Human populations differ in disease prevalences and in average values of phenotypes, but the extent to which differences are caused by genetic or environmental factors is unknown for most complex traits. Comparing phenotypic means across populations is confounded by environmental differences and comparisons based on polygenic predictors can lead to biased inference. Family-based analyses of genetically admixed individuals offer a powerful framework for disentangling the direct and associated effects of genetic ancestry on phenotypes. Here, we leverage genetic data from admixed adults in the Mexico City Prospective Study (MCPS) to estimate within-family ancestry effects. We quantified associations between genetic ancestry and 15 complex traits among 52,583 unrelated individuals and in 39,714 relatives across 17,627 families. At the population level, relative to a European ancestry baseline, we estimate an effect of Indigenous American (IAM) ancestry of -1.98 standard deviations (P < 2×10-16) for height and a natural log-odds ratio (lnOR) of 1.73 (95% confidence interval [CI] 1.54-1.92) for type 2 diabetes (T2D, P < 2×10-16), and multiple associations with other traits and ancestries. We estimated a within-family direct effect of IAM of -1.51 standard deviations (P = 1.02×10-8) for height and lnOR of 5.13 (95% CI 2.48-7.78, P = 1.51×10-4) for risk of T2D. These direct effects are supported by between-ancestry differences in polygenic burden and evidence of selection at trait-associated loci. In contrast, we found no evidence for a direct effect of ancestry on educational attainment or other study traits despite large and significant associations at the population level, implying environmental causes or confounding. Overall, this study provides an experimental design to study between- ancestry genetic effects for complex traits and reports significant ancestry differences for height, T2D, and metabolic-related traits in a genetically diverse population from Mexico City.

The authors have declared no competing interest.

This work was supported by funding from the Mexican Health Ministry; the National Council for Science and Technology (CONACyT) for Mexico; the Wellcome Trust [058299/Z/99]; Cancer Research UK; the British Heart Foundation [RE/13/1/30181]; and the UK Medical Research Council [MC_UU_00017/2, MR/Z504543/1]. Genotyping was supported through an academic partnership involving the National Autonomous University of Mexico, the University of Oxford, Regeneron Pharmaceuticals, and AstraZeneca. No authors received payment from a pharmaceutical company or other agency for writing this article.

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Ethics approval was obtained from the Mexican Ministry of Health, the Mexican National Council for Science and Technology, and the University of Oxford, UK.

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