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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.

Background: Hypertension is one of the most significant underlying ailments of cardiovascular disease; hence, methods that can accurately reveal the risk of hypertension at an early age are essential. Also, one of the most critical personal health objectives is to improve disease prediction accuracy by examining genetic variants. Objective: Therefore, various clinical and genetically based methods are used to predict the disease; however, the critical issue with these methods is the high number of input variables as genetic markers with small samples. One approach that can be used to solve this problem is machine learning. Methods: This study was conducted on participants' genetic markers in 20-year research of cardiometabolic genetics in Tehran (TCGS). Various machine learning methods were used, including linear regression, neural network, random forest, decision tree, and support vector machine. The top ten genetic markers were identified using importance-based ranking methods, including information gain, gain ratio, Gini index, χ², relief, and FCBF. Results: A model based on a neural network with AUC 89% was presented. This model has an accuracy and an f-measure of 0.89, which shows the quality. The final results indicate the success of the machine learning approach.

Fat mass and obesity-associated (FTO) is considered the first locus associated with adiposity, a concerning health problem worldwide. Many studies have evaluated the relationship between the FTO variants and obesity susceptibility. While the strong association of FTO rs1421085 with the risk of obesity across populations was reported in different studies, some researchers found a lack of association of this variant with adiposity. This systematic review and meta-analysis aimed to assess the association between obesity and rs1421085 polymorphism.We systematically searched PubMed, Scopus, and Google Scholar up to June 2022 to find pertinent studies. To further assess this issue, we surveyed the probable association of rs1421085 with obesity development among Iranian adults using the logistic regression analysis, and the obtained results were used for doing meta-analysis. After selection, nine eligible studies were included in the meta-analysis through the random- and fixed-effect models to determine the combined odds ratios (OR) and 95% confidence intervals (CI).According to our meta-analysis conducted on 5169 obese and 7772 non-obese individuals using different genetic models, including recessive, dominant, over-dominant, and additive, rs1421085 could positively increase the risk of obesity under all tested genetic models. Also, we detected a high to moderate level of heterogeneity among different studies under various genetic models.This meta-analysis further verified the positive association of FTO rs1421085 with the risk of developing obesity.This study is registered as PROSPERO CRD42021220092.Level I, systematic reviews and meta-analyses.

BackgroundThe rs2282679 polymorphism in the vitamin D binding protein (DBP) gene may influence the response to vitamin D supplementation. Therefore, we examine the effect of 1-year vitamin D supplementation on vitamin D deficiency (VDD) with the interaction of rs2282679 polymorphism in overweight and obese children and adolescents.Materials and methodsThe participants (n = 300) were part of a randomized controlled trial who received a daily supplement of either 1,000 or 2,000 IU or four supplements of 1,000 IU weekly (equal to 600 IU daily) of vitamin D3 for 12 months. Genotyping was performed using amplification refractory mutation system polymerase chain reaction (ARMS-PCR).ResultsThe mean of 25(OH)D values at baseline for participants with the TT, TG, and GG genotypes were 15.4, 14.4, and 10.8 ng/mL, respectively, and were not different between the three genotype groups (P = 0.062). A significant reduction in VDD was observed after vitamin D supplementation with dosages of 1,000 or 2,000 IU compared to 600 IU. No significant association of genotypes with risk of VDD was observed in each intervention group after vitamin D supplementation, except, that individuals with TG genotype showed a higher risk of VDD compared to those with TT genotype in the 2,000 IU group after 6 months of supplementation [odds ratio (95% CI): 6.94; 1.30–37.02]. We observed no interaction between time duration, three genotypes, and dosages with serum 25(OH)D, calcium, phosphorus, alkaline phosphatase, and parathyroid hormone levels.ConclusionResponse to vitamin D supplementation by three doses of 600, 1,000, and 2,000 IU could not be affected by rs2282679 polymorphism during 12 months in overweight and obese children and adolescents.

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.

High blood pressure is the heritable risk factor for cardiovascular and kidney diseases. Genome-wide association studies(GWAS) on blood pressure traits increase our understanding of its underlying genetic basis. However, a large proportion of GWAS was conducted in Europeans, and some roadblocks deprive other populations to benefit from their results. Iranians population with a high degree of genomic specificity has not been represented in international databases to date, so to fill the gap, we explored the effects of 652,919 genomic variants on Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Hypertension (HTN) in 7694 Iranian adults aged 18 and over from Tehran Cardiometabolic Genetic Study (TCGS). We identified consistent signals on ZBED9 associated with HTN in the genome-wide borderline threshold after adjusting for different sets of environmental predictors. Moreover, strong signals on ABHD17C and suggestive signals on FBN1 were detected for DBP and SBP, respectively, while these signals were not consistent in different GWA analysis. Our finding on ZBED9 was confirmed for all BP traits by linkage analysis in an independent sample. We found significant associations with similar direction of effects and allele frequency of genetic variants on ZBED9 with DBP (genome-wide threshold) and HTN (nominal threshold) in GWAS summary data of UK Biobank. Although there is no strong evidence to support the function of ZBED9 in blood pressure regulation, it provides new insight into the pleiotropic effects of hypertension and other cardiovascular diseases.

This study aimed to investigate the interaction of the Healthy eating index (HEI) and the dietary approach to stop hypertension (DASH) diets with FTO polymorphisms in relation to obesity traits. A total of 4480 subjects aged ≥18 years were selected from participants of the Tehran Lipid and Glucose Study and followed-up 3 years. Selected polymorphisms (rs1421085, rs1121980, rs8050136) were genotyped. HEI and DASH scores were computed. The interaction of diet quality scores with FTO gene variants concerning changes in body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR) and visceral adiposity index (VAI) was assessed. Higher adherence to both DASH and HEI diets were seen in older adults. Individuals with minor allele carriers of rs1121980 had a lower change in BMI when they had higher adherence to HEI, compared to subjects with lower HEI score (P trend=0.01). Change in WC in participants in the fourth quartile of HEI score in minor allele carriers of FTO variants was lower compared to the first quartile. No significant interaction was seen between FTO genetic variations and DASH and HEI diets regarding changes in any of obesity indices. Adherence to HEI and DASH diets modified the association between FTO genetic variations and obesity phenotypes. In minor allele (risk allele) carriers of FTO polymorphisms, low change in BMI and WC were seen with high adherence to the HEI. Conversely, high adherence to the DASH diet by this genotypic group was related to increase WC.

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.

The long non‐coding RNAs (lncRNAs) play a critical regulatory role in the host response to the viral infection. However, little is understood about the transcriptome architecture, especially lncRNAs pattern during the SARS‐CoV‐2 infection. In the present study, using publicly available RNA sequencing data of bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells (PBMC) samples from COVID‐19 patients and healthy individuals, three interesting findings highlighted: (a) More than half of the interactions between lncRNAs‐PCGs of BALF samples established by three trans‐acting lncRNAs (HOTAIRM1, PVT1 and AL392172.1), which also exhibited the high affinity for binding to the SARS‐CoV‐2 genome, suggesting the major regulatory role of these lncRNAs during the SARS‐CoV‐2 infection. (b) lncRNAs of MALAT1 and NEAT1 are possibly contributed to the inflammation development in the SARS‐CoV‐2 infected cells. (c) In contrast to the 3′ part of the SARS‐CoV‐2 genome, the 5′ part can interact with many human lncRNAs. Therefore, the mRNA‐based vaccines will not show any side effects because of the off‐label interactions with the human lncRNAs. Overall, the putative functionalities of lncRNAs can be promising to design the non‐coding RNA‐based drugs and to inspect the efficiency of vaccines to overcome the current pandemic.

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.

In recent decades, ongoing GWAS findings discovered novel therapeutic modifications such as whole-genome risk prediction in particular. Here, we proposed a method based on integrating the traditional genomic best linear unbiased prediction (gBLUP) approach with GWAS information to boost genetic prediction accuracy and gene-based heritability estimation. This study was conducted in the framework of the Tehran Cardio-metabolic Genetic study (TCGS) containing 14,827 individuals and 649,932 SNP markers. Five SNP subsets were selected based on GWAS results: top 1%, 5%, 10%, 50% significant SNPs, and reported associated SNPs in previous studies. Furthermore, we randomly selected subsets as large as every five subsets. Prediction accuracy has been investigated on lipid profile traits with a tenfold and 10-repeat cross-validation algorithm by the gBLUP method. Our results revealed that genetic prediction based on selected subsets of SNPs obtained from the dataset outperformed the subsets from previously reported SNPs. Selected SNPs’ subsets acquired a more precise prediction than whole SNPs and much higher than randomly selected SNPs. Also, common SNPs with the most captured prediction accuracy in the selected sets caught the highest gene-based heritability. However, it is better to be mindful of the fact that a small number of SNPs obtained from GWAS results could capture a highly notable proportion of variance and prediction accuracy.

Background Previous studies reported that common functional variants (rs780093, rs780094, and rs1260326) in the glucokinase regulator gene (GCKR) were associated with metabolic syndrome despite the simultaneous association with the favorable and unfavorable metabolic syndrome components. We decided to evaluate these findings in a cohort study with a large sample size of Iranian adult subjects, to our knowledge for the first time. We investigated the association of the GCKR variants with incident MetS in mean follow-up times for nearly 10 years. Methods Analysis of this retrospective cohort study was performed among 5666 participants of the Tehran Cardiometabolic Genetics Study (TCGS) at 19–88 years at baseline. Linear and logistic regression analyses were used to investigate the metabolic syndrome (JIS criteria) association and its components with rs780093, rs780094, and rs1260326 in an additive genetic model. Cox regression was carried out to peruse variants’ association with the incidence of metabolic syndrome in the TCGS cohort study. Results In the current study, we have consistently replicated the association of the GCKR SNPs with higher triglyceride and lower fasting blood sugar levels (p Conclusions Elevated triglyceride levels had the strongest association with GCKR selected variants among the metabolic syndrome components. Despite the association of these variants with decreased fasting blood sugar levels, T alleles of the variants were associated with metabolic syndrome incidence; so whether individuals are T allele carriers of the common functional variants, they have a risk factor for the future incidence of metabolic syndrome.

This study is the first study that aims to assess the association between SNPs located at the PPARG gene with long term persistent obesity. In this cohort association study, all adult individuals who had at least three consecutive phases of BMI (at least nine years) in Tehran genetic Cardio-metabolic Study (TCGS) were included. Individuals who always had 30 ≤ BMI

Backgrounds This randomized controlled trial aimed to investigate the effects of replacing red meat with legumes in the dietary approach to stop hypertension (DASH) diet on inflammatory markers over 16 weeks in overweight and obese individuals with type 2 diabetes. Also, the modulatory effects of TCF7L2 rs7903146 variant on this effect were assessed. Methods In this trial, 300 participants with type 2 diabetes, aged 30–65 years with an identified TCF7L2 rs7903146 genotype, were studied. The participants were randomly assigned to the DASH diet or the legume-based DASH diet over 16 weeks. In the DASH diet group, the participants were instructed to follow the standard DASH diet. The legume-based DASH diet was similar to the standard DASH diet, with the exception that one serving of red meat was replaced with one serving of legumes at least five days a week. At the beginning of the study and 16-week follow-up, venous blood samples were collected from all participants who fasted for 12–14 h overnight. The serum concentration of High-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) was measured using an enzyme-linked immunosorbent assay (ELISA) kit. Also, the serum malondialdehyde (MDA) concentration was assessed based on a colorimetric method using a commercial kit. The primary outcome was the difference in hs-CRP changes between the diets. A secondary outcomes was the difference in IL-6, TNF-α, and MDA between the groups among total population and based on TCF7L2 rs7903146 risk allele (CT + TT) and non-risk allele (CC) separately. Results The hs-CRP level reduced in the legume-based DASH diet group as compared to the DASH diet group in the 16-week follow-up group. The levels of TNF-α, IL-6, and MDA reduced after the legume-based DASH diet relative to the DASH diet. Reduction of inflammatory markers was observed in both carriers of rs7903146 risk allele and non-risk allele. Conclusions Substituting one serving of red meat with one serving of legumes in DASH diet, at least five days a week, could improve the hs-CRP, TNF-α, IL-6, and MDA in participants with type 2 diabetes regardless of having rs7903146 risk or non-risk allele. Trial registration IRCT, IRCT20090203001640N17.

Background This study aimed to investigate the effects of legumes in dietary approaches to stop hypertension (DASH) on blood pressure and urinary sodium and potassium in participants with type 2 diabetes. We further investigated whether changes in individual dietary food groups in the DASH diet contribute to blood pressure. Methods Participants were randomized to the traditional DASH diet (n = 150) or the legume-based DASH diet (n = 150). Blood pressure and urinary sodium and potassium were measured at baseline and after 16-week interventions. An intention-to-treat approach with multiple imputations of missing data was applied. The restricted cubic spline (RCS) was applied to assess the linearity and explore the shape of the relationship between the changes in food groups and systolic blood pressure (SBP) in the two intervention groups. Results A reduction in SBP and urinary sodium was observed at week 16 in both dietary interventions, and this reduction was more significant in the legume-based DASH diet, than in the DASH diet. In the legume-based DASH diet, SBP decreased with the legume intake of more than 95.8 g/day (P nonlinear Conclusions The DASH diet, enriched in legumes, could improve SBP in participants with type 2 diabetes. In DASH diet, the balance of consumption of refined grains and fruits along with higher vegetable consumption and lower sweet, sodium and energy intake reduced the SBP. Trial registration: IRCT20090203001640N17.

Background Obesity is a major public health concern in developed and even developing countries worldwide. Adiponectin is a protein secreted by adipose tissue that modulates many metabolic processes and plays a vital role in obesity. This study aimed to determine the association of four variants of the ADIPOQ gene with serum adiponectin, cortisol levels and obesity status. Methods This case-control study was performed on 164 obese individuals compared by 156 control from the Tehran Lipid and Glucose Study (TLGS). Standard procedures obtained anthropometric measures and metabolic parameters. Cortisol and adiponectin levels were measured by ELISA method. rs1501299, rs266729, rs17300539, and rs17366743 on the ADIPOQ gene were genotyped using the PCR-RFLP. The correlation between adiponectin gene SNPs and obesity were calculated by Additive, dominant, and recessive genetic models. Pearson’s or Spearman’s found correlations between adiponectin levels and metabolic and anthropometric variables. Data were analyzed using SPSS software Version 20. Results Adiponectin and cortisol levels were significantly lower in obese subjects compared to the control group (p r = − 0.147, r = − 0.324, r = 0.371, r = − 0.179, r = − 0.299, r = − 0.277, r = − 0.041, r = − 0.134, and r = − 0.149, respectively). A positive correlation was found between adiponectin and high-density lipoprotein cholesterol (HDL-C) (r = 0.29), but no significant correlations were found between adiponectin and Low-density lipoprotein cholesterol(LDL-C) and cortisol. ADIPOQ variant rs1501299 was significantly associated with cortisol levels in subjects with BMI ≥ 25 (P-value =0.039). Conclusions Adiponectin and cortisol levels were associated with obesity. No ADIPOQ gene variants and haplotypes were associated with cortisol, Adiponectin, and obesity.

Introduction Data shows that interactions between dietary factors and genetic variants can modulate the association of polymorphisms such as the Melanocortin-4 receptor (MC4R) gene with obesity. Considering the limited data available on this topic we aimed to investigate interactions between dietary patterns (DPs) and MC4R polymorphisms in relation to obesity phenotypes. Methods This cohort study was performed in the framework of Tehran Lipid and Glucose Study; for eligible participants in this study (n = 3850), the median follow-up was 4 years. DPs were determined using factor analysis. The genotypes of polymorphisms (17782313rs and 12970134rs) were identified and their interaction with DPs were assessed in relation to incidence of obesity phenotypes including central obesity, general obesity and visceral adiposity dysfunction. Results The mean age of participants (62.5% females) were 37.0 ± 13.7 years. Two main DPs (healthy and unhealthy) were extracted. C-allele carriers of rs17782313 in higher quartiles of the healthy DP score had a significant decrease in the incidence of general obesity, compared to those who had the TT genotype (HR = 0.61, 95% CI = 0.42–0.89, P interaction = 0.01). For rs12970134 A-allele carriers, subjects in the second compared to the first quartile of the healthy DP score, had a significant decrease in the incidence of general obesity (HR = 0.68, 95% CI = 0.46–0.99). There were no significant interaction between DPs and MC4R variants in relation to other obesity phenotypes. Conclusion Our results indicate that the healthy DP could interact with rs17782313 in relation to incidence of general obesity.

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.

Background: This study aimed to assess the genetic association between Apolipoprotein E (APOE) polymorphisms and susceptibility to metabolic syndrome (MetS) among the Tehran cardiometabolic genetic study (TCGS) participants. The results were then compared with similar studies in other populations using meta-analysis. Methods: the metabolic syndrome was defined according to the Joint Interim Statement (JIS) criteria. A total of 12282 subjects (5696 cases with metabolic syndrome and 6586 healthy controls) were genotyped using Human OmniExpress-24-v1-0 BeadChip. Subsequently, PubMed, Scopus, and Google Scholar databases were searched using relevant Medical Subject Headings (MeSH) terms to collect all studies that examined the association between polymorphisms of the APOE gene and risk of MetS. Results: the presence of the APOE-ε4 allele could not significantly increase the risk of MetS in the carriers of this allele compared to individuals lacking the risk allele in the TCGS population (OR = 1.11, 95% CI: 0.92 to 1.32). The meta-analysis results also indicated no significant association between the APOE-ε 4 allele and the risk of MetS. Conclusion: the frequency of the ε4 allele was almost same in the cases and the controls. Therefore, this allele cannot be considered as biomarker to predict the MetS susceptibility in the TCGS population or other populations with different genetic pools.

Morbid obesity could last for a long period of life and increase the risk of morbidity as well as premature mortality. Although bariatric surgery benefits patients by quick weight loss, not all bariatric patients lose the same percentage of weight after a long time from surgery, which may be the result of diet, physical activity, and genetic components. In this study, we evaluated the association between the MC4R gene and both excess weight loss percentage (EWL%) and excess BMI loss percentage (EBMIL%) in a cohort of bariatric surgery patients after 6 and 12 months from surgery. A total of 424 bariatric surgery patients who had participated in the Tehran Obesity Treatment Study and had weight measurements after 6 and 12 months from surgery were included in the study. Four SNPs in the MC4R gene were selected for evaluating the associations. We found that rs17773430 had a significant effect on both EWL% and EBMIL%, especially after 12 months of bariatric surgery. Furthermore, three other SNPs, rs17782313, rs476828, and rs11152213, did not show any significant association with EWL% and EBMIL%. This study was the first to report on the association of rs17773430 with both EWL% and EBMIL% in a cohort of patients after bariatric surgery. We found that weight loss after surgery is influenced by genetic factors, and there were significant differences between the distribution of EWL% and EBMIL% in morbid obese bariatric patients who have two minor alleles of the rs17773430 and other SNPs.

Objective Dietary total antioxidant capacity (DTAC) has been hypothesized as being involved in health promotion and disease prevention. However, data about the association of the DTAC (as estimated by ferric reducing antioxidant power) with diabetes chronic complications are scarce. Therefore, the aim of this study was to determine the associations between the DTAC and chronic kidney disease (CKD) risk in subjects with type 2 diabetic. Methods The present case-control study consisted of 210 (102 cases and 108 controls) patients with type 2 diabetic who were participants of the phase 5 Tehran Lipid and Glucose Study and were classified based on their CKD status. DTAC was estimated based on the ferric reducing antioxidant power of selected foods. Dietary intake, sociodemographic data, medical history, and anthropometric measurements were collected from participants using a validated questionnaire. Results The mean DTAC value, as well as total calorie intake, did not show significant differences between cases and controls. Conclusion No significant association was found between DTAC and CKD in patients with type 2 diabetic. Further studies are needed to confirm the effects of DTAC on the risk of CKD.

Structural equation modeling (SEM) is a powerful, comprehensive, and flexible multivariate statistical method for modeling relationships between observed and latent variables. However, in genetic association analysis, frequentist approaches to fitting SEMs do not always lead to convergence and admissible solutions for complex models, categorical variables, complicated data structures such as pedigree data and small sample sizes. Accordingly, to conduct a SEM pedigree data analysis, Stan platform as a probabilistic programming language was applied in our study to propose a new version of the Bayesian approach that adopts Hamiltonian Monte Carlo (HMC) and data augmentation techniques. At first, a comprehensive simulation study was conducted to compare the precision of each parameter of the suggested method with that of the classic technique in terms of bias, alpha error rate, and coverage probability. After that, the method was applied to real data with a conceptual model including ordinal indicators in order to conduct genetic association analysis of two well-known genetic markers with metabolic syndrome trait. The simulation findings revealed the proposed Bayesian method was a more efficient technique than MLE approach. Moreover, Bayesian approach yielded a better statistical performance in solving the problems than did classic approach. © 2019 Wiley Periodicals, Inc.

Background and aims The results of studies on the effect of trans-fatty acids (TFAs) and added sugars on obesity are not consistent. This study aimed to investigate whether the association of changes in general and central obesity with added sugar and TFA intakes is modified by common fat mass and obesity-associated gene (FTO) polymorphisms, in isolation or in a combined-form genetic risk score (GRS). Methods and results Subjects of this cohort study were selected from among adult participants of the Tehran Lipid and Glucose Study (n = 4292, 43.2% male). Dietary data were collected using a valid and reliable food frequency questionnaire. The genotypes of selected polymorphisms (rs1421085, rs1121980, and rs8050136) were determined. Genetic risk score (GRS) was calculated using the dominant weighted method. The mean age of participants was 42.6 ± 14 and 40.4 ± 13 years in men and women, respectively. FTO rs8050136 polymorphisms and TFAs have a significant interaction in changing body mass index (BMI) (P interaction = 0.01). There were no changes in waist circumference (WC) and BMI among FTO risk allele carriers, across quartiles of added sugar intake. GRS and TFA intakes significantly interacted in altering the BMI and WC; thus, a higher intake of TFAs was associated with higher changes of BMI and WC in subjects with high GRS (P trend Conclusion Our findings suggest that TFA intake can increase the genetic susceptibility of FTO SNPs to BMI or WC change.

A number of genome-wide association studies (GWASs) have identified several genetic determinants of plasma lipids in European populations, in which analytical approaches have often been based on the linear regression models and the association test between a SNP and each lipid component individually in cross-sectional designs. Since lipid variations are correlated, the consideration of pleiotropy is necessary and using methods that can perform simultaneous association test of multiple longitudinal traits provides more information about the recognition of the pleiotropic variants. To identify new pleiotropic variants and to determine whether loci identified in previous GWASs can also exert the same effect on lipid concentrations in Iranian population, longitudinal measurements of lipid variations were used in a sample of Iranian population (16,353 individuals within 3100 families) that followed up every 3 years and using a two-step model, the associations of 20,036 available SNPs on chromosome 16 were assessed. Twenty variants within the AC009035.1, SLC12A3, CETP, NLRC5, ESRP2 and, C16orf95 genes showed strong evidence for association with HDL-C, cholesterol, and triglycerides with p-values ranging from 1.7 × 10−102 to 6.6 × 10−5. Since many genetic variants associated with lipids still remain to be determined, the results of the present study may provide valuable information on identifying the associations of new genetic loci with lipid variations in other populations.

Backgroung: Hypertension is typically considered as the leading risk factor for cardiovascular disease. Epistasis studies may add another layer of complexity to our understanding of the genetic basis of hypertension. Methods: A nested case-control design was used on 4214 unrelated Tehran Cardiometabolic Genetic Study (TCGS) adults to evaluate 65 SNPs of previously associated genes, including ZBED9, AGT, and TNXB. The integrated effect of each gene was determined using the Sequence-based Kernel Association Test (SKAT). We used model-based multifactor dimension reduction (Mb-MDR) and entropy-based gene-gene interaction (IGENT) methods to determine interaction and epistasis patterns. Results: The integrated effect of each gene has a statistically significant association with blood pressure traits (P-value < 0.05). Single-locus analysis identified two missense variants in ZBED9 (rs450630) and AGT (rs4762) that are associated with hypertension. In the ZBED9 gene, significant local interactions were discovered. The G allele in rs450630 showed an antagonistic effect on hypertension, but interestingly, IGENT analysis revealed significant epistasis effects for different combinations of ZBED9, AGT, and TNXB loci. Conclusion: We discovered a novel interaction effect between a significant variant in an essential gene for hypertension (AGT) and a missense variant in ZBED9, which has shifted our focus to ZBED9's role in blood pressure regulation.

This population-based longitudinal study is the first investigation that assesses the association of common MC4R SNPs with the obesity-related parameters over time and determines the effect of risk alleles during the three adulthood life periods (early, middle, and late) in a large Iranian cohort, a population with a unique genetic make-up that has been understudied and relatively unexplored. We obtained the genotype of 5370 unrelated adults who participated in the ongoing Tehran Cardiometabolic Genetic Study (TCGS) cohort project for the common MC4R SNPs. Linear regression and linear mixed model analyses were performed to examine the effect of MC4R polymorphisms on maximum BMI and other obesity-related factors over time. We recognized that several SNPs associated with the maximum BMI and the increased BMI, waist circumference, and waist-hip ratio across Iranian adults over a lifetime. Interestingly, we found that rs9954571-A has a yet unreported protective role against obesity-related factors, including BMI, waist circumference, waist-hip ratio, and triglyceride level. Additionally, a survey of the impact of the MC4R risk score throughout the adulthood life periods indicated that the MC4R risk score is influenced both the elevated BMI and waist circumference only during the early adulthood period. Our findings can expand our knowledge about the MC4R genetic variant's contributions to adulthood obesity and highlight the importance of evaluating the genetic components affecting obesity over a lifetime, which could be considered for obesity clinical screening and treatment.

High blood pressure is the heritable risk factor for cardiovascular diseases. We investigated whether the presence of familial genetic and environmental risk factors are associated with increased risk of high blood pressure.A total of 4,559 individuals from 401 families were included in this study. Familial aggregation analysis was carried out on systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI) and waist circumference (WC), and heritability was estimated for SBP and DBP. The association between familial risk factors and blood pressure traits including, incidence of hypertension, SBP and DBP was estimated separately using regression-based two-level Haseman-Elston (HE) method, with individual and familial BMI and WC as environmental exposures and familial genetic profile of known variants as genetic risk factors in 210 index families (≥2 hypertensive cases). Models were adjusted for the two nested sets of covariates.During a follow-up of 15 years, the SBP, DBP, BMI and WC were highly correlated in inter class of mother-offspring and intraclass of sister-sister with heritability of 30 and 25% for DBP and SBP, respectively. Among index families, those whose members with higher familial BMI or WC had significantly increased risk of hypertension and consistent, strong signals of rs2493134 (Findings from this study show that familial genetic and environmental risk profile increase risk for high blood pressure beyond the effect of the individuals' own risk factors.

The current study aimed to evaluate the interaction of the dietary diversity score (DDS) and FTO polymorphisms concerning obesity phenotypes. The 4480 subjects of this cohort study were selected. The polymorphisms rs1121980, rs14211085 and rs8050136 were selected and genotyped. The weighted method was used to calculate the genetic risk score (GRS). Obesity marker changes were calculated. Those with minor allele carriers of rs1121980 had lower body mass index changes

Background: Comparison of LASSO, smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP) logistic classifiers in order to reconnaissance of related genes with COPD disease and assessing the genes effects on the progression of the disease based on one of the main classes of cells involved in the disease, Sputum Cells. We used a genome-wide expression profiling to define gene networks relevant to the disease. The data retrieved from Gene Expression Omnibus (GEO) with accession numbers "GSE22148". From 143 samples in GOLD stage 2-4 COPD ex-smokers, 54,675 probes primary were assessed. After normalization, LASSO, SCAD and MCP logistic regressions were applied. K-fold cross-validation scheme was used to evaluate the performance of two methods. All of the computational processes were done using "ncvreg", "Affy," "Limma" and "SVA" R packages. Results: The results of LASSO (AUC=0.95, sensitivity= 0.91, specificity= 0.86) and SCAD (AUC=0.97, sensitivity= 0.95, specificity= 0.85) logistic regression were almost similar. There were 23 and 22 significantly associated genes for LASSO and SCAD, respectively. The only difference between these models is related to "stromal interaction molecule 2". Comparing to MCP approach, the most conservative method, we detected only 7 significant genes (AUC= 0.94, sensitivity= 0.94, specificity= 0.82). Conclusions: In the present study, the relative expressions of thousands of the genes were assessed and identified as associated genes with the progression of COPD. Differential analysis of gene expression data is able to reduce the number of genes but in a limited manner. In order to find an efficient and small subset of genes, we should use alternative approaches like logistic regression. Regularization solves the high dimensionality problem in using this kind of regression.

This study is the first to evaluate familial aggregation, heritability and inheritance mode of type 2 diabetes (T2D) in Tehran Lipid Glucose Study (TLGS) participants as a representative sample of the Iranian population.From the ongoing family-based TLGS cohort, 13,741 individuals at least 20 years of age (mean ± standard deviation, 39.71±16.56) were assessed. After correcting family structures using genomic information from the Tehran Cardiometabolic Genetic Study, 2,594 constituent pedigrees were constructed. Familial aggregation was assessed based on genealogic index testing, familial intraclass correlation and positive family history. Family-based heritability was checked with 2 linear mixed models, including 2 different random components: the kinship matrix and the genomic relationship matrix. The mode of inheritance of T2D was investigated by complex segregation analysis (CSA).Familial aggregation of T2D was significant (p0.05), and family-based heritability showed a high degree of genetic variation in T2D between individuals at 65% (standard error, 0.034). Within first-degree relatives (parent/offspring and siblings), the likelihood of a parental affect was higher than in siblings (odds ratio, 4.11 vs 1.65). Family history of T2D among first-degree relatives was more noteworthy than for second-degree relatives (odds ratio, 3.84 vs 0.59). CSA revealed that the polygenic model is best to illustrate the mode of inheritance of T2D for TLGS participants.Our findings demonstrate that the heritability of T2D with polygenic mode in the Iranian population is higher than the global average. We also found that T2D is transmitted equally into siblings, with parental affect the leading risk factor. These data suggest that policymakers should change individual-level to family-level prevention.

Background: Current GWAS discoveries have discovered novel clinical improvements in recent decades, such as estimating whole-genome risk. Genetic prediction of traits has substantial impacts on public health care and disease prevention. This study aimed to investigate the effects of different linkage disequilibrium (LD) patterns on genomic prediction accuracy and SNP-based heritability estimation for four lipid profile traits.Results: This family-based study included 11,798 individuals ranging from 3 to 80 ys, extracted from Tehran Cardiometabolic Genetic Study (TCGS). LD patterns were considered on different thresholds (0.01, 0.03, 0.05, 0.07, 0.09, 0.1, 0.2, 0.3, 0.5, 0.6, 0.7, 0.8, and 0.9) to create subsets of SNPs. We have compared the prediction accuracy and SNP-based heritability estimation of the selected SNPs within these patterns as well as randomly selected SNPs with equal sizes. Subsets of SNPs selected based on LD patterns had a higher prediction accuracy level than subsets of SNPs selected randomly, and when the LD threshold increases, the difference tends to zero. The results were consistent when the prediction accuracy of subsets were adjusted for their SNP numbers in all traits. For all traits, when the number of SNPs was adjusted, between LD threshold 0.01 and 0.2, both prediction accuracy and SNP-based heritability have a dramatic rise. After substantial growth, there was a steady decline, and they reach a peak at an LD threshold between 0.2 and 0.3.Conclusions: This research indicated that having selected subsets of SNPs based on the LD threshold always outperform randomly selected SNPs for prediction objectives. However, determining the specific LD threshold for prediction purposes might be controversial since achieving the highest level of prediction accuracy, when the number of SNPs is adjusted, prompts different results (in our case, 0.3 when the SNP number was adjusted and 0.9 when the SNP number is not adjusted). Finally, we concluded that choosing the LD threshold as a tool to boost genetic prediction accuracy should be used with intense care.

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.

Obese individuals can be categorized as “healthy obese” (MHO) and “unhealthy obese” (MUO) based on the presence or absence of metabolic abnormality. This study sets out to assess potential genetic causes behind persistence of healthy metabolic status in individuals categorized as “healthy obese”. This study was conducted in the framework of the Tehran cardio-metabolic genetic study (TCGS). 766 MHO subjects at the start of the study followed up 15 years for occurrence of metabolic unhealthy status. These two groups (persistent MHO, MUO) were compared regarding the presence or absence of 16 single nucleotide polymorphisms (SNPs) identified as being associated with obesity phenotype in previous studies. We used logistic regression model for assessing the association between MHO/MUO with candidate SNPs. By the end of the follow up, 206 (27%) were categorized as the persistent MHO and 560 (73%) as MUO groups. Considering interaction effect between some SNP and sex, a sex stratification analysis was applied. When the analysis was performed by gender, rs1121980 associated with a decrease, and rs7903146 with an increase in the likelihood of persistent MHO individuals. Another analysis was separately performed on postmenopausal women from both groups; it showed that rs13107325 was associated with an increase in the likelihood of persistent MHO status in this subgroup of woman. In all cases, the markers had dominant inheritance. This findings suggest that the expression of some genetic markers are associated with persistence of healthy metabolic status, in female obese individuals.

Type 2 diabetes (T2D) is emerging as one of the serious public health issues in both developed and developing counties. Here, we surveyed the worldwide population differentiation in T2D-associated variants and assessed the genetic burden of the disease in an ongoing Tehran Cardio-Metabolic Genetic Study (TCGS) cohort represented the Iranian population. We found multiple SNPs that were significantly depleted or enriched in at least one of the five populations of 1,000 Genome Project (African, American, East Asian, European, and South Asian) as well as the Iranian population. Interestingly, TCF7L2, a well-known associated gene with T2D, harbors the highest number of enriched risk alleles almost in all populations except for East Asian, where this gene embraces the largest number of significantly depleted risk alleles. The polygenic risk score (PRS) of the enriched risk alleles was calculated for 1,867 diabetic and 2,855 non-diabetic participants in the TCGS cohort, interestingly demonstrating that the risk of developing T2D was almost two times higher in top PRS quintile compared with the lowest quintile after adjusting for other known risk factors.

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

Background The aim of this study was to investigate whether two variants of the TCF7L2 (rs7903146 and rs12255372) modify the association between nut consumption and the risk of metabolic syndrome (MetS). Additionally, the modifying effect of weight change during follow-up on these associations was investigated. Material and methods We prospectively studied 1423 participants of the Tehran Lipid and Glucose study aged 19–74 years who were followed-up for dietary assessment using a validated, semi-quantitative food frequency questionnaire. Multivariable-adjusted Cox regression was used to estimate hazard ratios (HRs) for MetS events. Genotyping was performed by Human Omni Express-24-v1-0 chip. Results Over a median 8.9 years of follow-up, 415 new cases of MetS were documented. The median nut consumption was 20.0 g/week (Interquartile Range (IQR): 8.6–38.9 g/week). Regarding the rs7903146 genotype, in carriers of T allele (CT + TT), highest tertile of nut consumption was associated with a reduced risk of MetS after adjusting for confounders (HR: 0.67 (0.50–0.91)). Regarding the rs12255372 genotype, highest versus lowest tertile of nut consumption in participants with T allele (GT + TT) resulted in 34% reduction of MetS risk after adjustment for confounders (HR: 0.66 (0.49–0.69)). After stratification by weigh change ( Conclusion Higher consumption of nuts may reduces the risk of MetS in T-risk allele of the TCF7L2 rs7903146 and rs12255372 variants and weight change may modify this association.