Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

DOCK2 is involved in the host genetics and biology of severe COVID-19.

Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1-5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.

Brugada syndrome in Japan and Europe: a genome-wide association study reveals shared genetic architecture and new risk loci.

BACKGROUND AND AIMS: Brugada syndrome (BrS) is an inherited arrhythmia with a higher disease prevalence and more lethal arrhythmic events in Asians than in Europeans. Genome-wide association studies (GWAS) have revealed its polygenic architecture mainly in European populations. The aim of this study was to identify novel BrS-associated loci and to compare allelic effects across ancestries. METHODS: A GWAS was conducted in Japanese participants, involving 940 cases and 1634 controls, followed by a cross-ancestry meta-analysis of Japanese and European GWAS (total of 3760 cases and 11 635 controls). The novel loci were characterized by fine-mapping, gene expression, and splicing quantitative trait associations in the human heart. RESULTS: The Japanese-specific GWAS identified one novel locus near ZSCAN20 (P = 1.0 × 10-8), and the cross-ancestry meta-analysis identified 17 association signals, including six novel loci. The effect directions of the 17 lead variants were consistent (94.1%; P for sign test = 2.7 × 10-4), and their allelic effects were highly correlated across ancestries (Pearson's R = .91; P = 2.9 × 10-7). The genetic risk score derived from the BrS GWAS of European ancestry was significantly associated with the risk of BrS in the Japanese population [odds ratio 2.12 (95% confidence interval 1.94-2.31); P = 1.2 × 10-61], suggesting a shared genetic architecture across ancestries. Functional characterization revealed that a lead variant in CAMK2D promotes alternative splicing, resulting in an isoform switch of calmodulin kinase II-δ, favouring a pro-inflammatory/pro-death pathway. CONCLUSIONS: This study demonstrates novel susceptibility loci implicating potentially novel pathogenesis underlying BrS. Despite differences in clinical expressivity and epidemiology, the polygenic architecture of BrS was substantially shared across ancestries.

Genetic Risk of Primary Aldosteronism and Its Contribution to Hypertension: A Cross-Ancestry Meta-Analysis of Genome-Wide Association Studies.

BACKGROUND: Hypertension imposes substantial health and economic burden worldwide. Primary aldosteronism (PA) is one of the most common causes of secondary hypertension, causing cardiovascular events at higher risk compared with essential hypertension. However, the germline genetic contribution to the susceptibility of PA has not been well elucidated. METHOD: We conducted a genome-wide association analysis of PA in the Japanese population and a cross-ancestry meta-analysis combined with UK Biobank and FinnGen cohorts (816 PA cases and 425 239 controls) to identify genetic variants that contribute to PA susceptibility. We also performed a comparative analysis for the risk of 42 previously established blood pressure-associated variants between PA and hypertension with the adjustment of blood pressure. RESULTS: In the Japanese genome-wide association study, we identified 10 loci that presented suggestive evidence for the association with the PA risk (P<1.0×10-6). In the meta-analysis, we identified 5 genome-wide significant loci (1p13, 7p15, 11p15, 12q24, and 13q12; P<5.0×10-8), including 3 of the suggested loci in the Japanese genome-wide association study. The strongest association was observed at rs3790604 (1p13), an intronic variant of WNT2B (odds ratio, 1.50 [95% CI, 1.33-1.69]; P=5.2×10-11). We further identified 1 nearly genome-wide significant locus (8q24, CYP11B2), which presented a significant association in the gene-based test (P=7.2×10-7). Of interest, all of these loci were known to be associated with blood pressure in previous studies, presumably because of the prevalence of PA among individuals with hypertension. This assumption was supported by the observation that they had a significantly higher risk effect on PA than on hypertension. We also revealed that 66.7% of the previously established blood pressure-associated variants had a higher risk effect for PA than for hypertension. CONCLUSIONS: This study demonstrates the genome-wide evidence for a genetic predisposition to PA susceptibility in the cross-ancestry cohorts and its significant contribution to the genetic background of hypertension. The strongest association with the WNT2B variants reinforces the implication of the Wnt/ß-catenin pathway in the PA pathogenesis.

Genetic architecture of microRNA expression and its link to complex diseases in the Japanese population.

Understanding the genetic effects on non-coding RNA (ncRNA) expression facilitates functional characterization of disease-associated genetic loci. Among several classes of ncRNAs, microRNAs (miRNAs) are key post-transcriptional gene regulators. Despite its biological importance, previous studies on the genetic architecture of miRNA expression focused mostly on the European individuals, underrepresented in other populations. Here, we mapped miRNA expression quantitative trait loci (miRNA-eQTL) for 343 miRNAs in 141 Japanese using small RNA sequencing and whole-genome sequencing, identifying 1275 cis-miRNA-eQTL variants for 40 miRNAs (false discovery rate < 0.2). Of these, 25 miRNAs having eQTL were unreported in the European studies, including 5 miRNAs with their lead variant monomorphic in the European populations, which demonstrates the value of miRNA-eQTL analysis in diverse ancestral populations. MiRNAs with eQTL effect showed allele-specific expression (ASE; e.g. miR-146a-3p), and ASE analysis further detected cis-regulatory variants not captured by the conventional miRNA-eQTL mapping (e.g. miR-933). We identified a copy number variation associated with miRNA expression (e.g. miR-570-3p, P = 7.2 × 10-6), which contributes to a more comprehensive landscape of miRNA-eQTLs. To elucidate a post-transcriptional modification in miRNAs, we created a catalog of miRNA-editing sites, including 10 canonical and 6 non-canonical sites. Finally, by integrating the miRNA-eQTLs and Japanese genome-wide association studies of 25 complex traits (mean n = 192 833), we conducted a transcriptome-wide association study, identifying miR-1908-5p as a potential mediator for adult height, colorectal cancer and type 2 diabetes (P < 9.1 × 10-5). Our study broadens the population diversity in ncRNA-eQTL studies and contributes to functional annotation of disease-associated loci found in non-European populations.

Extracting immunological and clinical heterogeneity across autoimmune rheumatic diseases by cohort-wide immunophenotyping.

OBJECTIVE: Extracting immunological and clinical heterogeneity across autoimmune rheumatic diseases (AIRDs) is essential towards personalised medicine. METHODS: We conducted large-scale and cohort-wide immunophenotyping of 46 peripheral immune cells using Human Immunology Protocol of comprehensive 8-colour flow cytometric analysis. Dataset consisted of >1000 Japanese patients of 11 AIRDs with deep clinical information registered at the FLOW study, including rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). In-depth clinical and immunological characterisation was conducted for the identified RA patient clusters, including associations of inborn human genetics represented by Polygenic Risk Score (PRS). RESULTS: Multimodal clustering of immunophenotypes deciphered underlying disease-cell type network in immune cell, disease and patient cluster resolutions. This provided immune cell type specificity shared or distinct across AIRDs, such as close immunological network between mixed connective tissue disease and SLE. Individual patient-level clustering dissected patients with AIRD into several clusters with different immunological features. Of these, RA-like or SLE-like clusters were exclusively dominant, showing immunological differentiation between RA and SLE across AIRDs. In-depth clinical analysis of RA revealed that such patient clusters differentially defined clinical heterogeneity in disease activity and treatment responses, such as treatment resistance in patients with RA with SLE-like immunophenotypes. PRS based on RA case-control and within-case stratified genome-wide association studies were associated with clinical and immunological characteristics. This pointed immune cell type implicated in disease biology such as dendritic cells for RA-interstitial lung disease. CONCLUSION: Cohort-wide and cross-disease immunophenotyping elucidate clinically heterogeneous patient subtypes existing within single disease in immune cell type-specific manner.

Obelisc: an identical-by-descent mapping tool based on SNP streak.

MOTIVATION: Genetic linkage analysis has made a huge contribution to the genetic mapping of Mendelian diseases. However, most previously available linkage analysis methods have limited applicability. Since parametric linkage analysis requires predefined model of inheritance with a fixed set of parameters, it is inapplicable without fully structured pedigree information. Furthermore, the analytical results are dependent on the specification of model parameters. While non-parametric linkage analysis can avoid these problems, the runs of homozygosity (ROH) mapping, a widely used non-parametric linkage analysis method, can only deal with recessive inheritance. The implementation of non-parametric linkage analyses capable of dealing with both dominant and recessive inheritance has been required. RESULTS: We have developed the Obelisc (Observational linkage scan), a flexibly applicable user-friendly non-parametric linkage analysis tool, which also provides an intuitive visualization of the analytical results. Obelisc is based on the SNP streak approach, which does not require any predefined inheritance model with parameters. In contrast to the ROH mapping, the SNP streak approach is applicable to both dominant and recessive traits. To illustrate the performance of Obelisc, we generated a pseudo-pedigree from the publicly available BioBank Japan Project genome-wide genotype dataset (n > 180 000). By applying Obelisc to this pseudo-pedigree, we successfully identified the regions with inherited identical-by-descent haplotypes shared among the members of the pseudo-pedigree, which was validated by the population-based haplotype phasing approach. AVAILABILITY AND IMPLEMENTATION: Obelisc is feely available at https://github.com/qsonehara/Obelisc as a python package with example datasets. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multi-trait and cross-population genome-wide association studies across autoimmune and allergic diseases identify shared and distinct genetic component.

OBJECTIVES: Autoimmune and allergic diseases are outcomes of the dysregulation of the immune system. Our study aimed to elucidate differences or shared components in genetic backgrounds between autoimmune and allergic diseases. METHODS: We estimated genetic correlation and performed multi-trait and cross-population genome-wide association study (GWAS) meta-analysis of six immune-related diseases: rheumatoid arthritis, Graves' disease, type 1 diabetes for autoimmune diseases and asthma, atopic dermatitis and pollinosis for allergic diseases. By integrating large-scale biobank resources (Biobank Japan and UK biobank), our study included 105 721 cases and 433 663 controls. Newly identified variants were evaluated in 21 778 cases and 712 767 controls for two additional autoimmune diseases: psoriasis and systemic lupus erythematosus. We performed enrichment analyses of cell types and biological pathways to highlight shared and distinct perspectives. RESULTS: Autoimmune and allergic diseases were not only mutually classified based on genetic backgrounds but also they had multiple positive genetic correlations beyond the classifications. Multi-trait GWAS meta-analysis newly identified six allergic disease-associated loci. We identified four loci shared between the six autoimmune and allergic diseases (rs10803431 at PRDM2, OR=1.07, p=2.3×10-8, rs2053062 at G3BP1, OR=0.90, p=2.9×10-8, rs2210366 at HBS1L, OR=1.07, p=2.5×10-8 in Japanese and rs4529910 at POU2AF1, OR=0.96, p=1.9×10-10 across ancestries). Associations of rs10803431 and rs4529910 were confirmed at the two additional autoimmune diseases. Enrichment analysis demonstrated link to T cells, natural killer cells and various cytokine signals, including innate immune pathways. CONCLUSION: Our multi-trait and cross-population study should elucidate complex pathogenesis shared components across autoimmune and allergic diseases.

Whole gut virome analysis of 476 Japanese revealed a link between phage and autoimmune disease.

OBJECTIVE: The relationship between autoimmune diseases and the gut microbiome has been intensively studied, and several autoimmunity-associated bacterial taxa have been identified. However, much less is known about the roles of the gut virome in autoimmune diseases. METHODS: Here, we performed a whole gut virome analysis based on the shotgun sequencing of 476 Japanese which included patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), multiple sclerosis and healthy control subjects. RESULTS: Our case-control comparison of the viral abundance revealed that crAss-like phages, which are one of the main components of a healthy gut virome, significantly decreased in the gut of the patients with autoimmune disease, specifically the patients with RA and SLE. In addition, Podoviridae significantly decreased in the gut of the patients with SLE. To understand how these viruses affected the bacteriome, we performed a quantitative virus-bacterium association analysis and clustered regularly interspaced short palindromic repeat-based virus-bacterium interaction analysis. We identified a symbiosis between Podoviridae and Faecalibacterium. In addition, multiple bacterial targets of crAss-like phages were identified (eg, Ruminococcus spp). CONCLUSION: Our data suggest that the gut virome can affect our body either directly or via bacteria. Our analyses have elucidated a previously missing part of the autoimmunity-associated gut microbiome and presented new candidates that contribute to the development of autoimmune diseases.

Metagenome-wide association study revealed disease-specific landscape of the gut microbiome of systemic lupus erythematosus in Japanese.

OBJECTIVE: Alteration of the gut microbiome has been linked to the pathogenesis of systemic lupus erythematosus (SLE). However, a comprehensive view of the gut microbiome in SLE and its interaction with the host remains to be revealed. This study aimed to reveal SLE-associated changes in the gut microbiome and its interaction with the host by a comprehensive metagenome-wide association study (MWAS) followed by integrative analysis. METHODS: We performed a MWAS of SLE based on shotgun sequencing of the gut microbial DNA from Japanese individuals (Ncase=47, Ncontrol=203). We integrated the result of the MWAS with the genome-wide association study (GWAS) data and plasma metabolite data. RESULTS: Via species level phylogenetic analysis, we identified and validated increases of Streptococcus intermedius and Streptococcus anginosus in the patients with SLE. Microbial gene analysis revealed increases of Streptococcus-derived genes including one involved in redox reaction. Additionally, microbial pathways related to sulfur metabolism and flagella assembly were altered in the patients with SLE. We identified an overlap in the enriched biological pathways between the metagenome and the germline genome by comparing the result of the MWAS and the GWAS of SLE (ie, MWAS-GWAS interaction). α-diversity and ß-diversity analyses provided evidence of dysbiosis in the metagenome of the patients with SLE. Microbiome-metabolome association analysis identified positive dosage correlation of acylcarnitine with Streptococcus intermedius, an SLE-associated taxon. CONCLUSION: Our MWAS followed by integrative analysis revealed SLE-associated changes in the gut microbiome and its interaction with the host, which contribute to our understanding of the relationship between the microbiome and SLE.

Oncogenic activity of BIRC2 and BIRC3 mutants independent of nuclear factor-κB-activating potential.

BIRC2 and BIRC3 are closely related members of the inhibitor of apoptosis (IAP) family of proteins and play pivotal roles in regulation of nuclear factor-κB (NF-κB) signaling and apoptosis. Copy number loss for and somatic mutation of BIRC2 and BIRC3 have been frequently detected in lymphoid malignancies, with such genetic alterations being thought to contribute to carcinogenesis through activation of the noncanonical NF-κB signaling pathway. Here we show that BIRC2 and BIRC3 mutations are also present in a wide range of epithelial tumors and that most such nonsense or frameshift mutations confer direct transforming potential. This oncogenic function of BIRC2/3 mutants is largely independent of their ability to activate NF-κB signaling. Rather, all of the transforming mutants lack an intact RING finger domain, with loss of ubiquitin ligase activity being essential for transformation irrespective of NF-κB regulation. The serine-threonine kinase NIK was found to be an important, but not exclusive, mediator of BIRC2/3-driven carcinogenesis, although this function was independent of NF-κB activation. Our data thus suggest that, in addition to the BIRC2/3-NIK-NF-κB signaling pathway, BIRC2/3-NIK signaling targets effectors other than NF-κB and thereby contributes directly to carcinogenesis. Identification of these effectors may provide a basis for the development of targeted agents for the treatment of lymphoid malignancies and other cancers with BIRC2/3 alterations.

Body mass index stratification optimizes polygenic prediction of type 2 diabetes in cross-biobank analyses.

Type 2 diabetes (T2D) shows heterogeneous body mass index (BMI) sensitivity. Here, we performed stratification based on BMI to optimize predictions for BMI-related diseases. We obtained BMI-stratified datasets using data from more than 195,000 individuals (nT2D = 55,284) from BioBank Japan (BBJ) and UK Biobank. T2D heritability in the low-BMI group was greater than that in the high-BMI group. Polygenic predictions of T2D toward low-BMI targets had pseudo-R2 values that were more than 22% higher than BMI-unstratified targets. Polygenic risk scores (PRSs) from low-BMI discovery outperformed PRSs from high BMI, while PRSs from BMI-unstratified discovery performed best. Pathway-specific PRSs demonstrated the biological contributions of pathogenic pathways. Low-BMI T2D cases showed higher rates of neuropathy and retinopathy. Combining BMI stratification and a method integrating cross-population effects, T2D predictions showed greater than 37% improvements over unstratified-matched-population prediction. We replicated findings in the Tohoku Medical Megabank (n = 26,000) and the second BBJ cohort (n = 33,096). Our findings suggest that target stratification based on existing traits can improve the polygenic prediction of heterogeneous diseases.

Genome-wide association study identifies risk loci within the major histocompatibility complex region for Hunner-type interstitial cystitis.

Hunner-type interstitial cystitis (HIC) is a rare, chronic inflammatory disease of the urinary bladder with unknown etiology and genetic background. Here, we conduct a genome-wide association study of 144 patients with HIC and 41,516 controls of Japanese ancestry. The genetic variant, rs1794275, in the major histocompatibility complex (MHC) region (chromosome 6p21.3) is associated with HIC risk (odds ratio [OR] = 2.32; p = 3.4 × 10-9). The association is confirmed in a replication set of 26 cases and 1,026 controls (p = 0.014). Fine mapping demonstrates the contribution to the disease risk of a completely linked haplotype of three human leukocyte antigen HLA-DQß1 amino acid positions, 71, 74, and 75 (OR = 1.94; p = 5 × 10-8) and of HLA-DPß1 amino acid position 178, which tags HLA-DPB1∗04:02 (OR = 2.35; p = 7.5 × 10-8). The three HLA-DQß1 amino acid positions are located together at the peptide binding groove, suggesting their functional importance in antigen presentation. Our study reveals genetic contributions to HIC risk that may be associated with class II MHC molecule antigen presentation.

Genetic footprints of assortative mating in the Japanese population.

Assortative mating (AM) is a pattern characterized by phenotypic similarities between mating partners. Detecting the evidence of AM has been challenging due to the lack of large-scale datasets that include phenotypic data on both partners, especially in populations of non-European ancestries. Gametic phase disequilibrium between trait-associated alleles is a signature of parental AM on a polygenic trait, which can be detected even without partner data. Here, using polygenic scores for 81 traits in the Japanese population using BioBank Japan Project genome-wide association studies data (n = 172,270), we found evidence of AM on the liability to type 2 diabetes and coronary artery disease, as well as on dietary habits. In cross-population comparison using United Kingdom Biobank data (n = 337,139) we found shared but heterogeneous impacts of AM between populations.

Pan-cancer and cross-population genome-wide association studies dissect shared genetic backgrounds underlying carcinogenesis.

Integrating genomic data of multiple cancers allows de novo cancer grouping and elucidating the shared genetic basis across cancers. Here, we conduct the pan-cancer and cross-population genome-wide association study (GWAS) meta-analysis and replication studies on 13 cancers including 250,015 East Asians (Biobank Japan) and 377,441 Europeans (UK Biobank). We identify ten cancer risk variants including five pleiotropic associations (e.g., rs2076295 at DSP on 6p24 associated with lung cancer and rs2525548 at TRIM4 on 7q22 nominally associated with six cancers). Quantifying shared heritability among the cancers detects positive genetic correlations between breast and prostate cancer across populations. Common genetic components increase the statistical power, and the large-scale meta-analysis of 277,896 breast/prostate cancer cases and 901,858 controls identifies 91 newly genome-wide significant loci. Enrichment analysis of pathways and cell types reveals shared genetic backgrounds across said cancers. Focusing on genetically correlated cancers can contribute to enhancing our insights into carcinogenesis.

A genome-wide association study for allergen component sensitizations identifies allergen component-specific and allergen protein group-specific associations.

Background: Allergic diseases are some of the most common diseases worldwide. Genome-wide association studies (GWASs) have been conducted to elucidate the genetic factors of allergic diseases. However, no GWASs for allergen component sensitization have been performed. Objective: We sought to detect genetic variants associated with differences in immune responsiveness against allergen components. Methods: The participants of the present study were recruited from the Tokyo Children's Health, Illness, and Development study, and allergen component-specific IgE level at age 9 years was measured by means of allergen microarray immunoassays. We performed GWASs for allergen component sensitization against each allergen (single allergen component sensitization, number of allergen components analyzed, n = 31), as well as against allergen protein families (allergen protein group sensitization, number of protein groups analyzed, n = 16). Results: We performed GWAS on 564 participants of the Tokyo Children's Health, Illness, and Development study and found associations between Amb a 1 sensitization and the immunoglobulin heavy-chain variable gene on chromosome 14 and between Phl p 1 sensitization and the HLA class II region on chromosome 6 (P < 5.0 × 10-8). A GWAS-significant association was also observed between the HLA class II region and profilin sensitization (P < 5.0 × 10-8). Conclusions: Our data provide the first demonstration of genetic risk for allergen component sensitization and show that this genetic risk is related to immune response genes including immunoglobulin heavy-chain variable gene and HLA.

Estimating gene-level false discovery probability improves eQTL statistical fine-mapping precision.

Statistical fine-mapping prioritizes putative causal variants from a large number of candidate variants, and is widely used in expression quantitative loci (eQTLs) studies. In eQTL fine-mapping, the existence of causal variants for gene expression is not guaranteed, since the genetic heritability of gene expression explained by nearby (cis-) variants is limited. Here we introduce a refined fine-mapping algorithm, named Knockoff-Finemap combination (KFc). KFc estimates the probability that the causal variant(s) exist in the cis-window of a gene through construction of knockoff genotypes (i.e. a set of synthetic genotypes that resembles the original genotypes), and uses it to adjust the posterior inclusion probabilities (PIPs). Utilizing simulated gene expression data, we show that KFc results in calibrated PIP distribution with improved precision. When applied to gene expression data of 465 genotyped samples from the Japan COVID-19 Task Force (JCTF), KFc resulted in significant enrichment of a functional score as well as reporter assay hits in the top PIP bins. When combined with functional priors derived from an external fine-mapping study (GTEx), KFc resulted in a significantly higher proportion of hematopoietic trait putative causal variants in the top PIP bins. Our work presents improvements in the precision of a major fine-mapping algorithm.

Genome-Wide Association Study of Intracranial Artery Stenosis Followed by Phenome-Wide Association Study.

The genetic background of intracranial artery stenosis (ICAS), a major cause of ischemic stroke, remains elusive. We performed the world's first genome-wide association study (GWAS) of ICAS using DNA samples from Japanese subjects, to identify the genetic factors associated with ICAS and their correlation with clinical features. We also conducted a phenome-wide association study (PheWAS) of the top variant identified via GWAS to determine its association with systemic disease. The GWAS involved 408 patients with ICAS and 349 healthy controls and utilized an Asian Screening Array of venous blood samples. The PheWAS was performed using genotypic and phenotypic data of the Biobank Japan Project, which contained information on 46 diseases and 60 quantitative trait data from > 150,000 Japanese individuals. The GWAS revealed that the East Asian-specific functional variant of RNF213, rs112735431 (c.14429G > A, p.Arg4810Lys), was associated with ICAS (odds ratio, 12.3; 95% CI 5.5 to 27.5; P = 7.8 × 10-10). Stratified analysis within ICAS cases demonstrated that clinical features of those with and without the risk allele were different. PheWAS indicated that high blood pressure and angina were significantly associated with RNF213 rs112735431. The first GWAS of ICAS, which stratifies subpopulations within the ICAS cases with distinct clinical features, revealed that RNF213 rs112735431 was the most significant variant associated with ICAS. Thus, RNF213 rs112735431 shows potential as an important clinical biomarker that characterizes pleiotropic risk in various vascular diseases, such as blood pressure and angina, thereby facilitating personalized medicine for systemic vascular diseases in East Asian populations.

Reconstruction of the personal information from human genome reads in gut metagenome sequencing data.

Human DNA present in faecal samples can result in a small number of human reads in gut shotgun metagenomic sequencing data. However, it is presently unclear how much personal information can be reconstructed from such reads, and this has not been quantitatively evaluated. Such a quantitative evaluation is necessary to clarify the ethical concerns related to data sharing and to enable efficient use of human genetic information in stool samples, such as for research and forensics. Here we used genomic approaches to reconstruct personal information from the faecal metagenomes of 343 Japanese individuals with associated human genotype data. Genetic sex could be accurately predicted based on the sequencing depth of sex chromosomes for 97.3% of the samples. Individuals could be re-identified from the matched genotype data based on human reads recovered from the faecal metagenomic data with 93.3% sensitivity using a likelihood score-based method. This method also enabled us to predict the ancestries of 98.3% of the samples. Finally, we performed ultra-deep shotgun metagenomic sequencing of five faecal samples as well as whole-genome sequencing of blood samples. Using genotype-calling approaches, we demonstrated that the genotypes of both common and rare variants could be reconstructed from faecal samples. This included clinically relevant variants. Our approach can be used to quantify personal information contained within gut metagenome data.