Distinct genetic risk profile in aortic stenosis compared to coronary artery disease

, , , Teresa Trenkwalder (Lead / Corresponding author), Carlo Maj, Baravan Al-Kassou, Radoslaw Debiec, Stefanie A. Doppler, Muntaser D. Musameh, Christopher P. Nelson, Pouria Dasmeh, Sandeep Grover, Katharina Knoll, Joonas Naamanka, Ify Mordi, Peter S. Braund, Martina Dreßen, Harald Lahm, Felix Wirth, Stephan BaldusMalte Kelm, Moritz von Scheidt, Johannes Krefting, David Ellinghaus, Aeron M. Small, Gina M. Peloso, Pradeep Natarajan, George Thanassoulis, James C. Engert, Line Dufresne, Andre Franke, Siegfried Görg, Matthias Laudes, Ulrike Nowak-Göttl, Mariliis Vaht, Andres Metspalu, Monika Stoll, Klaus Berger, Costanza Pellegrini, Adnan Kastrati, Christian Hengstenberg, Chim Lang, Thorsten Kessler, Iiris Hovatta, Georg Nickenig, Markus M. Nothen, Markus Krane, Heribert Schunkert, Nilesh J. Samani, Johannes Schumacher, Mart Kals, Anu Reigo, Maris Teder-Laving, Jan Gehlen, Thomas R. Webb, Ann-Sophie Giel, Laura L Koebbe, Nina Feirer, Maximilian Billman, Sundar Srinivasan, Sebastian Zimmer, Colin N A Palmer, Ling Li, Chuhua Yang, Oleg Borisov, Matti Adam, Verena Veulemans, Michael Joner, Erion Xhepa

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Number of pages10
JournalJAMA cardiology
Early online date6 Nov 2024
DOIs
Publication statusE-pub ahead of print - 6 Nov 2024

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