Population genomics and ancestral origins for health disparities research

Ameliorating health disparities – avoidable differences in health outcomes between population groups – is both a social imperative and a pressing scientific challenge. The relative importance of genetic versus environmental effects for health disparities, i.e. the enduring question of nature versus nurture, particularly for complex common diseases that have multifactorial etiologies, has long been debated. The importance of social and environmental determinants of health disparities is well established, whereas the role of genetics is more controversial. Nevertheless, these two classes of effects are not mutually exclusive; genes are expressed and function in the context of specific environmental conditions. Thus, it is reasonable to consider the influence of genetic and environmental factors on health disparities together. Indeed, the importance of interactions between genetic and environmental factors for shaping health outcomes has recently been recognized as a promising avenue for health disparities research. The major aim of this thesis was to investigate both genetic and environmental contributions to health disparities by leveraging population biobanks and large genomic datasets. Biobank datasets, which include collections of genetic data together with rich clinical, phenotypic, and environmental data for thousands of individuals, are ideally suited for this purpose. The thesis consists of two main parts: (1) population pharmacogenomics, and (2) complex common health disparities. The first part of the thesis investigates the partitioning of pharmacogenomic variation between populations in different geographic and socioeconomic locales (in Colombia and the US) to study differences in predicted therapeutic response among populations, and the second part of the thesis illustrates the use of a large population biobank to understand health disparities and their complex relationship to genetic, environmental, and social factors. Results from the first part of the thesis highlight how population genomics can be a powerful tool for clinical decision-making especially in settings where resources are limited (e.g. Colombia) or where resources are unequally distributed between population groups (e.g. US). These findings support the precision public health paradigm, which shifts the focus of genomic characterization efforts from individuals to populations to identify interventions that work best at the population level. This allows for uniform priors for treatment to be adjusted based on population membership. Results from the second part of the thesis demonstrate the massive potential of employing biobanks to investigate health disparities and to decompose their effects into genetic and environmental components. Interactions discovered between genetic and environmental risk factors underscore how environmental effects on disease can differ among ancestry groups, suggesting the need for group-specific interventions. Beyond these specific research advances, this thesis also takes a step towards addressing the lack of diversity in genomics research. Genomics research is currently biased towards European ancestry cohorts, and results from these studies may not transfer to more diverse ancestry groups. This genomics research gap has the potential to exacerbate existing health disparities. The focus on ancestrally diverse populations, both in developing countries and for underrepresented minority groups in the US and the UK, has the potential to support health equity through ancestrally-guided insights and interventions.Ph.D

Population Pharmacogenomics for Precision Public Health in Colombia

While genomic approaches to precision medicine hold great promise, they remain prohibitively expensive for developing countries. The precision public health paradigm, whereby healthcare decisions are made at the level of populations as opposed to individuals, provides one way for the genomics revolution to directly impact health outcomes in the developing world. Genomic approaches to precision public health require a deep understanding of local population genomics, which is still missing for many developing countries. We are investigating the population genomics of genetic variants that mediate drug response in an effort to inform healthcare decisions in Colombia. Our work focuses on two neighboring populations with distinct ancestry profiles: Antioquia and Chocó. Antioquia has primarily European genetic ancestry followed by Native American and African components, whereas Chocó shows mainly African ancestry with lower levels of Native American and European admixture. We performed a survey of the global distribution of pharmacogenomic variants followed by a more focused study of pharmacogenomic allele frequency differences between the two Colombian populations. Worldwide, we found pharmacogenomic variants to have both unusually high minor allele frequencies and high levels of population differentiation. A number of these pharmacogenomic variants also show anomalous effect allele frequencies within and between the two Colombian populations, and these differences were found to be associated with their distinct genetic ancestry profiles. For example, the C allele of the single nucleotide polymorphism (SNP) rs4149056 [Solute Carrier Organic Anion Transporter Family Member 1B1 (SLCO1B1)∗5], which is associated with an increased risk of toxicity to a commonly prescribed statin, is found at relatively high frequency in Antioquia and is associated with European ancestry. In addition to pharmacogenomic alleles related to increased toxicity risk, we also have evidence that alleles related to dosage and metabolism have large frequency differences between the two populations, which are associated with their specific ancestries. Using these findings, we have developed and validated an inexpensive allele-specific PCR assay to test for the presence of such population-enriched pharmacogenomic SNPs in Colombia. These results serve as an example of how population-centered approaches to pharmacogenomics can help to realize the promise of precision medicine in resource-limited settings

Investigation of hypertension and type 2 diabetes as risk factors for dementia in the All of Us cohort

The World Health Organization recently defined hypertension and type 2 diabetes (T2D) as modifiable comorbidities leading to dementia and Alzheimer's disease. In the United States (US), hypertension and T2D are health disparities, with higher prevalence seen for Black and Hispanic minority groups compared to the majority White population. We hypothesized that elevated prevalence of hypertension and T2D risk factors in Black and Hispanic groups may be associated with dementia disparities. We interrogated this hypothesis using a cross-sectional analysis of participant data from the All of Us (AoU) Research Program, a large observational cohort study of US residents. The specific objectives of our study were: (1) to compare the prevalence of dementia, hypertension, and T2D in the AoU cohort to previously reported prevalence values for the US population, (2) to investigate the association of hypertension, T2D, and race/ethnicity with dementia, and (3) to investigate whether race/ethnicity modify the association of hypertension and T2D with dementia. AoU participants were recruited from 2018 to 2019 as part of the initial project cohort (R2019Q4R3). Participants aged 40-80 with electronic health records and demographic data (age, sex, race, and ethnicity) were included for analysis, yielding a final cohort of 125,637 individuals. AoU participants show similar prevalence of hypertension (32.1%) and T2D (13.9%) compared to the US population (32.0% and 10.5%, respectively); however, the prevalence of dementia for AoU participants (0.44%) is an order of magnitude lower than seen for the US population (5%). AoU participants with dementia show a higher prevalence of hypertension (81.6% vs. 31.9%) and T2D (45.9% vs. 11.4%) compared to non-dementia participants. Dominance analysis of a multivariable logistic regression model with dementia as the outcome shows that hypertension, age, and T2D have the strongest associations with dementia. Hispanic was the only race/ethnicity group that showed a significant association with dementia, and the association of sex with dementia was non-significant. The association of T2D with dementia is likely explained by concurrent hypertension, since > 90% of participants with T2D also had hypertension. Black race and Hispanic ethnicity interact with hypertension, but not T2D, to increase the odds of dementia. This study underscores the utility of the AoU participant cohort to study disease prevalence and risk factors. We do notice a lower participation of aged minorities and participants with dementia, revealing an opportunity for targeted engagement. Our results indicate that targeting hypertension should be a priority for risk factor modifications to reduce dementia incidence