Characterizing rare and low-frequency height-associated variants in the Japanese population

Abstract

Human height is a representative phenotype to elucidate genetic architecture. However, the majority of large studies have been performed in European population. To investigate the rare and low-frequency variants associated with height, we construct a reference panel (N = 3,541) for genotype imputation by integrating the whole-genome sequence data from 1,037 Japanese with that of the 1000 Genomes Project, and perform a genome-wide association study in 191,787 Japanese. We report 573 height-associated variants, including 22 rare and 42 low-frequency variants. These 64 variants explain 1.7% of the phenotypic variance. Furthermore, a gene-based analysis identifies two genes with multiple height-increasing rare and low-frequency nonsynonymous variants (SLC27A3 and CYP26B1; P_SKAT-O < 2.5 × 10^-6). Our analysis shows a general tendency of the effect sizes of rare variants towards increasing height, which is contrary to findings among Europeans, suggesting that height-associated rare variants are under different selection pressure in Japanese and European populations.

Fig. 1

Plot of imputation qualities by different reference panels. The accuracy of imputation was evaluated for four different reference panels at “masked” HumanExome SNPs. BBJ1K + 1KGp3v5 panel (red) showed the best performance at every allele frequency bins. Even the BBJ1K panel showed much better accuracy than the 1KGp3v5 ALL panel regardless of the difference in sample size, indicating the contribution of deep haplotype information of the specific population to imputation accuracy. Median r² values are shown on the y-axis

Fig. 2

Scatter plot of MAF and effect size. We plotted the allele frequency (x-axis) and effect size (y-axis) of the minor alleles of the 609 variants that reached genome-wide significance in the discovery GWAS. Variants that remained genome-wide significant after the meta-analysis are indicated in blue. The orange line denotes 80% power to achieve genome-wide significance. To convert the standardized effect size to a centimeter scale, we regarded 1 standard error as 5.63 cm, which was calculated in the population-based cohorts (replication set)

Fig. 3

Summary of gene-based analysis. a Manhattan plot of the gene-based test. The yellow line represents significance threshold (P < 2.5 × 10⁻⁶). b Comparison of single-variant test P values and those of the gene-based test. Two genes (SLC27A3 and CYP26B1) showed much stronger associations in the gene-based test. c, d Positions and associations of nonsynonymous variants in SLC27A3 and CYP26B1. The colors of the plots denote the impact of the variants. The symbols (circle, diamond, and square) indicate the function of variants. The coding regions are colored according to their structural domains based on Pfam

Fig. 4

Relationship between the minor allele effect for height and MAF in the GWAS. A scatter plot of the mean minor allele effect according to each MAF bin (N = 100) is shown. The mean effects of the minor alleles were clearly greater in rarer variants