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Genetic risk score for coronary artery calcification and its predictive ability for coronary artery disease

Year: 2024
Type: article
Study design: Observational Study
Abstract: Aim: The modest added predictive value of the existing genetic risk scores (GRSs) for coronary artery disease (CAD) could be partly due to missing genetic components, hidden in the genetic architecture of intermediate phenotypes such as coronary artery calcification (CAC). In this study, we investigated the predictive ability of CAC GRS for CAD. Materials and methods: = 660) using summary data from the largest multi-ancestry GWAS meta-analysis of CAC to date. Added predictive value of the CAC GRS over the traditional CVD risk factors as well as metaGRS, a GRS for CAD constructed with 1.7 million genetic variants, was tested with standard train-test machine learning approach using the LURIC data, which had the largest sample size. Results: CAC GRS was significantly associated with CAD in LURIC (OR=1.41, 95 % CI [1.28-1.55]), TVS (OR=1.79, 95 % CI [1.05-3.21]) as well as in TSDS (OR=4.20, 95 % CI [1.74-10.52]). CAC GRS showed strong association with calcification areas in left (OR=1.78, 95 % CI [1.16-2.74]) and right (OR=1.71, 95 % CI [1.98-2.67]) coronary arteries. There was statistically significant added predictive value of the CAC GRS for CAD over the used traditional CVD risk factors (AUC 0.734 vs 0.717, p-value = 0.02). Furthermore, CAC GRS improved the prediction accuracy for CAD when combined with metaGRS. Conclusions: This study showed that CAC GRS is a new risk marker for CAD in three European cohorts, with added predictive value over the traditional CVD risk factors.
DOI: 10.1016/j.ajpc.2024.100884
Authors: Pashupati P. Mishra, Binisha H. Mishra, Leo-Pekka Lyytikäinen, Sirkka Goebeler, Mika Martiskainen, Emma Hakamaa, Marcus E. Kleber, Graciela E. Delgado, Winfried März, Mika Kähönen, Pekka J. Karhunen, Terho Lehtimäki
Institutions: Tampere University, Fimlab (Finland), University of Tampere, Finnish Institute for Health and Welfare, Heidelberg University, Medizinische Fakultät Mannheim, Synlab (Germany), Tampere University Hospital
Language: English
Subfield: Genetics
Open Access status: gold
Estimated APC paid: $1,338
Funders: Yrjö Jahnssonin Säätiö, European Commission, Academy of Finland, Jane ja Aatos Erkon Säätiö, Juho Vainion Säätiö, Signe ja Ane Gyllenbergin Säätiö, Emil Aaltosen Säätiö, Sydäntutkimussäätiö, Tampereen Tuberkuloosisäätiö, Diabetesliitto, Tays, Suomen kliinisen kemian yhdistys, Horizon 2020
Awards: A patient-centered early risk prediction, prevention, and intervention platform to support the continuum of care in coronary artery disease (CAD) using eHealth and artificial intelligence, G1335418636, G198835066, G234837756, Improving the early prediction of cardiovascular diseases by developing novel data-driven machine learning and multiomics approaches, G5646563246, G7094783928
OpenAlex ID: W4403286262
FWCI: 1.204
Cites: 33
Cited by: 5
Related to: 10