Pathway-Specific Polygenic Risk Scores for Blood Pressure Traits in a West African Cohort
Bormes, G.; Robbin, V.; Chikwore, T.; Zhang, Y.; Choudhury, A.; Hazelhurst, S.; Hanchard, N. A.; Adebamowo, S. N.; Adeyemo, A. A.; Tayo, B.
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IntroductionGenome-wide polygenic risk scores (PRS) are useful for stratifying individuals risk for polygenic diseases such as hypertension. However, a downside of genome-wide PRS is the lack of information about the distribution of risk burden across biologic pathways. We used pathway-specific PRS to investigate these effects within common anti-hypertensive therapy-target pathways on disease risk in a cohort of West Africans. MethodsA total of 11 pathways comprising 1,149 unique genes were selected based on the targets of common anti-hypertensive agents. Pathway-specific PRS for hypertension (individuals with systolic blood pressure (SBP) [≥]140 mmHg, diastolic blood pressure (DBP) [≥]90 mmHg, or taking anti-hypertensive medications) were computed in a cohort of 2,395 individuals. The model was then validated and tested in 1,614 and 966 separate individuals, respectively. All participants were recruited from the International Collaborative Study on Hypertension in Blacks. ResultsIn combined pathways analysis, PRS predicted risk better than base models fitted with only sex, age, and principal components. Compared to base models without the PRS, the incremental increases in R2 attributable to inclusion of PRS in predictive models were 2.6% for SBP (p = 0.009); 1.4% for DBP (p = 0.012); and 1.1% for mean arterial pressure (MAP) (p = 0.044.) PRS from certain pathways (MAPK, cAMP, and adrenergic signaling in cardiomyocytes) could stratify individuals in the top and bottom deciles for DBP. Adrenergic signaling in cardiomyocytes was also predictive of MAP when comparing top and bottom deciles. ConclusionsCombined pathway polygenic risk scores constructed from genes in well-defined genetic pathways predict hypertension risk in individuals of African ancestry. However, pathway-specific PRSs relatively low predictability supports the need to explore the broader influence of genetic, environmental, and epigenetic factors that cannot be captured by pathway-specific PRS alone.
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