faseb 2010 dmitry grapov
DESCRIPTION
Identification of circulating free fatty acid, oxylipin, and endocannabinoid markers of HbA1C, muscle fat oxidation, and Type 2 Diabetes severityDmitry Grapov1, Sean H Adams1,2, W. Timothy Garvey3, Kerry H Lok3, John W Newman1,2. 1Nutrition, University of California Davis, Davis, CA, 2USDA/ARS Western Human Nutrition Research Center, Davis, CA, 3Nutrition Sciences, University of Alabama, Birmingham, AL Obesity is associated with increased circulating non-esterified free fatty acids (NEFA) and endocannabinoids (eCBs). There is evidence that these species are involved in complex mechanisms leading to modulation of organismal insulin resistance, which are hypothesized to also involve oxylipins (OxL). The current study is a targeted metabolomic investigation of circulating NEFA (n=54), eCBs (n=35) and OxLs (n=80) in a cohort of obese African-American women (n=55). Study participants were BMI- and age-matched overweight to obese type 2 diabetics (T2D) (n = 43) and non-diabetics (n = 12), some of whom also harbor a missense G304A mitochondrial uncoupling protein 3 (UCP3 g/a) polymorphism. UCP3 g/a carriers display an increased respiratory quotient, reflective of ~50% reduction in whole body fat oxidation. Because UCP3 is primarily expressed in muscle and muscle accounts for ~80% of the organismal glucose utilization, metabolomic information regarding these subjects circulating lipids is hypothesized to provide a means to identify lipid markers reflective of altered muscle fat oxidation and elucidate their role in the progression of T2D severity. Principal components analysis was used to construct latent variables explaining the majority of the variation in metabolite concentrations, which were also significantly correlated with HbA1C, BMI, Age and fasting glucose. Monounsaturated fatty acid markers of de novo fatty acid synthesis were significantly increased in T2D and were significantly correlated to HbA1c. Orthogonal to the variation explained by changes HbA1C, 2-monoglycerol and N-acylethanolamide (NAE), eCBs, were found to decrease and increase respectively, in a manner significantly positively correlated with fasting glucose. Partial least-squares discriminant analysis (PLS-DA) was used to identify metabolic differences reflective of UCP3 gene polymorphism. In non-diabetics there were marked differences in arachidonic acid derived epoxides and ethanolamide. Alternatively in diabetics their were shifts in saturated fatty acids and stearate derived ethanolamide. The observed changes in metabolites, co-occuring with gene polymorphism are hypothesized to be reflective of differences in peroxisome proliferator activated receptors dependent signaling mechanisms. This work was supported by USDA-ARS Project 5306-51530-016-00D, NIH-NIDDK R01DK078328-01 and T32-GM08799.TRANSCRIPT
Dmitry Grapov1, Sean H Adams1,2, W. Timothy Garvey3, Kerry H Lok3,Theresa Pedersen2,John W Newman1,2. 1Nutrition, University of California Davis, Davis, CA, 2USDA, ARS, Western Human Nutrition Research Center, Davis, CA, 3Nutrition
Sciences, University of Alabama, Birmingham, AL
ResultsResults
ConclusionsConclusions
This work was supported by USDA-ARS Project 5306-51530-016-00D, NIH-NIDDK R01DK078328-01 and T32-GM08799.
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Marc Schwartz and Bill Venables (2009). gplots: Various programming tools for plotting data.
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B.Bolstad, M. Dettling, S. Dudoit, B. Ellis, L. Gautier, Y. Ge, and others 2004, Genome Biology, Vol. 5, R80
IntroductionIntroductionT2DM Phenotype
1Bioactive Lipids
Lipid Signaling
Lipid Metabolism
Can bioactive lipids predict T2DM pathopysiology?
T2DM impact on circulating lipids?
How are circulating lipids related to lipid mediators?2
3
Changes known to occur in T2DM
•Elevated fasting glucose
•Elevated glycosylated hemoglobin (HbA1c)
•Elevated total non-esterified fatty acids (NEFA)
•Elevated endocannabinoid, arachidonylethanolamide (AEA)
Hypothesis: An expanded assessment of lipidomic changes in type 2 diabetes (T2DM) is hypothesized to provide novel insights into metabolic changes associated with this malady.
Target circulating lipid mediators
•Investigate lipidomic changes associated with high fasting glucose and HbA1c
•Quantitatively describe T2DM-associated changes in circulating NEFA, oxylipins, and endocannabinoids.
•Use bioinformatic systems biology approach to develop improved measures for T2DM diagnosis, severity and, treatment efficacy monitoring.
AbstractAbstract
Experimental Design•Gullah-speaking population, participants in Sea Islands Genetic AfricanAmerican Registry
(Project SuGAR: Sale etal.,Diabetes 2009)
•Age- and BMI-matched, n=43 (type 2 diabetics), n=12 (non-diabetics)
Targeted Metabolomic Profiling•Fasting plasma
•LC/MS/MS (Oxylipins and Endocannabinoids)
•GC/MS (NEFA)
Bioinformatics•Projection modeling (PCA,PLS,OPLS-DA) using R1 and SIMCA-P+ 11.0 (Umetrics AB, Umeå Sweden)
•Multiple hypothesis testing2
•Metabolic network visualization3,4
•Multiple linear regression modeling5
MethodsMethods
AHBG, Index for T2DM SeverityAHBG, Index for T2DM Severity
Non-Diabetic Diabetic
22:6
n322
:5n6
20:5
n320
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EA
SE
Ac2
4:0
Res
olvi
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(iso
pros
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DE
9-H
OD
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TE
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(13)
-EpO
DE
8(9)
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TrE
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5)-E
pET
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(13)
-EpO
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(16)
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HO
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9,10
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22:5
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9:0
18:3
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2n6
18:2
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20:1
n918
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/1n7
t18
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c16:
0c1
8:0
18:2
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4:0
16:1
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t,11t
-CLA
18:3
n619
:1n9
1-O
G2-
OG
1-LG
2-LG
1-A
G2-
AG
NO
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AE
ALE
AP
EA
Dih
omo
GLA
EA
OE
AD
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AN
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ly
NA-GlyDHEAOEADihomo GLA EAPEALEAAEANO-Gly2-AG1-AG2-LG1-LG2-OG1-OG19:1n918:3n69ct,11t-CLA16:1n7c14:016:1n7t18:2n6c18:0c16:018:1n718:1n9/1n7t20:1n918:2n6tt20:3n9/20:2n618:3n3c19:022:5n322:4n69-HETE15-HETE8-HETE11-HETE15(S)-HEPE15-KETE15(S)-HETrE5-KETE5-HETE5,6-DiHETrE8,9-DiHETrE5(S)-HEPE11,12-DiHETrE14,15-DiHETrE19,20-DiHDPA14,15-DiHETE17,18-DiHETE9,10-DiHOME12,13-DiHOME15,16-DiHODE9,10-13-TriHOME9,12,13-TriHOME12-KETE12-HETE15(16)-EpODEEKODE12(13)-EpOME13-KODE9(10)-EpODE9(10)-EpOME11(12)-EpETrE14(15)-EpETrE8(9)-EpETrE12(13)-EpODE13-HOTE9-HOTE9-HODE13-HODEPGF2a / ( isoprostanes)Resolvin E1c24:0SEADEA20:4n620:3n620:5n322:5n622:6n3
++ ++++ +++ + ++ ++ + +++ ++++ + +++++ ++++ + ++++ ++ ++ +++ + ++++ +++++ + + + + ++++++++++++ + +++++++++ ++ ++ ++++ ++++++++++++ ++ +++ ++ + +++++++++++ +++ ++ +++ ++++++++++ ++ + +++ + ++++++ +++++++++++ +++++ + ++ ++++++++++ ++++++ ++ ++ +++++++++ +++++++ + +++ ++++++ ++++++++ ++ + ++++ + +++++ +++++++++ ++++ + ++++ ++++++++++ ++++ +++ +++++++++++ + +++ ++++ ++++++++++++ +++++ ++++++ + ++++++++++++++ ++++++++++++ ++++ + + +++ + + ++ +++ + ++ + + ++ ++++++++ ++ + + + +++ ++ ++++++++++ + ++ +++ ++ +++++++++++ ++ ++ ++ +++ ++++++++ +++ + +++++++ ++++ ++ +++ +++ + ++ +++++ ++ + ++++++ ++ ++ ++++++ ++++ +++ ++++ + + +++ + +++++++ ++ ++++++ +++ ++ +++++ + + ++ + ++++ ++ ++ +++ +++ +++++ ++++ +++ +++ ++++++ + + ++ + ++ + + + + + + + + + +++++ + + +++++ ++ ++++ + + ++++ + + + +++ +++ + + +++ + ++ + +++ +++ ++++ ++ + + + + ++ + + + + + ++ + + + +++ ++ ++++ + ++++++ +++++ + + + + +++ ++++++++ + ++ + + + + + ++ +++++++ ++ + + ++++++ ++ + +++ ++++++ +++ ++ + + ++++++++++++ +++ +++++ ++++ ++++++++++++ + + ++++ +++++ + +++ + ++ + +++ +++++ + + + + ++ ++++++ + + + ++++++++ ++++ ++ ++ ++++++++ ++ + ++ +++ + + + + + + ++ + ++ ++ +++ + + + + + + +++ +++++ +++ + ++++ ++++ + +++ ++++ +++++++++++++ +++ + ++++ ++++ + + + ++++ + + + ++++ +++ + + ++ ++ + + +++ + ++++ +
-0.2 0.2 0.6 1Value
050
150
Color Keyand Histogram
Cou
nt
22:6
n322
:5n6
20:5
n320
:3n6
20:4
n6D
EA
SE
Ac2
4:0
Res
olvi
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1P
GF
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pros
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TE
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(13)
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8(9)
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DE
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(13)
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ME
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(16)
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9,12
,13-
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HO
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9,10
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HO
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15,1
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E14
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18:3
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ALE
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NA-GlyDHEAOEADihomo GLA EAPEALEAAEANO-Gly2-AG1-AG2-LG1-LG2-OG1-OG19:1n918:3n69ct,11t-CLA16:1n7c14:016:1n7t18:2n6c18:0c16:018:1n718:1n9/1n7t20:1n918:2n6tt20:3n9/20:2n618:3n3c19:022:5n322:4n69-HETE15-HETE8-HETE11-HETE15(S)-HEPE15-KETE15(S)-HETrE5-KETE5-HETE5,6-DiHETrE8,9-DiHETrE5(S)-HEPE11,12-DiHETrE14,15-DiHETrE19,20-DiHDPA14,15-DiHETE17,18-DiHETE9,10-DiHOME12,13-DiHOME15,16-DiHODE9,10-13-TriHOME9,12,13-TriHOME12-KETE12-HETE15(16)-EpODEEKODE12(13)-EpOME13-KODE9(10)-EpODE9(10)-EpOME11(12)-EpETrE14(15)-EpETrE8(9)-EpETrE12(13)-EpODE13-HOTE9-HOTE9-HODE13-HODEPGF2a / ( isoprostanes)Resolvin E1c24:0SEADEA20:4n620:3n620:5n322:5n622:6n3
+ ++ ++ + +++++ + ++ + ++++++++++ + + ++ + + ++++ + + + + + + + ++ + + + + + +++ ++ +++ ++ + +++ + + + + ++ ++++ ++ + + + + + + ++++ + + + + ++ + +++ + + + ++ + + + + + + + + ++++ + + +++ + + + ++ + + + + ++ + ++++++ ++ + +++++ ++ + ++++++++ + + +++++ ++ + +++++++ ++ ++++ + + ++++++ ++ + + + +++++ ++ +++++++ ++++ +++++++ ++ ++++ +++++ +++++++ + ++ +++++ +++++++ + + + ++ ++++++++ + + +++ + + + + ++++++++ + ++ ++ ++ + ++++++++++ + + + + + + + + + ++++ +++++ + + + + + + + ++++++ + + +++ +++ +++ +++ + ++ +++ +++ + + + + + +++ +++ +++ + ++ ++ + +++ + + + ++ + + + +++ + + + + ++ + + + + + + +++++++++ + ++ + + + + + + + + ++ +++++++ + + ++ ++ ++ +++ ++ + + + ++ + + + + + + + + + + + +++ + + + + + + + + + + + ++ + + ++ + + +++ + + + ++ +++ + ++ + + ++++ ++ + + +++ ++ + + + + + ++ + ++ ++++++ ++++ ++ + +++ ++ + +++ ++ ++ + + + + + + ++ ++++ + +++++ + + +++++++++ ++++ + + ++++ + + + +++ ++ + + + + + + + ++ + + + + ++ ++ +++ + + + + + +++++ + +++ + + + + + ++ ++ ++ ++++ + + + + + +++ ++ ++++ + + + + ++++ + +++ ++ + + + ++ ++ ++ + + ++ + ++ + + ++ + ++++++++ + + + + + + + + + + + + + + + + ++++ + ++ + +++++++ +++ + + + +++ + +++ ++ + ++ ++ ++ + +++ +++ + + + + + +++++++++ + ++++ + ++ ++ +++++++ +
-0.5 0 0.5 1Value
05
015
0
Color Keyand Histogram
Cou
nt
≥
AEA
DHEA
9(10)-EpOME
14(15)-EpETrE
14,15-DiHETrE
NO-Gly
1
9(10)-EpOME
AEA
AEA
DHEA
DHEA
9(10)-EpOME
NO-Gly
14(15)-EpETrE
NO-Gly14(15)-EpETrE
14,15-DiHETrE
14,15-DiHETrE
22
Undirected metabolic network
•Adjacency based on multidimensionally scaled
correlations.
•Blue and orange edges denote significant
negative and positive correlations, respectively.
1
Network representation of changes in
metabolic relationships associated
with T2DM
•Blue and orange edges represent
significant decreases or increases in
correlation strength in diabetics relative
to non-diabetics
3
3
1
1
2
2
T2DM-associated changes in metabolic networks
1. Associated with T2DM is a loss in correlation between long chain
polyunsaturated fatty acids and c14-
c18 fatty acids
2. Diabetics exhibit and altered relationship between c14-c18 fatty
acids and epoxide oxylipins
3. DHEA, DHA omega-3 fatty acid ethanolamide, displays a significant
change in correlation pattern
4. Labeled species are hypothesized to be sensitive reporters of T2DM-
associated shifts in biological
relationships among lipid mediators
Heat map of linear
relationships among
lipidomic
measurements
•Darker or lighter
values represent
negative or positive
correlations
• +’s Denote significant correlations
at a 10% false discovery rate
1 Diabetics exhibit increased correlation
between c14-c18 fatty
acids and epoxide
oxylipins
2 Among diabetics ethanolamide
endocannabinoids are
strongly positively
correlated
Systems Biology ApproachSystems Biology Approach
2
0.2180.1451.0000.814AHBG
0.2180.1820.9170.791HbA1c
Diagnostic power
misclassification rate
Specificity
Sensitivity
Classification Parameter
*Subject on HCTZ, (thiazide diuretic,) and Normadyne (alpha/beta Adrenergic antagonist).
*
i. Index is normally distributed among diabetics and non-diabetics
ii. Shows high classifier sensitivity and specificity
iii. Is reportive of circulating epoxy and endocannabinoid lipid mediators
i
ii
iii
3
3
Principal Components Analysis Principal Components Analysis
Use unsupervised projection modeling
(PCA) to determine which variables explain
the maximum variance in the data
A. PCA Scores
B. PCA Loadings
C. Correlation between PC1 and HbA1c
• Colored by HbA1c quantiles
AGE, HbA1c, BMI, and fasting
glucose explain the maximum
variance in the data
• An algorithm combining these
variables is suggested as a
novel index for T2DM severity
(AHBG)
1
2
Evaluate clinical
measurements ability to
segregate diabetics and non-
diabetics
A
C
B
Lipidomic variables can be used to
segregate diabetics from non-diabetics
• Subject scores are correlated with
HbA1c
3
Lipid Biosynthetic NetworkLipid Biosynthetic Network
DHEA
product | precursor
%
Quantitative visualization of T2DM-associated changes in
biosynthetic relationships among select NEFA, oxylipins,
and endocannabinoids
1. Node and edge size represent fold change in diabetics relative
to non-diabetics
2. Labeled species are hypothesized to be sensitive reporters for
T2DM-associated perturbations in bioactive lipids biosynthesis
9(10)-EpOME
AEA
14(15)-EpETrE
Diverse regions of lipid
biochemistry
A. de novo synthesized fatty
acids
B. Omega-3 fatty acid
metabolites
C. Linoleic acid metabolites
D. Arachidonic acid
metabolites
A
B
AB
DC
C D
T2DM is a complex pathophysiological state, involving changes in organismal carbohydrate and lipid
metabolism
1. Targeted metabolomic profiling and bioinformatic, systems biology investigation, was applied to identify
T2DM-associated changes in circulating lipid mediators
2. PCA modeling of clinical variables was used to construct a novel index for T2DM severity
3. Systems biology investigation identified novel biomarkers which are reportive of major shifts in biological
relationships associated with T2DM severity
4. Multiple linear regression modeling was used to generate a lipid mediator dependent model for the
prediction of T2DM severity
p < 0.002
p < 0.0001
1