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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.
Subject(s)
Obesity, Abdominal , Pediatric Obesity , Humans , Iran/epidemiology , Male , Female , Cross-Sectional Studies , Adult , Middle Aged , Risk Assessment , Obesity, Abdominal/epidemiology , Obesity, Abdominal/diagnosis , Obesity, Abdominal/physiopathology , Child , Pediatric Obesity/epidemiology , Pediatric Obesity/diagnosis , Pediatric Obesity/physiopathology , Young Adult , Adolescent , Age Factors , Risk Factors , Health Status , Blood Glucose/metabolism , Body Mass Index , Fathers , Mothers , Sex Factors , Biomarkers/blood , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/diagnosis , Protective Factors , Heart Disease Risk Factors , Maternal HealthABSTRACT
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.
Subject(s)
Cardiovascular Diseases , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/genetics , Cardiovascular Diseases/prevention & control , Iran/epidemiology , Longitudinal Studies , Cohort StudiesABSTRACT
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.
Subject(s)
Cardiovascular Diseases , Pantothenic Acid , Female , Male , Humans , Iran , Cross-Sectional Studies , Likelihood Functions , Eating , Energy Intake , Vitamins , Nutrients , Ascorbic Acid , ChromiumABSTRACT
BACKGROUND AND AIMS: 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. METHODS: 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. RESULTS: 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 (AGT) linked with SBP and DBP, rs976683 (NLGN1) linked with SBP and HTN, and epistasis of rs2021783 (TNXB) and known genetic variants linked with all blood pressure traits. CONCLUSIONS: 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.
Subject(s)
Blood Pressure/genetics , Body Mass Index , Environmental Exposure/adverse effects , Genetic Variation , Hypertension , Models, Cardiovascular , Models, Genetic , Quantitative Trait, Heritable , Waist Circumference , Cell Adhesion Molecules, Neuronal/genetics , Cell Adhesion Molecules, Neuronal/metabolism , Female , Genome-Wide Association Study , Humans , Hypertension/blood , Hypertension/genetics , Hypertension/pathology , Hypertension/physiopathology , Male , Prospective Studies , Retrospective Studies , Risk Factors , Tenascin/genetics , Tenascin/metabolismABSTRACT
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.
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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.
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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.
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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.
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The degree of maintaining nutrient intake patterns, conformed in the family, for offspring into adulthood is unknown. The aim of this study was to investigate the correlation between nutrient intakes in three younger-middle-older generations of Tehranian adults by sex. Of individuals who participated in 2012-15 phase of the Tehran Lipid and Glucose Study, 1286 families (4685 subjects), who had at least two members of the family with complete data in two or three generations were entered in this cross-sectional study. The energy and nutrient intakes of parents and their young or adult offspring or grandparents-grandson/granddaughter dyads were compared. The differences were estimated using pairwise t-test and partial correlation. Data of parents with their offspring were paired based on living arrangement. There were 857 fathers (mean age: 55.4±11.1) and 1394 mothers (mean age: 50.1±11.4). The mean age of grandfathers and grandmothers were 69.4±7.9 and 63.7±8.5 respectively. The significant correlation in fathers-sons and father-daughter (living with their parents) pairs were observed for 9 and 7 nutrients, respectively. Correlations for most nutrients were significant for mother-daughter or sons (living with their parents) dyads. The mean percentage of energy from total fat and trans-fatty acids of sons or daughters (living with their parents) were higher than their parents. For most nutrients, there were no significant adjusted correlations between parents-adult offspring (living independent of their parents) dyads. Also few nutrient intakes of grandparents-grandson or granddaughter dyads were correlated. The nutrient intakes of adult offspring were not associated with their parents; this correlation for younger and older generations disappeared. There were weak to moderate correlation between nutrient intakes of parent-offspring dyads that lived with their parents. The resemblance was higher for mother-offspring than father-offspring. Overall, total fat and trans-fatty acid intakes of young offspring were higher than their parents.
Subject(s)
Eating , Glucose , Adult , Aged , Cross-Sectional Studies , Female , Humans , Iran , Lipids , Middle Aged , Mothers , ParentsABSTRACT
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 < 0.005). Surprisingly, a lack of association was observed for the rest of the markers (16 SNPs). These results revealed the moderator effects of age and sex on the association between the genetic variants (SNPs) of 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.
Subject(s)
Coronary Disease , Myocardial Infarction , Coronary Disease/epidemiology , Coronary Disease/genetics , Ethnicity , Female , Humans , Iran , Lipoprotein(a)/genetics , Longitudinal Studies , Male , Middle Aged , Myocardial Infarction/epidemiology , Myocardial Infarction/genetics , Risk FactorsABSTRACT
BACKGROUND: 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. METHODS: 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). RESULTS: Familial aggregation of T2D was significant (p<0.05), 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. CONCLUSIONS: 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.
Subject(s)
Diabetes Mellitus, Type 2 , Diabetes Mellitus, Type 2/epidemiology , Diabetes Mellitus, Type 2/genetics , Glucose , Humans , Iran/epidemiology , Lipids , ParentsABSTRACT
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 < 0.05) in Iranian adults. The CT genotype of the variants was associated with lower HDL-C levels. The proportional Cox adjusted model regression resulted that TT carriers of rs780094, rs780093, and rs1260326 were associated with 20%, 23%, and 21% excess risk metabolic syndrome incidence, respectively (p < 0.05). 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.
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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 (< 7% or ≥ 7% weight gain), in individuals with ≥ 7% weight gain, highest tertile of nut consumption was associated with reduced risk of MetS among the risk allele of rs7903146. In the risk allele of rs12255372, among individuals with < 7% weight gain, third tertile of nuts intake reduced the risk of MetS, after adjustment for confounders. 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.
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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.