Genetics may be at play in development of lone AF
Genetic variation, as observed using polygenic and genome-wide risk scores, may contribute to the development of atrial fibrillation in the absence of traditional CV risk factors, researchers reported.
According to data published in Circulation: Genomic and Precision Medicine, consideration of patient ancestry, age and sex may also improve discriminatory capacity of these risk scores for a lone AF phenotype.
“Our findings suggest that common genetic variation plays a critical role when AF develops in the absence of identifiable clinical risk factors, as illustrated by the remarkable distribution of the polygenic risk scores/genome-wide polygenic scores among AF cases relative to controls,” Julieta Lazarte, MSc, of the department of medicine at the Robarts Research Institute, Schulich School of Medicine & Dentistry, at Western University in London, Ontario, Canada, and colleagues wrote.
Basis in prior research
In a prior study, Lu-Chen Weng, PhD, and colleagues used a polygenic risk score of approximately 1,000 single nucleotide polymorphisms (SNPs) and found the highest tertile scores were associated with an elevated lifetime risk for AF at age 55 years. In another study, Amit V. Khera, MD, MSc, and colleagues used a genome-wide polygenic score that included approximately 6 million SNPs and determined a high score was associated with elevated risk for AF.
For this analysis, researchers included 186 patients with lone AF (mean age at AF diagnosis, 44 years; 81% men) and 86 self-reported healthy patients for controls (mean age, 41 years; 49% men), all of European ancestry, who underwent DNA microarray genotyping. Utilizing the polygenic risk score developed by Weng and colleagues and the genome-wide polygenic score developed by Khera and colleagues, researchers aimed to evaluate risk for lone AF within this population.
According to the study, a high polygenic score was defined as being within the top 10th percentile of the healthy control distribution.
“Although the roles of polygenic scores have begun to be evaluated in AF, they have yet to be assessed in a lone AF cohort, where their potential genetic impact is anticipated to be the most dramatic,” the researchers wrote. “Accordingly, we sought to evaluate two validated polygenic scores in a lone AF cohort.”
Odds of lone AF development
Participants were excluded if they had hypertension, CAD, left ventricular ejection fraction less than 50%, moderate-to-severe valvular heart disease, hyperthyroidism or obstructive sleep apnea.
Among participants with lone AF, a high polygenic risk score was observed in 33.3% and a high genome-wide polygenic risk score was observed in 26.3%.
Researchers found that a high polygenic risk score was associated with an adjusted 5.7-fold increased odds of AF (95% CI, 2.6-13.95; P < .0001), whereas a high genome-wide polygenic score was associated with 3.72-fold greater odds for AF (95% CI, 1.7-8.97; P = .0017) compared with the control group.
According to the study, addition of the polygenic scores to logistic regression models containing the first three principal components, age and sex (C statistic = 0.69; 95% CI, 0.62-0.77) improved discriminatory capacity (polygenic risk score C statistic = 0.77; 95% CI, 0.71-0.83; P = .0005; genome-wide polygenic score C statistic = 0.79; 95% CI, 0.73-0.84; P = .0007).
Researchers observed no difference between the polygenic risk score and genome-wide polygenic score models (P = .4).
“Although it could be anticipated that AF polygenic scores may exert a greater impact on the lone form of the arrhythmia relative to more common forms of AF, direct comparisons with the measures of association determined from prior population-based studies cannot be reasonably made owing to the different study bases and analytical methodologies used,” the researchers wrote. “Beyond highlighting the relevance of SNPs to lone AF pathophysiology, these findings also allude to the potential clinical utility of polygenic scores in the clinical setting, including its use as a tool to optimally guide delivery of upstream preventive therapies to vulnerable individuals.”