Elizabeth Barrera

Human populations differ in disease prevalence and phenotypes, but the extent to which differences are caused by genetic factors is unknown for most complex traits. Comparing phenotypic means across populations is confounded by environmental differences and using polygenic predictors can lead to biased inference ^1,2 . Family-based analyses of people of genetically admixed ancestry enable estimation of ancestry effects unconfounded by ancestry–environment correlations. Here we leverage genetic data from admixed adults in the Mexico City Prospective Study ^3,4 to estimate within-family ancestry effects ⁵ . We assessed genetic ancestry and 15 complex traits in 52,583 unrelated people and 39,714 relatives from 17,627 families. At the population level, relative to European ancestry, the effect of Indigenous American ancestry was −1.98 s.d. ( P < 2 × 10 ⁻¹⁶ ) for height and a natural log odds ratio of 1.73 (95% confidence interval, 1.54–1.92) for type 2 diabetes. Within families, the effect of Indigenous American ancestry was −1.51 s.d. ( P = 10 ⁻⁸ ) for height and natural log odds ratio of 5.13 (95% confidence interval, 2.48–7.78) for type 2 diabetes. These effects are supported by between-ancestry differences in trait-increasing allele counts and evidence of selection at trait-associated loci. We found no within-family ancestry effect on educational attainment or other traits despite significant associations at the population level, implying environmental causes or confounding. Overall, this study provides an experimental design to study between-ancestry genetic effects and identifies significant ancestry differences for height, type 2 diabetes and metabolic traits in a genetically diverse population from Mexico City.

Type 2 diabetes (T2D) is a highly heritable, polygenic disease with over 600 loci identified through genome-wide association studies (GWAS). However, despite possessing unique genetic variation shaped by demographic history and admixture, Latin American populations remain markedly underrepresented in global genomic research. To address this gap, we conducted genome- and exome-wide analyses of 19,431 T2D cases and 105,611 controls from the Mexico City Prospective Study (MCPS). We identified 86 independent GWAS associations, including 21 novel signals, 15 of which replicated in external cohorts. Risk alleles at novel loci were enriched in individuals with Indigenous American ancestry. Exome analyses revealed rare and ultra-rare missense variants with substantial risk effects at HNF1A and GCK , as well as a protein-damaging variant in SLC30A8 that reduced T2D risk by 45% in carriers. Integrative analyses indicate that T2D genetic architecture in Mexico is predominantly driven by common regulatory variation acting in the endocrine pancreas. Polygenic risk scores strongly stratified T2D risk and transferred to Indigenous Mexican populations. These findings demonstrate the power of large-scale genetic discovery in diverse populations to refine disease architecture and identify loci with potential therapeutic relevance.