Genome-wide Association Studies Loci Research Articles

Abstract 14675: High-Throughput CRISPR Screening Links CAD Loci to Endothelial Cell Programs and Causal Pathways

Introduction: Genome-wide association studies (GWAS) have discovered >300 associations for CAD. Few loci are functionally characterized and may represent new mechanisms of disease. Hypothesis: Can a high-throughput, unbiased transcriptional screen for all candidate GWAS genes identify the causal genes and biological pathways at CAD GWAS loci in endothelial cells (ECs)? Methods: We applied CRISPRi-Perturb-seq to knock down the expression of all genes within 500 Kb of coronary artery disease GWAS loci (2,300 genes in total) and measure their effects on the transcriptome using single-cell RNA-seq. Results: We identified 60 programs of co-expressed genes, which represent core cellular pathways (i.e. ribosome biogenesis) and EC-specific pathways such as flow response and angiogenesis. The EC-specific programs show the greatest contribution to CAD heritability. 6 EC-specific programs have the greatest number of CAD GWAS candidate genes. One of the EC-specific programs had genes regulated by KLF -transcription factors and was enriched for shear-stress response genes. The novel CAD candidate genes in this program included multiple known mediators of the cerebral cavernous malformation (CCM)-signaling complex. 9 known members of the CCM-signaling cascade and several potentially novel mediators of CAD clustered together in the KLF Perturb-seq topic. These included genetic variants in the CCM2 , KLF4 , RAC1 , and HEG1 loci as well as genes will a similar transcriptional profile but no prior connection to the CCM-signaling complex. Conclusions: High-throughput functional analysis of 2,300 genes proximal to CAD GWAS loci prioritized pathways—such as angiogenesis and EC migration—that are regulated by multiple risk SNPs. Our study identifies new genes that likely influence risk for CAD, identifies convergence of CAD genes into certain pathways in endothelial cells, and demonstrates a generalizable strategy to connect disease variants to functions.

Abstract 15063: Liver Gene Regulatory Mechanisms of Variants at Lipid and Cardio Metabolic Trait Loci

Genome-wide association studies (GWAS) have identified hundreds of risk loci for cardiometabolic and lipid-related traits. GWAS loci are enriched in tissue-specific transcriptional regulatory elements that affect target gene expression driving physiological changes. Most GWAS variants are located in non-coding regions, which makes identifying functional variants and target genes challenging. Previously, we identified GWAS signals colocalized with molecular quantitative trait loci for liver gene expression (eQTL) and liver accessible chromatin (caQTL) to predict regulatory variants for lipid and cardiometabolic traits. These caQTLs are rs13395911, rs11644920, rs34003091 and rs9556404 associated with liver enzymes, LDL-cholesterol, and triglycerides. To evaluate the predicted mechanisms, we tested these variants with surrounding regulatory elements for allelic effects on transcriptional reporter activity and for effects on target gene expression in HepG2 cell line. Along with the two previously reported intronic caQTL variants, rs13395911 and rs11644920 , we observed significant (P<0.05) allelic differences in transcriptional activity for rs9556404 and rs34003091, located at the promoters of GPR180 and ZNF329 , respectively. Based on eQTL and HiC data, the predicted genes for intronic enhancers rs13395911 and rs11644920 are EFHD1 and LITAF , respectively. To confirm the target genes for these two variants, we deployed inducible CRISPRi system by stably expressing dCas9 fused to a KRAB-repressor domain in HepG2 and targeting guide RNAs (gRNAs) to the DNA elements that span caQTL variants. For each element, we introduced ≥6 gRNAs into cells via lentiviruses and measured gene expression using qPCR. Compared to pools of non-targeted control gRNAs, preliminary analyses using pools of enhancer-targeting gRNAs surrounding rs13395911 and rs11644920 led to 30.3% lower EFHD1 and 38.6% lower LITAF expression at 7 days post-transduction, respectively. Thus, we identified and validated mechanisms by which DNA variants alter transcriptional activity and identified the target genes for lipid-related GWAS loci. These results suggest that this framework can be scaled up to map thousands of enhancers to genes in their native genomic state.

Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease.

Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Alzheimer's disease (AD). We present a network topology-based deep learning framework to identify disease-associated genes (NETTAG). We leverage non-coding GWAS loci effects on quantitative trait loci, enhancers and CpG islands, promoter regions, open chromatin, and promoter flanking regions under the protein-protein interactome. Via NETTAG, we identified 156 AD-risk genes enriched in druggable targets. Combining network-based prediction and retrospective case-control observations with 10 million individuals, we identified that usage of four drugs (ibuprofen, gemfibrozil, cholecalciferol, and ceftriaxone) is associated with reduced likelihood of AD incidence. Gemfibrozil (an approved lipid regulator) is significantly associated with 43% reduced risk of AD compared with simvastatin using an active-comparator design (95% confidence interval 0.51-0.63, p<0.0001). In summary, NETTAG offers a deep learning methodology that utilizes GWAS and multi-genomic findings to identify pathobiology and drug repurposing in AD.

Discovery of novel eGFR-associated multiple independent signals using a quasi-adaptive method.

A decreased estimated glomerular filtration rate (eGFR) leading to chronic kidney disease is a significant public health problem. Kidney function is a heritable trait, and recent application of genome-wide association studies (GWAS) successfully identified multiple eGFR-associated genetic loci. To increase statistical power for detecting independent associations in GWAS loci, we improved our recently developed quasi-adaptive method estimating SNP-specific alpha levels for the conditional analysis, and applied it to the GWAS meta-analysis results of eGFR among 783,978 European-ancestry individuals. Among known eGFR loci, we revealed 19 new independent association signals that were subsequently replicated in the United Kingdom Biobank (n = 408,608). These associations have remained undetected by conditional analysis using the established conservative genome-wide significance level of 5 × 10-8. Functional characterization of known index SNPs and novel independent signals using colocalization of conditional eGFR association results and gene expression in cis across 51 human tissues identified two potentially causal genes across kidney tissues: TSPAN33 and TFDP2, and three candidate genes across other tissues: SLC22A2, LRP2, and CDKN1C. These colocalizations were not identified in the original GWAS. By applying our improved quasi-adaptive method, we successfully identified additional genetic variants associated with eGFR. Considering these signals in colocalization analyses can increase the precision of revealing potentially functional genes of GWAS loci.

A family of methyl esterases converts methyl salicylate to salicylic acid in ripening tomato fruit.

Methyl salicylate imparts a potent flavor and aroma described as medicinal and wintergreen that is undesirable in tomato (Solanum lycopersicum) fruit. Plants control the quantities of methyl salicylate through a variety of biosynthetic pathways, including the methylation of salicylic acid to form methyl salicylate and subsequent glycosylation to prevent methyl salicylate emission. Here, we identified a subclade of tomato methyl esterases, SALICYLIC ACID METHYL ESTERASE1-4, responsible for demethylation of methyl salicylate to form salicylic acid in fruits. This family was identified by proximity to a highly significant methyl salicylate genome-wide association study locus on chromosome 2. Genetic mapping studies in a biparental population confirmed a major methyl salicylate locus on chromosome 2. Fruits from SlMES1 knockout lines emitted significantly (P < 0,05, t test) higher amounts of methyl salicylate than wild-type fruits. Double and triple mutants of SlMES2, SlMES3, and SlMES4 emitted even more methyl salicylate than SlMES1 single knockouts-but not at statistically distinguishable levels-compared to the single mutant. Heterologously expressed SlMES1 and SlMES3 acted on methyl salicylate in vitro, with SlMES1 having a higher affinity for methyl salicylate than SlMES3. The SlMES locus has undergone major rearrangement, as demonstrated by genome structure analysis in the parents of the biparental population. Analysis of accessions that produce high or low levels of methyl salicylate showed that SlMES1 and SlMES3 genes expressed the highest in the low methyl salicylate lines. None of the MES genes were appreciably expressed in the high methyl salicylate-producing lines. We concluded that the SlMES gene family encodes tomato methyl esterases that convert methyl salicylate to salicylic acid in ripe tomato fruit. Their ability to decrease methyl salicylate levels by conversion to salicylic acid is an attractive breeding target to lower the level of a negative contributor to flavor.

A gene regulatory network approach harmonizes genetic and epigenetic signals and reveals repurposable drug candidates for multiple sclerosis.

Multiple sclerosis (MS) is a complex dysimmune disorder of the central nervous system. Genome-wide association studies (GWAS) have identified 233 genetic variations associated with MS at the genome-wide significant level. Epigenetic studies have pinpointed differentially methylated CpG sites in MS patients. However, the interplay between genetic risk factors and epigenetic regulation remains elusive. Here, we employed a network model to integrate GWAS summary statistics of 14 802 MS cases and 26 703 controls with DNA methylation profiles from 140 MS cases and 139 controls and the human interactome. We identified differentially methylated genes by aggregating additive effects of differentially methylated CpG sites within promoter regions. We reconstructed a gene regulatory network (GRN) using literature-curated transcription factor knowledge. Colocalization of the MS GWAS and methylation quantitative trait loci (mQTL) was performed to assess the GRN. The resultant MS-associated GRN highlighted several single nucleotide polymorphisms with GWAS-mQTL colocalization: rs6032663, rs6065926 and rs2024568 of CD40 locus, rs9913597 of STAT3 locus, and rs887864 and rs741175 of CIITA locus. Moreover, synergistic mQTL and expression QTL signals were identified in CD40, suggesting gene expression alteration was likely induced by epigenetic changes. Web-based Cell-type Specific Enrichment Analysis of Genes (WebCSEA) indicated that the GRN was enriched in T follicular helper cells (P-value = 0.0016). Drug target enrichment analysis of annotations from the Therapeutic Target Database revealed the GRN was also enriched with drug target genes (P-value = 3.89 × 10-4), revealing repurposable candidates for MS treatment. These candidates included vorinostat (HDAC1 inhibitor) and sivelestat (ELANE inhibitor), which warrant further investigation.

RNA Modification-Related Genetic Variants in Genomic Loci Associated with Bone Mineral Density and Fracture.

Genome-wide association studies (GWASs) have identified more than 500 loci for bone mineral density (BMD), but functional variants in these loci are less known. The aim of this study was to identify RNA modification-related SNPs (RNAm-SNPs) for BMD in GWAS loci. We evaluated the association of RNAm-SNPs with quantitative heel ultrasound BMD (eBMD) in 426,824 individuals, femoral neck (FN) and lumbar spine (LS) BMD in 32,961 individuals and fracture in ~1.2 million individuals. Furthermore, we performed functional enrichment, QTL and Mendelian randomization analyses to support the functionality of the identified RNAm-SNPs. We found 300 RNAm-SNPs significantly associated with BMD, including 249 m6A-, 28 m1A-, 3 m5C-, 7 m7G- and 13 A-to-I-related SNPs. m6A-SNPs in OP susceptibility genes, such as WNT4, WLS, SPTBN1, SEM1, FUBP3, LRP5 and JAG1, were identified and functional enrichment for m6A-SNPs in the eBMD GWAS dataset was detected. eQTL signals were found for nearly half of the identified RNAm-SNPs, and the affected gene expression was associated with BMD and fracture. The RNAm-SNPs were also associated with the plasma levels of proteins in cytokine-cytokine receptor interaction, PI3K-Akt signaling, NF-kappa B signaling and MAPK signaling pathways. Moreover, the plasma levels of proteins (CCL19, COL1A1, CTSB, EFNA5, IL19, INSR, KDR, LIFR, MET and PLXNB2) in these pathways were found to be associated with eBMD in Mendelian randomization analysis. This study identified functional variants and potential causal genes for BMD and fracture in GWAS loci and suggested that RNA modification may play an important role in osteoporosis.

Systematic analysis of the effects of genetic variants on chromatin accessibility to decipher functional variants in non-coding regions.

Genome-wide association study (GWAS) has identified thousands of single nucleotide polymorphisms (SNPs) associated with complex diseases and traits. However, deciphering the functions of these SNPs still faces challenges. Recent studies have shown that SNPs could alter chromatin accessibility and result in differences in tumor susceptibility between individuals. Therefore, systematically analyzing the effects of SNPs on chromatin accessibility could help decipher the functions of SNPs, especially those in non-coding regions. Using data from The Cancer Genome Atlas (TCGA), chromatin accessibility quantitative trait locus (caQTL) analysis was conducted to estimate the associations between genetic variants and chromatin accessibility. We analyzed caQTLs in 23 human cancer types and identified 9,478 caQTLs in breast carcinoma (BRCA). In BRCA, these caQTLs tend to alter the binding affinity of transcription factors, and open chromatin regions regulated by these caQTLs are enriched in regulatory elements. By integrating with eQTL data, we identified 141 caQTLs showing a strong signal for colocalization with eQTLs. We also identified 173 caQTLs in genome-wide association studies (GWAS) loci and inferred several possible target genes of these caQTLs. By performing survival analysis, we found that ~10% caQTLs potentially influence the prognosis of patients. To facilitate access to relevant data, we developed a user-friendly data portal, BCaQTL (http://gong_lab.hzau.edu.cn/caqtl_database), for data searching and downloading. Our work may facilitate fine-map regulatory mechanisms underlying risk loci of cancer and discover the biomarkers or therapeutic targets for cancer prognosis. The BCaQTL database will be an important resource for genetic and epigenetic studies.

Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors.

Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources. We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations. In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis. Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.

Aortic Cellular Diversity and Quantitative Genome-Wide Association Study Trait Prioritization Through Single-Nuclear RNA Sequencing of the Aneurysmal Human Aorta.

Mural cells in ascending aortic aneurysms undergo phenotypic changes that promote extracellular matrix destruction and structural weakening. To explore this biology, we analyzed the transcriptional features of thoracic aortic tissue. Single-nuclear RNA sequencing was performed on 13 samples from human donors, 6 with thoracic aortic aneurysm, and 7 without aneurysm. Individual transcriptomes were then clustered based on transcriptional profiles. Clusters were used for between-disease differential gene expression analyses, subcluster analysis, and analyzed for intersection with genetic aortic trait data. We sequenced 71 689 nuclei from human thoracic aortas and identified 14 clusters, aligning with 11 cell types, predominantly vascular smooth muscle cells (VSMCs) consistent with aortic histology. With unbiased methodology, we found 7 vascular smooth muscle cell and 6 fibroblast subclusters. Differentially expressed genes analysis revealed a vascular smooth muscle cell group accounting for the majority of differential gene expression. Fibroblast populations in aneurysm exhibit distinct behavior with almost complete disappearance of quiescent fibroblasts. Differentially expressed genes were used to prioritize genes at aortic diameter and distensibility genome-wide association study loci highlighting the genes JUN, LTBP4 (latent transforming growth factor beta-binding protein 1), and IL34 (interleukin 34) in fibroblasts, ENTPD1, PDLIM5 (PDZ and LIM domain 5), ACTN4 (alpha-actinin-4), and GLRX in vascular smooth muscle cells, as well as LRP1 in macrophage populations. Using nuclear RNA sequencing, we describe the cellular diversity of healthy and aneurysmal human ascending aorta. Sporadic aortic aneurysm is characterized by differential gene expression within known cellular classes rather than by the appearance of novel cellular forms. Single-nuclear RNA sequencing of aortic tissue can be used to prioritize genes at aortic trait loci.

Pancan-MNVQTLdb: systematic identification of multi-nucleotide variantquantitative trait loci in 33 cancer types.

Multi-nucleotide variants (MNVs) are defined as clusters of two or more nearby variants existing on the same haplotype in an individual. Recent studies have identified millions of MNVs in human populations, but their functions remain largely unknown. Numerous studies have demonstrated that single-nucleotide variants could serve as quantitative trait loci (QTLs) by affecting molecular phenotypes. Therefore, we propose that MNVs can also affect molecular phenotypes by influencing regulatory elements. Using the genotype data from The Cancer Genome Atlas (TCGA), we first identified 223759 unique MNVs in 33 cancer types. Then, to decipher the functions of these MNVs, we investigated the associations between MNVs and six molecular phenotypes, including coding gene expression, miRNA expression, lncRNA expression, alternative splicing, DNA methylation and alternative polyadenylation. As a result, we identified 1397821 cis-MNVQTLs and 402381 trans-MNVQTLs. We further performed survival analysis and identified 46173 MNVQTLs associated with patient overall survival. We also linked the MNVQTLs to genome-wide association studies (GWAS) data and identified 119762 MNVQTLs that overlap with existing GWAS loci. Finally, we developed Pancan-MNVQTLdb (http://gong_lab.hzau.edu.cn/mnvQTLdb/) for data retrieval and download. Pancan-MNVQTLdb will help decipher the functions of MNVs in different cancer types and be an important resource for genetic and cancer research.

Large-scale sequencing identifies multiple genes and rare variants associated with Crohn's disease susceptibility.

Genome-wide association studies (GWASs) have identified hundreds of loci associated with Crohn's disease (CD). However, as with all complex diseases, robust identification of the genes dysregulated by noncoding variants typically driving GWAS discoveries has been challenging. Here, to complement GWASs and better define actionable biological targets, we analyzed sequence data from more than 30,000 patients with CD and 80,000 population controls. We directly implicate ten genes in general onset CD for the first time to our knowledge via association to coding variation, four of which lie within established CD GWAS loci. In nine instances, a single coding variant is significantly associated, and in the tenth, ATG4C, we see additionally a significantly increased burden of very rare coding variants in CD cases. In addition to reiterating the central role of innate and adaptive immune cells as well as autophagy in CD pathogenesis, these newly associated genes highlight the emerging role of mesenchymal cells in the development and maintenance of intestinal inflammation.

Splicing QTL analysis focusing on coding sequences reveals mechanisms for disease susceptibility loci

Splicing quantitative trait loci (sQTLs) are one of the major causal mechanisms in genome-wide association study (GWAS) loci, but their role in disease pathogenesis is poorly understood. One reason is the complexity of alternative splicing events producing many unknown isoforms. Here, we propose two approaches, namely integration and selection, for this complexity by focusing on protein-structure of isoforms. First, we integrate isoforms with the same coding sequence (CDS) and identify 369-601 integrated-isoform ratio QTLs (i2-rQTLs), which altered protein-structure, in six immune subsets. Second, we select CDS incomplete isoforms annotated in GENCODE and identify 175-337 isoform-ratio QTL (i-rQTL). By comprehensive long-read capture RNA-sequencing among these incomplete isoforms, we reveal 29 full-length isoforms with unannotated CDSs associated with GWAS traits. Furthermore, we show that disease-causal sQTL genes can be identified by evaluating their trans-eQTL effects. Our approaches highlight the understudied role of protein-altering sQTLs and are broadly applicable to other tissues and diseases.

DNA methylation analysis of normal colon organoids from familial adenomatous polyposis patients reveals novel insight into colon cancer development

BackgroundFamilial adenomatous polyposis (FAP) is an inherited colorectal cancer (CRC) syndrome resulting from germ line mutations in the adenomatous polyposis coli (APC) gene. While FAP accounts for less than 1% of all CRC cases, loss of APC expression is seen in > 80% of non-hereditary CRCs. To better understand molecular mechanisms underlying APC-driven CRC, we performed an epigenome-wide analysis of colon organoids derived from normal-appearing colons of FAP patients versus healthy subjects to identify differentially methylated regions (DMRs) that may precede the onset of CRC.ResultsWe identified 358 DMRs when comparing colon organoids of FAP patients to those of healthy subjects (FDR < 0.05, |mean beta difference| = 5%). Of these, nearly 50% of DMRs were also differentially methylated in at least one of three CRC tumor and normal adjacent tissue (NAT) cohorts (TCGA-COAD, GSE193535 and ColoCare). Moreover, 27 of the DMRs mapped to CRC genome-wide association study (GWAS) loci. We provide evidence suggesting that some of these DMRs led to significant differences in gene expression of adjacent genes using quantitative PCR. For example, we identified significantly greater expression of five genes: Kazal-type serine peptidase inhibitor domain 1 (KAZALD1, P = 0.032), F-Box and leucine-rich repeat protein 8 (FBXL8, P = 0.036), TRIM31 antisense RNA 1 (TRIM31-AS1, P = 0.036), Fas apoptotic inhibitory molecule 2 (FAIM2, P = 0.049) and (Collagen beta (1–0)galactosyltransferase 2 (COLGALT2, P = 0.049). Importantly, both FBXL8 and TRIM31-AS1 were also significantly differentially expressed in TCGA-COAD tumor versus matched NAT, supporting a role for these genes in CRC tumor development.ConclusionsWe performed the first DNA methylome-wide analysis of normal colon organoids derived from FAP patients compared to those of healthy subjects. Our results reveal that normal colon organoids from FAP patients exhibit extensive epigenetic differences compared to those of healthy subjects that appear similar to those exhibited in CRC tumor. Our analyses therefore identify DMRs and candidate target genes that are potentially important in CRC tumor development in FAP, with potential implications for non-hereditary CRC.

Pan-Cancer Analysis of Microbiome Quantitative Trait Loci.

This study provides insights into the host-microbiome interactions for multiple cancer types, which could help the research community understand the effects of inherited variants in tumorigenesis and development.

Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders.

To date, most expression quantitative trait loci (eQTL) studies, which investigate how genetic variants contribute to gene expression, have been performed in heterogeneous brain tissues rather than specific cell types. In this study, we performed an eQTL analysis using single-nuclei RNA sequencing from 192 individuals in eight brain cell types derived from the prefrontal cortex, temporal cortex and white matter. We identified 7,607 eGenes, a substantial fraction (46%, 3,537/7,607) of which show cell-type-specific effects, with strongest effects in microglia. Cell-type-level eQTLs affected more constrained genes and had larger effect sizes than tissue-level eQTLs. Integration of brain cell type eQTLs with genome-wide association studies (GWAS) revealed novel relationships between expression and disease risk for neuropsychiatric and neurodegenerative diseases. For most GWAS loci, a single gene co-localized in a single cell type, providing new clues into disease etiology. Our findings demonstrate substantial contrast in genetic regulation of gene expression among brain cell types and reveal potential mechanisms by which disease risk genes influence brain disorders.

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

GWAS meta-analysis of 16 790 patients with Barrett’s oesophagus and oesophageal adenocarcinoma identifies 16 novel genetic risk loci and provides insights into disease aetiology beyond the single marker level

ObjectiveOesophageal cancer (EC) is the sixth leading cause of cancer-related deaths. Oesophageal adenocarcinoma (EA), with Barrett’s oesophagus (BE) as a precursor lesion, is the most prevalent EC subtype in the...

A Multitrait Locus Regulates Sarbecovirus Pathogenesis.

ABSTRACTInfectious diseases have shaped the human population genetic structure, and genetic variation influences the susceptibility to many viral diseases. However, a variety of challenges have made the implementation of traditional human Genome-wide Association Studies (GWAS) approaches to study these infectious outcomes challenging. In contrast, mouse models of infectious diseases provide an experimental control and precision, which facilitates analyses and mechanistic studies of the role of genetic variation on infection. Here we use a genetic mapping cross between two distinct Collaborative Cross mouse strains with respect to severe acute respiratory syndrome coronavirus (SARS-CoV) disease outcomes. We find several loci control differential disease outcome for a variety of traits in the context of SARS-CoV infection. Importantly, we identify a locus on mouse chromosome 9 that shows conserved synteny with a human GWAS locus for SARS-CoV-2 severe disease. We follow-up and confirm a role for this locus, and identify two candidate genes, CCR9 and CXCR6, that both play a key role in regulating the severity of SARS-CoV, SARS-CoV-2, and a distantly related bat sarbecovirus disease outcomes. As such we provide a template for using experimental mouse crosses to identify and characterize multitrait loci that regulate pathogenic infectious outcomes across species.

HOTAIR interacts with PRC2 complex regulating the regional preadipocyte transcriptome and human fat distribution.

Mechanisms governing regional human adipose tissue (AT) development remain undefined. Here, we show that the long non-coding RNA HOTAIR (HOX transcript antisense RNA) is exclusively expressed in gluteofemoral AT, where it is essential for adipocyte development. We find that HOTAIR interacts with polycomb repressive complex 2 (PRC2) and we identify core HOTAIR-PRC2 target genes involved in adipocyte lineage determination. Repression of target genes coincides with PRC2 promoter occupancy and H3K27 trimethylation. HOTAIR is also involved in modifying the gluteal adipocyte transcriptome through alternative splicing. Gluteal-specific expression of HOTAIR is maintained by defined regions of open chromatin across the HOTAIR promoter. HOTAIR expression levels can be modified by hormonal (estrogen, glucocorticoids) and genetic variation (rs1443512 is a HOTAIR eQTL associated with reduced gynoid fat mass). These data identify HOTAIR as a dynamic regulator of the gluteal adipocyte transcriptome and epigenome with functional importance for human regional AT development.