Genetic, Molecular, and Environmental Effects on Survival Outcomes and Disparities
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Author(s)
Lee, Kara Keun
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Abstract
While disease mortality rates have steadily decreased over the last century, survival disparities among racial and ethnic population groups persist. Research on population survival disparities tends to be focused on specific diseases, with self-identified race and ethnicity (SIRE) and genetic ancestry (GA) often used interchangeably for studying genetic and environmental effects on disparities. Moreover, the underlying multidimensional factors and mechanisms that drive survival disparities are still largely unknown. This thesis explores the genetic, molecular, and environmental effects on overall and cause-specific survival disparities across population groups by leveraging genetic ancestry inference and population biobank data.
For the first study, cancers with significant survival disparities between GA and SIRE groups were identified using The Cancer Genome Atlas (TCGA), followed by the characterization of differential molecular signatures that interact with GA and exacerbate cancer survival disparities (CSD). For the second study, two of the four cancers showing significant CSD between African and European GA groups were further characterized by constructing GA-specific gene co-expression networks, revealing targeted sets of genes and associated biological processes underlying CSD in African ancestry patients. Finally, the third study broadens the research scope beyond cancer to investigate the overall and leading cause-specific mortality disparities in the UK Biobank. It shifts focus to environmental risk factors contributing to disparities in mortality across different ethnic groups. Numerous blood biomarkers and modifiable environmental and behavioral mortality risk factors were identified, several of which showed differential effects on mortality across ethnic groups.
Altogether, this thesis highlights (1) the group-specific genetic and environmental risk factors that contribute to disparities in survival outcomes, and (2) the utility and importance of population-specific study designs that leverage ancestry information and integrative analysis frameworks, combining clinical outcome data with genomic and socioenvironmental data, for greater clinical relevance and translatability of research findings that can help to improve health equity.
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2022-11-21
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Dissertation