The association between parental cardiovascular health status and the risk of obesity in their offspring: Tehran Lipid and Glucose Study.

BACKGROUND AND AIMS: Little is known about the association of parental cardiovascular risk factors with the risk of obesity in offspring. We aimed to investigate whether parental ideal cardiovascular health (ICVH) status was associated with the risk of general and central obesity in their young/adult offspring. METHODS AND RESULTS: Of individuals who participated in the 2012-15 phase of the Tehran Lipid and Glucose Study, 2395 pairs of parent-unmarried offspring aged ≥6 years were selected in this cross-sectional study. General and central obesity were defined based on Iranian BMI percentile reference data for offspring aged ≤18 years. For subjects aged ≥19 years, central obesity was defined based on the introduced cut-off points for Iranian adults. We employed the American Heart Association's 2020 impact goal criteria of ICVH. The mean ± SD age of fathers and mothers were respectively 55.4 ± 9.79 and 48.4 ± 9.88. About 55% of offspring were older than 19 years. Higher adherence to ICVH score in mothers was associated with lower risk of overweight/obesity in female offspring (OR for Q1-Q4: 1, 0.56, 0.57, 0.37, P < 0.05 for all quartiles). Among ICVH components, only ideal BMI status in fathers was observed to be associated with a lower risk of overweight/obesity in their male offspring. The risk of abdominal obesity decreased in female offspring with increasing total ICVH score in mothers. CONCLUSION: Higher adherence of parents to ICVH and its components was positively associated with a lower risk of general and abdominal obesity in their offspring. Our findings demonstrate that maternal-offspring relationship was stronger than paternal-offspring association.

Three candidate SNPs show associations with thyroid-stimulating hormone in euthyroid subjects: Tehran thyroid study.

Objectives: Previous studies have shown interindividual variation in free thyroxine (FT4) serum levels and thyroid stimulating hormone (TSH) in healthy persons. Genetic factors mainly determine this variation, and genome-wide association studies have increased the number of thyroid function-associated variants. The present study investigates the association of candidate variants with FT4 and TSH in a euthyroid Iranian population. Method: A total of 2931 unrelated euthyroid subjects (FT4 10.29-21.88 pmol/L; TSH 0.32-10 mIU/L, thyroid peroxidase antibody TPOAb < 33 IU/mL in men and < 35 IU/mL in women), with available genotypes were chosen from the Tehran Thyroid Study (TTS), to examine the impact of selected SNPs on thyroid hormone under the additive genetic model. In order to evaluate regional associations with FT4 and TSH levels, a haplotype analysis was done. Results: We identified a strong association between the rs4338740-C allele and TSH in the adjusted model (ß = -0.095, P-value = 0.0004). Also, findings indicated that rs4954192 ACMSD and rs4445669 CADM1 correlated with normal TSH levels (P-value = 0.011, P-value = 0.014, respectively). Haplotype analysis revealed that two haplotypes were significantly associated with TSH levels in euthyroid individuals. The ACGA and AC haplotypes on chromosomes 8 and 14 were significantly correlated with normal TSH levels, respectively (P-value = 0.014, P-value = 0.016). Conclusions: This is the first genetic association study with TSH and FT4 reference values in an Iranian population. Our findings indicate that a few gene variants associated with the reference values of TSH in other populations are also associated with the reference values of TSH in Iranians. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-023-01383-2.

Insulin resistance-related circulating predictive markers in the metabolic syndrome: a systematic review in the Iranian population.

Background: Specific biomarkers for metabolic syndrome (MetS) may improve diagnostic specificity for clinical information. One of the main pathophysiological mechanisms of MetS is insulin resistance (IR). This systematic review aimed to summarize IR-related biomarkers that predict MetS and have been investigated in Iranian populations. Methods: An electronic literature search was done using the PubMed and Scopus databases up to June 2022. The risk of bias was assessed for the selected articles using the instrument suggested by the Joanna Briggs Institute (JBI). This systematic review protocol was registered with PROSPERO (registration number CRD42022372415). Results: Among the reviewed articles, 46 studies investigated the association between IR biomarkers and MetS in the Iranian population. The selected studies were published between 2009 and 2022, with the majority being conducted on adults and seven on children and adolescents. The adult treatment panel III (ATP III) was the most commonly used criteria to define MetS. At least four studies were conducted for each IR biomarker, with LDL-C being the most frequently evaluated biomarker. Some studies have assessed the diagnostic potency of markers using the area under the curve (AUC) with sensitivity, specificity, and an optimal cut-off value. Among the reported values, lipid ratios and the difference between non-HDL-C and LDL-C levels showed the highest AUCs (≥ 0.80) for predicting MetS. Conclusions: Considering the findings of the reviewed studies, fasting insulin, HOMA-IR, leptin, HbA1c, and visfatin levels were positively associated with MetS, whereas adiponectin and ghrelin levels were negatively correlated with this syndrome. Among the investigated IR biomarkers, the association between adiponectin levels and components of MetS was well established. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-023-01347-6.

Energy and macronutrient intake heritability: A systematic review and meta-analysis of twin and family-based studies.

BACKGROUND/AIMS: The current meta-analysis aimed to examine the heritability and familial resemblance of dietary intakes, including energy and macronutrients in both twin and family-based studies. METHODS: The online literature databases, including PubMed, Scopus, and Web of Science were searched comprehensively until 2023 to identify the relevant studies. The heritability index in family studies was h2 and the heritability indices for twin studies were h2, A2, and E2. Three weighted methods were used to calculate the mean and SE of heritability dietary intakes. RESULTS: Eighteen papers including 8 studies on familial population and 12 for twin population studies were included in the present meta-analysis. The heritability of dietary intakes in twin studies (range of pooled estimated h2, A2, and E2 was 30-55%, 14-42%, and 52-79%, respectively) was higher than family studies (range of pooled estimated h2 = 16-39%). In family studies, the highest and lowest heritability for various nutrients was observed for the fat (%Kcal) (h2 range:36-38%) and carbohydrate in g (h2 range:16-18%), respectively. In twin studies, based on mean h2, the highest and lowest heritability for various nutrients was reported for the fat (%Kcal) (h2 range:49-55%) and protein intake in g (h2 range:30-35%), respectively. Also, based on the mean of A2, the highest and lowest heritability was observed for carbohydrates (% Kcal) (A2 range:42-42%), and protein (% Kcal) (A2 range:14-16%), respectively. Furthermore, in twin studies, the highest and lowest mean of E2 was shown for saturated fats (E2 range:74-79%) and energy intake (E2 range:52-57%), respectively. CONCLUSION: Our analysis indicated that both environmental factors and genetics have noticeable contributions in determining the heritability of dietary intakes. Also, we observed higher heritability in twins compared to family studies.

Parent-child correlation in energy and macronutrient intakes: A meta-analysis and systematic review.

In the current study, we aimed to review the evidence from twin and family-based studies that have assessed the familial similarity in intakes of energy and macronutrients among various parent-child pairs. The online literature databases, including Web of Science, PubMed, and Scopus, were searched up to December 2022 to find potentially eligible studies. We converted Pearson's, Spearman's, or intra-class correlation coefficients to z's using Fisher's z transformation to obtain approximate normality and then calculated a mean and standard error (SE) of transformed correlation weighted by the sample sizes in the studies. We reported pooled r and 95% CI as our final results in five groups, including parent-child, mother-daughter, mother-son, father-daughter, and father-son. Twenty-one eligible studies were included in this meta-analysis, in which the sample size ranged from 33 and 4310. Our analysis showed that family resemblance in the intake of energy and macronutrients in various parent-offspring pairs was weak to moderate which could be different based on family pairs, nutrients, and studies. The highest similarity in dietary intakes was observed among the mother-daughter pair, which was for carbohydrate and protein intake, respectively. The lowest correlations in dietary intakes were found between mother-son or father-son pairs. Our meta-analysis suggested that family similarity for intakes of energy and macronutrients was not strong in parent-child pairs. The highest correlation in dietary intake was mostly found in mother-daughter pairs. The weak similarities in dietary intake among parent-child pairs indicate the noticeable effect of the environment outside the family on individuals' dietary choices.

Causal effect of serum 25 hydroxyvitamin D concentration on cardioembolic stroke: Evidence from two-sample Mendelian randomization.

BACKGROUND AND AIMS: The putative association between serum 25-hydroxyvitamin D concentration [25(OH)D] and the risk of cardioembolic stroke (CES) has been examined in observational studies, which indicate controversial findings. We performed Mendelian randomization (MR) analysis to determine the causal relationship of serum 25(OH)D with the risk of CES. METHODS AND RESULTS: The summary statistics dataset on the genetic variants related to 25(OH)D was used from the published GWAS of European descent participants in the UK Biobank, including 417,580 subjects, yielding 143 independent loci in 112 1-Mb regions. GWAS summary data of CES was obtained from GIGASTROKE Consortium, which included European individuals (10,804 cases, 1,234,808 controls). Our results unveiled a causal relationship between 25(OH)D and CES using IVW [OR = 0.82, 95% CI: 0.67-0.98, p = 0.037]. Horizontal pleiotropy was not seen [MR-Egger intercept = 0.001; p = 0.792], suggesting an absence of horizontal pleiotropy. Cochrane's Q [Q = 78.71, p-value = 0.924], Rucker's Q [Q = 78.64, p-value = 0.913], and I2 = 0.0% (95% CI: 0.0%, 24.6%) statistic suggested no heterogeneity. This result remained consistent using different MR methods and sensitivity analyses, including Maximum likelihood [OR = 0.82, 95%CI: 0.67-0.98, p-value = 0.036], Constrained maximum likelihood [OR = 0.76, 95%CI: 0.64-0.90, p-value = 0.002], Debiased inverse-variance weighted [OR = 0.82, 95%CI: 0.68-0.99, p-value = 0.002], MR-PRESSO [OR = 0.82, 95%CI 0.77-0.87, p-value = 0.022], RAPS [OR = 0.82, 95%CI 0.67-0.98, p-value = 0.038], MR-Lasso [OR = 0.82, 95%CI 0.68-0.99, p-value = 0.037]. CONCLUSION: Our MR analysis provides suggestive evidence that increased 25(OH)D levels may play a protective role in the development of cardioembolic stroke. Determining the role of 25(OH)D in stroke subtypes has important clinical and public health implications.

Nanomaterials in electrochemical nanobiosensors of miRNAs.

Nanomaterial-based biosensors have received significant attention owing to their unique properties, especially enhanced sensitivity. Recent advancements in biomedical diagnosis have highlighted the role of microRNAs (miRNAs) as sensitive prognostic and diagnostic biomarkers for various diseases. Current diagnostics methods, however, need further improvements with regards to their sensitivity, mainly due to the low concentration levels of miRNAs in the body. The low limit of detection of nanomaterial-based biosensors has turned them into powerful tools for detecting and quantifying these biomarkers. Herein, we assemble an overview of recent developments in the application of different nanomaterials and nanostructures as miRNA electrochemical biosensing platforms, along with their pros and cons. The techniques are categorized based on the nanomaterial used.

The Tehran longitudinal family-based cardiometabolic cohort study sheds new light on dyslipidemia transmission patterns.

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.

An optimized method for PCR-based genotyping to detect human APOE polymorphisms.

Background: Apolipoprotein E (APOE) is one of the most polymorphic genes at two single nucleotides (rs429358 and rs7412). The various isoforms of APOE have been associated with a variety of diseases, including neurodegenerative, type 2 diabetes, etc. Hence, predicting the APOE genotyping is critical for disease risk evaluation. The purpose of this study was to optimize the tetra amplification refractory mutation system (Tetra-ARMS) PCR method for the detection of APOE mutations. Material and methods: Here, in our optimized Tetra-ARMS PCR method, different factors like cycle conditions, using HiFidelity enzyme instead of Taq polymerase and setting its best concentration, and the lack of using dimethylsulfoxide (DMSO) for amplifying the GC-regions were set up for all primer pairs. The sensitivity and accuracy were tested. For validation of the assay, the results were compared with known genotypes for the APOE gene that were previously obtained by two independent methods, RFLP and Chip-typing. Results: Successful Tetra-ARMS PCR and genotyping are influenced by multiple factors. Our developed method enabled us to amplify the DNA fragment by 25 cycles without adding any hazardous reagent, like DMSO. Our findings showed 100 % accuracy and sensitivity of the optimized Tetra-ARMS PCR while both criteria were 95 % for RFLP and 100 % for the chip-typing method. In addition, our results showed 91 % and 100 % consistency with RFLP and chip typing methods, respectively. Conclusions: Our current method is a simple and accurate approach for detecting APOE polymorphisms within a large sample size in a short time and can be performed even in low-tech laboratories.

Association of rs2282679 polymorphism in vitamin D binding protein gene (GC) with the risk of vitamin D deficiency in an iranian population: season-specific vitamin D status.

BACKGROUND: Genome-wide association studies in Western countries indicate a considerable impact of variations in vitamin D binding protein (GC) genes on serum concentrations of 25-hydroxyvitamin D (25(OH)D). We aimed to investigate an association between rs2282679 polymorphism in GC and vitamin D deficiency. METHODS: A cross-sectional study conducted in the framework of the Tehran Cardio-Metabolic Genetic Study (TCGS) cohort. A total of 1568 participants aged > 18 years were randomly selected, and their 25(OH) D concentration was measured. Vitamin D deficiency was assessed concerning rs2282679 by descriptive and multivariate analysis, odds ratio (OR), and 95% confidence intervals (95%CI) calculated. Since the interaction term between rs2282679 and recruitment season was significant, we performed regression analysis separately for individuals whose blood was taken in high sunny and those whose blood was drawn in the low sunny season. RESULTS: The rs2282679 polymorphism was in Hardy-Weinberg equilibrium (P > 0.05) in the studied population. The serum concentration of 25(OH) D median was 15.0 ng/mL, and the prevalence of VDD was 27.8%. The presence of the G allele in rs2282679 increases the risk of VDD in additive (OR = 1.35, 95% CI: 1.06-1.73) and dominant (OR = 1.33, 95% CI: 1.06-1.68) genetic models. After separating participants based on the recruitment season, the unfavorable association was observed in the additive and dominant only in the low sunny season. CONCLUSION: The finding of the current study indicates that the GC rs2282679 SNP is associated with vitamin D deficiency. It seems that the impact of risk allele increased in the low sunny season when UV exposure has been declined.

Association of baseline and changes in adiponectin, homocysteine, high-sensitivity C-reactive protein, interleukin-6, and interleukin-10 levels and metabolic syndrome incidence: Tehran lipid and glucose study.

Background: Metabolic syndrome (MetS) is accompanied by chronic low-grade inflammation, and inflammatory markers like high-sensitivity C-reactive protein(hs-CRP), interleukin-6(IL-6), and homocysteine(Hcy) contribute to inflammation, obesity, and insulin resistance. Adiponectin(AdipoQ) and interleukin-10(IL-10) are anti-inflammatory markers that play protective roles in MetS. This study aimed to investigate the association between these biochemical marker changes and MetS in a sample of the Tehranian population during six years of follow-up. Methods: In this longitudinal study, 340 adults at baseline and after a six-year follow-up, aged ≥18 years, were selected randomly from the Tehran Lipid and Glucose Study (TLGS). MetS was defined according to the Joint Interim Statement (JIS) criteria. Individuals were categorized into four groups based on their MetS status at baseline and follow-up: 1) non-MetS: participants who did not have MetS at both baseline and follow-up; 2) incident MetS: participants who did not have MetS at baseline but developed MetS during the follow-up ; 3) recovery MetS: participants who had MetS at baseline but no longer had MetS during the follow-up; 4) persistent MetS: participants who had MetS both at baseline and follow-up. Results: The mean follow-up time was 6.1 years. There were 176 subjects in the non-MetS group, 35 in the incident MetS group, 41 in the recovery MetS group, and 88 in the persistent MetS group. Increases in the levels of both hs-CRP 1.40 (95% CI: 1.15, 1.71, p = 0.001) and IL-6 1.09 (95% CI: 1.03, 1.17, p = 0.004) significantly increased the odds of the incident and persistent MetS, respectively. The area under the ROC curve (AUC) was more than 0.69 (p < 0.000) for hs-CRP in predicting MetS incidence and more than 0.86 (p < 0.000) for IL-6 in predicting MetS persistence. Conclusion: After a six-year average follow-up, hs-CRP and IL-6 levels were deemed more reliable predictors of MetS incidence and persistence, respectively.

Dietary approach to stop hypertension and healthy eating index 2015, modify the association between FTO polymorphisms and obesity phenotypes.

This study aimed to investigate the interaction of the healthy eating index (HEI) and the dietary approach to stop hypertension (DASH) diet scores with FTO polymorphisms in relation to change in 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 and genetic risk score (GRS) was computed. HEI and DASH scores were computed based on dietary data. Changes in body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR) and visceral adiposity index (VAI) were measured. Higher adherence to both DASH and HEI scores were increased with higher ages. Individuals with high GRS 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; conversely, higher adherence to the DASH score by this genotypic group was related to increase in WC. No significant interaction was seen between FTO polymorphisms and both diet scores regarding changes in any of obesity traits. In conclusion, in individuals with high GRS higher adherence to HEI score was associated with lower change in BMI and WC, while higher adherence to DASH diet was associated with higher change in WC, compared to individuals with lower adherence to both scores.

Familial resemblance and family-based heritability of nutrients intake in Iranian population: Tehran cardiometabolic genetic study.

BACKGROUND: We aimed to investigate the familial resemblance of dietary intakes, including energy and nutrients, and the family-based heritability of dietary intake in different age-sex dyads of the Tehran cardiometabolic genetic study. METHODS: This cross-sectional study was conducted on 9,798 participants, aged ≥ 18 years, with complete data in each of the third, fourth, fifth, and sixth surveys of the Tehran Cardiometabolic Genetic study, who were eligible to enter the current study based on inclusion and exclusion criteria. Nutrient intake was determined using a valid and reliable food frequency questionnaire (FFQ). FCOR command of the S.A.G.E. software was used to estimate the intra-class correlation coefficients of all relative pairs to verify the family resemblance of dietary nutrient intakes. Classical likelihood-based is used to assess the family-based heritability of dietary nutrient traits. RESULTS: There were 4338 families with a mean family size of 3.20 ± 2.89, including 1 to 32 members (2567 constituent pedigrees and 1572 singletons) and 3627 sibships. The mean ± SD age of participants was 42.0 ± 15.2 years, and 44.5% were males. The heritability of nutrient intake ranged from 3 to 21%. The resemblance degree of energy intake and most nutrients between spouses or between parents and children is weak to moderate; however, a high resemblance of intake was observed for some food components, especially among spouses, including trans fatty acids (TFAs) (r:0.70), chromium (r:0.44), fiber(r:0.35), pantothenic acid (r:0.31), and vitamin C(r:0.31). Based on our findings, the resemblance of nutrient intake in spouses was greater than in parent-offspring. The similarity in parent-offspring nutrient intake was different, and the correlation in mother-girls nutrient intakes was greater than other parent-child correlations. Also, the lowest resemblance in nutrient intake was observed among siblings. CONCLUSIONS: Our findings suggested a weak-to-moderate similarity between the nutrient intakes of parents and offspring. The resemblance degree in nutrient intake varied between different family pairs; the strongest correlation of nutrients was observed between spouses, which includes TFAs, chromium, fiber, pantothenic acid, and vitamin C. The lowest correlation of nutrients was between siblings, such as carbohydrates, thiamine, niacin, and vitamin K. An individual's nutrient intake can somewhat be influenced by genetics, family relationships, and the effects of parents, although the significant influence of environmental factors should not be ignored.

Overview of miR-106a Regulatory Roles: from Cancer to Aging.

MicroRNAs (miRNAs) comprise a class of non-coding RNA with extensive regulatory functions within cells. MiR-106a is recognized for its super-regulatory roles in vital processes. Hence, the analysis of its expression in association with diseases has attracted considerable attention for molecular diagnosis and drug development. Numerous studies have investigated miR-106 target genes and shown that this miRNA regulates the expression of some critical cell cycle and apoptosis factors, suggesting miR-106a as an ideal diagnostic and prognostic biomarker with therapeutic potential. Furthermore, the reported correlation between miR-106a expression level and cancer drug resistance has demonstrated the complexity of its functions within different tissues. In this study, we have conducted a comprehensive review on the expression levels of miR-106a in various cancers and other diseases, emphasizing its target genes. The promising findings surrounding miR-106a suggest its potential as a valuable biomolecule. However, further validation assessments and overcoming existing limitations are crucial steps before its clinical implementation can be realized.

Regularized Machine Learning Models for Prediction of Metabolic Syndrome Using GCKR, APOA5, and BUD13 Gene Variants: Tehran Cardiometabolic Genetic Study.

OBJECTIVE: 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 GCKR, BUD13 and APOA5, and environmental risk factors. MATERIALS AND METHODS: 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 GCKR, BUD13 and APOA5 genes of eligible participants were assessed to classify TCGS participant status in MetS development. The models' performance was evaluated by 10-repeated 10-fold crossvalidation. Various assessment measures of sensitivity, specificity, classification accuracy, and area under the receiver operating characteristic curve (AUC-ROC) and AUC-precision-recall (AUC-PR) curves were used to compare the models. RESULTS: 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. CONCLUSION: 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.

The effect of Apigenin on glycometabolism and cell death in an anaplastic thyroid cancer cell line.

AIMS AND BACKGROUND: A more pronounced characteristic of cancer cells is the energy dependence on glucose, which mitigated by glucose transporters. The comprehension of the regulatory mechanisms behind the Warburg effect holds promise for developing therapeutic interventions for cancers. Studies are lacking which targeted the GLUTs for treatment of malignancy of thyroid tumors. In our current investigation, we have undertaken this study to determine the potential of Apigenin, plant derived flavonoid in modulating tumor apoptosis by targeting GLUTs expression in SW1736 cell line of anaplastic thyroid carcinoma. MATERIAL METHODS: Flow cytometry with propidium iodide staining was used to determine cell apoptosis. For glucose uptake detection, the "GOD-PAP" enzymatic colorimetric test was used to measure the direct glucose levels inside the cells. To determine the expression of GLUT1 and GLUT3 mRNA in the SW1736 cell line qRT-PCR was employed. Protein levels of GLUT1 and GLUT3 in the SW1736 cell line were detected with western blotting. Also, the scratch wound healing assay was conducted for cell migration. RESULTS: According to qRT-PCR analysis, the levels of GLUT1 and GLUT3 mRNA were lower in the group that received Apigenin relative to the control group. The Apigenin treatment of SW1736 cells decreased protein expression of the GLUT1 and GLUT3 levels in conformity to qRT-PCR. The scratch assays revealed that Apigenin treatment of cancer cell lines inhibited cell migration as compared to control. CONCLUSION: These findings demonstrate the possibility of targeting the glucose facilitators' pathway for making thyroid cancer cells more susceptible to programmed cell death.

Evidence of familial resemblance and family-based heritability of food intakes derived from a longitudinal cohort study.

We sought to investigate the familial aggregation and family-based heritability of dietary intakes among adults in a population-based longitudinal study of the Tehran Lipid and Glucose Study (TLSG). Total of 4359 males and 5439 females entered our study. We categorized foods into main groups based on the literature on main food groups and their subgroups among the Iranian dietary habits and food culture as follows: grains, fruits, vegetables, dairy, meats, legume, nuts, beverages, snacks, and fats. The intraclass correlation coefficients (ICC) are estimated to verify familial resemblance of dietary habits for all relative pairs and spouses. Family-based heritability is obtained using a mixed effect framework with likelihood-based approach. For almost all food groups, the correlation between parents and offsprings tended to be larger than those of siblings. Family-based heritability of food groups varies from the lowest 6.36% for snacks to the highest 25.67% for fruits, and 25.66% for legume. Our findings indicated weak-to-moderate similarities between parents' and offspring's food intakes; however, the similarity in parent-child food intakes was different, and the correlation in mother-daughter food intakes was stronger than other parent-child correlations, and almost all of dietary components showed strong family-based heritability.

A wide range of missing imputation approaches in longitudinal data: a simulation study and real data analysis.

BACKGROUND: Missing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches have been proposed to address this issue. In this study, for the first time, the function of the longitudinal regression tree algorithm as a non-parametric method after imputing missing data using SI and MI was investigated using simulated and real data. METHOD: Using different simulation scenarios derived from a real data set, we compared the performance of cross, trajectory mean, interpolation, copy-mean, and MI methods (27 approaches) to impute missing longitudinal data using parametric and non-parametric longitudinal models and the performance of the methods was assessed in real data. The real data included 3,645 participants older than 18 years within six waves obtained from the longitudinal Tehran cardiometabolic genetic study (TCGS). The data modeling was conducted using systolic and diastolic blood pressure (SBP/DBP) as the outcome variables and included predictor variables such as age, gender, and BMI. The efficiency of imputation approaches was compared using mean squared error (MSE), root-mean-squared error (RMSE), median absolute deviation (MAD), deviance, and Akaike information criteria (AIC). RESULTS: The longitudinal regression tree algorithm outperformed based on the criteria such as MSE, RMSE, and MAD than the linear mixed-effects model (LMM) for analyzing the TCGS and simulated data using the missing at random (MAR) mechanism. Overall, based on fitting the non-parametric model, the performance of the 27 imputation approaches was nearly similar. However, the SI traj-mean method improved performance compared with other imputation approaches. CONCLUSION: Both SI and MI approaches performed better using the longitudinal regression tree algorithm compared with the parametric longitudinal models. Based on the results from both the real and simulated data, we recommend that researchers use the traj-mean method for imputing missing values of longitudinal data. Choosing the imputation method with the best performance is widely dependent on the models of interest and the data structure.

Sex-specific association of FABP2 polymorphisms with the risk of obesity in the Tehran Cardio-Metabolic Genetic Study (TCGS).

FABP2 is one of the key genes involved in obesity development across different populations. However, there is no comprehensive report about the FABP2 contribution to obesity incidence among Iranians. Hence, the present study was designed to assess the probable role of FABP2 polymorphisms in obesity incidence in the Tehran Cardio- metabolic Genetic Study (TCGS) representative Iran population. Unrelated adults who had BMI information for at least 3 consecutive phases of the TCGS cohort were included. The control and case groups were defined as individuals who always had long-term persistent normal weight (20 < BMI < 25; n = 1526) and individuals who were long-term persistent obese (30 < BMI < 35; n = 1313), respectively. The logistic regression test was used to assess the possible association between SNPs located in and around the FABP2 gene with obesity. Also, we used Haploview and SHEsis to perform haplotype analysis to detect whether or not this chromosomal region is correlated with obesity. We found a gender-dependent association between the rs10857064 FABP2 and the risk of obesity. The presence of the rs10857064-G allele could significantly increase the risk of obesity only in women, not men (OR = 1.26; 95 % CI: 1.02-1.57; p = 0.03). Through haplotype analysis, we also detected that the TG haplotype containing rs7670862 and rs10857064 could significantly enhance the risk of obesity in women, further supporting the central role of rs10857064 in women's long-term obesity risk. In the current study, we revealed that rs10857064-G FABP2 can significantly predispose women to develop obesity. It highlights the importance of different genetic variants in both genders, which could help us to distinguish more efficient obesity screening tests and treatments based on gender in the future.

Cohort profile update: Tehran cardiometabolic genetic study.

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.