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), 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, r = 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.

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The Great East Japan Earthquake (GEJE) and resulting tsunami of March 11, 2011 gave rise to devastating damage on the Pacific coast of the Tohoku region. The Tohoku Medical Megabank Project (TMM), which is being conducted by Tohoku University Tohoku Medical Megabank Organization (ToMMo) and Iwate Medical University Iwate Tohoku Medical Megabank Organization (IMM), has been launched to realize creative reconstruction and to solve medical problems in the aftermath of this disaster. We started two prospective cohort studies in Miyagi and Iwate Prefectures: a population-based adult cohort study, the TMM Community-Based Cohort Study (TMM CommCohort Study), which will recruit 80 000 participants, and a birth and three-generation cohort study, the TMM Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study), which will recruit 70 000 participants, including fetuses and their parents, siblings, grandparents, and extended family members. The TMM CommCohort Study will recruit participants from 2013 to 2016 and follow them for at least 5 years. The TMM BirThree Cohort Study will recruit participants from 2013 to 2017 and follow them for at least 4 years. For children, the ToMMo Child Health Study, which adopted a cross-sectional design, was also started in November 2012 in Miyagi Prefecture. An integrated biobank will be constructed based on the two prospective cohort studies, and ToMMo and IMM will investigate the chronic medical impacts of the GEJE. The integrated biobank of TMM consists of health and clinical information, biospecimens, and genome and omics data. The biobank aims to establish a firm basis for personalized healthcare and medicine, mainly for diseases aggravated by the GEJE in the two prefectures. Biospecimens and related information in the biobank will be distributed to the research community. TMM itself will also undertake genomic and omics research. The aims of the genomic studies are: 1) to construct an integrated biobank; 2) to return genomic research results to the participants of the cohort studies, which will lead to the implementation of personalized healthcare and medicine in the affected areas in the near future; and 3) to contribute the development of personalized healthcare and medicine worldwide. Through the activities of TMM, we will clarify how to approach prolonged healthcare problems in areas damaged by large-scale disasters and how useful genomic information is for disease prevention.

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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 < 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.

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Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.