Award Date
May 2024
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Mathematical Sciences
First Committee Member
Amei Amei
Second Committee Member
Malwane Ananda
Third Committee Member
Farhad Shokoohi
Fourth Committee Member
Mira Han
Number of Pages
57
Abstract
Human diseases are often caused by a complex interplay of multiple factors, including genetics and environmental factors. These factors can play critical roles in the development and progression of diseases. Although genome-wide association studies (GWAS) have successfully identified many genetic variants associated with human diseases, the estimated effects of these variants are small and can explain only a relatively small portion of the heritability of the underlying diseases.
Detecting gene-environment interactions (G × E) can shed light on the biological mechanisms of diseases. However, most existing methods that investigate G × E only look at how one environmental factor interacts with either common or rare genetic variants, not both. In this study, we propose two approaches to detect interaction effects of an environmental factor and a set of genetic markers containing both rare and common variants.
The first approach is derived from the MinQue for Summary statistics (MQS) method and has been adapted in our study to develop two sub-methods: the MArginal Gene-Environment Interaction Test with RANdom or FIXed genetic effects (MAGEIT_RAN or MAGEIT_FIX). Our second approach leverages the Generalized Method of Moments (GMM), leading to the Gene-Environment Interaction Test based on GMM (GEITGMM). Through simulation studies and real data analysis, we evaluate the performance of these methods. Both the MQS-based MAGEIT_RAN and MAGEIT_FIX, and the GMM-based GEITGMM are grounded in moment estimation and offer analytical tools for examining gene-environment interactions.
Keywords
gene-environment interaction; genome-wide study; method of moments; mixed effects model
Disciplines
Mathematics | Statistics and Probability
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Shen, Linchuan, "Identifying Disease-Related Gene-Environment Interactions Based on Method of Moments" (2024). UNLV Theses, Dissertations, Professional Papers, and Capstones. 5079.
http://dx.doi.org/10.34917/37650905
Rights
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