👤 Tahmineh Akbarzadeh

Metabolic syndrome (MetS) is a complex multifactorial disorder that considerably burdens healthcare systems. We aim to classify MetS using regularized machine learning models in the presence of the risk variants of A cohort study was conducted on 2,346 cases and 2,203 controls from eligible Tehran Cardiometabolic Genetic Study (TCGS) participants whose data were collected from 1999 to 2017. We used different regularization approaches [least absolute shrinkage and selection operator (LASSO), ridge regression (RR), elasticnet (ENET), adaptive LASSO (aLASSO), and adaptive ENET (aENET)] and a classical logistic regression (LR) model to classify MetS and select influential variables that predict MetS. Demographics, clinical features, and common polymorphisms in the During the follow-up period, 50.38% of participants developed MetS. The groups were not similar in terms of baseline characteristics and risk variants. MetS was significantly associated with age, gender, schooling years, body mass index (BMI), and alternate alleles in all the risk variants, as indicated by LR. A comparison of accuracy, AUCROC, and AUC-PR metrics indicated that the regularization models outperformed LR. Regularized machine learning models provided comparable classification performances, whereas the aLASSO model was more parsimonious and selected fewer predictors. Regularized machine learning models provided more accurate and parsimonious MetS classifying models. These high-performing diagnostic models can lay the foundation for clinical decision support tools that use genetic and demographical variables to locate individuals at high risk for MetS. Show less

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. Show less

Cinnamomum verum J. Presl. (Lauraceae), Myrtus communis L. (Myrtaceae), Ruta graveolens L. (Rutaaceae), Anethum graveolens L. (Apiaceae), Myristica fragrans Houtt. (Myristicaceae), and Crocus sativus L. (Iridaceae) have been recommended for improvement of memory via inhalation, in Iranian Traditional Medicine (ITM). In this respect, the essential oils (EOs) from those plants were obtained and evaluated for cholinesterase (ChE) inhibitory activity as ChE inhibitors are the available drugs in the treatment of Alzheimer's disease (AD). EOs obtained from the plants under investigation, were evaluated for their potential to inhibit acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) in vitro based on the modified Ellman's method. The most potent EO was candidate for the investigation of its beta-secretase 1 (BACE1) inhibitory activity and neuroprotectivity. Among all EOs, C. verum demonstrated the most potent activity toward AChE and BChE with IC Potent BChE inhibitory activity of C. verum EO can be considered in the development of cinnamon based dietary supplements for the management of patients with advanced AD. Show less

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. 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. 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. Our results indicate that the healthy DP could interact with rs17782313 in relation to incidence of general obesity. Show less

Obesity is currently an international epidemic and metabolic derangements pose these individuals at greater risk for future morbidity and mortality. Genetics and environmental factors have undeniable effects and among genetic risk factors, FTO/CETP genes are important. The current study examines the interaction between obesity phenotypes and FTO/CETP SNPs and their effects on lipid profile changes. We selected 954 adult subjects from TCGS (47.9% male). Participants were stratified according to their BMI and presence of metabolic syndrome according to the Joint Interim Statement (JIS) definition. Nine selected polymorphisms from FTO/CETP genes were genotyped using Tetra ARMS-PCR method. After age and sex adjustment the interaction of 9 markers with lipid profiles among phenotypes were tested by PASW. In three main groups, HDL_C level had a strong significant association with CETP markers: (rs3764261, β(95% CI) - 0.48(- 0.61 to - 0.35), P = 1.0 × 10 In the present study, we investigated the association between obesity phenotypes and some variations in FTO/CETP genes for the first time. Our study showed that four markers in the first intron of the FTO gene should be the risk marker in MUHO participants. Level III, case-control study. Show less