uab metabolomics symposium december 12, 2012 christopher b. newgard, ph.d. sarah w. stedman...

UAB Metabolomics SymposiumDecember 12, 2012

Christopher B. Newgard, Ph.D.

Sarah W. Stedman Nutrition and Metabolism Center

Department of Pharmacology & Cancer Biology

Duke University Medical Center

“Metabolomics applied to chronic disease mechanisms”

Evolving Metabolic Profiling PlatformStedman Nutrition and Metabolism Center,

DukeDefinition: Development of Comprehensive Tools for Metabolic Analysis of Cultured Cells, Animal Models, and Clinical Samples,via…

“Targeted” MS Methods• GC/MS and MS/MS for “targeted” analysis. Current

capability, 250 metabolites in 9 classes (free fatty acids, total fatty acids, LC acyl CoAs, SC acyl CoAs, acyl carnitines, organic acids, amino acids, purine precursors/nucleotides, ceramides/sphingolipids)

• Modules for sterols, phospholipids, and eicosanoids in development

“Non-Targeted” MS Methods•

~1000 compound spectral library developed (with Agilent, Oliver Fiehn, UC Davis) for non-targeted GC/MS

• LC-MS/MS for non-targeted analysis of thousands of metabolites/sample

Metabolic signatures of human disease states, including obesity, type 2 diabetes, CVD

Hypothesis generation engine for mechanistic studies in cells and animal models

Integration of metabolomics with other “omics” sciences (genomics, transcriptomics) for identification of novel regulatory pathways

Use of non-targeted metabolomics for discovery applications

Uses of comprehensive metabolic profiling tools

(metabolomics)

Obese vs. lean study: clinical characteristics

Measure Obese

(n=74)

Lean

(n=67)

p-value

Age 52.4 ± 10.9 50.2 ± 12.5 NS

Height 66.4 ± 4.0 67.9 ± 3.9 NS

Weight 235 ± 46 149 ± 20 < 0.0001

BMI 37.4 ± 5.3 22.8 ± 1.6 < 0.0001

Association of a BCAA-Related PCA Factor withInsulin Resistance in Humans

*PCA factor 1 comprised of Val, Leu/Ile, Glx, C3AC, C5AC, Phe, Tyr

0

5

10

15

20

25

30

-2 0 2 4 6

HO

MA

PCA Factor 1*

R = 0.604

Lean Subjects

Obese Subjects

Newgard, et al. Cell Metabolism 9: 311, 2009

Are BCAA predictive of disease or intervention outcomes?

Are BCAA responsive to our best current diabetes/obesity interventions?

Do increased BCAA and metabolites contribute to development of insulin resistance?

What are the mechanisms for increased circulating BCAA?

Important Questions

Poor association of weight loss and ∆HOMA in WLM subjects

_______________________________________________

HOMA decreased from entry to baseline.

HOMA increased from entry to baseline.

Change in Weight (Baseline – 6 months)

Factor Univariates for HOMA-Change Model

Entry Variable

Factor name F val P-valEffect Size (95%

CI)

F1 Medium Chain Acylcarnitines 0.08 0.78 -0.02 (-0.17, 0.13)

F2 Medium Chain Dicarboxyl-acylcarnitines 1.96 0.16 -0.11 (-0.26, 0.04)

F3 Branched-Chain Amino Acids (BCAA) 47.82 <.0001 -0.51 (-0.66, -0.37)

F4C2, C4-OH, C16:1, Total Ketones, 3-OH Butyrate, Nonesterified Fatty Acid

1.19 0.28 0.08(-0.07, 0.24)

F5

C18:1-OH/C16:1-DC, C18-OH/C16-DC, C20, C20:1-OH/C18:1-DC,

C20-OH/C18-DC

0.32 0.57 -0.04 (-0.20, 0.11)

Shah, et al. Diabetologia 55: 321, 2012

Science Translational Medicine 3: 80re2, 2011

Laferrere, et al., Science Transl. Med. 3: 80re, 2011

*

*

Larger decrease in BCAA (molar sum) in GBPcompared to dietary intervention matched for weight loss

Columbia cohort

Duke cohort

C3 + C5 Acylcarnitines decreased in GBPversus dietary intervention

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

GBP Diet

To

tal

C3

and

C5

um

ol/L

Total Acylcarnitines

*

C3 + C5 Acylcarnitines

Laferrere, et al., Science Transl. Med. 3: 80re, 2011

Rats fed HF/BCAA are insulin resistant despite normal body

weight

Newgard CB, et al. Cell Metabolism, 2009

HF + BCAA feeding induces acylcarnitine accumulation despite lower rate of food

intake

Feed Zucker-obese or Zucker-lean rats on standard chow, or standard chow with 45% depletion of BCAA in diet (not growth limiting)

Assess insulin sensitivity and metabolic profiles after 10 weeks of feeding

Phillip White, Amanda Lapworth, Jie An, ChinMeng Khoo, Erin Glynn

Does this mean that BCAA restriction might improve insulin sensitivity?

BCAA Restriction enhances insulin sensitivity: Isoglycemic Hyperinsulinemic Clamp

*p = 0.03

GeneticsEssential amino acids

Branched Chain Amino AcidsBranched Chain Amino Acids

Aromatic Amino AcidsAromatic Amino Acids

proteinproteinoxidationoxidation

Diagnostic Read-Out

Gut microbiome

What causes BCAA to rise in human metabolic diseases?

Shah, Svetkey & NewgardCell Metabolism 13: 491, 2011

Newgard, CB. Cell Metabolism 15:606, 2012Newgard, CB. Cell Metabolism 15:606, 2012

Hypothesis: The BCAA/aromatic amino acid metabolicsignature provides a clue to the mechanism underlying the association of obesity with behavioral disorders (anxiety, depression)

Why are Aromatic Amino Acids Always Part of the BCAA-related

Metabolite Signature?

BrainTrp

Serotonin

Blood Brain BarrierLAT1

Trp TyrPhe

Leu

Iso

Val

ValVal

ValIso

IsoLeu

LeuLeu

Leu

Leu

LeuLeuValVal

IsoIsoLeu Leu

Tyr

Dopamine

Norepinephrine

ValIso

Leu

Leu

TRANSPORT OF LNAA THROUGH THE BLOOD BRAIN BARRIER

BCAA supplementation of energy-dense diets reduces Trp and Tyr Levels in frontal

cortex

Coppola, et al. Am. J. Physiol. in press, 2012

ANOVA, BCAA, p < 0.002

BCAA supplementation of energy-dense diets causes anxious behavior (elevated

maze test)

Anna Coppola

ANOVA, BCAA, p < 0.002

Fluoxetine (Prozac) Does Not Reverse BCAA-induced Anxious Behavior……

Anna Coppola

……but Tryptophan Does

Anna Coppola

Anna Coppola

Trp supplementation normalizes kynurenic acid levels in frontal cortex

Anna Coppola

Metabolomic Profiling in CATHGEN

– Study 1• Subjects with coronary artery disease (CAD) compared to

race- and sex-matched controls, index and validation cohorts.

– Study 2

• CAD cases who experienced CV events (MI, CV-related death within 2 yr. of follow up) and controls with no events; index and validation cohorts.

– Study 3

• Nested prospective study of 2023 consecutive subjects undergoing diagnostic cardiac catheterization, with CV events as outcome.

– Study 4

• Adverse outcomes in 478 subjects that underwent coronary artery bypass surgery (CABG).

Shah et al, Circulation Cardiovasc. Genetics 3: 207, 2010

Shah et al, Am. Heart Journal 163: 844, 2012

Shah, et al. J. Thoracic Cardiovasc. Surgery 143: 873, 2012

Shah, Kraus, Newgard, Circulation 126: 1110, 2012

Metabolites in DC-AC principal component clusters that predict CVD

events1. Case/control CATHGEN study: C5-DC, C6:1-DC/C8:1-

OH, C8:1-DC, C6-DC, citrulline

2. Nested prospective CATHGEN study: C6:1-DC/C8:1-OH, C8:1-DC, C6-DC, C5-DC, Ci4DC/C4-DC, C5-OH/C3-DC, C10-OH/C8-DC, C10:3

3. CABP study: Ci-DC/C4-DC, C5-DC, C6-DC, C6:1-DC/C8:1-OH, C8:1, C8:1-DC, C10:1, C10:2, C10:3, C10-OH/C8-DC, C12-OH, C10-DC, citrulline

Common to all 3 setsCommon to 2 sets

Dicarboxylated acylcarnitines Predict Incident CVD Events

1st

Tertile

2nd

Tertile

3rd

Tertile

Median follow-up 3.1 yrs, 232 Deaths

Shah, Newgard, Hauser, Kraus, Newby et al., American Heart Journal 2012.

Study Population: N=3500 from CATHGEN biorepository, 70% with CAD, 29% with T2D

• All 3500 have targeted, quantitative metabolomic profling

•

• All have GWAS (Illumina Omni chip) genotyping completed

•

• All have peripheral blood gene expression profiling (Illumina microarray)

Allows analysis of genetic architecture underlying metabolic variability in this population

Ongoing Studies

Our laboratoryJie An Erin GlynnPhillip White Amanda LapworthDorothee Newbern Chinmeng KhooHelena Winfield Danhong LuSam Stephens Jeff TessemLisa Poppe Anna CoppolaMette Valentin Jensen Taylor Rosa Michelle Arlotto Paul AndersonTom Becker (Faculty) Heather HayesHans Hohmeier (Faculty) Jonathan HaldemanLarry Moss (Faculty) Jennifer Moss (Faculty)

CollaboratorsJames Bain (Faculty), Robert Stevens (Faculty), Brett Wenner, Olga Ilkayeva, Mike Muehlbauer, Stedman Center Core Laboratory; David Millington

Debbie Muoio, Tim Koves, Duke Stedman Center

Alan Attie, Mark Keller, University of Wisconsin

Bill Kraus, Svati Shah, E-Shyong Tai, Aslan Turer, Beth Hauser, Mihai Podgoreanu, Laura Svetkey, Lillian Lien, Andrea Haqq, Blandine LaFererre, Alfonso Torquati—Clinical Collaborators

Acknowledgments