To this end, GWASs have been conducted to investigate various quantitative traits, including anthropometric 1, 2, 3, metabolic 4, 5, kidney-related 6, 7, hematological 8, 9, and blood pressure traits 10, 11, 12. Elucidation of the underlying genetics, as well as inference of genetic relationships to diseases and implicated cell types, can provide clues about disease biology. 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.Ĭlinical laboratory measurements (e.g., blood test results) are powerful intermediate phenotypes that can be used to diagnose and monitor human diseases. 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. 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. Overall, we identified 1,407 trait-associated loci ( P < 5.0 × 10 −8), 679 of which were novel. 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. Clinical measurements can be viewed as useful intermediate phenotypes to promote understanding of complex human diseases.
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