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EFFICIENT TWO-STEP TESTING APPROACHES FOR DETECTING
GENE-ENVIRONMENT INTERACTIONS IN GENOME-WIDE ASSOCIATION
STUDIES, WITH AN APPLICATION TO THE CHILDREN’S HEALTH STUDY
by
Cassandra Elizabeth Murcray
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BIOSTATISTICS)
December 2010
Copyright 2010 Cassandra Elizabeth Murcray
Object Description
| Title | Efficient two-step testing approaches for detecting gene-environment interactions in genome-wide association studies, with an application to the Children’s Health Study |
| Author | Murcray, Cassandra Elizabeth |
| Author email | murcray@usc.edu; cassie.murcray@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Biostatistics |
| School | Keck School of Medicine |
| Date defended/completed | 2010-08-17 |
| Date submitted | 2010 |
| Restricted until | Unrestricted |
| Date published | 2010-09-03 |
| Advisor (committee chair) | Gauderman, William |
| Advisor (committee member) |
Conti, David Sun, Fengzhu |
| Abstract | Many complex diseases (e.g. asthma, diabetes) are likely to be a result of the interplay of genes and environmental exposures. The standard analysis in a genome-wide association study (GWAS) scans for main effects and ignores the potentially useful information in the available exposure data. This dissertation explores alternative approaches to detect gene-environment interactions (G×E) in GWA studies. The first chapter explores a novel approach aimed at prioritizing the large number of SNPs tested to highlight those most likely to be involved in a G×E interaction. This approach screens all markers available in a GWAS on a test that models the G-E association induced by an interaction in the combined case-control sample. Power and Type I error of this approach are compared to a traditional approach. In the second chapter of this dissertation, I explore alternative two-step approaches through the development of a likelihood based software package designed to compute power and sample size of a variety of approaches to detect G×E interactions. In the final chapter, I demonstrate the use of this software package in the optimization and analysis of a nested case-control sample from the Children’s Health Study to investigate heterogeneity of genetic risk by subgroups defined by environmental exposures on asthma susceptibility in children in southern California. I optimize this procedure to efficiently scan for G×E interactions that effect asthma susceptibility for binary (e.g.i.e. in utero tobacco smoke, close proximity to a major road) exposure, distance to major road or freeway) and continuous exposures (e.g. i.e. PMpm2.5, ozone, traffic-related pollution NOx) exposures. |
| Keyword | gene; environment; interactions; association studies; case-control |
| Geographic subject (state) | California |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m3421 |
| Rights | Murcray, Cassandra Elizabeth |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Murcray-4052 |
| Archival file | uscthesesreloadpub_Volume26/etd-Murcray-4052.pdf |
Description
| Title | Page 1 |
| Full text | EFFICIENT TWO-STEP TESTING APPROACHES FOR DETECTING GENE-ENVIRONMENT INTERACTIONS IN GENOME-WIDE ASSOCIATION STUDIES, WITH AN APPLICATION TO THE CHILDREN’S HEALTH STUDY by Cassandra Elizabeth Murcray A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (BIOSTATISTICS) December 2010 Copyright 2010 Cassandra Elizabeth Murcray |
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