Abstract
Lipids are ubiquitous metabolites with diverse functions; abnormalities in lipid metabolism appear to be related to complications from multiple diseases, including type 2 diabetes. Through technological advances, the entire lipidome has been characterized and researchers now need computational approaches to better understand lipid network perturbations in different diseases. Using a mouse model of type 2 diabetes with microvascular complications, we examined lipid levels in plasma and in renal, neural, and retinal tissues to identify shared and distinct lipid abnormalities. We used correlation analysis to construct interaction networks in each tissue, to associate changes in lipids with changes in enzymes of lipid metabolism, and to identify overlap of coregulated lipid subclasses between plasma and each tissue to define subclasses of plasma lipids to use as surrogates of tissue lipid metabolism. Lipid metabolism alterations were mostly tissue specific in the kidney, nerve, and retina; no lipid changes correlated between the plasma and all three tissue types. However, alterations in diacylglycerol and in lipids containing arachidonic acid, an inflammatory mediator, were shared among the tissue types, and the highly saturated cholesterol esters were similarly coregulated between plasma and each tissue type in the diabetic mouse. Our results identified several patterns of altered lipid metabolism that may help to identify pathogenic alterations in different tissues and could be used as biomarkers in future research into diabetic microvascular tissue damage.
Highlights
Lipids are ubiquitous metabolites with diverse functions; abnormalities in lipid metabolism appear to be related to complications from multiple diseases, including type 2 diabetes
The metabolic response of these tissues to diabetes has historically been thought to be similar and downstream of altered glucose metabolism [20], we recently found that glucose and fatty acid oxidation are tissue specific and dissimilar among the three diabetic end-organ target tissues of kidney, nerve, and retina [21]
To test whether any prespecified sets of lipids are differentially coexpressed between plasma and any of the tissues under study, we propose the following procedure, which provides adequate power in detecting the differentially coexpressed sets, while simultaneously keeping the false discovery rate (FDR) controlled at a prespecified level (e.g., 0.1)
Summary
Lipids are ubiquitous metabolites with diverse functions; abnormalities in lipid metabolism appear to be related to complications from multiple diseases, including type 2 diabetes. A limitation of current comprehensive shotgun lipidomic techniques is that lipids are identified by class group along with the total number of carbon molecules and double bonds in the aliphatic side chains. This information does not allow for the definitive identification of most lipid species because structural isomers cannot be positively assigned. This limits input primarily to the lipid class level and restricts the ability to map these lipid metabolites to databases such as Kyoto Encyclopedia of Genes and Genomes. Reconstruction of interaction networks among lipid species from their quantitative MS profiles would provide insights into associated biological mechanisms [3]
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