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Importance: Aortic stenosis (AS) and coronary artery disease (CAD) frequently coexist. However, it is unknown which genetic and cardiovascular risk factors might be AS-specific and which could be shared between AS and CAD., Objective: To identify genetic risk loci and cardiovascular risk factors with AS-specific associations., Design, Setting, and Participants: This was a genomewide association study (GWAS) of AS adjusted for CAD with participants from the European Consortium for the Genetics of Aortic Stenosis (EGAS) (recruited 2000-2020), UK Biobank (recruited 2006-2010), Estonian Biobank (recruited 1997-2019), and FinnGen (recruited 1964-2019). EGAS participants were collected from 7 sites across Europe. All participants were of European ancestry, and information on comorbid CAD was available for all participants. Follow-up analyses with GWAS data on cardiovascular traits and tissue transcriptome data were also performed. Data were analyzed from October 2022 to July 2023., Exposures: Genetic variants., Main Outcomes and Measures: Cardiovascular traits associated with AS adjusted for CAD. Replication was performed in 2 independent AS GWAS cohorts., Results: A total of 18 792 participants with AS and 434 249 control participants were included in this GWAS adjusted for CAD. The analysis found 17 AS risk loci, including 5 loci with novel and independently replicated associations (RNF114A, AFAP1, PDGFRA, ADAMTS7, HAO1). Of all 17 associated loci, 11 were associated with risk specifically for AS and were not associated with CAD (ALPL, PALMD, PRRX1, RNF144A, MECOM, AFAP1, PDGFRA, IL6, TPCN2, NLRP6, HAO1). Concordantly, this study revealed only a moderate genetic correlation of 0.15 (SE, 0.05) between AS and CAD (P = 1.60 × 10-3). Mendelian randomization revealed that serum phosphate was an AS-specific risk factor that was absent in CAD (AS: odds ratio [OR], 1.20; 95% CI, 1.11-1.31; P = 1.27 × 10-5; CAD: OR, 0.97; 95% CI 0.94-1.00; P = .04). Mendelian randomization also found that blood pressure, body mass index, and cholesterol metabolism had substantially lesser associations with AS compared with CAD. Pathway and transcriptome enrichment analyses revealed biological processes and tissues relevant for AS development., Conclusions and Relevance: This GWAS adjusted for CAD found a distinct genetic risk profile for AS at the single-marker and polygenic level. These findings provide new targets for future AS research.

Background: Genomic instability and evading apoptosis are two fundamental hallmarks of cancer and closely linked to DNA damage response (DDR). By analyzing expression quantitative trait loci (eQTL) upon cell stimulation (called exposure eQTL (e 2 QTL)) it is possible to identify context specific gene regulatory variants and connect them to oncological diseases based on genome-wide association studies (GWAS)., Results: We isolate CD8 + T cells from 461 healthy donors and stimulate them with high doses of 5 different carcinogens to identify regulatory mechanisms of DNA damage-induced apoptosis. Across all stimuli, we find 5,373 genes to be differentially expressed, with 85% to 99% of these genes being suppressed. While upregulated genes are specific to distinct stimuli, downregulated genes are shared across conditions but exhibit enrichment in biological processes depending on the DNA damage type. Analysis of eQTL reveals 654 regulated genes across conditions. Among them, 47 genes are significant e 2 QTL, representing a fraction of 4% to 5% per stimulus. To unveil disease relevant genetic variants, we compare eQTL and e 2 QTL with GWAS risk variants. We identify gene regulatory variants for KLF2, PIP4K2A, GPR160, RPS18, ARL17B and XBP1 that represent risk variants for oncological diseases., Conclusion: Our study highlights the relevance of gene regulatory variants influencing DNA damage-induced apoptosis in cancer. The results provide new insights in cellular mechanisms and corresponding genes contributing to inter-individual effects in cancer development., Competing Interests: Declarations. Ethics approval and consent to participate: The study was approved by the ethics committee of the University of Marburg and complied with the Helsinki Declaration. All participants gave written informed consent. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Tissue-specific gene expression and gene regulation lead to a better understanding of tissue-specific physiology and pathophysiology. We analyzed the transcriptome and genetic regulatory profiles of two distinct gastric sites, corpus and antrum, to identify tissue-specific gene expression and its regulation. Gastric corpus and antrum mucosa biopsies were collected during routine gastroscopies from up to 431 healthy individuals. We obtained genotype and transcriptome data and performed transcriptome profiling and expression quantitative trait locus (eQTL) studies. We further used data from genome-wide association studies (GWAS) of various diseases and traits to partition their heritability and to perform transcriptome-wide association studies (TWAS). The transcriptome data from corpus and antral mucosa highlights the heterogeneity of gene expression in the stomach. We identified enriched pathways revealing distinct and common physiological processes in gastric corpus and antrum. Furthermore, we found an enrichment of the single nucleotide polymorphism (SNP)-based heritability of metabolic, obesity-related, and cardiovascular traits and diseases by considering corpus- and antrum-specifically expressed genes. Particularly, we could prioritize gastric-specific candidate genes for multiple metabolic traits, like NQO1 which is involved in glucose metabolism, MUC1 which contributes to purine and protein metabolism or RAB27B being a regulator of weight and body composition. Our findings show that gastric corpus and antrum vary in their transcriptome and genetic regulatory profiles indicating physiological differences which are mostly related to digestion and epithelial protection. Moreover, our findings demonstrate that the genetic regulation of the gastric transcriptome is linked to biological mechanisms associated with metabolic, obesity-related, and cardiovascular traits and diseases. NEW & NOTEWORTHY We analyzed the transcriptomes and genetic regulatory profiles of gastric corpus and for the first time also of antrum mucosa in 431 healthy individuals. Through tissue-specific gene expression and eQTL analyses, we uncovered unique and common physiological processes across both primary gastric sites. Notably, our findings reveal that stomach-specific eQTLs are enriched in loci associated with metabolic traits and diseases, highlighting the pivotal role of gene expression regulation in gastric physiology and potential pathophysiology.

Aims: The present study aims to characterize the genetic risk architecture of bicuspid aortic valve (BAV) disease, the most common congenital heart defect., Methods and Results: We carried out a genome-wide association study (GWAS) including 2236 BAV patients and 11 604 controls. This led to the identification of a new risk locus for BAV on chromosome 3q29. The single nucleotide polymorphism rs2550262 was genome-wide significant BAV associated (P = 3.49 × 10-08) and was replicated in an independent case-control sample. The risk locus encodes a deleterious missense variant in MUC4 (p.Ala4821Ser), a gene that is involved in epithelial-to-mesenchymal transformation. Mechanistical studies in zebrafish revealed that loss of Muc4 led to a delay in cardiac valvular development suggesting that loss of MUC4 may also play a role in aortic valve malformation. The GWAS also confirmed previously reported BAV risk loci at PALMD (P = 3.97 × 10-16), GATA4 (P = 1.61 × 10-09), and TEX41 (P = 7.68 × 10-04). In addition, the genetic BAV architecture was examined beyond the single-marker level revealing that a substantial fraction of BAV heritability is polygenic and ∼20% of the observed heritability can be explained by our GWAS data. Furthermore, we used the largest human single-cell atlas for foetal gene expression and show that the transcriptome profile in endothelial cells is a major source contributing to BAV pathology., Conclusion: Our study provides a deeper understanding of the genetic risk architecture of BAV formation on the single marker and polygenic level., Competing Interests: Conflict of interest: None declared., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)