Abstract

Abstract Genetic factors, together with other environmental and/or social factors, contribute to the risk of diseases in any population. There is a well-recognized need to be more inclusive of diverse populations in genetic studies, but several obstacles continue to exist, including, but not limited to, the difficulty of recruiting individuals from diverse populations in large numbers and the lack of representation in available genomic references. These obstacles notwithstanding, studying diverse populations would provide informative and population-specific insights important for the healthcare management of a population. As an example of an understudied population, the Native Hawaiians have a unique genetic history that can be leveraged to enhance the design and interpretation of genetic studies. It has been shown that the predominant Polynesian genetic ancestry component in Native Hawaiians is associated with elevated risk of cardiometabolic diseases. This finding is consistent with, though not a proof of, the hypothesis that there exist population-enriched genetic variants underlying the risk of these diseases. At the same time, currently available genomic resources underserve the Native Hawaiians due to a lack of representation, such that genetic variants strongly associated with diseases could not be systematically discovered. Therefore, by developing key genomic resources, integrating evolutionary thinking into genetic epidemiology, and partnering with the community, we will have the opportunity to efficiently advance our knowledge of the genetic risk factors, ameliorate health disparity, and improve healthcare in this underserved population. Citation Format: Charleston Chiang. The opportunities and challenges of integrating population histories into genetic studies for diverse populations [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr IA-20.

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