Genome and atrial fibrillation

Figures

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  FIGURE 1. Differential contribution of polygenic risk scores and clinical factors to AF. A comparison between the late‐onset (age > 60) and early‐onset groups (age ≤ 60) showed that PRS contributed more toward detecting the early‐onset group, whereas clinical factors calculated from the CHARGE‐AF calculator contributed more toward detecting the late‐onset group. PRS, polygenic risk scores.

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  FIGURE 2. AF prediction using genetic risk score and clinical factors. (A) There was a 4.92‐fold difference in AF risk between the highest and lowest weighted genetic risk score (WGRS) using five AF‐associated SNVs (in PRRX1, ZFHX3, PITX2, HAND2, and NEURL1). WGRS, weighted genetic risk score. (B) Receiver operating characteristic analysis of WGRS yielded an area under the curve (AUC) of 0.73 in the screening cohort. The AF predictive logistic model constructed using a combination of WGRS and AF clinical risk factors (age, body mass index, gender, and hypertension) demonstrated better discrimination of AF than did WGRS alone (AUC, 0.84; sensitivity, 75.4%; specificity, 80.2%).

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  FIGURE 3. Kaplan–Meier analysis of AF recurrence with the GJA‐1 SNP rs1015451 (T > C) in each genotype group. The Kaplan–Meier analysis showed that AF patients with the GJA1 SNV rs1015451 minor C allele were prone to AF recurrence.