Genome-wide association study reveals novel genetic loci: a new polygenic risk score for mitral valve prolapse

Carolina Roselli, Mengyao Yu, Victor Nauffal, Adrien Georges, Qiong Yang, Katie Love, Lu-Chen Weng, Francesca N Delling, Svetlana R Maurya, Maren Schrölkamp, Jacob Tfelt-Hansen, Albert Hagège, Xavier Jeunemaitre, Stéphanie Debette, Philippe Amouyel, Wyliena Guan, Jochen D Muehlschlegel, Simon C Body, Svati Shah, Zainab SamadSergiy Kyryachenko, Carol Haynes, Michiel Rienstra, Thierry Le Tourneau, Vincent Probst, Ronan Roussel, Inez J Wijdh-Den Hamer, Joylene E Siland, Kirk U Knowlton, Jean Jacques Schott, Robert A Levine, Emelia J Benjamin, Ramachandran S Vasan, Benjamin D Horne, Joseph B Muhlestein, Giovanni Benfari, Maurice Enriquez-Sarano, Andrea Natale, Sanghamitra Mohanty, Chintan Trivedi, Moore B Shoemaker, Zachary T Yoneda, Quinn S Wells, Michael T Baker, Eric Farber-Eger, Hector I Michelena, Alicia Lundby, Russell A Norris, Susan A Slaugenhaupt, Christian Dina, Steven A Lubitz, Nabila Bouatia-Naji, Patrick T Ellinor, David J Milan

Research output: Contribution to journalJournal articleResearchpeer-review

34 Citations (Scopus)

Abstract

AIMS: Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder.

METHODS AND RESULTS: We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors.

CONCLUSION: We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-β signalling molecules and spectrin β. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention.

KEY QUESTION: Expand our understanding of the genetic basis for mitral valve prolapse (MVP). Uncover relevant pathways and target genes for MVP pathophysiology. Leverage genetic data for MVP risk prediction.

KEY FINDING: Sixteen genetic loci were significantly associated with MVP, including 13 novel loci. Interesting target genes at these loci included LTBP2, TGFB2, ALKP3, BAG3, RBM20, and SPTBN1. A risk score including clinical factors and a polygenic risk score, performed best at predicting MVP, with an area under the receiver operating characteristics curve of 0.677.

TAKE-HOME MESSAGE: Mitral valve prolapse has a polygenic basis: many genetic variants cumulatively influence pre-disposition for disease. Disease risk may be modulated via changes to transforming growth factor-β signalling, the cytoskeleton, as well as cardiomyopathy pathways. Polygenic risk scores could enhance the MVP risk prediction.

Original languageEnglish
JournalEuropean Heart Journal
Volume43
Issue number17
Pages (from-to)1668–1680
ISSN0195-668X
DOIs
Publication statusPublished - 2022

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