Heatmap displaying hierarchically clustered Spearman correlations between animal characteristics (weight and glucose) and major classes of measured metabolites and lipids. CLUSTER ANALYSIS Comprehensive measurements of > 1000 plasma lipids and metabolites were used to identify age- and sex-independent metabolic perturbations associated with T1D, which include: 1) increased carbohydrate oxidation products, glucono delta lactone and galactonic acid, and reduced cysteine, methionine and threonic acid; supporting increased oxidative stress 2) reductions in circulating polyunsaturated fatty acids and lipid signaling mediators, most notably arachidonic acid (AA) and AA-derived eicosanoids, implying impaired states of systemic inflammation 3) elevations in circulating triacylglyercides reflective of hypertriglyceremia and 4) reductions in major structural lipids, most notably lysophosphatidylcholines and phosphatidylcholines. Multi-omic profiling of type 1 diabetes progression in NOD mice reveals increased markers oxidative stress and hypertriglyceremia Dmitry Grapov 1,2 , Johannes Fahrmann 2 , Jun Yang 2 , Bruce Hammock 2 , Oliver Fiehn 2 , Manami Hara 3 1 Genome Analytics, Monsanto, Chesterfield, MO 2 NIHWest Coast Metabolomics Center, Davis, CA; University of California Davis, Davis, California 3 Department of Medicine, The University of Chicago, Chicago, Illinois METHODS Reference: Systemic Alterations in the Metabolome of Diabetic NOD Mice Delineate Increased Oxidative Stress Accompanied by Reduced Inflammation and Hypertriglyceridemia American Journal of Physiology - Endocrinology and Metabolism 2015 Vol. no. , DOI: 10.1152/ajpendo.00019.2015 Non-obese diabetic (NOD) mice are a commonly- used model of type 1 diabetes (T1D). However, not all animals develop hyperglycemia despite undergoing similar pancreatic autoimmune insult, which presents a unique opportunity to identify metabolic markers of T1D progression. A multi- omic approach comprised of gas chromatography time-of-flight (GC-TOF), ultra high performance liquid chromatography accurate mass quadruple time-of-flight (UHPLC-qTOF) and UHPLC-tandem mass spectrometry platforms, was used to identify circulating metabolic alterations in NOD mice progressing or not progressing to T1D. ABSTRACT Biochemical and structural similarity network displaying metabolic differences between diabetic and non- diabetic NOD mice. Metabolites are connected based precursor to product relationships (KEGG) or structural similarities in molecular fingerprints (PubChem, Tanimoto>0.07). BIOCHEMICAL and STRUCTURAL SIMILARITY NETWORK Primary Metabolites Complex Lipids Signaling Lipids Number of significantly altered metabolites between diabetic and non-diabetic animals. False discovery rate (FDR) adjusted Mann-Whitney U test p-value < 0.05. STATISTICAL ANALYSIS Significantly perturbed eicosanoids (p<0.05) within the KEGG arachidonic acid metabolism pathway. Pathway enrichment was determined based on FDR adjusted hypergeometric test p-values < 0.05 for KEGG pathways for Mus musculus. Figure displays relative fold changes in means between diabetic and non-diabetic animals. BIOCHEMICAL PATHWAY ENRICHMENT CONCLUSIONS Partial correlations between top predictors of animals’ diabetic status. Relationships (FDR adjusted p-value<0.05) are displayed for statistically different (FDR adjusted p-value<0.05 )and O-PLS- DA selected discriminants between diabetic and non-diabetic animals. Node size shows the fold change in means relative to non-diabetics. EMPIRICAL NETWORK Acknowledgements This research is supported in part by the NIH grant 1 U24 DK097154 and NIH West Coast Metabolomics Center Pilot Program.
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Heatmap displaying hierarchically clustered Spearman correlations between animal characteristics (weight and glucose) and major classes of measured metabolites and lipids.
CLUSTER ANALYSIS
Comprehensive measurements of > 1000 plasma lipids and
metabolites were used to identify age- and sex-independent
metabolic perturbations associated with T1D, which include:
1) increased carbohydrate oxidation products, glucono delta
lactone and galactonic acid, and reduced cysteine,
methionine and threonic acid; supporting increased oxidative
stress 2) reductions in circulating polyunsaturated fatty acids
and lipid signaling mediators, most notably arachidonic acid
(AA) and AA-derived eicosanoids, implying impaired states of
systemic inflammation 3) elevations in circulating
triacylglyercides reflective of hypertriglyceremia and 4)
reductions in major structural lipids, most notably
lysophosphatidylcholines and phosphatidylcholines.
Multi-omic profiling of type 1 diabetes progression in NOD mice reveals increased markers
oxidative stress and hypertriglyceremia
Dmitry Grapov1,2, Johannes Fahrmann2, Jun Yang2, Bruce Hammock2, Oliver Fiehn2, Manami Hara3
1Genome Analytics, Monsanto, Chesterfield, MO2NIH West Coast Metabolomics Center, Davis, CA; University of California Davis, Davis, California
3Department of Medicine, The University of Chicago, Chicago, Illinois
METHODS
Reference:
Systemic Alterations in the Metabolome of Diabetic NOD Mice Delineate Increased
Oxidative Stress Accompanied by Reduced Inflammation and Hypertriglyceridemia
American Journal of Physiology - Endocrinology and
Metabolism 2015 Vol. no. , DOI: 10.1152/ajpendo.00019.2015
Non-obese diabetic (NOD) mice are a commonly-
used model of type 1 diabetes (T1D). However, not
all animals develop hyperglycemia despite
undergoing similar pancreatic autoimmune insult,
which presents a unique opportunity to identify
metabolic markers of T1D progression. A multi-omic approach comprised of gas chromatography
time-of-flight (GC-TOF), ultra high performance
liquid chromatography accurate mass quadruple
time-of-flight (UHPLC-qTOF) and UHPLC-tandem
mass spectrometry platforms, was used to identify
circulating metabolic alterations in NOD mice
progressing or not progressing to T1D.
ABSTRACT
Biochemical and structural similarity network displaying metabolic differences between diabetic and non-diabetic NOD mice. Metabolites are connected based precursor to product relationships (KEGG) or structural similarities in molecular fingerprints (PubChem, Tanimoto>0.07).
BIOCHEMICAL and STRUCTURAL SIMILARITY NETWORK
Primary Metabolites
Complex Lipids
Signaling Lipids
Number of significantly altered metabolites between diabetic and non-diabetic animals. False discovery rate (FDR) adjusted Mann-Whitney U test p-value < 0.05.
STATISTICAL ANALYSIS
Significantly perturbed eicosanoids (p<0.05) within the KEGG arachidonic acid metabolism pathway. Pathway enrichment was determined based on FDR adjusted hypergeometric test p-values < 0.05 for KEGG pathways for Mus musculus. Figure displays relative fold changes in means between diabetic and non-diabetic animals.
BIOCHEMICAL PATHWAY ENRICHMENT
CONCLUSIONS
Partial correlations between top predictors of animals’ diabetic status. Relationships (FDR adjusted p-value<0.05) are displayed for statistically different (FDR adjusted p-value<0.05 )and O-PLS-DA selected discriminants between diabetic and non-diabetic animals. Node size shows the fold change in means relative to non-diabetics.
EMPIRICAL NETWORK
Acknowledgements
This research is supported in part by the NIH grant 1 U24 DK097154 and NIH West Coast Metabolomics Center Pilot Program.
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