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Dyslipidemia, as a metabolic risk factor, with the strongest and most heritable independent cause of cardiovascular diseases worldwide. We investigated the familial transmission patterns of dyslipidemia through a longitudinal family-based cohort, the Tehran Cardiometabolic Genetic Study (TCGS) in Iran. We enrolled 18,729 individuals (45% were males) aged > 18 years (mean: 38.15 (15.82)) and observed them over five 3-year follow-up periods. We evaluated the serum concentrations of total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol with the first measurement among longitudinal measures and the average measurements (AM) of the five periods. Heritability analysis was conducted using a mixed-effect framework with likelihood-based and Bayesian approaches. The periodic prevalence and heritability of dyslipidemia were estimated to be 65.7 and 42%, respectively. The likelihood of an individual having at least one dyslipidemic parent reveals an OR = 6.94 (CI 5.28–9.30) compared to those who do not have dyslipidemic parents. The most considerable intraclass correlation of family members was for the same-sex siblings, with ICC ~ 25.5%. For serum concentrations, heritability ranged from 33.64 to 60.95%. Taken together, these findings demonstrate that familial transmission of dyslipidemia in the Tehran population is strong, especially within the same-gender siblings. According to previous reports, the heritability of dyslipidemia in this population is considerably higher than the global average. [ABSTRACT FROM AUTHOR]

This study aimed at modelling the underlying predictor of ASCVD through the Bayesian network (BN). Data for the AZAR Cohort Study, which evaluated 500 healthcare providers in Iran, was collected through examinations, and blood samples. Two BNs were used to explore a suitable causal model for analysing the underlying predictor of ASCVD; Bayesian search through an algorithmic approach and knowledge-based BNs. Results showed significant differences in ASCVD risk factors across background variables' levels. The diagnostic indices showed better performance for the knowledge-based BN (Area under ROC curve (AUC) = 0.78, Accuracy = 76.6, Sensitivity = 62.5, Negative predictive value (NPV) = 96.0, Negative Likelihood Ratio (LR−) = 0.48) compared to Bayesian search (AUC = 0.76, Accuracy = 72.4, Sensitivity = 17.5, NPV = 93.2, LR− = 0.83). In addition, we decided on knowledge-based BN because of the interpretability of the relationships. Based on this BN, being male (conditional probability = 63.7), age over 45 (36.3), overweight (51.5), Mets (23.8), diabetes (8.3), smoking (10.6), hypertension (12.1), high T-C (28.5), high LDL-C (23.9), FBS (12.1), and TG (25.9) levels were associated with higher ASCVD risk. Low and normal HDL-C levels also had higher ASCVD risk (35.3 and 37.4), while high HDL-C levels had lower risk (27.3). In conclusion, BN demonstrated that ASCVD was significantly associated with certain risk factors including being older and overweight male, having a history of Mets, diabetes, hypertension, having high levels of T-C, LDL-C, FBS, and TG, but Low and normal HDL-C and being a smoker. The study may provide valuable insights for developing effective prevention strategies for ASCVD in Iran. [ABSTRACT FROM AUTHOR]