Abstract
Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3,4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5,6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
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Acknowledgements
This paper is the work of the ROHgen consortium. We thank the participants in all ROHgen studies; cohort-specific acknowledgements are detailed in Supplementary Table 6. This work was funded by a UK Medical Research Council (MRC) PhD studentship to P.K.J.; and J.F.W. and O.P. acknowledge support from the MRC Human Genetics Unit “QTL in Health and Disease” programme. We thank W. G. Hill for discussions and comments on the manuscript and K. Lindsay for administrative assistance.
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C.Hal., P.N., M.Me., H.B., N.J.S., D.C., D.A.M., R.S.C., P.F., G.P., S.F.G., H.H., L.F., R.A.S., A.D.M., C.N.P., G.De., P.D., L.B., U.L., S.I.B., C.M.L., N.J.T., A.Ton., P.B.M., T.I.S., C.N.R., D.K.A., A.J.O., S.L.K., B.B., G.Ga., A.P.M., J.G.E., M.J.W., N.G.M., S.C.H., J.M.S., I.J.D., L.R.G., H.T., N.Pi., J.Ka., N.J.W., L.P., J.G.W., G.Gi., M.J.C., O.R., D.D.B., C.Gi., P.v.d.H., A.A.H., P.Kr., J.S., P.Kn., M.J., P.K.M., A.H., R.Sc., I.B.B., E.Va., D.M.B., D.B., K.L.M., M.B., C.M.v.D., D.K.S., A.Te., E.Z., A.Me., P.G., S.U., C.O., D.T., G.D.S., I.R., D.J.P., M.C., T.D.S., C.Hay., J.D., R.J.L., A.F.W., G.R.C., P.V., A.Sh., P.M.R., J.I.R., N.S., U.G., K.E.N., M.P., B.M.P., D.R.W., M.La., V.G., A.Ta., J.C.C., J.S.K., D.P.S., H.C., J.N.H., M.P., O.P. and J.F.W. designed individual studies. T.N., J.D.F., S.E., V.V., S.Tr., D.I.C., S.S.N., M.Ma., D.R., A.F., L.R.Y., E.H., C.Bo., J.R.P., S.C., U.B., G.M., T.Li., I.D., J.Z., J.P.B., E.S., S.Y., M.A.A., S.J.B., G.R.B., E.P.B., A.Ca., Y. Chan, S.J.C., Y.D.I.C., F.S.C., J.C., A.Co., L.Cu., G.Da., M.D., S.B.E., B.F., M.F.F., I.F., C.S.F., T.M.F., N.Fri., F.Ge., I.Gi., O.G., F.Gr., C.Gu., C.J.H., S.E.H., N.D.H., N.L.H., K.H., L.J.H., G.Ho., P.G.H., E.I., Å.J., P.J., J.J., M.Ka., S.K., S.M.K., N.M.K., H.K.K., M.Ku., J.Ku., J.L., R.A.L., T.Le., D.C.L., L.Li., M.L.L., A.Lo., T.Lu., A.Lu., S.M., K.M., J.B.M., C.Mei., T.M., C.Men., F.D.M., L.M., G.W.M., R.H.M., R.N., M.N., M.S.N., G.T.O., A.O., S.P., W.R.P., J.S.P., I.Pa., K.P., N.Po., S.Ra., P.R., S.S.R., H.R., A.R., L.M.R., R.R., B.Sa., R.M.S., V.S., A.Sa., L.J.S., S.Se., P.S., B.H.S., N.Sor., A.V.St., M.G.S., K.S., N.Ta., K.D.T., B.O.T., A.Tog., M.To., J.T., A.G.U., A.v.H.V., T.V., S.V., E.Vl., E.Vu., M.W., J.B.W., S.W., G.W., C.S.Y., G.Z., X.Z., M.Me., H.B., N.J.S., D.C., D.A.M., R.S.C., G.P., S.F.G., H.H., L.F., R.A.S., G.De., P.D., L.B., U.L., S.I.B., G.D.S., N.J.T., A.Ton., P.B.M., T.I.S., C.N.R., D.K.A., A.J.O., S.L.K., B.B., M.K.K., G.Ga., J.G.E., M.J.W., N.G.M., S.C.H., J.M.S., I.J.D., L.R.G., J.Ka., N.J.W., L.P., J.G.W., G.Gi., M.J.C., O.R., D.D.B., C.Gi., P.v.d.H., A.A.H., P.Kr., J.S., P.Kn., M.J., P.K.M., A.H., R.Sc., I.B.B., E.Va., D.M.B., D.B., K.L.M., M.B., C.M.v.D., D.K.S., E.Z., A.Me., P.G., C.O., D.T., D.J.P., M.C., T.D.S., C.Hay., R.J.L., A.F.W., G.R.C., P.V., A.Sh., P.M.R., J.I.R., N.S., U.G., M.P., B.M.P., D.R.W., M.La., J.C.C., J.S.K., D.P.S., J.N.H., M.P., O.P. and J.F.W. collected the data. S.Tr., D.I.C., M.C.C., C.Bo., U.B., I.D., M.A., F.W.A., S.J.B., D.J.B., E.B., E.P.B., A.Cc., S.J.C., J.C., I.F., T.M.F., C.Gu., C.J.H., T.B.H., N.D.H., M.I., E.I., J.J., P.Ko., M.Ku., L.J.L., R.A.L., L.Li., R.A.M., K.M., J.B.M., G.W.M., R.H.M., P.A.P., K.P., S.S.R., R.R., H.S., P.S., B.H.S., N.Sor., N.Sot., D.Va., J.B.W., C.S.Y., M.Me., N.J.S., D.C., D.A.M., R.S.C., P.F., G.P., S.F.G., H.H., L.F., G.De., P.D., L.B., U.L., S.I.B., C.M.L., A.Ton., P.B.M.,.C.N.R., D.K.A., A.J.O., S.L.K., B.B., G.Ga., A.P.M., M.J.W., N.G.M., S.C.H., J.M.S., I.J.D., L.R.G., J.Ka., N.J.W., L.P., M.J.C., D.D.B., P.v.d.H., P.Kr., M.J., P.K.M., A.H., R.Sc., I.B.B., D.M.B., D.B., K.L.M., M.B., C.M.v.D., D.K.S., E.Z., A.Me., P.G., S.U., C.O., I.R., D.J.P., M.C., T.D.S., C.Hay., A.F.W., G.R.C., P.V., A.Sh., P.M.R., J.I.R., N.S., U.G., K.E.N., B.M.P., D.R.W., M.La., V.G., D.P.S., H.C., O.P. and J.F.W. contributed to funding. P.K.J., T.E., H.Ma., N.E., I.Ga., T.N., A.U.J., C.Sc., A.V.Sm., W.Zhan., Y.O., A.Stc., J.D.F., W. Zhao, T.M.B., M.P.C., N.Fra., S.E., V.V., S.Tr., X.G., D.I.C., J.R.O., T.C., S.S.N., Y. Chen, M.Ma., D.R., M.Ta., A.F., T.Kac., A.Bj., A.v.d.S., Y.W., A.K.G., L.R.Y., L.W., E.H., C.A.R., O.M., M.C.C., C.P., N.V., C.Ba., A.A.A., H.R.W., D.Vu., H.Me., J.R.P., S.S.Mi., M.C.B., S.S.Me., P.A.L., G.M., A.D., L.Y., L.F.B., D.Z., P.J.v.d.M., D.S., R.M., G.He., T.Kar., Z.W., T.Li., I.D., J.Z., W.M., L.La., S.W.v.L., J.P.B., A.R.W., A.Bo., T.S.A., L.M.H., E.S., S.Y., I.M.M., L.Ca., H.G.d.H., M.A., U.A., N.A., F.W.A., S.E.B., S.B., A.Ca., Y. Chan, C.C., G.Da., G.E., B.F., M.F.F., F.Ge., M.G., S.E.H., J.J.H., J.H., J.E.H., P.G.H., A.J., Y.K., S.K., R.A.L., B.L., M.Lo., S.J.Loo., Y.L., P.M., A.Ma., C.Men., F.D.M., E.M., M.E.M., A.Mo., A.O., I.Pa., F.P., I.Pr., L.M.R., B.Sa., R.M.S., R.Sa., H.S., W.R.S., C.Sa., C.Ma., B.Se., S.Sh., S.J.Lon., J.A.S., L.S., R.J.S., M.J.S., S.Ta., B.O.T., A.Tog., M.To., N.Ts., J.v.S., S.V., D.Vo., E.B.W., W.W., J.Y., G.Z., N.J.S., R.A.S., A.D.M., C.N.P., S.I.B., N.J.T., A.P.M., S.C.H., H.T., N.Pi., L.P., P.v.d.H., P.Kr., R.Sc., I.B.B., A.Te., C.O., M.C., J.D., J.I.R., N.S., K.E.N., A.Ta., J.C.C., J.S.K. and D.P.S. analysed the data. P.K.J., T.E., H.Ma., N.E., I.Ga., T.N., A.U.J., C.Sc., A.V.Sm., M.C.B. and D.P.S. performed beta-testing of scripts. P.K.J. and T.E. performed the meta-analysis. P.K.J., T.E., O.P. and J.F.W. wrote the manuscript. All authors approved the final manuscript.
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G.P. is a co-founder of CAVADIS B.V. S.W.v.L. is a former employee of CAVADIS B.V. B.M.P. serves on the Data and Safety Monitoring Board of a clinical trial funded by the LifeVest manufacturer (Zoll Lifecor) and on the Yale Open Data Access Project funded by Johnson & Johnson. N.Po. has received financial support and consultancy fees from several pharmaceutical companies that manufacture either blood-pressure-lowering or lipid-lowering agents or both. P.S. has received research awards from Pfizer. No other authors declared a conflict of interest.
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Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan.
Extended data figures and tables
Extended Data Figure 1 Forest plot for cognitive ability (g).
Individual sub-cohort estimates of effect size and the 95% confidence interval are plotted. Sub-cohorts are ordered from top to bottom according to their weight in the meta-analysis, so larger or more homozygous cohorts appear towards the top. The scale of is in intra-sex standard deviations. The meta-analytical estimate is displayed at the bottom. Sub-cohort names follow the conventions detailed in Supplementary Table 6 and the Supplementary Table 11 legend. Sample sizes, effect sizes and P values for association are given in Table 1. This trait was rank-transformed.
Extended Data Figure 2 Forest plot for educational attainment.
Individual sub-cohort estimates of effect size and the 95% confidence interval are plotted. Sub-cohorts are ordered from top to bottom according to their weight in the meta-analysis, so larger or more homozygous cohorts appear towards the top. The scale of is in intra-sex standard deviations. The meta-analytical estimate is displayed at the bottom. Sub-cohort names follow the conventions detailed in Supplementary Table 6 and the Supplementary Table 11 legend. Sample sizes, effect sizes and P values for association are given in Table 1.
Extended Data Figure 3 Forest plot for height.
Individual sub-cohort estimates of effect size and the 95% confidence interval are plotted. Sub-cohorts are ordered from top to bottom according to their weight in the meta-analysis, so larger or more homozygous cohorts appear towards the top. The scale of is in intra-sex standard deviations. The meta-analytical estimate is displayed at the bottom. Sub-cohort names follow the conventions detailed in Supplementary Table 6 and the Supplementary Table 11 legend. Sample sizes, effect sizes and P values for association are given in Table 1.
Extended Data Figure 4 Forest plot for forced expiratory lung volume in one second.
Individual sub-cohort estimates of effect size and the 95% confidence interval are plotted. Sub-cohorts are ordered from top to bottom according to their weight in the meta-analysis, so larger or more homozygous cohorts appear towards the top. The scale of is in intra-sex standard deviations. The meta-analytical estimate is displayed at the bottom. Sub-cohort names follow the conventions detailed in Supplementary Table 6 and the Supplementary Table 11 legend. Sample sizes, effect sizes and P values for association are given in Table 1. This trait was rank-transformed.
Extended Data Figure 5 Signals of directional dominance are robust to stratification by geography or demographic history or inclusion of educational attainment as covariate.
a, Cohorts are divided by continental biogeographic ancestry (African (15 sub-cohorts), East Asian (5), South and Central Asian (SC Asian; 10), Hispanic (3)), with Europeans being divided into Finns (13), other European isolates (self-declared, 23), and (non-isolated) Europeans (90). Meta-analysis was carried out for all subsets with 2,000 or more samples available. Sample numbers are as follows: cognitive g, Eur isolate, 6,638; European, 44,153; educational attainment, African 4,811; Eur isolate, 8,032; European, 55,549; Finland 9,068; height, African, 21,500; E Asian, 30,011; Eur isolate, 23,116; European, 228,813, Finland, 30,427, Hispanic, 5,469, SC Asian, 13,523; FEV1, African, 6,604, Eur isolate, 4,837, European, 49,223, Finland, 2,340. is consistent across geography and in both isolates and more cosmopolitan populations. b, Cohorts were divided into high and low ROH strata of equal power and meta-analysis repeated – the effects are consistent across strata for all four traits. The mean SROH for the high and low strata, respectively, are 13.4 and 4.3 Mb for cognitive g; 28.1 and 5.1 Mb for educational attainment; 31.9 and 10.8 Mb for height; and 41.4 and 4.5 Mb for FEV1. c, To assess the potential for socio-economic confounding, where available, educational attainment was included in the regression model (edu) and compared to a model without educational attainment (none) in the same subset of cohorts. The signals reduce slightly when the education covariate is included; the analysis is not possible for educational attainment as a trait. For cognitive g, numbers of subjects are 36,847 and 36,023; for height 131,614 and 120,945; and for FEV1, 15,717 and 15,425, for edu and none, respectively. The numbers differ because of missing individual educational data within cohorts. Plus signs indicate that the phenotype was rank-transformed. Trait units are intra-sex standard deviations and the genomic measure is unpruned SROH. Subset estimates of effect size for FROH and the 95% confidence are plotted.
Extended Data Figure 6 Signals of directional dominance are robust to model choice.
Meta-analytical estimates of effect size and standard errors are plotted for various models. Fixed, no mixed modelling was used; gr res, GRAMMAR+ residuals were fitted; hglm, full hierarchical generalized linear mixed model was used. Plus signs indicate that the phenotype was rank-transformed. 15,355 subjects were used for cognitive g, 36,060 for educational attainment, 89,112 for height and 15,262 for FEV1.
Extended Data Figure 7 Correlation in SROH for different genotyping arrays using HapMap populations.
a–c, x and y axes show SROH from 0–30 Mb. ill370, Illumina CNV370; aff6, Affymetrix6; illomni, Illumina OmniExpress. The graphs are shown for the specific PLINK call parameters used. d, Sample numbers per continent are presented in a bar chart. AFR, African; AMR, mixed American; ASN, East Asian; EUR, European; SAN, South Asian. Only samples with SROH below 30 Mb are plotted, to be conservative to the effect of outliers, which have very strongly correlated estimates of SROH (r = 0.96–0.97 for comparisons including such very homozygous individuals). In these plots, the correlation between SROH called by the two arrays, r = 0.93–0.94.
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Joshi, P., Esko, T., Mattsson, H. et al. Directional dominance on stature and cognition in diverse human populations. Nature 523, 459–462 (2015). https://doi.org/10.1038/nature14618
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DOI: https://doi.org/10.1038/nature14618
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