A polygenic risk score to predict sudden cardiac arrest in patients with coronary artery disease
Porcu, E.; Thorball, C. W.; Porretta, A. P.; Pruvot, E.; Wiskott, K.; Gilardi, F.; Thomas, A.; Redin, C.; Kutalik, Z.; Fracasso, T.; Muller, O.; Fellay, J.
Show abstract
Cardiovascular disease (CVD) is a leading health problem and the main cause of death globally. Even when underlying causative factors are known, it is unclear why a cardiovascular condition causes premature death in a victim while others can live longer with the same condition. Here we propose a combined polygenic risk score (metaPRS) based on coronary artery disease (CAD), myocardial infarction (MI), low-density lipoprotein (LDL) cholesterol, body mass index (BMI) and type 2 diabetes (T2D) to predict the risk of sudden cardiac arrest (SCA) in patients affected by severe cardiovascular conditions. We collected 2,114 patients with reported history of acute coronary syndrome from the Centre Hospitalier Universitaire Vaudois (CHUV) Genomic Biobank (BGC) and extracted data from the UK Biobank (UKB) on 13,696 participants with similar medical history. Among them, 303 and 932 had a further reported diagnosis of SCA or ventricular tachycardia/fibrillation according to the International Classification of Diseases (ICD-10) codes in BGC and UKB, respectively. We demonstrate that the metaPRS is significantly associated with SCA in both cohorts (ORBGC = 1.28, PBGC = 8.39 x 10-05 and ORUKB = 1.14, PUKB = 7.07 x 10-05). Furthermore, using the diagnosis based on the International Classification of Diseases (ICD-10) codes available in the UKB, the metaPRS exhibits a strong association with the presence of aortocoronary bypass graft (ORUKB = 1.31, PUKB = 6.93 x 10-33) and coronary angioplasty implant (ORUKB=1.14, PUKB=1.46x10-12). These results show that a combined genetic risk score for CVD and associated risk factors has the potential to predict the occurrence of SCA in patients with myocardial infarction, hence to identify patients who could benefit from further preventive measures.
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