Integrating Genetics Into Population-Based Studies
- Author(s): Tai, Caroline
- Advisor(s): Witte, John S
- et al.
As genotyping has become more affordable, there has been a growing effort to leverage genetic data to improve our understanding of the determinants of disease at the population level. New challenges arise with more widespread use of genetic data in epidemiological studies, from developing statistical methods and study designs that leverage genetic data to answering new bioethical questions around sharing research data with genetic information. This dissertation was comprised of three projects that showcase important topics for epidemiologists to consider when using genetic data. These include developing genetic risk scores, determining the analysis method most suitable for the available data; and understanding the ethical, legal and social implications of widely sharing biobank data, particularly genetic data. The first chapter explores differential genetic susceptibility between aggressive and non-aggressive prostate cancer and whether these differences can be used to develop a polygenic risk score for disease aggressiveness. This study was conducted in a Kaiser Permanente patient population electronic medical record and genotype data. Results from this analysis identified a subset of the known prostate cancer variants that are able to differentiate between aggressive and non-aggressive disease. The second chapter contrasts different gene-environment interaction parameters from various study designs using birth defects as the case example. This review aimed to clarify the options for conducting gene-environment interaction studies in the National Birth Defects Prevention Study. Lastly, the third chapter utilizes qualitative methods to explore the perceived harms and benefits of sharing biobank data, which includes genetic information, from the perspective of several stakeholder groups involved in the development of a Kaiser Permanente biobank, the Research Program on Genes, Environment, and Health. Results from this investigation revealed that although the benefits of data sharing are clear, it is paramount that biobank participants are given the opportunity to be involved in the data governance and/or access process. The lessons learned from this dissertation provide evidence that genetic data allows for exploration of inherited susceptibilities that can influence risk of disease but care must be taken to understand which groups of individuals should be compared and what questions are being answered, both scientifically and ethically.