Model with risk factors, single nucleotide polymorphisms may predict AF
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A novel predictive model with single nucleotide polymorphisms associated with atrial fibrillation plus clinical risk factors better predicted AF risk than genetic risk factors alone, according to a study published in HeartRhythm.
Yousaku Okubo, MD, of the department of cardiovascular medicine at Hiroshima University Graduate School of Biomedical and Health Sciences in Japan, and colleagues analyzed data from 540 patients with AF who were treated at Hiroshima University Hospital between November 2009 and April 2012. A control group without AF (n = 520) and a replication cohort without AF (n = 1,018) were also included in the study.
Data on several conventional clinical risk factors were assessed including BMI, sex, age, diabetes and hypertension. Genotyping was also performed to identify single nucleotide polymorphisms associated with AF, which was then used to calculate the weighted genetic risk score.
Patients with AF were more likely to be men (72.5% vs. 48%; P = 2.27 x 10-16) and older (59 years vs. 50 years; P = 5.01 x 10-30) compared with those without AF.
Researchers identified five single nucleotide polymorphisms that were associated with AF: ZFHX3, PRRX1, HAND2, PITX2 and NEURL1. Using a genetic risk score derived from these single nucleotide polymorphisms, there was a 4.92-fold difference in AF risk when the highest weighted genetic risk score was compared with the lowest score (P = 2.32 x 10-10).
The area under the curve of the receiver operating characteristic analysis of the weighted genetic risk score was 0.73 for the screening cohort and 0.72 for the validation cohort. Compared with the weighted genetic risk score alone, the use of the weighted genetic risk score and clinical risk factors for AF had better discrimination of AF, with an area under the curve of 0.84, sensitivity of 75.4% and specificity of 80.2%.
“Various new technologies such as wearable ECG patches, Apple Watch/smartphones and irregular beats-detecting blood pressure machines are being applied with increasing frequency in general practice,” Okubo and colleagues wrote. “Nonetheless, early AF detection is still challenging, especially in asymptomatic patients, so identifying patients at high risk of AF development based on genetic and other clinical risk factors is equally important for reduction of cardiovascular and stroke-related morbidity and mortality.” – by Darlene Dobkowski
Disclosures: The authors report no relevant financial disclosures.
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