Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry^1,2. 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.

BackgroundWe established a community-based cohort study to assess the long-term impact of the Great East Japan Earthquake on disaster victims and gene-environmental interactions on the incidence of major diseases such as cancer and cardiovascular diseases.MethodsWe asked participants to join our cohort in the health check-up settings and assessment center based settings. Inclusion criteria was aged 20 years or over and living in Miyagi or Iwate Prefecture. We obtained information on lifestyle, effect of disaster, blood, and urine information (Type 1 survey), and some detailed measurements (Type 2 survey), for example, carotid echography, calcaneal ultrasound bone mineral density, and so on. All participants agreed to measure genome information and to distribute their information widely.ResultsAs a result, 87,865 gave their informed consent to join our study. Participation rate at health check-up site was about 70%. The participants with Type 1 survey were more likely to have psychological distress than those of Type 2 survey, and women were more likely to have psychological distress than men. Additionally, coastal residents were more likely to have higher degrees of psychological distress than inland residents regardless of sex.ConclusionThis cohort comprised large sample size and it contains information on disaster, genome information, and metabolome information. This cohort also had several detailed measurements. Using this cohort enabled us to clarify the long-term effect of disaster and also to establish personalized prevention based on genome, metabolome, and other omics information.

Background: Lifestyle and life-environment factors have undergone drastic changes in Japan over the last few decades. Further, many molecular epidemiologic studies have reported that genetic, epigenetic and other biomarker information may be useful in predicting individual disease risk.Methods: Japan Public Health Center-based Prospective Study for the Next Generation (JPHC-NEXT) was launched in 2011 to identify risk factors for lifestyle-related disease, elucidate factors which extend healthy life expectancy, and contribute toward personalized healthcare based on our more than 20 years’ experience with the JPHC Study. Between 2011 and 2016, a baseline survey was conducted at 16 municipalities in 7 prefectures across the country. A self-administered questionnaire was distributed to all registered residents aged 40-74 which mainly asked about lifestyle factors, such as socio-demographic situation, personal medical history, smoking, alcohol and dietary habits. We obtained informed consent from each participant to participate in this long follow-up study of at least 20 years, including consent to the potential use of their residence registry, medical records, medical fee receipts, care insurance etc., and to the provision of biospecimens (blood and urine), including genomic analysis.Results and Conclusion: As of December 31, 2016, we have established a population-based cohort of 115,385 persons (Response rate 44.1%), among whom 55,278 (47.9% of participants) have provided blood and urine samples. The participation rate was slightly higher among females and in the older age group. In conclusion, we have established a large-scale population-based cohort for next-generation epidemiological study in Japan.

An East Asian–specific variant on aldehyde dehydrogenase 2 ( ALDH2 rs671, G>A) is the major genetic determinant of alcohol consumption. We performed an rs671 genotype-stratified genome-wide association study meta-analysis of alcohol consumption in 175,672 Japanese individuals to explore gene-gene interactions with rs671 behind drinking behavior. The analysis identified three genome-wide significant loci ( GCKR , KLB , and ADH1B ) in wild-type homozygotes and six ( GCKR , ADH1B , ALDH1B1 , ALDH1A1 , ALDH2 , and GOT2 ) in heterozygotes, with five showing genome-wide significant interaction with rs671. Genetic correlation analyses revealed ancestry-specific genetic architecture in heterozygotes. Of the discovered loci, four ( GCKR , ADH1B , ALDH1A1 , and ALDH2 ) were suggested to interact with rs671 in the risk of esophageal cancer, a representative alcohol-related disease. Our results identify the genotype-specific genetic architecture of alcohol consumption and reveal its potential impact on alcohol-related disease risk.