Literature DB >> 28460022

Korean atrial fibrillation network genome-wide association study for early-onset atrial fibrillation identifies novel susceptibility loci.

Ji-Young Lee1,2, Tae-Hoon Kim1, Pil-Sung Yang1, Hong Euy Lim3, Eue-Keun Choi4, Jaemin Shim5, Eunsoon Shin6, Jae-Sun Uhm1, Jin-Seok Kim3, Boyoung Joung1, Seil Oh4, Moon-Hyoung Lee1, Young-Hoon Kim5, Hui-Nam Pak1,2.   

Abstract

AIMS: Some genetic susceptibility loci for atrial fibrillation (AF) identified by genome-wide association studies (GWAS) in a European database showed ethnic differences in the Asian population. We explored novel AF susceptibility variants for patients with early-onset AF (≤60 years old) among Korean patients who underwent AF catheter ablation. METHODS AND
RESULTS: A genome-wide association study (GWAS) was conducted with 672 cases (≤60 years old, Yonsei AF Ablation cohort) and 3700 controls (Korea Genome Epidemiology Study). Association analysis was performed under an additive model of logistic regression, and replication study was conducted with 200 independent cases of Korean AF Network and 1812 controls. Five previously proven genetic loci (1q24/PRRX1, 4q25/PITX2, 10q24/NEURL, 12q24/TBX5, and 16q22/ZFHX3) were validated. Two novel genetic loci associated with early-onset AF were found on chromosomes 1q32.1/PPFIA4 (rs11579055, P = 6.84 × 10-10) and 4q34.1/HAND2 (rs8180252, P = 1.49 × 10-11) and replicated in an additional independent sample of the Korean AF Network. The identified loci implicate candidate genes that encode proteins related to cell-to-cell connection, hypoxic status, or long non-coding RNA.
CONCLUSION: Two novel genetic loci for early-onset AF were identified in Korean patients who underwent catheter ablation. One of the novel susceptibility loci on chromosome 4 has strong associations with previously proven gene in a European ancestry database. Published on behalf of the European Society of Cardiology. All rights reserved.
© The Author 2017. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  Atrial fibrillation; Genome-wide association study; Single nucleotide polymorphism

Mesh:

Substances:

Year:  2017        PMID: 28460022     DOI: 10.1093/eurheartj/ehx213

Source DB:  PubMed          Journal:  Eur Heart J        ISSN: 0195-668X            Impact factor:   29.983


  22 in total

Review 1.  Genetics of Atrial Fibrillation in 2020: GWAS, Genome Sequencing, Polygenic Risk, and Beyond.

Authors:  Carolina Roselli; Michiel Rienstra; Patrick T Ellinor
Journal:  Circ Res       Date:  2020-06-18       Impact factor: 17.367

2.  Monogenic and Polygenic Contributions to Atrial Fibrillation Risk: Results From a National Biobank.

Authors:  Seung Hoan Choi; Sean J Jurgens; Lu-Chen Weng; James P Pirruccello; Carolina Roselli; Mark Chaffin; Christina J-Y Lee; Amelia W Hall; Amit V Khera; Kathryn L Lunetta; Steven A Lubitz; Patrick T Ellinor
Journal:  Circ Res       Date:  2019-11-06       Impact factor: 17.367

3.  Sleep Apnea and Nocturnal Cardiac Arrhythmia: Understanding Differences Across Ethnicity.

Authors:  Reena Mehra
Journal:  J Clin Sleep Med       Date:  2017-11-15       Impact factor: 4.062

4.  Insights into the genetic basis of HMGB1 in atrial fibrillation in a Chinese Han population.

Authors:  Li Li; Yang Liu; Xinxin Li; Chunguang Qiu
Journal:  Cardiovasc Diagn Ther       Date:  2020-06

Review 5.  Atrial Fibrillation Genomics: Discovery and Translation.

Authors:  David H Yoo; Rolf Bodmer; Karen Ocorr; Christopher J Larson; Alexandre R Colas; Evan D Muse
Journal:  Curr Cardiol Rep       Date:  2021-10-01       Impact factor: 2.931

Review 6.  Genetics of atrial fibrillation-an update of recent findings.

Authors:  Aarthi Manoharan; Ravikumar Sambandam; Vishnu Bhat Ballambattu
Journal:  Mol Biol Rep       Date:  2022-05-19       Impact factor: 2.742

Review 7.  New biomarkers from multiomics approaches: improving risk prediction of atrial fibrillation.

Authors:  Jelena Kornej; Vanessa A Hanger; Ludovic Trinquart; Darae Ko; Sarah R Preis; Emelia J Benjamin; Honghuang Lin
Journal:  Cardiovasc Res       Date:  2021-06-16       Impact factor: 10.787

8.  Computational Modeling for Antiarrhythmic Drugs for Atrial Fibrillation According to Genotype.

Authors:  Inseok Hwang; Je-Wook Park; Oh-Seok Kwon; Byounghyun Lim; Myunghee Hong; Min Kim; Hee-Tae Yu; Tae-Hoon Kim; Jae-Sun Uhm; Boyoung Joung; Moon-Hyoung Lee; Hui-Nam Pak
Journal:  Front Physiol       Date:  2021-05-13       Impact factor: 4.566

Review 9.  Genetics of atrial fibrillation-practical applications for clinical management: if not now, when and how?

Authors:  Shinwan Kany; Bruno Reissmann; Andreas Metzner; Paulus Kirchhof; Dawood Darbar; Renate B Schnabel
Journal:  Cardiovasc Res       Date:  2021-06-16       Impact factor: 10.787

10.  Genetic heterogeneity of atrial fibrillation susceptibility loci across racial or ethnic groups.

Authors:  Henry Huang; Dawood Darbar
Journal:  Eur Heart J       Date:  2017-09-07       Impact factor: 35.855

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