Genome-wide analyses of variance in blood cell phenotypes provide new insights into complex trait biology and prediction.

Blood cell phenotypes are routinely tested in healthcare to inform clinical decisions. Genetic variants influencing mean blood cell phenotypes have been used to understand disease aetiology and improve prediction; however, additional information may be captured by genetic effects on observed variance. Here, we mapped variance quantitative trait loci (vQTL), i.e. genetic loci associated with trait variance, for 29 blood cell phenotypes from the UK Biobank (N~408,111). We discovered 176 independent blood cell vQTLs, of which 147 were not found by additive QTL mapping. vQTLs displayed on average 1.8-fold stronger negative selection than additive QTL, highlighting that selection acts to reduce extreme blood cell phenotypes. Variance polygenic scores (vPGSs) were constructed to stratify individuals in the INTERVAL cohort (N~40,466), where genetically less variable individuals (low vPGS) had increased conventional PGS accuracy (by ~19%) than genetically more variable individuals. Genetic prediction of blood cell traits improved by ~10% on average combining PGS with vPGS. Using Mendelian randomisation and vPGS association analyses, we found that alcohol consumption significantly increased blood cell trait variances highlighting the utility of blood cell vQTLs and vPGSs to provide novel insight into phenotype aetiology as well as improve prediction.

Ploidy inference from single-cell data: application to human and mouse cell atlases.

Ploidy is relevant to numerous biological phenomena, including development, metabolism, and tissue regeneration. Single-cell RNA-seq and other omics studies are revolutionizing our understanding of biology, yet they have largely overlooked ploidy. This is likely due to the additional assay step required for ploidy measurement. Here, we developed a statistical method to infer ploidy from single-cell ATAC-seq data, addressing this gap. When applied to data from human and mouse cell atlases, our method enabled systematic detection of polyploidy across diverse cell types. This method allows for the integration of ploidy analysis into single-cell studies. Additionally, this method can be adapted to detect the proliferating stage in the cell cycle and copy number variations in cancer cells. The software is implemented as the scPloidy package of the R software and is freely available from CRAN.

Four-week inhibition of the renin-angiotensin system in spontaneously hypertensive rats results in persistently lower blood pressure with reduced kidney renin and changes in expression of relevant gene networks.

AIMS: Prevention of human hypertension is an important challenge and has been achieved in experimental models. Brief treatment with renin-angiotensin system (RAS) inhibitors permanently reduces the genetic hypertension of the spontaneously hypertensive rat (SHR). The kidney is involved in this fascinating phenomenon, but relevant changes in gene expression are unknown. METHODS: In SHR, we studied the effect of treatment between 10 and 14 weeks of age with the angiotensin receptor blocker, losartan, or the angiotensin-converting enzyme (ACE) inhibitor, perindopril (with controls for non-specific effects of lowering BP) on differential RNA expression, DNA methylation and renin immunolabelling in the kidney at 20 weeks of age. RESULTS: RNA sequencing revealed a 6-fold increase in renin gene (Ren) expression during losartan treatment (P < 0.0001). Six weeks after losartan, arterial pressure remained lower (P = 0.006), yet kidney Ren showed reduced expression by 23% after losartan (P = 0.03) and by 43% after perindopril (P = 1.4 x 10-6) associated with increased DNA methylation (P = 0.04). Immunolabelling confirmed reduced cortical renin after earlier RAS blockade (P = 0.002). RNA sequencing identified differential expression of mRNAs, miRNAs and lncRNAs with evidence of networking and co-regulation. These included 13 candidate genes (Grhl1, Ammecr1l, Hs6st1, Nfil3, Fam221a, Lmo4, Adamts1, Cish, Hif3a, Bcl6, Rad54l2, Adap1, Dok4), the miRNA miR-145-3p and the lncRNA AC115371. Gene ontogeny analyses revealed that these networks were enriched with genes relevant to BP, RAS and the kidneys. CONCLUSIONS: Early RAS inhibition in SHR resets genetic pathways and networks resulting in a legacy of reduced Ren expression and BP persisting for a minimum of 6 weeks.

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.

Genotypes of Stim1 and the proximal region on chromosome 1 exert opposite effects on stroke susceptibility in stroke-prone spontaneously hypertensive rat.

BACKGROUND: The stroke-prone spontaneously hypertensive rat (SHRSP) is a genetic model for cerebral stroke. Although a recent study on a congenic SHRSP suggested that a nonsense mutation in stromal interaction molecule 1 ( Stim1 ) encoding a major component of store-operated Ca 2+ entry was a causal variant for stroke in SHRSP, this was not conclusive because the congenic region including Stim1 in that rat was too wide. On the other hand, we demonstrated that the Wistar-Kyoto (WKY)-derived congenic fragment adjacent to Stim1 exacerbated stroke susceptibility in a congenic SHRSP called SPwch1.71. In the present study, we directly examined the effects of the Stim1 genotype on stroke susceptibility using SHRSP in which wild-type Stim1 was knocked in (called Stim1 -KI SHRSP). The combined effects of Stim1 and the congenic fragment of SPwch1.71 were also investigated. METHODS: Stroke susceptibility was assessed by the stroke symptom-free and survival periods based on observations of behavioral symptoms and reductions in body weight. RESULTS: Stim1 -KI SHRSP was more resistant to, while SPwch1.71 was more susceptible to stroke than the original SHRSP. Introgression of the wild-type Stim1 of Stim1 -KI SHRSP into SPwch1.71 by the generation of F1 rats ameliorated stroke susceptibility in SPwch1.71. Gene expression, whole-genome sequencing, and biochemical analyses identified Art2b , Folr1 , and Pde2a as possible candidate genes accelerating stroke in SPwch1.71. CONCLUSION: The substitution of SHRSP-type Stim1 to wild-type Stim1 ameliorated stroke susceptibility in both SHRSP and SPwch1.71, indicating that the nonsense mutation in Stim1 is causally related to stroke susceptibility in SHRSP.

Deciphering the genetic landscape of obesity: a data-driven approach to identifying plausible causal genes and therapeutic targets.

OBJECTIVES: Genome-wide association studies (GWAS) have successfully revealed numerous susceptibility loci for obesity. However, identifying the causal genes, pathways, and tissues/cell types responsible for these associations remains a challenge, and standardized analysis workflows are lacking. Additionally, due to limited treatment options for obesity, there is a need for the development of new pharmacological therapies. This study aimed to address these issues by performing step-wise utilization of knowledgebase for gene prioritization and assessing the potential relevance of key obesity genes as therapeutic targets. METHODS AND RESULTS: First, we generated a list of 28,787 obesity-associated SNPs from the publicly available GWAS dataset (approximately 800,000 individuals in the GIANT meta-analysis). Then, we prioritized 1372 genes with significant in silico evidence against genomic and transcriptomic data, including transcriptionally regulated genes in the brain from transcriptome-wide association studies. In further narrowing down the gene list, we selected key genes, which we found to be useful for the discovery of potential drug seeds as demonstrated in lipid GWAS separately. We thus identified 74 key genes for obesity, which are highly interconnected and enriched in several biological processes that contribute to obesity, including energy expenditure and homeostasis. Of 74 key genes, 37 had not been reported for the pathophysiology of obesity. Finally, by drug-gene interaction analysis, we detected 23 (of 74) key genes that are potential targets for 78 approved and marketed drugs. CONCLUSIONS: Our results provide valuable insights into new treatment options for obesity through a data-driven approach that integrates multiple up-to-date knowledgebases.

Gene-regulation modules in nonalcoholic fatty liver disease revealed by single-nucleus ATAC-seq.

We investigated the progression of nonalcoholic fatty liver disease from fatty liver to steatohepatitis using single-nucleus and bulk ATAC-seq on the livers of rats fed a high-fat diet (HFD). Rats fed HFD for 4 wk developed fatty liver, and those fed HFD for 8 wk further progressed to steatohepatitis. We observed an increase in the proportion of inflammatory macrophages, consistent with the pathological progression. Utilizing machine learning, we divided global gene regulation into modules, wherein transcription factors within a module could regulate genes within the same module, reaffirming known regulatory relationships between transcription factors and biological processes. We identified core genes-central to co-expression and protein-protein interaction-for the biological processes discovered. Notably, a large part of the core genes overlapped with genes previously implicated in nonalcoholic fatty liver disease. Single-nucleus ATAC-seq, combined with data-driven statistical analysis, offers insight into in vivo global gene regulation as a combination of modules and assists in identifying core genes of relevant biological processes.

Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. 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 previously unreported. We define eight non-overlapping clusters of T2D signals characterised 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, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.

Double-Stranded RNA Induces Mortality in an MDA5-Mediated Type I Interferonopathy Model.

Gain-of-function mutations in the viral dsRNA sensor melanoma differentiation-associated protein 5 (MDA5) lead to autoimmune IFNopathies, including Singleton-Merten syndrome (SMS) and Aicardi-Goutières syndrome. However, much remains unclear regarding the mechanism of disease progression and how external factors such as infection or immune stimulation with vaccination can affect the immune response. With this aim, we generated mice with human MDA5 bearing the SMS-associated mutation R822Q (hM-R822Q). hM-R822Q transgenic (Tg) mice developed SMS-like heart fibrosis, aortic valve enlargement, and aortic calcification with a systemic IFN-stimulated gene signature resulting in the activation of the adaptive immune response. Although administration of the viral dsRNA mimic polyinosinic-polycytidylic acid [poly(I:C)] did not have remarkable effects on the cardiac phenotype, dramatic inflammation was observed in the intestines where IFN production was most elevated. Poly(I:C)-injected hM-R822Q Tg mice also developed lethal hypercytokinemia marked by massive IL-6 levels in the serum. Interrupting the IFN signaling through mitochondrial antiviral signaling protein or IFN-α/ß receptor alleviated hM-R822Q-induced inflammation. Furthermore, inhibition of JAK signaling with tofacitinib reduced cytokine production and ameliorated mucosal damage, enabling the survival of poly(I:C)-injected hM-R822Q Tg mice. These findings demonstrate that the MDA5 R822Q mutant introduces a critical risk factor for uncontrollable inflammation on viral infection or vaccination.

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

Identification of genetic effects underlying type 2 diabetes in South Asian and European populations.

South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n = 16,677) and controls (n = 33,856), followed by combined analyses with Europeans (neff = 231,420). We identify 21 novel genetic loci for significant association with T2D (P = 4.7 × 10-8 to 5.2 × 10-12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile. Our results provide further insights into the genetic mechanisms underlying T2D, and highlight the opportunities for discovery from joint analysis of data from across ancestral populations.

A polygenic risk score improves risk stratification of coronary artery disease: a large-scale prospective Chinese cohort study.

AIMS: To construct a polygenic risk score (PRS) for coronary artery disease (CAD) and comprehensively evaluate its potential in clinical utility for primary prevention in Chinese populations. METHODS AND RESULTS: Using meta-analytic approach and large genome-wide association results for CAD and CAD-related traits in East Asians, a PRS comprising 540 genetic variants was developed in a training set of 2800 patients with CAD and 2055 controls, and was further assessed for risk stratification for CAD integrating with the guideline-recommended clinical risk score in large prospective cohorts comprising 41 271 individuals. During a mean follow-up of 13.0 years, 1303 incident CAD cases were identified. Individuals with high PRS (the highest 20%) had about three-fold higher risk of CAD than the lowest 20% (hazard ratio 2.91, 95% confidence interval 2.43-3.49), with the lifetime risk of 15.9 and 5.8%, respectively. The addition of PRS to the clinical risk score yielded a modest yet significant improvement in C-statistic (1%) and net reclassification improvement (3.5%). We observed significant gradients in both 10-year and lifetime risk of CAD according to the PRS within each clinical risk strata. Particularly, when integrating high PRS, intermediate clinical risk individuals with uncertain clinical decision for intervention would reach the risk levels (10-year of 4.6 vs. 4.8%, lifetime of 17.9 vs. 16.6%) of high clinical risk individuals with intermediate (20-80%) PRS. CONCLUSION: The PRS could stratify individuals into different trajectories of CAD risk, and further refine risk stratification for CAD within each clinical risk strata, demonstrating a great potential to identify high-risk individuals for targeted intervention in clinical utility.

Clinical Implication of Smoking-Related Aryl-Hydrocarbon Receptor Repressor (AHRR) Hypomethylation in Japanese Adults.

BACKGROUND: Tobacco smoking is a leading preventable cause of morbidity and mortality worldwide; still, the success rate of smoking cessation is low in general. From the viewpoint of public health and clinical care, an objective biomarker of long-term smoking behavior is sought.Methods and Results: This study assessed DNA methylation as a biomarker of smoking in a hospital setting through a combination of molecular approaches including genetic, DNA methylation and mRNA expression analyses. First, in an epigenome-wide association study involving Japanese individuals with chronic cardiovascular disease (n=94), genome-wide significant smoking association was identified at 2 CpG sites on chromosome 5, with the strongest signal at cg05575921 located in intron 3 of the aryl-hydrocarbon receptor repressor (AHRR) gene. Highly significant (P<1×10-27) smoking-cg05575921 association was validated in 2 additional panels (n=339 and n=300). For the relationship of cg05575921 methylation extent with time after smoking cessation and cumulative cigarette consumption among former smokers, smoking-related hypomethylation was found to remain for ≥20 years after smoking cessation and to be affected by multiple factors, such as cis-interaction of genetic variation. There was a significant inverse correlation (P=0.0005) between cg05575921 methylation extent and AHRR mRNA expression. CONCLUSIONS: The present study results support that reversion of AHRR hypomethylation can be a quantifiable biomarker for progress in and observance of smoking cessation, although some methodological points need to be considered.

Transcriptomic Response in the Heart and Kidney to Different Types of Antihypertensive Drug Administration.

Certain classes of antihypertensive drug may exert specific, blood pressure (BP)-independent protective effects on end-organ damages such as left ventricular hypertrophy, although the overall evidence has not been definitive in clinical trials. To unravel antihypertensive drug-induced gene expression changes that are potentially related to the amelioration of end-organ damages, we performed in vivo phenotypic evaluation and transcriptomic analysis on the heart and the kidney, with administration of antihypertensive drugs to two inbred strains (ie, hypertensive and normotensive) of rats. We chose 6 antihypertensive classes: enalapril (angiotensin-converting enzyme inhibitor), candesartan (angiotensin receptor blocker), hydrochlorothiazide (diuretics), amlodipine (calcium-channel blocker), carvedilol (vasodilating ß-blocker), and hydralazine. In the tested rat strains, 4 of 6 drugs, including 2 renin-angiotensin system inhibitors, were effective for BP lowering, whereas the remaining 2 drugs were not. Besides BP lowering, there appeared to be some interdrug heterogeneity in phenotypic changes, such as suppressed body weight gain and body weight-adjusted heart weight reduction. For the transcriptomic response, a considerable number of genes showed prominent mRNA expression changes either in a BP-dependent or BP-independent manner with substantial diversity between the target organs. Noticeable changes of mRNA expression were induced particularly by renin-angiotensin system blockade, for example, for genes in the natriuretic peptide system (Nppb and Corin) in the heart and for those in the renin-angiotensin system/kallikrein-kinin system (Ren and rat Klk1 paralogs) and those related to calcium ion binding (Calb1 and Slc8a1) in the kidney. The research resources constructed here will help corroborate occasionally inconclusive evidence in clinical settings.

Case Report of Left Ventricular Noncompaction Cardiomyopathy Characterized by Undulating Phenotypes in Adult Patients.

Left ventricular noncompaction cardiomyopathy (LVNC) is a heart muscle disorder morphologically characterized by reticulated trabeculations and intertrabecular recesses in the left ventricular (LV) cavity. LVNC is a genetically and phenotypically heterogeneous condition, which has been increasingly recognized with the accumulation of evidence provided by genotype-phenotype correlation analyses. Here, we report 2 sporadic adult cases of LVNC; both developed acute heart failure as an initial clinical manifestation and harbored causal sarcomere gene mutations. One case was a 57-year-old male with digenic heterozygote mutations, p.R1344Q in myosin heavy chain 7 (MYH7) and p.R144W in troponin T2, cardiac type (TNNT2), who showed morphological characteristics of LVNC in the lateral to apical regions of the LV together with a comorbidity of non-transmural myocardial infarction, resulting from a coronary artery stenosis. After the removal of ischemic insult and standard heart failure treatment, LVNC became less clear, and LV function gradually improved. The other case was a 36-year-old male with a heterozygote mutation, p.E334K in myosin binding protein C3 (MYBPC3), who exhibited cardiogenic shock on admission with morphological characteristics of LVNC being most prominent in the apical segment of the LV. The dosage of beta-blocker was deliberately increased in an outpatient clinic over 6 months following hospitalization, which remarkably improved the LV ejection fraction from 21% to 54.3%. Via a combination of imaging and histopathological and genetic tests, we have found that these cases are not compatible with a persistent phenotype of primary cardiomyopathy, but their morphological features are changeable in response to treatment. Thus, we point out phenotypic plasticity or undulation as a noticeable element of LVNC in this case report.

Integrative genomic analysis of blood pressure and related phenotypes in rats.

Despite remarkable progress made in human genome-wide association studies, there remains a substantial gap between statistical evidence for genetic associations and functional comprehension of the underlying mechanisms governing these associations. As a means of bridging this gap, we performed genomic analysis of blood pressure (BP) and related phenotypes in spontaneously hypertensive rats (SHR) and their substrain, stroke-prone SHR (SHRSP), both of which are unique genetic models of severe hypertension and cardiovascular complications. By integrating whole-genome sequencing, transcriptome profiling, genome-wide linkage scans (maximum n=1415), fine congenic mapping (maximum n=8704), pharmacological intervention and comparative analysis with transcriptome-wide association study (TWAS) datasets, we searched causal genes and causal pathways for the tested traits. The overall results validated the polygenic architecture of elevated BP compared with a non-hypertensive control strain, Wistar Kyoto rats (WKY); e.g. inter-strain BP differences between SHRSP and WKY could be largely explained by an aggregate of BP changes in seven SHRSP-derived consomic strains. We identified 26 potential target genes, including rat homologs of human TWAS loci, for the tested traits. In this study, we re-discovered 18 genes that had previously been determined to contribute to hypertension or cardiovascular phenotypes. Notably, five of these genes belong to the kallikrein-kinin/renin-angiotensin systems (KKS/RAS), in which the most prominent differential expression between hypertensive and non-hypertensive alleles could be detected in rat Klk1 paralogs. In combination with a pharmacological intervention, we provide in vivo experimental evidence supporting the presence of key disease pathways, such as KKS/RAS, in a rat polygenic hypertension model.

Venous thromboembolism is caused by prothrombin p.Arg541Trp mutation in Japanese individuals.

Venous thromboembolism (VTE) is a multifactorial disease. Because low-frequency variants and rare mutations have been found to predispose carriers toward VTE, there is a need for variant discovery in clinical settings. Therefore, we used a whole-exome approach for a young VTE patient with a positive family history. We identified in the proband and his affected mother a rare, functional missense variant of prothrombin, p.Arg541Trp, which contributes to the clinical picture of VTE.

Nonlinear ridge regression improves cell-type-specific differential expression analysis.

BACKGROUND: Epigenome-wide association studies (EWAS) and differential gene expression analyses are generally performed on tissue samples, which consist of multiple cell types. Cell-type-specific effects of a trait, such as disease, on the omics expression are of interest but difficult or costly to measure experimentally. By measuring omics data for the bulk tissue, cell type composition of a sample can be inferred statistically. Subsequently, cell-type-specific effects are estimated by linear regression that includes terms representing the interaction between the cell type proportions and the trait. This approach involves two issues, scaling and multicollinearity. RESULTS: First, although cell composition is analyzed in linear scale, differential methylation/expression is analyzed suitably in the logit/log scale. To simultaneously analyze two scales, we applied nonlinear regression. Second, we show that the interaction terms are highly collinear, which is obstructive to ordinary regression. To cope with the multicollinearity, we applied ridge regularization. In simulated data, nonlinear ridge regression attained well-balanced sensitivity, specificity and precision. Marginal model attained the lowest precision and highest sensitivity and was the only algorithm to detect weak signal in real data. CONCLUSION: Nonlinear ridge regression performed cell-type-specific association test on bulk omics data with well-balanced performance. The omicwas package for R implements nonlinear ridge regression for cell-type-specific EWAS, differential gene expression and QTL analyses. The software is freely available from https://github.com/fumi-github/omicwas.

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.