Validation of the SCORE2 risk prediction algorithm in a Portuguese population: A new model to estimate 10-year cardiovascular disease incidence in Europe.

INTRODUCTION AND OBJECTIVES: Subjects without cardiovascular (CV) disease (CVD) may suffer from subclinical atherosclerosis, and are at increased risk for atherosclerotic CV events (ASCVE). The ESC/EAS risk SCORE was updated by SCORE2, which estimates 10-year risk of fatal and non-fatal CVD in European populations aged 40-69 years without established CVD or diabetes. Our aim was to compare the two ESC/EAS risk scores and to validate SCORE2 in our population. METHODS: A total of 1071 individuals (age 57.2±6.1 years; 75.2% male) without CVD or diabetes, from GENEMACOR study controls, were analyzed over 5.4±3.9 years. The population was stratified into risk categories according to the two scores, and the area under the ROC curve (AUC) and Harrell's C-index assessed the scores' performance. Calibration was performed using the goodness-of-fit test, and occurrence of the first event assessed by Cox regression. Kaplan-Meier analysis estimated SCORE2 survival. RESULTS: SCORE stratified subjects into four risk categories: low (7.4%), moderate (46.5%), high (25.3%) and very high (20.8%), and SCORE2 into three: low-to-moderate (24.7%), high (59.0%) and very high (16.2%). SCORE presented good discrimination for CV mortality (AUC=0.838; C-index=0.834, 95% CI: 0.728-0.940), as did SCORE2 for total CV events (AUC=0.744; C-index=0.728, 95% CI: 0.648-0.808). Calibration did not show a disparity between observed and expected ASCVE. The probability of ASCVE was eight times higher in very-high-risk SCORE2 (p=0.001), and three times in the high-risk group (p=0.049). Event-free survival was 99%, 90% and 72% in the low-to-moderate, high and very-high-risk categories, respectively (p<0.0001). CONCLUSIONS: SCORE2 improved population stratification by identifying higher-risk patients, enabling early preventive measures. It showed good discriminative ability for all ASCVE.

Predictive improvement of adding coronary calcium score and a genetic risk score to a traditional risk model for cardiovascular event prediction.

AIMS: Coronary artery calcium score (CACS) and polygenic risk score have been used as novel markers to predict cardiovascular (CV) events of asymptomatic individuals compared with traditional scores. No previous studies have directly compared the additive capacity of these two markers relative to conventional scores. The aim of the study was to evaluate the change in CV risk prediction ability when CACS, genetic risk score (GRS), or both are added to Systematic Coronary Risk Evaluation 2 (SCORE2). METHODS AND RESULTS: In a prospective, observational population-based study, 1002 asymptomatic subjects (mean age 53.1 ± 6.8 years, 73.8% male), free of clinical coronary disease and diabetes, were selected from GENEMACOR-study controls. SCORE2, CACS, and GRS were estimated to evaluate CV events' predictive and discriminative ability through Harrell's C-statistics. Net reclassification improvement (NRI) and integrated discrimination index were used to reclassify the population. Multivariable Cox proportional hazard ratio (HR) analysis assessed the variables independently associated with CV events. C-statistic demonstrated that the discriminative value for CV event occurrence was 0.608 for SCORE2, increasing to 0.749 (P = 0.001) when CACS was added, and improved to 0.802 (P = 0.0008) with GRS, showing a better discriminative capacity for CV events. Continuous NRI reclassified >70% of the population. Cox proportional analysis showed that the highest categories of SCORE2, CACS, and GRS remained in the equation with an HR of 2.9 (P = 0.003), 5.0 (P < 0.0001), and 3.2 (P = 0.003), respectively, when compared with the lowest categories. CONCLUSION: In our population, CACS added to SCORE2 had better ability than GRS in CV event risk prediction, discrimination, and reclassification. However, adding the three scores can become clinically relevant, especially in intermediate-risk persons.

Our study highlights the impact of including coronary artery calcium score (CACS) and genetic risk score (GRS) alongside Systematic Coronary Risk Evaluation 2 (SCORE2) for enhancing cardiovascular (CV) risk assessment in primary prevention. In our population, adding CACS to SCORE2 exhibited a superior discriminative capacity for CV events compared with GRS alone in terms of risk prediction, discrimination, and reclassification. Our results emphasize the potential clinical relevance of using all three scores to identify high-risk individuals who would benefit from earlier and more stringent cardiovascular risk management strategies to prevent future cardiovascular events.

Transcription factor 21 gene and prognosis in a coronary population.

INTRODUCTION AND OBJECTIVES: Transcription factor 21 (TCF21) is a member of the basic helix-loop-helix (bHLH) transcription factor family, and is critical for embryogenesis of the heart. It regulates differentiation of epicardium-derived cells into smooth muscle cell (SMC) and fibroblast lineages. The biological role of TCF21 in the progression of atherosclerosis is the subject of debate. The aim of this study was to investigate the impact of the TCF21 rs12190287 gene variant on the prognosis of coronary artery disease (CAD) in a Portuguese population from Madeira island. METHODS: We analyzed major adverse cardiovascular events (MACE) in 1713 CAD patients, mean age 53.3±7.8, 78.7% male, for 5.0±4.3 years. Genotype and allele distribution between groups with and without MACE was determined. The dominant genetic model (heterozygous GC plus homozygous CC) was used and compared with the wild GG to assess survival probability. Cox regression with risk factors and genetic models assessed variables associated with MACE. Kaplan-Meier analysis was used to estimate survival. RESULTS: The wild homozygous GG, heterozygous GC and risk CC genotypes were found in 9.5%, 43.2% and 47.3% of the population, respectively. The dominant genetic model remained in the equation as an independent risk factor for MACE (HR 1.41; p=0.033), together with multivessel disease, chronic kidney disease, low physical activity and type 2 diabetes. The C allele in the dominant genetic model showed worse survival (22.5% vs. 44.3%) at 15 years of follow-up. CONCLUSION: The TCF21 rs12190287 variant is a risk factor for CAD events. This gene may influence fundamental SMC processes in response to vascular stress, accelerating atherosclerosis progression, and may represent a target for future therapies.

Impact of genetic information on coronary disease risk in Madeira: The GENEMACOR study.

INTRODUCTION: Coronary artery disease (CAD), characterized by an atherogenic process in the coronary arteries, is one of the leading causes of death in Madeira. The GENEMACOR (GENEs in MAdeira and CORonary Disease) study sought to investigate the main risk factors - environmental and genetic - and estimate whether a genetic risk score (GRS) improves CAD prediction, discrimination and reclassification. METHODS: Traditional risk factors and 33 CAD genetic variants were considered in a case-control study with 3139 individuals (1723 patients and 1416 controls). The multivariate analysis assessed the likelihood of CAD. A multiplicative GRS (mGRS) was created, and two models (with and without mGRS) were prepared. Two areas under receiver operating characteristic curve (area under curve (AUC)) were analyzed and compared to discriminate CAD likelihood. Net reclassification improvement (NRI) and integrated discrimination index (IDI) were used to reclassify the population. RESULTS: All traditional risk factors were strong and independent predictors of CAD, with smoking being the most significant (OR 3.25; p<0.0001). LPA rs3798220 showed a higher CAD likelihood (odds ratio 1.45; p<0.0001). Individuals in the fourth mGRS quartile had an increased CAD probability of 136% (p<0.0001). A traditional risk factor-based model estimated an AUC of 0.73, rising to 0.75 after mGRS inclusion (p<0.0001), revealing a better fit. Continuous NRI better reclassified 28.1% of the population, and categorical NRI mainly improved the reclassification of the intermediate risk group. CONCLUSIONS: CAD likelihood was influenced by traditional risk factors and genetic variants. Incorporating GRS into the traditional model improved CAD predictive capacity, discrimination and reclassification. These approaches may provide helpful diagnostic and therapeutic advances, especially in the intermediate risk group.

WITHDRAWN: Impact of genetic information on Coronary Disease risk in Madeira: The GENEMACOR study.

The Publisher regrets that this article is an accidental duplication of an article that has already been published, 10.1016/j.repc.2022.10.005. The duplicate article has therefore been withdrawn. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population.

The inclusion of a genetic risk score (GRS) can modify the risk prediction of coronary artery disease (CAD), providing an advantage over the use of traditional models. The predictive value of the genetic information on the recurrence of major adverse cardiovascular events (MACE) remains controversial. A total of 33 genetic variants previously associated with CAD were genotyped in 1587 CAD patients from the GENEMACOR study. Of these, 18 variants presented an hazard ratio >1, so they were selected to construct a weighted GRS (wGRS). MACE discrimination and reclassification were evaluated by C-Statistic, Net Reclassification Index and Integrated Discrimination Improvement methodologies. After the addition of wGRS to traditional predictors, the C-index increased from 0.566 to 0.572 (p=0.0003). Subsequently, adding wGRS to traditional plus clinical risk factors, this model slightly improved from 0.620 to 0.622 but with statistical significance (p=0.004). NRI showed that 17.9% of the cohort was better reclassified when the primary model was associated with wGRS. The Kaplan-Meier estimator showed that, at 15-year follow-up, the group with a higher number of risk alleles had a significantly higher MACE occurrence (p=0.011). In CAD patients, wGRS improved MACE risk prediction, discrimination and reclassification over the conventional factors, providing better cost-effective therapeutic strategies.