effect of DHA on inflammation following

ischemia/reperfusion. The fat-1 mouse endogenously converts n-6 to n-3 PUFA, leading

to high brain DHA concentrations104. Following 20 min occlusion of the common carotid

artery, the fat-1 mouse had reduced hippocampal TNF-, IL-1, glial fibrillary acidic

protein (GFAP), and ionized calcium-binding adaptor molecule 1 (Iba-1) protein levels

compared to its wildtype control after 7 days of reperfusion160.

Sub-chronic studies have replicated the anti-inflammatory effects of n-3 PUFA

observed in chronic exposure. Rats given daily DHA injections (500 nmol [164

g]/kg/day i.p.) for 3 days prior to brain ischemia have diminished infarct sizes at 3 days

post-ischemia (without reperfusion), accompanied by reduced microglial markers,

neutrophil and macrophage infiltration, and lower TNF-, IL-1 and IL-6 mRNA

levels161. Daily EPA injections (500 mg/kg i.p., 4 weeks) prior to ischemia/reperfusion

also result in neuroprotection in gerbils, increasing neuronal survival in the hippocampus

and reducing microglial activation162. Similarly, 6 weeks of daily DHA injections (500

nmol [164 g]/kg/day i.p.) prior to ischemia/reperfusion injury lowers infarct size, while

also reducing leukocyte infiltration and IL-6 levels compared to control163. This effect is

dose-dependent, as 100 nmol (33 g)/kg/day DHA is ineffective at lowering leukocyte

infiltration and IL-6 protein. Similar results were reported with single acute injections of

100 nmol (33 g) and 500 nmol (164 g)/kg DHA either 1 hr or 3 days prior to the

ischemic injury163.

30

Six acute studies have demonstrated similar anti-inflammatory effects of n-3

PUFA on ischemia/reperfusion models, even when administered post-occlusion. Three

separate studies report that i.v. injection of DHA (5 to 14 mg) 1 hr after 2 hr of ischemia

in rats results in a decreased infarct size 7 days post reperfusion and improves

neurological scores, while increasing GFAP protein expression, an astrocytic marker, in

the cortex164-166. This is also accompanied by decreases in CD68 protein, a marker of

microglia and macrophages165, 166. A fourth study found that i.v. infusions (1hr and 12hr

post occlusion) of 21.5 mg/kg or 32.5 mg/kg of DHA and EPA, respectively, attenuates

ischemia/reperfusion-induced IL-1, TNF-, and nucleotide binding domain and leucine

rich containing protein 3, a protein involved in IL-1 processing, increased expression.

Treatment also reduced the microglial M1 phenotype mRNA marker Arg1167.

Complexing DHA to albumin appears to have an additive effect, where infusion of 5 mg

of DHA complexed with 0.63g of albumin causes a greater decrease in the

microglia/macrophage marker CD68 than DHA alone in both young168 and aged rats169.

The mechanism by which n-3 PUFA may provide protection in these models is

not agreed upon. One suggested mechanism is through the enzymatic conversion of n-3

PUFA to specialized pro-resolving lipid mediators, including resolvins and protectins42.

Within the mouse brain, ischemia/reperfusion injury induces resolvin D1 production,

with higher levels in the fat-1 mouse, which is protected against ischemia/reperfusion

injury, compared to its wildtype littermate160. Further, acute injection of 5 mg of DHA 3

hrs post-ischemia increases production of protectin D1 and its precursor compared to the

saline control165. Direct i.v. infusion of 333 g/kg of the stereoisomer of protectin D1,

aspirin-triggered protectin D1, 1 hr post-reperfusion produces similar anti-inflammatory

31

effects as previous n-3 PUFA studies, increasing GFAP and reducing CD68 protein while

reducing the infarct size170.

Not all studies, however, show anti-inflammatory effects of n-3 PUFA in

ischemic and ischemia/reperfusion models. Black and colleagues reported that 135 min of

i.v. infusion of 833 g EPA 5 min prior to ischemia does not reduce the concentrations of

pro-inflammatory mediators including PGE2171. Moreover, a second study reported an

increase in infarct size following administration of 500 nmol (164 g) of DHA i.p. 1 hr

after reperfusion along with increased leukocyte infiltration and COX-2 mRNA

expression 24 hr post reperfusion172. Similar results were obtained following injection of

ARA, but not stearic acid172. The authors argue that the injection of PUFA, including

DHA and ARA, results in increased oxidative damage following ischemic injuries.

When looking at all the studies together, evidence appears to point to a

neuroprotective effect of endogenously synthesized n-3 PUFA, dietary n-3 PUFA, or n-3

PUFA injection to reduce the inflammation related to animal models of ischemia and

ischemia/reperfusion injury. There are contradicting results regarding the effects of post-

ischemia treatment, as one study172 suggests possible damaging effects of n-3 PUFA.

2.3.2. n-3 PUFA and neuroinflammation in spinal cord injury

Microglia and astrocyte activation is a major component of the pathophysiology

of spinal cord injury. During spinal cord injury, additional immune cells, leukocytes, are

recruited from the blood to the site of the injury where they release various pro-

inflammatory lipid mediators and cytokines, exacerbating the innate inflammatory

32

response that leads to extensive tissue damage and potentially contributes to loss of

function173.

Nine studies (Table 2-2) have evaluated the outcome of intravenous n-3 PUFA

administration either before or following spinal cord injury on neuroinflammatory

markers. It was reported that 250 nmol (82 g)/kg of DHA administered i.v. 30 min after

spinal hemisection reduces lesion size, and increases neuronal survival and motor

recovery, despite its lack of effect on CD68 protein levels 174. In contrast, injection of 250

nmol (76 g)/kg ARA in the same model exacerbates neuroinflammation and decreases

cell viability 174. The lack of anti-inflammatory effect of acute DHA is in agreement with

results reported by 2 separate studies, which find that i.v. injection of 250 nmol (76 or 82

g)/kg of either EPA or DHA 30 min post spinal compression does not decrease protein

concentrations of TNF-, IL-1 and IL-6175, 176. However, Hall et al. did observe a

decrease in JT1, a marker of neutrophil infiltration, following DHA administration175.

Similar to the report of King and colleagues174, Lim et al. show EPA administration

increases cell survival and motor recovery even though there is no effect on a marker of

neuroinflammation176.

While the studies above reported no effect of n-3 PUFA administered following

spinal injury on inflammatory markers, other studies show reduced pro-inflammatory

markers following i.v. infusion of n-3 PUFA. In separate studies, i.v. injection of 250

nmol (82 g)/kg DHA following spine compression reduced COX-269, GFAP, TNF-

and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-B) protein

concentrations177, while also decreasing activated microglial markers CD68 and Iba-169,

177.

33

Table 2-2: Summary of studies investigating the effects of n-3 PUFA in spinal cord injury models Authors (year)


Treatment Duration/

Time point

Brain n-3 PUFA



Lang-Lazdunski et al. (2003)

Ischemia SCI Sprague-Dawley rats

250 nmol (70 g)/kg ALA i.v.

Vehicle i.v. 30min pre surgery or immediately following surgery

Not reported

↑ neurological outcome ↓ apoptosis

↑ neuronal survival

↓ spinal NF-κB protein

King et al. (2006)

Hemisection SCI

Wistar rats Per kg body weight i.v.: a) 250 nmol (82 g) DHA b) 250 nmol (70 g) ALA

c) 250 nmol (76g) ARA

Vehicle i.v. 250 nmol/kg OA i.v.

Acute i.v. 30 min post surgery

Not reported

a,b↓ lesion size c ↑ lesion size a,b↓ apoptosis c↑ apoptosis a,b ↑ neuronal survival c ↓ neuronal survival a,b ↑ oligodendrocyte survival c↓ oligodendrocyte survival a,b ↓ RNA oxidation c↑ RNA oxidation a,b ↑ motor recovery c ↔ motor recovery

a,b ↔ spinal CD68 protein

c↑ spinal CD68 protein

Huang et al. (2007)

Compression SCI

Sprague Dawley rats

a) 250 nmol (82 g)/kg DHA i.v.+ control diet b) 250 nmol (82 g)/kg DHA i.v. + 400 mg/kg/d

Saline i.v. + control diet

Acute i.v. 30 min post surgery 1 or 6 weeks

Not reported

a,b↑ spinal neuronal survival a,b↑ spinal

a,b ↓ spinal CD68 protein

34

DHA/EPA p.o.

diet post surgery

oligodendrocyte survival a,b↓ spinal neuron injury a,b↑ motor recovery a,b ↓ RNA oxidation

Compression SCI

Sprague Dawley rats

250 nmol (82 g)/kg DHA i.v.

Saline i.v. Acute i.v. 30 min post surgery

Not reported

↓ spinal lipid peroxidation ↓ spinal protein oxidation

↓ spinal COX-2 protein

Lim et al. (2010)

Compression SCI

Sprague-Dawley rats

250 nmol (76 g)/kg EPA i.v.

Saline i.v. Acute i.v. 30 min post surgery

Not reported

↑ spinal neuronal survival ↑ spinal oligodendrocyte ↓ spinal neuron injury ↑ motor recovery

↔ spinal CD68 protein

Figueroa et al. (2012)

Compression SCI

Sprague Dawley rats

250 nmol (82 g)/kg DHA i.v.

vehicle i.v. 1 hr and 1 week prior to injury

Not reported

↑ Motor recovery ↑ axonal conductance ↑ myelin and axonal integrity ↓ cell death

↔ spinal GFAP, CD68 (macrophage), CD11 (microglia) protein

Hall et al. (2012)

Compression SCI

Sprague Dawley rats

Per kg body weight i.v.: a) 250 nmol (82 g) DHA b) 250 nmol (76 g) EPA

Vehicle i.v. Acute i.v. 30 min post surgery

Not reported

a,b ↔ hepatic neutrophil a↓plasma CRP

a↓ventral horn JTI protein (neutrophil marker) 24hr post injury and ventrolateral white matter JTI 4hr post injury a,b ↔ spinal IL-6, IL-1β, TNF-α,

35

KC/GRO/CINC protein Lim et al. (2013)

Compression SCI

Fat-1 mice Fat-1 on 10% corn oil

a) WT littermate on 10% corn oil b) WT littermate on n-3 PUFA adequate diet

12 weeks ↑ spinal PL DHA

↑cell survival

↑ Motor recovery

↓ spinal Iba-1 protein

↓ spinal IL-6 protein (vs. a only) ↔ spinal IL-1β protein

Lim et al. (2013)

Compression SCI

C57Bl/6 mice

a) 500 nmol (164 g)/kg DHA i.v.+ control diet b) saline i.v. + 400 mg/kg/d DHA/EPA p.o. c) 500 nmol (164 g)/kg DHA i.v. + 400 mg/kg/d DHA/EPA p.o.

Vehicle i.v. + control diet

Acute i.v. 30 min post surgery 4 weeks diet post surgery

Not reported

a,c↑ oligodendrocyte survival a,c ↑ neuronal survival a,c ↑ Motor recovery

a,c↓ dorsal horn Iba-1 protein a,b,c↓ ventral horn Iba-1 protein

Paterniti et al. (2014)

Compression SCI

CD1 mice 250 nmol (82 g)/kg DHA i.v.

Saline i.v. 30 min following injury Daily injection for 9 days for motor testing

Not reported

↓Histological damage ↑ Motor recovery ↓ apoptosis

↑ spinal IκB-a, protein

↓ spinal NF-κB, GFAP, TNF-α, Iba-1, iNOS, nitrotyrosine protein

ALA, α-linolenic acid; Alb, albumin; ARA, arachidonic acid; CD, cluster of differentiation; COX, cyclooxygenase; CRP, c-reactive protein; DHA, docosahexaenoic acid; EPA, eicosapentaenoic acid; GFAP, glial fibrillary acidic protein; IkB-a, nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha; IL, interleukin; INOS, nitric oxide synthase; NF-B, nuclear factor-κB; OA, oleic acid; PL, phospholipid; PUFA, polyunsaturated fatty acid; SCI, spinal cord injury; TNF, tumor necrosis factor; WT, wildtype; a,b,c indicates treatment group represented in outcome columns (brain n-3 PUFA, primary outcome, inflammatory outcome)

36

The effect of chronic oral administration of n-3 PUFA following spinal

compression was assessed in two studies, with mixed results. Huang and colleagues

reported that 400 mg/kg of DHA p.o. for 4 weeks following injury, in combination with

an acute injection of 250 nmol (82 g)/kg of DHA i.v. 30 minute after the injury reduces

microglial markers compared to control and appears to have an additive effect compared

to injection alone69. A second study, however, found that oral intake of 400 mg/kg of

DHA alone for 4 weeks only reduces microglial activation in the ventral horn of the

spinal cord with no effect on motor control, while injection of 500 nmol (164 g)/kg of

DHA i.v. alone or in combination with oral DHA supplementation reduces microglial

activation in both ventral and dorsal horns and increases motor recovery178.

Three studies have evaluated n-3 PUFA administration prior to spinal cord injury.

While acute injection of 250 nmol (82 g)/kg of DHA in rats either 1 hr or 1 week prior

to spinal compression had no effect on GFAP, CD68 and CD11179, 250 nmol (70 g)/kg

of alpha-linolenic acid i.v. 30 minute prior to spinal cord ischemia appeared to decrease

NF-B staining180. The transgenic fat-1 mouse, with higher brain DHA, had reduced

spinal cord injury-induced Iba-1 and IL-6 protein increase compared to wildtype

littermates181.

Taking all of these studies together, it is difficult to reach a conclusion on the anti-

inflammatory properties of n-3 PUFA in spinal cord injury. n-3 PUFA have variable

effects on astroglial and microglial markers in spinal cord injury, despite the fact that n-3

PUFA appear to increase motor control recovery and cell survival in these models.

37

2.3.3. n-3 PUFA and neuroinflammation in aging

Aging is associated with cognitive decline, as well as activated microglia182 and

reactive astrocytes183, which release pro-inflammatory cytokines. Alzheimer’s disease is

associated with similar neuroinflammatory markers, as well as neuronal loss and

accumulation of A plaques and neurofibrillary tangles116. There are 9 studies evaluating

the effects of n-3 PUFA on neuroinflammation induced by aging or Alzheimer pathology

(Table 2-3).

When comparing young vs. aged rats, 3 weeks of dietary supplementation of 10

and then 20 mg/kg of ethyl-EPA in aged rats reduces the IL-1protein concentration to

levels present in young rats184, 185, while also elevating the anti-inflammatory cytokine IL-

4 in the cortex184. This is in agreement with the observation that supplementation of 125

mg/day of ethyl-EPA for 4 weeks lowers CD40, IL-1 and IFN-186 while elevating IL-

4186 and PPAR187 in the hippocampus of aged rats. Similarly, chronic (8 week) dietary

tuna oil composed of 0.55% EPA and 0.36% DHA (% of total diet weight), prevents age-

induced elevation of hippocampal TNF- and monocytic marker CD11b protein levels,

whereas GFAP and IL-1 increase despite supplementation 188. A separate study

demonstrates that supplementing aged mice with 200 mg/kg/day of EPA elevates cortical

DHA, EPA and n-3 docosapentaenoic acid, while n-3 docosapentaenoic acid

supplementation only raises cortical n-3 docosapentaenoic acid. Despite this difference,

both treatments decrease levels of major histocompatibility complex (MHC) II, a protein

found on antigen presenting cells, in the hippocampus and cortex of n-3 PUFA

supplemented compared to control chow groups 189. Moranis et al., however, report no

effect of an n-3 PUFA adequate diet consisting of alpha-linolenic acid in aged mice on

38

Table 2-3: Summary of studies investigating the effects of n-3 PUFA in aging and Alzheimer’s disease models Authors (year)


Treatment Duration/

Time point

Brain n-3 PUFA



Martin et al. (2002)

Aging (4 vs. 22 mo)

Wistar rats chow supplemented with 10mg/d then 20mg/d eEPA

chow 3 weeks (10 mg/day) + 5 weeks (20 mg/day)

Not reported

↑ LTP

↓ apoptotic markers

↓ CX and HIP IL-1

Maher et al. (2004)

Aging (4 vs. 22 mo)

Wistar rats chow supplemented with 10mg/d then 20mg/d eEPA

chow 3 weeks (10 mg/day) + 5 weeks (20 mg/day)

Not reported

↓ apoptotic markers ↓ neurotrophic factors

↓ CX IL-1 protein ↔ CX IL-1RI protein ↑ CX IL-4 protein

Lynch et al. (2007)

Aging (4 vs. 22 mo)

Wistar rats chow supplemented with 125mg/d eEPA

chow supplemented with MUFA (isocaloric)

4 weeks Not reported

↓ HIP MHCII and CD40 (microglial activation) ↓ HIP IL-1, IFN- protein

↓ HIP IL-1 mRNA

↑ HIP IL-4 protein and mRNA

A (i.c.v.) in aged rats (22 mo)




↑ LTP

↓ HIP IL-1 protein

Minogue et al. (2007)

Aβ (i.c.v.) Wistar rats chow supplemented with 125mg/d eEPA



↑ LTP ↓ HIP IFN-, IL-1 protein

↑ HIP PPAR protein

Aging (3 vs. 22 mo)




↑ HIP PPAR protein

Kelly et al. (2011)

Aging (4 mo vs. 20 mo)

Rats (Strain unspecified)

a) Chow + EPA (200 mg/kg/d) b) chow + DPAn-3 (200 mg/kg/d)

Chow + MUFA

8 weeks a↑CX total DHA a ↑CX total EPA a,b↑ CX total

a,b ↑ LTP a,b ↑ learning and memory (MWM) a,b ↓ apoptotic markers

a ,b ↓CX MHCII protein a ,b ↓HIP MHCII mRNA

39

DPAn-3

a,b ↓ oxidative stress

Lebbadi et al. (2011)

3xTg-AD mice (12 vs. 20 *mo)

3xTg-AD/Fat-1 mice

3xTg-AD/Fat-1 on low n-3 diet

3xTg-AD/WT on low n-3 diet

18 month ↑CX total DHA ↑ n-3/n-6 ratio

*↓ in some AD markers

*↓ CX GFAP protein

Moranis et al. (2012)

Aging (3-5* vs. 19-23 mo)

CD1 mice n-3 adequate diet (fatty acids 10.7% LA, 1.6% ALA)

n-3 deficient diet (0.1% ALA of fatty acids)

3-5 months or 19-23 months

↑ CX DHA ↓ depressive-behaviour (FST)§ * ↑ spatial memory (YM) ↔ age-induced spatial memory loss (YM)

↔ CX IL-6 or IL-10 protein

Labrousse et al. (2012)

Aging (3 mo vs. 22 mo)

C57Bl/6 mice

Control + Tuna oil (0.55% EPA, .36% DHA of total diet weight)

Rapeseed oil, high oleic sunflower oil and palm oil (0.08% ALA of total diet weight)

8 weeks ↑ DHA, EPA

↑spatial memory (YM)

↔ object recognition ↑DG c-fos,

↓ HIP CD11b, IL-6, TNF-α mRNA ↔ HIP GFAP, IL-1 mRNA ↑ HIP astrocyte process length

Parrott et al. (2015)

TgCRND8 mice

TgCRND8 mice

Whole food diet containing 0.246% DHA (total diet weight)

Corn oil 27 weeks ↓spatial memory (MWM) ↓problem solving ↔ caudate nucleus task ↔ Aburden

↑HIP TNF-α mRNA ↔ HIP GFAP mRNA

ALA, α-linolenic acid; A, amyloid beta; AD, Alzheimer’s disease; CD, cluster of differentiation; DHA, docosahexaenoic acid; DPAn-3, docosapentaenoic acid; EPA, eicosapentaenoic acid; eEPA, ethyl-EPA; FST, forced swim test; GFAP, glial fibrillary acidic protein; HIP, hippocampus; IFN, interferon; IL, interleukin; LA, linoleic acid; LTP, long term potentiation; MHCII, major histocompability complex II; MWM, Morris water maze; MUFA, monounsaturated fatty acid; PPARγ, peroxisome proliferator activated protein γ; PUFA, polyunsaturated fatty acids; TNF, tumor necrosis factor; WT, wildtype; YM, y maze a,b,,* indicates treatment group represented in outcome columns (brain n-3 PUFA, primary outcome, inflammatory outcome)

40

levels of pro and anti-inflammatory cytokines (IL-6 and IL-10 respectively) and age-

induced memory deficits, despite the fact that the n-3 PUFA adequate diet increases

cortical DHA and decreases depressive behaviour compared to an n-3 PUFA deficient

diet 190.

When challenged with A i.c.v., aged mice supplemented with 125 mg/kg ethyl-

EPA have lower IL-1 186 and higher PPAR compared to those on a control diet 187.

Twenty month old 3xTg-AD mice, a transgenic mouse model of Alzheimer’s disease,

have a reduction in GFAP protein in the parieto-temporal cortex when crossed with the

fat-1 mouse 191.

Administration of n-3 PUFA has not always yielded positive results in

Alzheimer’s disease models. When supplemented with 0.246% DHA (% of total diet

weight) for 27 weeks, the TgCRND8 transgenic mouse, which overexpresses two

mutated forms of the amyloid precursor protein gene, demonstrates poor spatial memory

in the Morris water maze and elevated TNF- gene expression in the hippocampus

compared to a mouse receiving corn oil. It should be noted that DHA was delivered in a

whole food diet, which also contained vitamins and phytochemicals 192.

2.3.4. n-3 PUFA and neuroinflammation in Parkinson’s disease

Parkinson’s disease has a neuroinflammatory component, with evidence of

activated microglia, and high pro-inflammatory cytokine and NFB levels in both

postmortem human samples and in vivo animal models 193. n-3 PUFA may target

neuroinflammation in Parkinson’s disease models, along with other potential

mechanisms, including oxidative stress and increased neurotrophic factors 194.

41

Six studies were identified that investigate the effects of n-3 PUFA on neuroinflammation

in Parkinson’s disease models (Table 2-4). When supplementing mice with a diet

containing 0.8% ethyl-EPA (% of total diet weight), Luchtman et al. observed a reduction

in s.c. 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine induced increases in striatal TNF-

and IFN-protein. Midbrain IL-10 was also reduced by ethyl-EPA treatment, while

expression of COX-2 and calcium dependent cytosolic phospholipase A2, enzymes

involved in inflammatory signaling, were unaffected 195. Similarly, Meng and colleagues

found no difference in striatal COX-2 or calcium dependent cytosolic phospholipase A2

mRNA expression following 6 weeks of 0.8% ethyl EPA prior to i.c.v. injection of 1-

methyl-4-phenylpyridinium, the active metabolite of 1-methyl-4-phenyl-1,2,3,6-

tetrahydropyridine. Both studies achieved increases in brain EPA, but not brain DHA

with s.c. ethyl-EPA 195, 196. In a third study, fat-1 transgenic mice with raised cortical

DHA, have lower levels of the astrocytic marker GFAP compared to their wildtype

littermates after 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced injury 197.

Injecting LPS directly into the substantia nigra causes dopaminergic neuron injury

and a neuroinflammatory response similar to Parkinson’s disease. Feeding a diet

containing 15% fish oil (% of total diet weight) to Sprague Dawley rats for 2 weeks

minimizes dopaminergic injury, while also reducing monocytic marker OX42 (also

known as CD11b), TNF-α and IL-1β protein 198. In the last study, the authors evaluated n-

3 PUFA supplementation in A53T α –synuclein transgenic mice, a transgenic model of

Parkinson’s disease expressing mild symptoms. Supplementation with a diet containing

13% n-3 PUFA of total fatty acids does not affect lectin, a microglial marker,

42

Table 2-4: Summary of studies investigating the effects of n-3 PUFA in Parkinson’s disease models Authors (year)


Treatment Duration/

Time point

Brain n-3 PUFA



Meng et al. (2010)

MPP+ C57Bl/6 mice

Chow + 0.8% eEPA

Chow + 0.8% palm oil

6 weeks ↑ ST/FCX Total EPA and DPA ↔ ST/FCX Total DHA

↔ ST, FCX^ DA ↔ ST Bcl-2 mRNA ↓ ST Bax, Caspase-3 mRNA

↔ ST cPLA2 and COX-2 mRNA

Muntane et al. (2010)

A53T α -synuclein transgenic mice

A53T α -synuclein transgenic mice

a) Low n-3 + 11.4% DHA (13% of fatty acid n-3) b) Low n-3 (0.9% of fatty acid n-3)

Control (8% of fatty acid n-3)

6 months from 6 months of age

a ↑total DHA and EPA

a,b↓ oxidative stress a,b ↔ α-synuclein

a,b ↔ CX lectin (microglia) and GFAP

Bousquet et al. (2011)

MPTP (i.p.) Fat-1 transgenic mice (C57Bl/6 x C3H)

fat-1 transgenic mice on high n-6/low n-3 diet (101.79:1 n6/n3 ratio)

wildtype littermates on high n-6/low n-3 diet (101.79:1 n6/n3 ratio)

6 months ↑ CX DHA

↔ striatal or nigral dopaminergic injuryΨ

↓ CX GFAP

Luchtman et al. (2012)

MPTP-P (s.c.)

C57Bl/6 mice

chow + 0.8% eEPA chow + 0.8% palm oil

6 weeks ↑ CX EPA, DPA n-3 ↔ CX DHA

↓hypokinesia and anxiety (RT, PT, OF) ↑ learning and memory (MWM)

↓ striatal TNF-, IFN-γ protein

↓ midbrain IL-10 protein

↔ striatal cPLA2, COX-2 mRNA

Ji et al. (2012)

SN LPS (i.c.v.)

Sprague Dawley rats

15% fish oil diet (30% fish oil as EPA and DHA)

15% corn oil diet


↓ dopaminergic injury ↓ nigral dopaminergic neuron degeneration

↓ SN CD11b, TNF-, IL-1 p65

(NF-B subunit) protein

Zhang et al. SN LPS (i.c.v.) Sprague Per kg body weight Not reported 3 days prior Not b,c↓rotational a,b,c↓ SN CD11b protein

43

(2015) Dawley rats

(route not specified): a) 25 g RvD2 b) 50 g RvD2 c) 100 g RvD2

to LPS and 27 days post

reported behaviour (RT) b,c↑dopaminergic neurons

COX; cyclooxygenase; CX, cortex; DA; dopamine; DPA, docosapentaenoic acid; DHA, docosahexaenoic acid; eEPA, ethyl-EPA; EPA; eicosapentaenoic acid; FCX; frontal cortex; GFAP, glial fibrillary acidic protein; IFN, interferon; IL, interleukin; LPS, lipopolysaccharide; MPP+, 1-methyl-4-phenylpyridinium; MPTP, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine; MWM; morris water maze; NF-B, nuclear factor kappa light chain enhancer of activated B cell OF, open field; PLA, phospholipase; PT; pole test; PUFA, polyunsaturated fatty acids; RT; rotorod test; Rv, resolvin: SN, substantial nigra; ST, striatum; TNF, tumor necrosis factor a,b, indicates treatment group represented in outcome columns (brain n-3 PUFA, non-inflammatory outcome, inflammatory outcome) EPA lowered COX-2 mRNA compared to palm oil in saline (control) injected animals Ψ protection from nigral dopaminergic injury was correlated to brain DHA levels (secondary analysis) ^EPA increased striatal dopamine in saline injected group

44

or GFAP-positive cell counts 199. Injecting 25, 50, and 100 g/kg of resolvin D2 (route of

administration not specified) for 3 days prior to LPS injection followed by 27 daily

injections decreased the LPS-induced increases in CD11b protein. The 25 g/kg dose,

however, was ineffective at reducing apomorphine induced rotational behaviour 200.

Overall, the supplementation of n-3 PUFA does not appear to affect the

arachidonic cascade in Parkinson’s disease models. It is does appear, however, that n-3

PUFA does reduce cytokine production and may reduce astrocyte and microglial

activation.

2.3.5. n-3 PUFA and neuroinflammation with lipopolysaccharide

There are five studies (Table 2-5) that evaluated the effects of n-3 PUFA on the in

vivo brain response to LPS. Four of these studies administered LPS peripherally by i.p.

injection. Kavanagh et al. reported that mice receiving 50 mg/day of either ethyl EPA,

ethyl gamma linolenic acid (GLA) or a combination of both fatty acids for 4 weeks were

protected from LPS-induced (100 g/kg i.p.) decreases in anti-inflammatory cytokines

IL-4 and IL-10 in the hippocampus, while only ethyl-EPA and ethyl-EPA + ethyl-gamma

linolenic acid attenuated the decrease in PPAR protein. None of the treatments reduced

hippocampal IL-1 protein concentration 201. The lack of decrease of IL-1 from n-3

PUFA administration in this study agrees with the observation that an n-3 PUFA + n-6

PUFA diet (6% total weight made of rapeseed and peanut) fed to dams from gestation

through to 8 weeks postnatal does not attenuate hippocampal IL-6 mRNA response of

pups to 30 mg/kg LPS i.p. compared to an n-6 PUFA-only diet (6% peanut) 202. A

separate study, however, reported that 500 mg/day ethyl-EPA for 4 weeks, decreases

45

Table 2-5: Summary of studies investigating the effects of n-3 PUFA in lipopolysaccharide models Authors (year)


Treatment Duration/ Time point

Brain n-3 PUFA



Kavanagh et al. (2004)

Systemic LPS (i.p.)

Wistar rats a) chow +50 mg/d eEPA b) chow + 50 mg/d eGLA c) chow + 50 mg/d eEPA and eGLA

chow 4 weeks Not reported

a,b,c ↑ LTP

a,b,c ↑ HIP IL-10, IL-4 protein a,c ↑ HIP PPAR protein a,b,c ↔ HIP IL-1β protein

Lonergan et al. (2004)

Systemic LPS (i.p.)

Wistar rats chow supplemented with 500 mg/d eEPA

chow 4 weeks Not reported

↑ LTP

↓ apoptotic markers

↓ HIP IL-1 protein

Mingam et al. (2008)

Systemic LPS (i.p.)

CD1 mice 6% peanut + rapeseed oil (n-6 + n-3) diet

6% peanut oil (n-6) diet

Gestation + 8 weeks post-natal

↑ CX DHA ↓ social interaction ↔ food intake

↔ HIP IL-6 mRNA

Orr et al. (2012)

LPS i.c.v. C57Bl/6 mice

8% safflower + 2% fish oil

10% safflower diet

9 weeks ↑ HIP total DHA ↔ HIP FFA DHA

↓ HIP COX-2 mRNA

↔ HIP IL-1, GFAP, cPLA2, CCL3, iNOS, mPGES, RelB, CD11b, CD45, CCL2, CYBB, TNF-α mRNA

LPS i.c.v. C57Bl/6 mice

a) 40 μg i.c.v. DHA b) 1 μg i.c.v.17S-HpDHA

aCSF i.c.v. 24 hr infusion post surgery

b↑HIP NPD1

a,b↓ HIP IL-1, CCL3, TNF-α, CD11b, CD45, CYBB mRNA b↓HIP GFAP, CD11b mRNA a,b ↔ HIP GFAP, cPLA2, COX-2, iNOS, mPGES, RelB, CCL2, CD11b mRNA a ↔ HIP GFAP, CD11b mRNA

LPS i.c.v. Fat-1 transgenic mice (C57Bl/6 x C3H)

Fat-1 transgenic mice on 10% safflower diet

Wildtype littermate on 10% safflower diet (n-3 deficient)

12 weeks ↑ HIP total and FFA DHA

↓ HIP IL-1, GFAP, cPLA2, COX-2, CCL3, INOS, mPGES, RelB, CD11b, CD45, CCL2, CYBB, TNF-α mRNA ↓ HIP GFAP, Iba-1, FJb protein

LPS i.c.v. Fat-1 transgenic mice

Fat-1 transgenic mice on 10% safflower diet

Wildtype littermate on 8%

12 weeks (wildtype were on fish

↔ HIP total and FFA DHA

↑ HIP mPGES mRNA

↔ HIP IL-1, GFAP, cPLA2, COX-2, CCL3, INOS, mPGES,

46

(C57Bl/6 x C3H)

safflower diet + 2% fish oil

oil for only 9 weeks)

RelB, CD11b, CD45, CCL2, CYBB, TNF-α mRNA

Delpech et al. (2014)

Systemic LPS (i.p.)

Fat-1 transgenic mice (C57Bl/6 x C3H)

Fat-1 transgenic mice on standard diet (4.8% of total fatty acids n-3 PUFA)

Wildtype littermate on standard diet (4.8% of total fatty acids n-3 PUFA)

3-5 months ↔ HIP total DHA ↑ HIP total DPA n-3 and EPA

↑ learning and memory (YM) ↑ food consumption ↔ body weight loss

↑ HIP COX-2, TGF-β1, mPGES-1 and CX3CL1 mRNA ↓ HIP IL-1β mRNA 24hr post LPS ↔ HIP TNF-α, IL-6, IL-10, CX3CL1 mRNA 24hr post LPS ↑ HIP CD36 and MHCII protein 24hr post LPS ↑ HIP IL-10 mRNA 2hr post LPS ↔ HIP TNF-α, IL-1β and IL-6 mRNA 2hr post LPS

17-HpDHA, 17-hydroperoxy-DHA; CCL, chemokine (c-c motif) ligand; aCSF, artificial cerebrospinal fluid; CX3CL, chemokine (c-x3-c motif) ligand; COX, cyclooxygenase, CX, cortex; CYBB, cytochrome b-245 beta polypeptide DHA, docosahexaenoic acid; DPA, docosapentaenoic acid, eEPA, ethyl-EPA; eGLA, ethyl-gamma-linolenic acid ; EPA, eicosapentaenoic acid; FFA, free fatty acid; FJ, Fluoro-jade; GFAP, glial fibrillary acidic protein; HIP, hippocampus; Iba, ionized calcium-binding adapter molecule; IL, interleukin; LPS, lipopolysaccharide; LTP, long term potentiation; MHC, major histocompatibility complex n, omega; NOS, nitric oxide synthase; NP, neuroprotectin; PGES, prostaglandin E synthase PLA, phospholipase; PPAR, peroxisome proliferator activated protein, PUFA, polyunsaturated fatty acids; RelB, nuclear factor-κB subunit ; TGF, transforming growth factor; TNF, tumor necrosis factor; YM, y maze a,b indicates treatment group represented in outcome columns (brain n-3 PUFA, non-inflammatory outcome, inflammatory outcome)

47

hippocampal IL-1 along with apoptotic cell markers 203. Finally, 24 hr following 125

g/kg of LPS i.p., fat-1 transgenic mice have attenuated LPS-induced increases in IL-1

mRNA compared to their wildtype littermates. However, fat-1 mice also have augmented

LPS-induced increases in COX-2, membrane associated PGE synthase-1, transforming

growth factor 1 and chemokine (c-x3-c) ligand (CX3CL) 1. The authors argued that

increases in these genes reflect an anti-inflammatory phenotype, where the fat-1 mouse

has a higher proportion of M2 phenotype microglia 24hr post-LPS 204.

The fifth study administered 5 g of LPS directly into the brain left lateral

ventricle, which avoids systemic effects that i.p. injection of LPS may have 91. C57bl/6

mice supplemented with 2% fish oil (% of total diet weight) for 9 weeks had elevated

hippocampal total phospholipid DHA, but showed no changes in the non-esterified fatty

acid pool. Out of a panel of inflammatory markers, only hippocampal COX-2 mRNA

were decreased by dietary fish oil supplementation upon LPS administration. The fat-1

mouse, which has both elevated total and non-esterified DHA in the hippocampus

compared to its wildtype counterpart, showed attenuated LPS-induced mRNA expression

of a panel of pro-inflammatory genes including IL-1, GFAP, COX-2, and CD45. When

wildtype littermates are switched to a 2% fish oil diet for 9 weeks from weaning until

surgery, phospholipid and non-esterified DHA reaches the same concentration as in fat-1

mice, and gene expression profiles are similar with the exception of increased

hippocampal expression of membrane PGE synthase mRNA 91. This suggests the

possibility that the non-esterified pool may be the important pool for regulating

neuroinflammation.

The authors concluded the study by evaluating the effect of infusing either 40 g

48

of DHA or 1 g of 17S-hydroperoxy DHA (protectin D1 precursor) i.c.v. immediately

following LPS injection for 24 hr. While only 17-HpDHA infusion increased protectin

D1 concentrations, both treatments decreased LPS-induced pro-inflammatory markers

including TNF- and IL-1. 17S-hydroperoxy DHA appears to be more potent, as 1 µg

decreased CD11b and GFAP mRNA expression, which 40 µg DHA was unable to do.

Unlike the transgenic and feeding approaches, i.c.v. administration of DHA or 17S-

hydroperoxy DHA does not modulate the ARA cascade enzymes COX-2 and calcium

dependent cytosolic phospholipase A2 91

2.3.6. n-3 PUFA and neuroinflammation in i.c.v. IL-1

We identified three studies that investigated the effect of n-3 PUFA on

neuroinflammation induced by i.c.v. injection of IL-1Table 2-6)Supplementing rats

for seven weeks with 1% ethyl EPA (% of total diet weight) prior to injection of IL-

1ng i.c.v.)reduces not only memory deficits in the Morris water maze, but also

brain PGE2 compared to the control coconut oil supplementation. However,

supplementation of 0.2% EPA or with 5% soybean oil is ineffective at attenuating the

effects of i.c.v. IL-1 205. In a comparable study, 0.5% of either ethyl EPA or ethyl

gamma linolenic acid (% of total diet weight) for 7 weeks prior to IL-1administration

(15 ng i.c.v.) reduces hippocampal PGE2. This study finds EPA is more effective than

gamma linolenic acid at reducing IL-1-induced amygdaloid PGE2 concentration and

elevating IL-10 while also decreasing anxiety and memory deficits 206. Finally,

Taepavarapruk and Song also report anti-inflammatory properties of ethyl EPA in the

i.c.v. IL-1model (15 ng i.c.v.), where 0.8% ethyl EPA (% of total diet weight) for 7

49

Table 2-6: Summary of studies investigating the effects of n-3 PUFA in IL-1 models Authors (year)


Treatment Duration/

Time point

Brain n-3 PUFA



Song and Horrobin (2004)

IL-1 (i.c.v.) Wistar rats a) 5% soybean, 4.8% coconut oil + 0.2% eEPA, b) 4% coconut oil + 1% eEPA diet

5% coconut oil diet


b↓ memory loss (MWM)

b ↓ brain PGE2

Song et al. (2008)

IL-1β (i.c.v.) Wistar rats a) 4.5% palm oil + 0.5% eEPA b) 4.5% palm oil + 0.5% eGLA c) 4% palm oil + 1% ARA-rich oil diet

5% palm oil diet


a ↓ memory loss (MWM) a ↓ anxiety (EPM)

a,b↓ HIP PGE2 a↓ amygdala PGE2 a↑ amygdala, hypothalamus IL-10 protein

Taepavarapruk and Song (2010)

IL-1β i.c.v. Long-Evans rats

0.8% (v/w) eEPA 0.8% (v/w) palm oil

7 weeks prior surgery

Not reported

↔ Acetylcholine release ↑ NGF

↑ Learning and memory (8ARM)

↓HC IL-1 mRNA

8ARM, 8-arm radial maze; ARA, arachidonic acid; eEPA; ethyl eicosapentaenoic acid; eGLA, ethyl-gamma-linolenic acid; EPM, elevated plus maze; HIP, hippocampus; IL, interleukin; MWM; morris water maze; NGF, nerve growth factor; PG, prostaglandin; PUFA, polyunsaturated fatty acids a,b,c, indicates treatment group represented in outcome columns (brain n-3 PUFA, non-inflammatory outcome, inflammatory outcome)

50

weeks reduces IL-1induction of IL-1 mRNA, even though it does not alter

acetylcholine concentrations 207.

2.3.7. n-3 PUFA and neuroinflammation in traumatic brain injury

Traumatic brain injury is associated with an increase in pro-inflammatory

cytokine production, including IL-1 and TNF-, and also is marked by increased

microglial activation 208, 209. Three studies (Table 2-7) have evaluated the anti-

neuroinflammatory properties of n-3 PUFA in traumatic brain injury models.

Supplementing mice with a DHA- and EPA-enriched diet (1.5% of total diet weight) 60

days prior to controlled cortical impact decreases IL-1, IL-1 and TNF- mRNA

expression following the injury compared to mice fed a low n-3 PUFA control. Mice on a

high n-3 PUFA diet also exhibit lower COX-2 mRNA and protein concentrations

following controlled cortical impact 210. A separate study found that following controlled

cortical impact, CD68 protein levels are lower in mice consuming 40 mg/kg of DHA

compared to no supplementation 211.

Traumatic brain injury by midline fluid percussion induces cognitive impairment

and motor deficits, while increasing activated microglia. The administration of 100 ng of

aspirin-triggered resolvin D1 i.p. for 7 days, starting 3 days before the percussion,

reduced the injury induced cognitive impairment and motor deficit, but did not reduce

microglial activation. Resolvin E1, however, did reduce traumatic brain injury induced

microglial activation, while not having any effects on the cognitive impairments and

motor deficits 212.

51

Table 2-7: Summary of studies investigating the effects of n-3 PUFA on traumatic brain injury models Authors (year)


Treatment Duration/

Time point

Brain n-3 PUFA



Mills et al. (2011)

Traumatic brain injury

Sprague Dawley rats

Per kg per day: a) 4 mg DHA b) 12 mg DHA c) 40 mg DHA

No treatment

30 days prior injury

Not reported

c↓ axon injury c↓ apoptosis c↑ learning and memory (MWM)

c↓ CD68 protein

Pu et al. (2013)


C57Bl/6 mice

DHA and EPA supplemented diet (15g/kg of diet)

Low n-3 diet (0.5% n-3)

2 months prior injury

↑ total brain DHA, EPA and n-3 DPA

↑ sensorimotor control (FF, WH, CT) ↑ learning and memory (MWM) ↔ lesion volume ↑ CA3 neuronal survival ↓ myelin injury ↑ nerve conductance

↓ CX Iba-1 COX-2 protein

↓ CX IL-1α, IL-1β, TNF-α, COX-2 iNOS mRNA

Harrison et al. (2015)


C57Bl/6 mice

a) 100 ng AT-RvD1 i.p. b) 100 ng RvE1 i.p.

Saline i.p. Daily for 7 days starting 3 days before injury

Not reported

a↓ motor deficit a↓learning and memory (OR) b ↑ sleep ↔ righting reflex

b ↓activated microglia b ↓rod microglia b ↑ramified microglia

52

AT, aspirin triggered; CA, cornu ammonis, COX, cyclooxygenase; CT, cylinder test; CX, cortex, DHA, docosahexaenoic acid; DPA, docosapentaenoic acid, EPA, eicosapentaenoic acid; FF, foot fault; IL, interleukin; Iba, ionized calcium-binding adapter molecule; MWM, morris water maze; NOS, nitric oxide synthase; PUFA, polyunsaturated fatty acids; Rv, resolvin; TNF, tumor necrosis factor; WH, wire hang

53

2.3.8. n-3 PUFA and neuroinflammation in neuropathic pain

Neuropathic pain is a disorder associated with a lesion of a nerve in either the

peripheral or central nervous system 213, 214. Microglia are present in both acute and

chronic neuropathic pain 215, while pro-inflammatory cytokines such TNF- and IL-1

are thought to modulate pain responses 214.

Two studies were identified that evaluated the response of neuroinflammation

following n-3 PUFA bioactive mediator treatment in a neuropathic pain model (Table 2-

8). Injection of 300 ng of protectin D1 at the site of injury immediately following chronic

constriction of the sciatic nerve lowered the concentration of CCL2, a chemotractant for

microglia, and microglial activation in the spinal cord dorsal horn 216. Similar protection

was obtained with 3 days of intrathecal injection of 100 ng of resolvin E1, a bioactive

mediator derived from EPA, following injury. Resolvin E1 decreases pro-inflammatory

Iba-1 and GFAP mRNA expression and TNF- protein concentration 217.

2.3.9. n-3 PUFA and neuroinflammation in diabetes

There is evidence that diabetes is linked with increased neuroinflammation,

including NFB induction 218. Moreover, diabetics often experience diabetic neuropathic

pain, which itself is associated with neuroinflammation including microglial activation

219. Two studies investigated whether DHA was anti-neuroinflammatory in the

streptozotocin diabetic rat model (Table 2-9). Streptozotocin is a toxin that targets

pancreatic beta cells, inducing diabetes. Rats gavaged with 13.3 mg/kg/day of DHA for

12 weeks prior to streptozotocin (i.p.)-induction had decreased hippocampal NF-B and

54

Table 2-8: Summary of studies investigating the effects of n-3 PUFA in neuropathic pain models Authors (year)


Treatment Duration/

Time point

Brain n-3 PUFA



Xu et al. (2013)

Chronic constriction injury

CD1 mice 300 ng NPD1 s.c. perisurgical

Vehicle perisurgical

1 week prior to surgery

Not reported

↓ mechanical allodynia ↓ on going pain ↓ autotomy

↓ spinal LTP

↓ axonal injury

↓ spinal cord dorsal horn Iba-1 protein ↓ spinal cord dorsal horn GFAP, IL-1β and CCL2 mRNA

Xu et al. (2013)

Chronic constriction injury

CD1 mice 100 ng RvE1 i.t. Vehicle i.t. Daily for 3 days post injury

Not reported

↓ mechanical allodynia ↔ heat hyperalgesia

↓ dorsal horn Iba-1 and GFAP mRNA ↓ dorsal horn TNF-α protein

CCL, chemokine (c-c motif) ligand; GFAP, glial fibrillary acidic protein; Iba, ionized calcium-binding adapter molecule; IL, interleukin; LTP, long term potentiation; NP, neuroprotection, PUFA, polyunsaturated fatty acids; Rv, resolvin; TNF, tumor necrosis factor

55

Table 2-9: Summary of studies investigating the effects of n-3 PUFA in diabetes models Authors (year)


Treatment Duration/

Time point

Brain n-3 PUFA



Alvarez-Nölting et al. (2012)

STZ (i.p.) Wistar rats chow plus 13.3 mg/kg/d DHA by gavage

Chow# 12 weeks Not reported

↔ blood glucose and glycated hemoglobin ↑ HIP neurogenesis ↓ HIP neuronal apoptosis ↓ HIP oxidative stress ↑ learning and memory (MWM)

↓ HIP NF-κB protein

Jia et al. (2014)

STZ (i.p.) Sprague Dawley rats

4% fish oil (1.2% EPA + DHA)

chow 1 week prior to STZ and 5 week post STZ

Not reported

↔ blood glucose ↓ HIP oxidative stress ↑ learning and memory (MWM)

↓ HIP TNF-α mRNA,

↓ HIP pIKKβ, TNF-α, NF-κB proteins ↑ HIP IBα protein

DHA, docosahexaenoic acid, EPA, eicosapentaenoic acid; HIP, hippocampus; IB, nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha; IKK, inhibitor of nuclear factor kappa-B kinase subunit beta; MWM, morris water maze; NF-B, nuclear factor kappa light chain enhancer of activated B cell; STZ, PUFA, polyunsaturated fatty acids; STZ, streptozotocin; TNF, tumor necrosis factor # insulin-treated rats were also included in the study and were similar to DHA-only treated rats in all measures excluding weight, glycemic control, and oxidative stress

56

memory deficits despite elevated blood glucose levels, which were not impacted by DHA

treatment 220. Likewise, Jia and colleagues supplemented Sprague-Dawley rats with 4%

fish oil (% of total diet weight), starting 1 week prior to streptozotocin injection and

continuing 5-weeks post-streptozotocin, and showed that supplementation attenuates

streptozotocin-induced TNF- mRNA and protein increases in the hippocampus 221. Rats

receiving fish oil performed better in the Morris water maze, indicating improved

memory, even though blood glucose levels remained high 221.

2.3.10. n-3 PUFA and neuroinflammation in other models

Several studies have reported on the anti-inflammatory effects of n-3 PUFA in

other models (Table 2-10). Radiotherapy is a common therapeutic strategy against brain

tumors, and it is associated with cognitive dysfunction and increases in pro-inflammatory

cytokines mRNA such as IL-1 and TNF-222, 223. Lynch et al. observed that 4-week

supplementation of 250 or 500 mg/day of ethyl EPA attenuated the increase of pro-

inflammatory cytokines in the hippocampus of rats, including IL-1, IL-1RI, IL-1RAcP,

induced by whole body irradiation. Interestingly, the lower dose of 250 mg/day also

raised IL-10 concentration 224.

Olfactory bulbectomy has been proposed as a model of depression in rats 225,

presenting with changes in immunity 226 and increased brain pro-inflammatory cytokines

227. Olfactory bulbectomized rats supplemented with 1% ethyl EPA (% of total diet

weight) for 7 weeks demonstrated lower induction of calcium dependent cytosolic

phospholipase A2 mRNA expression and protein activity compared to rats supplemented

57

Table 2-10: Summary of studies investigating the effects of n-3 PUFA on other neuroinflammatory models Authors (year)


Treatment Duration/

Time point

Brain n-3 PUFA



Lynch et al. (2003)

Whole body irradiation

Wistar rats a) chow + 250 mg/d eEPA b) chow + 500 mg/d eEPA

chow 4 weeks prior to irradiation

Not reported

a,b↓ apoptotic markers

a,b↓ HIP IL-1, IL-1RI, IL-1RAcP protein a,b ↔ HIP IRAK protein phosphorylation ratio a↑ HIP IL-10 protein

Song et al. (2009)

Olfactory bulbectomy (depression)

Sprague Dawley rats

1% eEPA diet 1% palm oil diet


↓ depressive-like symptoms (MWM and OF)

↓ hypothalamus cPLA2 mRNA and activity

Cupri et al. (2012)

BAFF transgenic mice (lupus and Sjogren’s syndrome)

BAFF transgenic mice

n-3 supplemented diet (1.54% of fatty acids n-3 PUFA)

Control (0% of fatty acids n-3 PUFA)


↑ neurogenesis ↑ LTP

↓ HIP CD68 protein

Terrando et al. (2013)

Surgically induced cognitive decline

C57bl/6 mice

100 ng AT-RvD1 i.p. Vehicle i.p. Prior to incision

Not reported

↓ plasma LXA4, IL-6, AST protein ↑ LTP

↑ memory retention (FTC)

↑ HIP GFAP area

Yip et al. (2013)

G93A-SOD1 (ALS)

G93A-SOD1

300 mg/kg/d eEPA and 43 mg/kg/d eDHA

Control diet From 14 to 20 weeks

↑ spinal DHA ↑ Brain DHA and EPA

↔ disease progression in symptomatic mice ↑ disease progression in pre-

↓ spinal GFAP, Iba-1, and CD11b protein

58

symptomatic ↑ spinal vacuoles ↔ neuron morphology ↑ lipid peroxidation

Keleshian et al. (2014)

NMDA induced excitotoxicity

a) n-3 adequate (4.6% of diet n-3 PUFA) b) fish oil (9.4% of diet n-3 PUFA)

n-3 deficient (0.2% of diet n-3 PUFA)

15 weeks ↑DHA a,b↔ BDNF, NGF, iPLA2 protein a,b↓iPLA2 activity

b↓body weight

a,b↔ IL-1 , cPLA2, sPLA2, COX-1, COX-2 and GFAP protein a,b↔ sPLA2 activity a,b↑cPLA2 activity in saline

ALS, amyotrophic lateral sclerosis; AST, aspartate transaminase; AT, aspirin triggered; BDNF, brain derived neurotrophic factor; COX, cyclooxygenase; DHA, docosahexaenoic acid; EPA, eicosapentaenoic acid; eDHA; ethyl DHA; eEPA, ethyl-EPA; GFAP, glial fibrillary acidic protein; HIP, hippocampus; FTC, fear conditioning test; Iba-1, ionized calcium binding adaptor molecule; IL, interleukin; IkB-a, nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha; IL, interleukin; IRAK, IL-1 receptor-associated kinase; LTP, long term potentiation; LX, lipoxin; MWM, Morris water maze; n, omega; NGF, nerve growth factor; OF, open field; PUFA, polyunsaturated fatty acids; PLA, phospholipase a,b indicates treatment group represented in outcome columns (brain n-3 PUFA, primary outcome, inflammatory outcome)

59

with 1% palm oil 228. Ethyl-EPA supplemented rats also have reduced depressive

behaviour in the open field test and improved scores in the Morris water maze 228.

The BAFF (B cell activating factor belonging to the TNF family) transgenic

mouse is a mouse model that presents as a model of lupus. This model has been reported

to have microglial activation 229. When compared to an n-3 PUFA deficient control,

BAFF transgenic mice consuming a diet containing 1.54% n-3 PUFA (% of total fatty

acids, combination of -linolenic acid, EPA and DHA) have improved neurogenesis and

long-term potentiation, and lower hippocampal CD68 protein concentrations 230.

Surgery is associated with cognitive decline 231. Administering 100 ng of the

specialized pro-resolving lipid mediators aspiring-triggered resolvin D1 to mice prior to

tibia fracture stabilization increases and improves memory retention compared to mice

receiving vehicle control. This protection against surgery-induced cognitive decline was

accompanied with an increase in GFAP labeling in the hippocampus 232.

NMDA-induced excitotoxicity increases inflammatory markers in the brain,

including GFAP 233. Fish oil supplemented and n-3 PUFA adequate diets appeared to

decrease NMDA-induced cytosolic phospholipase A2 activity compared to diets deficient

in n-3 PUFA, despite not changing cytosolic phospholipase A2 protein level. Fish oil and

n-3 PUFA adequate diets also did not modify NMDA-induced GFAP, IL-1 or secretory

phospholipase A2 increases in protein levels 234.

In some instances, however, reducing inflammation with n-3 PUFA has been

reported to worsen symptoms. In the G93A-SOD1 mouse, a model of amyotrophic lateral

sclerosis, pre-symptomatic mice fed 343 mg/kg/day of n-3 PUFA for 6 weeks have

lowered GFAP and microglial markers levels, but accelerated symptom progression and

60

increased lipid peroxidation compared to mice on control diet 235.

2.4. Conclusion

In animal models, n-3 PUFA are generally associated with protection against

neuroinflammation, although with varying efficacy and consistency between disease

models. Herein we have summarized the growing body of literature on the modulation of

neuroinflammation by n-3 PUFA in animal models of stroke, spinal cord injury, aging,

Alzheimer’s disease, Parkinson’s disease, lipopolysaccharide and IL-1β injections,

diabetes, neuropathic pain, traumatic brain injury, depression, diabetes, surgically-

induced cognitive decline, whole body irradiation, amyotrophic lateral sclerosis and

lupus. In some cases, such as stroke, the evidence for an anti-inflammatory effect is

strong, where in other instances such as in spinal cord injury, the results are relatively

mixed.

The differences in results may be due to heterogeneity between studies. There are

vast differences between the type of n-3 PUFA administered (alpha-linolenic acid vs.

EPA vs. DHA), the route of administration (i.v. vs. p.o. vs. i.p. vs. i.c.v.), the dose (from

g to mg), the duration of administration (acute bolus to 18 months), the inclusion of

antioxidants, the inflammatory markers (microglial vs. astrocytic vs. cytokines) measured

and the timing of measurement. Moreover, control diets used in the studies reviewed vary

greatly in n-3 PUFA content, with some studies using an n-3 PUFA adequate diet while

others use an n-3 PUFA deficient diet. Thus, it is often unclear whether the phenotype

observed is related to supplementation or lack of apparent deficiency. Considering that

the relationship between n-3 PUFA levels is likely not linear to their biological effects 236,

61

it is difficult to compare studies that use different baselines to determine the efficacy of

augmenting n-3 PUFA levels.

As most studies measured only a few inflammatory markers in their experiments,

it is important to note that differentiation between various immune cell types is often

difficult or impossible based on a single marker; microglia and peripheral macrophages

share multiple known surface markers, and only techniques that can compare the origin

of the cells or the relative expression of various surface markers, such as flow cytometry,

are reliable for identification 118, 237. In addition, neutrophils have also been shown to

express CD68 and CD11b on occasion, while macrophages can express the common

neutrophil marker myeloperoxidase, highlighting the need for multiple methods of

identification 238.

It is also important to take into consideration that most studies evaluated the

expression of neuroinflammatory marker(s) at a single time point. Different cellular

markers and cytokines, however, change expression at different rates 239, 240. Evaluating

only single time points may result in false negatives, and limit any conclusion to be made

on the resolution of neuroinflammation.

Due to the small number of null studies reported in this review, combined with the

multiple variables mentioned above, it is difficult to define therapeutic dose and duration

of administration when comparing null studies with studies that found a positive or

negative effect of n-3 PUFA. Considering this, there does not appear to be a definite

therapeutic acute dose across all studies. While a dose of 833 g was reported to be

ineffective at lowering ischemia induced rise in PGE2 concentration 171, a lower dose of

20 g was successful at reducing ischemia induced myeloperoxidase activity 241. The

62

same issue arises with duration of n-3 PUFA treatment. While 20 months of n-3 PUFA

adequate diet administration did not mitigate the aging induced decrease in IL-10 190, the

consumption of ethyl EPA for 4 weeks was able to mitigate the LPS induced decrease in

IL-10 201. It may be possible to suggest, however, that DHA is more potent than EPA.

Out of 3 studies that evaluated the anti-inflammatory effects of EPA alone 162, 171, 176, only

one reported anti-inflammatory properties of EPA 162. Due to the small number of studies,

however, more studies are needed to establish the higher potency of DHA.

From the data presented in this review, it is also hard to determine whether n-3

PUFA always act directly on neuroinflammatory pathways. It is possible that n-3 PUFA

reduced the injury directly, such as by decreasing infarct size or neuronal cell death, and

attenuated the neuroinflammatory response that accompanies such injuries as a

consequence. Studies infusing IL-1 and LPS, however, directly activate

neuroinflammatory pathways with minimal injury. Consistent with the direct anti-

inflammatory properties of n-3 PUFA observed in cell culture 39, n-3 PUFA reduced

neuroinflammation in response to i.c.v. injection of both LPS and IL-1 indicating that

n-3 PUFA may have the ability to impact neuroinflammatory pathways separate from

their modulation of non-inflammatory pathways.

The mechanism by which n-3 PUFA convey their anti-inflammatory properties is

not clear. One hypothesis is that enzymatic metabolism of n-3 PUFA to bioactive

mediators is primarily responsible for the anti-inflammatory effect of increased tissue n-3

PUFA levels. As reported above, these bioactive lipid mediators are sufficient to reduce

neuroinflammation in stroke, i.c.v. LPS, neuropathic pain models, and surgery-induced

cognitive decline. Future studies evaluating the mechanism of n-3 PUFA in

63

neuroinflammation are warranted.

N-3 PUFA administration has been tested in multiple clinical trials for various

neurological and psychiatric disorders. At best, these have yielded mixed results 242-245. It

is unknown, however, whether neuroinflammation was actually targeted and lowered in

these trials. With the link between neuroinflammation and both neurological and

psychiatric disorders 117, 120, it would be important to correlate any reduction of

neuroinflammation to symptoms. With the development of translocator protein 18 kDa, a

receptor highly expressed in activated microglia, ligands for positron emission

tomography imaging, neuroinflammation can now be imaged in vivo in humans 246. Since

n-3 PUFA modulate microglia markers such as Iba1 as described above, future clinical

studies in humans could image neuroinflammation following n-3 PUFA treatment and

relate translocator protein 18 kDa binding with the reduction with symptoms.

Overall, this review summarizes all of the known literature on n-3 PUFA and

neuroinflammation. N-3 PUFA appear to target brain inflammation signaling in a variety

of animal models. However, the mechanism by which n-3 PUFA are anti-

neuroinflammatory and whether the neuroinflammatory effects observed are direct effects

or secondary have yet to be determined.

2.5. Acknowledgments

This work was supported by grants from the Natural Sciences and Engineering

Research Council of Canada and the Canadian Institutes of Health Research to

RPB. MOT received a studentship from the Natural Sciences and Engineering Research

Council of Canada and RPB holds a Canada Research Chair in Brain Lipid Metabolism.

64

Chapter 3: Objectives and Hypotheses

65

3.1 Objectives

1. To measure the rat neurolipidome and to determine the effect of using microwave

fixation on the neurolipidome.

2. To develop a self-resolving model of neuroinflammation following i.c.v. LPS

injection.

3. To determine if increasing brain DHA increases the resolution of

neuroinflammation following i.c.v. LPS injection.

3.2. Hypotheses

1. Bioactive mediators will be increased due to ischemia and will be inhibited by

microwave fixation.

2. DHA derived bioactive mediators will be correlated with the resolution of

neuroinflammation following i.c.v. LPS injection.

3. Increasing brain DHA will increase the resolution of neuroinflammation

following i.c.v. LPS injection.

66

Chapter 4: High-resolution lipidomics coupled with rapid

fixation reveals novel ischemia-induced signaling in the rat

neurolipidome Adapted from: Marc-Olivier Trépanier, Michael Eiden, Delphine Morin-Rivron, Richard

P. Bazinet, Mojgan Masoodi (Submitted to Journal of Neurochemistry)

Contribution: Along with RPB, I helped design the study. I collected all brain samples and travelled to Lausanne, Switzerland to perform the lipid extraction and learn the mass spectrometry techniques. Along with MM, I performed the statistical analysis. I wrote the first draft of the manuscript, with some technical help from MM.

67

4.1. Abstract

The field of lipidomics has evolved vastly since its creation 15 years ago.

Advancements in mass spectrometry have allowed for the identification of hundreds of

intact lipids and lipid mediators. However, due to the release of fatty acids from the

phospholipid membrane in the brain caused by ischemia, identifying the neurolipidome

has been challenging. Microwave fixation has been shown to reduce the ischemia-

induced release of several lipid mediators. Therefore, this study aimed to develop a

method combining high-resolution tandem mass spectrometry, high-energy head-focused

microwave fixation and statistical modeling, allowing for the measurement of intact

lipids and lipid mediators in order to eliminate the ischemia-induced release of fatty acids

and identify the rat neurolipidome. In this study, we demonstrated the ischemia-induced

production of bioactive lipid mediators, and the reduction of variability by using

microwave fixation in combination with liquid chromatography with tandem mass

spectrometry. We have also illustrated for the first time the microwave inhibition of

alterations of intact lipid species due to ischemia. While many phospholipid species were

unchanged by ischemia, other intact lipid classes such as lysophospholipids were

increased due to ischemia.

68

4.2 Introduction

The field of lipidomics has vastly expanded since its emergence approximately 15

years ago247-249. Due to the diversity of lipid species, as well as the wide range of their

concentrations, it is essential to use different lipidomic approaches to produce a global

profile of structurally and functionally diverse lipids to understand lipid metabolism and

signaling in brain tissue biology. Lipidomic approaches have previously been reported in

various tissues, in either normal or pathological state, including adipose250, nasal

washes251 and brain24, 252.

Mass spectrometry-based lipidomics is currently the most commonly used tool for

profiling lipid species. There are currently two main analytical approaches which in

parallel provide a comprehensive, global profiling of the brain tissue lipidome. Firstly,

there is the lipidomics of intact lipids, including shotgun lipidomics (developed by Han

and Gross)249 and liquid chromatography with tandem mass spectrometry-based

lipidomics, which aims at the rapid identification of hundreds of molecular lipids across

multiple structural classes. The second approach, lipidomics of lipid-signaling molecules,

captures a wide range of low-abundance lipid species within a class or specific pathway.

It is essential to combine these two approaches to capture and study the lipidome

and related lipid signaling in the brain. Chromatographic separation, solid-phase

extraction and liquid-liquid fractionation can greatly improve the recovery of low-

abundance lipid species. In brain tissue, due to the high concentration of lipids,

fractionation of different classes of lipids is essential prior to analysis of lipid mediators.

Brain tissue is capable of generating a wide range of signaling molecules.

Arachidonic acid (ARA), for example, is an important component of mammalian cell

69

membrane phospholipids. Depending on the enzyme that cleaves ARA from the

membrane, ARA can present in the forms of non-esterified ARA, 2-arachidonyl glycerol

and arachidonyl ethanolamine. Non-esterified ARA, a signaling molecule in itself, can

also be further metabolized by a multitude of enzymes, generating a vast array of

bioactive mediators such as the pro-inflammatory prostaglandins (PG) and pro-resolving

lipoxins253.

The identification and quantification of fatty acid-, fatty acyl glycerol- and fatty

acyl ethanolamide-related bioactive lipids is a challenging task. This is mainly due to the

large number of bioactive lipids with similar chemical properties which are produced

within the same cascade and are part of a complex regulatory network. Thus, they have to

be measured simultaneously to assess the biochemical processes being studied. This task

is further complicated by the presence of a large number of isomers of bioactive lipids

with very similar physiochemical properties but diverse biological functions. Therefore,

the comprehensive study of lipids requires a highly sensitive and selective analytical

method.

We have developed a lipidomics platform using high-mass accuracy and mass-

resolution mass spectrometry, which allows us to identify the wide range of bioactive

lipids in biological systems254. High-resolution mass spectrometry allows the separation

of many isobars by measuring the accurate mass/charge (m/z) ratios of the lipid species

and by computing the elemental formulae when combined with tandem mass

spectrometry. This simplifies the identification and structural elucidation of unknown

lipid mediators254, 255.

70

The challenges of brain tissue lipidomics include the development of relevant

analytical methodologies as well as bioinformatics tools for determination of alterations

in lipid metabolic pathways and signaling during disease progress. Although currently

available databases such as LIPID MAPS and METLIN provide valuable tools for the

identification of lipid species in brain tissue, the development of sophisticated

bioinformatics tools such as lipid prediction for database-independent approaches,

theoretical databases and search algorithms is critical for the identification of unknown

lipid species254, 256, 257.

The measurement of artifacts poses another challenge in the attempt to describe

the brain lipidome. It has been known for some time that the lipid profile of the brain

drastically changes under hypoxic conditions258. Coined the “Bazan Effect”259, Bazan and

colleagues demonstrated that ischemia releases various fatty acid from the phospholipid

membrane into the non-esterified fatty acid pool due in part to increased glutaminergic

transmission260-262, resulting in increased activity of phospholipases263. While multiple

fatty acids are affected by ischemia, ARA is the main component of that release258. The

released fatty acids are then metabolized and increase the low basal concentrations of the

downstream mediators264, 265. This release of non-esterified fatty acids from the

phospholipid membrane causes complications when applying lipidomics approaches to

measure lipid species in the brain, and especially low abundance downstream mediators.

In order to minimize the Bazan Effect and eliminate the increased variability in

the data, microwave fixation has been applied as a method of euthanasia266. In short, a

focused high-energy microwave beam is aimed at the top of the head, denaturing all

proteins involved in the release of fatty acids from the phospholipid membrane as well as

71

the proteins involved in downstream metabolism, effectively fixing the brain in its current

state. Previous studies utilizing microwave-fixation have used microwaves that generate

approximately 3 to 13 kW beams for 1.6 sec up to 3.5 sec267-269, which allows for rapid

and humane euthanasia and further reduces the potential confounding effects of ischemia.

In this study, we used of high-energy head-focused microwave fixation in

combination with multiple mass spectrometry methods in order to characterize and to

illustrate the effect of ischemia on the rat neurolipidome (Figure 4-1). The rat

neurolipidome was assessed using high-energy head-focused microwave fixation and

compared to the neurolipidome following CO2 asphyxiation. Furthermore, we measured

the rat neurolipidome following LPS-induced inflammatory signals independent of

ischemia.

4.3. Methods

4.3.1. Subjects

The present study was conducted in accordance to the standards of the Canadian

Council for Animal Care and was approved by Animal Care Committee of the Faculty of

Medicine at the University of Toronto (protocol number 20009449). Two month old

Long Evans rats were purchased from Charles Rivers (La Prairie, Qc). Animals were

housed 3 per cage in a vivarium on a 12 hr light/dark cycle and maintained at a

temperature of 21 C. Water and food were available ad libidum. The rat chow (Teklad

Global, 2018 18% Protein Rodent Diet; Envigo, Madison, WI, U.S.A.) composition

consisted of 189 g/kg protein, 60 g/kg fat, 554 g/kg carbohydrates, 38 g/kg fiber, 59 g/kg

72

ash, and 100 g/kg moisture. The diet fat composition (in percent of total fatty acids) was

palmitate (18.5%), stearate (2.8%), oleate (18.5%), linoleate (54.8%), and α-linolenate

73

LC-MS/MS

Direct-

infusion

MS/MS

MW

LPS

CO2+MW CO2

Figure 4-1. Flow of methods in Chapter 4

CO2

CO2 + MW LPS

MW

Head focused

High energy

Microwave fixation

13.5kW, 1.6s

CO2 asphyxiation

5 min

Brain

homogenization

SPE

column

MTBE

extraction

Mediators

Intact lipid

74

4.3.2. Treatment groups

Following the acclimatization period, the animals were separated into 4 groups

based on the proposed euthanasia method; 1) microwave fixation (MW, n=10), 2) CO2

asphyxiation (CO2, n=10), 3) CO2 asphyxiation followed by microwave fixation

(CO2+MW, n=9) and 4) lipopolysaccharide (LPS, Sigma Aldrich, St-Louis, MO, USA)

i.p. (1 mg/kg, 1mg/ml in 0.9% saline solution) 3 hr prior to microwave fixation (LPS,

n=9).

Group 3 served as a positive control to ensure that microwave fixation did not

denature lipid species, while group 4 served to identify lipid mediators that have

previously been shown not be present at basal levels and need an inflammatory insult to

increase its production270.

4.3.3. Microwave fixation

In order to perform high-energy head-focused microwave fixation, conscious,

unanesthetized animals are placed into an animal restrainer and immediately inserted into

the microwave (Cober Electronics Inc., Norwalk, CT, model S15P Vivostat). Following

insertion of the animal restrainer into the microwave, a single microwave beam (13.5 kW,

1.6s, 2450 MHz) is aimed directly at the top of the head. For CO2 asphyxiation group,

animals were placed in a CO2 tank and left inside the tank for 5 minutes following the

end of respiration.

Once euthanized, the heads of all 4 groups were cut off and placed on ice for 5

minutes. Brains were excised following the 5 minutes wait period and flash frozen in

75

liquid nitrogen for 15 seconds. Brains were placed in glass vials and the vials were filled

with N2 gas and stored at -80C until analysis.

(5.6%)236. The acclimatization period was 2 weeks, and the animals were handled every

2nd day to reduce stress during experimental procedures.

4.3.4. Brain preparation

Once all brains had been collected and were ready to analyze, they were kept on

dry ice to keep frozen, along with tubes to be used. Frozen brains were then inserted into

tissueTUBETM (Covaris Ltd., Brighton, U.K.) and attached to the cooled tubes.

TissueTUBETM containing frozen brains were quickly inserted in a cryoPREPTM CP02

impactor (Covaris Ltd., Brighton, U.K.) and received 1 to 3 calibrated impacts in order to

get brain into powder form. TissueTUBETM were inverted, transferring the brain powder

into attached cooled tubes and quickly returned to dry ice to avoid thawing.

Approximately 100 mg of crushed brain was weighed and transferred into a new frozen

Eppendorf tube to maintain brain frozen.

4.3.5. Lipid extraction

100 mg of whole brain tissue was homogenized in 1 ml of ammonium bicarbonate

buffer (concentration: 150 mM of ammonium bicarbonate in water) using a Tissue Lyser

(Qiagen AG, Switzerland) at a speed of 25 Hertz for 2.5 min. 150 l of the homogenate

was collected for intact lipid analysis, leaving 850 l for bioactive mediator analysis.

76

20 l of the 150 l homogenate was further diluted with 160 l of ammonium

bicarbonate buffer using Hamilton Robot and 810 l of MTBE /methanol (7/2 v/v)

containing internal standard was added to this mixture. The internal standard mixture

contained: lysophasphatidylglycerol 17:1, lysophosphatidic acid 17:0,

phosphatidylcholine 17:0/17:0, phosphatidylserine 17:0/17:0, phosphatidylglycerol

17:0/17:0, phosphatidic acid 17:0/17:0, lysophposphatidylinositol 13:0,

lysophosphatidylserine 13:0, lysophosphatidylcholine 12:0,

lysophosphatidylethanolamine, cholesteryl D6, diacylglycerol 17:0/17:0, triacylglycerol

17:0/17:0/17:0, ceramide 18:1;2/17:0, sphingomyelin 18:1;2/ 12:0,

phosphatidylethanolamine 17:0/17:0, cholesteryl ester 20:0, phosphatidylinositol

16:0/16:0. The solution was mixed at 700 rpm, 15 min at 4°C using a ThermoMixer C

(Eppendorf AG, Hamburg, Germany) and then centrifuged at 3000 g for 5 min. 100 l of

the organic phase was transferred to a 96-well plate, and dried in a speed vacuum

concentrator. Lipid extract was reconstituted in 40 l of 7.5 mM ammonium acetate in

chloroform/methanol/propanol (1:2:4, V/V/V). All liquid handling steps were performed

using a Hamilton STAR robotic platform with the Anti Droplet Control feature for

organic solvents pipetting as described previously271.

The remaining 850 l of homogenate was used for bioactive mediator analysis.

150 l of 100% methanol was added to the remaining homogenate to bring the volume to

1 ml. The mixture was spun at approximately 25000 g (5430 R centrifuge, FA-45-24-11-

HS rotor) (Eppendorf AG, Hamburg, Germany) for 5 min at 4C. The supernatant was

removed into a new glass tube on ice. One ml of 15% methanol was added to the pellet

and homogenized in a Tissue Lyser (25 Hz, 2.5 min). The homogenate was spun

77

(25000g, 5 min, 4C) and the supernatant was added to the glass tube. One ml of 15%

methanol was used to make a final volume of 3 ml.

Extraction of lipid mediators from the brain tissue was performed according to

our published protocol254 with slight modifications, outlined as follows: internal standards

PGB2-d4 (40 ng), 12-hydroxyeicosatetraenoic acid-d8 and arachidonyl ethanolamine-d8

(Cayman Chemicals, Ann Arbor, MI, USA) were added to the homogenized brain in 15%

(v/v) methanol in water. The cartridges (Strata-X 33 u Polymeric Reversed phase 60 mg

/3 ml) were washed with methanol (3 ml) followed by water (3 ml) prior to loading the

homogenate (3 ml). The cartridges were then washed with 15% methanol in water (3 ml)

and lipid mediators were eluted in methanol (3 ml) and collected in glass tubes. The

organic solvent was evaporated using a fine stream of nitrogen and the remaining residue

was re-dissolved in ethanol (100 l) and stored at –20ºC awaiting analysis.

4.3.6. Mass spectrometry analysis

Lipidomics analysis of intact lipids was performed using a QExactive mass

spectrometer (Thermo Fisher Scientific) equipped with a TriVersa NanoMate ion source

(Advion Biosciences) as described previously 271. The data were acquired in both positive

and negative mode using a resolving power of 140,000 in full scan and 17,500 in tandem

mass spectrometry mode. Scan m/z range from 200 to 1,000.

The lipidomics analysis of bioactive lipid mediators was performed as previously

described272 on an LTQ Elite (Thermo Scientific) linear ion trap-orbitrap mass

spectrometer using a heated electrospray ionization source in both negative and positive

ionization mode. Chromatographic analyses were performed using a A I-Class ultra

78

performance liquid chromatography system (Waters Corporation, Milford, MA, USA)

combining a binary pump, a FTN autosampler and a column oven. The autosampler

temperature was set at 4°C. Ten l out of the 100 l sample was injected onto a

chromatographic column. For the negative mode, the bioactive lipids were separated on a

C18 reversed-phase liquid chromatography column (Phenomenex Luna, 3 m particles,

1502 mm) using a linear mobile phase gradient (A, 0.02% glacial acetic acid in water;

B, 0.02% glacial acetic acid in acetonitrile) at a rate of 0.5 mL/min. Starting conditions

consisted of 35% B and were maintained for 1 minute. The gradient was then increased to

95% B over 12 min, remained there for 2 min and finally was returned to the initial

conditions for 2 min to allow equilibration. For the positive mode, the bioactive lipids

were separated on a C18 reversed-phase liquid chromatography column (Phenomenex

Kinetex-XB-C18, 2.6 m particles, 1002 mm) using a gradient (A: 10 mM ammonium

acetate+ 0.1% formic acid; B: ACN: H2O: formic acid (90:10:0.1)+ 10 mM ammonium

acetate) at 0.5 mL/min. Starting conditions consisted of 35% B and were maintained for 4

min. The gradient was then increased to 95% B over 6 min, maintained for 2 min and

finally returned to the initial conditions for 2 min to allow equilibration. Capillary and

source heater temperatures were set to 325 °C and 50 °C, respectively, and spray voltage

was adjusted to 4,000 V. A resolving power of 120,000 was used in full scan and 1,500 in

tandem mass spectrometry mode. Scan m/z ranges of 150 to 500 (mass spectrometry) and

50 to 500 (tandem mass spectrometry) were used. Method development and validation,

along with identification process, bioinformatics and related software have been

described previously 254, 271, 272.

79

4.3.7. Data analysis

Univariate statistical analysis using one-way analysis of variance (ANOVA) was

performed on log transformed concentrations due to unequal variance. For protectin D1,

17-hydroxy DHA, PGE2 and thromboxane B2, samples below the detection limits were

removed from the analysis. Since protectin D1 was not detected in either the MW and

LPS groups, a t-test was performed on the log transformed protectin D1 concentration of

the CO2 and CO2+MW groups. Differences in variability of concentrations were

measured by Bartlett’s test273.

For unsupervised multivariate statistical analysis, we used hierarchical cluster

analysis (HCA) using Ward’s algorithm. Supervised analysis was performed using Partial

Least Squares Discriminant Analysis (PLS-DA), where repeated stratified cross-

validation was used for model validation. All multivariate data analyses were performed

using the programming language R using custom-built scripts as well as the 'pls' and

'pheatmap' packages.

We calculated pairwise correlations between all variables in order to

visualize a correlation network in The BioLayout Express 3D software. The

Fruchterman-Reingold algorithm was used to generate the layout and only edges with a

pairwise correlation of higher than 0.85 were considered. To further clean up the data,

only cliques with more than 10 connected members were considered.

80

4.4. Results

In order to investigate the changes between the different treatment groups, we first

used unsupervised concepts of multivariate statistical analysis. HCA using Ward’s

algorithm was used to detect clusters in the data sets from lipid mediators and intact

lipids.

In the case of the of the lipid mediators (Figure 4-2a), the CO2 asphyxiation group

showed strong differences and clustered together compared to the other treatment groups.

(Figure 4-2a). The CO2+MW samples also grouped together (with the exception of a

single sample) and again showed a similar tendency to have elevated metabolite

concentrations compared to the MW group, albeit with much lower levels of metabolite

concentration compared to the CO2 group (Figure 4-2a). For example, PGE2

concentration was 522-fold higher in the CO2 group compared to the MW (Figure 4-2b).

In the CO2+MW group, PGE2 was also increased compared to the MW, but only

by 59 fold. This would indicate that microwave fixation is a crucial sample pre-

processing step in order to mitigate the increased mediator concentration measured

following ischemia. Injecting LPS 3 hours prior to microwave fixation increased the

production of PGE2 by 19 fold compared to the MW (Figure 4-2b).

Most mediators, such as thromboxane B2, arachidonyl ethanolamide, 12-

hydroxyeicosatetraenoic acid, and 17-hydroxy DHA, showed similar increases in the CO2

and CO2+MW groups, but no effect of LPS (Figure 4-2c,d,e,f). Some mediators, such as

protectin D1, were detected in the CO2 and CO2+MW groups, but were below detection

limits in the other two groups (Figure 4-2g). Furthermore, variability between groups was

81

Figure 4-2. Microwave fixation inhibits ischemia-induced production of

bioactive lipid mediators

CO 2

CO 2

+MW

LPS

MW

0.00

0.05

0.10

0.15

PD

1 (p

mo

l/m

g o

f bra

in ti

ssu

e)

N.D. N.D.

A

B

CO 2

CO 2

+MW

LPS

MW

0.0

0.4

0.84

6

8

12

-HE

TE

(p

mo

l/m

g o

f b

rain

tis

su

e)

A

B

C C

CO 2

CO 2

+MW

LPS

MW

0.000

0.005

0.010

0.03

0.04

AE

A (p

mo

l/m

g o

f b

rain

tissu

e) A

B

C C

CO 2

CO 2

+MW

LPS

MW

0.0

0.2

0.41.0

1.5

2.0

PG

E2 (p

mo

l/m

g o

f b

rain

tissu

e)

A

B

C D

CO 2

CO 2

+MW

LPS

MW

0.000

0.005

0.010

0.15

0.20

0.25

TX

B2 (p

mo

l/m

g o

f b

rain

tis

su

e) A

B

C CA

G F

E D

C B

H

Heat map representation illustrates that CO2 asphyxiation and CO2+MW clusters separately

from other groups (A). Brain concentrations (n=9-10, ± SEM) of prostaglandin (PG) E2 (B),

thromboxane (TX) B2 (C), arachidonyl ethanolamide (AEA) (D), 12-hydroxyeicosatetraenoic

acid (HETE) (E), 17-hydroxy DHA (HdoHE) (F), and protectin D1 (PD1) (G). Bar labeled

with different superscripts identifies significant differences identified by one-way ANOVA

and Tukey’s post hoc test of log-transformed concentrations (p<0.05). PLS-DA was

performed to elucidate the metabolites driving the separation. A 77.2% overall predictive

accuracy was achieved (H).

CO 2

CO 2

+MW

LPS

MW

0.00

0.25

0.50

3

4

5

17

-Hd

oH

E (p

mo

l/m

g o

f b

rain

tis

su

e)

A

B

C C

82

significantly different from one another, with the MW and LPS groups (aside for PGE2)

having the lowest variability.

To further elucidate what metabolites are driving the separation between the

groups, we performed a supervised multivariate analysis using PLS-DA (Figure 4-2h). To

test the group separation, we performed repeated stratified cross-validation and evaluated

the predictive performance on the respective hold out data sets. Separation of the four

phenotypic groups on the lipid mediator data set results in an overall prediction accuracy

of 77.2% (Tables 4-1). Inspecting the class-based prediction statistics (Tables 4-2) adds

more detail to the predictive performance. The lipid mediators data sets for the CO2 group

could be predicted with a balanced accuracy of 94%. Also the CO2+MW group had

strong predictive performance, reaching more than 89% balanced accuracy. In addition,

and not clearly observable in the heat map representation, the supervised analysis showed

that the MW group showed decent classification performance (87% balanced accuracy)

(Tables 4-2).

Similar to lipid mediators, the CO2 group showed very distinct differences in

intact lipid concentrations and formed a separate cluster (Figure 4-3a). In contrast to the

previous observation with lipid mediators, the CO2+MW, the MW and LPS group could

not be clearly separated from each other in the unsupervised inspection of the intact lipid

data, which is indicative of high intra-group variation. There was not any significant

difference in phospholipid levels upon 5 minutes of hypoxic-ischemia. For example, PI

38:4 showed no differences across all groups (Figure 4-3b). The release of non-esterified

ARA, however, caused a 535% increase in lysophposphatidylinositol 18:0

83

Table 4-1: Confusion matrix for PLS-DA calculated for lipid mediators.

CO2 CO2+MW LPS MW

CO2 23.4 0.0 0.0 0.0 CO2+MW 3.1 19.3 0.0 0.0

LPS 0.0 2.7 9.3 1.4 MW 0.3 1.3 14.0 25.3

True values in columns, predicted values in rows. Overall prediction accuracy: 77.2%. Values represent percentages of table totals obtained from repeated stratified cross-validation.

Table 4-2: Class-based prediction statistics for PLS-DA calculated for lipid meditators.

CO2 CO2+MW LPS MW

Sensitivity 88% 83% 40% 95% Specificity 100% 96% 95% 79%

Pos. Pred. Value 100% 86% 69% 62% Neg. Pred. Value 96% 95% 84% 98%

Balanced Acc. 94% 89% 67% 87%

84

CO 2

CO 2

+MW

LPS

MW

0

1000

2000

3000

PI 3

8:4

(p

mo

l/m

g o

f b

rain

tis

su

e)

B Figure 4-3. Microwave fixation inhibits ischemia-induced changes of intact lipids

CO 2

CO 2

+MW

LPS

MW

0

100

200

300

400

500

A

B B B

Ce

r 3

6; 1

:2 (p

mo

l/m

g o

f bra

in o

f tissu

e)

CO

2

CO2+

MW

LPS

MW

0

100

200

300

400

500A

B

B B

DA

G 3

8:4

(p

mo

l/mg

of b

rain

tis

su

e)

CO 2

CO 2

+MW

LPS

MW

0

500

1000

1500

2000

SM

36

:1;2

(p

mo

l/mg

of b

rain

tissu

e)

A

H

G

CO

2

CO2+

MW

LPS

MW

0

5

10

15

TA

G 5

4:6

(p

mo

l/mg

of b

rain

tissu

e)

A

BB

AB

C

E D

F

Heat map representation illustrates that CO2 asphyxiation group clusters separately

from other groups (A). Brain concentrations relative to internal standard (n=9-10, ±

SEM) of phosphatidylinositol (PI) 38:4 (B), lysophosphatidylinositol (LPI) 18:0 (C),

triacylglycerol (TAG) 54:6 (D), diacylglycerol (DAG) 38:4 (E), ceramide (Cer)

36:1;2 (F), sphingomyelin (SM) 36:1;2 (G). Bars labeled with different superscripts

identify significant differences identified by one-way ANOVA and Tukey’s post hoc

test of log-transformed concentrations (p<0.05). PLS-DA was performed to

elucidate the metabolites driving the separation. A 63.6% overall predictive accuracy

was achieved (H).

CO 2

CO 2

+MW

LPS

MW

0

200

400

600

800

1000 A

B

C C

LP

I 1

8:0

(p

mo

l/m

g o

f b

rain

tis

su

e)

85

compared to MW (Figure 4-3c). While the release of fatty acids caused no change in the

phospholipid pool (Figure 4-3b), smaller pools such as triacylglycerols, such as

triacylglycerol 54:6, were decreased in the hypoxic group compared to the MW (Figure

4-3d). Reciprocal increases in diacylglycerol, for example diacylglycerol 38:4, were

observed (Figure 4-3e).

Ischemia also increased the production of ceramides (Figure 4-3f) while other

species, such as sphingomyelin, showed no differences between groups (Figure 4-3g). An

overall prediction accuracy of 63.6% (Table 4-3) could be achieved using PLS-DA (see

Figure 4-3h showing PLS components 1 and 2). Also here, class-based prediction

statistics yielded a very high balanced accuracy for CO2 and CO2+MW (100% and 94%

respectively, Table 4-4). Unlike lipid mediators, however, the classification performance

for the MW group using intact lipids was poor. The LPS group also had poor

classification performance throughout the data sets.

To further investigate the classification outcomes, we inspected which variables

contributed most to the group separation observed. Tables 4-5 and 4-6 show the top 20

most important variables for the separation of the respective groups in descending order.

The values shown are derived from the regression coefficients of the underlying PLS-DA

model across the number of PLS components chosen. The importance values are

calculated separately for each class and have been scaled between 0 and 100 for better

interpretability. High values indicate a high contribution of the given variable for the

discrimination.

Finally, in order to elucidate the relationship between the intact lipids and

the bioactive lipids, we calculated correlation networks within the four phenotypic

86

Table 4-3: Confusion matrix for PLS-DA calculated for intact lipids.

CO2 CO2+MW LPS MW

CO2 26.8 0.0 0.0 0.0 CO2+MW 0.0 20.7 1.0 0.3

LPS 0.0 2.6 7.4 17.4 MW 0.0 0.0 14.8 9.1

True values in columns, predicted values in rows. Overall prediction accuracy: 63.9%. Values represent percentages of table totals obtained from repeated stratified cross-validation.

Table 4-4: Class-based prediction statistics for PLS-DA calculated for intact lipids.

CO2 CO2+MW LPS MW

Sensitivity 100% 89% 32% 34% Specificity 100% 98% 74% 80%

Pos. Pred. Value 100% 94% 27% 38% Neg. Pred. Value 100% 97% 78% 77%

Balanced Acc. 100% 94% 53% 57%

87

Table 4-5: Top 20 lipid mediators in PLS-DA discrimination of the four phenotypic

groups

CO2 CO2+MW LPS MW

5-oxo-ETE 7.668 100 30.452 37.257 20-HETE 5.661 57.852 31.011 32.401

14,15-DHET 4.562 27.616 18.028 19.304 TXB2 7.236 22.05 11.67 5.411

5-HETE 5.994 22.04 11.666 11.089 16-HDoHE 4.811 18.988 11.692 13.18 12-HEPE 5.727 17.199 8.106 11.99

PGE2 5.093 14.692 15.161 12.809 14-HDoHE 6.766 14.372 5.587 4.899 15-HETE 5.616 12.438 5.576 6.205

10-HDoHE 5.526 12.402 5.866 8.492 PGF2a 6.988 11.963 6.405 0

15-HEDE 4.703 11.96 6.27 7.447 6keto-F1a 6.871 11.408 7.382 6.441

PGD2 6.835 9.508 3.28 5.028 10,17-DiHDoHE 5.794 8.423 2.801 4.128

7-HDoHE 4.967 8.396 4.858 6.737 8-HDoHE* 4.978 8.328 6.639 7.465 4-HDoHE 5.074 6.877 6.995 7.955 8,9-DHET 5.1 7.498 7.551 5.833

DHET, dihydroxyeicosatrienoic acid; DiHDoHE, protectin D1; ETE, eicosatetraenoic

acid; HDoHE, hydroxydocosahexaenoic acid; HEDE, hydroxyeicosadeinoic acid; HEPE,

hydroxyeicosapentaenoic acid; HETE, hydroxyeicosatetraenoic acid, PG, prostaglandin;

TX, thromboxane

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Table 4-6: Top 20 intact lipids in PLS-DA discrimination of the four phenotypic groups

Cer, ceramide; DAG, diacylglycerol; LPI, lysophosphatidylinositol; LPC,

lysophosphatidylcholine; PC, phosphatidylcholine; TAG, triacylglycerol

CO2 CO2+MW LPS MW

LPI 22:6 10.732 100 43.711 24.95 LPI 20:4 19.007 97.5 44.252 26.79 LPI 18:1 17.623 82.48 42.161 19.09 LPC 12:1 11.03 76.38 31.595 25.55 TAG 58:8 5.295 67.45 29.944 29.44 PC 38:7 3.64 38.25 32.063 57.87 LPI 18:2 27.3 56.36 32.674 19.05 LPC 12:2 38.969 54.6 36.201 26.99

Cer 42:3;2 53.244 31.91 10.978 16.94 DAG 36:2 53.141 17.63 5.49 11.78 DAG 36:1 52.968 17.66 6.418 12.29 DAG 34:1 52.281 15.52 7.785 11.18 Cer 36:2;2 52.186 31.52 11.393 18.1 DAG 38:5 52.139 17.75 4.693 10.81 DAG 38:4 52.079 15.86 6.558 10.66 DAG 36:4 51.876 14.66 8.835 10.74 DAG 40:4 50.899 28.26 7.22 12.86 Cer 40:2;2 49.939 33.3 12.248 12.16 DAG 38:6 49.378 24.63 22.993 15.03 Cer 38:2;2 49.306 36.86 12.792 18.91

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groups. To visualize potential relationships between variables, we constructed

correlation networks. For better interpretability, we excluded edges with correlation of

less than 0.85. Furthermore, nodes with less than 3 connections were omitted from the

network. In addition, cliques of fewer than 10 members were removed leaving only big

clusters in the network. Figure 4-4 shows a correlation network for the CO2 asphyxiation

group visualized in the BioLayout Express3D software. Lipid mediators are colored in

red and are clustered almost exclusively together in the top right hand corner of the plot.

The intact lipids they share the strongest interaction with are lipids of the

lysophosphatidylethanolamine and lysophosphatidylcholine class.

Lysophposphatidylinositol and diacylglycerol formed separate unique clusters, unrelated

to the lipid mediators.

4.5. Discussion

The purpose of this study was 1) to describe the rat brain lipidome using a method

utilizing multiple mass spectrometry approaches and 2) to describe the effect of ischemia

on the rat brain lipidome by utilizing high-energy head-focus microwave fixation.

The major findings of this study were that ischemia induces an increase in the

production of bioactive mediators from lipids released from the phospholipid membrane.

Head-focused high-energy microwave fixation reduces this production, while the effects

of LPS were much smaller than the effect of ischemia.

Following ischemia, ARA is released from the phospholipid membrane in the brain as

unesterified ARA, a phenomenon known as the Bazan effect. This unesterified ARA

becomes available for metabolism into mediators. It has previously been demonstrated

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Figure 4-4. Correlation network between lipid mediators and intact lipids in the CO2

group.

Correlation analysis shows that lipid mediator (red) cluster almost exclusively together

and has strongest network connection with lysophosphatidylcholine (light blue) and

lysophosphatidylethanolamine (purple).

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that ischemia results in a 4- to 20-fold increase in PGE2 concentration in the cortex270, 274,

275. In this study, we report a similar, though much higher magnitude, increase in PGE2

production. PGE2 concentration was 522-fold higher in the CO2 group compared to the

MW group. The higher PGE2 increase in our study may be a result of longer hypoxic

periods compared to other studies270.

Similarly, CO2+MW had an increase in PGE2 of 59 fold compared the MW group.

Although the production of PGE2 in the CO2+MW group is lower than in the CO2 group,

it is still elevated compared to the MW group, suggesting that that microwave fixation

does not degrade PGE2.

Similar results are seen with the other bioactive mediators measured in this study.

The differences between the CO2 and CO2+MW groups may be explained by the

differences in ischemia time between the two groups. In the CO2+MW group, animals

were exposed to CO2 for 5 minutes prior to microwave fixation. The CO2 group was also

exposed to 5 minutes of CO2, however, ischemia continued while the head was placed on

ice for 5 minutes (in order to be consistent with the other 3 groups) and for another few

minutes in order to remove the brain and place the brain in liquid N2. It is possible that

the higher ischemia time in the CO2 group resulted in higher production of bioactive lipid

mediators258, 268.

A similar pattern has been reported for other bioactive lipid mediators such as

PGD2270, 276, thromboxane B2

270, 17-hydroxy DHA277 and arachidonyl ethanolamide267.

Results with these mediators are all in agreement with the results in this study. There

were some mediators, such as protectin D1, which were detectable in the CO2 group, but

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were below the detection limit of our equipment in the MW group. This is in agreement

with the earlier reports, which failed to detect protectin D1 following head-focused

microwave fixation277, 278. However, it should be noted that Farias and colleague did not

measure protectin D1 following 5 minutes of ischemia, which differs from the CO2 group

in this study277. The reason for this disparity is unclear. In this study, we expand on this

current list of mediators with several new mediators, including several

hydroxyeicosatetraenoic acids and hydroxy DHA, all of which show the same pattern as

the other mediators.

In order to stimulate the production of some mediators, LPS was injected

systematically 3 hours prior to microwave fixation, as described in previous studies268.

Only PGE2 was increased by LPS injection. LPS injection resulted in a 19 fold increase

in PGE2 production compared to the MW group. Despite being a significant increase

compared to the MW group, this is a much smaller effect than the ischemia effect on

PGE2 production. It is therefore possible that this effect of LPS would not be detected in

hypoxic animals due to the greater production of PGE2 and the increased variability in

concentration, although this was not tested in this study. It should be noted that no other

group received any vehicle injection, which could affect interpretation. It is not believed,

however, that vehicle injection would result in the release of inflammatory mediators.

The increase in bioactive mediators in ischemia can be explained by the Bazan

effect, where phospholipases are activated and release lipids from the phospholipid

membrane 258. To this date, the effect of microwave-fixation has yet to be reported on

intact lipids. Although generally no changes in phospholipid species were observed due

to their high concentrations, increases in lysophospholipids, such as

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lysophposphatidylinositol 18:0 were detected in the CO2 group compared to the MW

group. This is in agreement with the phospholipases increasing cleavage of ARA in

ischemic environments, resulting in higher lysophospholipid production. Due to the

smaller size of their pool, the release of fatty acids from triacylglycerols caused by

ischemia, reducing triacylglycerol concentration, was inhibited in the MW group. It had

previously shown that increasing ischemic time reduced triacylglyceride concentration258.

In parallel, this results in an increase in diacylglycerol. In agreement with this result,

diacylglycerol has previously been shown to be reduced by freezing fixation in in vitro

neuronal culture279 and when ischemia time is reduced in vivo280.

Interestingly, degradation and production could be occurring simultaneously in

hypoxic brains. It has previously been reported that while ischemic brains had 60 times

more 2-arachidonyl glycerol 30 minutes following death, exogenously infused labeled 2-

arachidonyl glycerol had decreased by approximately 99%281. This suggest that although

fatty acids are increasing through their release from the phospholipid in ischemia,

degradation of fatty acids also appears to be active at a slower rate.

It should be noted that these new lipidomic approaches of mass spectrometry have

identified novel odd chain fatty acids, which had not previously been measured with

older techniques. Targeted studies using standards for these odd chain fatty acids should

be used in the future to determine whether these fatty acids truly exists or are only

artifacts.

This study was the first to attempt to compare the effect of ischemia on the

neurolipidome to the neurolipidome of animals euthanized by microwave fixation using a

lipidomic approach. Overall, the ischemia-induced neurolipidome is clearly distinct from

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that of the microwave fixed neurolipidome. With the changes induced by ischemia, we

were able to determine which lipids are tightly related to one another. Bioactive

mediators are closely related to lysophosphatidylcholine and

lysophosphatidylethanolamine, suggesting a possible source for these mediators.

In summary, we demonstrated a systematic approach to assess the lipidome of the

rat brain. While bioactive lipids were all decreased due to microwave fixation, only

specific intact lipid pools were either increased or decreased by this fixation method.

Moreover, this effect of ischemia is much larger than that of LPS injection and this effect

is attenuated with the use of microwave-fixation. The use of microwave fixation

decreases variability in measurements, allowing for increased sensitivity in accessing

small differences between experimental groups. This study demonstrates the need to

consider the effect of ischemia when measuring lipid profile of non-microwaved brain

tissue, more specifically postmortem brain tissue. It questions the interpretation that can

be achieved with these results.

4.6. Acknowledgements

MOT holds a studentship from the Natural Sciences and Engineering Research

Council of Canada. RPB acknowledges funding from the Canadian Institutes of Health

Research (grant # 303157) and the Natural Health Science and Research Council of

Canada (grant # 482597), and holds a Canada Research Chair in Brain Lipid

Metabolism. MM and DM are supported by the Nestlé Institute of Health Sciences.

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4.7. Author contributions

MOT was responsible for sample collection. MOT and DM performed sample

preparation and lipid extraction. MOT, MM and RPB designed the study. MM generated

and interpreted the data. MM and MOT performed statistical analyses and MM

performed data modeling. MOT and MM wrote the manuscript. All the authors

contributed to writing the manuscript and approved it.

4.8. Conflict of interest statement

There is no competing financial interest

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Chapter 5: N-3 polyunsaturated fatty acids mediate small

changes in the resolution of neuroinflammation following

intracerebroventricular lipopolysaccharide injection

independent of pro-resolving lipid mediators

Marc-Olivier Trépanier, Kathryn E. Hopperton, Vanessa Giuliano, Ali Salahpour, Mojgan Masoodi, Richard P. Bazinet

Contribution: Along with RPB, I helped design the study. With KEH, I maintained and fed the mouse colony. I performed all the surgeries and collected all samples analyzed in this study. I performed most of the immunohistochemistry presented in this study, along with VG. I travelled to Lausanne to perform the lipid extraction for mass spectrometry analysis. I conducted the Y-maze test and TLDA. I performed the statistical analysis and wrote the first draft of the manuscript.

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5.1. Abstract

Resolution of inflammation in the periphery was once thought to be a passive

process, but new research now suggests it is an active process mediated by specialized

pro-resolving lipid mediators derived from omega-3 polyunsaturated fatty acids (n-3

PUFA). However, this has yet to be illustrated in neuroinflammation. The purpose of this

study was 1) to develop a self-resolving model of neuroinflammation and 2) to test

whether increasing brain docosahexaenoic acid (DHA) affects the resolution of

neuroinflammation.

C57Bl/6 mice (Experiment 1) and the fat-1 mice and their wildtype littermates,

fed either fish oil or safflower oil (Experiment 2), received lipopolysaccharide (LPS) in

the left lateral ventricle. Animals were then euthanized at various time points for

immunohistochemistry, gene expression, and lipidomic analysis. They were also tested in

the Y-Maze.

In Experiment 1, peak microglial activation was observed at 5 days post-surgery

and the resolution index was 10 days. Of the approximately 350 genes significantly

changed over the 28 days post LPS injection, 130 were uniquely changed at 3 days post

injection. While cytokine expression peaks at 24hr post injection, microglial marker

expression peaks at 3 days. No changes were observed in the phospholipid and bioactive

mediator pools. However, a few lysophospholipid species were decreased at 24hr post

surgery. LPS-treated animals did not show deficits in spontaneous alternation

performance in the Y-maze at 7 days post LPS injection.

When brain DHA is increased (Experiment 2), microglial cell density resolves

slightly faster. In terms of gene expression, only COX-2 mRNA expression is affected by

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increasing brain DHA. In conclusion, resolution of neuroinflammation appears to be

independent of specialized pro-resolving lipid mediators. Increasing brain DHA has a

small effect in this model. This model may be more appropriate for a pharmaceutical

approach.

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5.2. Introduction

Neuroinflammation is a characteristic of many neurological and psychiatric

disorders. In vivo and postmortem studies have both reported increased

neuroinflammation in Alzheimer’s disease, Parkinson’s disease, and schizophrenia116, 117.

Growing evidence is suggesting a potential causal effect of neuroinflammation in the

progression of the pathogenesis of neurological and psychiatric disorders116, 120.

The brain is an immunologically privileged tissue, blocking most peripheral

immune cells from entry121. It contains its own resident immune cell in the microglia.

Microglia survey the environment, and communicate with other glia and neurons.

Following insults or tissue damage, microglia are activated to an M1 phenotype, releasing

pro-inflammatory cytokines such as tumor necrosis (TNF)-and interleukin (IL)-1119,

123. These signals activate astrocytes to release more pro-inflammatory cytokines

including IL-1. When chronic inflammation persists, neuronal death ensues. Microglia,

however, can be also be activated by IL-4 and IL-13 to a M2 phenotype, which releases

anti-inflammatory cytokine IL-10 and growth factors such as insulin growth factor and

transforming growth factor119, 123.

Classically, it was thought that inflammation dissipated passively. It is becoming

clear, however, that the resolution of inflammation is an active process42, 282. Resolution

of inflammation in the periphery is driven by specialized pro-resolving lipid mediators

derived from the enzymatic oxygenation of polyunsaturated fatty acids (PUFA)42, 44.

Specialized pro-resolving lipid mediators are considered both anti-inflammatory and pro-

resolving. In the periphery, specialized pro-resolving lipid mediators actively return the

inflamed tissue to homeostasis by blocking neutrophil entry and activating the

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recruitment of macrophages to the tissue to repair and clear debris. While omega (n)-6

PUFA are typically considered pro-inflammatory due to the production of prostaglandins

and leukotrienes, they also produce the specialized pro-resolving mediator lipoxins.

Through the enzymatic activity of lipoxygenase, n-3 PUFA also produce specialized pro-

resolving lipid mediators including protectins, resolvins, and maresins. Due to the

differences between inflammation in the periphery and neuroinflammation, it is

unknown, however, whether resolution of neuroinflammation utilizes the same

mechanism.

In the brain, n-3 PUFA make up approximately 10% of all lipids278, 283.

Docosahexaenoic acid (DHA) is the most abundant n-3 PUFA in the brain and is

involved in regulating neuronal and glial structure, while also producing signaling

molecules. Due to its abundance and multiple functions in the brain, it is not surprising

that a link between n-3 PUFA and both neurological and psychiatric disease has been

proposed and investigated242, 284-287. Observational studies have suggested a protective

role of n-3 PUFA in multiple brain disorders, such as Alzheimer’s disease and

depression139, 288, 289. The results from clinical trials, however, are conflicting285, 290, 291

with only a few studies pointing to a protective effect242, 243, 292.

There have been several mechanisms proposed for the protective effects of n-3

PUFA in neurological and psychiatric disorders. These include anti-apoptotic,

neurotrophic, and anti-oxidative mechanisms293. Another potential mechanism of n-3

PUFA involves their anti-neuroinflammatory actions293. N-3 PUFA have anti-

inflammatory properties in a multitude of disease models including stroke, spinal cord

injury, Alzheimer’s disease and Parkinson’s disease (For review, see Chapter 2294).

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Increased brain DHA, either through dietary intervention or in the fat-1 mouse, has

decreased pro-inflammatory gene expression 24 hours following i.c.v. injection of

lipopolysaccharide (LPS). Moreover, i.c.v. injection of 17S-hydroperoxyDHA, a

precursor of protectin D1, had a more potent effect than DHA itself, suggesting that some

or all of the anti-neuroinflammatory effects of DHA may be mediated by its metabolism

to protectin D191. This is consistent with the anti-neuroinflammatory effects of protectin

D1, aspirin-triggered resolvin D1, resolvin E1, and resolvin D2 in stroke170, 241,

Parkinson’s295, traumatic brain injury212 and neuropathic pain models216, 217.

Despite the fact that animal studies have generally pointed to anti-

neuroinflammatory properties of n-3 PUFA, not much is known regarding their effects on

resolution, as most studies have evaluated only a few pro-inflammatory markers at one

time point294. It is therefore possible that the effects of n-3 PUFA may have been missed

if the wrong marker or time point was chosen.

The goal of this study was first to develop a self-resolving model of

neuroinflammation following i.c.v. LPS over 28 days utilizing microarray and lipidomic

approaches (Experiment 1). Once developed, the second goal of this study was to

determine whether resolution of neuroinflammation is influenced by increasing brain

DHA (Experiment 2).

5.3. Methods

The present experiments were conducted in accordance with the standards of the

Canadian Council on Animal Care and were approved by the Animal Care Committee of

the Faculty of Medicine of the University of Toronto. Animals were housed 1-4 per cage

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in our animal facility where temperature (21C) and light (14/10 light/dark cycle) were

controlled. Food and water were available ad libitum.

5.3.1. Diets

Animals were fed one of 3 diets, 1) rodent chow (Teklad Global Diets, Envigo,

Madison, WI), 2) 10% safflower oil (D04092701, Research diets, New Brunswick, NJ),

or 3) 8% safflower and 2% menhaden oil (D04092702, Research Diets, New Brunswick,

NJ).

Diet fatty acid composition was confirmed in triplicate by gas chromatography

flame ionization detection and is presented in Table 5-1. The rodent chow contained

18.9% oleic acid, 56.4% linoleic acid and 6.5% -linolenic acid as a % of total fatty

acids. Eicosapentaenoic acid (EPA) was not detected by gas chromatography flame

ionization detection in the rodent chow diet, while a trace amount of DHA was detected.

Gas chromatography with mass spectrometry, however, was not able to detect any DHA

in the rodent chow diet.

The safflower diet contained 13.3% oleic acid, 67.3% linoleic acid and 0.2% -

linolenic acid as a percent of total fatty acids. Similar to rodent chow, a trace amount of

DHA was measured by gas chromatography flame ionization detection. Gas

chromatography with mass spectrometry confirmed that the DHA percent composition

was 0.01%. The trace amount of EPA is also believed to be artifact, although it was not

confirmed by gas chromatography with mass spectrometry.

The fish oil diet was composed of 5.0% oleic acid, 58.8% linoleic acid, and 0.43%

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Table 5-1: Percent of total fatty acids of the 3 experimental diets.

Fish oil

Safflower oil Chow

C12:0 0.01 0.01 0.00

C14:0 1.97 0.29 0.10

C14:1 0.06 0.00 4.37

C16:0 10.92 8.56 8.88

C16:1 2.16 0.14 0.13

C18:0 5.01 6.21 2.68

C18:1 n-9 14.64 13.35 18.93

C18:1 n-7 0.64 1.55 0.68

C18:2 n-6 58.75 67.25 56.44

C18:3 n-6 0.10 0.01 0.17

C18:3 n-3 0.43 0.20 6.46

C20:0 0.39 0.44 0.24

C20:1 n-9 0.55 0.33 0.33

C20:2 n-6 0.20 0.13 0.16

C20:3 n-6 0.03 0.00 0.01

C20:4 n-6 0.11 0.00 0.00

C20:3 n-3 0.03 0.00 0.00

C20:5 n-3 1.51 0.12 0.00

C22:0 0.36 0.42 0.22

C22:1 n-9 0.28 0.30 0.09

C22:5 n-6 0.05 0.00 0.00

C22:5 n-3 0.22 0.01 0.00

C22:6 n-3* 1.37 0.01 N.D

C24:1 n-9 0.21 0.17 0.00

*composition was confirmed by gas chromatography with mass spectrometry

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-linolenic acid as a percent of total fatty acids. It was composed of 1.5% and 1.4%

EPA and DHA respectively.

5.3.2. Subjects

C57Bl/6 male mice were ordered at 10 weeks of age from Charles River (Saint

Constant, Qc). Animals were fed rodent chow and allowed to acclimatize for 2 weeks.

Fat-1 male mice (C57Bl/6 X C3H background)102 were graciously donated by Dr. David

Ma (University of Guelph) for breeding purposes. Subject mice were obtained by mating

male fat-1 mice with C57Bl/6 females from Charles River (Saint Constant, Qc, Canada).

Females were fed safflower oil diet two weeks prior to being placed in harems. Pups were

genotyped at 2-3 weeks of age prior to weaning as described before91. F1 male progeny

were used as experimental subjects. At 3 weeks of age, wildtype pups were weaned and

either maintained on safflower diet or placed on the fish oil diet. Fat-1 pups were placed

only on safflower diet as previous work in our laboratory has shown that fish oil does not

further increase brain DHA104.

5.3.3. Intracerebroventricular LPS injections

At 12 weeks of age, subjects were anesthetized by isofluorane (3% induction, 2%

maintenance). The head was secured in a stereotaxic apparatus (Stoelting, Wood Dale,

IL, USA) and 150 l of 0.03% sensorcaine was injected s.c. at the incision site.

Following the incision and exposing the skull, a small hole was drilled (-1.0 mm

medial/lateral, -0.5 mm anterior/posterior). A 33g needle was lowered into the left

105

ventricle (-2.4 mm dorsal/ventral) and LPS (5 g in 5 l, E.coli serotype 055:B5, Sigma

Aldrich, St-Louis, MO, USA) was infused over 5 minutes by electronic pump (Stoelting,

Wood Dale, IL, USA). The needle remained in the left ventricle for 25 minutes post

infusion to ensure LPS diffused within the ventricle. The needle was removed slowly to

avoid infusate backflow. The skull was closed with bone wax and sutured. Mice were

euthanized at 4hr, 8hr, 12hr, 1, 2, 3, 5, 7, 14, and 28 days following surgeries. Non-

surgery animals were used throughout the study as controls. The accuracy of the LPS

injection was sporadically checked with Evan’s blue injection.

5.3.4. Immunohistochemistry

For immunohistochemistry, mice were anesthetized by i.p. injection of Avertin

(20 ml/g, 250 mg 2,2,2 tribromoethanol, 0.5 ml 2-methyl-2-butanol, 20 ml dH2O, Sigma

Aldrich, St-Louis, MO, USA) and were euthanized by transcardiac perfusion at 4hr, 12hr,

1, 3, 5, 7, 14 and 28 days (n = 6-10 per group). Approximately 12 ml phosphate buffered

saline was infused by peristaltic pump (GE Healthcare, Mississauga, ON, Canada)

followed by 18 ml of 4% paraformaldehyde. Brains were post-fixed overnight in 4%

paraformaldehyde and dehydrated in 30% sucrose on the following day. Brains remained

in sucrose until frozen in cryostat sectioning medium prior to slicing. Brains were

sectioned in 40 m slices in a Leica cryostat (CM 1510S, Concord, ON)

Anti-ionized calcium-binding adapter molecule (Iba) 1 was utilized as a microglia

marker. Slices were quenched with 0.5% sodium borohydride and washed with 3

phosphate-buffered saline washes. Slices were then blocked for 2 hr in a blocking

solution (10% normal goat serum, 0.75% bovine serum albumin, 0.1% Triton-x). Anti-

106

Iba (1:2000, Wako Chemicals, Richmond, VA, USA) was applied overnight. Slices were

labeled with Alexa Fluor 680 (1:2000, Life Technologies, Burlington, ON, Canada) for 1

hr the next day. Slices were imaged on a LI-COR Odyssey (settings: Resolution, 21;

Quality, Highest; Intensity, 4; Lincoln, NE). Optical density of images was recorded

using ImageJ (version 1.46R. Bethesda, MD). Differences from baseline were calculated

by comparing subjects receiving LPS to non-surgery animals analyzed on the same day to

avoid methodological variation. Cell counting was conducted using an epi-fluorescence

microscopy in order to see possible regional differences. Iba1 reactive cells (secondary

Alexa Fluor 568, Life Technologies, Burlington, ON, Canada) were counted as described

previously296 using Nikon Elements software (NIS-Elements Basic Research, version

3.10) at 10X magnification. Using automatic exposure, the fluorescent intensity

thresholds limits were automatically determined and were set to fall within the linear

range. Counts were completed by a blind observer.

5.3.5. Genetic expression analysis

For gene expression analysis, animals were euthanized by CO2 asphyxiation at 8

hr, 1, 2, 3, 7, 14 and 28 days following LPS surgery (n=8 per group). The left

hippocampus was dissected and frozen by liquid N2.

For the microarray analysis for Experiment 1, RNA was extracted using an

Agencourt RNAdvance Tissue Kit (Beckman Coulter, Inc.). The quality of total RNA

was checked using the BioAnalyzer 2100 with Total RNA Nano kit (Agilent

Technologies, Santa Clara, CA). Quantification was done using the Quant-iT RiboGreen

RNA Assay Kit assay (Life Technologies, Inc.). 300ng of RNA was reversed transcribed

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and 750 ng of cRNA was loaded unto a MouseRef-8 v2.0 Expression BeadChip

(Illumina, San Diego, CA), which contains approximately 25,600 novel transcripts and

measures over 19,100 separate genes.

For the Taqman Low Density Array analysis in Experiment 2, total RNA was

extracted using Trizol (Thermo Fisher Scientific, Waltham, MA) following the

manufacturer’s instructions. Samples were stored at -80C. RNA quantity and quality

(OD230/260, OD260/280) were measured by a Nanodrop 1000 Spectrophotometer

(Nanodrop Technologies, Wilmington, DE, USA). Random samples were sent for

analysis by BioAnalyzer 2100 to confirm RNA quality. RNA was reverse transcribed

using a High Capacity cDNA Reverse Transcription kit (Thermo Fisher Scientific,

Waltham, MA). 150 ng of cDNA in 50 l of RNase free water was combined with 50 l

Taqman Fast Advance Mastermix (Thermo Fisher Scientific, Waltham, MA) in Taqman

Low Density Array wells as instructed by the manufacturer’s instructions (Thermo Fisher

Scientific, Waltham, MA). Plates were custom designed with 45 separate assays

including, microglial markers Iba1 (assay ID Mm00479862_g1), translocator protein

(TSPO, assay ID Mm00437828_m1), Cluster of Differentiation 86 (CD86, assay ID

Mm00444543_m1), CD68 (assay ID Mm03047343_m1), arginase 1 (arg1,

Mm00475988_m1), triggering receptor on myeloid cell 2 (Trem2, assay ID

Mm04209424_g1), CD11b (Mm00434455_m1), and CD206 (Mm01329362_m1),

cytokines and chemokines IL-10 (assay ID Mm01288386_m1), IL-1 (assay ID

Mm00434228_m1), TNF (assay ID Mm00443258_m1), chemokine (c-c motif) ligand 5

(CCL5, assay ID Mm01302427_m1), and chemokine (c-x-c motif) ligand 1 (CXCL1,

assay ID Mm04207460_m1), astrocytic markers glial fibrillary acidic protein (GFAP,

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assay ID Mm01253033_m1) and S100 calcium-binding protein b (S100b, assay ID

Mm00485897_m1), arachidonic cascade markers cyclooxygenase-2 (COX-2, assay ID

Mm00478374_m1), prostaglandin E synthase (PTGES, assay ID Mm00452105_m1),

cytosolic phospholipase A2 (cPLA2, assay ID Mm00447040_m1), nuclear factor kappa-

light-chain-enhancer of activated b cell (NF-B) pathway markers NFKB1 (assay ID

Mm00476361_m1), transcription factor p65 (Rela, Mm00501346_m1), and NF-B

inhibitor, alpha (IB, assay ID Mm00477798_m1), fatty acid and specialized pro-

resolving mediator receptors free fatty acid receptor 4 (GPR120, assay ID

Mm00725193_m1), chemokine like receptor 1 (ChemR23, Mm02619757_s1), and

peroxisome proliferator-activated receptor gamma (PPARg, assay ID,

Mm00440940_m1), fatty acid metabolising enzymes cytochrome p450 1b1 (cyp1b1,

assay ID Mm00487229_m1), 5-lipoxygenase (ALOX5, assay ID Mm01182747_m1),

ALOX12 (assay ID Mm00545833_m1), ALOX15 (assay ID Mm00507789_m1), BBB

marker matrix metallopeptidase 9 (MMP9, assay ID Mm00442991_m1) and other makers

identified in the microarray of Experiment 1 including S100a8 (assay ID

Mm00496696_g1), S100a9 (assay ID Mm00656925_m1), intracellular adhesion

molecule (ICAM-1, ID Mm00516023_m1), chitinase like 1 (Chil1, assay ID

Mm00801477_m1), vascular endothelial growth factor A (VEGFA assay ID

Mm00437306_m1), lipocalin 2 (LCN2, assay ID Mm01324470_m1), serum amyloid A3

(SAA3, assay ID Mm00441203_m1), interferon-induced guanylate-binding protein 2

(GBP2, assay ID Mm00494576_g1), interferon-induced protein with tetratricopeptide

repeats 3 (IFIT3, assay ID Mm01704846_s1), interferon-induced transmembrane protein

3 (IFITM3, assay ID Mm00847057_s1), Fas (assay ID Mm01204974_m1), 2’-5’

109

oligoadenylate synthase-like 2 (OASL2, assay ID Mm00496187_m1), tissue inhibitor of

metalloproteinase (TIMP1, assay ID Mm01341361_m1), serine peptidase inhibitor clade

A, member 3N (SERPINA3N, assay ID Mm00776439_m1), lysozyme 1 (Lyz1, assay ID

Mm00657323_m1), and inducible nitric oxide synthase 2 (NOS2, assay ID

Mm00440502_m1). Plates were analyzed on a ViiA 7 real time PCR machine (Thermo

Fisher Scientific, Waltham, MA).

5.3.6. Lipidomic analysis

To measure lipid changes following i.c.v. LPS, we utilized our lipidomic

approach developed in Chapter 4 in order to eliminate the ischemia-induced changes to

the neurolipidome. Following LPS surgery, animals were euthanized at 1, 3, 7, 14, and 28

days post surgery (n = 6 per group). Animals were gently inserted in the mouse restrainer

and placed inside the microwave (Cober Electronics Inc., Norwalk, CT, model S15P

Vivostat) where a single high-energy microwave beam was focused directly on top of the

skull (approximately 1,900 J, 0.5 kW, 2,450 MHz). Brains were quickly excised and the

left hippocampus was dissected from the remainder of the brain. The left hippocampus

was flash frozen by liquid N2 and stored at -80C until analysis.

5.3.7. Bioactive mediator extraction

The whole left hippocampus (approximately 12 mg of tissue) was homogenized in

1 ml of 15% methanol by Tissue Lyser (Qiagen AG, Switzerland) at a speed of 25 Hertz

for 2.5 min. 100 l of the homogenate was collected for intact lipid analysis.

110

The remaining homogenate was used for bioactive mediator analysis using a

method similar to Chapter 4. 100 l of 100% methanol was added to the remaining

homogenate and spun at approximately 25,000 g (5430 R centrifuge, FA-45-24-11-HS

rotor) (Eppendorf AG, Hamburg, Germany) for 5 min at 4C. Supernatant was removed

into new glass tubes on ice. One ml of 15% methanol was added to the pellet and

homogenized by Tissue Lyser (25 Hz, 2.5 min). The homogenate was spun (25,000g, 5

min, 4C.) and supernatant was added to the glass tube. One ml of 15% methanol was

used to make a final volume of 3 ml.

Extraction of lipid mediators from the brain tissue was performed according to a

previously published protocol254 with slight modifications outlined as follows: internal

standards PGB2-d4 (40 ng), 12-hydroxyeicosatetraenoic acid-d8 and arachidonyl

ethanolamide-d8 (Cayman Chemicals, Ann Arbor, MI, USA) were added to the

homogenized brain in 15% (v/v) methanol in water. The cartridges (Strata-X 33 u

Polymeric Reversed phase 60 mg /3 ml) were washed with methanol (3 ml) followed by

water (3 ml) prior to loading the homogenate (3 ml). The cartridges were then washed

with 15% methanol in water (3 ml) and lipid mediators were eluted in methanol (3 ml)

and collected in glass tubes. The organic solvent was evaporated using a fine stream of

nitrogen and the remaining residue was re-dissolved in ethanol (100 μl) and stored at –

20ºC prior to analysis.

5.3.8. Extraction of intact lipids from the brain

The remaining 100 l of the homogenate used for intact lipid analysis was further

diluted with 160 l of ammonium bicarbonate buffer using a Hamilton Robot and 810 l

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of MTBE /methanol (7/2 v/v) containing internal standard which was added to this

mixture. The internal standard mixture contained: lysophasphatidylglycerol 17:1,

lysophosphatidic acid 17:0, phosphatidylcholine 17:0/17:0, phosphatidylserine 17:0/17:0,

phosphatidylglycerol 17:0/17:0, phosphatidic acid 17:0/17:0, lysophposphatidylinositol

13:0, lysophosphatidylserine 13:0, lysophosphatidylcholine 12:0,

lysophosphatidylethanolamine, cholesteryl D6, diacylglycerol 17:0/17:0, triacylglycerol

17:0/17:0/17:0, ceramide 18:1;2/17:0, sphingomyelin 18:1;2/ 12:0,

phosphatidylethanolamine 17:0/17:0, cholesteryl ester 20:0, phosphatidylinositol

16:0/16:0. The solution was mixed at 700 rpm, 15 min at 4°C using a ThermoMixer C

(Eppendorf AG, Hamburg, Germany) and then centrifuged at 3,000 rcf for 5 min. 100 l

of the organic phase was transferred to a 96-well plate, and dried in a speed vacuum

concentrator. Lipid extract was reconstituted in 40 µL of 7.5 mM ammonium acetate in

chloroform/methanol/propanol (1:2:4, V/V/V). All liquid handling steps were performed

using a Hamilton STAR robotic platform with the Anti Droplet Control feature for

organic solvents pipetting as described previously271.

5.3.9. Mass spectrometry analysis

Lipidomic analysis of intact lipids was performed using a QExactive mass

spectrometer (Thermo Fisher Scientific) equipped with a TriVersa NanoMate ion source

(Advion Biosciences) as described previously271. The data were acquired in both positive

and negative mode using resolving power of 140,000 in full scan and 17,500 in tandem

mass spectrometry mode. Scan mass charge ratio (m/z) range from 200 to 1,000.

112

Lipidomics analysis of bioactive lipid mediators was performed on an LTQ Elite

(Thermo Scientific) linear ion trap-orbitrap mass spectrometer using a heated

electrospray ionization source in both negative and positive ionization mode. Capillary

and source heater temperatures were set to 325°C and 50°C, respectively, and spray

voltage was adjusted to 4,000 V. A resolving power of 120,000 was used in full scan and

1,500 in tandem mass spectrometry mode. Scan m/z ranges of 150 to 500 (mass

spectrometry) and 50 to 500 (tandem mass spectrometry) were used.

5.3.10. Total lipid extraction

For lipid analysis, total lipids were extracted from the rest of brain (from brains

used for gene expression analysis) into 6 ml of chloroform / methanol (2:1 v/v), using

1.75 ml of 0.88% KCl to separate the aqueous phase. Non-esterified heptadecanoic acid

(Nu Chek Prep, Elysian, MN) in hexane was added as an internal standard. Brains were

homogenized by glass homogenizer. This was followed by a wash with 4 ml of

chloroform. The total lipid extract was then dried under nitrogen and reconstituted in 4 ml

of hexane.

Ten percent of total lipids were then methylated in 14% methanolic BF3 (2 ml)

and hexane (2 ml) at 100°C for 1 hour. The samples were allowed to cool at room

temperature for 10 minutes and then centrifuged at 1460 rpm for 10 minutes following

the addition of deionized water (2 ml). The upper hexane layer was extracted, dried under

nitrogen and reconstituted in 1 ml of hexane

113

5.3.11. Fatty acid methyl ester analysis by gas-chromatography for Experiment 2

Fatty acid methyl esters were analyzed on a Varian-430 gas chromatograph

(Varian, Lake Forest, CA, USA) equipped with an Agilent capillary column (DB-23; 30

m x 0.25 mm i.d. x 0.25 µm film thickness, Santa Clara, Ca). One μl of fatty acid methyl

esters was injected in splitless mode. The carrier gas was helium, set to a constant flow

rate of 0.7 ml/min. The injector and detector ports were set at 250oC. Fatty acid methyl

esters were eluted using a temperature program set initially at 50oC for 2 minutes,

followed by a ramp-up at 20oC/min to 170oC, a hold at 170oC for 1 minute, and an

increase of 3oC/min to 212oC and a hold at 212oC for 5 minutes. Peaks were confirmed

by identifying the retention times of authentic fatty acid methyl ester standards of known

composition (Nu-Chek Prep, Elysian, MN). Fatty acid concentrations (nmol/g of brain

tissue) were calculated by proportional comparisons of the gas chromatography peak

areas with that of the heptadecanoic acid internal standard.

5.3.12. Y-maze

Seven days following surgery on mice naïve to the test (n=19), working memory

was measured using a standard Y-maze. Non-surgery mice served as controls (n=18). The

Y-maze consisted of 3 arms of the same length meeting at 120 at the centre

(38X7.6X12.7 cm3, San Diego Instruments, San Diego, CA). Each arm was defined as a

zone (Zone A, B or C), from the end of the arm up to 5 cm from the centre of the maze.

Subjects were introduced in zone A and were allowed to navigate for 8 minutes.

Movement was recorded using the video-based tracking software Biobserve Viewer2.

Spontaneous alternations were recorded when the subject entered each arm of the maze

114

consecutively before entering an arm previously entered (Either ABC, ACB and CAB).

The spontaneous alternations performance was calculated by the following equation:

total spontaneous alternation/(total arm entries -2)X100

5.3.13. Statistics

Results are expressed as mean standard error of the mean (SEM). For the

immunohistochemistry, differences between groups were measured by one-way ANOVA

(Experiment 1) and two-way ANOVA (Experiment 2), with Tukey’s post hoc analysis.

Modified from the definition by Serhan et al.54, the resolution index (Ri) was defined as

the time between the time of maximal microglial activation to the time of 50% maximal

inflammation of the untreated group (WT safflower fed mice, WTSO). Linear regression

from the maximal inflammation to the return to baseline was performed and the slope and

x-intercepts were calculated as further resolution indices. For the microarray analysis, a

one-way ANOVA was performed on Log2 transformed, quantile normalized data,

followed by a Benjamini-Hochberg correction with a cutoff of 0.01 to identify the

number of genes significantly expressed differently compared to non-surgery controls.

Specific pro-inflammatory and lipid metabolism genes of interest were selected for

analysis by one-way ANOVA and Tukey’s post hoc analysis to evaluate the time course

of their expression. Differences between time points for different lipid species were

evaluated by one-way ANOVA and Tukey’s post hoc analysis. The difference between

the 2 groups in the Y-maze was analyzed by Student’s t-test. A two-way ANOVA was

utilized to detect any differences between treatment groups and time in respect to delta

CT measured by Taqman low-density array. No differences in analysis were observed

115

between the three reference genes (PGK1, beta-actin, and 18S). Data were presented as

fold change of baseline using PGK1 as the reference gene.

5.4. Results

5.4.1. Experiment 1

5.4.1.1. Microglial activation peaked by 5 days and resolved by 21 days, independent

of neutrophil and macrophage infiltration

In order to define resolution of neuroinflammation, C57Bl/6 mice were

euthanized at various time points following i.c.v. LPS surgery. LPS was directly injected

in the left lateral ventricle in order to minimize systemic inflammation created by the

injection of LPS in the periphery.

We observed an initial increase in Iba1 labeling by immunohistochemistry at 24

hours following LPS injection. Microglia labeling continued to increase up to 5 days

(Tmax) and was reduced by half (T50) at day 15 (Figure 5-1A-E). In order to define

resolution, the Ri was calculated to be 10 days. We also calculated the slope of the fitted

line from the maximal point (Day 5) to the return to baseline (Day 21). The slope was

calculated to be -0.12 Fold change/day, while the x-intercept was calculated to be 28.24

days (Figure 5-1A insert).

116

Figure 5-1. Time course of Iba1 optical density in the hippocampus in the C57Bl/6 mouse

following i.c.v. LPS.

Maximal microglial activation was found at day 5. Microglial activation was reduced by half at day 15, and the resolution index was calculated to be 10 (n=6-10, SEM) (A). Examples of Iba1 labeling as measured by LI-COR imaging representing non-surgery (B), 3 days post surgery (C), 7 days post surgery (D), and 28 post surgery animals (E) are shown above. Linear regression from time of maximal optical density to return to baseline (insert) illustrates an alternative resolution index.

0 10 20 300

1

2

3

4

Days

Fo

ld C

ha

ng

e F

rom

Ba

se

line

0 10 20 300

1

2

3

4

Days

Fo

ld C

ha

ng

e F

rom

Ba

se

lin

e

A

B

Slope = -0.12 x-intercept = 28.24

Tmax = 5d

T50= 15d

Ri = 10d

C D E

117

Since Iba1 labels both microglia and infiltrating macrophages, CD45, which is

only found on macrophages, was used to determine whether the labeling observed was

due to microglia or macrophages. No CD45 labeling was observed (data not shown),

suggesting that Iba1 is reporting only microglia (Figure 5-1). No myeloperoxidase

labeling, a neutrophil marker, was observed throughout the time course (data not shown).

5.4.1.2. Gene expression of various neuroinflammatory markers have different time

courses of expression following LPS injection

In order to evaluate which genes change following i.c.v. LPS, hippocampi were

collected at 1, 3, 7, 14 and 28 days post LPS injection and analyzed by microarray.

Following a Benjamini-Hochberg correction for false discovery, there were 106 genes

significantly upregulated and 25 down regulated compared to non-surgery controls at 1

day following LPS injection (p<0.01). Fold changes of the top 20 genes are presented in

Table 5-2. The highest fold changes compared to non-surgery controls in gene expression

were present at 1 day following surgery, with lipocalin 2 (LCN2) and serum amyloid A3

(SAA3) being 33 and 22 fold higher respectively (Table 5-2). The expressions of these 2

genes also exhibited the highest fold change at 3 days following surgery, however fold

change compared to baseline dropped to 5.9 (SAA3) and 5.4 (LCN2) (Table 5-2).

118

Table 5-2. Top 20 fold change in gene expression at each time point following LPS injection

24 hr 3 days 7 days 14 days 28 days

Gene Fold Change Gene Fold Change Gene Fold Change Gene Fold Change Gene Fold Change

Lcn2 33.6 Saa3 5.9 Lyz 2.2 Kcnk6 1.17 Pigz 1.17

Saa3 22.4 Lcn2 5.5 Saa3 2.0 Cd86 1.10 Abi3 1.15

S100a8 14.1 Lyz 4.2 C1qb 1.5 Ralb 1.09 Ass1 1.14

Timp1 9.8 C3 3.6 C1qc 1.4 Plekhf2 1.08 Fbxo2 1.12

Ifitm3 7.0 Lyz2 2.8 Ly86 1.4 Slc7a7 1.06 Rpp25 1.11

S100a9 6.5 Cd52 2.8 Cldn5 1.3 Cops3 1.05 St3gal6 1.11

Gbp2 5.9 Ifi27 2.6 Ctsh 1.3 Tmpo 1.05 Pacsin3 1.11

Serpina3n 4.7 Ifitm3 2.2 Tgfbr2 1.3 Galnt3 1.03 Snapin 1.11

C3 4.6 Lgals3bp 2.2 Itgb5 1.2 Vegfb 1.10

Ccl5 4.4 C1qc 2.1 Nnat 1.2 Dolk 1.09

Cxcl1 4.3 C1qb 2.1 Lag3 1.2 Cyb5r3 1.09

Ms4a6d 4.2 B2m 2.0 P2ry6 1.2 Arrb1 1.09

Ifit3 3.8 Chi3l1 2.0 Grn 1.2 Dab1 1.08

Cp 3.7 S100a8 2.0 Trem2 1.2 Cart 1.08

Anxa2 3.3 B2m 2.0 Abi3 1.2 Hipk2 1.07

Gfap 3.2 C4b 1.9 Klhl6 1.2 G0s2 1.07

Gpr84 3.2 Fcer1g 1.9 Sla 1.2 Ppfia3 1.07

Ch25h 3.1 Ccl5 1.9 Casp1 1.2 Jak2 1.06

Oasl2 3.1 Ctsh 1.9 Pld4 1.2 Micall2 1.06

Ly6a 3.1 Ly86 1.8 Rps6ka1 1.2 Tmpo 1.06

119

Despite not having the biggest fold changes, 3 days post surgeries had the most affected

genes, with 229 genes being significantly up regulated and 24 being downregulated. Of

those 253 significantly different genes, only 50 overlapped with the 24 hr post surgery

group. The number of differently expressed genes decreased following 3 days, and the

genes with the largest fold changes for 7 days, 14 days and 28 days are presented in Table

5-2 respectively.

Specific pro-inflammatory genes were chosen to be evaluated. Similar to the

immunohistochemistry results, various activated microglial markers were significantly

elevated at 1, 3 and 7 days post LPS injection (Figure 5-2). While translocator protein 18

kDa and CD11b expressions were only elevated at 24 hr following surgery (Figure 5-2A

and B), Iba1, CD68 and CD86 expressions were still elevated at 3 and 7 days (Figure 5-

2C, D, and E).

We also attempted to map the time course of “M2” microglia markers. Both Ym1

and Arg1 gene expressions were elevated 24 hr following surgery (Figure 5-3A and B).

While not being elevated at 24 hr, CD206 gene expression was significantly increased at

3 days and returned to baseline at 7 days (Figure 5-3C). Trem2, another M2 microglia

marker, gene expression was decreased at 24 hr, while being elevated at both 3 and 7

days compared to non-surgery controls (Figure 5-3D).

Since peripheral macrophages also express Iba1, we wanted to measure CD45

expression, which is only present on macrophages. Gene expression of CD45 did not

significantly change across time points following LPS injection (Figure 5-4A).

Neutrophils also have the potential of infiltrating the brain following brain insult241.

120

Figure 5-2. Hippocampal microglial

M1 markers’ response to i.c.v. LPS

over time.

mRNA expression (n=8, SEM) of CD11b (A), TSPO (B), Iba1(C), CD68(D) and CD86(E) are increased over time and return to baseline by 28 days. Significant differences compared to baseline measured by one-way ANOVA and Tukey’s post hoc test are represented by * (p<0.05)

CD86

0 1 3 7 14 28

6.5

7.0

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Iba1

0 1 3 7 14 28

6.5

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7.5

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8.5

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Days

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* **

TSPO

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6.5

7.0

7.5

8.0

8.5

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*

CD11b

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CD68

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121

Figure 5-3. Hippocampal microglial M2 markers’ response to i.c.v. LPS over time.

mRNA expression (n =8, SEM) of Ym1(A), Arg1(B), CD206(C), and Trem2(D) are increased over time and return to baseline by 28 days. Significant differences compared to baseline measured by one-way ANOVA and Tukey’s post hoc test are represented by * (p<0.05)

Ym1

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Trem2

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*

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Arg1

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122

Figure 5-4. Hippocampal mRNA expression of infiltrating cell markers following i.c.v.

LPS over time.

mRNA expression (n=8, SEM) of the macrophage marker CD45 (A), and neutrophil markers Ly6g6c(B), and MPO(C) are unchanged at any time point following LPS injection by one-way ANOVA.

Ly6g6c

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Expression of neutrophil markers myeloperoxidase and Ly6g6c did not change at any

time following LPS injection (Figure 5-4B and C).

The astrocytic marker GFAP was significantly elevated at 1 and 3 days (Figure 5-

5A). Another astrocytic marker, S100b, however, did not significantly change (Figure 5-

5B).

We were also interested in the time course of cytokines following LPS injection.

IL-1 and TNF- gene expression peaked at 24 hr post LPS injection and returned to

baseline by 3 days post surgery (Figure 5-6A and B). On the other hand, IL-6 gene

expression was unchanged at any time point following LPS injection (Figure 5-6C). Anti-

inflammatory cytokine IL-10 gene expression increased 24 hr following LPS and was

back to baseline at 14 days post surgery (Figure 5-6D). IL-13 expression, another

cytokine with anti-inflammatory properties, remained unchanged following surgery

(Figure 5-6E).

Since LPS activates the Toll-like receptor 4, which activates the NF-B pathway,

several members of the NF-B pathway were investigated. Gene expression for NFkB1,

IkBa, Rela and Relb was elevated at 24hr post LPS injection for all of these genes and

had returned to baseline at 3 days (Figure 5-7).

The arachidonic cascade has been shown to be affected by LPS-induced

neuroinflammation. While gene expression of prostaglandin E synthase 1 was increased

at 24 hr (Figure 5-8A), gene expression for prostaglandin E synthase 3, calcium

independent phospholipase A2 and COX-2 remained unchanged following LPS

administration (Figure 5-8B, C, D).

124

Figure 5-5. Hippocampal mRNA expression of astrocytic markers following i.c.v. LPS

over time.

mRNA expression (n=8, SEM) of GFAP (A) increased over time and returned to baseline by 28 days while S100b (B) mRNA was unchanged. Significant differences compared to baseline measured by one-way ANOVA and Tukey’s post hoc test are represented by * (p<0.05)

GFAP

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A S100b

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125

Figure 5-6. Hippocampal cytokine

mRNA response to i.c.v. LPS over

time

mRNA expression (n=8, SEM) of

pro-inflammatory cytokines IL-1

(A) and TNF- (B) was increased

at 24hr following surgery. On the

other hand, IL-6 (C) was

unchanged throughout the 28 days.

IL-10 (D), an anti-inflammatory

cytokine, expression was elevated

up to 7 days post surgery while IL-

13 (E) was unchanged. Significant

differences compared to baseline

as measured by one-way ANOVA

and Tukey’s post hoc test are

represented by * (p<0.05)

TNF-a

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Figure 5-7. Hippocampal NF-B pathways mRNA markers’ response to i.c.v. LPS over

time.

mRNA expression (n=8, SEM) of NFB1(A), IB(B), Rela(C) and Relb(D) was elevated 24 hr following LPS and returned to baseline by 3 days. Significant differences compared to baseline measured by one-way ANOVA and Tukey’s post hoc test are represented by * (p<0.05).

Relb

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Rela

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127

Figure 5-8. Hippocampal arachidonic cascade markers’ response to i.c.v. LPS over time.

mRNA expression (n-8, SEM) of PTGES(A) was elevated 24 hr following LPS and returned to baseline by 3 days post injection. PTGES3 (B) iPLA2 (C) and COX-2

mRNA expression were unchanged throughout the 28 days following surgery. Significant

differences compared to baseline measured by one-way ANOVA and Tukey’s post hoc

test are represented by * (p<0.05).

PTGES1

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5.4.1.3. Neuroinflammation alters some intact lipid species, but does not affect the

production of bioactive mediators

With our lipidomic approach, no pro-resolving lipid mediators were detected at

any time point following LPS injection in C57Bl/6 mice. There were 207 intact lipid

species that were detected. LPS injection did not affect many lipid species. There were,

however, a few significant changes. Lysophosphatidic acid 20:4 was decreased 24 hr

following surgery and returned to baseline at 3 days (Figure 5-9A). Similarly,

lysophosphatidylethanolamine 18:1 concentration was decreased at 24 hr compared to

baseline (Figure 5-9B). Interestingly, although not significant, phosphatidic acid18:1/18:1

and phosphatidic acid 18:1/16 concentrations were increased at 24 hr post surgery

compared to baseline (Figure 5-9C and D). Similarly, triacylglycerol 52:2 concentration

was elevated 28 days after i.c.v. LPS injection (Figure 5-9E), with similar non-significant

increases of triacylglycerol 54:6 observed.

5.4.1.4. Neuroinflammation does not affect cognitive abilities in the Y-maze

Seven days following LPS injection, mice exhibited a 56% spontaneous

alternation performance compared to the 62% of non-surgery mice. This difference,

however, was not statistically different (p>0.05) (Figure 5-10).

5.4.2. Experiment 2

5.4.2.1. The fat-1 gene and fish oil diet increases brain DHA

To confirm phenotypic changes due to dietary treatment or the presence of the fat-

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Figure 5-9. Hippocampal intact lipid concentrations following i.c.v. LPS over time. A significant overall effect was detected by one-way ANOVA for on the concentration (n=6, SEM) of lysophosphatidic acid (LPA) 20:4 (A) and lysophosphatidylethanolamine (LPE) 18:1 (B) following LPS and returned to baseline by 3 days. Conversely a trend towards an overall significance was detected for phosphatidic acid (PA) 18:1/16:0 (C) and 18:1/18:1 (D). One-way ANOVA followed by Tukey’s post hoc test found a significant increase in triacylglycerol (TAG) 52:2 at 28 days post surgery. Significant differences compared to baseline are represented by * (p<0.05)

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Figure 5-10. Spontaneous alternation performance in the Y-maze 7 days following i.c.v.

LPS injection.

Following i.c.v. LPS, C57Bl/6 mice animals were allowed to recover for 7 days and working memory was tested in the Y-maze (n=19). Non-surgery mice served as control (n=18). LPS injection did not statistically alter (as measured by Student’s t-test) spontaneous alternation performance % (SEM) in the Y-maze compared to non-surgery controls.

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1 gene, total lipid analysis was performed on the rest of brains (where hippocampus had

been collected for gene expression). At 12 weeks of age, the brains of fish oil fed mice

(WTFO) have a 92% increase in DHA concentration compared to wildtype animals

maintained on safflower diet (WTSO) (Figure 5-11). Similarly, the fat-1 mice on

safflower (F1SO) had 93% more DHA compared to their wildtype littermates. There

were no significant differences in DHA concentrations between mice on fish oil diet and

the fat-1 mice. Both the fat-1 mice and the fish oil group had significant decreases in n-6

docosapentaenoic acid concentration compared to the safflower group. No observed

changes were observed for ARA between the groups.

5.4.2.2. Increased brain DHA increases microglial resolution

In order to test whether increased brain DHA increases resolution of

neuroinflammation, we measured the time course of activated microglia in our 3 groups.

LI-COR imaging did not result in differences between groups (data not shown). We

therefore evaluated resolution of neuroinflammation by classical immunohistochemistry

of Iba1 measured by microscope for higher resolution. The time course of microglial

activation is illustrated in Figure 5-12A. For all groups, microglial activation peaked at 3

days following LPS injection, and returned to baseline by 14 days. Two-way ANOVA

reveals a significant effect of time. Treatment groups, however, did not differ from one

another at any time point. Slopes were calculated to be -0.06, -0.06 and -0.08 Fold

change/day for the deficient, fish oil and fat-1 group respectively. There were no

significant differences in slopes between groups. However, there was a significant

difference in x-intercept, with F1SO having the lowest x-intercept (Figure 5-12B).

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Figure 5-11. Increased brain DHA in the fat-1 mice and mice fed a fish oil diet at 12

weeks of age.

Average brain DHA as % of total fatty (SEM) is increased in both fat-1 mice (F1SO) and mice fed fish oil (WTFO) compared to wildtype fed safflower diet (WTSO) (n=6). Significant differences between groups compared to WTSO are indicated by * as measured by one-way ANOVA and Tukey’s post hoc test (p<0.05)

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Figure 5-12. Effect of increased brain DHA on the resolution of microglial activation

Resolution of microglial activation is decreased in the safflower mouse (A). Linear regression found a significant difference in x-intercept were also measured, with the fat-1 mouse having the lowest x-intercept (B). Both the fat-1 mouse (F1SO) and wildtype fish oil fed mouse (WTFO) had reduced resolution indices compared to the wildtype safflower group (WTSO) (C-D) (n=2-7, SEM).

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Looking at Ri, both the F1SO and WTFO group had lower resolution indices (3 and 4

days respectively) compared to the WTSO (10 days) (Figure 5-12C and D).

5.4.3.3. Increased brain DHA decreases COX-2 expression but not the expression of

other pro-inflammatory markers

To determine if increasing brain DHA affected other pro-inflammatory markers,

we decided to evaluate the expression of pro-inflammatory markers in the fat-1 mice and

mice fed a fish oil diet. Increased brain DHA is known to affect expression of the

arachidonic cascade91, 297. Following LPS injection, COX-2 mRNA expression was

decreased by 36% in both the fat-1 mice and the fish oil supplemented mice compared to

the safflower group at 24 hr following LPS (Figure 5-13A). Although not significant, this

effect was trending (p=0.09). No other changes were observed at other time points. The

effect of higher brain DHA observed at 24 hr post surgery on COX-2 expression was not

observed cytosolic phospholipase A2 and microsomal prostaglandin E synthase

expression, other members of the ARA cascade.

Increased brain DHA did not alter cytokine expression either. CCL5 expression

peaked at 8hr (p < 0.05) following surgery and returned to baseline by 7 days. Neither the

WTFO nor the F1SO group had significant differences in CCL5 expression (Figure 5-

13B). Similar expression patterns were observed for other cytokines and chemokines

such as IL-1F- and CXCL1.

Similar to cytokine gene expression, increasing brain DHA did not result in

attenuated neuroinflammatory response of microglial markers. All 3 groups exhibited a

similar effect of time (p < 0.05) microglial markers Iba1 (Figure 5-13C), translocator

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Figure 5-13. Effect of increased brain DHA on the time course of mRNA expression of

example pro-inflammatory markers.

Two-way ANOVA found a significant effect of time (n=5-6)(p<0.05), but no effect of gene/diet on the average expression (SEM) COX-2(A), CCL5 (B), Iba1 (C), LCN2 (D). One-way ANOVA showed a trend for higher COX-2 expression (p=0.09) in the WTSO group at 24 hr, but no other groups

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protein 18 kDa, CD11b, CD68, and CD86 peaking at 2 days post surgery. M2 microglial

markers CD206, Arg1 and Ym1 gene expression also did not significantly differ between

groups. Similar findings were observed for the top hits in our microarray of Experiment

1, LCN2 (Figure 5-13D), SAA3 and Oasl2, members of the NF-B pathway including

NFB1, rela and IB, BBB markers ICAM1 and MMP9, and miscellaneous markers

such as GFAP, iNOS and Fas.

5.4. Discussion

Resolution of inflammation has been shown to be an active process in the

periphery. This process, however, has never been shown in the brain. In this study, we

developed a self-resolving model of neuroinflammation defined by cellular markers, gene

expression analysis, and lipid profile. Microglia were identified to be the major immune

cells to be involved in the process, where infiltrating cells such as macrophages and

neutrophils were not detected at any point throughout the resolution process. While

resolution in the periphery is driven by specialized pro-resolving lipid mediators 42, these

were not detected in our model. However, changes in lysophospholipids and

triacylglycerols were detected throughout resolution. Finally, with our newly developed

resolution model we tested the effect of increasing brain DHA, which had previously

been reported to have anti-inflammatory properties (Chapter 2294). While increased brain

DHA increased the resolution of microglia and decreased COX-2 expression, which had

been previously reported91, other markers were unaffected.

This study is unique as it the first study aiming to investigate the resolution of

neuroinflammation. Many studies have evaluated neuroinflammation at a single time

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point, however, depending on which marker is measured, this may make interpretation of

resolution difficult. As illustrated by this study, different markers have different time

courses. While cytokine mRNA expression increases shortly after LPS injection,

microglial activation occurs later following LPS injection and remains elevated for

weeks. Some studies have measured neuroinflammation at multiple time points88. In these

studies, however, the neuroinflammation is secondary to peripheral inflammation or

insult such as stroke165, 168. Although perhaps more clinically relevant, it is difficult to

determine whether the inflammation observed in the brain is neuroinflammation or

inflammation induced by the periphery. By directly injecting LPS in the left lateral

ventricle, we are directly activating the brain immune system through the Toll-like

receptor 4 located on microglia. Although the surgical process does cause some damage

and neuroinflammation, our lab has previously demonstrated that LPS induces more

neuroinflammation than surgery alone91. Interestingly, the gene expression profile

following i.c.v. LPS is very similar to the profile following systemic LPS298.

Resolution of inflammation in the periphery is driven by the production of

specialized pro-resolving lipid mediators. In this study, we did not detect any specialized

pro-resolving lipid mediators in the left hippocampus of the mouse at any time point

following LPS injection. This is contrary to a few studies which have reported brain

specialized pro-resolving lipid mediators 91, 155, 160, 165, 241. However, 4 of those studies

measured ischemic brains, either due to the fact that microwave fixation was not used, or

from using an ischemic stroke model. As reported in Chapter 4, ischemia increases

production of brain specialized pro-resolving lipid mediators and therefore may explain

differences between those studies and the values reported in this study. However, our

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group has previously reported the presence of protectin D1, 17-hydroxy DHA, and

maresin 191. Differences in the extraction methods may explain the differences between

the 2 studies. However, the lack of specialized pro-resolving lipid mediators detected in

this study would be in agreement with the lack of infiltrating neutrophils, which carry the

lipoxygenase enzyme that metabolize these specialized pro-resolving lipid mediators299,

as measured by immunohistochemistry and gene expression. This is in agreement with

previous reports that low doses of daily LPS do not increase infiltrating neutrophils300.

Marcheselli and colleagues, which have reported increases in specialized pro-resolving

lipid mediators, also reported neutrophil infiltration in their ischemia model241, which

could explain differences between their study and the results reported in this study.

We did report a few changes in intact lipids in this study. Lysophosphatidic acid

20:4 was lowered 24 hr following surgery, while phosphatidic acid 18:1/16:0 and

phosphatidic acid 18:1/18:1 were increased in parallel. In agreement with these findings,

autotaxin expression, the enzyme responsible for the production of lysophosphatidic acid,

was trending lower at 24 hr (p = 0.056) compared to non-surgery animals. The exact

nature of the decrease of lysophosphatidic acid in this study is not clear. Changes in

lysophospholipids following inflammatory insults have previously been demonstrated.

Frasch and colleagues reported an increase in lysophosphatidylserine in peritoneal cells

following zymosan injection. However, concentrations of lipid species returned to

baseline approximately 2 hours after the inflammatory insult, whereas lysophosphatidic

acid species returned to baseline days after the insult in our study301. Interestingly,

lysophosphatidic acids have been associated with inflammatory pathways by activating

astrocytes302 and promoting microglia proliferation303. Moreover, lysophosphatidic acid

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concentration is increased in spinal cord injury and exogenous administration of

lysophosphatidic acids decreases recovery304, 305. Conversely, it also has been reported

that lysophosphatidic acid infusion reduces circulating TNF-and myeloperoxidase

protein in mice exposed to LPS306. In this study, we also report an increase in

triacylglycerols at 28 days following LPS surgery. While it is unknown why this increase

only occurs at 28 days, it does agree with earlier reports that LPS induces lipogenesis and

increases triacylglycerol concentrations in macrophage307 and microglial308 culture.

Similarly, the COX-2 knockout mouse displays lower triacylglycerol concentration in the

brain, suggesting that suppressing neuroinflammation can reduce triacylglycerols in the

brain309. Interestingly, it has been suggested that increasing triacylglycerol accumulation,

resulting in increases in lipolysis, may be a preparation for more efficient phagocytosis307,

310, although it is unclear if this is what is occurring in this study.

Having developed a resolution model, this allows the testing of pro-resolving

compounds. In this study, we tested the effect of higher brain DHA on resolution of

neuroinflammation. Animals with higher brain DHA did appear to have a slightly faster

resolution of microglial activation. We also did notice a trend towards a reduction in

COX-2 mRNA expression at 24 hr post surgery, in agreement with previous reports69, 91,

159, 210, 241. However, no other pro-inflammatory markers were decreased by higher brain

DHA. Our laboratory has previously shown decreases in IL-1, CD11b and microsomal

prostaglandin E synthase 91 in mice with higher brain DHA which were not observed in

this study.

Several reasons could explain the differences, including 1) differences in volume

(not amount) of LPS injected, 2) only ipsilateral hippocampus being collected, and 3)

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different colonies of animals being used. While total brain DHA concentration was

measured, unesterified DHA was not. Orr and colleagues demonstrated that a change in

unesterified DHA is needed to observe changes in pro-inflammatory marker expression.

The unesterified DHA pool is tightly controlled and changes in total DHA do not

necessarily mean an increase in unesterified DHA. Future work should measure this pool

in order to rule out a lack of change in unesterified DHA as the reason for no changes in

pro-inflammatory marker mRNA expression.

In conclusion, we have developed a self-resolving model of neuroinflammation

independent of peripheral inflammation. Moreover, we have illustrated the need to

measure several types of markers over several time points in order to get a full picture of

the time course of the inflammation. Finally, while DHA did show some small pro-

resolving properties, this model may be more suited for testing pharmaceutical agents.

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Chapter 6: Discussion

142

6.1. Overall findings

The aim of Chapter 4 was to measure the lipidomic signature of the rat brain

without the effect of ischemia. To this date, lipidomic analysis of the rat brain has only

been performed on hypoxic brains311, 312. However, as illustrated by various studies267, 270,

277, 281, ischemia induces the production of lipid mediators which is inhibited by high-

energy microwave fixation. The research presented in this study provides further

evidence of a unique lipidomic signature induced by ischemia. We have replicated the

increase of numerous lipid mediators, such as PGE2 and arachidonyl ethanolamide, while

also adding to a number of bioactive mediators now known to be increased by ischemia

including protectin D1. Moreover protectin D1 was not detected with microwave fixation.

We have also reported the novel finding of changes in certain, but not all, intact lipid

pools induced by ischemia which are inhibited by microwave fixation. The major lipid

pool in the brain, the phospholipids, was unaffected by ischemia, while smaller pools

such, as lysophospholipids and diacylglycerol, were increased in ischemic states.

Conversely, triacylglycerols were decreased in ischemia. We illustrate how microwave

fixation inhibits these changes. We also demonstrate how changes in certain pools may

correlate with changes in other pools.

Resolution of inflammation had been defined in the periphery in various models

of peritonitis and lung inflammation. However, resolution of neuroinflammation had yet

to be defined in the brain. In order to address this gap, using our lipidomic approach

developed in Chapter 4 to avoid the ischemia-induced changes on the neurolipidome, we

attempted to develop a self-resolving model of neuroinflammation and measure the

production of specialized pro-resolving lipid mediators following i.c.v. LPS (Chapter 5).

143

Our model was a self-resolving model of neuroinflammation involving only microglia.

No neutrophils or macrophages were detected at any point following LPS injection. Since

neutrophils carry the lipoxygenase enzymes, no change in lipoxygenase expression was

measured and specialized pro-resolving mediator production was unaltered, suggesting a

specialized pro-resolving mediator independent pathway of resolution of

neuroinflammation. Interestingly, lipidomic profiling illustrated minor changes following

LPS injection, including decreases in lysophosphatidic acid and increases

triacylglycerols.

Finally, we report that increases in brain DHA have a mild effect on brain

inflammation, with small increases in resolution of microglial activation and decreases of

COX-2 expression. However, these effects were small and most inflammatory markers

were unaltered by increased brain DHA.

6.2. Limitations

There were many limitations to the studies presented in Chapter 4 and 5. Firstly,

in Chapter 4, the major limitation of the study lies in the differences in ischemia time

between the CO2 and the CO2+MW group. After both groups were exposed to 5 minutes

of CO2, ischemia was immediately stopped by microwave fixation in the CO2+MW group

while ischemia continued in the CO2 group for another 5 minutes while the head stayed

on ice and for a few minutes during the brain removal from the skull. This may explain

the difference in lipid concentrations observed in the two hypoxic groups as it has

previously been shown that an added 8 minute of ischemia resulted in approximately a

40% increase in free fatty acid release258. Due to the differences between groups, we

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cannot eliminate the possibility that microwave fixation destroys mediators. However,

certain lipid species have been shown to withstand degradation by microwave fixation281,

313. Moreover, the fact that concentrations in the CO2+MW group were consistently

elevated compared to the MW group suggests that the microwave fixation is not

destroying the mediators, as a scenario where microwave fixation destroys mediators to

different concentrations is not clear. Future studies should ensure that ischemia time is

equal across all groups in order to eliminate the possibility that microwave fixation is

destroying the mediators.

Another limitation to Chapter 4, and to the field of lipidomics in general, is the

use of different extraction and identification methods across studies. We were able to

replicate several studies which were unable to detect specialized pro-resolving lipid

mediators following microwave fixation277, 278. However, some studies have reported

specialized pro-resolving lipid mediators in both human and rat brain tissue46, 91, 155, 160,

170, 241, 314. While 6 of these 7 studies used brains exposed to ischemia, the lipid

extractions methods utilized were different and therefore cannot be excluded as a possible

explanation for the differences between these studies and the results reported in this

thesis. Moreover, our group has detected protectin D1 in microwave fixed mouse

hippocampus91 extracted using a different method315 from the one used in this study.

Several limitations are also present in Chapter 5. In terms of technical limitations,

due to the sheer number of groups and animals, non-surgery animals were used as

control, as sham-surgery control would have doubled the number of surgeries. The

surgery itself does induce neuroinflammation and therefore the lack of sham surgery

controls does limit interpretation. However, the purpose of this study was to develop a

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model of self-resolving inflammation and the inflammation induced by the surgery is part

of the model.

Several differences were observed between the results presented in this thesis and

the work reported by Orr and colleagues91. While COX-2 mRNA expression was similar

in both studies, reduction of several pro-inflammatory markers by increasing brain DHA

was not observed in this study. This may be due to a few technical differences between

the two studies. To minimize back flow following removal of the syringe from the brain,

5 g of LPS was dissolved in 5l of sterile saline instead of 1 l as utilized by Orr and

colleagues91. This was done in order to make sure as much LPS as possible remained in

the left lateral ventricle. However, this may have produced a stronger inflammatory

response, which could have been too potent for elevated levels of brain DHA to exert any

notable anti-inflammatory effect. In this thesis, only the ipsilateral hippocampus was

collected and analyzed whereas the whole hippocampus was previously collected91.

Collecting both sides of the hippocampus may have diluted the neuroinflammatory effect

of LPS, as microglial activation spreads from the ipsilateral side to the contralateral side.

It is possible that the DHA reduced neuroinflammation starting from the contralateral

side, where the LPS signal was the weakest, moving back towards the ipsilateral

hippocampus. Therefore, the effect of DHA may not have been observed in the ipsilateral

hippocampus where the inflammatory signal was the strongest. It would be of interest to

test whether any differences reported in neuroinflammatory markers by Orr and

colleagues91 are detected in the contralateral hippocampus.

Orr and colleagues reported that an increase in unesterified DHA was necessary in

order to convey anti-neuroinflammatory properties. While we did obtain an increase in

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brain total DHA, unesterified DHA was not measured91. In this study, a different colony

and batch of diet were utilized compared to Orr and colleagues91. It is possible that the

small differences in batches of food and colonies could have resulted in no differences in

brain unesterified DHA despite seeing increases in brain total DHA. Future studies

should measure unesterified DHA to confirm whether the differences between the two

studies are related to differences in unesterified concentrations.

This thesis set out to evaluate the resolution of neuroinflammation and the role of

specialized pro-resolving lipid mediators in this process. While we do report self-

resolution of microglia over time, specialized pro-resolving lipid mediators were not

detected in our model. In the periphery, specialized pro-resolving lipid mediators are

produced by infiltrating neutrophils299. In this model, neutrophils were not observed and

specialized pro-resolving lipid mediators were not detected throughout the time course of

LPS-induced inflammation. Models of ischemia, however, have reported neutrophil

infiltrations and specialized pro-resolving lipid mediators production163, 170, 172, 241. While

i.c.v. LPS may be a good model to study specialized pro-resolving mediator-independent

resolution of neuroinflammation, it is possible that a separate mechanism of resolution of

neuroinflammation involving specialized pro-resolving lipid mediators exist.

6.3. Future directions

Several experiments are needed in order to address the limitations outlined above

and to further our knowledge in the field in general. As stated above, there is a vast array

of extraction methods carried out in lipidomic studies316. One study evaluated 6 different

solid phase extraction cartridges for the extraction of 14 bioactive mediators317. However,

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this type of comparative analysis is needed for all lipids measured by lipidomic analysis

in order to develop a standardized method. Without standardizing protocols,

interpretation of results may be difficult, as extraction methods may lead to variation in

results across studies.

In Chapter 5, we developed a self-resolving model of neuroinflammation.

However, this model, unlike models of resolution in the periphery, was independent of

specialized pro-resolving mediator production and infiltrating cells. Other models of

neuroinflammation have been reported to have infiltrating cells and specialized pro-

resolving lipid mediators have been detected in the brain163, 172, 241. It would therefore be

of interest to measure resolution in these models. Moreover, it would also be of interest to

test whether n-3 PUFA increase resolution more in those models than the amount that

was observed in this thesis. N-3 PUFA have been shown to have anti-inflammatory

properties in these models (Chapter 2294), and increasing brain DHA has been shown to

increase specialized pro-resolving lipid mediators 160, 165. Since neutrophils do infiltrate in

the brain and the presence of specialized pro-resolving lipid mediators is observed in

these models, it is possible that a specialized pro-resolving mediator driven resolution of

neuroinflammation could be influenced by increasing brain DHA in these models.

Since no specialized pro-resolving lipid mediators were detected in our model, the

effects of increasing brain DHA on resolution in Chapter 5 are likely due to DHA and not

its mediators. However, specialized pro-resolving lipid mediators have been shown to

have anti-neuroinflammatory properties in other models91, 170, 241, 295. It is possible that

they could mediate resolution if present in the brain. Future studies should investigate

whether infusing these mediators increases resolution of neuroinflammation. Moreover,

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this could be beneficial in disentangling whether they possess anti-inflammatory or pro-

resolving properties in the brain. If infused at the same time as the LPS injection and

subsequently reducing neuroinflammation, this would suggest anti-inflammatory

properties. If infused at the time of maximal inflammation and if inflammation is reduced

faster, this would suggest pro-resolving properties.

In our study, we saw small differences in microglia cells counts measured by

classical immunohistochemistry using microscopy, which were not detected by LI-COR

measurements. It is possible these changes were due to modifications in microglia

morphology. DHA has been reported to decrease hypertrophy in N9 microglial cell

cultures, as measured by confocal imaging, induced by low doses (100 ng/ml) of LPS37.

In vivo, DHA treatment was reported to increase microglia ramification, illustrating DHA

shifting microglia towards a surveying phenotype318. Similarly, n-3 PUFA deficiency has

been shown to reduce microglia motility by Two-Photon imaging319. Confocal imaging

should be performed in the future in order to test the hypothesis that higher brain DHA

reduces hypertrophy and increases ramification.

Our studies are limited as the time course of inflammation can only be

approximated because subjects were not surveyed throughout the whole resolution of

neuroinflammation. Each subject served for only one time point in the analysis since

brains needed to be collected in order to make our measurements. However, it would be

useful to continuously measure resolution of microglial activation. The use of PET

imaging would allow for this. Translocator protein 18 kDa ligands, markers of microglial

activation, have been used in PET imaging in several models, such as epilepsy320, 321,

traumatic brain injury322, 323, stroke324, 325, and multiple sclerosis326. PET imaging of the

149

ligand [11C]PK11195, a translocator protein 18 kDa ligand, has been used in one study of

LPS-induced neuroinflammation in rats 16 hours following LPS injection327. However,

resolution of microglia following LPS injection was not measured. This method would

allow for a measurement of the effect of DHA on resolution in vivo, as measured in the

periphery328, 329.

6.4. Significance

The work reported in this thesis has direct implications for the field of lipidomics

and resolution. Various studies have previously reported the presence of specialized pro-

resolving lipid mediators in various animal models. However, a subset of these studies

did not consider using high-energy microwave fixation to denature the proteins

responsible for the release of unesterified fatty acids from the phospholipid membrane155,

160. As illustrated in Chapter 4, ischemia results in increased production of bioactive

mediators, including protectin D1. Interestingly, both of these studies utilized models of

ischemia, which therefore could account for the increase in specialized pro-resolving

mediator production in these studies155, 160.

To this date, two studies have reported on the production of lipoxin A4, resolvin

D5, maresin 1 and protectin D1 in postmortem brains of Alzheimer’s disease patients46,

314. However, the two studies did not agree on the increases in lipoxin A4 in Alzheimer’s

disease. The postmortem interval was approximately 20 hr for both studies before brains

were collected and stored at -80C. Moreover, although not statistically significant, the

postmortem interval was 3 hr higher in the Alzheimer’s group than the control group. We

reported here that even small differences, such as 5 min in hypoxic time can result in

150

large differences in concentrations of these mediators. These large postmortem interval

times, combined with the variability in postmortem interval times, could have resulted in

the differences detected between the two groups in these studies. Although microwave

fixation of human brain tissue is not feasible, the effect of ischemia should be considered

when interpreting the results obtained from human postmortem brains.

We reported that neuroinflammation induced by i.c.v. LPS appears to be

independent of neutrophil infiltration. This has major implications on our interpretation

of resolution of neuroinflammation. Classically, resolution of inflammation in the

periphery is mediated by infiltration of neutrophils into the inflamed tissue. In doing so,

the neutrophils carry in the lipoxygenase enzyme which can upregulate the production of

specialized pro-resolving lipid mediators. The fact that no neutrophils were observed in

our model would agree with the fact the lipoxygenase enzyme was unchanged and

specialized pro-resolving lipid mediators were not detected throughout the time course of

neuroinflammation. This would suggest that resolution of neuroinflammation following

i.c.v. LPS is independent of specialized pro-resolving lipid mediators. However,

neutrophils have been reported in several animal models241, 330-333 and clinical studies333,

334. This could imply that the resolution in these models may be different than the

resolution reported in this thesis, and may actually rely upon the production of

specialized pro-resolving lipid mediators.

Our work also supports, in part, a potential beneficial effect of DHA for brain

health. While the results in our study were mild, increasing brain DHA did increase the

resolution of microglial activation following LPS injection and did reduce COX-2

expression. Since neuroinflammation has been associated with a large number of

151

neurological and psychiatric disorders116, 117, treatments that can reduce

neuroinflammation may convey beneficial effects in these disorders. Moreover, there is

evidence, although variable, which suggests that these disorders are associated with

decreased n-3 PUFA in the brain335-337. This suggests that a decrease in brain n-3 PUFA

could predispose subjects to neuroinflammation and/or neurological and psychiatric

disorders. A large body of epidemiological289, 337 and animal evidence (Chapter 2) has

supported the claim that DHA promotes brain health. This work furthers the possible

notion of the beneficial effects of n-3 PUFA. However, these effects were mild and

pharmaceutical approaches may be more beneficial in treating neuroinflammation.

6.5. Conclusions

Overall, the results reported in this thesis support the idea that microwave fixation

is required in order to measure accurately lipid concentrations without ischemia-induced

artifacts. While bioactive mediators were all elevated in states of ischemia, different

species of intact lipid were either increased, decreased or remain unchanged due to

ischemia and these effects were inhibited by high-energy head-focused microwave

fixation.

We also developed a self-resolving model of neuroinflammation in the mouse.

While this model is self-resolving, it appears to be independent of specialized pro-

resolving mediator production and infiltrating cells, with only microglia and astrocytes

actively involved in the process. This model stresses the need to evaluate

neuroinflammation temporally. As different neuroinflammatory markers vary over time,

multiple time points need to be considered in order to evaluate resolution.

152

Finally, increasing brain total DHA had small increases in resolution of microglial

activation and COX-2 gene expression. However, the majority of neuroinflammatory

markers were unaffected. This model may be more suited to test pharmaceutical agents

on the resolution of neuroinflammation.

153

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Appendix 1: Postmortem evidence of cerebral inflammation in schizophrenia: a systematic review

Adapted from: Marc-Olivier Trépanier, Kathryn E Hopperton, Romina Mizrahi, Naguib Mechawar and Richard P Bazinet

(Accepted in Molecular Psychiatry, DOI 10.1038/mp.2016.90) http://www.nature.com/mp/journal/v21/n8/full/mp201690a.html

Contribution: I came up with inclusion and exclusion criteria and came up with search strategy. I also went through all search results and decided on which papers to include or exclude. I extracted all information and wrote the first draft of the paper.

187

A.1 Abstract

Schizophrenia is a psychiatric disorder which has a lifetime prevalence of

approximately 1%. Multiple candidate mechanisms have been proposed in the

pathogenesis of schizophrenia. One such mechanism is the involvement of

neuroinflammation. Clinical studies, including neuroimaging, peripheral biomarkers, and

randomized control trials, have suggested the presence of neuroinflammation in

schizophrenia. Many studies have also measured markers of neuroinflammation in

postmortem brain samples from schizophrenia patients.

The objective of this study was to conduct a systematic search of the literature on

neuroinflammation in postmortem brains of schizophrenia patients indexed in

MEDLINE, Embase and PsycINFO. Databases were searched up until March 20th 2016

for articles published on postmortem brains in schizophrenia evaluating microglia,

astrocytes, glia, cytokines, the arachidonic cascade, substance P, and other markers of

neuroinflammation. Two independent reviewers extracted the data.

Out of 5385 articles yielded by the search, 119 articles were identified that

measured neuroinflammatory markers in schizophrenic postmortem brains. Glial

fibrillary acidic protein (GFAP) expression was elevated, lower or unchanged in 6, 6 and

21 studies respectively, and similar results were obtained for glial cell densities. On the

other hand, microglial markers were increased, lower, or unchanged in schizophrenia in

11, 3 and 8 studies respectively.

Results were variable across all other markers, but SERPINA3 and IFITM were

consistently increased in 4 and 5 studies respectively. Despite the variability, some

studies evaluating neuroinflammation in postmortem brains in schizophrenia suggest an

188

increase in microglial activity and other markers such as SERPINA3 and IFITM.

Variability across studies is partially explained by multiple factors including brain region

evaluated, source of the brain, diagnosis, age at time of death, age of onset, and the

presence of suicide victims in the cohort.

189

A.2. Introduction Schizophrenia is a psychiatric disorder which affects approximately 0.5% to 1%

of the population in their lifetime1, 2. Psychosis normally arises in the late teenage years

or early adulthood, between 18 to 25 years of age3. Although the cause underlying this

mental illness remains to be elucidated, several biological factors have been proposed,

including abnormalities in oligodendrocytes4, 5, NMDA signaling6, and dopaminergic

transmission7.

Neuroinflammation has been suggested to be a potential contributor in the

pathogenesis of the schizophrenia8-11. Classically, the brain is considered to be

immunologically privileged due to the blood-brain barrier limiting cell entry12. Under

normal conditions, microglia, the resident immune cells of the brain, are found in a

ramified (“resting”) state, surveying the environment. Following injury or the exposure to

pro-inflammatory signals such as interferon (IFN)-γ and tumor necrosis factor (TNF)-α,

ramified microglia can become activated and release pro-inflammatory cytokines such as

interleukin (IL)-1β, IL-6, IFN-γ, or chemokine (c-x-c motif) ligand (CCL) 1113.

Microglia also increase the expression of cyclooxygenase (COX)-2, an enzyme involved

in the arachidonic cascade, which can lead to the production of the proinflammatory lipid

mediator prostaglandin E214. Pro-inflammatory cytokines released from microglia, such

as IL-1β, can activate astrocytes. In turn, activated astrocytes also have the ability to

release pro-inflammatory cytokines and chemokines, such as IL-1β, CCL5, and TNF-α15,

and typically display increased glial fibrillary acidic protein (GFAP) expression16.

Evidence has accumulated supporting a link between inflammation and

schizophrenia. Serum or plasma concentrations of pro-inflammatory markers have been

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investigated in several studies. Two meta-analyses illustrate that IL-6 is consistently

elevated in serum and plasma of patients with schizophrenia17, 18, while IL-1β and TNF-α

were found to be increased in one meta-analysis18, but not in the other17. Genetic studies

have also linked polymorphisms in major histocompatibility complex (MHC) regions

with risk of schizophrenia19, 20.

Neuroinflammation has also been associated with schizophrenia. Advancements

in in vivo PET imaging has enabled imaging of neuroinflammation in schizophrenic

patients21. However, studies imaging the translocator protein 18 kDa (TSPO), a marker of

activated microglia, have yielded mixed results. Early studies utilizing the TSPO ligand

[11C]PK11195 suggested that schizophrenic patients have higher levels of activated

microglia compared to healthy controls22, 23. More recent studies, using second-

generation TSPO ligands, however, had mixed results, with some reporting increased

microglia activation in schizophrenia24, while others failed to replicate earlier studies and

found no difference between patients and healthy controls25, 26. The reasons for the

disparities between studies are not clear, but likely related to different TSPO ligands used

or different samples studied across research groups.

Since schizophrenia has been associated with inflammation, attempts have been

made to treat symptoms with non-steroidal anti-inflammatory drugs (NSAID) as an add-

on therapy to conventional treatments. While some studies found added benefits of

NSAID on symptoms27-29, one study did not show any beneficial effects30. A meta-

analysis of 5 published and 3 non-published studies found no effect of NSAID on the

Positive and Negative Syndrome Scale total scores, but did detect a small yet statistically

significant beneficial effect of NSAID add-on therapy for the treatment of positive

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symptoms31. Omega-3 polyunsaturated fatty acids (n-3 PUFA), which are also thought to

have anti-neuroinflammatory properties32, 33, have also yielded mixed results in the

treatment of schizophrenia. Administration of 3 g per day of n-3 PUFA in combination

with 300 mg per day of alpha-lipoic acid for up to 2 years did not decrease the relapse

rate of schizophrenic patients34. An earlier report, however, found that administration of

n-3 PUFA was beneficial in reducing the conversion of subthreshold psychosis to a first

episode psychotic event in adolescents35.

It is unclear whether neuroinflammation associated with schizophrenia is causing

or a result of the disorder. It has been suggested that microglia activation and cytokine

release could lead to neuronal and glial injury36, resulting in dopaminergic and

glutaminergic system dysregulation37, 38. Neurogenesis and synapse connectivity may

also be affected by neuroinflammation39, 40. Moreover, activation of astrocytes may also

cause abnormal production of kynurenic acid and upregulate the expression of glutamate

transporters9, 11, 41.

Despite the mixed results in both in vivo imaging and clinical trials, it appears

plausible that inflammation may play a role in schizophrenia. Numerous postmortem

studies have measured pro-inflammatory markers in patients suffering from

schizophrenia. To date, no systematic review of the field has been published on the topic.

This article set out to systematically characterize the literature on neuroinflammation as

measured in postmortem brains from schizophrenia patients.

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A.3. Methods

We performed a systematic search for literature indexed in MEDLINE, Embase

and PsycINFO up to March 20th, 2016. Full search criteria can be found in the

Supplementary materials. Only peer-reviewed primary research articles were considered

as eligible studies. References of yielded articles were searched for possible eligible

articles that were missed by the search.

Once duplicate articles were removed, studies were screened based on title and

abstract for several components including studies which were on schizophrenia and 1)

carried out with postmortem brain samples, 2) measured neuroinflammatory markers, and

3) were compared to matched psychiatrically and neurologically healthy controls. Studies

evaluating markers of astroglia, microglia, gliosis, cytokines, arachidonic acid cascade

and substance P were included (For full search terms, see Supplementary Materials).

Other markers were considered if the authors referred to their implication in

neuroinflammation. Although not always stated by the authors as a microglial marker,

MHC (also know as human leukocyte antigen, HLA) complex I and II were both

considered as possible microglial markers since both have been shown to be elevated in

microglia42. Untargeted approaches, such a microarray and shotgun proteomics, were also

excluded unless targeted approaches were used to confirm the results. Viruses and

infection were not considered for this review and were excluded. Reviews were searched

for relevant articles, but themselves were excluded from the results. Finally, non-English

papers and conference abstracts were also excluded.

Articles were evaluated and data were extracted onto an electronic data extraction

form by M.O.T. Extractions were confirmed by a second independent reviewer (K.E.H.).

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From eligible studies, number of subjects, sex, race, duration of illness, onset of illness,

postmortem interval, freezer time, death from suicide, substance abuse, medication, RNA

quality, and brain pH were extracted as background information. Unless specifically

stated, suicide was not assumed as cause of death. Study design information, such as

neuroinflammatory markers measured, measuring techniques, and in which brain regions

the measurements were made were all extracted, along with comparative results between

schizophrenia and healthy controls. Thus, all results discussed below are relative to

controls unless otherwise stated.

A.4. Results

Following removal of duplicates, the search yielded 5385 unique results. A total

of 5168 articles were excluded based on either title or abstract. The remaining 217

articles were fully screened for potential inclusion. Out of those remaining 217 articles,

only 115 articles met the inclusion criteria. Four more articles were found in the reference

section of papers yielded from the search (Figure 2-1).

A.4.1. Astroglia

Our search yielded a total of 42 studies which assessed astrocytes in postmortem

brain in schizophrenia (Table 2-1).

Of those 42 studies, 33 studies evaluated potential differences in astrocytes in

schizophrenia by measuring glial fibrillary acidic protein (GFAP) expression or

immunoreactive distribution. Out of the 33 studies evaluating GFAP expression, 21 did

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not detect any schizophrenia-associated changes, 6 studies reported a decrease in GFAP

expression, while 6 studies reported increased expression.

The first study to evaluate GFAP was published in 1986 by Robert et al. In their

study of the temporal cortex of 5 schizophrenic patients, immunohistochemical analysis

found no differences in GFAP staining in schizophrenia brains compared to healthy

controls43, and was confirmed in a subsequent study with a larger cohort44. Similarly,

many quantitative immunohistochemical studies found no differences in GFAP cell

density in several other brain regions including the hippocampus45, 46, amygdala47, 48,

subiculum45, 49, mediodorsal thalamus50, caudate50, 51, periventricular nucleus51, nucleus

basalis52, premotor cortex49, dorsolateral prefrontal cortex53, midfrontal cortex45, 46,

orbitofrontal cortex45, 46, entorhinal cortex45-47, 49, 54, visual cortex45, calcarine cortex46,

and anterior cingulate cortex53. When compared to Alzheimer’s and Huntington’s disease

patients, schizophrenic patients had lower GFAP labeled cells43, 45, 46. However,

schizophrenic patients presenting with dementia had significantly higher GFAP cell

density than schizophrenic patients without dementia in multiple brain regions including

hippocampus, entorhinal cortex and orbitofrontal cortex45. GFAP was also reported to be

correlated with age54. While Hercher and colleagues also found no differences in GFAP

cell density in the dorsolateral prefrontal cortex in schizophrenia, they did find a

decrease in GFAP fraction area and increased clustering55. Phosphorylated GFAP was

investigated in one immunohistochemical study. In a cohort of 15 patients, no difference

in phosphorylated GFAP was observed between schizophrenic brains and those of

healthy controls in the hippocampus56. The authors did note, however, a decrease in

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phosphorylated GFAP labeled cells in the dorsolateral prefrontal cortex next to blood

vessels56.

Similar to the immunohistochemical studies mentioned above, multiple studies

reported no increases in GFAP expression measured by other methods. No increase in

GFAP mRNA expression was detected in the prefrontal57 and cingulate cortices58 of

schizophrenics. Beasley et al found no differences in GFAP in the anterior limb of

internal capsule of schizophrenia compared to healthy controls as measured by enzyme-

linked immunosorbent assay59. Western blot analysis, similarly, found no increase in

GFAP protein concentration in the cerebellum60, 61, frontal cortex61, 62, prefrontal cortex63-

65, visual cortex64, occipital cortex61, temporal cortex61, parietal cortex62, thalamus61, and

pons61 of schizophrenic patients. Another study evaluating GFAP protein expression by

western blot of various brain regions of 23 schizophrenics, including the dorsolateral

prefrontal cortex, visual cortex, anterior cingulate cortex, hippocampus and temporal

gyrus, failed to detect any changes in GFAP protein expression in schizophrenia, except

for a significant decrease in the anterior cingulate cortex66.

A few studies have detected differences in GFAP protein expression. Williams et

al. reported a decrease in GFAP cell density in the subgenual cingulate cortex and the

corpus callosum in both the grey and white matter in a cohort of 10 schizophrenic

patients compared to healthy controls67. More specifically, another study found a

decrease in number of fibrillary astrocytes in the subgenual anterior cingulate cortex68.

The authors, however, found no differences in gemistocytic astrocytes68. In a separate

study, the same group also found a decrease in GFAP cell density in the substantia

nigra69. Falkai and colleagues reported a decrease in GFAP cell density in the left inferior

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horn in men, while no effect was observed in women49. On the other hand, Rajkowska et

al. reported, in a cohort of 9 schizophrenic brains, an increase in GFAP cell density in

layer V of the dorsolateral prefrontal cortex, while GFAP labeling area was reduced by

32%70. These changes were layer specific, as no differences were detected in layer III and

IV70. This is slightly different from what Toro and colleagues observed, where increases

in GFAP, as measured by autoradiography, where observed in layers II, III and IV of the

prefrontal cortex in schizophrenia71. Importantly, this increase in GFAP was correlated

with antipsychotic use. A decrease in GFAP in the orbitofrontal cortex was also

observed71. The authors proposed that the increase in prefrontal cortex was due to

medication use while the decrease in the orbitofrontal cortex was due to the disease71.

Markova and colleague reported increased GFAP positive cell area and reduced

anisotropy, indicating gliosis, in the olfactory tubercle in schizophrenia72. This is in

agreement with another study where GFAP labeled cells had changed in morphology in

the prefrontal cortex of schizophrenics, being more stained and stunted, while also having

a 2.4 fold increase in protein concentration and 30% increase in mRNA expression73.

Other studies have also shown that GFAP mRNA expression changes in schizophrenia.

Barley and colleagues found that schizophrenic patients had increased GFAP mRNA

expression in the putamen and mediodorsal thalamic nuclei74. Like Toro et al., increases

in GFAP expression was correlated with duration of neuroleptic treatment74. While Catts

and colleagues found no changes in GFAP mRNA expression in the dorsolateral

prefrontal cortex between schizophrenic patients and healthy controls, a difference was

observed in schizophrenia patients when they were stratified based on the presence of

other neuroinflammatory markers including serpin peptidase inhibitor (SERPIN) A3, IL-

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1β, IL-6 and IL-875. Individuals with elevated neuroinflammation had a larger proportion

of hypertrophic astrocytes compared to low neuroinflammation subjects75. On the other

hand, GFAP mRNA, as measured by riboprobe was decreased in the white matter of the

anterior cingulate cortex76. This effect, however, was not seen in the grey matter76.

Other astrocytic markers have also been measured in postmortem brain specimen

of patients with schizophrenia. Hwang and colleagues showed increases in apolipoprotein

1 and adenosine A2A receptor mRNA expression, markers of perivascular astrocytes and

implicated in inflammatory responses, in the hippocampus in schizophrenia77. Similarly,

along with increases in GFAP, schizophrenia was associated with increases in aldehyde

dehydrogenase (ALDH)1 mRNA in several brain regions including the putamen,

anteroventral nucleus, internal capsule and mediodorsal thalamic nucleus74. In contrast,

two other studies found no association between schizophrenia and ALDH1L1 mRNA

measured in the deep layer of the cingulate cortex58 and protein concentration in the

dorsolateral prefrontal cortex65. Similar results were observed for GFAP and other

astrocytic markers including vimentin58, 65, excitatory amino acid transporter (EAAT)165

and phosphate-activated glutaminase58. Katsel and colleagues, however, did find several

other astrocytic markers, including S100b and EAAT2 mRNA to be downregulated in the

cingulate cortex in schizophrenia58. Differences in expression of various astrocytic

markers may point to different types of astrocytes being affected in schizophrenia58.

S100b has been measured in a few other studies with mixed results. While one study

found decreases in S100b protein measured by western blot analysis in the corpus

callosum78, another found no effect in several brain regions including Brodmann area

(BA) 9, 10, 40 and 4662. When separating paranoid schizophrenia from residual

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schizophrenia, one study found an increase in S100b positive cells in paranoid

schizophrenia compared to both residual schizophrenia and healthy controls in the

dorsolateral prefrontal cortex79. No effect was seen, however, in the white matter, as

well as other brain regions such as hippocampus, mediodorsal thalamus, anterior

cingulate cortex, superior temporal cortex and orbitofrontal cortex79.

Astrocytes have also been identified in postmortem brains by microscopic

analysis with other staining techniques. Casanova et al. found no differences in astrocytes

identified using Holzer’s technique between the hippocampus of 6 schizophrenia patients

and 7 healthy controls80. Similar to other studies comparing schizophrenic brains to those

with Alzheimer’s disease45, 46, Alzheimer’s disease brains had more astrocytes compared

to both the schizophrenia and control groups80. Similarly, stereological counting of Nissl

stained astrocytes showed no differences in cell counts in the hippocampus81, basolateral

nucleus of the amygdala82, and pallidum82. However, a significant decrease in astrocytes

was measured in both the nucleus accumbens and mediodorsal thalamic nucleus82.

Changes in astrocytes in schizophrenia have also been investigated by electron

microscopy83. In a cohort of 19 schizophrenia patients, astrocyte morphology was

unchanged in the hippocampus compared to healthy controls83. However, when patients

were separated based on age, increased astrocytes were observed in patients younger than

50 years old, but this effect was lost in older patients. On the other hand, astrocytic end

feet were increased in both paranoid and non-paranoid schizophrenia in the prefrontal

cortex84, however, this effect was not present in the visual cortex in non-paranoid

schizophrenics84.

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A.4.2. Microglia

From our search, a total of 22 articles reported on microglial markers in postmortem

schizophrenic brains (Table 2-2). Out of these 22 studies, 11 studies reported

an increase in microglial markers in postmortem brains, while 8 studies found no effect

and 3 studies found a decrease in microglial markers.

Bayer et al. found that 3 of 14 schizophrenic patients had positive HLA-D related

(DR) staining, MHC class II molecules involved in antigen presentation, while control

subjects showed no staining in the hippocampus and frontal cortex85. This is in agreement

with 2 subsequent studies, where HLA-DR was increased in the prefrontal cortex86,

dorsolateral prefrontal cortex53, superior temporal gyrus53, inferior temporal gyrus87 and

frontal lobe in schizophrenia87. No changes, however, were seen in the cingulate cortex53.

This increase in HLA-DR labeling in the hippocampus appears to be more pronounced in

paranoid schizophrenics, as this group has increased HLA-DR compared to both control

and residual schizophrenics, although only significantly different from residual

schizophrenics88. Immunohistochemistry revealed differences in morphology of HLA-DR

labeled cells in schizophrenia, presenting a stunted and stronger labeling phenotype in the

frontal cortex73. It also has been reported that although patients show stronger HLA-DR

labeling in the anterior cingulate cortex, microglia appear to be degenerating89.

Calprotectin, a member of the S100 family, co-expressed with microglial marker CD68

and was increased 2 fold in the dorsolateral prefrontal cortex in schizophrenic patients

compared to healthy controls90.

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Not all studies found significant differences in microglia density. Steiner and

colleagues found no differences in HLA-DR protein in various brain regions

betweenschizophrenia and healthy controls, but did note that the 2 individuals who

committed suicide in their cohort did show more HLA-DR labeling91. A follow-up study

by the same group found a similar lack of effect of diagnosis, but that suicide was

accompanied with higher HLA-DR positive cells92. In a microarray analysis, an increase

in HLA-A, MHC I molecules, mRNA expression in the frontal cortex and superior

frontal gyrus was observed between schizophrenia and healthy controls in the frontal

cortex93. This effect, however, was not statistically significant when mRNA expression

was confirmed by qPCR93. Schmitt et al observed, in a microarray analysis of the

temporal cortex of 10 schizophrenic patients and controls, lower mRNA expression of

HLA-DRB3 and HLA-DPA1, subunits of HLA-DR, in schizophrenia94. Similar to Saetre

and colleagues, however, this effect was once again lost when analyzed by qPCR94.

Similarly, MHC II positive cells were also unchanged in the subventricular zone in

schizophrenia compared to healthy controls95. Nakatani and colleagues also found no

differences in HLA-DRA mRNA expression in the dorsolateral prefrontal cortex in

schizophrenia, despite seeing a difference between control and bipolar disorder96. Other

microglial markers are also unchanged in schizophrenia. For example, ionized calcium-

binding adapter molecule (Iba)1 as measured by immunohistochemistry showed no

differences in microglial density in the cingulate cortex or dorsolateral prefrontal

cortex55, 97. Two prospective studies following patients who developed schizophrenia

found no change in CD68 protein in the caudate nucleus50, mediodorsal nucleus of the

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thalamus50, hippocampus46, and entorhinal46 and calcarine46 cortices in schizophrenic

patients.

Similar decreases in HLA-DRA and HLA-DRB4 mRNA expression were

observed in the temporal lobe98. Despite not seeing changes in HLA-DR positive cells, a

separate study found microglial production of quinolinic acid was reduced in the

hippocampus, and more specifically in the cornu ammonis (CA)1, of schizophrenic

patients99. MHC I protein concentration was lower in the dorsolateral prefrontal cortex

in a non-smoking schizophrenic population, while no differences were seen in the

orbitofrontal cortex100. This effect was not seen in a smoking population100. Systemic

inflammation, however, appears to play a role in potential differences between patients

with schizophrenia and healthy controls. In one study, schizophrenic patients with no

systemic inflammation showed no differences as compared with healthy controls, but

schizophrenics displaying systemic inflammation had lower HLA-A mRNA expression

compared to psychiatrically healthy controls with systemic inflammation101. However,

when that same cohort was divided into smokers and non-smokers, regardless of systemic

inflammation, HLA-B mRNA expression was increased in schizophrenic patients101. The

authors did report that HLA-A appeared to co-localize with glutaminergic neurons101.

A.4.3. Undifferentiated Glial Cells

Multiple studies have evaluated glial cells in schizophrenia without the use of cell

type-specific markers. Some studies separated the types of glial cells (i.e. astrocytes,

oligodendrocytes, microglia), as discussed previously. However, many studies using

Nissl staining, evaluated the effect of schizophrenia on glial cells without differentiating

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between cell types. In total, 34 studies evaluated glial cells in schizophrenia, where 25

studies reported no difference, 7 studies found a decrease and 2 found an increase in glial

cell densities (Table 2-3).

Stevens et al. published the first study which met our inclusion criteria on the

effect of schizophrenia on glial cells. In a cohort of 18 schizophrenic patients, fibrous

gliosis measured by Holzer’s staining was more pronounced in several brain regions

including the hippocampus, hypothalamus, amygdala, thalamus, and periventricular areas

compared to control102. Comparable effects were observed in another study, which found

increased fibrous gliosis as measured by Holzer’s technique in the cerebral cortex of

patients with schizophrenia103.

The increase in gliosis measured by Holzer’s technique appears to differ,

however, with a study published shortly after the report by Stevens and colleagues, which

found, using a Nissl staining technique, a decrease in glial cell density in the CA3 and

CA4 of the hippocampus104. No effect of schizophrenia, however, was observed in the

CA1 and subiculum104. Similar decreases in glia were observed by Giemsa staining in the

anterior cingulate cortex105 and by cresyl violet staining in the temporal cortex106 and

planum temporale107. A layer specific decrease in glial cell density measured by cresyl

violet staining was observed in 3 studies, where effects were only in layer V of the

dorsolateral prefrontal cortex108, layer VI of the anterior cingulate cortex (statistical

significance was lost following multiple corrections)109 and layer III of the motor

cortex110. The latter study did not detect any differences in both the prefrontal and

cingulate cortices110. Gliosis measured by [3H]PK11195 binding, a ligand which binds to

the TSPO receptor found on activated microglia and astrocytes, was reduced in

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schizophrenia in the occipital cortex, parietal cortex, and putamen but not in the

prefrontal cortex, temporal cortex, thalamus, pallidum, substantia nigra, and caudate111.

Twenty-five studies, however, found no effect of schizophrenia on glial cell

density in postmortem brains. In a study of 13 schizophrenic postmortem brains from the

Stanley Foundation Neuropathology Consortium, Nissl staining revealed no differences

in glial cell density or size in the amygdala112. Similarly, no changes in glial density were

obtained in the prefrontal113-116, frontal114, subgenual prefrontal117, occipital113, 115 and

entorhinal118 cortices in schizophrenia compared to healthy controls. By comparison,

Huntington’s Disease had an approximately 50% increase in glial cell density compared

to healthy controls113. Moreover, Huntington’s disease had increased density of larger

glial cells115. When glial cell density was measured by cresyl violet staining, no changes

were detected between schizophrenia patients and healthy controls in several brain

regions including the fusiform cortex119, prefrontal gyrus120, mediodorsal thalamic

nucleus121, layer III and V of the Heschl’s gyrus122, anterior cingulate cortex123-125,

prefrontal cortex125, insular cortex126, orbitofrontal cortex127, hippocampus128, planum

temporale129, substantia nigra130, and lateral geniculate nucleus131. It should be noted that

although Bogerts et al. failed to detect a difference in glial cell density in schizophrenia,

they did report a significant reduction in glial size in schizophrenia patients130.

Gallocyanin, another staining technique, also did not detect an effect of schizophrenia on

glial cell density in the dorsolateral prefrontal cortex of 13 male schizophrenic

patients132. Similarly, Beckmann and colleagues did not find any significant differences

in glial density in several brain regions including the striatum, caudate, putamen, and

nucleus accumbens133. Crow et al. also did not detect a difference in gliosis in the

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temporal horn and in the periventricular region using Holzer’s technique between

schizophrenia patients and control. This was confirmed using diazepam inhibitor binding

to evaluate gliosis134. In another study, Nasrallah and colleague found no differences in

glial cell density in the corpus callosum in schizophrenia compared to healthy controls

using hematoxylin and eosin staining135. The authors did note that gliosis rating scores

were higher in late onset schizophrenia compared to early onset and control patients135.

A.4.4. Cytokines and Chemokines

Ten studies evaluated cytokine and chemokine expression in postmortem brains

of schizophrenic patients (Table 2-4). Two studies reported no difference in IL-1β mRNA

in the prefrontal cortex86, 136, despite measuring increases IL-1RA136, IL-686 and IL-8

mRNA86. IFN-γ, measured by enzyme-linked immunosorbent assay, was reported to be

increased in the prefrontal cortex of 35 schizophrenia patients compared to unaffected

controls137. However, Rao et al. reported 150% and 3.9 fold increases in IL-1β protein

and mRNA respectively in the frontal cortex of schizophrenics. TNF-α protein and

mRNA concentrations were also increased, 76% and 2.3 fold respectively, in

schizophrenic patients73. In a study of 19 schizophrenics, TNF-α receptor 1 mRNA was

increased in the dorsolateral prefrontal and cingulate cortices compared to controls,

whereas soluble TNF-α protein, transmembrane TNF-α protein and TNF-α receptor 2

mRNA concentrations were unchanged138.

A microarray analysis, followed by qPCR validation, found a decrease in IL-8 and

IL-1α mRNA expression in the temporal cortex of 10 schizophrenic patients as compared

to healthy control patients. However, increases detected in the microarray were not

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reproduced by qPCR for cytokines and chemokines such IL-1β, and CCL294. Another

study also found a decrease in IL-8 mRNA in the middle frontal gyrus in schizophrenia,

while IL-1β, TNF-α, IL-18, and IL-6 were not changed139. Two more microarray studies

A.4.5. Arachidonic Acid Cascade

Seven studies have evaluated the arachidonic acid cascade in postmortem

schizophrenic brains (Table 2-5).

Regional differences in concentration of cytosolic prostaglandin E synthase

(PGES) protein were reported in schizophrenia compared to healthy controls. In

schizophrenia, cytosolic PGES was elevated in the prefrontal cortex, but no changes were

observed in the temporal and occipital cortices140. COX-1 and 2, enzymes regulating the

production of prostaglandin E2, were not altered in the brains of schizophrenics140. No

changes in COX-2 mRNA expression were also observed in the dorsolateral prefrontal

cortex86, 141 and middle frontal gyrus139, while COX-1 mRNA expression was unchanged

in the dorsolateral prefrontal cortex141. Similarly, immunohistochemical analysis of the

hippocampus shows no differences in COX-2 positive cell density between schizophrenia

and healthy controls142. It should be noted that age did affect COX-1 and COX-2 mRNA

expression in schizophrenia, with older schizophrenia patients having increased COX-1

and decreased COX-2 mRNA expression141. ALOX5AP, a protein regulating 5-

lypoxygenase (LOX) activity, was found to have lower mRNA expression in the

temporal lobe of 66 schizophrenia patients compared to control patients98.

In contrast, Rao et al observed no changes in cytosolic PGES mRNA and protein

in the frontal cortex in schizophrenia. They also reported no changes in other arachidonic

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cascade enzymes, such as calcium-independent phospholipase (PLA)2, LOX5, LOX12,

LOX15 and microsomal PGES. They did, however, find COX-2 to be increased in

schizophrenia, along with cytosolic PLA2 and secretory PLA273.

A.4.6. Substance P

Substance P has been measured in postmortem brains of patients with

schizophrenia in 11 studies (Table 2-6).

One study evaluated preprotachykinin A, a precursor to substance P, and reported

that mRNA measured by in situ hybridization is decreased in the basal and lateral nuclei

of the amygdala, while no changes were measured in the temporal cortex143. Similarly,

the density of cells containing preprotachykinin A mRNA measured by in situ

hybridization is also not changed in the caudate and putamen in schizophrenia144.

Substance P density in multiple brain regions, including substantia nigra145, caudate

nucleus146, frontal cortex146, basal ganglia146 and hypothalamus146, detected by

radioimmunoassay, is not different in schizophrenia compared to healthy controls.

Psychosis without schizophrenia, such as affective disorder and unspecified functional

psychosis, did exhibit higher substance P protein concentrations146. An

immunohistochemical study also did not detect any changes in substance P in the basal

ganglia of 6 schizophrenia patients compared to unaffected controls147.

Two studies, however, have reported differences in substance P concentration in

schizophrenia. Toru et al. found a significant increase in substance P detected by

radioimmunoassay in the orbitofrontal cortex and hippocampus148, and in anti-psychotic

medication users in the thalamus, substantia nigra and temporal cortex148. Similarly,

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Roberts and colleagues found increased hippocampal substance P, but no changes were

seen in multiple brain regions including the amygdala, thalamus, basal ganglia, and

temporal, frontal, parietal and cingulate cortices149.

Five studies evaluated substance P binding to substance P neurokinin 1 receptor.

Autoradiography found no changes in neurokinin 1 receptor density in the putamen150,

anterior cingulate cortex151 and temporal cortex143. There was, however, an increase in

receptor density in the caudate150 and nucleus accumbens150. Immunohistochemical

analysis found similar increases in substance P receptor in the prefrontal cortex in

schizophrenia152, but not in the amygdala153. This lack of change in the amygdala cell

density expressing substance P receptor was consistent with mRNA expression153.

A.4.7. Other Markers

Multiple other markers associated with inflammation that do not fit the categories

mentioned above have also been measured in postmortem brains of schizophrenic

patients to evaluate a potential link between neuroinflammation and schizophrenia. We

identified 16 studies evaluating miscellaneous markers in postmortem brains in

schizophrenia. (Table 2-7)

ICAM-1 is a marker of neuroinflammation, associated with blood brain barrier

disruption. Thomas et al found no differences in ICAM-1 labeled cells in both the

dorsolateral prefrontal cortex and anterior cingulate cortex of 15 schizophrenia patients

of the Stanley Foundation Neuropathology Consortium compared to healthy controls154.

Four studies investigated the NF-κB pathway in postmortem schizophrenia brains.

Rao et al. measured increases in both NF-κB p50 and p65 subunits mRNA expression in

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the BA 10 of schizophrenia patients73. A second study evaluating the prefrontal cortex of

schizophrenics reported increased NF-κB1 and 2 mRNA expression155. However, 2

separate studies could not detect any differences in NF-κB2 expression in the frontal

cortex156 and NF-κB in the dorsolateral prefrontal cortex86 between schizophrenics and

healthy controls. Schnurri-2, a NF-κB site binding protein inhibiting downstream

transcription, has been reported to be decreased in the prefrontal cortex of schizophrenia

patients155.

Microarray analyses followed by q-PCR have proposed markers associated with

the immune system or inflammatory response being associated with schizophrenia. One

such marker, which was reported in 4 microarray analyses, is SERPINA3, a protease

inhibitor that is involved in inflammatory processes and connective tissue turnover. In the

dorsolateral prefrontal cortex, SERPINA3 mRNA expression was significantly higher in

the brains of schizophrenics compared to healthy controls86. The same group confirmed

this finding in a second cohort, finding increased SERPINA3 mRNA expression in the

medial frontal gyrus in schizophrenia, while not measuring any changes in IL-1RL1

expression139. Similar increases of SERPINA3 mRNA expression were reported in 2

other microarray studies in the frontal cortices of 5593 and 14157 schizophrenia patients

and were confirmed by q-PCR.

These two microarray studies also found elevated interferon-induced

transmembrane protein (IFITM)1, 2, and 3, proteins involved in regulation of the immune

response, mRNA expression in the prefrontal cortex in schizophrenia93, 157. A third study

confirmed the increased IFITM3 mRNA expression in the prefrontal cortex158. Similar

overexpression of IFITM1, 2 and 3 was observed by microarray and confirmed by q-PCR

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in the hippocampus of schizophrenic patients77. A fifth study targeted IFITM1 and 2/3

expression in a separate cohort of prefrontal cortices of schizophrenia patients and

reported an increase in both markers independent of antipsychotic use159.

Other markers that either increased or decreased in microarrays include CD163

and S100a8 and 9 in the hippocampus77, CHI3L1157 and GBP193 in the prefrontal cortex,

TNFSF8, 10, and 13 (although 8 and 13 were not significant in PCR validation) in the

dorsolateral prefrontal cortex160, 161, and TIMP1, TYROB and TNFSRF1A in the

temporal lobe98. However, unlike the decrease in TIMP1 mRNA expression measured in

the temporal lobe, TIMP1 protein concentration, measured by enzyme-linked

immunosorbent assay, was not changed in the prefrontal cortex in another study137.

Schmitt et al reported 6 out of 23 immune-related genes are down regulated in the

superior temporal cortex in schizophrenia. The 23 immune-related genes include

cytokines and microglial markers, discussed above, and other markers including LPL,

CFD, PTGER4 and EDG3 being downregulated and ITGA1, LCP1, LTC4S, MTHFD2,

CD84, GPX, IFI16 and SOD2 being unchanged94.

A.5. Discussion

Schizophrenia has been linked to neuroinflammation8-10. Schizophrenic patients

have been shown to have elevated cytokines in blood17, 18 and elevated microglia

activation in the brain as measured by PET analysis in some22, 23 but not all25, 26 reports.

This paper systematically reviewed the literature covering neuroinflammatory analyses in

postmortem brains from schizophrenic patients.

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Multiple studies evaluating neuroinflammation in postmortem brain samples

found evidence of neuroinflammation in schizophrenia. However, a definitive statement

cannot be made on whether neuroinflammation is present in schizophrenic postmortem

brain samples due to the large number of null studies. For example, out of 33 studies

evaluating GFAP, 21 studies did not find any effect of schizophrenia on GFAP

expression, while 6 studies found a decrease in GFAP and 6 studies had elevated GFAP

expression. Similarly, out of 34 studies that evaluated glial cell density, 25 studies found

no effect of schizophrenia, while 7 found a decrease in glial cells and 2 found an increase.

Variability is also observed for 4 microglial markers (HLA, CD11b, CD68, calprotectin),

where 11 studies had elevated expression of microglial markers, 8 found no differences

and 3 found a decrease. SERPINA3, a protease inhibitor that is involved in inflammatory

processes and connective tissue turnover, however, was elevated in the 4 studies, which

have reported on its mRNA expression. IFITM, a viral restriction factor, was also

reported elevated in 4 microarrays, and confirmed in 1 targeted study.

These discrepancies may be explained, at least partly, by the heterogeneity in

study designs across studies. One of the heterogeneous variable across studies is brain

region analyzed. For example, studies evaluating GFAP expression have analyzed 34

brain regions, including the hippocampus and prefrontal, entorhinal, orbitofrontal, and

cingulate cortices among others. While all 5 studies analyzing GFAP expression in the

entorhinal cortex found no differences in schizophrenia, 4 of the 13 studies evaluating

GFAP expression in the frontal cortex, prefrontal cortex or dorsolateral prefrontal cortex

(BA 9, 10, or 46) identified differences between schizophrenia and healthy controls.

However, classification of the frontal cortices varied between studies and may explain

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differing results. Moreover, 4 out of 6 studies examining the cingulate cortex, subgenual

cingulate cortex or anterior cingulate cortex found significant changes in GFAP in

schizophrenia. It is possible that certain brain regions, such as the cingulate cortex, are

more susceptible to change in schizophrenia compared to other regions such as the

entorhinal cortex. Nevertheless, despite more studies pointing to a decrease in GFAP

expression in the cingulate cortex in schizophrenia, not all studies show decreases despite

evaluating the same brain region and marker53, 58.

Consideration of the cortical layer in which the markers are measured may be

needed in order to tease out the differences across studies. Many studies found layer

specific effects in various brain regions and markers. For example, in 2 studies, GFAP

expression was increased solely in layer V of the dorsolateral prefrontal cortex70 and

layer I in subgenual cingulate cortex67. This could explain differences across studies

measuring GFAP in the whole prefrontal cortex mentioned above. Similarly, layer

specific effects of schizophrenia on glial cell density measured by cresyl violet were

observed in several studies evaluating the motor cortex (layer III), planum temporale

(layer IV), cingulate cortex (layer IV) and dorsolateral prefrontal cortex (layer V).

Differences in methodological approaches also warrant consideration when

evaluating the results of the studies mentioned above. Stereological analysis, an unbiased

cell counting method, was applied to approximately half of the studies measuring glial

cells. Only one study utilizing stereology measured differences in glial cell density, while

7 studies using other methods reported differences. However, the use of stereology is not

always clear in the methods section and therefore the results above should be considered

with caution. Similarly, double labeling could be utilized to detect different subtypes of

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cells. However, few studies in this review utilized double labeling, thus the lack of

change in cell densities may not reflect possible changes in cell subtypes.

Another variable that may contribute to the heterogeneous results is the stage of

the disorder. By separating paranoid schizophrenia from residual schizophrenia,

differences in S100b positive cells were observed79. Microglia are also elevated in

paranoid schizophrenia, where HLA-DR positive cell density is higher in paranoid

schizophrenia compared to residual schizophrenia88. Moreover, differences in gliosis

score are seen between early onset and late onset schizophrenia135. Similarly, the 3

patients with microgliosis in the study by Bayer and colleague were all defined to have

late onset schizophrenia85.

Suicide is common in schizophrenia. This is important to consider as postmortem

brains from suicide victims may present elevated proinflammatory cytokines162, 163. This

is in agreement with Steiner and colleagues where the 2 schizophrenia patients that

committed suicide had the highest HLA-DR positive cell density91. When accounting for

suicide victims, the same group found no differences between diagnosis groups. They

did, however, find a relation between suicide and HLA-DR positive cells92. Similarly,

higher GFAP cell density is elevated in the dorsolateral prefrontal cortex of suicide

victims compared to non-suicide schizophrenic patients55. This effect on GFAP, in the

dorsolateral prefrontal cortex of suicide victims, however, was not seen in another study

measuring GFAP by western blot65. No effect of suicide was also observed for ICAM-1

expression154. This is also an important consideration for control group selection. Tooney

et al. found an effect of schizophrenia on neurokinin-1 receptor compared to a control

group that contained suicide victims, which may potentially confound the results152.

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While a few studies considered the effect of suicide on their measurements, many studies

do not report this data or include it in their statistical analysis, making it a limitation and

should be considered in future studies.

Several other confounding factors have been associated with potential effects on

neuroinflammatory markers in schizophrenia in postmortem brains. Antipsychotics have

been associated with modulation of inflammation164. Typical antipsychotics generally

reduce pro-inflammatory markers while atypical antipsychotics generally increase

them164, 165. In our systematic review, antipsychotics were reported to raise GFAP53, 71, 74,

substance P148 and HLA53. No effect of medication, however, was seen on IL-1β136. This

is important to note, as not all studies measured antipsychotic levels at time of death or

corrected for this potential confounder. Moreover, even when measured, separation of

typical and atypical antipsychotics was not considered in the statistical analysis. Also,

control subjects would not have been exposed to antipsychotic medication, potentially

creating a confounder between controls and the experimental group. Similarly, age is

positively correlated to the expression of GFAP66, S100b58 and substance P receptor

binding151. Lifestyle choices, such as smoking and alcohol abuse, may also contribute to

neuroinflammation. In one study, decreases in MHC I observed in the dorsolateral

prefrontal cortex of non-smoking schizophrenia patients were no longer apparent in the

smoking population100. Interestingly, lifestyle choices and antipsychotic use are also risk

factors for the development of type II diabetes166, which is more prevalent in

schizophrenia167 and has been associated with neuroinflammation168, 169. Although not

reported in the studies in this review, it would be of interest for future studies to

investigate a potential link between diabetes in schizophrenia and neuroinflammation.

214

The source of the brains also needs consideration. Several brain banks produced

multiple studies utilizing several different brain regions and markers. Moreover, the same

brain regions could be used for multiple studies. Brain banks may have different

diagnosis methods, inclusion and exclusion criteria, storage, and demographics among

many other variables. Thus, it is possible that the results may be biased by the samples

available at these banks. For example, the 33 studies on GFAP reported in this paper

were generated from brains from 15 separate brain banks. Of those 33 studies, 6 studies

reported a decrease in GFAP. Of those 6 studies, 2 studies utilized the Stanley

Foundation Neuropathology Consortium while 3 others used the Corsellis Brain

Collection.

Despite the heterogeneity across studies, the expression of both SERPINA3 and

IFITM was repeatedly found to be increased in microarray studies. SERPINA3, a

member of the serine protein inhibitor family, is an acute-phase protein which increases

during inflammatory episodes170 and is expressed in reactive astrocytes171. SERPINA3

has previously been linked with decreased age of onset of Alzheimer’s symptoms172.

Moreover, SERPINA3 expression is correlated with GFAP positive cells in Alzheimer’s

disease173. Patients with multiple sclerosis have elevated SERPINA3 CFS

concentration174. In depression, no association was reported between blood levels of

SERPINA3 and symptoms175. IFITM, on the other hand, is an immune-related protein

involved in viral replication. In animal models of inflammation, IFITM1 is increased in

the cortex of mice lacking the NF-κB site binding protein Schnurri-2176. Similarly,

IFITM1 and 3 expression is upregulated in the hippocampus following centrally

215

administered lipopolysaccharide injection177, suggesting its involvement in

neuroinflammatory processes.

In conclusion, while the majority of studies note a lack of change in

neuroinflammatory markers in postmortem brain samples of patients with schizophrenia,

there are still multiple studies indicating either increases or decreases in

neuroinflammatory markers. Although approximately 70% of studies evaluating

astrocytes or glial cells in schizophrenia found no change, there were still approximately

30% of studies showing either an increase or decrease in astrocytic markers and glial cell

density. The changes in microglial markers in schizophrenia is more variable across

studies, with approximately 45% of studies showing an increase and 40% of studies

showing no change. Similarly, pro-inflammatory cytokine concentration in the

postmortem schizophrenia brain is also variable across studies, with studies showing both

elevated and decreased cytokine levels in schizophrenia. The cause of this heterogeneity

in results is not clear at the moment, but may be due to several factors including brain

region measured, stage of disorder, source of the brain and medication. Despite this

heterogeneity, microarray analyses have consistently indicated markers such as

SERPINA3 and IFITM to be elevated in schizophrenia. Future studies should consider

these potential sources of heterogeneity when measuring neuroinflammatory markers in

postmortem brain samples of schizophrenia patients.

A.6. Acknowledgements

MOT holds a studentship from the Natural Sciences and Engineering Research

Council of Canada (PGSD-442373-2013). RPB acknowledges funding from the

216

Canadian Institutes of Health Research (#303157) and holds a Canada Research Chair in

Brain Lipid Metabolism. The authors would also like to acknowledge Dr. John

Sievenpiper for the helpful discussions regarding systematic reviews.

A.7. Conflict of Interest

The authors declare no conflict of interest.

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Figure A-‐1. Systematic Search Results.

Articles yielded from search of databases (n=5385)

Full article assessment for eligibility (n=217)

Excluded base on title and abstract (n=5168)

Articles included (n=115)

Excluded (n=102): Did not measure neuroinflammatory markers (n=69) Wrong study design (in vivo, in vitro, clinical, microarray, ect) (n=27) No healthy control (n=3) Not in English (n=1) Not schizophrenia (n=1) Duplicated study (n=1)

Total articles included and extracted (n=119)

Articles found through other sources (n=4)

235

author brain bank n sex (m/f) age

death from suicide Brain region technique

inflammatory markers results

Altshuler 2010 SFNC scz 9 ctr 14

scz 5/4 ctr 8/6

scz 45 ctr 47 scz 3

basolateral nucleus of the amygdala IHC GFAP ↔

Arnold 1996 prospective study

*scz 7 # scz + d 14 ctr 12

scz 3/4 scz + d 6/8 ctr 5/7

scz 74 scz + d 82 ctr 75 NA

EC*, SB#, CA3*, CA1*, DG*, MFC*, OFC#, VC* IHC GFAP#, VIM* ↔*↑#

Arnold 1998 prospective study scz 23 ctr 14

scz 8/15 ctr 6/8

scz 80 ctr 75 NA

EC (BA 28) CA1 HPC, SB MFC (BA9 and 46), OFC (BA11), CL (BA17) IHC GFAP ↔

Barley 2009 SFNC

Varies across brain regions

Varies across brain regions

Varies across brain regions NA AVN, PU, IC, MTN PCR

GFAP ALDH1 ↑

Beasley 2009 NYSPIBC scz 15 ctr 13

scz 9/6 ctr 10/3

scz 54 ctr 51 none

anterior limb of internal capsule ELISA GFAP ↔

Casanova 1990 NC scz 6 ctr 7

scz 4/2 ctr 4/3

scz 39 ctr 61 NA DG, PP

Holzer’s Technique astrocytes ↔

Catts 2014 NSWTRC scz 37 ctr 37

scz 24/13 ctr 30/7

scz 51 ctr 51 scz 8 DLPFC (BA46) PCR, IHC, WB GFAP ↔

Damadzic 2001 1) CBDBNIMH 2) SFNC

study 1) scz 7 ctr 8 study 2) scz 14 ctr 15

study 1) scz 3/4 ctr 3/5 study 2) scz 9/5 ctr 9/6

study 1 scz 49 ctr 47 study 2 scz 46 ctr 48

study 1 scz 3 ctr 1 study 2 scz 3 EC IHC GFAP ↔

Dean 2006 NA scz 20 ctr 20

scz 13/7 ctr 13/7

scz 56 ctr 56 NA BA9, 10, 40, 46 WB, PCR s100b, GFAP ↔

Falkai 1999 DBC scz 33 ctr 26

scz 14/19 ctr 13/13

scz 54 ctr 53 scz 4

PMC, SB, EC, IH, SVZ3V IHC GFAP ↔

Falke 2000 Prospective study scz 12 ctr 11

scz 3/9 ctr 7/4

Scz 81 ctr 78 NA MTN, CT IHC GFAP ↔

Fatemi 2004 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 44 ctr 48 scz 4 lateral CB WB GFAP ↔

Feresten 2013 SMRIAC scz 35 ctr 35

scz 26/9 ctr 26/9

scz 43 ctr 44 scz 7 DLPFC (BA9) WB

GFAP#, VIM*, ALDH1L1*, EAAT* ↔* ↑#

Hercher 2014 SMRIAC scz 20 ctr 20

scz 13/7 ctr 14/6

scz 45 ctr 45 scz 4 DLPFC (BA9) IHC GFAP ↔

Hwang 2013 SFNC, SMRIAC scz 33 scz 23/10 scz 44 NA HPC PCR, IHC APOL1 ↑

236

ctr 34 ctr 23/11 ctr 46 ADORA2A

Karson 1993 DCMEO scz 25 ctr 28

scz 22/3 ctr 22/6

scz 34 ctr 35

scz 16 ctr 8

FC, TC, OC, CB, TH, pons (n= 8-23/region) WB GFAP ↔

Karson 1999 NA scz 14 ctr 12

scz 13/1 ctr 11/1

scz 65 ctr 67 NA PFC (BA10)

WB, northern blot GFAP ↔

Katsel 2011 NA scz 18 ctr 21

scz 10/8 ctr 10/11

scz 78 ctr 77 scz 0

cingulate cortex (BA24/32) PCR

GFAP #, s100b*, VIM#, EAAT2*, ALDH1L1#, AQP4*, DIO*, GS*, THBS4*, GL#

↓*↔# (deep layer only)

Kolomeets 2010 ADMPH scz 19 ctr 16

scz 11/8 ctr 11/5

scz 54 ctr 56 NA HPC

electron microscope astrocytes ↔

Markova 2000 NA scz 12 ctr 10 NA

scz 62 ctr NA NA olfactory tubercle IHC GFAP ↑

Pakkenberg 1990 NA scz 12 ctr 12

scz 8/4 ctr 66

scz 63 ctr 62 NA

MTN*, AG#, NAS*, PL# Nissl astrocytes ↓*↔#

Pantazopoulos 2010 HBTRC

scz 11 ctr 15

scz 7/4 ctr 10/5

scz 62 ctr 66 scz 1 AG, EC IHC GFAP ↔

Perrone-Bizzozero 1996 HBTRC

scz 17 ctr 18

scz 17/0 ctr 18/0

scz 44 ctr 48

scz 4 ctr 2

VC (BA17,20) PFC (BA9,10) WB GFAP ↔

Radewicz 2000 Prospective study scz 12 ctr 11 NA

scz 80 ctr 72 NA

DLPFC (BA9), ACC (BA24), superior TC (BA22) IHC GFAP ↔

Rajkowska 2003 CCCO scz 9 ctr 15

scz 2/7 ctr 10/5

scz 47 ctr 47 scz 3 DLPFC (BA9) IHC GFAP ↑(layer V only)

Rao 2013 HBTRC scz 10 ctr 10

scz 6/4 ctr 7/3

scz 59 ctr 49 NA FC (BA10) IHC, PCR, WB GFAP ↑

Roberts 1986 VIBR scz 5 ctr 7

scz 1/4 ctr 4/3

scz 39 ctr 51 NA

TL, PC, PU, CT, AG, HPC, TH IHC GFAP ↔

Roberts 1987 runwell series 1 brain collection

scz 18 ctr 12

scz 14/4 ctr 9/3

scz 69. ctr 55 NA TL IHC GFAP ↔

Schmitt 2009 DBC scz 10 ctr 10

scz 5/5 ctr 5/5

scz 55 ctr 50 scz 1 CA1,2/3,4, SB cresyl violet astrocytes ↔

Steffek 2008 MSMC, BVAMC scz 23 ctr 27

scz 16/7 ctr 14/13

scz 72 ctr 79 none

DLPFC#, VC#, ACC*, HPC#, temporal gyrus# WB GFAP ↓*↔#

Steiner 2008 MBC

*p scz 9 #r scz 9 ctr 16

p scz 5/4 r scz 4/5 ctr 7/9

p scz 56 r scz 54 ctr 56

p scz 3 r scz 2

ACC*, DLPFC#, OFC #, sTC#, HPC#, MTN# IHC s100b ↑*↔#

Steiner 2014 WMSH, HUIN scz 9 ctr 7

scz 5/4 ctr 5/2

scz 68 ctr 65 none CO WB, MS s100b ↓

Stevens 1988 VIBR scz 5 NA NA NA CT, PVN IHC GFAP ↔

237

ctr 7

Tkachev 2003 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 44 ctr 48 scz 4 PFC (BA9) PCR GFAP ↔

Toro 2006 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 45 ctr 48 scz 4

PFC* (BA9,32,46) OFC# (BA11/47) IAR GFAP ↑*↓#

Uranova 2010 MHRC scz 26 ctr 26

scz 11/15 ctr 21/5

scz 53 ctr 52 NA

PFC (BA10) and VC (BA17)

electron microscopy

astrocytic end-feet

↑(except for VC of non p scz)

Williams 2013 CC scz 10 ctr 19

scz 5/5 ctr 11/8

scz 58 ctr 66 scz 1

subgenual cingulate cortex*, CO IHC GFAP ↓ (only in layer I*)


Scz 6/7 ctr 4/12

scz 57 ctr 55 scz 2 nucleus basalis IHC GFAP ↔


scz 7/4 ctr 9/4

scz 60 ctr 52 scz 2 substantia nigra IHC GFAP ↓


scz 5/5 ctr 11/8

scz 58 ctr 66 scz 1

subgenual cingulate cortex IHC GFAP ↓

Webster 2001 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 44 ctr 48 scz 4 DLPFC, HPC IHC

phosphorylated GFAP

↔ (except DLPFC blood vessel labeling)

Webster 2005 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 45 ctr 48 scz 4 ACC (BA24)

riboprobe and in situ hybridization GFAP

↓(white matter only)

Table A-1. Astrocytes in postmortem schizophrenia brain. ACC, anterior cingulate cortex; ADMPH, Anatomical Department of Moscow Psychiatric Hospital; ADORA2A, adenosine A2A receptor; AG, amygdala; ALDH, aldehyde dehydrogenase; APOL, apolipoprotein; AQP, aquaporin; AVN, anteroventral nucleus; BA, Brodmann area; BVAMC, Bronx Veterans Administration Medical Center; CA, cornu ammonis; CB, cerebellum; CBDBNIMH, Clinical Brain Disorder Branch at the National Institute of Mental Health; CC, Corsellis Collection; CL, calcarine cortex; CO, corpus callosum; CT; caudate; ctr, control; CCCO, Cuyahoga Country Coroner’s Office; d, dementia; DBC; Dusseldorf Brain Collection, DCMEO, District of Columbia Medical Examiner’s Office; DG, dentate gyrus; DIO, diodinase; DLFPC, dorsolateral prefrontal cortex; EAAT, excitatory amino acid transporter; EC, entorhinal cortex; ELISA, enzyme-linked immunoadsorbent assay; FC, frontal cortex; GFAP, glial fibrillary acidic protein; GL, phosphate-activated glutaminase; GS, glutamine synthase; HBTRC, Harvard Brain Tissue Resource Centre; HPC, hippocampus; HUIN, Heidelberg University Institute of Neuropatholagy; IAR, immunoautoradiography; IC, internal capsule; IH, inferior horn; IHC, immunohistochemistry; MBC, Magdeburg Brain Collection; MHRC, Mental Health Research Centre; MFC, midfrontal cortex; MS, mass spectrometry; MSMC, Mount Sinai Medical Centre; MTN, mediodorsal thalamic nucleus; NA, not available; NC, Neuman Collection; NSWTRC, New South Wales Tissue Resource Centre; NYSPIBC, New York State Psychiatric Institute Brain Collection; OC, occipital cortex; OFC, orbitofrontal cortex; PC, parietal cortex; PCR, polymerase chain reaction; PFC, prefrontal cortex; PMC, premotor cortex; PP, perforant path; PU, putamen; PVN, paraventricular nucleus; SB, subiculum scz, schizophrenia; scz (p), paranoid schizophrenia, scz (r). residual schizophrenia; SFNC, Stanley Foundation Neuropathology Consortium; SMRIAC, Stanley Medical Research Institute Array Collection; ST, striatum; SVZ, subventricular zone; TC, temporal cortex; TH, thalamus; THBS, thrombospondin; TL, Temporal lobe; VBBN, Victorian Brain Bank Network; VC, visual cortex; VIBR; Vogt Institute of Brain Research; VIM, vimentin; WB, western blot; WMSH, Wiesloch Mental State Hospital

238


death from suicide brain region technique


Arnold 1998 prospective study scz 23 ctr 14

scz 8/15 ctr 6/8

scz 80 ctr 75 NA

EC (BA 28) CA1, SB, MFC (BA9 and 46), OFC (BA11), CL (BA17) IHC CD68 ↔

Bayer 1999 INUBMC, INMD scz 14 ctr 13

scz 3/11 ctr 8/5

scz 64 ctr 58 NA FC, HPC IHC HLA-DR ↑

Busse 2012 MBC

scz (p) 10* scz (r) 7 ctr 11

scz (p) 5/5 scz (r) 4/3 ctr 6/5

scz (p) 50 scz (r) 56 ctr 56 scz 5# HPC IHC HLA-DR ↑*#

Comte 2012 SFNC Scz 15 ctr 15

scz 9/6 ctr 9/6

scz 44 ctr 48 scz 4 SVZ IHC MHC II ↔

Connor 2009 HBTRC scz 22 ctr 45

scz 9/13 ctr 24/21

scz 68 ctr 70 NA ACC (BA24), DLPFC IHC Iba1 ↔

Durrenberger 2015 BBPDGU

scz 10 ctr 10

scz 5/5 ctr 5/5

scz 66 ctr 61 NA temporal lobe (BA22) PCR

HLA-DRA, HLA-DRB4 ↓.

Falke 2000 Prospective study scz 12 ctr 11

scz 3/9 ctr 7/4

scz 81 ctr 78 NA MTN, CT IHC

CD68 ↔

Fillman 2013 NSWTRC scz 37 ctr 37

scz 24/13 ctr 30/7

scz 53 ctr 51 NA DLPFC (BA46) WB, IHC

HLA-DR/DP/DQ ↑

Foster 2006 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 44 ctr 48 scz 4 DLPFC (BA9) ELISA, IHC

Calprotectin* CD68# ↑*↔#

Gos 2014 MBC scz 13 ctr 12

scz 7/6 ctr 6/6

scz 51 ctr 49 scz 2 CA1*,2,3, DG IHC

HLA-DR#, quinolinic acid* ↓*↔#

Hercher 2014 SMRIAC scz 20 ctr 20

scz 13/7 ctr 14/6

scz 45 ctr 45.3 scz 4 DLPFC (BA9)

IHC, cresyl violet Iba1 ↔

Kano 2011 SMRIAC scz 35 ctr 35

scz 26/9 ctr 26/9

scz 43 ctr 44 scz 7 DLFPC*, OFC# WB MHC I ↓*,↔#

Nakatani 2006 VIFM scz 7 ctr 7

scz 3/4 ctr 3/4

scz 61 ctr 61 scz 1

DLPFC (BA46), PC (BA40) PCR HLA-DRA ↔

Radewicz 2000 Prospective study scz 12 ctr 11 NA

scz 80 ctr 72 NA

DLPFC (BA9)*, ACC (BA24)#, superior TC (BA22)* IHC HLA-DR ↑*↔#


scz 6/4 ctr 7/3

scz 59 ctr 49 NA FC (BA10) IHC, PCR, WB

HLA-DR, CD11b ↑

Saetre 2007 SFNC, HBTRC, MBB

55 per group NA

scz 58 ctr 56 NA

FC (BA8 and 9) superior frontal gyrus PCR HLA-A ↔

239

Schmitt 2011 BBPDGU 10 per group

scz 5/5 ctr 8/2

scz 66 ctr 61 NA TC (BA22) PCR

HLA-DRB3, HLA-DPA1 ↔

Sinkus 2013 SRCBB scz 42 ctr 47

scz 28/14 ctr 33/14

scz 51 ctr 53

scz 0 ctr 1 HPC PCR

HLA-A#, HLA-B* ↑*↔#

Steiner 2006 MBC scz 16* ctr 16

scz 8/8 ctr 8/8

scz 55 ctr 58 scz 2#

HPC, ACC, DLPFC, MTN IHC HLA-DR ↔*↑#

Steiner 2008 MBC scz 16* ctr 10

scz 7/9 ctr 5/5

scz 54 ctr 55 scz 6 #

HPC*, DLPFC#, ACC#, MTN# IHC HLA-DR ↔*↑#

Wierzba-Bobrowicz 2004 NA

scz 12 ctr 7

scz 0/12 ctr 0/6

scz 59 ctr 56 NA

Frontal lobe with cingulate gyrus (BA24) IHC

HLA-DP/DQ/DR ↑

Wierzba-Bobrowicz 2005 NA

scz 9 ctr 6 NA

scz 56 ctr 56 NA

gyrus temporal inferior (BA20), gyrus cinguli (BA24) IHC

HLA-DP/DQ/DR ↑

Table A-2. Microglia in postmortem schizophrenia brain. ACC, anterior cingulate cortex; BA, Brodmann area; BBPDGU, Brain Bank for Psychiatric Diseases at the Gottingen University; CA, cornu ammonis; CD, cluster of differentiation; CL, calcarine cortex; CT, caudate; ctr, control; DG, dentate gyrus; DLFPC, dorsolateral prefrontal cortex; EC, entorhinal cortex; ELISA; enzyme-linked immunoadsorbent assay; FC, frontal cortex; HBTRC, Harvard Brain Tissue Resource Centre; HLA, Human Leukocyte Antigen; HPC, hippocampus; IHC, immunohistochemistry; Iba, ionized calcium-binding adaptor molecule; INMD, Institute for Nervous and Mental Diseases; INUBMC, Institute of Neuropathology, University of Bonn Medical Centre; MBB, Maudsley Brain Bank; MBC, Magdeburg Brain Collection; MHC, major histocompatibility complex; MFC, midfrontal cortex; MTN, mediodorsal thalamic nucleus; NA, not available; NSWTRC, New South Wales Tissue Resource Centre; OFC, orbitofrontal cortex; PC, parietal cortex; PCR, polymerase chain reaction; SB, subiculum; scz, schizophrenia; scz (p), paranoid schizophrenia, scz (r). residual schizophrenia; SFNC, Stanley Foundation Neuropathology Consortium; SMRIAC, Stanley Medical Research Institute Array Collection; SRCBB, Schizophrenia Research Center Brain Bank; SVZ, subventricular zone; TC, temporal cortex; VIFM, Victorian Institute of Forensic Medicine; WB, western blot

240




Beasley 2005 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 44 ctr 48 scz 4 planum temporal cresyl violet glia ↔

Beasley 2009 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 44 ctr 48 scz 4 planum temporal cresyl violet glia ↓

Beckmann 1997 WBC scz 9 ctr 9

scz 9/0 ctr 9/0

scz 55 ctr 52 scz 1 ST, PU, NAS, CT gallocyanin glia ↔

Benes 1986 HBTRC scz 10 ctr 10 NA

scz 60 ctr 66 scz 1

PFC (BA10)#, motor cortex (BA4)*, cingulate cortex (BA24)# cresyl violet glia

↓* (only layer III) ↔#

Benes 1991 HBTRC

scz 9 scz + md 9 ctr 12 NA

scz 53 scz + md 49 ctr 59 NA

PFC (BA10) ACC (BA24) cresyl violet glia ↔

Benes 2001 HBTRC scz 11 ctr 12

scz 7/4 ctr 7/5

scz 52 ctr 58 scz 5 ACC (BA24) cresyl violet glia ↔

Bezchlibnyk 2007 SFNC scz 13 ctr 15

scz 8/5 ctr 9/6

scz 47 ctr 48 NA AG Nissl glia ↔

Bogerts 1983 VIBR scz 6 ctr 9

scz 2/6 ctr 5/4

scz 51 scz 43 NA SN cresyl violet glia ↔ (reduction in size)

Brauch 2006 SNFC scz 13 ctr 14 NA

scz 46 ctr 47 NA TC cresyl violet glia ↓

Bruton 1990 NA scz 48 ctr 56 NA NA NA FC, PC, TC

Holzer’s Technique glia ↑

Chana 2003 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 45 ctr 48 scz 7 ACC (BA24) cresyl violet glia ↔

Chana 2008 SFNC scz 14 ctr 15 NA NA NA MTN NA glia ↔

Cotter 2001 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 45 ctr 48 scz 7 ACC cresyl violet glia ↔


scz 9/6 ctr 9/6

scz 45 ctr 48 scz 7 DLFPC (BA9, 46) cresyl violet glia ↓ (only layer V)

241


scz 9/6 ctr 9/6

scz 44 ctr 48 scz 4

Heschl’s gyrus (BA41) (layer 3 and 5) cresyl violet glia ↔


scz 9/6 ctr 9/6

scz 45 ctr 48 scz 7 OFC cresyl violet glia ↔

Crow 1989 NA scz 22 ctr 26 NA NA NA temporal horn

Holzer’s Technique, IHC

Glia, diazepam binding inhibitor-like ↔

Cullen 2006 NA scz 10 ctr 10

scz 6/4 ctr 6/4

scz 60 ctr 60 NA frontal gyrus (BA9) cresyl violet glia ↔

Di Rosa 2009 NA scz 11 ctr 13

scz 6/5 ctr 7/6

scz 66 ctr 68 scz 1 fusiform gyrus cresyl violet glia ↔

Falkai 1986 VIBR scz 13 ctr 11

scz 2/11 ctr 7/4

scz 43 ctr 43 scz 1

CA1#, 3*, 4,* PSB,* SB# Nissl glia ↓*, ↔#

Falkai 1988 VIBR scz 13 ctr 11

scz 11/2 ctr 7/4

scz 43 ctr 43 NA EC Nissl glia ↔

Hoistad 2013 NA scz 13 ctr 13

scz 13/0 ctr 13/0

scz 52 ctr 52 scz 3 ACC (BA24) gallocyanin glia ↔

Jonsson 1997 NA scz 4 ctr 8

scz 4/0 ctr 8/0

scz 82 ctr 77 NA HPC cresyl violet glia ↔

Kurumaji 1997 NA scz 13 ctr 10

scz 8/5 ctr 7/3

scz 60 ctr 67 NA

PFC#, TC#, OC*, PC*, PU*, CT#, SN#, PL# and TH#

receptor binding assay

[3H] PK11195 binding (gliosis) ↓*, ↔#

Nasrallah 1983 NIMH

escz 11 lscz 7 ctr 11 Na

escz 66 lscz 73 ctr 64 NA CO

hematoxylin-eosin stain glia ↔

Ongur 1998 SFNC scz 11 ctr 11

scz 7/3 ctr 7/4

scz 40 ctr 39 scz 4 sg24 Nissl glia ↔

Pennington 2008 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 46 ctr 48 scz 4 insular cortex cresyl violet glia ↔

Rajkowska 1998 HTBRC, NIMH, UZ

scz 9 ctr 10

scz 7/2 ctr 6/4

scz 41 ctr 44 scz 5

PFC (BA9), OC (BA17) Nissl glia ↔

Selemon 1995 HTBRC, NIMH, UZ

scz 16 ctr 19

scz 12/4 ctr 10/9

scz 40 ctr 47 scz 10

PFC (BA 9), OC (BA17) Nissl glia ↔

Selemon 1998 HTBRC, UZ scz 9 ctr 10

scz 6/3 ctr 7/3

scz 44 ctr 48 scz 5 PFC (BA9,46) Nissl glia ↔

242

Selemon 2003 HBTRC, NIMH scz 9 ctr 14

scz 6/3 ctr 10/4

scz 56 ctr 54 scz 3

FC (BA44) and DLPFC (BA9) Nissl glia ↔

Selemon 2007 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 45 ctr 48 scz 4

lateral geniculate nucleus Nissl glia ↔

Stark 2004 NA scz 12 ctr 14

scz 7/5 ctr 7/7

scz 70 ctr 69 scz 1 ACC (BA24)*, BA32# Giemsa stain glia ↓*,↔#

Stevens 1982 SEH scz 28 ctr 18

scz 13/15 ctr 11/7

scz 41 ctr 37 NA multiple brain regions

Holzer’s Technique glia ↑

Table A-3. Undifferentiated glial cells and postmortem schizophrenia brain. ACC, anterior cingulate cortex; AG, amygdala; BA, Brodmann area; CA, cornu ammonis; CO, corpus callosum; CT; caudate; ctr, control; DBC; Dusseldorf Brain Collection, DLFPC; dorsolateral prefrontal cortex; EC, entorhinal cortex; escz, early onset schizophrenia; FC, frontal cortex; HBTRC; Harvard Brain Tissue Resource Centre; HPC, hippocampus; lscz; late onset schizophrenia; md, mood disturbance; MTN, mediodorsal thalamic nucleus; NA, not available; NAS, nucleus accumbens; OC, occipital cortex; OFC, orbitofrontal cortex; PC, parietal cortex; PFC, prefrontal cortex; PL, pallidum; PSB, presubiculum; PU, putamen; SB, subiculum; scz, schizophrenia; SFNC; Stanley Foundation Neuropathology Consortium; sg, subgenual prefrontal cortex; SN; substantia nigra; ST, striatum; SEH, ST. Elizabeth's Hospital; TC, temporal cortex; TH, thalamus; UZ, University of Zagreb; VIBR, Vogt Institute of Brain Research; WBC, Würzburg Brain Collection

243




Dean 2013 VBBN scz 19 ctr 20

scz 15/4 ctr 16/4

scz 48 ctr 47 scz 8

DLPFC (BA 46) ACC (BA 24) WB, PCR

sTNF-α#, tmTNF-α#, TNF-α receptor1*,2# ↑*↔#


scz 10 ctr 10

scz 5/5 ctr 5/5

scz 66 ctr 61 NA TL (BA22) PCR IL13RA1 ↓.


scz 24/13 ctr 30/7

scz 51.3 ctr 51.1 NA DLPFC (BA46) PCR, WB, IHC

IL-8*, IL-6*, IL-1β# ↑*↔#

Fillman 2014 SMRIAC scz 35 ctr 35

scz 26/9 ctr 26/9

scz 42.6 ctr 44.2 scz 7 middle frontal gyrus PCR

IL6#, IL8*, IL1β#, IL18#, TNF-α# ↓*↔#

Harris 2012 SMRIAC scz 35 ctr 33

scz 26/9 ctr 25/8

scz 42.6 ctr 44.8 NA BA10 ELISA IFN-γ ↑

Nakatani 2006 VIFM scz 7 ctr 7

scz 3/4 ctr 3/4

scz 61.4 ctr 61.4 scz 1

DLPFC (BA46), PC (BA40) PCR CCL3 ↓


scz 6/4 ctr 7/3

scz 59 ctr 49 NA FC (BA10)

PCR, WB TNF-α, IL-1β ↑

Schmitt 2011 BBPDGU scz 10 ctr 10

scz 5/5 ctr 8/2

scz 66.3 ctr 61.2 NA TC (BA22) PCR

IL-8*, IL-1α*, CCL2#, IL-1β# ↓*↔#

Toyooka 2003 NA scz 22 ctr 23

scz 16/6 ctr 14/9

scz 59.29 ctr 66.39 NA

PFC (BA 46)*, posterior hypothalamic region, PC (BA 1-3), PU PCR, WB

ΙL−1β #, IL-1RA* ↓*↔#

Volk 2015 ACOME scz 62 ctr 62

scz 47/15 ctr 47/15

scz 48 ctr 49 scz 16 PFC (BA9) PCR

IL-1β∗, IL-6*, IL-8#, IFN-β∗ ↑*↔#

Table A-4. Cytokine and chemokine in postmortem schizophrenia brain. ACC, anterior cingulate cortex; BA, ACOME, Allegheny County Office of the Medical Examiner; Brodmann area; BBPDGU, Brain Bank for Psychiatric Diseases at the Gottingen University, CCL, chemokine (c-c motif) ligand; CCR, chemokine (c-c motif) receptor; ctr, control; DLFPC; dorsolateral prefrontal cortex; ELISA; enzyme-linked immunoadsorbent assay; FC, frontal cortex; HBTRC; Harvard Brain Tissue Resource Centre; IHC, IFN, interferon; IL, interleukin; NA, not available; NSWTRC; New South Wales Tissue Resource Centre; PC, parietal cortex; PFC, prefrontal cortex; PU, putamen; PCR, polymerase chain reaction; scz, schizophrenia; SMRIAC, Stanley Medical Research Institute Array Collection; sTNF, soluble TNF; TC, temporal cortex; TL, temporal lobe; tmTNF, transmembrane TNF; TNF, Tumor necrosis factor; VBBN, Victorian Brain Bank Network; VIFM, Victorian Institute of Forensic Medicine; WB, western blot

244





scz 10 ctr 10

scz 5/5 ctr 5/5

scz 66 ctr 61 NA temporal lobe (BA22) PCR ALOX5AP, ↓.


scz 24/13 ctr 30/7

scz 51 ctr 51 NA DLPFC (BA46) PCR PTGS2 ↔


scz 26/9 ctr 26/9

scz 43 ctr 44 scz 7 middle frontal gyrus PCR PTGS2 ↔

Maida 2006 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 45 ctr 48 scz 4

PFC (BA8)*, TC (BA21 and BA22)# OC (BA18)# WB, IHC

COX-1#, COX-2 #, cPGE2* ↓*↔#


scz 6/4 ctr 7/3


PCR, WB

COX-1#, COX-2*, LOX5#, LOX12#, LOX15#, cPLA2*, sPLA2*, iPLA2#, cPGES#, mPGES# ↑*↔#

Tang 2012 VBBN scz 38 ctr 38 NA

scz 43 ctr 44 NA DLPFC (BA46) PCR

PTGS1, PTGS2, PTGER3, CYP4Z1 ↔

Yokota 2004 NA scz 17 ctr 22

scz 12/5 ctr 13/9

scz 69 ctr 71 scz 0 HPC IHC COX-2 ↔

Table A-5. Arachidonic acid cascade in postmortem schizophrenia brain. ALOX5AP, 5-lypoxygenase activating protein; BA, Brodmann Area; BBPDGU, Brain Bank for Psychiatric Diseases at the Gottingen University; ctr, control; COX, cyclooxygenase; cPGE, cytosolic prostaglandin E; FC, frontal cortex; CYP; cytochrome P450; HBTRC, Harvard Brain Tissue Resource Centre; IHC, immunohistochemistry; LOX, lipoxygenase; NA, not available; NSWTRC, New South Wales Tissue Resource Centre; OC, occipital cortex; PCR, polymerase chain reaction; PLA, phospholipase; PFC, prefrontal cortex; PGES, prostaglandin E synthase; PTGS, prostaglandin endoperoxide synthase; PTGER, prostaglandin E receptor 3; scz, schizophrenia; SFNC, Stanley Foundation Neuropathology Consortium; SMRIAC; Stanley Medical Research Institute Array Collection, TC, temporal cortex; VBBN, Victorian Brain Bank Network; WB, western blot

245


death from suicide Brain region technique


Burnet 2000 SFNC scz 13 ctr 14

scz 8/5 ctr 9/5

scz 44 ctr 47 scz 3 ACC AR

[125I]BH–substance P binding (NK1 receptor) ↔

Carletti 2005 SFNC scz 14 ctr 15

scz 9/5 ctr 9/6

scz 44 ctr 48 scz 4 AG*, TC#

in situ hybridization binding assay

preprotachykinin A*, NK1 receptor# ↓*↔#

Harrington 1995 NA scz 4 ctr 5

scz 0/4 ctr 4/1

scz 71 ctr 69 NA CT, PU in situ hybridisation

preprotachykinin A ↔

Iadarola 1991 DCCO scz 12 ctr 9

scz 10/2 ctr 8/1

scz 33 ctr 45 scz 9 SN RIA substance p ↔

Kleinmann 1983, 1985 DCCO

scz 40 ctr 18 NA

scz 48 ctr 50 NA

FC, CT, NAS, PU, GB, HPL RIA substance p

↔ (increased in other non schizophrenia psychotic disorders)

Rioux 1998 NA scz 5 ctr 5 NA

scz 70 ctr 70 NA NAS#, PU*, CT# AR

[125I]BH–substance P binding (NK1 receptor) ↔*,↑#

Roberts 1983 NA scz 14 ctr 12

scz 8/6 ctr 7/5

scz 62 ctr 82 scz 2

TC (BA21/22)*, FC (BA4)*, PC (BA7)*, CI (BA24)*, HPC#, AG*, TH*, BG* RIA substance p ↔*, ↑#

Tooney 2001 NSWTRC scz 6 ctr 6

scz 6/0 ctr 5/1

scz 44 ctr 43

scz 2 ctr 3 PFC (BA9) IHC NK1 receptor ↑(except layer VI)

Toru 1988 NA scz 14 ctr 10

scz 9/5 ctr 7/3

scz 58 ctr 67 NA

BG*, SN*, TH*, HPC*, TC*, PFC*, PC*, OFC# RIA substance p ↔ *, ↑#

Weidenhofer 2006 NSWTRC

scz 12 ctr 15

scz 10/2 ctr 13/2

scz 48 ctr 48 scz 3 AG IHC, PCR NK1 receptor ↔

Zech 1985 NA scz 6 ctr 5

scz 1/5 ctr 3/2

scz 31 ctr 45 NA BG IHC substance p ↔

Table A-6. Substance P in postmortem schizophrenia brain. ACC, anterior cingulate cortex; AG, amygdala; AR, autoradiography; BA, Brodmann Area; BG, basal ganglia; CI; cingulate cortex; CT, caudate; ctr, control; DCCO, District of Colombia Coroner’s Office; FC, frontal cortex; HPC, hippocampus; HPL, hypothalamus; IHC, immunohistochemistry; NA, not available; NAS, nucleus accumbens; NK1, neurokinin 1; NSWTRC, New south wales tissue resource centre; OFC, orbitofrontal cortex; PC, parietal cortex; PCR, polymerase chain reaction; PFC, prefrontal cortex; PU, putamen; RIA, radioimmunoassay; scz, schizophrenia; SN, substantia nigra: SFNC, Stanley Foundation Neuropathology Consortium; TC, temporal cortex; TH, thalamus

246




Arion 2007 UPCNMDBB scz 14 ctr 14

scz 12/2 ctr 12/2


SERPINA3, IFITM1, IFITM3, CHI3L1, HSPB1, MT2A ↑

Catts 2012 SMRIAC, NSWTRC

scz 72 ctr 71

scz 50/22 ctr 55/16

scz 47 ctr 48 scz 15 DLPFC*, OFC# PCR TNFSF13 ↑*, ↔#


scz 10 ctr 10

scz 5/5 ctr 5/5

scz 66 ctr 61 NA TL (BA22) PCR

TIMP1, TNFRSF1A, TYROBP ↓.


scz 24/13 ctr 26/9


NFκB#, SERPINA3*, IL6ST# ↑*↔#


scz 26/9 ctr 26/9

scz 43 ctr 44 scz 7 middle frontal gyrus PCR

SERPINA3*, IL1RL1#, ↑*↔#

Harris 2012 SMRIAC scz 35 ctr 33

scz 26/9 ctr 25/8

scz 43 ctr 45 NA BA10 ELISA TIMP1 ↔

Hwang 2013 SNFC, SMRIAC scz 33 ctr 34

scz 23/10 ctr 23/11

scz 44 ctr 46 NA HPC PCR

CD163 S100a8 and 9 IFITM1 IFITM2 IFITM3 ↑

Iwamoto 2004 SFNC scz 13 ctr 15

scz 8/5 ctr 9/6

scz 44 ctr 48 scz 4 PFC (BA10) PCR IFITM3 ↑


scz 6/4 ctr 7/3


PCR, WB

IL-1R#, NFκBp50*, NFκBp65*, iNOS ↑*↔#

Saetre 2007 SFNC, HBTRC, MBB

scz 55 ctr 55 NA

scz 59 ctr 55 NA

FC (BA8 and 9) superior frontal gyrus PCR

IFITM2, IFITM3, SERPINA3, GPB1 ↑

Schmitt 2011 BBPDGU scz 10 ctr 10

scz 5/5 ctr 8/2

scz 66 ctr 61 NA TC (BA22) PCR

LPL*, CFD*, PTGER4*, EDG3* ITGA1#, LCP1#, LTC4S#, MTHFD2#, SOD2#, ↓* ↔#

247

CCR1#, IL1RAP#, IFI16#, IFNAR2#, CD84#, GPX#

Shao 2008 SMRIAC scz 32 ctr 27

scz 23/9 ctr 23/6


TNFSF8 TFNSF10 ↔

Siegel 2014 ACOME scz 57 ctr 57

scz 42/15 ctr 42/15

scz 47 ctr 48 scz 16 PFC (BA9)

PCR, in situ hybridization

IFITM1, IFITM2/3 ↑

Sun 2001 SFNC NA NA NA NA FC PCR NFκB2 ↔

Thomas 2004 SFNC scz 15 ctr 15

scz 9/6 ctr 9/6

scz 45 ctr 48 scz 4

DLFPC (BA9,46), ACC (BA24) IHC ICAM-1 ↔

Volk 2015 ACOME scz 62 ctr 62

scz 47/15 ctr 47/15


NFκB1#, NFκB2#, Shn-2* ↓*↑#

Table A-7. Other markers in postmortem schizophrenia brain. ACC, anterior cingulate cortex; ACOME, Allegheny County Office of the Medical Examiner; APOL, apoliprotein L; BA, Brodmann area; BBPDGU, Brain Bank for Psychiatric Diseases at the Gottingen University; CCR, chemokine (c-c motif) receptor: CD, cluster of differentiation; CFD, complement factor D; CHI3L1, chitinase-3 like protein 1; ctr, control; DLFPC; dorsolateral prefrontal cortex; EDG3, endothelial differentiation, sphingolipid g-coupled-receptor; FC, frontal cortex; GPX, glutathione peroxidase; GPB, guanylate binding protein; HBTRC, Harvard Brain Tissue Resource Centre; HPC, hippocampus; HSPB, heat shock protein beta; ICAM, intercellular adhesion molecule; IFI, interferon gamma-inducible; IFITM; interferon-induced transmembrane; IFNAR, interferon (alpha, beta, and omega) receptor: IHC, immunohistochemistry; IL1RAP; interleukin 1 receptor accessory protein; IL1RL, interleukin 1 receptor like; IL6ST, glycoprotein 130; ITGA, integrin alpha; iNOS, inducible nitric oxide; LCP, lymphocyte cytosolic protein; LPL, lipoprotein lipase; LTC4S, leukotriene C4 synthase; MBB, Maudsley Brain Bank; MT2A, metallothionein 2A; MTHFD, methylenetetrahydrofolate dehydrogenase; NA, not available; NFκB, nuclear factor kappa-light-chain-enhancer of activated B cells; NSWTRC; New South Wales Tissue Resource Centre; OFC, orbitofrontal cortex; PCR, polymerase chain reaction; scz, schizophrenia; PFC, prefrontal cortex; PTGER, prostaglandin E receptor 4; SERPIN, serine protease inhibitor; SFNC; Stanley Foundation Neuropathology Consortium; Shn-2, Schnurri-2; SMRIAC, Stanley Medical Research Institute Array Collection; SOD, superoxide dismutase; TC, temporal cortex; TIMP; tissue inhibitor of metalloproteinases; TL, Temporal lobe; TNFSF, tumor necrosis factor superfamily; TYROBP, TYRO protein tyrosine kinase binding protein; UPCNMDBB, University of Pittsburgh’s center for the neuroscience of mental disorder brain bank

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