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WITHDRAWN: Impact of genetic information on Coronary Disease risk in Madeira: The GENEMACOR study.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 The duplicate article has therefore been withdrawn.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.

A Patent Foramen Ovale Grants Cardiac Output Over an Obstructive Primary Cardiac Lymphoma.

Primary cardiac lymphomas are extremely rare and involve mainly the pericardium. We present the case of a 77-year-old man with a germinal center diffuse large B-cell lymphoma causing severe right ventricular inflow obstruction. Clinical presentation of isolated dyspnea and severe desaturation and cyanosis were, otherwise, unexpected. (Level of Difficulty: Beginner.).

Epicardial Adipose Tissue: The Genetics Behind an Emerging Cardiovascular Risk Marker.

Evidence points epicardial adipose tissue (EAT) as an emerging cardiovascular risk marker. Whether genetic polymorphisms linked with atherosclerosis are associated with higher EAT is still unknown. We aim to assess the role of genetic burden of atherosclerosis and its association to EAT in a cohort of asymptomatic individuals without coronary disease. A total of 996 participants were prospectively enrolled in a single Portuguese center. EAT volume was measured by Cardiac Computed Tomography and participants were distributed into 2 groups, above and below median EAT. SNPs were genotyped and linked to their respective pathophysiological axes. A multiplicative genetic risk score (mGRS) was constructed, representing the genetic burden of the studied SNPs. To evaluate the association between genetics and EAT, we compared both groups by global mGRS, mGRS by functional axes, and SNPs individually. Individuals above-median EAT were older, had a higher body mass index (BMI) and higher prevalence of hypertension, metabolic syndrome, diabetes, and dyslipidemia. They presented higher GRS, that remained an independent predictor of higher EAT volumes. The group with more EAT consistently presented higher polymorphic burden across numerous pathways. After adjustment, age, BMI, and mGRS of each functional axis emerged as independently related to higher EAT volumes. Amongst the 33 SNPs, MTHFR677 polymorphism emerged as the only significant and independent predictor of higher EAT volumes. Patients with higher polymorphism burden for atherosclerosis present higher EAT volumes. We present the first study in a Portuguese population, evaluating the genetic profile of EAT through GWAS and GRS, casting further insight into this complicated matter.

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.

KAsH: A new tool to predict in-hospital mortality in patients with myocardial infarction.

INTRODUCTION: Complex risk scores have limited applicability in the assessment of patients with myocardial infarction (MI). In this work, the authors aimed to develop a simple to use clinical score to stratify the in-hospital mortality risk of patients with MI at first medical contact. METHODS: In this single-center prospective registry assessing 1504 consecutively admitted patients with MI, the strongest predictors of in-hospital mortality were selected through multivariate logistic regression. The KAsH score was developed according to the following formula: KAsH=(Killip class×Age×Heart rate)/systolic blood pressure. Its predictive power was compared to previously validated scores using the DeLong test. The score was categorized and further compared to the Killip classification. RESULTS: The KAsH score displayed excellent predictive power for in-hospital mortality, superior to other well-validated risk scores (AUC: KAsH 0.861 vs. GRACE 0.773, p<0.001) and robust in subgroup analysis. KAsH maintained its predictive capacity after adjustment for multiple confounding factors such as diabetes, heart failure, mechanical complications and bleeding (OR 1.004, 95% CI 1.001-1.008, p=0.012) and reclassified 81.5% of patients into a better risk category compared to the Killip classification. KAsH's categorization displayed excellent mortality discrimination (KAsH 1: 1.0%, KAsH 2: 8.1%, KAsH 3: 20.4%, KAsH 4: 55.2%) and better mortality prediction than the Killip classification (AUC: KAsH 0.839 vs. Killip 0.775, p<0.0001). CONCLUSION: KAsH, an easy to use score calculated at first medical contact with patients with MI, displays better predictive power for in-hospital mortality than existing scores.