Genetic information or coronary artery calcium score? What is more helpful in today's clinical practice?. (3rd October 2022) - Sa, D; Mendonca, M I; Temtem, M; Santos, M; Serrao, M; Sousa, A C; Borges, S; Freitas, S; Rodrigues, M; Henriques, E; Guerra, G; Ornelas, I; et al.
Abstract: Introduction: Coronary artery calcium (CAC) score has emerged as the most predictive cardiovascular risk marker in asymptomatic individuals, capable of adding prognostic information beyond the traditional risk factors (TRF). Genetic risk score (GRS) significantly improves cardiovascular genetic risk assessment at the individual level providing a more personalized measure of disease risk. Purpose: We intend to evaluate which tool, added to TRF, is more valuable in predicting and discriminating cardiovascular events and death (MACE) - GRS or CAC score? Methods: We performed a prospective study with 1153 participants without CAD history at baseline (74.2% male, age 51.7±8.3 years) during a mean follow-up of 5.4±3.4 years. We selected 14 SNPs previously associated with CAD presenting a risk (HR) for cardiovascular events ≥1. A weighted GRS was calculated, as the sum of these 14 risk alleles weighted by the corresponding effect size in prognostic (HR), and subsequently, subdivided into tertiles. CAC (Agatson) score was calculated in all participants and categorized into: low CAC (0≤CAC<100 or P<50); moderate CAC (100≤CAC<400 or P50–75) and high or severe CAC (CAC≥400 or P>75). Two models were created with TRF baseline (hypertension, smoking, body mass index, dyslipidemia, diabetes, chronic kidney disease, physical inactivity): 1) plus wGRS and 2) plus CAC score categories. Cox Regression Analyses and C-statistic assessed the predictive and discriminative capacity of both models. Results: For model 1, Cox regression presented an HR of 4.292 for TRF (p=0.007) and 2.713 for 3rd tertile of wGRS (0.036). A modest but statistically significant improvement in MACE discriminative capacity was verified by adding wGRS to TRF, increasing the C-statistic from 0.617 to 0.687 (ΔC=0.070; p=0.013). On the other hand, model 2 better discriminated MACE when the CAC score (C-statistic = 0.765) was added to TRF (ΔC=0.148; p=0.001). Cox regression displayed an HR of 4.42 for TRF (p=0.015) and an HR of 4.55 for high-risk CAC score (p=0.001). Conclusion: Our results suggest that adding a polygenic risk score to conventional risk factors provides a modest improvement in the discrimination of first-onset MACE. However, the CAC score added to the traditional model allows better discrimination of MACE compared to wGRS. CAC score could be helpful for MACE prediction, at least in individuals belonging to the higher genetic risk group. However, further investigation is required before clinical implementation. Funding Acknowledgement: Type of funding sources: Public hospital(s). Main funding source(s): SESARAM EPERAM