1. UAB Metabolomics Symposium December 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”

2. Evolving Metabolic Profiling Platform Stedman Nutrition and Metabolism Center, Duke Definition: 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

3.  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)

4. Obese vs. lean study: clinical characteristics MeasureObese (n=74) Lean (n=67) p-value Age52.4 ± 10.950.2 ± 12.5NS Height66.4 ± 4.067.9 ± 3.9NS Weight235 ± 46149 ± 20< 0.0001 BMI37.4 ± 5.322.8 ± 1.6< 0.0001

5. Association of a BCAA-Related PCA Factor with Insulin Resistance in Humans *PCA factor 1 comprised of Val, Leu/Ile, Glx, C3AC, C5AC, Phe, Tyr Newgard, et al. Cell Metabolism 9: 311, 2009

6.  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

7. 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)

8. Factor Univariates for HOMA-Change Model Entry Variable Factor nameF valP-val Effect Size (95% CI) F1 Medium Chain Acylcarnitines 0.080.78 -0.02 (-0.17, 0.13) F2 Medium Chain Dicarboxyl-acylcarnitines 1.960.16 -0.11 (-0.26, 0.04) F3 Branched-Chain Amino Acids (BCAA) 47.82<.0001 -0.51 (-0.66, -0.37) F4 C2, C4-OH, C16:1, Total Ketones, 3-OH Butyrate, Nonesterified Fatty Acid 1.190.28 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 0.320.57 -0.04 (-0.20, 0.11) Shah, et al. Diabetologia 55: 321, 2012

10. Science Translational Medicine 3: 80re2, 2011

11. Laferrere, et al., Science Transl. Med. 3: 80re, 2011 * * Larger decrease in BCAA (molar sum) in GBP compared to dietary intervention matched for weight loss Columbia cohort Duke cohort

12. C3 + C5 Acylcarnitines decreased in GBP versus dietary intervention Total Acylcarnitines * C3 + C5 Acylcarnitines Laferrere, et al., Science Transl. Med. 3: 80re, 2011

13. Rats fed HF/BCAA are insulin resistant despite normal body weight Newgard CB, et al. Cell Metabolism, 2009

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

15.  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?

17. BCAA Restriction enhances insulin sensitivity: Isoglycemic Hyperinsulinemic Clamp *p = 0.03

18. Genetics Essential amino acids Branched Chain Amino Acids Aromatic Amino Acids proteinoxidation Diagnostic Read-Out Gut microbiome What causes BCAA to rise in human metabolic diseases? Shah, Svetkey & Newgard Cell Metabolism 13: 491, 2011

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

20. Hypothesis: The BCAA/aromatic amino acid metabolic signature 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?

21. Brain Trp Serotonin Blood Brain Barrier LAT1 TrpTyr Phe Leu Iso Val Iso Leu Val Iso Leu Tyr Dopamine Norepinephrine Val Iso Leu TRANSPORT OF LNAA THROUGH THE BLOOD BRAIN BARRIER

22. 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

23. BCAA supplementation of energy-dense diets causes anxious behavior (elevated maze test) Anna Coppola ANOVA, BCAA, p < 0.002

24. Fluoxetine (Prozac) Does Not Reverse BCAA- induced Anxious Behavior…… Anna Coppola

25. ……but Tryptophan Does Anna Coppola

27. Trp supplementation normalizes kynurenic acid levels in frontal cortex Anna Coppola

28. 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

29. Metabolites in DC-AC principal component clusters that predict CVD events 1.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 sets Common to 2 sets

30. Dicarboxylated acylcarnitines Predict Incident CVD Events 1 st Tertile 2 nd Tertile 3 rd Tertile Median follow-up 3.1 yrs, 232 Deaths Shah, Newgard, Hauser, Kraus, Newby et al., American Heart Journal 2012.

31. 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

32. Our laboratory Jie AnErin Glynn Phillip WhiteAmanda Lapworth Dorothee NewbernChinmeng Khoo Helena WinfieldDanhong Lu Sam StephensJeff Tessem Lisa PoppeAnna Coppola Mette Valentin JensenTaylor Rosa Michelle ArlottoPaul Anderson Tom Becker (Faculty)Heather Hayes Hans Hohmeier (Faculty)Jonathan Haldeman Larry Moss (Faculty)Jennifer Moss (Faculty) Collaborators James 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