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Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

Primary open-angle glaucoma (POAG), is a heritable common cause of blindness world-wide. To identify risk loci, we conduct a large multi-ethnic meta-analysis of genome-wide association studies on a total of 34,179 cases and 349,321 controls, identifying 44 previously unreported risk loci and confirming 83 loci that were previously known. The majority of loci have broadly consistent effects across European, Asian and African ancestries. Cross-ancestry data improve fine-mapping of causal variants for several loci. Integration of multiple lines of genetic evidence support the functional relevance of the identified POAG risk loci and highlight potential contributions of several genes to POAG pathogenesis, including SVEP1, RERE, VCAM1, ZNF638, CLIC5, SLC2A12, YAP1, MXRA5, and SMAD6. Several drug compounds targeting POAG risk genes may be potential glaucoma therapeutic candidates.

Genome-wide association studies (GWASs) have identified loci for erythrocyte traits in primarily European ancestry populations. We conducted GWAS meta-analyses of six erythrocyte traits in 71,638 individuals from European, East Asian, and African ancestries using a Bayesian approach to account for heterogeneity in allelic effects and variation in the structure of linkage disequilibrium between ethnicities. We identified seven loci for erythrocyte traits including a locus (RBPMS/GTF2E2) associated with mean corpuscular hemoglobin and mean corpuscular volume. Statistical fine-mapping at this locus pointed to RBPMS at this locus and excluded nearby GTF2E2. Using zebrafish morpholino to evaluate loss of function, we observed a strong in vivo erythropoietic effect for RBPMS but not for GTF2E2, supporting the statistical fine-mapping at this locus and demonstrating that RBPMS is a regulator of erythropoiesis. Our findings show the utility of trans-ethnic GWASs for discovery and characterization of genetic loci influencing hematologic traits.

We analyzed genome-wide association studies (GWASs), including data from 71,638 individuals from four ancestries, for estimated glomerular filtration rate (eGFR), a measure of kidney function used to define chronic kidney disease (CKD). We identified 20 loci attaining genome-wide-significant evidence of association (p < 5 × 10(-8)) with kidney function and highlighted that allelic effects on eGFR at lead SNPs are homogeneous across ancestries. We leveraged differences in the pattern of linkage disequilibrium between diverse populations to fine-map the 20 loci through construction of "credible sets" of variants driving eGFR association signals. Credible variants at the 20 eGFR loci were enriched for DNase I hypersensitivity sites (DHSs) in human kidney cells. DHS credible variants were expression quantitative trait loci for NFATC1 and RGS14 (at the SLC34A1 locus) in multiple tissues. Loss-of-function mutations in ancestral orthologs of both genes in Drosophila melanogaster were associated with altered sensitivity to salt stress. Renal mRNA expression of Nfatc1 and Rgs14 in a salt-sensitive mouse model was also reduced after exposure to a high-salt diet or induced CKD. Our study (1) demonstrates the utility of trans-ethnic fine mapping through integration of GWASs involving diverse populations with genomic annotation from relevant tissues to define molecular mechanisms by which association signals exert their effect and (2) suggests that salt sensitivity might be an important marker for biological processes that affect kidney function and CKD in humans.

Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.

Laboratory red blood cell (RBC) measurements are clinically important, heritable and differ among ethnic groups. To identify genetic variants that contribute to RBC phenotypes in African Americans (AAs), we conducted a genome-wide association study in up to ~16 500 AAs. The alpha-globin locus on chromosome 16pter [lead SNP rs13335629 in ITFG3 gene; P < 1E-13 for hemoglobin (Hgb), RBC count, mean corpuscular volume (MCV), MCH and MCHC] and the G6PD locus on Xq28 [lead SNP rs1050828; P < 1E - 13 for Hgb, hematocrit (Hct), MCV, RBC count and red cell distribution width (RDW)] were each associated with multiple RBC traits. At the alpha-globin region, both the common African 3.7 kb deletion and common single nucleotide polymorphisms (SNPs) appear to contribute independently to RBC phenotypes among AAs. In the 2p21 region, we identified a novel variant of PRKCE distinctly associated with Hct in AAs. In a genome-wide admixture mapping scan, local European ancestry at the 6p22 region containing HFE and LRRC16A was associated with higher Hgb. LRRC16A has been previously associated with the platelet count and mean platelet volume in AAs, but not with Hgb. Finally, we extended to AAs the findings of association of erythrocyte traits with several loci previously reported in Europeans and/or Asians, including CD164 and HBS1L-MYB. In summary, this large-scale genome-wide analysis in AAs has extended the importance of several RBC-associated genetic loci to AAs and identified allelic heterogeneity and pleiotropy at several previously known genetic loci associated with blood cell traits in AAs.

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.

Background: We established a patient-oriented biobank, BioBank Japan, with information on approximately 200,000 patients, suffering from any of 47 common diseases. This follow-up survey focused on 32 diseases, potentially associated with poor vital prognosis, and collected patient survival information, including cause of death. We performed a survival analysis for all subjects to get an overview of BioBank Japan follow-up data. Methods: A total of 141,612 participants were included. The survival data were last updated in 2014. Kaplan–Meier survival analysis was performed after categorizing subjects according to sex, age group, and disease status. Relative survival rates were estimated using a survival-rate table of the Japanese general population. Results: Of 141,612 subjects (56.48% male) with 1,087,434 person-years and a 97.0% follow-up rate, 35,482 patients died during follow-up. Mean age at enrollment was 64.24 years for male subjects and 63.98 years for female subjects. The 5-year and 10-year relative survival rates for all subjects were 0.944 and 0.911, respectively, with a median follow-up duration of 8.40 years. Patients with pancreatic cancer had the least favorable prognosis (10-year relative survival: 0.184) and patients with dyslipidemia had the most favorable prognosis (1.013). The most common cause of death was malignant neoplasms. A number of subjects died from diseases other than their registered disease(s). Conclusions: This is the first report to perform follow-up survival analysis across various common diseases. Further studies should use detailed clinical and genomic information to identify predictors of mortality in patients with common diseases, contributing to the implementation of personalized medicine.

Background: The BioBank Japan (BBJ) Project was launched in 2003 with the aim of providing evidence for the implementation of personalized medicine by constructing a large, patient-based biobank (BBJ). This report describes the study design and profile of BBJ participants who were registered during the first 5-year period of the project. Methods: The BBJ is a registry of patients diagnosed with any of 47 target common diseases. Patients were enrolled at 12 cooperative medical institutes all over Japan from June 2003 to March 2008. Clinical information was collected annually via interviews and medical record reviews until 2013. We collected DNA from all participants at baseline and collected annual serum samples until 2013. In addition, we followed patients who reported a history of 32 of the 47 target diseases to collect survival data, including cause of death. Results: During the 5-year period, 200,000 participants were registered in the study. The total number of cases was 291,274 at baseline. Baseline data for 199,982 participants (53.1% male) were available for analysis. The average age at entry was 62.7 years for men and 61.5 years for women. Follow-up surveys were performed for participants with any of 32 diseases, and survival time data for 141,612 participants were available for analysis. Conclusions: The BBJ Project has constructed the infrastructure for genomic research for various common diseases. This clinical information, coupled with genomic data, will provide important clues for the implementation of personalized medicine.

Background: To implement personalized medicine, we established a large-scale patient cohort, BioBank Japan, in 2003. BioBank Japan contains DNA, serum, and clinical information derived from approximately 200,000 patients with 47 diseases. Serum and clinical information were collected annually until 2012. Methods: We analyzed clinical information of participants at enrollment, including age, sex, body mass index, hypertension, and smoking and drinking status, across 47 diseases, and compared the results with the Japanese database on Patient Survey and National Health and Nutrition Survey. We conducted multivariate logistic regression analysis, adjusting for sex and age, to assess the association between family history and disease development. Results: Distribution of age at enrollment reflected the typical age of disease onset. Analysis of the clinical information revealed strong associations between smoking and chronic obstructive pulmonary disease, drinking and esophageal cancer, high body mass index and metabolic disease, and hypertension and cardiovascular disease. Logistic regression analysis showed that individuals with a family history of keloid exhibited a higher odds ratio than those without a family history, highlighting the strong impact of host genetic factor(s) on disease onset. Conclusions: Cross-sectional analysis of the clinical information of participants at enrollment revealed characteristics of the present cohort. Analysis of family history revealed the impact of host genetic factors on each disease. BioBank Japan, by publicly distributing DNA, serum, and clinical information, could be a fundamental infrastructure for the implementation of personalized medicine.

Background: Prostate cancer is the sixth leading cause of cancer-related deaths in Japan. We aimed to elucidate the clinical and histopathological characteristics of patients with prostate cancer in the BioBank Japan (BBJ) project. Methods: Four thousand, seven hundred and ninety-three patients diagnosed with prostate cancer in the BBJ project were included. Clinical and histopathological data, including causes of death, were analyzed. Relative survival (RS) rates of prostate cancer were calculated. Results: Four thousand, one hundred and seventy-one prostate cancer patients with available histological data had adenocarcinoma. The mean age of the patients was 72.5 years. The proportion of patients who were non-smokers, non-drinkers, had a normal body mass index, did not exercise, had a normal prostate-specific antigen level, and had a family history of prostate cancer were 30.7%, 28.0%, 66.6%, 58.1%, 67.6%, and 6.5%, respectively. The proportion of patients with Stage II, III, and IV disease were 24.4%, 7.3%, and 4.4%, respectively. After limiting to patients with a time from the initial diagnosis of prostate cancer to entry into the study cohort of ≤90 days (n = 869), the 5- and 10-year RS rates were 96.3% and 100.5%, respectively, although we were unable to consider management strategies due to a plenty of data missing. Conclusions: We provide an overview of patients with prostate cancer in the BBJ project. Our findings, coupled with those from various high throughput “omics” technologies, will contribute to the implementation of prevention interventions and medical management of prostate cancer patients.