Stroke genetics informs drug discovery and risk prediction across ancestries.

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.

A novel CCDC91 isoform associated with ossification of the posterior longitudinal ligament of the spine works as a non-coding RNA to regulate osteogenic genes.

Ossification of the posterior longitudinal ligament of the spine (OPLL) is a common intractable disease that causes spinal stenosis and myelopathy. We have previously conducted genome-wide association studies for OPLL and identified 14 significant loci, but their biological implications remain mostly unclear. Here, we examined the 12p11.22 locus and identified a variant in the 5' UTR of a novel isoform of CCDC91 that was associated with OPLL. Using machine learning prediction models, we determined that higher expression of the novel CCDC91 isoform was associated with the G allele of rs35098487. The risk allele of rs35098487 showed higher affinity in the binding of nuclear proteins and transcription activity. Knockdown and overexpression of the CCDC91 isoform in mesenchymal stem cells and MG-63 cells showed paralleled expression of osteogenic genes, including RUNX2, the master transcription factor of osteogenic differentiation. The CCDC91 isoform directly interacted with MIR890, which bound to RUNX2 and decreased RUNX2 expression. Our findings suggest that the CCDC91 isoform acts as a competitive endogenous RNA by sponging MIR890 to increase RUNX2 expression.

Genotype imputation accuracy and the quality metrics of the minor ancestry in multi-ancestry reference panels.

Large-scale imputation reference panels are currently available and have contributed to efficient genome-wide association studies through genotype imputation. However, whether large-size multi-ancestry or small-size population-specific reference panels are the optimal choices for under-represented populations continues to be debated. We imputed genotypes of East Asian (180k Japanese) subjects using the Trans-Omics for Precision Medicine reference panel and found that the standard imputation quality metric (Rsq) overestimated dosage r2 (squared correlation between imputed dosage and true genotype) particularly in marginal-quality bins. Variance component analysis of Rsq revealed that the increased imputed-genotype certainty (dosages closer to 0, 1 or 2) caused upward bias, indicating some systemic bias in the imputation. Through systematic simulations using different template switching rates (θ value) in the hidden Markov model, we revealed that the lower θ value increased the imputed-genotype certainty and Rsq; however, dosage r2 was insensitive to the θ value, thereby causing a deviation. In simulated reference panels with different sizes and ancestral diversities, the θ value estimates from Minimac decreased with the size of a single ancestry and increased with the ancestral diversity. Thus, Rsq could be deviated from dosage r2 for a subpopulation in the multi-ancestry panel, and the deviation represents different imputed-dosage distributions. Finally, despite the impact of the θ value, distant ancestries in the reference panel contributed only a few additional variants passing a predefined Rsq threshold. We conclude that the θ value substantially impacts the imputed dosage and the imputation quality metric value.

Novel susceptibility loci for steroid-associated osteonecrosis of the femoral head in systemic lupus erythematosus.

Osteonecrosis of the femoral head (ONFH) involves necrosis of bone and bone marrow of the femoral head caused by ischemia with unknown etiology. Previous genetic studies on ONFH failed to produce consistent results, presumably because ONFH has various causes with different genetic backgrounds and the underlying diseases confounded the associations. Steroid-associated ONFH (S-ONFH) accounts for one-half of all ONFH, and systemic lupus erythematosus (SLE) is a representative disease underlying S-ONFH. We performed a genome-wide association study (GWAS) to identify genetic risk factors for S-ONFH in patients with SLE. We conducted a two-staged GWAS on 636 SLE patients with S-ONFH and 95 588 non-SLE controls. Among the novel loci identified, we determined S-ONFH-specific loci by comparing allele frequencies between SLE patients without S-ONFH and non-SLE controls. We also used Korean datasets comprising 148 S-ONFH cases and 37 015 controls to assess overall significance. We evaluated the functional annotations of significant variants by in silico analyses. The Japanese GWAS identified 4 significant loci together with 12 known SLE susceptibility loci. The four significant variants showed comparable effect sizes on S-ONFH compared with SLE controls and non-SLE controls. Three of the four loci, MIR4293/MIR1265 [odds ratio (OR) = 1.99, P-value = 1.1 × 10-9)], TRIM49/NAALAD2 (OR = 1.65, P-value = 4.8 × 10-8) and MYO16 (OR = 3.91, P-value = 4.9 × 10-10), showed significant associations in the meta-analysis with Korean datasets. Bioinformatics analyses identified MIR4293, NAALAD2 and MYO16 as candidate causal genes. MIR4293 regulates a PPARG-related adipogenesis pathway relevant to S-ONFH. We identified three novel susceptibility loci for S-ONFH in SLE.

Fundamentals for predicting transcriptional regulations from DNA sequence patterns.

Cell-type-specific regulatory elements, cataloged through extensive experiments and bioinformatics in large-scale consortiums, have enabled enrichment analyses of genetic associations that primarily utilize positional information of the regulatory elements. These analyses have identified cell types and pathways genetically associated with human complex traits. However, our understanding of detailed allelic effects on these elements' activities and on-off states remains incomplete, hampering the interpretation of human genetic study results. This review introduces machine learning methods to learn sequence-dependent transcriptional regulation mechanisms from DNA sequences for predicting such allelic effects (not associations). We provide a concise history of machine-learning-based approaches, the requirements, and the key computational processes, focusing on primers in machine learning. Convolution and self-attention, pivotal in modern deep-learning models, are explained through geometrical interpretations using dot products. This facilitates understanding of the concept and why these have been used for machine learning for DNA sequences. These will inspire further research in this genetics and genomics field.

Genetic Risk Score for Intracranial Aneurysms: Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity.

BACKGROUND: Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. METHODS: A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. RESULTS: Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20-1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01-1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59-0.67) to 0.65 (95% CI, 0.62-0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (ß=-4.82×10-3 per year [95% CI, -6.49×10-3 to -3.14×10-3]; P=1.82×10-8), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86-0.98]; P=0.0041). CONCLUSIONS: The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH.

Polygenic modelling and machine learning approaches in pharmacogenomics: Importance in downstream analysis of genome-wide association study data.

Genome-wide association studies (GWAS) have identified genetic variations associated with adverse drug effects in pharmacogenomics (PGx) research. However, interpreting the biological implications of these associations remains a challenge. This review highlights 2 promising post-GWAS methods for PGx. First, we discuss the polygenic architecture of the PGx traits, especially for drug-induced liver injury. Experimental modelling using multiple donors' human primary hepatocytes and human liver organoids demonstrated the polygenic architecture of drug-induced liver injury susceptibility and found biological vulnerability in genetically high-risk tissue donors. Second, we discuss the challenges of interpreting the roles of variants in noncoding regions. Beyond methods involving expression quantitative trait locus analysis and massively parallel reporter assays, we suggest the use of in silico mutagenesis through machine learning methods to understand the roles of variants in transcriptional regulation. This review underscores the importance of these post-GWAS methods in providing critical insights into PGx, potentially facilitating drug development and personalized treatment.

Genetically increased circulating FUT3 level leads to reduced risk of idiopathic pulmonary fibrosis: a Mendelian randomisation study.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal fibrotic interstitial lung disease. Few circulating biomarkers have been identified to have causal effects on IPF. METHODS: To identify candidate IPF-influencing circulating proteins, we undertook an efficient screen of circulating proteins by applying a two-sample Mendelian randomisation (MR) approach with existing publicly available data. For instruments, we used genetic determinants of circulating proteins which reside cis to the encoded gene (cis-single nucleotide polymorphisms (SNPs)), identified by two genome-wide association studies (GWASs) in European individuals (3301 and 3200 subjects). We then applied MR methods to test if the levels of these circulating proteins influenced IPF susceptibility in the largest IPF GWAS (2668 cases and 8591 controls). We validated the MR results using colocalisation analyses to ensure that both the circulating proteins and IPF shared a common genetic signal. RESULTS: MR analyses of 834 proteins found that a 1 sd increase in circulating galactoside 3(4)-l-fucosyltransferase (FUT3) and α-(1,3)-fucosyltransferase 5 (FUT5) was associated with a reduced risk of IPF (OR 0.81, 95% CI 0.74-0.88; p=6.3×10-7 and OR 0.76, 95% CI 0.68-0.86; p=1.1×10-5, respectively). Sensitivity analyses including multiple cis-SNPs provided similar estimates both for FUT3 (inverse variance weighted (IVW) OR 0.84, 95% CI 0.78-0.91; p=9.8×10-6 and MR-Egger OR 0.69, 95% CI 0.50-0.97; p=0.03) and FUT5 (IVW OR 0.84, 95% CI 0.77-0.92; p=1.4×10-4 and MR-Egger OR 0.59, 95% CI 0.38-0.90; p=0.01). FUT3 and FUT5 signals colocalised with IPF signals, with posterior probabilities of a shared genetic signal of 99.9% and 97.7%, respectively. Further transcriptomic investigations supported the protective effects of FUT3 for IPF. CONCLUSIONS: An efficient MR scan of 834 circulating proteins provided evidence that genetically increased circulating FUT3 level is associated with reduced risk of IPF.

Biological insights into systemic lupus erythematosus through an immune cell-specific transcriptome-wide association study.

OBJECTIVE: Genome-wide association studies (GWAS) have identified >100 risk loci for systemic lupus erythematosus (SLE), but the disease genes at most loci remain unclear, hampering translation of these genetic discoveries. We aimed to prioritise genes underlying the 110 SLE loci that were identified in the latest East Asian GWAS meta-analysis. METHODS: We built gene expression predictive models in blood B cells, CD4+ and CD8+ T cells, monocytes, natural killer cells and peripheral blood cells of 105 Japanese individuals. We performed a transcriptome-wide association study (TWAS) using data from the latest genome-wide association meta-analysis of 208 370 East Asians and searched for candidate genes using TWAS and three data-driven computational approaches. RESULTS: TWAS identified 171 genes for SLE (p<1.0×10-5); 114 (66.7%) showed significance only in a single cell type; 127 (74.3%) were in SLE GWAS loci. TWAS identified a strong association between CD83 and SLE (p<7.7×10-8). Meta-analysis of genetic associations in the existing 208 370 East Asian and additional 1498 cases and 3330 controls found a novel single-variant association at rs72836542 (OR=1.11, p=4.5×10-9) around CD83. For the 110 SLE loci, we identified 276 gene candidates, including 104 genes at recently-identified SLE novel loci. We demonstrated in vitro that putative causal variant rs61759532 exhibited an allele-specific regulatory effect on ACAP1, and that presence of the SLE risk allele decreased ACAP1 expression. CONCLUSIONS: Cell-level TWAS in six types of immune cells complemented SLE gene discovery and guided the identification of novel genetic associations. The gene findings shed biological insights into SLE genetic associations.

Genome-wide association study of colorectal polyps identified highly overlapping polygenic architecture with colorectal cancer.

No genome-wide association studies (GWAS) were reported for colorectal polyps and the overlap in polygenic backgrounds conferring risk of colorectal cancer and polyps remains unclear. We performed GWAS on subjects with colorectal polyps using the BioBank Japan data with 4447 cases and 157,226 controls. We evaluated genetic correlations between colorectal polyps and cancer, and effects on colorectal polyps of single nucleotide polymorphisms (SNPs) known to be associated with colorectal cancer. We identified CUX2, a known genetic locus to colorectal cancer, as a susceptibility locus to colorectal polyps (p value = 1.1 × 10-15). Subsequent fine-mapping analysis indicated that rs11065828 in CUX2 is the causal variant for colorectal polyps. We found that known colorectal cancer-susceptible SNPs were also associated with colorectal polyps. The genetic correlation between colorectal cancer and polyps is very high (r = 0.98 and p value = 0.0006). We additionally identified 14 significant loci of colorectal polyps and three significant loci of colorectal cancer by applying the multi-trait analysis of GWAS of colorectal cancer and colorectal polyps. We showed very similar germline polygenic features, which gives us the additional insight into potential cancers at polygenic levels for patients with polyps who are followed up at outpatients' clinic; thus, close observation and polypectomy is critical to prevent colorectal cancers.

Eight novel susceptibility loci and putative causal variants in atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD) is the most common allergic disease in the world. While genetic components play critical roles in its pathophysiology, a large proportion of its genetic background is still unexplored. OBJECTIVES: This study sought to illuminate the genetic associations with AD using genome-wide association study (GWAS) and its downstream analyses. METHODS: This study conducted a GWAS for AD comprising 2,639 cases and 115,648 controls in the Japanese population, followed by a trans-ethnic meta-analysis with UK Biobank data and downstream analyses including partitioning heritability analysis by linkage disequilibrium score regression. RESULTS: This study identified 17 significant susceptibility loci, among which 4 loci-AFF1, ITGB8, EHMT1, and EGR2-were novel in the Japanese GWAS. The trans-ethnic meta-analysis revealed 4 additional novel loci, namely-ZBTB38,LOC105755953/LOC101928272, TRAF3, andIQGAP1. This study found a missense variant (R243W) with a deleterious functional effect in NLRP10 and a variant altering expression of CCDC80 via enhancer expression as highly likely causal variants. These 2 regions were Asian-specific, and these population-specific associations could be explained by the frequency of causal variants. The gene-based test showed SMAD4 as an additional novel significant locus. Downstream analyses revealed substantial overlap of GWAS significant signals in enhancers of skin cells and immune cells, especially CD4 T cells. A highly shared polygenic architecture of AD between Europeans and Asians was also found. CONCLUSIONS: This study identified Japanese-specific loci and novel significant loci shared by different populations. Two putative causal variants were illuminated in Japanese-specific loci. Trans-ethnic analyses revealed strong heritability enrichment in immune-related pathways, and relevant cell types shared among populations.

The kinase PERK represses translation of the G-protein-coupled receptor LGR5 and receptor tyrosine kinase ERBB3 during ER stress in cancer cells.

As a branch of the unfolded protein response, protein kinase R-like endoplasmic reticulum kinase (PERK) represses global translation in response to endoplasmic reticulum (ER) stress. This pathophysiological condition is associated with the tumor microenvironment in cancer. Previous findings in our lab have suggested that PERK selectively represses translation of some mRNAs, but this possibility awaits additional investigation. In this study, we show that a stem-cell marker protein, leucine-rich repeat-containing G-protein-coupled receptor 5 (LGR5), is rapidly depleted in colon cancer cells during ER stress, an effect that depended on the PERK-mediated translational repression. Indeed, the PERK inhibition led to the accumulation of premature, underglycosylated forms of LGR5, which were produced only at low levels during proper PERK activation. Unlike the mature LGR5 form, which is constitutively degraded regardless of PERK activation, the underglycosylated LGR5 exhibited a prolonged half-life and accumulated inside the cells without being expressed on the cell surface. We also found that Erb-B2 receptor tyrosine kinase 3 (ERBB3) is subjected to a similarly-regulated depletion by PERK, whereas the epidermal growth factor receptor (EGFR), stress-inducible heat-shock protein family A (Hsp70) member 5 (HSPA5), and anterior gradient 2 protein-disulfide isomerase family member (AGR2) were relatively. insensitive to the PERK-mediated repression of translation. These results indicate that LGR5 and ERBB3 are targets for PERK-mediated translational repression during ER stress.

Meta-analysis of 208370 East Asians identifies 113 susceptibility loci for systemic lupus erythematosus.

OBJECTIVE: Systemic lupus erythematosus (SLE), an autoimmune disorder, has been associated with nearly 100 susceptibility loci. Nevertheless, these loci only partially explain SLE heritability and their putative causal variants are rarely prioritised, which make challenging to elucidate disease biology. To detect new SLE loci and causal variants, we performed the largest genome-wide meta-analysis for SLE in East Asian populations. METHODS: We newly genotyped 10 029 SLE cases and 180 167 controls and subsequently meta-analysed them jointly with 3348 SLE cases and 14 826 controls from published studies in East Asians. We further applied a Bayesian statistical approach to localise the putative causal variants for SLE associations. RESULTS: We identified 113 genetic regions including 46 novel loci at genome-wide significance (p<5×10-8). Conditional analysis detected 233 association signals within these loci, which suggest widespread allelic heterogeneity. We detected genome-wide associations at six new missense variants. Bayesian statistical fine-mapping analysis prioritised the putative causal variants to a small set of variants (95% credible set size ≤10) for 28 association signals. We identified 110 putative causal variants with posterior probabilities ≥0.1 for 57 SLE loci, among which we prioritised 10 most likely putative causal variants (posterior probability ≥0.8). Linkage disequilibrium score regression detected genetic correlations for SLE with albumin/globulin ratio (rg=-0.242) and non-albumin protein (rg=0.238). CONCLUSION: This study reiterates the power of large-scale genome-wide meta-analysis for novel genetic discovery. These findings shed light on genetic and biological understandings of SLE.

Comparison of effects of UGT1A1*6 and UGT1A1*28 on irinotecan-induced adverse reactions in the Japanese population: analysis of the Biobank Japan Project.

It has been reported that there are differences in effects on irinotecan-induced adverse reactions between UGT1A1*6 and UGT1A1*28. In order to compare those differences in the Japanese population, we examined the associations between UGT1A1 and irinotecan-induced adverse reactions using the BioBank Japan Project database. We genotyped UTG1A1*6 and UGT1A1*28 and conducted case-control analyses. A total of 651 patients (102 cases and 549 tolerant controls) were included in this study. The results showed that UGT1A1*6/*6 is a predictor of adverse drug reactions (ADRs) (p-value 0.00070, odds ratio 6.59, 95% confidence interval 2.33-18.6), whereas UGT1A1*6/*28 and UGT1A1*28/*28 were not. The subanalysis comprising only patients with UGT1A1*6/*6, UGT1A1*6/*28, and UGT1A1*28/*28 revealed a trend towards an increased risk of ADRs in patients with UGT1A1*6 (p-value 0.0092, odds ratio 4.39, 95% confidence interval 1.57-14.9). Multiple logistic regression analyses showed that use of platinum-based antineoplastic drugs and presence of UGT1A1*6/*6 were independent variables, significantly associated with ADRs. The diagnostic performance of a predictive model had a sensitivity of 49.0%, specificity of 70.1%, and a number needed to screen of 5.8. We concluded that UGT1A1 testing could be useful to predict irinotecan-induced ADRs, and that UTG1A1*6 rather than UGT1A1*28 contributed to ADR occurrence.

PMEPA1, a TGF-ß- and hypoxia-inducible gene that participates in hypoxic gene expression networks in solid tumors.

Prostate transmembrane protein, androgen induced 1 (PMEPA1) is highly expressed in various solid tumors and is known to play important roles in the transforming growth factor-ß (TGF-ß) signaling pathway. Here, we demonstrate a novel relationship between PMEPA1 and hypoxia, a common microenvironmental stress condition in solid tumors. We showed that induction of PMEPA1 expression occurred during hypoxia in a manner dependent on both TGF-ß signaling and hypoxia-inducible factor-1 (HIF-1) pathways. Furthermore, overexpression and knockdown experiments revealed that PMEPA1 enhanced HIF-1 transcription activity. Bioinformatics analyses of PMEPA1-correlated genes using a gene expression database in clinical settings showed significant enrichment of gene sets defined by TGF-ß and hypoxia and these two signaling pathways-related angiogenesis and epithelial-mesenchymal transition in many types of solid tumors. Collectively, our findings indicated that PMEPA1 participates in TGF-ß- and hypoxia-regulated gene expression networks in solid tumors and thereby may contribute to tumor progression.

RNF213 Variants, Vasospastic Angina, and Risk of Fatal Myocardial Infarction.

Importance: Vasospastic angina (VSA) is vasospasm of the coronary artery and is particularly prevalent in East Asian populations. However, the specific genetic architecture for VSA at genome-wide levels is not fully understood. Objective: To identify genetic factors associated with VSA. Design, Setting, and Participants: This was a case-control genome-wide association study of VSA. Data from Biobank Japan (BBJ; enrolled patients from 2002-2008 and 2013-2018) were used, and controls without coronary artery disease (CAD) were enrolled. Patients from the BBJ were genotyped using arrays or a set of arrays. Patients recruited between 2002 and 2005 were classified within the first dataset, and those recruited between 2006 and 2008 were classified within the second dataset. To replicate the genome-wide association study in the first and second datasets, VSA cases and control samples from the latest patients in the BBJ recruited between 2013 and 2018 were analyzed in a third dataset. Exposures: Single-nucleotide variants associated with VSA. Main Outcomes and Measures: Cases with VSA and controls without CAD. Results: A total of 5720 cases (mean [SD] age, 67 [10] years; 3672 male [64.2%]) and 153 864 controls (mean [SD] age, 62 [15] years; 77 362 male [50.3%]) in 3 datasets were included in this study. The variants at the RNF213 locus showed the strongest association with VSA across the 3 datasets (odds ratio [OR], 2.34; 95% CI, 1.99-2.74; P = 4.4 × 10-25). Additionally, rs112735431, an Asian-specific rare deleterious variant (p.Arg4810Lys) experimentally shown to be associated with reduced angiogenesis and a well-known causal risk for Moyamoya disease was the most promising candidate for a causal variant explaining the association. The effect size of rs112735431 on VSA was distinct from that of other CADs. Furthermore, homozygous carriers of rs112735431 showed an association with VSA characterized by a large effect estimate (OR, 18.34; 95% CI, 5.15-65.22; P = 7.0 × 10-6), deviating from the additive model (OR, 4.35; 95% CI, 1.18-16.05; P = .03). Stratified analyses revealed that rs112735431 exhibited a stronger association in males (χ21 = 7.24; P = .007) and a younger age group (OR, 3.06; 95% CI, 2.24-4.19), corresponding to the epidemiologic features of VSA. In the registry, carriers without CAD of the risk allele rs112735431 had a strikingly high mortality rate due to acute myocardial infarction during the follow-up period (hazard ratio, 2.71; 95% CI, 1.57-4.65; P = 3.3 × 10-4). As previously reported, a possible overlap between VSA and Moyamoya disease was not found. Conclusions and Relevance: Results of this study suggest that vascular cell dysfunction mediated by variants in the RNF213 locus may promote coronary vasospasm, and the presence of the risk allele could serve as a predictive factor for the prognosis.

Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing.

We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.

An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases.

Transcribed enhancer maps can reveal nuclear interactions underpinning each cell type and connect specific cell types to diseases. Using a 5' single-cell RNA sequencing approach, we defined transcription start sites of enhancer RNAs and other classes of coding and noncoding RNAs in human CD4+ T cells, revealing cellular heterogeneity and differentiation trajectories. Integration of these datasets with single-cell chromatin profiles showed that active enhancers with bidirectional RNA transcription are highly cell type-specific and that disease heritability is strongly enriched in these enhancers. The resulting cell type-resolved multimodal atlas of bidirectionally transcribed enhancers, which we linked with promoters using fine-scale chromatin contact maps, enabled us to systematically interpret genetic variants associated with a range of immune-mediated diseases.

Annotation of nuclear lncRNAs based on chromatin interactions.

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.