Chemistry and Chemical Biology ETDs

Publication Date

Summer 7-29-2025

Abstract

Obesity has reached epidemic proportions globally, driven by a complex interplay of genetic, environmental, and socio-economic factors. While genome-wide association studies have identified many genetic variants associated with obesity, detecting true associations remains challenging due to small effect sizes and statistical noise. In this study, we advanced the understanding of obesity’s genetic architecture using two complementary approaches. First, we applied Gene set Refinements through Interacting Networks (GRIN) and advanced prioritization algorithms to identify and rank high-confidence obesogenic genes from 22 genome-wide association studies. Second, we investigated the functional impact of a common, apparently benign haplotype in the NPC1 gene, revealing significant differences in lipid accumulation and protein expression through integrated experimental and computational analyses. These findings provide a prioritized list of obesogenic genes and demonstrate that a common haplotype within one such gene has notable functional consequences, offering new insights and identifying targets for future research and potential therapeutic intervention.

Project Sponsors

UNM

Language

English

Keywords

GWAS, Bioinformatics, Obesity, Genetics, Biochemistry, Metabolism

Document Type

Dissertation

Degree Name

Chemistry and Chemical Biology

Level of Degree

Doctoral

Department Name

Department of Chemistry and Chemical Biology

First Committee Member (Chair)

William Sherman Garver

Second Committee Member

Jeffrey Long

Third Committee Member

Jeremy Edwards

Fourth Committee Member

Michael Garvin

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Available for download on Thursday, July 29, 2027

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