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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”
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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
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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)
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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
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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
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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
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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)
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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
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Science Translational Medicine 3: 80re2, 2011
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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
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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
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Rats fed HF/BCAA are insulin resistant despite normal body
weight
Newgard CB, et al. Cell Metabolism, 2009
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HF + BCAA feeding induces acylcarnitine accumulation despite lower rate of food
intake
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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?
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BCAA Restriction enhances insulin sensitivity: Isoglycemic Hyperinsulinemic Clamp
*p = 0.03
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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
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Newgard, CB. Cell Metabolism 15:606, 2012Newgard, CB. Cell Metabolism 15:606, 2012
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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?
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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
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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
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BCAA supplementation of energy-dense diets causes anxious behavior (elevated
maze test)
Anna Coppola
ANOVA, BCAA, p < 0.002
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Fluoxetine (Prozac) Does Not Reverse BCAA-induced Anxious Behavior……
Anna Coppola
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……but Tryptophan Does
Anna Coppola
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Anna Coppola
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Trp supplementation normalizes kynurenic acid levels in frontal cortex
Anna Coppola
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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
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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
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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.
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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
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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