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Uncovering the Molecular Networks of Metabolic Diseases Using Systems Biology


Common complex metabolic diseases (MetDs) such as obesity, type 2 diabetes (T2D), coronary artery disease (CAD) and non-alcoholic fatty liver disease (NAFLD), impose an unprecedented burden on public health worldwide and demonstrate sex differences. Our general hypothesis is that genetic risk factors perturb set of genes in the form of functional gene networks, which subsequently induces the initiation and progression of MetDs. Following this hypothesis, our research focuses on dissecting the molecular networks that are perturbed by genetic risk factors of MetDs utilizing multiomics systems biology approaches. To address this challenge, I embarked interdisciplinary systems biology studies encompassing the development of an accessible multi-omics integration webserver, elucidation of genetically perturbed tissue networks in numerous MetDs, and uncovering the relative contribution of three sex factors in gene regulation in tissues relevant to MetDs. First, I contributed to the development of a user-friendly webserver for multiomics integration, network modeling, and network-based drug repositioning for complex diseases such as MetDs. Second, I investigated the genetically perturbed gene networks that underly various MetDs, namely, lipid traits, diabetes, CAD, and NAFLD. Third, I employed systems biology approaches to uncover the individual and interactive contribution of three sex factors (sex chromosomes, gonads, and sex hormones) in gene regulation in tissues relevant to MetDs. Completion of these projects offer a user-friendly bioinformatic tool, molecular insights, and drug candidates for MetDs.

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