Cardiovascular disease

Electrocardiogram-Based Artificial Intelligence to Identify Coronary Artery Disease.

Kany S, Friedman SF, Al-Alusi M, et al. Electrocardiogram-Based Artificial Intelligence to Identify Coronary Artery Disease. JACC. Advances. 2025;4(9):102041. doi:10.1016/j.jacadv.2025.102041Google Scholar PubMed DOI

Coagulation factor XII haploinsufficiency is protective against venous thromboembolism in a population-scale multidimensional analysis.

Haj AK, Paul DS, Jurgens SJ, et al. Coagulation factor XII haploinsufficiency is protective against venous thromboembolism in a population-scale multidimensional analysis. Nature communications. 2025;16(1):8176. doi:10.1038/s41467-025-62789-5Google Scholar PubMed DOI

Pathogenic Cardiomyopathy-Associated Gene Variants and Prognosis in Atrial Fibrillation: Results in 18,000 Clinical Trial Participants.

Jurgens SJ, Melloni GEM, Kany S, et al. Pathogenic Cardiomyopathy-Associated Gene Variants and Prognosis in Atrial Fibrillation: Results in 18,000 Clinical Trial Participants. Journal of the American College of Cardiology. 2025;86(10):738-753. doi:10.1016/j.jacc.2025.06.052Google Scholar PubMed DOI

Polygenic Susceptibility in Peripartum, Alcohol-Induced, and Cancer Therapy-Related Cardiomyopathies.

Maamari DJ, Biddinger KJ, Jurgens SJ, et al. Polygenic Susceptibility in Peripartum, Alcohol-Induced, and Cancer Therapy-Related Cardiomyopathies. JAMA cardiology. 2025. doi:10.1001/jamacardio.2025.3248Google Scholar PubMed DOI

A Deep Learning Model to Identify Mitral Valve Prolapse From the Echocardiogram.

Al-Alusi MA, Lau ES, Small AM, et al. A Deep Learning Model to Identify Mitral Valve Prolapse From the Echocardiogram. JACC. Cardiovascular imaging. 2025. doi:10.1016/j.jcmg.2025.08.011Google Scholar PubMed DOI

Contributions of Common, Rare, and Somatic Genetic Variants to Incidence of Atrial Fibrillation.

Zhang R, Kim MS, Yin W, et al. Contributions of Common, Rare, and Somatic Genetic Variants to Incidence of Atrial Fibrillation. JAMA cardiology. 2025. doi:10.1001/jamacardio.2025.3664Google Scholar PubMed DOI

An African ancestry-specific nonsense variant in CD36 is associated with a higher risk of dilated cardiomyopathy.

Huffman JE, Gaziano L, Sayed ZRA, et al. An African ancestry-specific nonsense variant in CD36 is associated with a higher risk of dilated cardiomyopathy. Nature genetics. 2025. doi:10.1038/s41588-025-02372-2Google Scholar PubMed DOI

Meta-Analysis of Genome-Wide Association Studies Reveals Genetic Mechanisms of Supraventricular Arrhythmias.

Weng LC, Khurshid S, Hall AW, et al. Meta-Analysis of Genome-Wide Association Studies Reveals Genetic Mechanisms of Supraventricular Arrhythmias. Circulation. Genomic and precision medicine. 2024:e004320. doi:10.1161/CIRCGEN.123.004320Google Scholar PubMed DOI

Brain and cancer associated binding domain mutations provide insight into CTCF's relationship with chromatin and its ability to act as a chromatin organizer.

Do C, Jiang G, Cova G, et al. Brain and cancer associated binding domain mutations provide insight into CTCF’s relationship with chromatin and its ability to act as a chromatin organizer. Research square. 2024. doi:10.21203/rs.3.rs-4670379/v1Google Scholar PubMed DOI

Molecular convergence of risk variants for congenital heart defects leveraging a regulatory map of the human fetal heart.

Ma R, Conley SD, Kosicki M, et al. Molecular convergence of risk variants for congenital heart defects leveraging a regulatory map of the human fetal heart. medRxiv : the preprint server for health sciences. 2024. doi:10.1101/2024.11.20.24317557Google Scholar PubMed DOI