RESUMO
Currently, the vast majority of genomic research cohorts are made up of participants with European ancestry. Genomic medicine will only reach its full potential when genomic studies become more broadly representative of global populations. We are working to support the establishment of genomic medicine in developing countries in Latin America via studies of ethnically and ancestrally diverse Colombian populations. The goal of this study was to analyze the effect of ethnicity and genetic ancestry on observed disease prevalence and predicted disease risk in Colombia. Population distributions of Colombia's three major ethnic groups - Mestizo, Afro-Colombian, and Indigenous - were compared to disease prevalence and socioeconomic indicators. Indigenous and Mestizo ethnicity show the highest correlations with disease prevalence, whereas the effect of Afro-Colombian ethnicity is substantially lower. Mestizo ethnicity is mostly negatively correlated with six high-impact health conditions and positively correlated with seven of eight common cancers; Indigenous ethnicity shows the opposite effect. Malaria prevalence in particular is strongly correlated with ethnicity. Disease prevalence co-varies across geographic regions, consistent with the regional distribution of ethnic groups. Ethnicity is also correlated with regional variation in human development, partially explaining the observed differences in disease prevalence. Patterns of genetic ancestry and admixture for a cohort of 624 individuals from Medellín were compared to disease risk inferred via polygenic risk scores (PRS). African genetic ancestry is most strongly correlated with predicted disease risk, whereas European and Native American ancestry show weaker effects. African ancestry is mostly positively correlated with disease risk, and European ancestry is mostly negatively correlated. The relationships between ethnicity and disease prevalence do not show an overall correspondence with the relationships between ancestry and disease risk. We discuss possible reasons for the divergent health effects of ethnicity and ancestry as well as the implication of our results for the development of precision medicine in Colombia.
RESUMO
Genome-wide association studies have uncovered thousands of genetic variants that are associated with a wide variety of human traits. Knowledge of how trait-associated variants are distributed within and between populations can provide insight into the genetic basis of group-specific phenotypic differences, particularly for health-related traits. We analyzed the genetic divergence levels for 1) individual trait-associated variants and 2) collections of variants that function together to encode polygenic traits, between two neighboring populations in Colombia that have distinct demographic profiles: Antioquia (Mestizo) and Chocó (Afro-Colombian). Genetic ancestry analysis showed 62% European, 32% Native American, and 6% African ancestry for Antioquia compared with 76% African, 10% European, and 14% Native American ancestry for Chocó, consistent with demography and previous results. Ancestry differences can confound cross-population comparison of polygenic risk scores (PRS); however, we did not find any systematic bias in PRS distributions for the two populations studied here, and population-specific differences in PRS were, for the most part, small and symmetrically distributed around zero. Both genetic differentiation at individual trait-associated single nucleotide polymorphisms and population-specific PRS differences between Antioquia and Chocó largely reflected anthropometric phenotypic differences that can be readily observed between the populations along with reported disease prevalence differences. Cases where population-specific differences in genetic risk did not align with observed trait (disease) prevalence point to the importance of environmental contributions to phenotypic variance, for both infectious and complex, common disease. The results reported here are distributed via a web-based platform for searching trait-associated variants and PRS divergence levels at http://map.chocogen.com (last accessed August 12, 2020).