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Jahangiri M, Kazemnejad A, Goldfeld KS, Daneshpour MS, Mostafaei S, Khalili D, Moghadas MR, Akbarzadeh M. A wide range of missing imputation approaches in longitudinal data: a simulation study and real data analysis. BMC Med Res Methodol 2023; 23:161. [PMID: 37415114 PMCID: PMC10327316 DOI: 10.1186/s12874-023-01968-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 06/08/2023] [Indexed: 07/08/2023] Open
Abstract
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.
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Affiliation(s)
- Mina Jahangiri
- Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Anoshirvan Kazemnejad
- Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
| | - Keith S Goldfeld
- Division of Biostatistics, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Maryam S Daneshpour
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Shayan Mostafaei
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Davood Khalili
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Moghadas
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mahdi Akbarzadeh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Piko P, Llanaj E, Nagy K, Adany R. Genetic Background of Metabolically Healthy and Unhealthy Obesity Phenotypes in Hungarian Adult Sample Population. Int J Mol Sci 2023; 24:ijms24065209. [PMID: 36982283 PMCID: PMC10049500 DOI: 10.3390/ijms24065209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 03/06/2023] [Accepted: 03/07/2023] [Indexed: 03/30/2023] Open
Abstract
A specific phenotypic variant of obesity is metabolically healthy (MHO), which is characterized by normal blood pressure and lipid and glucose profiles, in contrast to the metabolically unhealthy variant (MUO). The genetic causes underlying the differences between these phenotypes are not yet clear. This study aims to explore the differences between MHO and MUO and the contribution of genetic factors (single nucleotide polymorphisms-SNPs) in 398 Hungarian adults (81 MHO and 317 MUO). For this investigation, an optimized genetic risk score (oGRS) was calculated using 67 SNPs (related to obesity and to lipid and glucose metabolism). Nineteen SNPs were identified whose combined effect was strongly associated with an increased risk of MUO (OR = 1.77, p < 0.001). Four of them (rs10838687 in MADD, rs693 in APOB, rs1111875 in HHEX, and rs2000813 in LIPG) significantly increased the risk of MUO (OR = 1.76, p < 0.001). Genetic risk groups based on oGRS were significantly associated with the risk of developing MUO at a younger age. We have identified a cluster of SNPs that contribute to the development of the metabolically unhealthy phenotype among Hungarian adults suffering from obesity. Our findings emphasize the significance of considering the combined effect(s) of multiple genes and SNPs in ascertaining cardiometabolic risk in obesity in future genetic screening programs.
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Affiliation(s)
- Peter Piko
- ELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
- Epidemiology and Surveillance Centre, Semmelweis University, 1085 Budapest, Hungary
| | - Erand Llanaj
- ELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
| | - Karoly Nagy
- Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
| | - Roza Adany
- ELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary
- Epidemiology and Surveillance Centre, Semmelweis University, 1085 Budapest, Hungary
- Department of Public Health, Semmelweis University, 1089 Budapest, Hungary
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Identification and Association of Single Nucleotide Polymorphisms of the FTO Gene with Indicators of Overweight and Obesity in a Young Mexican Population. Genes (Basel) 2023; 14:genes14010159. [PMID: 36672899 PMCID: PMC9858641 DOI: 10.3390/genes14010159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/29/2022] [Accepted: 01/04/2023] [Indexed: 01/10/2023] Open
Abstract
(1) Background: obesity is a global public health problem; various factors have been associated with this disease, and genetic factors play a very important role. Previous studies in multiple populations have associated a gene with fat mass and obesity (FTO). Thus, the present work aims to identify and determine associations between genetic variants of FTO with indicators of overweight and obesity in the Mexican population. (2) Methods: a total of 638 subjects were evaluated to compile data on body mass index (BMI), the percentage of body fat (%BF), the waist circumference (WC), the serum levels of triglycerides (TG), and food consumption. A total of 175 genetic variants in the FTO gene were sampled by a microarray in the evaluated population, followed by association statistical analyses and comparisons of means. (3) Results: a total of 34 genetic variants were associated with any of the 6 indicators of overweight and obesity, but only 15 showed mean differences using the recessive model after the Bonferroni correction. The present study shows a wide evaluation of FTO genetic variants associated with a classic indicator of overweight and obesity, which highlights the importance of genetic analyses in the study of obesity.
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Hoseini Tavassol Z, Mousavi SM, Molaei B, Bandarian F, Ejtahed HS, Khalagi K, Ghannadi S, Larijani B, Hasani-Ranjbar S. Association of fat mass and obesity-associated ( FTO) gene polymorphisms with non-communicable diseases (NCDs) in the Iranian population: A systematic review of observational studies. J Diabetes Metab Disord 2022; 21:1975-1989. [PMID: 36404828 PMCID: PMC9672241 DOI: 10.1007/s40200-022-01139-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Accepted: 10/03/2022] [Indexed: 10/31/2022]
Abstract
Background Single nucleotide polymorphisms have been implicated in various diseases, most notably non-communicable diseases (NCDs). The aim of this study was to review available evidence regarding associations between FTO polymorphisms and NCDs in the Iranian population. Methods A comprehensive search was conducted through PubMed/Medline and Scopus databases up to December 2021, as well as reference lists of pertinent articles and key journals. All observational studies that examined the association between FTO gene polymorphisms and NCDs in the Iranian population were included. There was no limitation on the publication year. The Newcastle-Ottawa Scale (NOS) was used to assess the study's quality. Results The initial search yielded 95 studies, of which 30 studies were included in the current systematic review. The underlying disorders were obesity, type 2 diabetes, breast and colorectal cancers, depression, and metabolic syndrome. These studies found an association between FTO gene polymorphisms and obesity in the Iranian population, but the relationship with other NCDs was debatable. Even though, other diseases such as diabetes and metabolic syndrome, which are closely related to obesity, may also be associated with FTO gene polymorphisms. Conclusion FTO gene polymorphism appears to play a role in the occurrence of NCDs. Some of the study results may be misleading due to ethnic differences and the effect of other genetic factors on disease onset, which needs to be investigated further. Finally, FTO gene polymorphisms can be studied as a preventive or therapeutic target. Supplementary Information The online version contains supplementary material available at 10.1007/s40200-022-01139-4.
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Affiliation(s)
- Zahra Hoseini Tavassol
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Mohammad Mousavi
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Bahareh Molaei
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Bandarian
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institutes, Tehran University of Medical Sciences, Tehran, Iran
| | - Hanieh-Sadat Ejtahed
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Kazem Khalagi
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Osteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Shima Ghannadi
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Shirin Hasani-Ranjbar
- Obesity and Eating Habits Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
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Falbová D, Vorobeľová L, Siváková D, Beňuš R. Association between FTO (rs17817449) genetic variant, gamma-glutamyl transferase, and hypertension in Slovak midlife women. Am J Hum Biol 2021; 34:e23672. [PMID: 34436809 DOI: 10.1002/ajhb.23672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 05/11/2021] [Accepted: 08/13/2021] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVES This cross-sectional study investigates associations between the FTO rs 17817449 genetic variant, liver enzymes, and hypertension in Slovak midlife women. METHODS We assessed 576 Slovak women aged 39 to 65 years. The women were interviewed and examined during their medical examination at local Health Centers and then divided into subgroups according to their blood pressure status; 255 women with hypertension and 321 normotensive. The FTO genetic variant was detected by polymerase chain reaction-restriction fragment length polymorphism. Resultant data was analyzed by linear regression analysis and general linear models to adjust for risk factors associated with gamma-glutamyl transferase levels (GGT), including waist to hip ratio (WHR) and uric acid (UA). RESULTS A significant association between the FTO variant and GGT levels was observed in the hypertensive group after control for confounding covariates, including WHR and UA (p = .004). The predicted GGT level for GT/TT hypertensive carriers is 0.158 μkat/L higher than for GG carriers. Moreover, the two-way analysis of covariance revealed significant interaction between FTO effects and hypertension on logGGT levels (p = .042). Finally, hypertensive women with the T-allele had the highest estimated marginal mean value of logGGT at -0.39 μkat/L while the GG-genotype in both hypertensive and normotensive women had the lowest value at -0.54 μkat/L. CONCLUSIONS This study suggests that the FTO (rs17817449) variant is associated with higher serum GGT levels in hypertensive midlife women.
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Affiliation(s)
- Darina Falbová
- Department of Anthropology, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovakia
| | - Lenka Vorobeľová
- Department of Anthropology, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovakia
| | - Daniela Siváková
- Department of Anthropology, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovakia
| | - Radoslav Beňuš
- Department of Anthropology, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovakia
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Paczkowska-Abdulsalam M, Kretowski A. Obesity, metabolic health and omics: Current status and future directions. World J Diabetes 2021; 12:420-436. [PMID: 33889288 PMCID: PMC8040086 DOI: 10.4239/wjd.v12.i4.420] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 02/22/2021] [Accepted: 03/30/2021] [Indexed: 02/06/2023] Open
Abstract
The growing obesity epidemic is becoming a major public health concern, and the associated costs represent a considerable burden on societies. Among the most common complications of severe obesity are the development of hypertension, dyslipidemia, type 2 diabetes, cardiovascular disease, and various types of cancer. Interestingly, some obese individuals have a favorable metabolic profile and appear to be somehow protected from the detrimental effects of excessive adipose tissue accumulation. These individuals remain normoglycemic, insulin sensitive, and hypotensive with proper blood lipid levels, despite their high body mass index and/or waist circumference. Multiple independent observations have led to the concept of the metabolically healthy obese (MHO) phenotype, yet no consensus has been reached to date regarding a universal definition or the main mechanism behind this phenomenon. Recent technological advances and the use of high-throughput analysis techniques have revolutionized different areas of biomedical research. A multi-omics approach, which is used to investigate changes at different molecular levels in an organism or tissue, may provide valuable insights into the interplay between the molecules or pathways and the roles of different factors involved in the mechanisms underlying metabolic health deterioration. The aim of this review is to present the current status regarding the use of omics technologies to investigate the MHO phenotype, as well as the results of targeted analyses conducted in MHO individuals.
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Affiliation(s)
| | - Adam Kretowski
- Clinical Research Centre, Medical University of Bialystok, Bialystok 15-276, Poland
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, Bialystok 15-276, Poland
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Genetic markers and continuity of healthy metabolic status: Tehran cardio-metabolic genetic study (TCGS). Sci Rep 2020; 10:13600. [PMID: 32788640 PMCID: PMC7423921 DOI: 10.1038/s41598-020-70627-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 07/23/2020] [Indexed: 12/29/2022] Open
Abstract
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.
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Abolnezhadian F, Hosseini SA, Alipour M, Zakerkish M, Cheraghian B, Ghandil P, Cheraghpour M. Association Metabolic Obesity Phenotypes with Cardiometabolic Index, Atherogenic Index of Plasma and Novel Anthropometric Indices: A Link of FTO-rs9939609 Polymorphism. Vasc Health Risk Manag 2020; 16:249-256. [PMID: 32612360 PMCID: PMC7322142 DOI: 10.2147/vhrm.s251927] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 05/26/2020] [Indexed: 12/13/2022] Open
Abstract
Background The role of metabolic states in cardiovascular risks among individuals with varying degrees of obesity is unknown. The study aimed to compare cardiometabolic index (CMI), atherogenic index of plasma (AIP), lipid accumulation product (LAP) and novel anthropometric indices in metabolic and non-metabolically obese individual with regard to the role of FTO gene in Iranian adults. Methods In total, 165 individuals were recruited into this cross-sectional study. Individuals grouped into four groups: metabolic healthy normal-weight (MHNW) individuals, metabolically unhealthy normal-weight (MUNW) individuals, metabolically healthy obese (MHO) individuals and metabolic unhealthy obese (MUO) individuals. The dietary intake was evaluated by food frequency questionnaire (FFQ). The cardiovascular indices (CMI, AIP and LAP) were calculated. A variety of anthropometric indices were calculated, including body adiposity Index (BAI), weight-adjusted-waist index (WWI), A body shape index (ABSI) and waist-height ratio (WHR). The genotypes of FTO-rs9939609 subjects were detected by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Results The individuals with metabolically unhealthy phenotypes (MUO, MUNW) have higher levels of triglyceride and cardiovascular indices (AIP, LAP and CMI) than the individuals with metabolic healthy phenotypes (MHO, MHNW). With a similar degree of obesity, the anthropometric indices (BAI, WWI and WHR) levels were higher in metabolic unhealthy groups than metabolically healthy groups. The highest frequency of obesity-risk allele AA of FTO gene was observed in MUO, MHO, MUNW and MHNW, respectively. Conclusion Normal-weight individuals with metabolic unhealthy status are at higher risk for cardiovascular diseases than obese individuals with metabolically healthy status. The genotype frequencies of obesity-risk allele AA of FTO gene were higher in obesity phenotypes than metabolic phenotypes.
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Affiliation(s)
- Farhad Abolnezhadian
- Division of Immunology and Allergy, Department of Pediatrics, School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Seyed Ahmad Hosseini
- Hyperlipidemia Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.,Nutrition and Metabolic Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Meysam Alipour
- Nutrition and Metabolic Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Mehrnoosh Zakerkish
- Department of Endocrinology and Metabolism, Diabetes Research Center, Health Research Institute, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Bahman Cheraghian
- Department of Statistics and Epidemiology, Faculty of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Pegah Ghandil
- Department of Medical Genetics, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Makan Cheraghpour
- Nutrition and Metabolic Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
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Nagrani R, Foraita R, Gianfagna F, Iacoviello L, Marild S, Michels N, Molnár D, Moreno L, Russo P, Veidebaum T, Ahrens W, Marron M. Common genetic variation in obesity, lipid transfer genes and risk of Metabolic Syndrome: Results from IDEFICS/I.Family study and meta-analysis. Sci Rep 2020; 10:7189. [PMID: 32346024 PMCID: PMC7188794 DOI: 10.1038/s41598-020-64031-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 04/07/2020] [Indexed: 12/13/2022] Open
Abstract
As the prevalence of metabolic syndrome (MetS) in children and young adults is increasing, a better understanding of genetics that underlie MetS will provide critical insights into the origin of the disease. We examined associations of common genetic variants and repeated MetS score from early childhood to adolescence in a pan-European, prospective IDEFICS/I.Family cohort study with baseline survey and follow-up examinations after two and six years. We tested associations in 3067 children using a linear mixed model and confirmed the results with meta-analysis of identified SNPs. With a stringent Bonferroni adjustment for multiple comparisons we obtained significant associations(p < 1.4 × 10−4) for 5 SNPs, which were in high LD (r2 > 0.85) in the 16q12.2 non-coding intronic chromosomal region of FTO gene with strongest association observed for rs8050136 (effect size(β) = 0.31, pWald = 1.52 × 10−5). We also observed a strong association of rs708272 in CETP with increased HDL (p = 5.63 × 10−40) and decreased TRG (p = 9.60 × 10−5) levels. These findings along with meta-analysis advance etiologic understanding of childhood MetS, highlighting that genetic predisposition to MetS is largely driven by genes of obesity and lipid metabolism. Inclusion of the associated genetic variants in polygenic scores for MetS may prove to be fundamental for identifying children and subsequently adults of the high-risk group to allow earlier targeted interventions.
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Affiliation(s)
- Rajini Nagrani
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
| | - Ronja Foraita
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Francesco Gianfagna
- Mediterranea Cardiocentro, Napoli, Italy.,EPIMED Research Center, Department of Medicine and Surgery, University of Insubria, Varese, Italy
| | - Licia Iacoviello
- IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Italy
| | - Staffan Marild
- Department of Paediatrics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Nathalie Michels
- Department of Public Health and Primary Care, Ghent University, 9000, Ghent, Belgium
| | - Dénes Molnár
- Department of Paediatrics, Medical School, University of Pécs, Pécs, Hungary
| | - Luis Moreno
- GENUD (Growth, Exercise, Nutrition, and Development) Research Group, University of Zaragoza, Zaragoza, Spain
| | - Paola Russo
- Institute of Food Sciences, National Research Council, Avellino, Italy
| | | | - Wolfgang Ahrens
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.,Institute of Statistics, Faculty of Mathematics and Computer Science, Bremen University, Bremen, Germany
| | - Manuela Marron
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
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Daneshpour MS, Hedayati M, Sedaghati-Khayat B, Guity K, Zarkesh M, Akbarzadeh M, Javanrooh N, Zadeh-Vakili A, Azizi F. Genetic Identification for Non-Communicable Disease: Findings from 20 Years of the Tehran Lipid and Glucose Study. Int J Endocrinol Metab 2018; 16:e84744. [PMID: 30584432 PMCID: PMC6289296 DOI: 10.5812/ijem.84744] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2018] [Revised: 10/02/2018] [Accepted: 10/09/2018] [Indexed: 11/24/2022] Open
Abstract
CONTEXT Tehran Lipid and Glucose Study (TLGS), a longitudinal family based cohort study, is the oldest and largest longitudinal family based study in Iran, aimed at investigating effects of environmental, social and biological factors on the health of Tehranians over time. Considering the importance of genetic studies in this aspect, here we present a summary of the important genetic findings, and the potentiality of their contributions to future related projects. EVIDENCE ACQUISITION For all related studies during the past 20 years the search sources were all prominent search engines such as PubMed, Scopus, and Google Scholar with the most proper Medical Subject Headings (MeSH). RESULTS This review summarizes associations of 6 binary phenotypes and 17 quantitative traits with genetic markers in 26 genes. Of the 47 genetic markers, studied most were related to cardio metabolic risk factors. Results of heritability and linkage analysis were also collected and the highest heritability was found to be related to HDL-C (0.5). CONCLUSION Considering the opportunity provided by large-scale cohort studies to investigate molecular effects of genetic variants on causality and different omics' data, genetic studies conducted on TLGS population have had a remarkable success in identifying genetic variants that facilitating a unique genetic database on Iranian populations. The results of genome wide association studies in this population are currently facilitating investigations to define the Iranian genetic differences with other population.
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Affiliation(s)
- Maryam S Daneshpour
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mehdi Hedayati
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Bahareh Sedaghati-Khayat
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Kamran Guity
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Zarkesh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mahdi Akbarzadeh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Niloofar Javanrooh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Azita Zadeh-Vakili
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Corresponding Author: Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P. O. Box: 19195-4763, Tehran, Iran. Tel: +98-2122432500, Fax: +98-2122416264,
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