Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution.

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution.

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation, and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here, we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues, using personalized reference genomes to mitigate technical confounding. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B, and T cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.

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.

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.

Genetic determinants of risk in autoimmune pulmonary alveolar proteinosis.

Pulmonary alveolar proteinosis (PAP) is a devastating lung disease caused by abnormal surfactant homeostasis, with a prevalence of 6-7 cases per million population worldwide. While mutations causing hereditary PAP have been reported, the genetic basis contributing to autoimmune PAP (aPAP) has not been thoroughly investigated. Here, we conducted a genome-wide association study of aPAP in 198 patients and 395 control participants of Japanese ancestry. The common genetic variant, rs138024423 at 6p21, in the major-histocompatibility-complex (MHC) region was significantly associated with disease risk (Odds ratio [OR] = 5.2; P = 2.4 × 10-12). HLA fine-mapping revealed that the common HLA class II allele, HLA-DRB1*08:03, strongly drove this signal (OR = 4.8; P = 4.8 × 10-12), followed by an additional independent risk allele at HLA-DPß1 amino acid position 8 (OR = 0.28; P = 3.4 × 10-7). HLA-DRB1*08:03 was also associated with an increased level of anti-GM-CSF antibody, a key driver of the disease (ß = 0.32; P = 0.035). Our study demonstrated a heritable component of aPAP, suggesting an underlying genetic predisposition toward an abnormal antibody production.

Fine Mapping of the Major Histocompatibility Complex Region and Association of the HLA-B*52:01 Allele With Cervical Cancer in Japanese Women.

Importance: Understanding the genetic contribution of the major histocompatibility complex (MHC) region to the risk of cervical cancer (CC) will help understand how immune responses to infection with human papillomaviruses are associated with CC. Objective: To determine whether the HLA-B*52:01 allele is associated with CC in Japanese women. Design, Setting, and Participants: This was a multicenter genetic association study. Genotype and phenotype data were obtained from BioBank Japan Project. Additional patients with CC were enrolled from the Aichi Cancer Center Research Institute. An MHC fine-mapping study was conducted on CC risk in the Japanese population by applying a human leukocyte antigen (HLA) imputation method to the large-scale CC genome-wide association study data of using the Japanese population-specific HLA reference panel. Participants included 540 women in BioBank Japan Project with CC or 39 829 women without gynecologic diseases, malignant neoplasms, and MHC-related diseases as controls. An additional 168 patients with CC were recruited from Aichi Cancer Center Research Institute. Histopathological subtypes and clinical stages were not considered. Participants with low genotype call rate, closely related participants, and outliers in the principal component analysis were excluded. Data analysis was performed from August 2018 to January 2020. Main Outcomes and Measures: Loci within the MHC region associated with CC risk, and the direction and size of association. Results: A total of 704 CC cases and 39 556 controls were analyzed. All participants were Japanese women with a median (range) age of 67 (18 to 100) years. One of the class I HLA alleles of HLA-B*52:01 was significantly associated with CC risk (odds ratio, 1.60; 95% CI, 1.38-1.86; P = 7.4 × 10-10). Allele frequency spectra of HLA-B*52:01 are heterogeneous among worldwide populations with high frequency in Japanese populations (0.109 in controls), suggesting its population-specific risk associated with CC. The conditional analysis suggested that HLA-B*52:01 could explain most of the MHC risk associated with CC because no other HLA alleles remained significant after conditioning on the HLA-B*52:01. The HLA amino acid residue-based analysis suggested that HLA-B p.Tyr171His located in the peptide-binding groove was associated with the most significant CC risk (odds ratio, 1.47; 95% CI, 1.30-1.66; P = 1.2 × 10-9). Conclusions and Relevance: The results of this study contribute to understanding of the genetic background of CC. The results suggest that immune responses mediated by class I HLA molecules are associated with susceptibility to CC.

The Polygenic and Monogenic Basis of Blood Traits and Diseases.

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.

Large-scale genome-wide association study in a Japanese population identifies novel susceptibility loci across different diseases.

The overwhelming majority of participants in current genetic studies are of European ancestry. To elucidate disease biology in the East Asian population, we conducted a genome-wide association study (GWAS) with 212,453 Japanese individuals across 42 diseases. We detected 320 independent signals in 276 loci for 27 diseases, with 25 novel loci (P < 9.58 × 10-9). East Asian-specific missense variants were identified as candidate causal variants for three novel loci, and we successfully replicated two of them by analyzing independent Japanese cohorts; p.R220W of ATG16L2 (associated with coronary artery disease) and p.V326A of POT1 (associated with lung cancer). We further investigated enrichment of heritability within 2,868 annotations of genome-wide transcription factor occupancy, and identified 378 significant enrichments across nine diseases (false discovery rate < 0.05) (for example, NKX3-1 for prostate cancer). This large-scale GWAS in a Japanese population provides insights into the etiology of complex diseases and highlights the importance of performing GWAS in non-European populations.

Genome-wide analysis of dental caries and periodontitis combining clinical and self-reported data.

Dental caries and periodontitis account for a vast burden of morbidity and healthcare spending, yet their genetic basis remains largely uncharacterized. Here, we identify self-reported dental disease proxies which have similar underlying genetic contributions to clinical disease measures and then combine these in a genome-wide association study meta-analysis, identifying 47 novel and conditionally-independent risk loci for dental caries. We show that the heritability of dental caries is enriched for conserved genomic regions and partially overlapping with a range of complex traits including smoking, education, personality traits and metabolic measures. Using cardio-metabolic traits as an example in Mendelian randomization analysis, we estimate causal relationships and provide evidence suggesting that the processes contributing to dental caries may have undesirable downstream effects on health.

GREP: genome for REPositioning drugs.

SUMMARY: Making use of accumulated genetic knowledge for clinical practice is our next goal in human genetics. Here we introduce GREP (Genome for REPositioning drugs), a standalone python software to quantify an enrichment of the user-defined set of genes in the target of clinical indication categories and to capture potentially repositionable drugs targeting the gene set. We show that genes identified by the large-scale genome-wide association studies were robustly enriched in the approved drugs to treat the trait of interest. This enrichment analysis was also highly applicable to other sets of biological genes such as those identified by gene expression studies and genes somatically mutated in cancers. This software should accelerate investigators to reposition drugs to other indications with the guidance of known genomics. AVAILABILITY AND IMPLEMENTATION: GREP is available at https://github.com/saorisakaue/GREP as a python source code. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.