SUGAR metabolomics dataset

Published: 30 April 2018| Version 1 | DOI: 10.17632/9z7ncwvxnz.1
Contributor:
Baback Roshanravan

Description

Chronic kidney disease (CKD) leads to decreased sensitivity to the metabolic effects of insulin. We examined the plasma metabolome in 95 adults without diabetes in the fasted state (58 with moderate-severe CKD, 37 with normal glomerular filtration rate) of whom 60 had plasma collected during a hyperinsulinemic-euglycemic clamp (40 with CKD). We assessed heterogeneity in the response to insulin to identify potential cellular metabolic pathways linking CKD with insulin resistance. In the fasting state, differences between CKD and control subjects included significant abnormalities in tryptophan metabolism, ubiquinone biosynthesis, and the TCA cycle. Insulin infusion markedly decreased plasma metabolite levels, predominantly amino acids and their metabolites. CKD was associated with attenuated insulin-induced changes in nicotinamide, arachidonic acid, and glutamine/glutamate metabolic pathways. These findings suggest that broad disruption in amino acid metabolism and mitochondrial function as putative mechanisms or manifestations of the impaired anabolic effects of insulin in CKD.

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Steps to reproduce

Since metabolite distributions were greatly skewed, all plasma metabolite concentrations were transformed by log(1+x) prior to performing statistical analysis. To compare the fold changes in metabolite levels between CKD and non-CKD participants, we used linear regression with robust Huber-White standard errors of the log-transformed metabolite on CKD status, additionally adjusted for the potential confounders of age, sex, race/ethnicity (white versus non-white) and weight. To account for the correlation of measurements within participants, we examined the fold changes associated with the clamp procedure via a linear mixed model with random intercepts, regressing the log-transformed metabolite on the sample type (during clamp versus fasting sample), adjusted for the covariates listed above, as well as batch. Finally, to evaluate whether the effect of the hyperinsulinemic-euglycemic clamp procedure differed between CKD and non-CKD participants, we again used a linear mixed model approach with random intercepts, in which the log-transformed metabolite was regressed on sample type (clamp versus fasting), CKD status (CKD versus non-CKD) and the interaction of the two, additionally adjusting for age, sex, race/ethnicity, weight, and batch. To account for multiple comparisons, in each analysis we used a Benjamini-Hochberg false discovery rate of 10% to declare statistical significance. Under this approach, 10% of the metabolites identified as significant would be expected to be false positives. All of the statistical analyses described above were conducted using R, version 3.4.050. Targeted metabolic pathway analysis was performed using Metaboanalyst version 3.551. Pathway topology analysis was performed analyzing differences in fasting plasma metabolite between CKD and controls. Fold change analysis of discrete metabolites was performed using Metaboanalyst software to calculate the absolute value change between fasting and during insulin infusion plasma metabolites group averages for the entire cohort which was used to construct a volcano plot. Using pathway topology analysis, we identified significant metabolic pathways affected by insulin infusion using log transformed pre- and during infusion metabolite levels. Determination of significant metabolic pathways modified by CKD status involved comparing the fold change of each metabolite calculated by subtracting log-transformed values of during clamp from the pre-clamp time points. Data is presented for hyperinsulinemic-euglycemic clamp-induced plasma changes in the overall cohort and comparing CKD to non-CKD.

Institutions

University of Washington

Categories

Metabolomics, Chronic Kidney Disease, Insulin Resistance

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