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Kind, T.

Publications and source records attributed to Kind, T..

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The circulating lipidome is largely defined by sex descriptors in the GOLDN, GeneBank and the ADNI studies

Biological sex is one of the major anthropometric factors which influences physiology, metabolism and health status. We have investigated the effect of sexual dimorphism on the blood lipidome profile in three large population level studies - the Alzheimers disease neuroimaging initiative - ADNI (n =806), the GeneBank Functional Cardio-Metabolomics cohort (n= 1015) and the Genetics of Lipid lowering Drugs and Diet Network - GOLDN (n=422). In total, 355 unique lipids from 15 lipid classes were detected across all three studies using LC-MS. Sixty percent of these lipids differed between men and women in all three cohorts, and up to 87% of all lipids demonstrated sex differences in at least one cohort. ChemRICH enrichment statistics on lipid classes showed that phosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, ceramides, sphingomyelins and cholesterol esters were found at higher levels in female subjects while triacylglycerols and lysophosphatidylcholines were found at higher levels in male participants across the three cohorts. This strong sex effect on the blood lipidome suggests that specific regulatory mechanisms may exist that regulate lipid metabolism in a different manner between men and women. Cohort studies involving blood lipidomics should consider separate analyses for male and female participants instead of combined analyses treating sex as a confounding factor.

biochemistry

A comprehensive plasma metabolomics dataset for a cohort of mouse knockouts within the international mouse phenotyping consortium

Mouse knockouts allow studying gene functions. Often, multiple phenotypes are impacted when a gene is inactivated. The International Mouse Phenotyping Consortium (IPMC) has generated thousands of mouse knockouts and catalogued their phenotype data. We have acquired metabolomics data from 220 plasma samples of 30 mouse gene knockouts and corresponding wildtype mice from IMPC. To acquire comprehensive metabolomics data, we have used liquid chromatography (LC) combined with mass spectrometry (MS) for detecting polar and lipophilic compounds in an untargeted approach. We have also used targeted methods to measure bile acids, steroids and oxylipins. In addition, we have used gas chromatography GC-TOFMS for measuring primary metabolites. The metabolomics dataset reports 832 unique structurally identified metabolites from 124 chemical classes as determined by ChemRICH software. The GCMS and LCMS raw data files, intermediate and finalized data matrices, R-Scripts, annotation databases and extracted ion chromatograms are provided in this data descriptor. The dataset can be used for subsequent studies to link genetic variants with molecular mechanisms and phenotypes.\n\nData SetThe dataset is available at the MetabolomicsWorkbench repository (accession ID: ST001154)\n\nData Set Licenselicense under which the data set is made available (CC0).

bioinformatics