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Ancestral genetic components are consistently associated with the complex trait landscape in European biobanks

Pankratov, Vasili, Mezzavilla, Massimo, Aneli, Serena, Kuznetsov, Ivan A., Fusco, Daniela, Wilson, James F., Metspalu, Mait, Provero, Paolo, Pagani, Luca, Marnetto, Davide·2024·European Journal of Human Genetics
DOI 10.1038/s41431-024-01678-9PMC PMC11576899

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Abstract

The genetic structure in Europe was mostly shaped by admixture between the Western Hunter-Gatherers, Early European Farmers and Steppe Bronze Age ancestral components. Such structure is regarded as a confounder in GWAS and follow-up studies, and gold-standard methods exist to correct for it. However, it is still poorly understood to which extent these ancestral components contribute to complex trait variation in present-day Europe. In this work we harness the UK Biobank to address this question. By extensive demographic simulations, exploiting data on siblings and incorporating previous results we obtained from the Estonian Biobank, we carefully evaluate the significance and scope of our findings. Heart rate, platelet count, bone mineral density and many other traits show stratification similar to height and pigmentation traits, likely targets of selection and divergence across ancestral groups. We show that the reported ancestry-trait associations are not driven by environmental confounders by confirming our results when using between-sibling differences in ancestry. The consistency of our results across biobanks further supports this and indicates that these genetic predispositions that derive from post-Neolithic admixture events act as a source of variability and as potential confounders in Europe as a whole.

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Fig. 1 Simulation results. A Effect on βcovA(1) of reference populations differentiation, defined as the difference between the highest and the second highest mean genetic values among the three ancestries, normalized by trait standard deviation in the simulated present-day population (see Supplementary Text for details). B The same as A but plotting on x-axis local ancestry’s mean genetic values instead. C βcovA(1) values as a function of trait optimum in the ancestry with the highest genetic value (p = 1). The x-axis indicates the trait optimum in this ancestry, while other ancestries have an optimum set to 0. Three sub-panels present results of simulations with different fitness function SD (ω) and heritability (h2) values. Each boxplot is based on 50 individual simulations. Scenarios with more than 50 simulation runs were randomly downsampled. The boxes show 25th, 50th and 75th quantiles, while the whiskers show values within 1.5 times the interquartile range (IQR).
Fig. 1 Simulation results. A Effect on βcovA(1) of reference populations differentiation, defined as the difference between the highest and the second highest mean genetic values among the three ancestries, normalized by trait standard deviation in the simulated present-day population (see Supplementary Text for details). B The same as A but plotting on x-axis local ancestry’s mean genetic values instead. C βcovA(1) values as a function of trait optimum in the ancestry with the highest genetic value (p = 1). The x-axis indicates the trait optimum in this ancestry, while other ancestries have an optimum set to 0. Three sub-panels present results of simulations with different fitness function SD (ω) and heritability (h2) values. Each boxplot is based on 50 individual simulations. Scenarios with more than 50 simulation runs were randomly downsampled. The boxes show 25th, 50th and 75th quantiles, while the whiskers show values within 1.5 times the interquartile range (IQR).CC BY · PubMed Central
Fig. 2 Trait-ancestry associations in UKBB and across Biobanks. A CovA effect size (βcovA or ORcovA) estimates together with their 95% confidence interval, for each ancestry and for 53 traits analyzed. For each trait, TAGR-covAs are used in independent models as trait regressors together with several covariates (including two GW-covAs). TAGR-covAs not adding significant information according to double-sided coefficient p-value at 5% FDR are shown in pastel colors. Trait-ancestry associations significant and concordant in the sibling analysis are marked with one asterisk (p < 0.05) or two (FDR < 0.05). All βcovA represented in this figure, including those estimated in the sibling analysis, are reported in Table S6-7. B TAGR-covA test statistics compared between UK Biobank and Estonian Biobank. Z-scores in X axis are extracted from the original paper [33], and computed differently than β/SE. Shaded areas represent linear regression slope confidence intervals for each ancestry independently, the solid gray lines mark nominal significance boundaries for βcovA while the y = x line is represented as dashed. Traits showing an absolute value > 4 in any of the two axes are labeled C Same as B but here covA is computed genome-wide. D Maximal absolute TAGR-covA and GW-covA test statistics. Each dot is a trait.
Fig. 2 Trait-ancestry associations in UKBB and across Biobanks. A CovA effect size (βcovA or ORcovA) estimates together with their 95% confidence interval, for each ancestry and for 53 traits analyzed. For each trait, TAGR-covAs are used in independent models as trait regressors together with several covariates (including two GW-covAs). TAGR-covAs not adding significant information according to double-sided coefficient p-value at 5% FDR are shown in pastel colors. Trait-ancestry associations significant and concordant in the sibling analysis are marked with one asterisk (p < 0.05) or two (FDR < 0.05). All βcovA represented in this figure, including those estimated in the sibling analysis, are reported in Table S6-7. B TAGR-covA test statistics compared between UK Biobank and Estonian Biobank. Z-scores in X axis are extracted from the original paper [33], and computed differently than β/SE. Shaded areas represent linear regression slope confidence intervals for each ancestry independently, the solid gray lines mark nominal significance boundaries for βcovA while the y = x line is represented as dashed. Traits showing an absolute value > 4 in any of the two axes are labeled C Same as B but here covA is computed genome-wide. D Maximal absolute TAGR-covA and GW-covA test statistics. Each dot is a trait.CC BY · PubMed Central

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Metadata

Authors
Pankratov, V., Mezzavilla, M., Aneli, S., Kuznetsov, I. A., Fusco, D., Wilson, J. F., Metspalu, M., Provero, P., Pagani, L., & Marnetto, D.
ORCID
Venue
European Journal of Human Genetics
Publisher
Springer Science and Business Media LLC
Published
2024-08-10
Volume
32
Issue
11
Pages
1492-1499
ISSN
  • 1018-4813
  • 1476-5438
DOI
10.1038/s41431-024-01678-9
PMC
PMC11576899
Cited by
10
References
12
Language
en
Licence
Funders
  • Università degli Studi di Torino (Grant For Internationalization 2022)
  • EC | Horizon 2020 Framework Programme (810645)
  • EC | European Regional Development Fund (MOBEC008)
  • Eesti Teadusagentuur (PRG1899)

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