Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases

被引:0
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作者
Masahiro Kanai
Masato Akiyama
Atsushi Takahashi
Nana Matoba
Yukihide Momozawa
Masashi Ikeda
Nakao Iwata
Shiro Ikegawa
Makoto Hirata
Koichi Matsuda
Michiaki Kubo
Yukinori Okada
Yoichiro Kamatani
机构
[1] Osaka University Graduate School of Medicine,Department of Statistical Genetics
[2] RIKEN Center for Integrative Medical Sciences,Laboratory for Statistical Analysis
[3] Harvard Medical School,Department of Biomedical Informatics
[4] National Cerebral and Cardiovascular Center,Department of Genomic Medicine, Research Institute
[5] RIKEN Center for Integrative Medical Sciences,Laboratory for Genotyping Development
[6] Fujita Health University School of Medicine,Department of Psychiatry
[7] RIKEN Center for Integrative Medical Sciences,Laboratory for Bone and Joint Diseases
[8] The University of Tokyo,Institute of Medical Science
[9] The University of Tokyo,Graduate School of Frontier Sciences
[10] RIKEN Center for Integrative Medical Sciences,Laboratory of Statistical Immunology
[11] Immunology Frontier Research Center (WPI-IFReC),Center for Genomic Medicine
[12] Osaka University,undefined
[13] Kyoto University Graduate School of Medicine,undefined
来源
Nature Genetics | 2018年 / 50卷
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摘要
Clinical measurements can be viewed as useful intermediate phenotypes to promote understanding of complex human diseases. To acquire comprehensive insights into the underlying genetics, here we conducted a genome-wide association study (GWAS) of 58 quantitative traits in 162,255 Japanese individuals. Overall, we identified 1,407 trait-associated loci (P < 5.0 × 10−8), 679 of which were novel. By incorporating 32 additional GWAS results for complex diseases and traits in Japanese individuals, we further highlighted pleiotropy, genetic correlations, and cell-type specificity across quantitative traits and diseases, which substantially expands the current understanding of the associated genetics and biology. This study identified both shared polygenic effects and cell-type specificity, represented by the genetic links among clinical measurements, complex diseases, and relevant cell types. Our findings demonstrate that even without prior biological knowledge of cross-phenotype relationships, genetics corresponding to clinical measurements successfully recapture those measurements’ relevance to diseases, and thus can contribute to the elucidation of unknown etiology and pathogenesis.
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页码:390 / 400
页数:10
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