Lian Liu1, Yusuke Ebana1, Jun-Ichi Nitta2, Yoshihide Takahashi3, Shinsuke Miyazaki4, Toshihiro Tanaka5, Masatoshi Komura6, Mitsuaki Isobe7, Tetsushi Furukawa8. 1. Department of Bio-informational Pharmacology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan. 2. Cardiovascular Division, Saitama Red Cross Hospital, Saitama, Japan. 3. Cardiovascular Division, National Disaster Medical Center, Tokyo, Japan. 4. Heart Rhythm Center, Tsuchiura Kyodo Hospital, Tokyo, Japan. 5. Bio-resource Research Center, Research and Industry-University Alliance Organization, Tokyo Medical and Dental University, Tokyo, Japan. 6. Cardiovascular Division, Kashiwa City Hospital, Tokyo, Japan. 7. Department of Cardiovascular Medicine, Tokyo Medical and Dental University, Tokyo, Japan. 8. Department of Bio-informational Pharmacology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan. Electronic address: t_furukawa.bip@mri.tmd.ac.jp.
Abstract
BACKGROUND: Atrial fibrillation (AF) affects millions of individuals worldwide. The genome-wide association studies have identified robust genetic associations with AF. METHODS: We genotyped 5461 participants of Japanese ancestry for 11 AF-related loci and determined the effects of carrying different numbers of risk alleles on disease development and age at disease onset. The weighted genetic risk score (GRS) was calculated, and its ability to predict AF was determined. RESULTS: Six single-nucleotide polymorphisms-rs593479 (1q24 in PRRX1), rs1906617 (4q25 near PITX2), rs11773845 (7q31 in CAV1), rs6584555 (10q25 in NEURL), rs6490029 (12q24 in CUX2), and rs12932445 (16q22 in ZFHX3) (P < 1.9 × 10-5)-were confirmed as being associated with AF. Patients with a high total number of risk alleles (9-12) had a younger median age at onset of AF (58 years; 95% confidence interval [CI], 55-60 years) than those with a low total number (1-4) (63 years; 95% CI, 61-64 years) (P = 0.0015). We observed a 4.38-fold (95% CI, 3.69-5.19) difference in risk of AF between individuals with scores in the top and bottom quartiles of the GRS. Receiver operating characteristic analysis indicated an area under the curve of 0.641 (95% CI, 0.628-0.653; P < 0.0001). CONCLUSIONS: Six loci were validated as associated with AF in a Japanese population. This study suggests that a combination of common genetic markers modestly facilitates discrimination of AF. This is the first report, to our knowledge, to demonstrate that the age of onset of AF is affected by common risk alleles.
BACKGROUND:Atrial fibrillation (AF) affects millions of individuals worldwide. The genome-wide association studies have identified robust genetic associations with AF. METHODS: We genotyped 5461 participants of Japanese ancestry for 11 AF-related loci and determined the effects of carrying different numbers of risk alleles on disease development and age at disease onset. The weighted genetic risk score (GRS) was calculated, and its ability to predict AF was determined. RESULTS: Six single-nucleotide polymorphisms-rs593479 (1q24 in PRRX1), rs1906617 (4q25 near PITX2), rs11773845 (7q31 in CAV1), rs6584555 (10q25 in NEURL), rs6490029 (12q24 in CUX2), and rs12932445 (16q22 in ZFHX3) (P < 1.9 × 10-5)-were confirmed as being associated with AF. Patients with a high total number of risk alleles (9-12) had a younger median age at onset of AF (58 years; 95% confidence interval [CI], 55-60 years) than those with a low total number (1-4) (63 years; 95% CI, 61-64 years) (P = 0.0015). We observed a 4.38-fold (95% CI, 3.69-5.19) difference in risk of AF between individuals with scores in the top and bottom quartiles of the GRS. Receiver operating characteristic analysis indicated an area under the curve of 0.641 (95% CI, 0.628-0.653; P < 0.0001). CONCLUSIONS: Six loci were validated as associated with AF in a Japanese population. This study suggests that a combination of common genetic markers modestly facilitates discrimination of AF. This is the first report, to our knowledge, to demonstrate that the age of onset of AF is affected by common risk alleles.
Authors: Kathryn E Hendee; Elena A Sorokina; Sanaa S Muheisen; Linda M Reis; Rebecca C Tyler; Vujica Markovic; Goran Cuturilo; Brian A Link; Elena V Semina Journal: Hum Mol Genet Date: 2018-05-15 Impact factor: 6.150
Authors: Lindsay Fernández-Rhodes; Jennifer R Malinowski; Yujie Wang; Ran Tao; Nathan Pankratz; Janina M Jeff; Sachiko Yoneyama; Cara L Carty; V Wendy Setiawan; Loic Le Marchand; Christopher Haiman; Steven Corbett; Ellen Demerath; Gerardo Heiss; Myron Gross; Petra Buzkova; Dana C Crawford; Steven C Hunt; D C Rao; Karen Schwander; Aravinda Chakravarti; Omri Gottesman; Noura S Abul-Husn; Erwin P Bottinger; Ruth J F Loos; Leslie J Raffel; Jie Yao; Xiuqing Guo; Suzette J Bielinski; Jerome I Rotter; Dhananjay Vaidya; Yii-Der Ida Chen; Sheila F Castañeda; Martha Daviglus; Robert Kaplan; Gregory A Talavera; Kelli K Ryckman; Ulrike Peters; Jose Luis Ambite; Steven Buyske; Lucia Hindorff; Charles Kooperberg; Tara Matise; Nora Franceschini; Kari E North Journal: PLoS One Date: 2018-07-25 Impact factor: 3.240