Genome-wide Association Studies Signals Research Articles

Lack of evidence for GWAS signals of exfoliation glaucoma working via monogenic loss-of-function mutation in the nearest gene.

Exfoliation syndrome (XFS) is a systemic disease of elastin-rich tissues involving a deposition of fibrillar exfoliative material (XFM) in the anterior chamber of the eye, which can promote glaucoma. The purpose of this study was to create mice with CRISPR/Cas9-induced variations in candidate genes identified from human genome-wide association studies (GWAS) and screen them for indices of XFS. Variants predicted to be deleterious were sought in the Agpat1, Cacna1a, Loxl1, Pomp, Rbms3, Sema6a, and Tlcd5 genes of C57BL/6J mice using CRISPR/Cas9-based gene editing. Strains were phenotyped by slit-lamp, SD-OCT imaging, and fundus exams at 1-5 mos of age. Smaller cohorts of 12-mos-old mice were also studied. Deleterious variants were identified in six targets; Pomp was recalcitrant to targeting. Multiple alleles of some targets were isolated, yielding 12 strains. Across all genotypes and ages, 277 mice were assessed by 902 slit-lamp exams, 928 SD-OCT exams, and 358 fundus exams. Homozygosity for Agpat1 or Cacna1a mutations led to early lethality; homozygosity for Loxl1 mutations led to pelvic organ prolapse, preventing aging. Loxl1 homozygotes exhibited a conjunctival phenotype of potential relevance to XFS. Multiple other genotype-specific phenotypes were variously identified. XFM was not observed in any mice. This study did not detect XFM in any of the strains. This may have been due to species-specific differences, background dependence, or insufficient aging. Alternatively, it is possible that the current candidates, selected based on proximity to GWAS signals, are not effectors acting via monogenic loss-of-function mechanisms.

Cis-eQTLs in seven duck tissues identify novel candidate genes for growth and carcass traits

BackgroundExpression quantitative trait loci (eQTL) studies aim to understand the influence of genetic variants on gene expression. The colocalization of eQTL mapping and GWAS strategy could help identify essential candidate genes and causal DNA variants vital to complex traits in human and many farm animals. However, eQTL mapping has not been conducted in ducks. It is desirable to know whether eQTLs within GWAS signals contributed to duck economic traits.ResultsIn this study, we conducted an eQTL analysis using publicly available RNA sequencing data from 820 samples, focusing on liver, muscle, blood, adipose, ovary, spleen, and lung tissues. We identified 113,374 cis-eQTLs for 12,266 genes, a substantial fraction 39.1% of which were discovered in at least two tissues. The cis-eQTLs of blood were less conserved across tissues, while cis-eQTLs from any tissue exhibit a strong sharing pattern to liver tissue. Colocalization between cis-eQTLs and genome-wide association studies (GWAS) of 50 traits uncovered new associations between gene expression and potential loci influencing growth and carcass traits. SRSF4, GSS, and IGF2BP1 in liver, NDUFC2 in muscle, ELF3 in adipose, and RUNDC1 in blood could serve as the candidate genes for duck growth and carcass traits.ConclusionsOur findings highlight substantial differences in genetic regulation of gene expression across duck primary tissues, shedding light on potential mechanisms through which candidate genes may impact growth and carcass traits. Furthermore, this availability of eQTL data offers a valuable resource for deciphering further genetic association signals that may arise from ongoing extensive endeavors aimed at enhancing duck production traits.

OA30 Primary osteoarthritis chondrocyte map of chromatin conformation reveals novel effector genes

Abstract Background/Aims Osteoarthritis is a complex disease with a huge public health burden. Genome-wide association studies (GWAS) have identified hundreds of osteoarthritis-associated sequence variants, but the effector genes underpinning these signals remain largely elusive. Understanding chromosome organisation in 3D space is essential for identifying long-range contacts between distant genomic features (e.g., between genes and regulatory elements), in a tissue-specific manner. Here, we generate the first whole genome chromosome conformation analysis (Hi-C) map of primary osteoarthritis chondrocytes and identify novel effector genes for the disease. Methods Primary chondrocytes collected from eight knee osteoarthritis patients underwent Hi-C analysis to link chromosomal structure to genomic sequence. The identified loops were then combined with osteoarthritis GWAS results to identify variants involved in gene regulation via enhancer-promoter interactions. Results We identified 36 genetic variants residing within chromatin loop anchors that are associated with 13 osteoarthritis GWAS signals. Five of these variants reside directly in enhancer regions of 3 enhancer-promoter loops newly described in chondrocytes, pointing to high-confidence effector genes: PAPPA, NSD2 and NCOA6. PAPPA is directly associated with the turnover of IGF-1 transport proteins, and IGF-1 is an important factor in the repair of damaged chondrocytes. Conclusion We have constructed the first Hi-C map of primary human chondrocytes and have made it available as a resource for the scientific community. By integrating 3D-genomics with large-scale genetic association data, we identify high-confidence osteoarthritis effector genes which enhance our understanding of disease and can serve as putative high-value novel targets. Disclosure N. Bittner: None. C. Shi: None. D. Zhao: None. J. Ding: None. L. Southam: None. D. Swift: None. P. Kreitmaier: None. M. Tutino: None. J. Hankinson: None. M. Wilkinson: None. G. Orozco: None. E. Zeggini: None.

A Cell Specific Effect of MBOAT7 MAFLD-risk Variant on Immune Cells.

Disease risk variants are likely to affect gene expression in a context- and cell-type specific manner. The membrane bound O-acyltransferase domain containing 7 (MBOAT7) rs8736 metabolic-dysfunction-associated fatty liver disease (MAFLD)-risk variant was recently reported to be a negative regulator of toll-like receptors (TLRs) signalling in macrophages. Whether this effect is generic or cell-type specific in immune cells is unknown. We investigated the impact of modulating TLR signaling on MBOAT7 expression in peripheral blood mononuclear cells (PBMCs). We also examined whether the rs8736 polymorphism in MBOAT7 regulates this effect. Furthermore, we measured the allele-specific expression of MBOAT7 in various immune cell populations under both unstimulated and stimulated conditions. We show that MBOAT7 is down-regulated by TLRs in PBMCs. This effect is modulated by the MBOAT7 rs8736 polymorphism. Additionally, we provide evidence that MBOAT7 acts primarily as a modulator of TLR signalling in mononuclear phagocytes. Our results highlight the importance of studying Genome-Wide Association Studies (GWAS) signals in the specific cell types in which alterations of gene expression are found.

Constructing eRNA-mediated gene regulatory networks to explore the genetic basis of muscle and fat-relevant traits in pigs

BackgroundEnhancer RNAs (eRNAs) play a crucial role in transcriptional regulation. While significant progress has been made in understanding epigenetic regulation mediated by eRNAs, research on the construction of eRNA-mediated gene regulatory networks (eGRN) and the identification of critical network components that influence complex traits is lacking.ResultsHere, employing the pig as a model, we conducted a comprehensive study using H3K27ac histone ChIP-seq and RNA-seq data to construct eRNA expression profiles from multiple tissues of two distinct pig breeds, namely Enshi Black (ES) and Duroc. In addition to revealing the regulatory landscape of eRNAs at the tissue level, we developed an innovative network construction and refinement method by integrating RNA-seq, ChIP-seq, genome-wide association study (GWAS) signals and enhancer-modulating effects of single nucleotide polymorphisms (SNPs) measured by self-transcribing active regulatory region sequencing (STARR-seq) experiments. Using this approach, we unraveled eGRN that significantly influence the growth and development of muscle and fat tissues, and identified several novel genes that affect adipocyte differentiation in a cell line model.ConclusionsOur work not only provides novel insights into the genetic basis of economic pig traits, but also offers a generalizable approach to elucidate the eRNA-mediated transcriptional regulation underlying a wide spectrum of complex traits for diverse organisms.

Bayesian colocalization of GWAS and eQTL signals reveals cell type-specific genes and regulatory variants for susceptibility to subtypes of ischemic stroke

A colocalization analysis of genome-wide association study (GWAS) signals and expression quantitative trait loci (eQTL) was conducted to pinpoint target genes and their regulatory nucleotide variants for subtypes of ischemic stroke. We utilized GWAS data from prominent meta-analysis consortia (MEGASTROKE and GIGASTROKE) and single-cell eQTL data in brain and blood tissues to enhance accuracy and minimize noise inherent in bulk RNA-seq. Employing Bayesian colocalization methods, we identified ten shared loci between GWAS and eQTL signals, targeting five eGenes. Specifically, RAPH1 and ICA1L were discovered for small vessel stroke (SVS), whereas SCYL3, CAV1, and CAV2 were for cardioembolic stroke (CS). However, no findings have been made for large artery stroke. The exploration and subsequent functional analysis of causal variants within the colocalized regions revealed their regulatory roles, particularly as enhancer variants (e.g., rs144505847 and rs72932755 targeting ICA1L; rs629234 targeting SCYL3; rs3807989 targeting CAV1 and CAV2). Notably, our study unveiled that all eQTL for CS were identified in oligodendrocytes, while those for SVS were across excitatory neurons, astrocytes, and oligodendrocyte precursor cells. This underscores the heterogeneous tissue-specific genetic factors by subtypes of ischemic stroke. The study emphasizes the need for intensive research efforts to discover causative genes and variants, unravelling the cell type-specific genetic architecture of ischemic stroke subtypes. This knowledge is crucial for advancing our understanding of the underlying pathophysiology and paving the way for precision neurology applications.

Genome-wide Association Studies of Novel Resilience Traits Identify Important Immune QTL Regions and Candidate Genes in Duroc Pigs

Resilience traits in pig populations allow animals to deal better with infectious disease and suboptimal production environments. The data on daily weight, feed intake and feed behaviors in pigs are collected in test period by automated feeding stations, which facilitate to evaluate the resilience traits. In this study, we adopted the mean square error roots (RMSE) of ordinary least squares (OLS) and the negative residuals of quantile regression (QR) to generate four different novel resilience traits using daily records of feed intake and feed duration between 90 and 180 days of age in a population of commercial Duroc pigs. The genome-wide association studies (GWAS) based on single- and two- trait mixed models were carried out on 550 pigs using 48,603 single nucleotide polymorphisms (SNPs) to identify genomic regions associated with resilience traits in growing pigs. We further focused on the GWAS signals to conduct gene annotation, colocalization with multi-tissue eQTL summary statistics of PigGTEx project and identification of enhancers and promoters using the publicly available data. The genomic heritabilities of four novel resilience traits ranged from 0.09 to 0.41. The pairwise genetic and phenotypic correlations ranged from 0.16 to 0.95 and from 0.05 to 0.36, respectively. Twenty-seven SNPs were identified to be significantly associated with these resilience traits. They were distributed on nine chromosomes (SSC1, SSC2, SSC6, SSC7, SSC8, SSC12, SSC14, SSC16, and SSC17). After annotation, 39 QTLs and 49 candidate genes were identified. Several of these are functionally relevant candidate genes including OTUD4, TIFA and CARD14, which are involved in the host immune response, disease susceptibility and signal transduction. Eight unique SNPs were found to be causal in both GWAS and eQTL analyses across 15 tissues. Notably, one SNP (rs80794541) was associated with eQTLs identified concurrently across seven tissues/cell types, including the macrophage cell type. Furthermore, four significant SNPs (rs81467127, rs81356029, rs80794541, and rs81305085) were linked to the function of the primed enhancer, active element, and poised promoter in five pig tissues. Using the porcine fibroblast HiC dataset, SNP (rs81356029) on SSC2 regulates the CARNS1 and SSH3, while SNP (rs80794541) on SSC7 regulates the H2AC6. In this study, we generated four novel resilience traits and identified SNPs significantly associated with these resilience traits in a Duroc pig population. GWAS signals were associated with candidate genes involving in the immune traits, and were linked to the crucial regulatory elements as well. Our findings will contribute to elucidating the genetic mechanism that can enhance genome-enabled breeding and inform further research on resilience in domestic pigs.

Rome III Criteria Capture Higher Irritable Bowel Syndrome SNP-Heritability and Highlight a Novel Genetic Link with Cardiovascular Traits

Irritable bowel syndrome (IBS) shows genetic predisposition, and large-scale genome-wide association studies (GWAS) are emerging, based on heterogeneous disease definitions. We aimed at investigating the genetic architecture of IBS defined according to gold-standard Rome Criteria. We conducted GWAS meta-analyses of Rome III IBS and its subtypes in 24,735 IBS cases and 77,149 asymptomatic controls from two independent European cohorts (UK Biobank and Lifelines). SNP-based heritability (h2SNP) and genetic correlations (rg) with other traits were calculated. IBS risk loci were functionally annotated to identify candidate genes. Sensitivity and conditional analyses were conducted to assess impact of confounders. Polygenic risk scores (PRS) were computed and tested in independent datasets. Rome III IBS showed significant SNP-heritability (up to 13%) and similar genetic architecture across subtypes, including those with manifestations at the opposite ends of the symptom spectrum (rg=0.48 between IBS-D and IBS-C). Genetic correlations with other traits highlighted commonalities with family history of heart disease and hypertension, coronary artery disease, and angina pectoris (rg=0.20-0.45), among others. Four independent GWAS signals (p<5×10-8) were detected, including two novel loci for IBS (rs2035380) and IBS-Mixed (rs2048419) that had been previously associated with hypertension and coronary artery disease. Functional annotation of GWAS risk loci revealed genes implicated in circadian rhythm (BMAL1), intestinal barrier (CLDN23), immunomodulation (MFHAS1), and the cAMP pathway (ADCY2). PRS allowed the identification of individuals at increased risk of IBS (OR=1.34, p=1.1×10-3). Rome III Criteria capture higher SNP-heritability than previously estimated for IBS. The identified link between IBS and cardiovascular traits may contribute to the delineation of alternative therapeutic strategies, warranting further investigation.

Abstract 7002: RNA m6A modification and lung cancer risk: An epitranscriptome-wide association study

Abstract N6-Methyladenosine (m6A), the most prevalent epitranscriptomic modification in eukaryotic mRNA, determines the fate of target RNAs. Key m6A regulators have been elucidated to be essential for lung cancer cell proliferation. However, the relationship between individual m6A markers and lung cancer risk remains inadequately explored. We conducted an epitranscriptome-wide association study (EpiTWAS) to investigate genetically predicted m6A in association with lung cancer risk. Genetic and m6A data of 30 lung, 12 heart, 28 muscle, and 50 brain tissues from 87 donors predominantly of European ancestry were obtained from Genotype-Tissue Expression (GTEx). For each m6A marker, we built a single-tissue model via elastic net, focusing on lung tissue, and a cross-tissue model through the unified test for molecular signatures (UTMOST) approach, capturing genetic influences on m6A shared by lung and other tissues. SPrediXcan was used to apply these models to data of genome-wide association studies (GWAS) among 38,422 lung cancer cases and 677,930 controls of European descent from International Lung Cancer Consortium (ILCCO), UK Biobank, and FinnGen. For m6A markers significantly associated with lung cancer risk at false discovery rate (FDR)&amp;lt;0.05, we assessed the differential expression of proteins encoded by their target mRNAs in lung cancer versus adjacent normal tissues (200 pairs), using data from Clinical Proteomic Tumor Analysis Consortium (CPTAC). Of the 38,841 high-quality m6A markers in 11,715 genes analyzed, prediction models were built for 6,809 m6A markers in 4,548 genes with performance of R&amp;gt;0.1 (P&amp;lt;0.05), ~85.2% (5,801) of which were single-tissue models. Among these, 28 m6A markers in 26 genes were significantly associated with overall lung cancer risk (FDR&amp;lt;0.05). Notably, 12 (~43%) of these markers in 12 loci are &amp;gt;2 megabases away from any of GWAS-identified lung cancer risk variants. When conditioning on nearby GWAS signals, these 12 associations did not change materially, whereas 15 of the remaining 16 associations lost statistical significance. Analyses by lung cancer histology and smoking status revealed no significant heterogeneity among the 28 associations but identified eight additional m6A markers significantly (FDR&amp;lt;0.05) associated with the risk of adenocarcinoma (n=2), squamous cell carcinoma (n=3), and overall lung cancer among ever- (n=2) or never-smokers (n=1). Of the 33 target RNAs of those 36 m6A markers, 30 encode proteins and 22 of these proteins displayed a significant tumor-normal differential expression at fold change &amp;gt;1.5 and FDR&amp;lt;0.05 in CPTAC lung tissue data. Our study demonstrates the ability of EpiTWAS to decipher GWAS loci and uncover signals potentially missed by GWAS. Our results imply that certain m6A markers may impact lung cancer risk by modulating mRNA translation, underscoring the need for further research to fully unravel the role of m6A in lung cancer etiology. Citation Format: Yaohua Yang, Yaxin Chen, Yawen Qi, Hongmo Liu, Guochong Jia, Jie Ping, Xiao-Ou Shu, Wei Zheng, Weimin Li, Jirong Long, Qiuyin Cai. RNA m6A modification and lung cancer risk: An epitranscriptome-wide association study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7002.

The association of cigarette smoking with DNA methylation and gene expression in human tissue samples

Cigarette smoking adversely affects many aspects of human health, and epigenetic responses to smoking may reflect mechanisms that mediate or defend against these effects. Prior studies of smoking and DNA methylation (DNAm), typically measured in leukocytes, have identified numerous smoking-associated regions (e.g., AHRR). To identify smoking-associated DNAm features in typically inaccessible tissues, we generated array-based DNAm data for 916 tissue samples from the GTEx (Genotype-Tissue Expression) project representing 9 tissue types (lung, colon, ovary, prostate, blood, breast, testis, kidney, and muscle). We identified 6,350 smoking-associated CpGs in lung tissue (n= 212) and 2,735 in colon tissue (n= 210), most not reported previously. For all 7 other tissue types (sample sizes 38-153), no clear associations were observed (false discovery rate 0.05), but some tissues showed enrichment for smoking-associated CpGs reported previously. For 1,646 loci (in lung) and 22 (in colon), smoking was associated with both DNAm and local gene expression. For loci detected in both lung and colon (e.g., AHRR, CYP1B1, CYP1A1), top CpGs often differed between tissues, but similar clusters of hyper- or hypomethylated CpGs were observed, with hypomethylation at regulatory elements corresponding to increased expression. For lung tissue, 17 hallmark gene sets were enriched for smoking-associated CpGs, including xenobiotic- and cancer-related gene sets. At least four smoking-associated regions in lung were impacted by lung methylation quantitative trait loci (QTLs) that co-localize with genome-wide association study (GWAS) signals for lung function (FEV1/FVC), suggesting epigenetic alterations can mediate the effects of smoking on lung health. Our multi-tissue approach has identified smoking-associated regions in disease-relevant tissues, including effects that are shared across tissue types.

Primary osteoarthritis chondrocyte map of chromatin conformation reveals novel candidate effector genes

ObjectivesOsteoarthritis is a complex disease with a huge public health burden. Genome-wide association studies (GWAS) have identified hundreds of osteoarthritis-associated sequence variants, but the effector genes underpinning these signals remain...

Abstract A109: Novel germline genetic variants in pseudogenes associated with overall survival in advanced stage ovarian cancer treated with carboplatin, paclitaxel, and bevacizumab: Results from the ROSiA trial

Abstract A109: Novel germline genetic variants in pseudogenes associated with overall survival in advanced stage ovarian cancer treated with carboplatin, paclitaxel, and bevacizumab: Results from the ROSiA trial

Genetic regulatory effects in response to a high-cholesterol, high-fat diet in baboons

Steady-state expression quantitative trait loci (eQTLs) explain only a fraction of disease-associated loci identified through genome-wide association studies (GWASs), while eQTLs involved in gene-by-environment (GxE) interactions have rarely been characterized in humans due to experimental challenges. Using a baboon model, we found hundreds of eQTLs that emerge in adipose, liver, and muscle after prolonged exposure to high dietary fat and cholesterol. Diet-responsive eQTLs exhibit genomic localization and genic features that are distinct from steady-state eQTLs. Furthermore, the human orthologs associated with diet-responsive eQTLs are enriched for GWAS genes associated with human metabolic traits, suggesting that context-responsive eQTLs with more complex regulatory effects are likely to explain GWAS hits that do not seem to overlap with standard eQTLs. Our results highlight the complexity of genetic regulatory effects and the potential of eQTLs with disease-relevant GxE interactions in enhancing the understanding of GWAS signals for human complex disease using non-human primate models.

Variant to gene mapping for carpal tunnel syndrome risk loci implicates skeletal muscle regulatory elements

Carpal tunnel syndrome (CTS) is a common disorder caused by compression of the median nerve in the wrist, resulting in pain and numbness throughout the hand and forearm. While multiple behavioural and physiological factors influence CTS risk, a growing body of evidence supports a strong genetic contribution. Recent genome-wide association study (GWAS) efforts have reported 53 independent signals associated with CTS. While GWAS can identify genetic loci conferring risk, it does not determine which cell types drive the genetic aetiology of the trait, which variants are "causal" at a given signal, and which effector genes correspond to these non-coding variants. These obstacles limit interpretation of potential disease mechanisms. We analysed CTS GWAS findings in the context of chromatin conformation between gene promoters and accessible chromatin regions across cellular models of bone, skeletal muscle, adipocytes and neurons. We identified proxy variants in high LD with the lead CTS sentinel SNPs residing in promoter connected open chromatin in the skeletal muscle and bone contexts. We detected significant enrichment for heritability in skeletal muscle myotubes, as well as a weaker correlation in human mesenchymal stem cell-derived osteoblasts. In myotubes, our approach implicated 117 genes contacting 60 proxy variants corresponding to 20 of the 53 GWAS signals. In the osteoblast context we implicated 30 genes contacting 24 proxy variants coinciding with 12 signals, of which 19 genes shared. We subsequently prioritized BZW2 as a candidate effector gene in CTS and implicated it as novel gene that perturbs myocyte differentiation invitro. Taken together our results suggest that the CTS genetic component influences the size, integrity, and organization of multiple tissues surrounding the carpal tunnel, in particular muscle and bone, to predispose the nerve to being compressed in this disease setting. This work was supported by NIH Grant UM1 DK126194 (SFAG and WY), R01AG072705 (SFAG & KDH) and the Center for Spatial and Functional Genomics at CHOP (SFAG & ADW). SFAG is supported by the Daniel B. Burke Endowed Chair for Diabetes Research. WY is supported by the Perelman School of Medicine of the University of Pennsylvania.

Disentangling Accelerated Cognitive Decline from the Normal Aging Process and Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach.

The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points. To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach. We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline. We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G > T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neurons and plays a role in controlling cell growth and differentiation. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Our deep learning model effectively extracted relevant neuroimaging features and predicted individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene.

The cells of the sensory epithelium, and not the stria vascularis, are the main cochlear cells related to the genetic pathogenesis of age-related hearing loss

Age-related hearing loss (ARHL) is a major health concern among the elderly population. It is hoped that increasing our understanding of its underlying pathophysiological processes will lead to the development of novel therapies. Recent genome-wide association studies (GWASs) discovered a few dozen genetic variants in association with elevated risk for ARHL. Integrated analysis of GWAS results and transcriptomics data is a powerful approach for elucidating specific cell types that are involved in disease pathogenesis. Intriguingly, recent studies that applied such bioinformatics approaches to ARHL resulted in disagreeing findings as for the key cell types that are most strongly linked to the genetic pathogenesis of ARHL. These conflicting studies pointed either to cochlear sensory epithelial or to stria vascularis cells as the cell types most prominently involved in the genetic basis of ARHL. Seeking to resolve this discrepancy, we integrated the analysis of four ARHL GWAS datasets with four independent inner-ear single-cell RNA-sequencing datasets. Our analysis clearly points to the cochlear sensory epithelial cells as the key cells for the genetic predisposition to ARHL. We also explain the limitation of the bioinformatics analysis performed by previous studies that led to missing the enrichment for ARHL GWAS signal in sensory epithelial cells. Collectively, we show that cochlear epithelial cells, not stria vascularis cells, are the main inner-ear cells related to the genetic pathogenesis of ARHL.

Convergence of coronary artery disease genes onto endothelial cell programs.

Linking variants from genome-wide association studies (GWAS) to underlying mechanisms of disease remains a challenge1-3. For some diseases, a successful strategy has been to look for cases in which multiple GWAS loci contain genes that act in the same biological pathway1-6. However, our knowledge of which genes act in which pathways is incomplete, particularly for cell-type-specific pathways or understudied genes. Here we introduce a method to connect GWAS variants to functions. This method links variants to genes using epigenomics data, links genes to pathways de novo using Perturb-seq and integrates these data to identify convergence of GWAS loci onto pathways. We apply this approach to study the role of endothelial cells in genetic risk for coronary artery disease (CAD), and discover 43 CAD GWAS signals that converge on the cerebral cavernous malformation (CCM) signalling pathway. Two regulators of this pathway, CCM2 and TLNRD1, are each linked to a CAD risk variant, regulate other CAD risk genes and affect atheroprotective processes in endothelial cells. These results suggest a model whereby CAD risk is driven in part by the convergence of causal genes onto a particular transcriptional pathway in endothelial cells. They highlight shared genes between common and rare vascular diseases (CAD and CCM), and identify TLNRD1 as a new, previously uncharacterized member of the CCM signalling pathway. This approach will be widely useful for linking variants to functions for other common polygenic diseases.

PostGWAS: A web server for deciphering the causality post the genome-wide association studies

While genome-wide association studies (GWAS) have unequivocally identified vast disease susceptibility variants, a majority of them are situated in non-coding regions and are in high linkage disequilibrium (LD). To pave the way of translating GWAS signals to clinical drug targets, it is essential to identify the underlying causal variants and further causal genes. To this end, a myriad of post-GWAS methods have been devised, each grounded in distinct principles including fine-mapping, co-localization, and transcriptome-wide association study (TWAS) techniques. Yet, no platform currently exists that seamlessly integrates these diverse post-GWAS methodologies. In this work, we present a user-friendly web server for post-GWAS analysis, that seamlessly integrates 9 distinct methods with 12 models, categorized by fine-mapping, colocalization, and TWAS. The server mainly helps users decipher the causality hindered by complex GWAS signals, including casual variants and casual genes, without the burden of computational skills and complex environment configuration, and provides a convenient platform for post-GWAS analysis, result visualization, facilitating the understanding and interpretation of the genome-wide association studies. The postGWAS server is available at http://g2g.biographml.com/.

The Impact of Inherited Genetic Variation on DNA Methylation in Prostate Cancer and Benign Tissues of African American and European American Men.

American men of African ancestry (AA) have higher prostate cancer incidence and mortality rates compared with American men of European ancestry (EA). Differences in genetic susceptibility mechanisms may contribute to this disparity. To gain insights into the regulatory mechanisms of prostate cancer susceptibility variants, we tested the association between SNPs and DNA methylation (DNAm) at nearby CpG sites across the genome in benign and cancer prostate tissue from 74 AA and 74 EA men. Genome-wide SNP data (from benign tissue) and DNAm were generated using Illumina arrays. Among AA men, we identified 6,298 and 2,641 cis-methylation QTLs (meQTL; FDR of 0.05) in benign and tumor tissue, respectively, with 6,960 and 1,700 detected in EA men. We leveraged genome-wide association study (GWAS) summary statistics to identify previously reported prostate cancer GWAS signals likely to share a common causal variant with a detected meQTL. We identified nine GWAS-meQTL pairs with strong evidence of colocalization (four in EA benign, three in EA tumor, two in AA benign, and three in AA tumor). Among these colocalized GWAS-meQTL pairs, we identified colocalizing expression quantitative trait loci (eQTL) impacting four eGenes with known roles in tumorigenesis. These findings highlight epigenetic regulatory mechanisms by which prostate cancer-risk SNPs can modify local DNAm and/or gene expression in prostate tissue. Overall, our findings showed general consistency in the meQTL landscape of AA and EA men, but meQTLs often differ by tissue type (normal vs. cancer). Ancestry-based linkage disequilibrium differences and lack of AA representation in GWAS decrease statistical power to detect colocalization for some regions.

Liver regulatory mechanisms of noncoding variants at lipid and metabolic trait loci

Genome-wide association studies (GWASs) have identified hundreds of risk loci for liver disease and lipid-related metabolic traits, although identifying their target genes and molecular mechanisms remains challenging. We predicted target genes at GWAS signals by integrating them with molecular quantitative trait loci for liver gene expression (eQTL) and liver chromatin accessibility QTL (caQTL). We predicted specific regulatory caQTL variants at four GWAS signals located near EFHD1, LITAF, ZNF329, and GPR180. Using transcriptional reporter assays, we determined that caQTL variants rs13395911, rs11644920, rs34003091, and rs9556404 exhibit allelic differences in regulatory activity. We also performed a protein binding assay for rs13395911 and found that FOXA2 differentially interacts with the alleles of rs13395911. For variants rs13395911 and rs11644920 in putative enhancer regulatory elements, we used CRISPRi to demonstrate that repression of the enhancers altered the expression of the predicted target and/or nearby genes. Repression of the element at rs13395911 reduced the expression of EFHD1, and repression of the element at rs11644920 reduced the expression of LITAF, SNN, and TXNDC11. Finally, we showed that EFHD1 is a metabolically active gene in HepG2 cells. Together, these results provide key steps to connect genetic variants with cellular mechanisms and help elucidate the causes of liver disease.