Genetic footprints of assortative mating in the Japanese population

Abstract

Assortative mating (AM) is a pattern characterized by phenotypic similarities between mating partners. Detecting the evidence of AM has been challenging due to the lack of large-scale datasets that include phenotypic data on both partners, especially in populations of non-European ancestries. Gametic phase disequilibrium between trait-associated alleles is a signature of parental AM on a polygenic trait, which can be detected even without partner data. Here, using polygenic scores for 81 traits in the Japanese population using BioBank Japan Project genome-wide association studies data (n = 172,270), we found evidence of AM on the liability to type 2 diabetes and coronary artery disease, as well as on dietary habits. In cross-population comparison using United Kingdom Biobank data (n = 337,139) we found shared but heterogeneous impacts of AM between populations.

Fig. 1. An overview of the study design.

We randomly divided the BBJ mainland samples into ten subsets to apply the LOGO method. We conducted GWAS using training samples and withholding the target subset using GCTA-fastGWA. We derived PGS for even-/odd-numbered chromosomes (PGS_odd/PGS_even) in the target subset using the PRS-CS method and estimated GPD for even-/odd-numbered chromosomes (θ_{even_to_odd} and θ_{odd_to_even}). We then meta-analysed the GPD estimates across the ten subsets. For the six independent Japanese or EAS cohorts, we derived PGS_odd/PGS_even based on fastGWA results from the whole mainland sample in BBJ. Finally, we performed a meta-analysis of the GPD estimates across all EAS datasets (n = 172,270). We adopted the same LOGO method to estimate GPD in the UKB data (n = 337,139).

Fig. 2. Estimates of GPD for 81 complex traits in the Japanese population.

For 81 human complex traits, we quantified GPD as the correlation between trait-specific PGSs for odd-/even-numbered chromosomes. We selected the meta-analysed GPD estimate (θ) with the larger variance between θ_{even_to_odd} and θ_{odd_to_even} in all Japanese or EAS cohorts (n = 172,270). P values were determined by two-sided Wald test. We set a study-wide significance threshold at P < 6.2 × 10⁻⁴ (=0.05/81) by applying Bonferroni’s correction for multiple comparison. Statistically significant traits are marked with an asterisk and in bold. Detailed results are presented in Supplementary Table 6. The bar plots represent the point estimates, and error bars represent the s.e. Freq., frequency.

Fig. 3. Correlations between GPD estimates from even to odd chromosomes and GPD estimates from odd to even chromosomes for 81 traits in BBJ.

a, The correlation plot of 81 traits between θ_{even_to_odd} and θ_{odd_to_even} in the Japanese population. b, The enlarged plot of a around the trait of ever versus never drinking. The x axis indicates the meta-analysed GPD estimated from even to odd chromosomes (θ_{even_to_odd}), and the y axis indicates that from odd to even chromosomes (θ_{odd_to_even}). The error bars represent s.e. The dashed line represents θ_{odd_to_even} = θ_{even_to_odd}.

Fig. 4. GPD estimates for six complex traits in the UKB.

For six complex traits, we quantified GPD as the correlation between trait-specific PGSs for odd-/even-numbered chromosomes. GPD estimate (θ) with the larger variance between θ_{even_to_odd} and θ_{odd_to_even} was selected in white British individuals from UKB data (n = 337,139). The bar plots represent the point estimates, and error bars represent the s.e.

Fig. 5. Forest plots of GPD estimates of five traits related to AM.

Forest plots of five significant traits, T2D, CAD, light-PA, natto consumption and yoghurt consumption. For all plots, a given label and number along vertical axes represent the name and the sample size of the cohort, respectively. The points indicate the point estimates, and error bars indicate 95% confidence intervals. Osaka Univ., Osaka University healthy cohort; Meta, meta-analysis.