Award Date

5-1-2024

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

File Format

pdf

File Size

1864 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

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