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Activity Number: 46 - Statistical Challenges and Breakthroughs in Diabetes and Obesity Research in the Big Data Era
Type: Topic-Contributed
Date/Time: Sunday, August 8, 2021 : 3:30 PM to 5:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #317410
Title: Microbial Metabolites and Microbiome in Vitamin D/Vitamin D Receptor Deficiency Are Associated with Obesity
Author(s): Yinglin Xia* and Jun Sun
Companies: University of Illinois at Chicago and University of Illinois at Chicago
Keywords: Metabolites; Microbiome; Obesity; principal component analysis (PCA); hierarchical clustering analysis (HCA); random forest(RF)

Microbiota derived metabolites are chemical messengers impacting on host physiology. Vitamin D receptor (VDR) is a key genetic factor shaping microbiome. Obesity is associated with vitamin D deficiency. We hypothesize that host factors and high-fat-diet (HFD) modulate microbial metabolites and microbiome, thus contributing to the high risk of obesity. We investigated microbiome and metabolite data from mice with tissue-specific deletion of VDR and mice fed by HFD or chow diet. We evaluated the high-dimensional metabolite data via PCA, HCA and RF analysis. The statistical differences were tested by three-way ANOVA and Welch’s two-sample t-test. The multiple comparisons were adjusted by FDR. PCA found that samples tended to separate by diet the most with additional grouping by sex within the mice on HFD, which tended to cluster together in HCA. Obese-associated microbiome is very different from their controls. We identified microbiome-associated metabolites, e.g. significant perturbations in phenylalanine, tyrosine, tryptophan and histidine in obesity and vitamin D deficiency. Metabolomic results indicate altered gut homeostasis, which further lead to altered metabolism in obesity.

Authors who are presenting talks have a * after their name.

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