Genetic Risk Score for Coronary Heart Disease: Review

Advancements in Biomarkers for Early Detection and Risk Stratification of Cardiovascular Diseases-A Literature Review

Introduction

CVDs is a leading cause of morbidity, mortality, and healthcare expenditure worldwide. Identifying individuals at risk or in the incipient stages of disease is instrumental in enabling timely interventions, preventive measures, and tailored treatment regimens. The landscape of CVDs is complicated by their heterogeneity, encompassing a spectrum of conditions such as coronary artery disease, heart failure, arrhythmias, and valvular disorders. In recent years, the integration of biomarkers into cardiovascular medicine has emerged as a paradigm-shifting approach with the potential to revolutionize early detection and risk stratification. By synthesizing a multitude of studies, we aim to provide a comprehensive resource that illuminates the transformative potential of biomarkers in ushering in a new era of precision cardiovascular medicine.

Aim

To identify the biomarkers for the detection and diagnosis of CVDs.

Materials and Methods

This review examines key studies from 2015 to the present that investigate the impact of cardiac biomarkers on cardiovascular outcomes. Data were gathered from PubMed, Cochrane Library, and Embase to ensure a comprehensive analysis. The review focuses on various cardiac biomarkers, assessing their levels and changes in relation to cardiovascular health, with special emphasis on advanced biomarkers such as proteomic and metabolomic markers in cardiovascular disease (CVD) diagnosis. Peer-reviewed studies published in English that evaluated the diagnostic, prognostic, or therapeutic role of cardiac biomarkers were included, with priority given to clinical trials, cohort studies, systematic reviews, and meta-analyses providing quantitative biomarker data. Studies unrelated to cardiac biomarkers, case reports, editorials, conference abstracts, and those with small sample sizes or insufficient methodological rigor were excluded. The review also accounts for potential confounding factors and research limitations, ensuring a balanced assessment of the literature. By synthesizing data from academic papers, clinical reports, and research articles, this study provides a comprehensive evaluation of the evolving role of cardiac biomarkers in CVD diagnosis and risk stratification.

Results

Biomarkers play a pivotal role in cardiovascular disease risk prediction, diagnosis, and treatment by providing dynamic biological insights. High-sensitivity cardiac troponins (hs-cTn) enhance myocardial injury detection, while circulating microRNAs (miR-208, miR-499) serve as early indicators of myocardial infarction and heart failure. Lipoprotein(a) [Lp(a)] predicts long-term cardiovascular risk, and inflammatory biomarkers such as C-reactive protein (CRP) and interleukin-6 (IL-6) are linked to adverse outcomes. Multi-biomarker panels, such as hs-cTn with B-type natriuretic peptide (BNP), improve heart failure prognosis, while metabolomic profiling enables precision medicine. Additionally, biomarkers like BNP and NT-proBNP facilitate real-time therapeutic monitoring. These findings underscore the critical role of biomarkers in refining risk stratification, improving diagnostic accuracy, and enabling personalized treatment strategies in cardiovascular medicine.

Conclusion

The advancement of cardiovascular biomarkers has significantly enhanced early detection, risk stratification, and personalized treatment. Emerging biomarkers, including genetic variants, metabolomics, microRNAs, and imaging-based markers, provide deeper insights into disease mechanisms. Integrating multi-omic approaches with artificial intelligence may further refine predictive accuracy and therapeutic decision-making. However, clinical translation requires rigorous validation through large-scale, multicenter studies to ensure reliability and applicability across diverse populations. Standardization, cost-effectiveness assessments, and the development of biomarker panels are essential for clinical adoption. Future research should focus on bridging discovery and implementation, advancing precision medicine to improve cardiovascular outcomes.

Association of the ABCG2 rs2231142 variant with the Framingham Cardiovascular Disease Risk score in the Taiwanese population

Background

Serum uric acid (SUA) is an important predictor of cardiovascular events and mortality. The ABCG2 rs2231142 variant (TT genotype) is associated with hyperuricemia (HUA), but the relationship between ABCG2 gene polymorphisms and coronary artery disease (CAD) risk is poorly elucidated. We investigated the association between ABCG2 rs2231142 genetic variants and the Framingham Risk Score for Cardiovascular Disease (FRS-CVD) in a Taiwanese population.

Methods

This cross-sectional study enrolled 139,508 Taiwanese participants aged 30-70 years based on data from the Taiwan Biobank (TWB) database that was obtained from questionnaires, laboratory investigations, anthropometry, and Affymetrix TWB genome-wide single-nucleotide polymorphism (SNP) chip data analysis. The association between ABCG2 rs2231142 and FRS-CVD risk was evaluated using logistic regression analysis.

Results

Compared to those with the GG genotype, participants with the ABCG2 rs2231142 TT genotype had a significantly lower systolic blood pressure, smoking rate, body mass index, triglyceride level, waist circumference, waist-hip ratio, and body fat percentage, but had higher high-density lipoprotein cholesterol level. Despite the same FRS-CVD score, participants with TT genotypes had higher SUA. Even with the same SUA, TT carriers had a lower FRS-CVD than GT and GG carriers. Participants with the TT genotype had significantly lower CVD risk, particularly female participants with HUA and BMI <27 (OR: 0.760, 95 % CI: 0.587-0.985; p = 0.0381) group.

Conclusion

The ABCG2 rs2231142 TT genotype is associated with a lower FRS-CVD, particularly in non-obese hyperuricemic female individuals. The complicated interplay among genetic variations, metabolic profile, and CVD risk provides insights for precision health.

Genetic Risk Score for Prediction of Coronary Heart Disease in the Korean Genome and Epidemiology Study

Background

Using a genetic risk score (GRS) to predict coronary heart disease (CHD) may detect disease earlier. The current study aims to assess whether GRS is associated with CHD incidence and whether it is clinically useful for improving prediction using traditional risk factors (TRFs) as well as family history.

Methods

Data from a total of 48,941 participants in the Korean Genome and Epidemiology Study were analyzed in the current study. The weighted GRS was constructed using 55 single-nucleotide polymorphisms based on published genome-wide association studies. The association of GRS with incident CHD was analyzed using Cox proportional hazard model. Discrimination and reclassification were assessed to demonstrate the clinical utility of GRS. The analyses were performed separately by sex.

Results

After adjusting for family history and TRFs, GRS was significantly associated with CHD incidence in men; compared to the low GRS group, men in the high GRS group had a 2.07-fold increased risk of CHD (95% confidence interval [CI]: 1.51-2.85). In men, the combination of TRFs, family history, and GRS had better performance than TRFs alone (C statistics for TRF-only model, 0.66, 95% CI, 0.64-0.69; C statistics for combination model, 0.68, 95% CI, 0.65-0.71; category-free reclassification index, 15%). In women, however, there was no significant association between GRS and CHD and no improvement between models.

Conclusions

GRS was associated with CHD incidence and contributed to a small improvement of CHD prediction in men. The potential clinical use of GRS may not outweigh the value of family history.

Functionally Significant Variants in Genes Associated with Abdominal Obesity: A Review

The high prevalence of obesity and of its associated diseases is a major problem worldwide. Genetic predisposition and the influence of environmental factors contribute to the development of obesity. Changes in the structure and functional activity of genes encoding adipocytokines are involved in the predisposition to weight gain and obesity. In this review, variants in genes associated with adipocyte function are examined, as are variants in genes associated with metabolic aberrations and the accompanying disorders in visceral obesity.

The "Common Soil Hypothesis" Revisited-Risk Factors for Type 2 Diabetes and Cardiovascular Disease

The prevalence and the incidence of type 2 diabetes (T2D), representing >90% of all cases of diabetes, are increasing rapidly worldwide. Identification of individuals at high risk of developing diabetes is of great importance, as early interventions might delay or even prevent full-blown disease. T2D is a complex disease caused by multiple genetic variants in interaction with lifestyle and environmental factors. Cardiovascular disease (CVD) is the major cause of morbidity and mortality. Detailed understanding of molecular mechanisms underlying in CVD events is still largely missing. Several risk factors are shared between T2D and CVD, including obesity, insulin resistance, dyslipidemia, and hyperglycemia. CVD can precede the development of T2D, and T2D is a major risk factor for CVD, suggesting that both conditions have common genetic and environmental antecedents and that they share “common soil”. We analyzed the relationship between the risk factors for T2D and CVD based on genetics and population-based studies with emphasis on Mendelian randomization studies.