Transcript Takeda/Duke/RTI meeting

“Metabolomics applied to chronic disease
mechanisms”
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
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
Uses of comprehensive metabolic profiling tools
(metabolomics)
 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
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 with
Insulin Resistance in Humans
30
HOMA
25
20
R = 0.604
Lean Subjects
15
Obese Subjects
10
5
0
-2
0
2
4
6
PCA Factor 1*
*PCA factor 1 comprised of Val, Leu/Ile, Glx, C3AC, C5AC, Phe, Tyr
Newgard, et al. Cell Metabolism 9: 311, 2009
Important Questions
 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?
Poor association of weight loss and
∆HOMA in WLM subjects
_______________________________
________________
6
HOMA
increased
from entry
to baseline.
4
∆HOMA
2
0
-2
-4
HOMA
decreased
from entry
to baseline.
-6
-8
-10
4.0
9.0
14.0
19.0
24.0
Change in Weight (Baseline – 6 months)
29.0
Factor Univariates for HOMA-Change Model
Entry
Variable
F1
F2
F3
F4
F5
Factor name
F val
P-val
Effect Size (95%
CI)
Medium Chain
Acylcarnitines
Medium Chain
Dicarboxyl-acylcarnitines
Branched-Chain Amino
Acids (BCAA)
C2, C4-OH, C16:1, Total
Ketones, 3-OH Butyrate,
Nonesterified Fatty Acid
C18:1-OH/C16:1-DC,
C18-OH/C16-DC, C20,
C20:1-OH/C18:1-DC,
C20-OH/C18-DC
0.08
0.78
-0.02 (-0.17, 0.13)
1.96
0.16
-0.11 (-0.26, 0.04)
47.82
<.0001
-0.51 (-0.66, -0.37)
1.19
0.28
0.08(-0.07, 0.24)
0.32
0.57
-0.04 (-0.20, 0.11)
Shah, et al. Diabetologia 55: 321, 2012
Science Translational Medicine 3: 80re2, 2011
Larger decrease in BCAA (molar sum) in GBP
compared to dietary intervention matched for weight loss
*
*
Laferrere, et al., Science Transl. Med. 3: 80re, 2011
Columbia cohort
Duke cohort
C3 + C5 Acylcarnitines decreased in GBP
versus dietary intervention
C3 + C5 Acylcarnitines
Total Acylcarnitines
1.0
Total C3 and C5 umol/L
0.9
0.8
0.7
*
0.6
0.5
0.4
0.3
0.2
0.1
0.0
GBP
Laferrere, et al., Science Transl. Med. 3: 80re, 2011
Diet
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
Does this mean that BCAA restriction might
improve insulin sensitivity?
 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
BCAA Restriction enhances insulin sensitivity: Isoglycemic
Hyperinsulinemic Clamp
18
18
16
GIR (mg.kg.min-1)
14
12
10
OB CTL (n-5)
8
OB 45% DEF (n-5)
6
4
Mean GIR (mg.kg.min-1)
16
*
14
12
10
8
6
4
2
2
0
0
0
10
20
30
40
OB CTL (n-5)
50
Time (minutes)
OB 45% DEF (n-5)
20
20
18
18
16
16
14
12
10
OB CTL (n-5)
8
OB 45% DEF (n-5)
6
4
Mean Glycemia (mM)
Glycemia (mM)
*p = 0.03
14
12
10
8
6
4
2
2
0
0
10
20
30
Time (minutes)
40
50
0
OB CTL (n-5)
OB 45% DEF (n-5)
What causes BCAA to rise in human metabolic diseases?
Essential amino acids
Gut microbiome
Genetics
oxidation Branched Chain Amino Acids
Aromatic Amino Acids
Shah, Svetkey & Newgard
Cell Metabolism 13: 491, 2011
protein
Diagnostic Read-Out
Newgard, CB. Cell Metabolism 15:606, 2012
Why are Aromatic Amino Acids Always
Part of the BCAA-related Metabolite
Signature?
Hypothesis: The BCAA/aromatic amino acid metabolic
signature provides a clue to the mechanism underlying the
association of obesity with behavioral disorders (anxiety,
depression)
TRANSPORT OF LNAA THROUGH THE
BLOOD BRAIN BARRIER
Dopamine
Serotonin
Leu Iso
Val
Leu
Leu
Val
Iso
Leu
Norepinephrine
Trp Leu Val Tyr
Val
Leu Iso Leu
Trp Iso
Leu
Phe
Iso
Leu
Tyr
Val
Val
Leu
BCAA supplementation of energy-dense diets
reduces Trp and Tyr Levels in frontal cortex
ANOVA, BCAA, p < 0.002
Coppola, et al. Am. J. Physiol. in press, 2012
BCAA supplementation of energy-dense diets
causes anxious behavior (elevated maze test)
ANOVA, BCAA, p < 0.002
Anna Coppola
Fluoxetine (Prozac) Does Not Reverse BCAAinduced 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 raceand 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 events
1. Case/control CATHGEN study: C5-DC, C6:1DC/C8:1-OH, C8:1-DC, C6-DC, citrulline
2. Nested prospective CATHGEN study: C6:1DC/C8:1-OH, C8:1-DC, C6-DC, C5-DC, Ci4DC/C4DC, C5-OH/C3-DC, C10-OH/C8-DC, C10:3
3. CABP study: Ci-DC/C4-DC, C5-DC, C6-DC, C6:1DC/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
Dicarboxylated acylcarnitines Predict Incident
CVD Events
1
2
3
Median follow-up 3.1 yrs, 232 Deaths
Shah, Newgard, Hauser, Kraus, Newby et al., American Heart Journal 2012.
st
Tertile
nd
rd
Tertile
Tertile
Ongoing Studies
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
Acknowledgments
Our laboratory
Jie An
Erin Glynn
Phillip White
Amanda Lapworth
Dorothee Newbern
Chinmeng Khoo
Helena Winfield
Danhong Lu
Sam Stephens
Jeff Tessem
Lisa Poppe
Anna Coppola
Mette Valentin Jensen
Taylor Rosa
Michelle Arlotto
Paul 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