Performance of cardiometabolic polygenic scores in a high-altitude Peruvian population: the CRONICAS cohort

Polygenic scores (PGS) aggregate the effects of many genetic variants to estimate disease risk, but limited ancestral diversity in discovery datasets may reduce their performance in underrepresented populations. We evaluated the transferability of published cardiometabolic PGS in 679 participants from the high-altitude Puno site of the CRONICAS Cohort Study. Genotype data were imputed, and genetic ancestry proportions were estimated. We assessed PGS for nine traits, including blood pressure, lipids, anthropometric measures, and glycemic traits. Scores included six derived from multi-ancestry genome-wide association studies and three from European-only studies. All PGS were standardized and analyzed using linear regression models adjusted for age and sex, with Bonferroni correction for nine tests (P < 0.0056). Participants were predominantly of Native South American ancestry (93.2%). Higher PGS were significantly associated with blood pressure, lipid levels, body mass index, and waist circumference. Compared with prior performance in Hispanic populations, the variance explained was comparable for blood pressure, body mass index, and waist circumference, but showed attenuation for lipid traits. No significant associations were observed for fasting glucose or insulin. These findings suggest that some cardiometabolic PGS retain predictive utility in this population, while highlighting the need for more diverse genetic studies to improve performance, particularly for glycemic traits.