Exploring the Genetics and Biological Pathways of Obesity through Computational Biology and Statistical Approaches Restricted; Files Only

Chen, Hongyue (Spring 2023)

Permanent URL: https://etd.library.emory.edu/concern/etds/w9505176f?locale=zh
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Abstract

Background: Obesity is a chronic and complex disease that has become one of the most serious public health concerns of our time. One significant factor contributing to the development of obesity is genetics, with the fat mass and obesity-associated (FTO) gene considered to carry the highest risk of developing the obesity phenotype. Specifically, the rs1421085 variant of the FTO gene has been shown to have the strongest association with obesity.

Objectives: In this study, we aim to investigate the rs1421085 associated genotype within 49 specific tissues provided by the GTEx project to identify potential obesity-associated genes, tissues, and biological mechanisms. This research will provide valuable insights into the complex genetic and molecular mechanisms underlying obesity and may lead to new approaches for preventing and treating this growing public health issue.

Methods: We utilized various data resources in this study, including 49 raw tissue-specific datasets from the open-access GTEx Analysis version 8, as well as curated gene sets from BioCarta and KEGG subsets of canonical pathways. We performed differential gene expression analysis on the normalized TPM gene data to discover quantitative changes in expression levels between groups with rs1421085. Additionally, we employed Gene Set Enrichment Analysis (GSEA) to determine whether a previously defined set of genes showed statistically significant, concordant differences between phenotypes. To carry out these analyses, we utilized the PLINK 1.07 and RStudio Version 4.1.2 software tools.

Results: The "C" allele of the rs1421085 gene variant is a risk allele for obesity, according to GTEx statistics. The small intestine was found to be the most rs1421085-associated tissue, with increased transit time potentially due to effective nutrient absorption and decreased satiety signals. The valid genes associated with rs1421085 were TBC1D3E, CCL3L3, CSF3, CXCL3, and IL6, with evidence from various studies. Pathway analysis revealed cytokine-cytokine receptor interaction and IL-17 signaling pathway as associated pathways, potentially linking chronic inflammation with obesity.

Conclusions: In the studies, we explored candidate genes, biological pathways, and tissues associated with obesity through computational biology and statistical methods. The research given the ideas of obesity is inflammation associated, which give researchers an insight in the field of future obesity study.

Table of Contents

Introduction: 1-2 Method: 2-5 Results: 5-12 Discussion: 12-13 Reference: 14-17

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