Modeling poster
Download as PPTX, PDF2 likes563 views
This document summarizes a study that used multi-omic profiling to identify metabolic perturbations in type 1 diabetic (T1D) mice compared to non-diabetic mice. The study found: 1) Increased markers of oxidative stress and reduced levels of anti-inflammatory lipids in T1D mice; 2) Elevated triglycerides and reductions in major structural lipids in T1D mice, indicating hypertriglyceridemia; 3) Over 1000 plasma metabolites were measured and biochemical network analysis identified differences between T1D and non-T1D mice related to oxidative stress, inflammation, and lipid metabolism.
Modeling poster
- 1. 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, MO 2NIH 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.