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The Tehran cardiometabolic genetic study (TCGS) is a large population-based cohort study that conducts periodic follow-ups. TCGS has created a comprehensive database comprising 20,367 participants born between 1911 and 2015 selected from four main ongoing studies in a family-based longitudinal framework. The study's primary goal is to identify the potential targets for prevention and intervention for non-communicable diseases that may develop in mid-life and late life. TCGS cohort focuses on cardiovascular, endocrine, metabolic abnormalities, cancers, and some inherited diseases. Since 2017, the TCGS cohort has augmented by encoding all health-related complications, including hospitalization outcomes and self-reports according to ICD11 coding, and verifying consanguineous marriage using genetic markers. This research provides an update on the rationale and design of the study, summarizes its findings, and outlines the objectives for precision medicine.

The Tehran Cardiometabolic Genetic Study (TCGS) is a large population-based cohort study with periodic follow-ups, which created a comprehensive database of 20,367 participants born between 1911-2015 selected from 4 different longitudinal, ongoing, and family-based studies. The study aims to identify the potential targets for prevention and intervention for non-communicable diseases in mid-life and late life. The study focuses on cardiovascular, endocrine, metabolic abnormalities, cancers, and some inherited diseases. Since 2017, the cohort expanded the information by coding all health-related complications (hospitalization outcomes and self-reports) based on ICD11 coding and confirming the consanguineous marriage with genetic markers. This article presents an update on the rationale and design of the study. We also present a summary of our findings and our goals toward precision medicine.

Metabolic syndrome (MetS) is one of the most important risk factors for cardiovascular disease. The 11p23.3 chromosomal region plays a potential role in the pathogenesis of MetS. The present study aimed to assess the association between 18 single nucleotide polymorphisms (SNPs) located at the BUD13, ZPR1, and APOA5 genes with MetS in the Tehran Cardio-metabolic Genetics Study (TCGS). In 5421 MetS affected and non-affected participants, we analyzed the data using two models. The first model (MetS model) examined SNPs' association with MetS. The second model (HTg-MetS Model) examined the association of SNPs with MetS affection participants who had a high plasma triglyceride (TG). The four-gamete rules were used to make SNP sets from correlated nearby SNPs. The kernel machine regression models and single SNP regression evaluated the association between SNP sets and MetS. The kernel machine results showed two sets over three sets of correlated SNPs have a significant joint effect on both models (p –7; HTg-MetS: OR = 1.4, p = 2.3 × 10–11) and the T allele in rs651821 (MetS: OR = 1.3, p = 2.8 × 10–7; HTg-MetS: OR = 1.4, p = 3.6 × 10–11). In the present study, the kernel machine regression models could help assess the association between the BUD13, ZPR1, and APOA5 gene variants (11p23.3 region) with lipid-related traits in MetS and MetS affected with high TG.

Due to the central role in insulin secretion, the potassium inwardly-rectifying channel subfamily J member 11 (KCNJ11) gene is one of the essential genes for type 2 diabetes (T2D) predisposition. However, the relevance of this gene to T2D development is not consistent among diverse populations. In the current study, we aim to capture the possible association of common KCNJ11 variants across Iranian adults, followed by a meta-analysis. We found that the tested variants of KCNJ11 have not contributed to T2D incidence in Iranian adults, consistent with similar insulin secretion levels among individuals with different genotypes. The integration of our results with 72 eligible published case–control studies (41,372 cases and 47,570 controls) as a meta-analysis demonstrated rs5219 and rs5215 are significantly associated with the increased T2D susceptibility under different genetic models. Nevertheless, the stratified analysis according to ethnicity showed rs5219 is involved in the T2D risk among disparate populations, including American, East Asian, European, and Greater Middle Eastern, but not South Asian. Additionally, the meta-regression analysis demonstrated that the sample size of both case and control groups was significantly associated with the magnitude of pooled genetic effect size. The present study can expand our knowledge about the KCNJ11 common variant's contributions to T2D incidence, which is valuable for designing SNP-based panels for potential clinical applications in precision medicine. It also highlights the importance of similar sample sizes for avoiding high heterogeneity and conducting a more precise meta-analysis.

Biological processes involving environmental and genetic factors drive the interplay between age- and sex-regulating lipid profile. The relation between variations in the LPA gene with increasing the risk of coronary heart disease is dependent on population differences, sex, and age. The present study tried to do a gene candidate association analysis in people with myocardial infarction (MI) in a 22 year cohort family-based longitudinal cohort study, Tehran Cardiometabolic Genetic Study (TCGS). After adjusting p value by the FDR method, only the association of rs6415084 with the MI probability and the age-of-CHD-onset was significant in males in their middle age (p LPA and heart disease risk. Our observations may provide new insights into the biology that underlies lipid profile with age or the sexual dimorphism of Lp(a) metabolism. Finally, Lp(a) appears to be an independent risk factor; however, the role of sex and ethnicity is important.

Recent genome-wide association studies (GWAS) highlighted the importance of genetic variations on SLC22A3 and MIA3 genes in developing coronary heart disease (CHD) among different ethnicities. However, the influence of these variations is not recognized within the Iranian population. Hence, in the present study, we aim to investigate two key single nucleotide polymorphisms (SNPs) on CHD incidence in this population. For this purpose, from Tehran Cardiometabolic Genetic Study (TCGS), 453 individuals with CHD were selected as a case and 453 individuals as a control that matched their age and gender. After quality control of two selected SNPs, rs2048327 (SLC22A3) and rs17465637 (MIA3), we used genotyps resulted from chip-typing technology and conducted the logistic regression analysis adjusted for non-genetic risk factors to detect the possible association of these SNPs with the CHD development. Our findings demonstrated the rs2048327-G and rs17465637-C can significantly increase the risk of CHD development about two times in only males and females, respectively. Interestingly, in the male carriers of the risk allele (G) of rs2048327, the low high-density lipoprotein (HDL) level can significantly predispose them to develop coronary heart disease in the future. According to our results, paying more attention to gender and genetic markers can help more efficient coronary heart disease screening and diagnosis.

Obesity is the most crucial phenotype in metabolic syndrome (MetS), and waist circumference (WC) and body mass index (BMI) are two common indexes to define obesity. It is an accepted fact that genetic and environmental interaction influence obesity and MetS. Microsatellites are a subcategory of tandem repeats with a length of 1 to 10 nucleotides. Tandem repeats make up repetitive genomic regions. Differences in the number of tandem repeats or their variation (alleles) result in microsatellite polymorphisms. Thus, we attempted to find microsatellite variation associated with WC and BMI in a family-based study. Twelve microsatellite markers were selected to investigate possible genes or chromosomal regions in 91 families with at least one affected MetS. The cut-off values for BMI and WC were considered 25 kg/m2 and 90 cm, respectively. In all members of the families, the strongest association was observed between the marker D11S1304 (allele 1) with both WC and BMI, independently, by the biallelic model in the family-based association test analysis (P