Lack of association between FTO gene variations and metabolic healthy obese (MHO) phenotype: Tehran Cardio-metabolic Genetic Study (TCGS)

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.

Genetic Background of Metabolically Healthy and Unhealthy Obesity Phenotypes in Hungarian Adult Sample Population

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.

Identification and Association of Single Nucleotide Polymorphisms of the FTO Gene with Indicators of Overweight and Obesity in a Young Mexican Population

(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.

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

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.

Association between FTO (rs17817449) genetic variant, gamma-glutamyl transferase, and hypertension in Slovak midlife women

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.

Obesity, metabolic health and omics: Current status and future directions

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.

Genetic markers and continuity of healthy metabolic status: Tehran cardio-metabolic genetic study (TCGS)

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.

Association Metabolic Obesity Phenotypes with Cardiometabolic Index, Atherogenic Index of Plasma and Novel Anthropometric Indices: A Link of FTO-rs9939609 Polymorphism

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.

Common genetic variation in obesity, lipid transfer genes and risk of Metabolic Syndrome: Results from IDEFICS/I.Family study and meta-analysis

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, p_Wald = 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.

Genetic Identification for Non-Communicable Disease: Findings from 20 Years of the Tehran Lipid and Glucose Study

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.