Explore the vast range of titles available.

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. A genome-wide association study (GWAS) of 58 traits using data from the Biobank Japan Project identifies 1,407 loci, 679 of which are novel. Comparison with disease GWASs and analysis of genetic correlations and cell-type enrichment show that these clinical measurements are relevant to human disease.

Clinical use of gene panel testing for hematopoietic neoplasms in areas, such as diagnosis, prognosis prediction, and exploration of treatment options, has increased in recent years. The keys to interpreting gene variants detected in gene panel testing are to distinguish between germline and somatic variants and accurately determine whether the detected variants are pathogenic. If a variant is suspected to be a pathogenic germline variant, it is essential to confirm its consistency with the disease phenotype and gather a thorough family history. Donor eligibility must also be considered, especially if the patient’s variant is also detected in the expected donor for hematopoietic stem cell transplantation. However, determining the pathogenicity of gene variants is often complicated, given the current limited availability of databases covering germline variants of hematopoietic neoplasms. This means that hematologists will frequently need to interpret gene variants themselves. Here, we outline how to assess the pathogenicity of germline variants according to criteria from the American College of Medical Genetics and Genomics/Association for Molecular Pathology standards and guidelines for the interpretation of variants using DDX41 , a gene recently shown to be closely associated with myeloid neoplasms with a germline predisposition, as an example.

The diversity in our genome is crucial to understanding the demographic history of worldwide populations. However, we have yet to know whether subtle genetic differences within a population can be disentangled, or whether they have an impact on complex traits. Here we apply dimensionality reduction methods (PCA, t -SNE, PCA- t -SNE, UMAP, and PCA-UMAP) to biobank-derived genomic data of a Japanese population ( n  = 169,719). Dimensionality reduction reveals fine-scale population structure, conspicuously differentiating adjacent insular subpopulations. We further enluciate the demographic landscape of these Japanese subpopulations using population genetics analyses. Finally, we perform phenome-wide polygenic risk score (PRS) analyses on 67 complex traits. Differences in PRS between the deconvoluted subpopulations are not always concordant with those in the observed phenotypes, suggesting that the PRS differences might reflect biases from the uncorrected structure, in a trait-dependent manner. This study suggests that such an uncorrected structure can be a potential pitfall in the clinical application of PRS. Population structure, even subtle differences within seemingly homogenous populations, can have an impact on the accuracy of polygenic prediction. Here, Sakaue et al. use dimensionality reduction methods to reveal fine-scale structure in the Biobank Japan cohort and explore the performance of polygenic risk scores.

Infection with Helicobacter pylori is known to confer a risk of gastric cancer. In this study, persons who carried certain genetic variants and were infected with H. pylori had an excess risk of gastric cancer.

Previous clinical trials indicate that 10%–25% of patients received genomically matched therapy after comprehensive genomic profiling (CGP) tests. However, the clinical utility of CGP tests has not been assessed in clinical practice. We assessed the clinical utility of CGP tests for advanced or metastatic solid tumor and determined the proportion of patients receiving genomically matched therapy among those with common and non‐common cancers. From August 2019 to July 2020, a total of 418 patients had undergone CGP tests, and the results were discussed through the molecular tumor board at our site. The median age of patients was 57 (range: 3–86) years. Colorectal cancer was the most common, with 47 (11%) patients. Actionable genomic alterations (median 3, range: 1–17) were identified in 368 (88.0%) of 418 patients. Druggable genomic alterations were determined in 196 (46.9%) of 418 patients through the molecular tumor board. Genomically matched therapy was administered as the subsequent line of therapy in 51 (12.2%) patients, which is comparable to the proportion we previously reported in a clinical trial (13.4%) (p = 0.6919). The proportion of patients receiving genomically matched therapy was significantly higher among those with common cancers (16.2%) than non‐common cancers (9.4%) (p = 0.0365). Genomically matched therapy after the CGP tests was administered to 12.2% of patients, which is similar to the proportion reported in the previous clinical trials. The clinical utility of CGP tests in patients with common cancers greatly exceeded that in patients with non‐common cancers. Genomically matched therapy after comprehensive genomic profiling (CGP) tests was administered to 12.2% of patients in clinical practice. We demonstrated the clinical utility of CGP tests in clinical practice, particularly among those with common cancers who received genomically matched therapy more frequently than those with non‐common cancers.

To understand the genetics of type 2 diabetes in people of Japanese ancestry, we conducted A meta-analysis of four genome-wide association studies (GWAS; 36,614 cases and 155,150 controls of Japanese ancestry). We identified 88 type 2 diabetes–associated loci ( P  < 5.0 × 10 −8 ) with 115 independent signals ( P  < 5.0 × 10 −6 ), of which 28 loci with 30 signals were novel. Twenty-eight missense variants were in linkage disequilibrium ( r 2  > 0.6) with the lead variants. Among the 28 missense variants, three previously unreported variants had distinct minor allele frequency (MAF) spectra between people of Japanese and European ancestry (MAF JPN  > 0.05 versus MAF EUR  < 0.01), including missense variants in genes related to pancreatic acinar cells ( GP2 ) and insulin secretion ( GLP1R ). Transethnic comparisons of the molecular pathways identified from the GWAS results highlight both ethnically shared and heterogeneous effects of a series of pathways on type 2 diabetes (for example, monogenic diabetes and beta cells). Genome-wide association analyses identify 28 new susceptibility loci for type 2 diabetes in the Japanese population. Transethnic comparisons highlight the key role of beta cell dysfunction in type 2 diabetes across different ancestry groups.

Yoichiro Kamatani and colleagues perform a genome-wide association study (GWAS) for body mass index using data from 173,430 Japanese individuals. They find 85 significant loci, 51 of which are novel, and use trans-ancestral meta-analysis of GWAS from European samples to identify 61 additional new loci. Obesity is a risk factor for a wide variety of health problems. In a genome-wide association study (GWAS) of body mass index (BMI) in Japanese people ( n = 173,430), we found 85 loci significantly associated with obesity ( P < 5.0 × 10 −8 ), of which 51 were previously unknown. We conducted trans-ancestral meta-analyses by integrating these results with the results from a GWAS of Europeans and identified 61 additional new loci. In total, this study identifies 112 novel loci, doubling the number of previously known BMI-associated loci. By annotating associated variants with cell-type-specific regulatory marks, we found enrichment of variants in CD19 + cells. We also found significant genetic correlations between BMI and lymphocyte count ( P = 6.46 × 10 −5 , r g = 0.18) and between BMI and multiple complex diseases. These findings provide genetic evidence that lymphocytes are relevant to body weight regulation and offer insights into the pathogenesis of obesity.

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. Thousands of genetic loci are known to associate with human height, but these are mainly based on studies in European ancestry populations. Here, Akiyama et al. construct a genotype reference panel for the Japanese population followed by GWAS and report 573 height associated variants in 191,787 Japanese.

While polygenic risk scores (PRSs) are poised to be translated into clinical practice through prediction of inborn health risks 1 , a strategy to utilize genetics to prioritize modifiable risk factors driving heath outcome is warranted 2 . To this end, we investigated the association of the genetic susceptibility to complex traits with human lifespan in collaboration with three worldwide biobanks ( n total  = 675,898; BioBank Japan ( n  = 179,066), UK Biobank ( n  = 361,194) and FinnGen ( n  = 135,638)). In contrast to observational studies, in which discerning the cause-and-effect can be difficult, PRSs could help to identify the driver biomarkers affecting human lifespan. A high systolic blood pressure PRS was trans-ethnically associated with a shorter lifespan (hazard ratio = 1.03[1.02–1.04], P meta  = 3.9 × 10 −13 ) and parental lifespan (hazard ratio = 1.06[1.06–1.07], P  = 2.0 × 10 −86 ). The obesity PRS showed distinct effects on lifespan in Japanese and European individuals ( P heterogeneity  = 9.5 × 10 −8 for BMI). The causal effect of blood pressure and obesity on lifespan was further supported by Mendelian randomization studies. Beyond genotype–phenotype associations, our trans-biobank study offers a new value of PRSs in prioritization of risk factors that could be potential targets of medical treatment to improve population health. Cross-biobank analysis reveals that polygenic risk scores (PRS) for hypertension and obesity are associated with shorter lifespan, serving as a proof-of-principle that PRS could pinpoint causal risk factors that affect long-term health outcomes.

To perform detailed fine-mapping of the major-histocompatibility-complex region, we conducted next-generation sequencing (NGS)-based typing of the 33 human leukocyte antigen (HLA) genes in 1,120 individuals of Japanese ancestry, providing a high-resolution allele catalog and linkage-disequilibrium structure of both classical and nonclassical HLA genes. Together with population-specific deep-whole-genome-sequencing data ( n  = 1,276), we conducted NGS-based HLA, single-nucleotide-variant and indel imputation of large-scale genome-wide-association-study data from 166,190 Japanese individuals. A phenome-wide association study assessing 106 clinical phenotypes identified abundant, significant genotype–phenotype associations across 52 phenotypes. Fine-mapping highlighted multiple association patterns conferring independent risks from classical HLA genes. Region-wide heritability estimates and genetic-correlation network analysis elucidated the polygenic architecture shared across the phenotypes. Sequencing of the MHC region in the Japanese population provides insight into population-specific allelic and structural variability. These data enable discovery and fine-mapping of genotype–phenotype associations across 52 phenotypes.