TY - JOUR
T1 - Genomic approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility
AU - Patel, Kush Ketan
AU - Venkatesan, Cynthia
AU - Abdelhalim, Habiba
AU - Zeeshan, Saman
AU - Arima, Yuichiro
AU - Linna-Kuosmanen, Suvi
AU - Ahmed, Zeeshan
N1 - Funding Information: This study was supported by the Institute for Health, Health Care Policy and Aging Research (IFH), and Rutgers Robert Wood Johnson Medical School (RWJMS), Rutgers Biomedical and Health Sciences (RBHS) at the Rutgers, the State University of New Jersey, and Japan Agency for Medical Research and Development (AMED) and the New York Academy of Sciences (NYAS)—The interstellar Initiative (Project# 22jm0610087h0001). Funding Information: We appreciate great support by the Rutgers Institute for Health, Health Care Policy, and Aging Research (IFH); Department of Medicine, Rutgers Robert Wood Johnson Medical School (RWJMS); Center for Innovation in Health and Aging Research (CIHAR); and Rutgers Biomedical and Health Sciences (RBHS), at the Rutgers, the State University of New Jersey. We thank members and collaborators of Ahmed Lab at Rutgers (IFH, RWJMS, RBHS) for their participation, and contribution to this study. We are grateful to the Japan Agency for Medical Research and Development (AMED) and the New York Academy of Sciences (NYAS)—The interstellar Initiative (Project# 22jm0610087h0001) for the support. Publisher Copyright: © 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - Atrial fibrillation (AF) and heart failure (HF) contribute to about 45% of all cardiovascular disease (CVD) deaths in the USA and around the globe. Due to the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. To improve the deciphering of CVD mechanisms, we need to deeply investigate well-known and identify novel genes that are responsible for CVD development. With the advancements in sequencing technologies, genomic data have been generated at an unprecedented pace to foster translational research. Correct application of bioinformatics using genomic data holds the potential to reveal the genetic underpinnings of various health conditions. It can help in the identification of causal variants for AF, HF, and other CVDs by moving beyond the one-gene one-disease model through the integration of common and rare variant association, the expressed genome, and characterization of comorbidities and phenotypic traits derived from the clinical information. In this study, we examined and discussed variable genomic approaches investigating genes associated with AF, HF, and other CVDs. We collected, reviewed, and compared high-quality scientific literature published between 2009 and 2022 and accessible through PubMed/NCBI. While selecting relevant literature, we mainly focused on identifying genomic approaches involving the integration of genomic data; analysis of common and rare genetic variants; metadata and phenotypic details; and multi-ethnic studies including individuals from ethnic minorities, and European, Asian, and American ancestries. We found 190 genes associated with AF and 26 genes linked to HF. Seven genes had implications in both AF and HF, which are SYNPO2L, TTN, MTSS1, SCN5A, PITX2, KLHL3, and AGAP5. We listed our conclusion, which include detailed information about genes and SNPs associated with AF and HF.
AB - Atrial fibrillation (AF) and heart failure (HF) contribute to about 45% of all cardiovascular disease (CVD) deaths in the USA and around the globe. Due to the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. To improve the deciphering of CVD mechanisms, we need to deeply investigate well-known and identify novel genes that are responsible for CVD development. With the advancements in sequencing technologies, genomic data have been generated at an unprecedented pace to foster translational research. Correct application of bioinformatics using genomic data holds the potential to reveal the genetic underpinnings of various health conditions. It can help in the identification of causal variants for AF, HF, and other CVDs by moving beyond the one-gene one-disease model through the integration of common and rare variant association, the expressed genome, and characterization of comorbidities and phenotypic traits derived from the clinical information. In this study, we examined and discussed variable genomic approaches investigating genes associated with AF, HF, and other CVDs. We collected, reviewed, and compared high-quality scientific literature published between 2009 and 2022 and accessible through PubMed/NCBI. While selecting relevant literature, we mainly focused on identifying genomic approaches involving the integration of genomic data; analysis of common and rare genetic variants; metadata and phenotypic details; and multi-ethnic studies including individuals from ethnic minorities, and European, Asian, and American ancestries. We found 190 genes associated with AF and 26 genes linked to HF. Seven genes had implications in both AF and HF, which are SYNPO2L, TTN, MTSS1, SCN5A, PITX2, KLHL3, and AGAP5. We listed our conclusion, which include detailed information about genes and SNPs associated with AF and HF.
KW - Atrial fibrillation
KW - Cardiovascular diseases
KW - Genes
KW - Genetic loci
KW - Genomics
KW - Heart failure
KW - Multi-OMICS
UR - http://www.scopus.com/inward/record.url?scp=85160879762&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85160879762&partnerID=8YFLogxK
U2 - https://doi.org/10.1186/s40246-023-00498-0
DO - https://doi.org/10.1186/s40246-023-00498-0
M3 - Review article
C2 - 37270590
SN - 1473-9542
VL - 17
JO - Human genomics
JF - Human genomics
IS - 1
M1 - 47
ER -