Integrating Genetic and Conventional Risk Fcators for Improving Coronary Heart Disease Risk Prediction

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Introduction: Coronary heart disease (CHD) is a global health concern, and preventive intervention is available for high-risk individuals. Objectives: The study aims to summarize genetic and conventional risk factor (CRF) modelling studies for CHD risk prediction, assess the performance of risk prediction models, and evaluate the potential improvement by incorporating genetic information. Our study also aims to compare the sociodemographic, and lifestyle factors associated with CHD risk in the Hungarian (Roma and general) populations, estimate the allele frequencies of genetic risk scores (GRSs), and develop new models (by integrating GRS and CRFs) for predicting CHD/AMI risk among the Hungarian populations and assess their performance. Methods: A systematic review and cross-sectional were conducted, utilizing various databases (Embase, PubMed, Cochrane, Web of Science, and Scopus), and multivariable regression analyses (ROC curve analyses were also performed to assess the models' performances). Genetic analyses involved the calculation of GRSs and weighted GRS weres from the genotype data of 558 participants Results: The review identified coronary artery calsification (CAC) as an effective predictor of CHD risk. GRS analysis revealed differences between the general and Roma populations, suggesting higher genetic predisposition among the general population, and greater susceptibility to environmental factors among Roma. Socioeconomic disparities were noted, influencing health outcomes. Roma had a higher prevalence rate of various diseases but differed in certain risk factors like smoking and lipid levels. integration of CRFs and GRSs improved CHD prediction, with age, medication of elevated total cholesterol, and hypertension emerging as significant predictors. Conclusion: Age and cholesterol medication were key predictors for CHD among the general population while hypertension medication was predominant among among the Roma. population. Integrating CRFs and genetic components enhanced predictive performance, emphasizing the importance of comprehensive risk assessment for CHD prevention.

Genetic, Coventional risk Factors, Coronary Heart Disease, Risk Prediction