Dataset Information

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; PSKAT-O?

SUBMITTER: Akiyama M

PROVIDER: S-EPMC6764965 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Akiyama Masato M Ishigaki Kazuyoshi K Sakaue Saori S Momozawa Yukihide Y Horikoshi Momoko M Hirata Makoto M Matsuda Koichi K Ikegawa Shiro S Takahashi Atsushi A Kanai Masahiro M Suzuki Sadao S Matsui Daisuke D Naito Mariko M Yamaji Taiki T Iwasaki Motoki M Sawada Norie N Tanno Kozo K Sasaki Makoto M Hozawa Atsushi A Minegishi Naoko N Wakai Kenji K Tsugane Shoichiro S Shimizu Atsushi A Yamamoto Masayuki M Okada Yukinori Y Murakami Yoshinori Y Kubo Michiaki M Kamatani Yoichiro Y

Nature communications 20190927 1

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-associ ...[more]

PMID: 31562340

Similar Datasets

Project description:Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P < 5.0 × 10 - 7). One of the most significant signals (Pall histologies = 1.01 × 10 - 13;Pserous = 3.54 × 10 - 14) occurred at 3q25.31 for rs62273959, a missense variant mapping to the LEKR1 gene that is in LD (r2 = 0.90) with a previously identified 'best hit' (rs7651446) mapping to an intron of TIPARP. Suggestive associations (5.0 × 10 - 5 > P≥5.0 ×10 - 7) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (PAML = 3.23 × 10 - 5; PSKAT-o = 9.23 × 10 - 4) and KRT13 (PAML = 1.67 × 10 - 4; PSKAT-o = 1.07 × 10 - 5), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets