A Multi-Scale, Systems Biology View of Fat Distribution and Storage Provides Novel Insight into Gene Regulation in Adipose Tissue

Author: ORCID icon orcid.org/0000-0002-6190-9037
Reed, Jordan, Biomedical Engineering - School of Engineering and Applied Science, University of Virginia
Civelek, Mete, MD-BIOM Biomedical Eng, University of Virginia

Adipose tissue is a complex organ that is capable of maintaining metabolic homeostasis. Storing fat, and specifically storing fat in the abdomen, increases the risk of cardio-metabolic diseases. Abdominal fat confers disease risk by inducing inflammation and insulin resistance. Pathways in the brain control overall obesity, while the preferential storage of fat in abdominal depots is likely controlled intrinsically by adipose tissue. Obesity and fat distribution are both complex traits, and genetic, lifestyle, and environmental factors interact to modify risk. Our understanding of the cellular and molecular mechanisms that cause obesity has allowed us to develop targeted therapeutics to treat it, but our understanding of body fat distribution is more limited.
In this dissertation, we investigate how gene expression and regulation in adipose tissue can influence fat storage at multiple biological scales. Chapter 1 summarizes abdominal and lower body adipose tissue function in health and disease states, how adipocytes contribute to tissue expansion. We discuss the genetics of complex diseases and review the genetics of obesity and fat distribution.
In Chapter 2, we predicted genes that were likely to regulate fat distribution in adipose tissue by modeling the gene-gene interactions using Bayesian networks. We first explored the parameters that influence the predictive power and biological Visibility
relevance of the networks. We used optimal parameters to construct sex- and depot-specific models of adipose tissue gene regulation, and identified the putative network regulators in two independent datasets.
In Chapter 3, we narrowed this list of putative fat distribution regulators by considering publicly available data. We prioritize seven candidate genes within the Wnt signaling pathway or in mitochondria. We identify novel functions for five genes in adipogenesis or in mitochondrial function.
In Chapter 4, we study how diet composition and genetic background interact to influence body weight and other metabolic parameters in mice. We found that genetic background accounted for much of the variation, though diet was able to modify these effects. We identified genes in visceral adipose tissue that also respond to genetic background and diet interactions and found that these were partially explanatory of the observed phenotypes.
In Chapter 5, we discuss how our findings align with known biology and highlight some of our novel findings and predictions. Taking a systems biology approach, we integrate results from Chapters 2 and 3 to assess the predictive power of our models. We discuss future experimental and computational research directions.
Broadly, these studies investigated the regulation of gene expression in adipose tissue and the consequences on whole-body fat storage and metabolism. We identify novel regulators of adipocyte fat storage, and hypothesize a role for many more. We integrate predictive and experimental data at multiple biological scales to provide a holistic picture of how gene expression influences tissue function in health and disease.

PHD (Doctor of Philosophy)
Adipose Tissue, Bayesian Network, Gene Expression
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