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Genomic approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility.
Patel, Kush Ketan; Venkatesan, Cynthia; Abdelhalim, Habiba; Zeeshan, Saman; Arima, Yuichiro; Linna-Kuosmanen, Suvi; Ahmed, Zeeshan.
Afiliación
  • Patel KK; Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, 112 Paterson St, New Brunswick, NJ, USA.
  • Venkatesan C; Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, 112 Paterson St, New Brunswick, NJ, USA.
  • Abdelhalim H; Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, 112 Paterson St, New Brunswick, NJ, USA.
  • Zeeshan S; Rutgers Cancer Institute of New Jersey, Rutgers University, 195 Little Albany St, New Brunswick, NJ, USA.
  • Arima Y; Developmental Cardiology Laboratory, International Research Center for Medical Sciences, Kumamoto University, 2-2-1 Honjo, Kumamoto City, Kumamoto, Japan.
  • Linna-Kuosmanen S; A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, 70211, Kuopio, Finland.
  • Ahmed Z; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Hum Genomics ; 17(1): 47, 2023 06 03.
Article en En | MEDLINE | ID: mdl-37270590
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fibrilación Atrial / Insuficiencia Cardíaca Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Hum Genomics Asunto de la revista: GENETICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fibrilación Atrial / Insuficiencia Cardíaca Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Hum Genomics Asunto de la revista: GENETICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos