Common variants near MC4R are associated with fat mass, weight and risk of obesity

INSIG2 rs7566605 single nucleotide variant and global DNA methylation index levels are associated with weight loss in a personalized weight reduction program

Single nucleotide polymorphisms associated with lipid metabolism and energy balance are implicated in the weight loss response caused by nutritional interventions. Diet-induced weight loss is also associated with differential global DNA methylation. DNA methylation has been proposed as a predictive biomarker for weight loss response. Personalized biomarkers for successful weight loss may inform clinical decisions when deciding between behavioral and surgical weight loss interventions. The aim of the present study was to investigate the association between global DNA methylation, genetic variants associated with energy balance and lipid metabolism, and weight loss following a non-surgical weight loss regimen. The present study included 105 obese participants that were enrolled in a personalized weight loss program based on their allelic composition of the following five energy balance and lipid metabolism-associated loci: Near insulin-induced gene 2 (INSIG2); melanocortin 4 receptor; adrenoceptor β2; apolipoprotein A5; and G-protein subunit β3. The present study investigated the association between a global DNA methylation index (GDMI), the allelic composition of the five energy balance and lipid metabolism-associated loci, and weight loss during a 12 month program, after controlling for age, sex and body mass index (BMI). The results demonstrated a significant association between the GDMI and near INSIG2 locus, after adjusting for BMI and weight loss, and significant trends were observed when stratifying by gender. In conclusion, a combination of genetic and epigenetic biomarkers may be used to design personalized weight loss interventions, enabling adherence and ensuring improved outcomes for obesity treatment programs. Precision weight loss programs designed based on molecular information may enable the creation of personalized interventions for patients, that use genomic biomarkers for treatment design and for treatment adherence monitoring, thus improving response to treatment.

The genetic underpinnings of body fat distribution

Obesity, defined as a body mass index (BMI) ≥ 30 kg/m², has reached epidemic proportions; people who are overweight (BMI > 25 kg/m²) or obese now comprise more than 25% of the world's population. Obese individuals have a higher risk of comorbidity development including type 2 diabetes, cardiovascular disease, cancer, and fertility complications. Areas covered: The study of monogenic and syndromic forms of obesity have revealed a small number of genes key to metabolic perturbations. Further, obesity and body shape in the general population are highly heritable phenotypes. Study of obesity at the population level, through genome-wide association studies of BMI and waist-to-hip ratio (WHR), have revealed > 150 genomic loci that associate with these traits, and highlight the role of adipose tissue and the central nervous system in obesity-related traits. Studies in animal models and cell lines have helped further elucidate the potential biological mechanisms underlying obesity. In particular, these studies implicate adipogenesis and expansion of adipose tissue as key biological pathways in obesity and weight gain. Expert commentary: Further work, including a focus on integrating genetic and additional genomic data types, as well as modeling obesity-like features in vitro, will be crucial in translating genome-wide association signals to the causal mechanisms driving disease.

Metabolic biomarkers and gallstone disease - a population-based study

OBJECTIVES

The objectives for this study were to examine the associations between metabolic biomarkers of obesity including insulin resistance, vascular dysfunction, systemic inflammation, genetic susceptibility and ultrasound proven gallstone disease or cholecystectomy in a population-based cross-sectional study.

MATERIAL AND METHODS

A total of 2650 participants were included, of whom 422 had gallstone disease. Associations between selected metabolic biomarkers and gallstone disease were estimated by multivariable logistic regression models and expressed as odds ratio (OR) and 95% confidence interval (CI).

RESULTS

Gallstone disease was associated with fasting glucose (OR 1.14, 95% CI [1.05;1.24]), fasting insulin (OR 1.03, 95% CI [1.01;1.05]), homeostasis model assessment insulin resistance (OR 1.18, 95% CI [1.02;1.36]), the metabolic syndrome (OR 1.51, 95% CI [1.16;1.96]), white blood cell count (OR 1.07, 95% CI [1.00;1.15]) and C-reactive protein (OR 1.03, 95% CI [1.01;1.05]). A tendency towards an association for soluble urokinase plasminogen activator receptor was also found (OR 1.08, 95% CI [0.99;1.18]). The MC4R(rs17782313) (OR 1.27, 95% CI [1.02;1.58]), MAP2K5(rs2241423) (OR 1.80, 95% CI [1.04;3.41]), NRXN3(rs10146997) (OR 1.26, 95% CI [1.01;1.57]), HHEX(rs1111875) (OR 1.29, 95% CI [1.03;1.62]), FAIM2(rs7138803) (OR 0.66, 95% CI [0.48;0.91]), and apolipoprotein E4 allele (OR 0.76, 95% CI [0.59;0.98]) were associated with gallstone disease. Urinary albumin was not associated with gallstone disease. The association between BMI and gallstone disease was explained by insulin resistance.

CONCLUSIONS

Biomarkers of insulin resistance, systemic inflammation and genetic obesity or type 2 diabetes risk alleles seem to be associated with gallstone disease. Future studies should explore temporal associations and genetic associations in other populations in order to clarify targets for prevention or intervention.

The Genetics of Physical Activity

PURPOSE OF REVIEW

Physical activity (PA) is a well-established modifiable lifestyle determinant for multiple cardio-metabolic outcomes. While many psychosocial and environmental correlates of PA have been identified, current understanding of the genetic architecture that contributes to PA is still very limited, especially when compared to other phenotypes such as obesity and diabetes.

RECENT FINDINGS

This review systematically and comprehensively assesses available evidence from animal experiments, family studies, population-based candidate gene analyses, and genome-wide association studies (GWAS) studying the genetics of physical activity patterns. It discusses the scientific evolution in the field of PA genetics, including the recognition of increased sample sizes, the shift from early family-based approaches to association-based design, and the rapidly advancement of enabling genotyping and sequencing technologies. In addition, this review points to the gaps in the current knowledge base, including the general lack of GWAS and whole-genome sequence analyses particularly understudied populations, and the need for large-scale collaborative effort in both observational and experimental settings. In this review, we also call for research utilizing systems biology strategies for PA genetic research and accounting for complex gene-environment interactions that may vary by race/ethnicity. The epidemic of physical inactivity has been a public health nemesis, encompassing a large burden of diseases and high societal costs. A better understanding of the genetic basis of PA can inform public health policies for the prevention, control, and treatment of many chronic diseases related to physical inactivity.

Genetics of Insulin Resistance and the Metabolic Syndrome

Insulin resistance and the metabolic syndrome are complex metabolic traits and key risk factors for the development of cardiovascular disease. They result from the interplay of environmental and genetic factors but the full extent of the genetic background to these conditions remains incomplete. Large-scale genome-wide association studies have helped advance the identification of common genetic variation associated with insulin resistance and the metabolic syndrome, and more recently, exome sequencing has allowed the identification of rare variants associated with the pathogenesis of these conditions. Many variants associated with insulin resistance are directly involved in glucose metabolism; however, functional studies are required to assess the contribution of other variants to the development of insulin resistance. Many genetic variants involved in the pathogenesis of the metabolic syndrome are associated with lipid metabolism.

CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits

There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01–0.2%), with large effects on height (>2.4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m²). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m² for each Mb of total deletion burden (P = 2.5 × 10⁻¹⁰, 6.0 × 10⁻⁵, and 2.9 × 10⁻³). Our study provides evidence that the same genes (e.g., MC4R, FIBIN, and FMO5) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders.

Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.

Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting

Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) (p = 0.07).

Developmental Programming of Obesity and Liver Metabolism by Maternal Perinatal Nutrition Involves the Melanocortin System

Maternal obesity predisposes offspring to metabolic dysfunction and Non-Alcoholic Fatty Liver Disease (NAFLD). Melanocortin-4 receptor (Mc4r)-deficient mouse models exhibit obesity during adulthood. Here, we aim to determine the influence of the Mc4r gene on the liver of mice subjected to perinatal diet-induced obesity. Female mice heterozygous for Mc4r fed an obesogenic or a control diet for 5 weeks were mated with heterozygous males, with the same diet continued throughout pregnancy and lactation, generating four offspring groups: control wild type (C_wt), control knockout (C_KO), obese wild type (Ob_wt), and obese knockout (Ob_KO). At 21 days, offspring were genotyped, weaned onto a control diet, and sacrificed at 6 months old. Offspring phenotypic characteristics, plasma biochemical profile, liver histology, and hepatic gene expression were analyzed. Mc4r_ko offspring showed higher body, liver and adipose tissue weights respect to the wild type animals. Histological examination showed mild hepatic steatosis in offspring group C_KO. The expression of hepatic genes involved in regulating inflammation, fibrosis, and immune cell infiltration were upregulated by the absence of the Mc4r gene. These results demonstrate that maternal obesogenic feeding during the perinatal period programs offspring obesity development with involvement of the Mc4r system.

Two obesity susceptibility loci in LYPLAL1 and ETV5 independently associated with childhood hypertension in Chinese population

AIMS

Genome-wide association studies have identified novel obesity-associated susceptibility loci. Associations of these variants with childhood obesity have been studied in our previous research. The purpose of this study is to investigate if these loci are associated with hypertension being independent of obesity in Chinese children and adolescents.

METHODS

Nineteen candidate SNPs were genotyped using Sequenom MassARRAY platform among Chinese children (N=2954, 514 hypertension and 2440 controls, aged 7-17years). Dietary behaviors were assessed through face to face investigations.

RESULTS

Of the nineteen obese related SNPs, ten SNPs were found to be associated with systolic blood pressure (SBP) or diastolic blood pressure (DBP) in Chinese children. After adjusting for age, sex and WHtR, rs2605100 in LYPLAL1was found to be associated with high blood pressure (HBP) under dominant model (P=0.024) with the OR of 1.274 (95% CI =1.033-1.572, effect genotype=GG). The distribution of genotype of rs7647305 in ETV5 showed significant difference between HBP and non-HBP subjects under dominant model (P=0.011) with the OR of 0.654 (95% CI=0.471-0.909, effect genotype=CC). Using rs2605100 and rs7647305, the genetic risk score (GRS) analysis showed that, after adjusted for age, sex and WHtR, subjects carrying one or two risk alleles had the risks of hypertension with the ORs 1.797 (95% CI, 1.168-2.765), 2.149 (95% CI, 1.375-3.357) comparing with the subjects with non-risk-allele.

CONCLUSIONS

Genetic variations of obesity-associated loci, LYPLAL1 rs2605100 and ETV5 rs7647305 independently associate with the risk of childhood hypertension in China.

The contribution of genetics and environment to obesity

BACKGROUND

Obesity is a global health problem mainly attributed to lifestyle changes such as diet, low physical activity or socioeconomics factors. However, several evidences consistently showed that genetics contributes significantly to the weight-gain susceptibility.

SOURCES OF DATA

A systematic literature search of most relevant original, review and meta-analysis, restricted to English was conducted in PubMed, Web of Science and Google scholar up to May 2017 concerning the contribution of genetics and environmental factors to obesity.

AREAS OF AGREEMENT

Several evidences suggest that obesogenic environments contribute to the development of an obese phenotype. However, not every individual from the same population, despite sharing the same obesogenic environment, develop obesity.

AREAS OF CONTROVERSY

After more than 10 years of investigation on the genetics of obesity, the variants found associated with obesity represent only 3% of the estimated BMI-heritability, which is around 47-80%. Moreover, genetic factors per se were unable to explain the rapid spread of obesity prevalence.

GROWING POINTS

The integration of multi-omics data enables scientists having a better picture and to elucidate unknown pathways contributing to obesity.

AREAS TIMELY FOR DEVELOPING RESEARCH

New studies based on case-control or gene candidate approach will be important to identify new variants associated with obesity susceptibility and consequently unveiling its genetic architecture. This will lead to an improvement of our understanding about underlying mechanisms involved in development and origin of the actual obesity epidemic. The integration of several omics will also provide insights about the interplay between genes and environments contributing to the obese phenotype.

Improving power of association tests using multiple sets of imputed genotypes from distributed reference panels

The accuracy of genotype imputation depends upon two factors: the sample size of the reference panel and the genetic similarity between the reference panel and the target samples. When multiple reference panels are not consented to combine together, it is unclear how to combine the imputation results to optimize the power of genetic association studies. We compared the accuracy of 9,265 Norwegian genomes imputed from three reference panels-1000 Genomes phase 3 (1000G), Haplotype Reference Consortium (HRC), and a reference panel containing 2,201 Norwegian participants from the population-based Nord Trøndelag Health Study (HUNT) from low-pass genome sequencing. We observed that the population-matched reference panel allowed for imputation of more population-specific variants with lower frequency (minor allele frequency (MAF) between 0.05% and 0.5%). The overall imputation accuracy from the population-specific panel was substantially higher than 1000G and was comparable with HRC, despite HRC being 15-fold larger. These results recapitulate the value of population-specific reference panels for genotype imputation. We also evaluated different strategies to utilize multiple sets of imputed genotypes to increase the power of association studies. We observed that testing association for all variants imputed from any panel results in higher power to detect association than the alternative strategy of including only one version of each genetic variant, selected for having the highest imputation quality metric. This was particularly true for lower frequency variants (MAF < 1%), even after adjusting for the additional multiple testing burden.

The MC4R genotype is associated with postpartum weight reduction and glycemic changes among women with prior gestational diabetes: longitudinal analysis

The genetic variants near the Melanocortin-4 receptor gene (MC4R), a key protein regulating energy balance and adiposity, have been related to obesity and glucose metabolism. We aimed to assess whether the MC4R genotype affected longitudinal changes in body weight and glucose metabolism biomarkers among women with prior gestational diabetes mellitus (GDM). The MC4R genotype, postpartum weight reduction, and glycemic changes between after delivery and pregnancy were assessed in a cohort of 1208 Chinese women who had experienced GDM. The adiposity-increasing allele (C) of the MC4R variant rs6567160 was associated with greater postpartum increase of HbA1c (β = 0.08%; P = 0.03) and 2-hour OGTT glucose concentrations (β = 0.25 mmol/L; P = 0.02). In addition, we found an interaction between the MC4R genotype and postpartum weight reduction on changes in fasting plasma glucose (P-interaction = 0.03). We found that the MC4R genotype was associated with postpartum glycemic changes; and the association with fasting glucose were significantly modified by postpartum weight reduction in women who had experienced GDM.

Alcohol consumption and its interaction with adiposity-associated genetic variants in relation to subsequent changes in waist circumference and body weight

Background

Studies have suggested a link between alcohol intake and adiposity. However, results from longitudinal studies have been inconsistent, and a possible interaction with genetic predisposition to adiposity measures has often not been taken into account.

Objective

To examine the association between alcohol intake recorded at baseline and subsequent annual changes in body weight (∆BW), waist circumference (ΔWC) and WC adjusted for BMI (ΔWC_BMI), and to test for interaction with genetic predisposition scores based on single nucleotide polymorphisms (SNPs) associated with various forms of adiposity.

Method

This study included a total of 7028 adult men and women from MONICA, the Diet, Cancer and Health cohort (DCH), and the Inter99 studies. We combined 50 adiposity-associated SNPs into four scores indicating genetic predisposition to BMI, WC, WHR_BMI and all three traits combined. Linear regression was used to examine the association of alcohol intake (drinks of 12 g (g) alcohol/day) with ΔBW, ΔWC, and ΔWC_BMI, and to examine possible interactions with SNP-scores. Results from the analyses of the individual cohorts were combined in meta-analyses.

Results

Each additional drink/day was associated with a ΔBW/year of −18.0 g (95% confidence interval (CI): −33.4, −2.6, P = 0.02) and a ΔWC of −0.3 mm/year (−0.5, −0.0, P = 0.03). In analyses of women only, alcohol intake was associated with a higher ΔWC_BMI of 0.5 mm/year (0.2, 0.9, P = 0.002) per drink/day. Overall, we found no statistically significant interactions between the four SNP-scores and alcohol intake in relation to changes in adiposity measures. However in analyses of women separately, we found interaction between the complete score of all 50 SNPs and alcohol intake in relation to ΔBW (P for interaction = 0.03). No significant interaction was observed among the men.

Conclusion

Alcohol intake was associated with a decrease in BW and WC among men and women, and an increase in WC_BMI among women only_. We found no strong indication that these associations depend on a genetic predisposition to adiposity.

Trial registration

Registry: ClinicalTrials.gov Trial number: CT00289237, Registered: 19 September 2005 retrospectively registered.

Electronic supplementary material

The online version of this article (10.1186/s12937-017-0274-1) contains supplementary material, which is available to authorized users.

Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome

The translation of the growing increase of findings emerging from basic nutritional science into meaningful and clinically relevant dietary advices represents nowadays one of the main challenges of clinical nutrition. From nutrigenomics to deep phenotyping, many factors need to be taken into account in designing personalized and unbiased nutritional solutions for individuals or population sub-groups. Likewise, a concerted effort among basic, clinical scientists and health professionals will be needed to establish a comprehensive framework allowing the implementation of these new findings at the population level. In a world characterized by an overwhelming increase in the prevalence of obesity and associated metabolic disturbances, such as type 2 diabetes and cardiovascular diseases, tailored nutrition prescription represents a promising approach for both the prevention and management of metabolic syndrome. This review aims to discuss recent works in the field of precision nutrition analyzing most relevant aspects affecting an individual response to lifestyle/nutritional interventions. Latest advances in the analysis and monitoring of dietary habits, food behaviors, physical activity/exercise and deep phenotyping will be discussed, as well as the relevance of novel applications of nutrigenomics, metabolomics and microbiota profiling. Recent findings in the development of precision nutrition are highlighted. Finally, results from published studies providing examples of new avenues to successfully implement innovative precision nutrition approaches will be reviewed.

Genetics of body fat mass and related traits in a pig population selected for leanness

Obesity is characterized as the excessive accumulation of body fat and has a complex genetic foundation in humans including monogenic high-risk mutations and polygenic contributions. Domestic pigs represent a valuable model on an obesity-promoting high-caloric diet while constantly evaluated for body characteristics. As such, we investigated the genetics of obesity-related traits, comprising subcutaneous fat thickness, lean mass percentage, and growth rate, in a pig population. We conducted genome-wide association analyses using an integrative approach of single-marker regression models and multi-marker Bayesian analyses. Thus, we identified 30 genomic regions distributed over 14 different chromosomes contributing to the variation in obesity-related traits. In these regions, we validated the association of four candidate genes that are functionally connected to the regulation of appetite, processes of adipogenesis, and extracellular matrix formation. Our findings revealed fundamental genetic factors which deserves closer attention regarding their roles in the etiology of obesity.

Impact of the Polymorphism Near MC4R (rs17782313) on Obesity- and Metabolic-Related Traits in Women Participating in an Aerobic Training Program

The C/T polymorphism (rs17782313) mapped 188 kb downstream of the melanocortin-4 receptor gene (MC4R) shows a strong relationship with an increased body mass index (BMI) and the risk of type 2 diabetes. However, the information on polymorphism’s potential modifying effect on obesity- and metabolic-related traits achieved through training is still unknown. Therefore, we decided to check if selected body measurements observed in physically active participants would be modulated by the genotype. The genotype distribution was examined in a group of 201 Polish women measured for chosen traits before and after the completion of a 12 week moderate-intensive aerobic training program. A statistically significant relationship between the glucose level and the genotype was identified (p = 0.046). Participants with CC and CT genotypes had a higher glucose level during the entire study period compared with the TT genotype. However, our results did not confirm the relationship between the C allele and an increased BMI or other obesity-related traits. Additionally, we did not observe a near MC4R C/T polymorphism x physical activity interaction. However, our results revealed that majority of obesity-related variables changed significantly during the 12 week training program. The effect sizes (d) of these changes ranged from small to medium (d = 0.11-0.80), whereas the largest effect (d = 0.80; i.e. medium) was reported for the fat mass content (FM). We found a relationship between the near MC4R C/T polymorphism and an increased glucose level, and it is thus a candidate to influence type 2 diabetes. Interestingly, after the 12 week training program, participants with the C (risk) allele with fasting hyperglycemia had a normal glucose level. Although, this change was not statistically significant, it shows an important trend which needs further investigation.

Epidemiology in Germany-general development and personal experience

Did you ever hear about epidemiology in Germany? Starting from an epidemiological desert the discipline has grown remarkably, especially during the last 10-15 years: research institutes have been established, research funding has improved, multiple curriculae in Epidemiology and Public Health are offered. This increase has been quite steep, and now the epidemiological infrastructure is much better. Several medium-sized and even big population cohorts are ongoing, and the number and quality of publications from German epidemiologists has reached a respectable level. My own career in epidemiology started in the field of environmental health. After German reunification I concentrated for many years on environmental problems in East Germany and observed the health benefits after improvement of the situation. Later, I concentrated on population-based cohorts in newborns (GINI/LISA) and adults (KORA, German National Cohort), and on biobanking. This Essay describes the development in Germany after worldwar 2, illustrated by examples of research results and build-up of epidemiological infractructures worth mentioning.

Effects of single genetic variants and polygenic obesity risk scores on disordered eating in adolescents - The HUNT study

PURPOSE

Improving the understanding of the role of genetic risk on disordered eating (DE).

METHODS

A case-control study including 1757 (F: 979, M: 778) adolescents (aged 13-19 years) from the Nord-Trøndelag Health Study (HUNT), an ethnically homogenous Norwegian population based study. Cases and controls were defined using a shortened version of the Eating Attitude Test. Logistic regression was employed to test for associations between DE phenotypes and 24 obesity and eating disorder susceptibility SNPs, and the joint effect of a subset of these in a genetic risk score (GRS).

RESULTS

COMT was shown to be associated with poor appetite/undereating (OR: 0.6, CI 95%: 0.43-0.83, p = 0.002). Independent of obesity associations, the weighted GRS was associated to overeating in 13-15 year old females (OR: 2.07, CI 95%: 1.14-3.76, p = 0.017). Additionally, a significant association was observed between the GRS and loss of control over eating in the total sample (OR: 1.62, CI 95%: 1.01-2.61, p = 0.046).

CONCLUSIONS

The COMT variant (rs4680) was associated with poor appetite/undereating. Our study further confirms prior findings that obesity risk also confers risk for loss of control over eating; and overeating amongst girls.

The association of insertions/deletions (INDELs) and variable number tandem repeats (VNTRs) with obesity and its related traits and complications

BACKGROUND

Despite the fact that insertions/deletions (INDELs) are the second most common type of genetic variations and variable number tandem repeats (VNTRs) represent a large portion of the human genome, they have received far less attention than single nucleotide polymorphisms (SNPs) and larger forms of structural variation like copy number variations (CNVs), especially in genome-wide association studies (GWAS) of complex diseases like polygenic obesity. This is exemplified by the vast amount of review papers on the role of SNPs and CNVs in obesity, its related traits (like anthropometric measurements, biochemical variables, and eating behavior), and its related complications (like hypertension, hypertriglyceridemia, hypercholesterolemia, and insulin resistance-collectively known as metabolic syndrome). Hence, this paper reviews the types of INDELs and VNTRs that have been studied for association with obesity and its related traits and complications. These INDELs and VNTRs could be found in the obesity loci or genes from the earliest GWAS and candidate gene association studies, like FTO, genes in the leptin-proopiomelanocortin pathway, and UCP2/3. Given the important role of the brain serotonergic and dopaminergic reward system in obesity susceptibility, the association of INDELs and VNTRs in these neurotransmitters' metabolism and transport genes with obesity is also reviewed. Next, the role of INS VNTR in obesity and its related traits is questionable, since recent large-scale studies failed to replicate the earlier positive associations. As obesity results in chronic low-grade inflammation of the adipose tissue, the proinflammatory cytokine gene IL1RA and anti-inflammatory cytokine gene IL4 have VNTRs that are implicated in obesity. A systemic proinflammatory state in combination with activation of the renin-angiotensin system and decreased nitric oxide bioavailability as found in obesity leads to endothelial dysfunction. This explains why VNTR and INDEL in eNOS and ACE, respectively, could be predisposing factors of obesity. Finally, two novel genes, DOCK5 and PER3, which are involved in the regulation of the Akt/MAPK pathway and circadian rhythm, respectively, have VNTRs and INDEL that might be associated with obesity.

SHORT CONCLUSION

In conclusion, INDELs and VNTRs could have important functional consequences in the pathophysiology of obesity, and research on them should be continued to facilitate obesity prediction, prevention, and treatment.

Evidence for Association between SH2B1 Gene Variants and Glycated Hemoglobin in Nondiabetic European American Young Adults: The Add Health Study

Glycated hemoglobin (HbA1c) is used to classify glycaemia and type 2 diabetes (T2D). Body mass index (BMI) is a predictor of HbA1c levels and T2D. We tested 43 established BMI and obesity loci for association with HbA1c in a nationally representative multiethnic sample of young adults from the National Longitudinal Study of Adolescent to Adult Health [Add Health: age 24-34 years; n = 5641 European Americans (EA); 1740 African Americans (AA); 1444 Hispanic Americans (HA)] without T2D, using two levels of covariate adjustment (Model 1: age, sex, smoking, and geographic region; Model 2: Model 1 covariates plus BMI). Bonferroni adjustment was made for 43 SNPs and we considered P < 0.0011 statistically significant. Means (SD) for HbA1c were 5.4% (0.3) in EA, 5.7% (0.4) in AA, and 5.5% (0.3) in HA. We observed significant evidence for association with HbA1c for two variants near SH2B1 in EA (rs4788102, P = 2.2 × 10(-4) ; rs7359397, P = 9.8 × 10(-4) ) for Model 1. Both results were attenuated after adjustment for BMI (rs4788102, P = 1.7 × 10(-3) ; rs7359397, P = 4.6 × 10(-3) ). No variant reached Bonferroni-corrected significance in AA or HA. These results suggest that SH2B1 polymorphisms are associated with HbA1c, largely independent of BMI, in EA young adults.

Rs12970134 near MC4R is associated with appetite and beverage intake in overweight and obese children: A family-based association study in Chinese population

Background

Recent studies indicated that eating behaviors are under genetic influence, and the melanocortin 4 receptor (MC4R) gene polymorphisms can affect the total energy intake and the consumption of fat, protein and carbohydrates. Our study aims at investigating the association of the MC4R polymorphism with appetite and food intake among Chinese children.

Methods

A family-based association study was conducted among 151 Chinese trios whose offsprings were overweight/obese children aged 9–15 years. The rs12970134 near MC4R was genotyped, and the Children Eating Behavior Questionnaire (CEBQ) and a self-designed questionnaire measuring food intake were performed. The FBAT and PBAT software packages were used.

Results

The family-based association analysis showed that there was a significant association between rs12970134 and obesity (Z = 2.449, P = 0.014). After adjusting for age, gender and standardized BMI, rs12970134 was significantly associated with food responsiveness (FR) among children (β'_b = 0.077, P_b = 0.028), and with satiety responsiveness (SR) in trios (P = -0.026). The polymorphism was associated with beverage intake (β'_b = 0.331, P_b = 0.00016 in children; P = 0.043 in trios), but not significantly associated with vegetable, fruit or meat intake (P>0.050). We further found a significant mediation effect among the rs12970134, FR and beverage intake (b = 0.177, P = 0.047).

Conclusions

Our study is the first to report that rs12970134 near MC4R was associated with appetite and beverage intake, and food responsiveness could mediate the effect of rs12970134 on beverage intake in overweight and obese Chinese children population. Further studies are needed to uncover the genetic basis for eating behaviors, which could lead to develop and implement effective interventional strategies early in life.

Genes, emotions and gut microbiota: The next frontier for the gastroenterologist

Most medical specialties including the field of gastroenterology are mainly aimed at treating diseases rather than preventing them. Genomic medicine studies the health/disease process based on the interaction of the human genes with the environment. The gastrointestinal (GI) system is an ideal model to analyze the interaction between our genes, emotions and the gut microbiota. Based on the current knowledge, this mini-review aims to provide an integrated synopsis of this interaction to achieve a better understanding of the GI disorders related to bad eating habits and stress-related disease. Since human beings are the result of an evolutionary process, many biological processes such as instincts, emotions and behavior are interconnected to guarantee survival. Nourishment is a physiological need triggered by the instinct of survival to satisfy the body's energy demands. The brain-gut axis comprises a tightly connected neural-neuroendocrine circuitry between the hunger-satiety center, the dopaminergic reward system involved in the pleasure of eating and the gut microbiota that regulates which food we eat and emotions. However, genetic variations and the consumption of high-sugar and high-fat diets have overridden this energy/pleasure neurocircuitry to the point of addiction of several foodstuffs. Consequently, a gut dysbiosis generates inflammation and a negative emotional state may lead to chronic diseases. Balancing this altered processes to regain health may involve personalized-medicine and genome-based strategies. Thus, an integrated approach based on the understanding of the gene-emotions-gut microbiota interaction is the next frontier that awaits the gastroenterologist to prevent and treat GI disorders associated with obesity and negative emotions.

Microbiota manipulation for weight change

Manipulation of the intestinal microbiota has been linked to weight changes and obesity. To explore the influence of specific agents that alter the intestinal flora on weight in different patient groups we conducted a meta-analysis of randomized controlled trials (RCTs) reporting on the effects of probiotics, prebiotics, synbiotics, and antibiotics on weight. We searched the Pubmed and Cochrane Library databases for trials on adults, children, and infants evaluating the effects of these substances on weight. Our primary outcome was weight change from baseline. Standardized mean differences (SMDs) with 95% confidence intervals were calculated. We identified and included 13 adult, 17 children, and 23 infant RCTs. Effects were opposite among adults and children, showing weight loss among adults (SMD -0.54 [-0.83, -0.25)) and minor weight gains among children (SMD 0.20 [0.04, 0.36]) and infants (SMD 0.30 [-0.01, 0.62]) taking mainly Lactobacillus probiotic supplements. Heterogeneity was substantial in the adult and infant analyses and could not be explained by intervention or patient characteristics. Azithromycin administration in children with pulmonary disease was associated with weight gain (SMD 0.39 [0.24, 0.54]), without heterogeneity. A high risk of selective reporting and attrition bias was detected across the studies, making it difficult to draw firm conclusions. Overall, our meta-analysis suggests that there may be a role for probiotics in promoting weight loss in adults and weight gain in children, however additional studies are needed. Though we cannot recommend antibiotic administration for weight manipulation, its use provides advantageous weight gain in children with cystic fibrosis and bronchiectasis.

ANRIL Promoter DNA Methylation: A Perinatal Marker for Later Adiposity

Experimental studies show a substantial contribution of early life environment to obesity risk through epigenetic processes. We examined inter-individual DNA methylation differences in human birth tissues associated with child's adiposity. We identified a novel association between the level of CpG methylation at birth within the promoter of the long non-coding RNA ANRIL (encoded at CDKN2A) and childhood adiposity at age 6-years. An association between ANRIL methylation and adiposity was also observed in three additional populations; in birth tissues from ethnically diverse neonates, in peripheral blood from adolescents, and in adipose tissue from adults. Additionally, CpG methylation was associated with ANRIL expression in vivo, and CpG mutagenesis in vitro inhibited ANRIL promoter activity. Furthermore, CpG methylation enhanced binding to an Estrogen Response Element within the ANRIL promoter. Our findings demonstrate that perinatal methylation at loci relevant to gene function may be a robust marker of later adiposity, providing substantial support for epigenetic processes in mediating long-term consequences of early life environment on human health.

Recent Advances in Human Genetics and Epigenetics of Adiposity: Pathway to Precision Medicine?

Obesity is a heritable trait that contributes to substantial global morbidity and mortality. Here, we summarize findings from the past decade of genetic and epigenetic research focused on unravelling the underpinnings of adiposity. More than 140 genetic regions now are known to influence adiposity traits. The genetics of general adiposity, as measured by body mass index, and that of abdominal obesity, as measured by waist-to-hip ratio, have distinct biological backgrounds. Gene expression associated with general adiposity is enriched in the nervous system. In contrast, genes associated with abdominal adiposity function in adipose tissue. Recent population-based epigenetic analyses have highlighted additional distinct loci. We discuss how associated genetic variants can lead to understanding causal mechanisms, and to disentangling reverse causation in epigenetic analyses. Discoveries emerging from population genomics are identifying new disease markers and potential novel drug targets to better define and combat obesity and related diseases.

Causal relationship between obesity and serum testosterone status in men: A bi-directional mendelian randomization analysis

CONTEXT

Obesity in men is associated with low serum testosterone and both are associated with several diseases and increased mortality.

OBJECTIVES

Examine the direction and causality of the relationship between body mass index (BMI) and serum testosterone.

DESIGN

Bi-directional Mendelian randomization (MR) analysis on prospective cohorts.

SETTING

Five cohorts from Denmark, Germany and Sweden (Inter99, SHIP, SHIP Trend, GOOD and MrOS Sweden).

PARTICIPANTS

7446 Caucasian men, genotyped for 97 BMI-associated SNPs and three testosterone-associated SNPs.

MAIN OUTCOME MEASURES

BMI and serum testosterone adjusted for age, smoking, time of blood sampling and site.

RESULTS

1 SD genetically instrumented increase in BMI was associated with a 0.25 SD decrease in serum testosterone (IV ratio: -0.25, 95% CI: -0.42--0.09, p = 2.8*10-3). For a body weight reduction altering the BMI from 30 to 25 kg/m2, the effect would equal a 13% increase in serum testosterone. No association was seen for genetically instrumented testosterone with BMI, a finding that was confirmed using large-scale data from the GIANT consortium (n = 104349).

CONCLUSIONS

Our results suggest that there is a causal effect of BMI on serum testosterone in men. Population level interventions to reduce BMI are expected to increase serum testosterone in men.

Recent progress in genetics, epigenetics and metagenomics unveils the pathophysiology of human obesity

In high-, middle- and low-income countries, the rising prevalence of obesity is the underlying cause of numerous health complications and increased mortality. Being a complex and heritable disorder, obesity results from the interplay between genetic susceptibility, epigenetics, metagenomics and the environment. Attempts at understanding the genetic basis of obesity have identified numerous genes associated with syndromic monogenic, non-syndromic monogenic, oligogenic and polygenic obesity. The genetics of leanness are also considered relevant as it mirrors some of obesity's aetiologies. In this report, we summarize ten genetically elucidated obesity syndromes, some of which are involved in ciliary functioning. We comprehensively review 11 monogenic obesity genes identified to date and their role in energy maintenance as part of the leptin-melanocortin pathway. With the emergence of genome-wide association studies over the last decade, 227 genetic variants involved in different biological pathways (central nervous system, food sensing and digestion, adipocyte differentiation, insulin signalling, lipid metabolism, muscle and liver biology, gut microbiota) have been associated with polygenic obesity. Advances in obligatory and facilitated epigenetic variation, and gene-environment interaction studies have partly accounted for the missing heritability of obesity and provided additional insight into its aetiology. The role of gut microbiota in obesity pathophysiology, as well as the 12 genes associated with lipodystrophies is discussed. Furthermore, in an attempt to improve future studies and merge the gap between research and clinical practice, we provide suggestions on how high-throughput '-omic' data can be integrated in order to get closer to the new age of personalized medicine.

Assessing gene-environment interaction effects of FTO, MC4R and lifestyle factors on obesity using an extreme phenotype sampling design: Results from the HUNT study

BACKGROUND

Our aim was to assess the influence of age, gender and lifestyle factors on the effect of the obesity-promoting alleles of FTO and MCR4.

METHODS

The HUNT study comprises health information on the population of Nord-Trøndelag county, Norway. Extreme phenotype participants (gender-wise lower and upper quartiles of waist-hip-ratio and BMI ≥ 35 kg/m2) in the third survey, HUNT3 (2006-08), were genotyped for the single-nucleotide polymorphisms rs9939609 (FTO) and rs17782313 (MC4R); 25686 participants were successfully genotyped. Extreme sampling was chosen to increase power to detect genetic and gene-environment effects on waist-hip-ratio and BMI. Statistical inference was based on linear regression models and a missing-covariate likelihood approach for the extreme phenotype sampling design. Environmental factors were physical activity, diet (artificially sweetened beverages) and smoking. Longitudinal analysis was performed using material from HUNT2 (1995-97).

RESULTS

Cross-sectional and longitudinal genetic effects indicated stronger genetic associations with obesity in young than in old, as well as differences between women and men. We observed larger genetic effects among physically inactive compared to active individuals. This interaction was age-dependent and seen mainly in 20-40 year olds. We observed a greater FTO effect among men with a regular intake of artificially sweetened beverages, compared to non-drinkers. Interaction analysis of smoking was mainly inconclusive.

CONCLUSIONS

In a large all-adult and area-based population survey the effects of obesity-promoting minor-alleles of FTO and MCR4, and interactions with life style factors are age- and gender-related. These findings appear relevant when designing individualized treatment for and prophylaxis against obesity.

How mice are indispensable for understanding obesity and diabetes genetics

PURPOSE OF REVIEW

The task of cataloging human genetic variation and its relation to disease is rapidly approaching completion. The new challenge is to discover the function of disease-associated genes and to understand the pathways that lead to human disease. We propose that achieving this new level of understanding will increasingly rely on the use of model organisms. We discuss the advantages of the mouse as a model organism to our understanding of human disease.

RECENT FINDINGS

The collection of available mouse strains represents as much genetic and phenotypic variation as is found in the human population. However, unlike humans, mice can be subjected to experimental breeding protocols and the availability of tissues allows for a far greater and deeper level of phenotyping. New methods for gene editing make it relatively easy to create mouse models of known human mutations. The distinction between genetic and epigenetic inheritance can be studied in great detail. Various experimental protocols enable the exploration of the role of the microbiome in physiology and disease.

SUMMARY

We propose that there will be an interdependence between human and model organism research. Technological advances and new genetic screening platforms in the mouse have greatly improved the path to gene discovery and mechanistic studies of gene function.

A comprehensive survey of genetic variation in 20,691 subjects from four large cohorts

The Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)). We observed the strongest BMI association for the FTO SNP rs55872725 (β = 0.45, p = 3.48x10-22), and using a significance level of p = 0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR = 2.17, 95% CI: 1.79-2.63, p = 2.70x10-15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes.

Predicting Polygenic Obesity Using Genetic Information

Except in rare cases, obesity tends to be a consequence of both an unhealthy lifestyle and a genetic susceptibility to gain weight. With more than 200 common genetic variants identified, there is a growing interest in developing personalized preventive and treatment strategies to predict an individual's obesity risk. We review the literature on the prediction of obesity and show that models based on the established genetic variants have poorer predictive ability than traditional predictors, such as family history of obesity and childhood obesity. Current findings suggest that opportunities for precision medicine in common obesity may be limited.

A Robust and Powerful Set-Valued Approach to Rare Variant Association Analyses of Secondary Traits in Case-Control Sequencing Studies

In many case-control designs of genome-wide association (GWAS) or next generation sequencing (NGS) studies, extensive data on secondary traits that may correlate and share the common genetic variants with the primary disease are available. Investigating these secondary traits can provide critical insights into the disease etiology or pathology, and enhance the GWAS or NGS results. Methods based on logistic regression (LG) were developed for this purpose. However, for the identification of rare variants (RVs), certain inadequacies in the LG models and algorithmic instability can cause severely inflated type I error, and significant loss of power, when the two traits are correlated and the RV is associated with the disease, especially at stringent significance levels. To address this issue, we propose a novel set-valued (SV) method that models a binary trait by dichotomization of an underlying continuous variable, and incorporate this into the genetic association model as a critical component. Extensive simulations and an analysis of seven secondary traits in a GWAS of benign ethnic neutropenia show that the SV method consistently controls type I error well at stringent significance levels, has larger power than the LG-based methods, and is robust in performance to effect pattern of the genetic variant (risk or protective), rare or common variants, rare or common diseases, and trait distributions. Because of the SV method's striking and profound advantage, we strongly recommend the SV method be employed instead of the LG-based methods for secondary traits analyses in case-control sequencing studies.

A multianalytical approach to evaluate the association of 55 SNPs in 28 genes with obesity risk in North Indian adults

OBJECTIVES

The aim of the study was to investigate the association of 55 SNPs in 28 genes with obesity risk in a North Indian population using a multianalytical approach.

METHODS

Overall, 480 subjects from the North Indian population were studied using strict inclusion/exclusion criteria. SNP Genotyping was carried out by Sequenom Mass ARRAY platform (Sequenom, San Diego, CA) and validated Taqman® allelic discrimination (Applied Biosystems® ). Statistical analyses were performed using SPSS software version 19.0, SNPStats, GMDR software (version 6) and GENEMANIA.

RESULTS

Logistic regression analysis of 55 SNPs revealed significant associations (P < .05) of 49 SNPs with BMI linked obesity risk whereas the remaining 6 SNPs revealed no association (P > .05). The pathway-wise G-score revealed the significant role (P = .0001) of food intake-energy expenditure pathway genes. In CART analysis, the combined genotypes of FTO rs9939609 and TCF7L2 rs7903146 revealed the highest risk for BMI linked obesity. The analysis of the FTO-IRX3 locus revealed high LD and high order gene-gene interactions for BMI linked obesity. The interaction network of all of the associated genes in the present study generated by GENEMANIA revealed direct and indirect connections. In addition, the analysis with centralized obesity revealed that none of the SNPs except for FTO rs17818902 were significantly associated (P < .05).

CONCLUSIONS

In this multi-analytical approach, FTO rs9939609 and IRX3 rs3751723, along with TCF7L2 rs7903146 and TMEM18 rs6548238, emerged as the major SNPs contributing to BMI linked obesity risk in the North Indian population.

Sexual dimorphisms in genetic loci linked to body fat distribution

Obesity is a chronic condition associated with increased morbidity and mortality and is a risk factor for a number of other diseases including type 2 diabetes and cardiovascular disease. Obesity confers an enormous, costly burden on both individuals and public health more broadly. Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes. Body fat distribution is distinct from overall obesity in measurement, but studies of body fat distribution can yield insights into the risk factors for and causes of overall obesity. Sexual dimorphism in body fat distribution is present throughout life. Though sexual dimorphism is subtle in early stages of life, it is attenuated in puberty and during menopause. This phenomenon could be, at least in part, due to the influence of sex hormones on the trait. Findings from recent large genome-wide association studies (GWAS) for various measures of body fat distribution (including waist-to-hip ratio, hip or waist circumference, trunk fat percentage and the ratio of android and gynoid fat percentage) emphasize the strong sexual dimorphism in the genetic regulation of fat distribution traits. Importantly, sexual dimorphism is not observed for overall obesity (as assessed by body mass index or total fat percentage). Notably, the genetic loci associated with body fat distribution, which show sexual dimorphism, are located near genes that are expressed in adipose tissues and/or adipose cells. Considering the epidemiological and genetic evidence, sexual dimorphism is a prominent feature of body fat distribution. Research that specifically focuses on sexual dimorphism in fat distribution can provide novel insights into human physiology and into the development of obesity and its comorbidities, as well as yield biological clues that will aid in the improvement of disease prevention and treatment.

Validation of obesity susceptibility loci identified by genome-wide association studies in early childhood in South Brazilian children

BACKGROUND

The prevalence of childhood obesity has been dramatically increasing in developing countries as it has been reported for developed nations. Identifying susceptibility genes in early life could provide the foundations for interventions in lifestyle to prevent obese children to become obese adults.

OBJECTIVES

The objective of this study was to evaluate the influence of genetic variants related to obesity identified by genome-wide association studies (MC4R, TMEM18, KCTD15, SH2B1, SEC16B, BDNF, NEGR1, OLFM4 and HOXB5 genes) on anthropometric and dietary phenotypes in two Brazilian cohorts followed-up since birth.

METHODS

There were 745 children examined at birth, after 1 year and after 3.5 years of follow-up. Ten single nucleotide polymorphisms were genotyped. Anthropometric and dietary parameters were compared among genotypes. Children were classified as overweight when body mass index Z-score was >+1.

RESULTS

Overweight prevalence was 30.7% at 3.5 years old. Significant associations were identified at 3.5 years old for TMEM18 rs6548238, NEGR1 rs2815752, BDNF rs10767664 and rs6265 (1 year old and 3.5 years old) with anthropometric phenotypes and at 3.5 years old for SEC16B rs10913469 with dietary parameters.

CONCLUSIONS

Our results indicate that genetic variants in/near these genes contribute to obesity susceptibility in childhood and highlight the age at which they begin to affect obesity-related phenotypes.

Decreased peripheral brain-derived neurotrophic factor levels in Alzheimer's disease: a meta-analysis study (N=7277)

Studies suggest that dysfunction of brain-derived neurotrophic factor (BDNF) is a possible contributor to the pathology and symptoms of Alzheimer's disease (AD). Several studies report reduced peripheral blood levels of BDNF in AD, but findings are inconsistent. This study sought to quantitatively summarize the clinical BDNF data in patients with AD and mild cognitive impairment (MCI, a prodromal stage of AD) with a meta-analytical technique. A systematic search of Pubmed, PsycINFO and the Cochrane Library identified 29 articles for inclusion in the meta-analysis. Random-effects meta-analysis showed that patients with AD had significantly decreased baseline peripheral blood levels of BDNF compared with healthy control (HC) subjects (24 studies, Hedges' g=-0.339, 95% confidence interval (CI)=-0.572 to -0.106, P=0.004). MCI subjects showed a trend for decreased BDNF levels compared with HC subjects (14 studies, Hedges' g=-0.201, 95% CI=-0.413 to 0.010, P=0.062). No differences were found between AD and MCI subjects in BDNF levels (11 studies, Hedges' g=0.058, 95% CI=-0.120 to 0.236, P=0.522). Interestingly, the effective sizes and statistical significance improved after excluding studies with reported medication in patients (between AD and HC: 18 studies, Hedges' g=-0.492, P<0.001; between MCI and HC: 11 studies, Hedges' g=-0.339, P=0.003). These results strengthen the clinical evidence that AD or MCI is accompanied by reduced peripheral blood BDNF levels, supporting an association between the decreasing levels of BDNF and the progression of AD.

Obesity-related genetic polymorphisms and adiposity indices in a young Italian population

Pediatric obesity develops when a complex biological predisposition collides with an obesogenic environment. To further elucidate the role of genetics in obesity onset, we performed a candidate-gene association study in a young and sportive Italian population by testing the association of functional polymorphisms in ACE (rs4646994), FTO (rs9939609), MC4R (rs17782313) and PPARG (rs1801282) genes with body mass index (BMI) and waist-to-height ratio (WHtR). We also tested the combinations of identified risk genotypes and epistatic interactions among them to determine the existence of cumulative effects in predicting the predisposition to gain weight. Our results confirm a significant direct influence of MC4R rs17782313 and PPARG rs1801282 on body composition, that is, minor allele homozygotes showed significantly higher BMI (rs17782313, β = 1.258, P = 0.031; rs1801282, β = 6.689, P = 1.2 × 10^-4 ) and WHtR (rs17782313, β = 0.021, P = 0.005; rs1801282, β = 0.069, P = 0.003) values. Moreover, by leveraging multifactor dimensionality reduction and general linear model (GLM) approaches we identified an epistatic interaction between ACE and MC4R, where heterozygosity at ACE rs4646994 seems to protect from the unfavorable predisposition to gain weight given by C/C genotype at MC4R rs17782313 (GLM, P = 0.004). In conclusion, to clarify the role of genetics in multifactorial diseases remains a difficult goal, even for the most investigated polymorphisms and in controlled populations. Further studies on epistasis and gene-gene interaction will help to elucidate this complex scenario. © 2017 IUBMB Life, 69(2):98-105, 2017.

Molecular genetics of human obesity: A comprehensive review

Obesity and its related health complications is a major problem worldwide. Hypothalamus and their signalling molecules play a critical role in the intervening and coordination with energy balance and homeostasis. Genetic factors play a crucial role in determining an individual's predisposition to the weight gain and being obese. In the past few years, several genetic variants were identified as monogenic forms of human obesity having success over common polygenic forms. In the context of molecular genetics, genome-wide association studies (GWAS) approach and their findings signified a number of genetic variants predisposing to obesity. However, the last couple of years, it has also been noticed that alterations in the environmental and epigenetic factors are one of the key causes of obesity. Hence, this review might be helpful in the current scenario of molecular genetics of human obesity, obesity-related health complications (ORHC), and energy homeostasis. Future work based on the clinical discoveries may play a role in the molecular dissection of genetic approaches to find more obesity-susceptible gene loci.

Physical Activity and Sedentary Behaviors Modify the Association between Melanocortin 4 Receptor Gene Variant and Obesity in Chinese Children and Adolescents

Effects of MC4R variants in previous Chinese population studies were inconsistent. Gene-environment interactions might influence the effect of MC4R variants on obesity, which was still unclear. We performed the study to clarify the association of variants near MC4R gene with obesity-related phenotypes and gene-environment interactions in Chinese children and adolescents. Two common variants (rs12970134 and rs17782313) near MC4R were genotyped in 2179 children and adolescents aged 7-18 years in Beijing of China. Associations between the variants and obesity-related phenotypes together with gene-environment interactions were analyzed. The A-alleles of rs12970134 were nominally associated with risk of overweight/obesity (Odds Ratios (OR) = 1.21, 95%CI: 1.03-1.44, P = 0.025) and BMI (β = 0.33 kg/m2, 95%CI: 0.02-0.63, P = 0.025), respectively. The rs12970134 was also associated with HDL-C (β = -0.03mmol/L per A-allele, 95%CI: -0.05, -0.01, P = 0.013) independent of BMI. In the further analysis, we found the significant interaction of rs12970134 and physical activity/sedentary behaviors on BMI (Pinteraction = 0.043). The rs12970134 was found to be associated with BMI only in children with physical activity<1h/d and sedentary behaviors ≥2h/d (BMI: β = 1.27 kg/m2, 95%CI: 0.10-2.45, P = 0.034). The association was not detected in their counterparts with physical activity≥1h/d or sedentary behaviors <2h/d. We identified the effect of MC4R rs12970134 on overweight/obesity and BMI, and we also found physical activity and sedentary behaviors modified the association between the rs12970134 and BMI in Chinese children and adolescents.

BMI loci and longitudinal BMI from adolescence to young adulthood in an ethnically diverse cohort

Objective

The association of obesity susceptibility variants with change in body mass index (BMI) across the life course is not well understood.

Subjects

In ancestry stratified models of 5,962 European American (EA), 2,080 African American (AA), and 1,582 Hispanic American (HA) individuals from the National Longitudinal Study of Adolescent to Adult Health (Add Health), we examined associations between 34 obesity SNPs with per year change in BMI, measured by the slope from a growth-curve analysis of two or more BMI measurements between adolescence and young adulthood. For SNPs nominally associated with BMI change (p<0.05), we interrogated age differences within data collection Wave and time differences between age categories that overlapped between Waves.

Results

We found SNPs in/near FTO, MC4R, MTCH2, TFAP2B, SEC16B, and TMEM18 were significantly associated (p<0.0015 ≈ 0.05/34) with BMI change in EA and the ancestry-combined meta-analysis. Rs9939609 in FTO met genome-wide significance at p<5e-08 in the EA and ancestry combined analysis, respectively [Beta(se)=0.025(0.004);Beta(se)=0.021(0.003)]. No SNPs were significant after Bonferroni correction in AA or HA, although 5 SNPs in AA and 4 SNPs in HA were nominally significant (p<0.05). In EA and the ancestry-combined meta-analysis, rs3817334 near MTCH2 showed larger effects in younger respondents, while rs987237 near TFAP2B, showed larger effects in older respondents across all Waves. Differences in effect estimates across time for MTCH2 and TFAP2B are suggestive of either era or cohort effects.

Conclusion

The observed association between variants in/near FTO, MC4R, MTCH2, TFAP2B, SEC16B, and TMEM18 with change in BMI from adolescence to young adulthood suggest that the genetic effect of BMI loci varies over time in a complex manner, highlighting the importance of investigating loci influencing obesity risk across the life course.

Genetic risk clustering increases children's body weight at 2 years of age - the STEPS Study

BACKGROUND

Genetic determinants have an impact on adult weight but the association between genetic determinants and weight at young age is still poorly understood.

OBJECTIVE

The objective of this study was to examine the association between genetic risk scores and early growth from birth to 2 years of age.

METHODS

Genetic risk scores of 83 adiposity-related or obesity-related single nucleotide polymorphisms (SNPs) (genetic risk score [GRS]83) were calculated for 1278 children. Specific phenotype score for 16 weight-related SNPs (weightGRS) was calculated. Anthropometric data were obtained at birth, 13 months and 2 years of age.

RESULTS

The GRS83 was associated with weight at 13 months (β = 0.080, P = 0.015) and 2 years (β = 0.080, P = 0.017) of age and with weight gain from birth to 13 months (β = 0.069, P = 0.036) and to 2 years of age (β = 0.074, P = 0.028). At 2 years of age, the GRS83 was also associated with weight for height (β = 0.065, P = 0.046), weight-for-height standard deviation score (SDS) (β = 0.074, P = 0.022) and body mass index SDS (β = 0.068, P = 0.045). WeightGRS was associated with higher body weight at 13 months (β = 0.081, P = 0.014) and 2 years of age (β = 0.086, P = 0.011). The genetic effect on weight varied from 0.69 to 1.89 kg at 2 years of age according to number of risk alleles. Children with high genetic risk for adiposity were heavier than children with low genetic risk at 2 years of age (12.8 vs. 13.4 kg, P = 0.017).

CONCLUSION

The GRS 83 revealed increased genetic risk for higher weight in children already at 13 months and 2 years of age, which may result in increased obesity risk later in life.

Relationships between FTO rs9939609, MC4R rs17782313, and PPARγ rs1801282 polymorphisms and the occurrence of selected metabolic and hormonal disorders in middle-aged and elderly men - a preliminary study

PURPOSE

Metabolic disorders, including MetS, obesity, and lipid disorders, may be related to genetic factors. Metabolic disorders are associated with decreased TS levels in aging men. The aim of this study was to evaluate the relationship between FTO rs9939609, MC4R rs17782313, and PPARγ rs1801282 polymorphisms and the presence of MetS and its components, the concurrent lipid disorders, as well as sex hormone concentrations.

SUBJECTS AND METHODS

This study involved 272 men of Caucasian descent aged 50-75 years. Lipid profile, including TCh, LDL, HDL, and TG, was evaluated by spectrophotometric method. Anthropometric measurements concerned WC and blood pressure. MetS was diagnosed according to the criteria of the IDF. Sex hormone profile, including TST, FTS, E2, DHEAS, and SHBG, was examined using enzyme-linked immunosorbent assay. Polymorphisms within FTO, MC4R, and PPARγ genes were identified using polymerase chain reaction-restriction fragments length polymorphism.

RESULTS

This study did not show links between the analyzed genetic polymorphisms and the presence of MetS, T2DM, HT, and obesity. However, higher concentrations of TCh and LDL were found in men with the FTO rs9939609 polymorphism in the recessive mode of inheritance (P=0.03 and P=0.05, respectively). Lower WC was found to be associated with MC4R rs17782313 gene inherited in the same model (P=0.005).

CONCLUSION

FTO rs9939609, MC4R rs17782313, and PPARγ rs1801282 polymorphisms seem to have little effect on the incidence of metabolic malfunctions and no effect on androgen-related disorders in the examined middle-aged and elderly men.

The continuum of causality in human genetic disorders

Studies of human genetic disorders have traditionally followed a reductionist paradigm. Traits are defined as Mendelian or complex based on family pedigree and population data, whereas alleles are deemed rare, common, benign, or deleterious based on their population frequencies. The availability of exome and genome data, as well as gene and allele discovery for various conditions, is beginning to challenge classic definitions of genetic causality. Here, I discuss recent advances in our understanding of the overlap between rare and complex diseases and the context-dependent effect of both rare and common alleles that underscores the need for revising the traditional categorizations of genetic traits.

Fat mass obesity-associated (FTO) (rs9939609) and melanocortin 4 receptor (MC4R) (rs17782313) SNP are positively associated with obesity and blood pressure in Mexican school-aged children

Childhood overweight and obesity are worldwide public health problems and risk factors for chronic diseases. The presence of SNP in several genes has been associated with the presence of obesity. A total of 580 children (8-13 years old) from Queretaro, Mexico, participated in this cross-sectional study, which evaluated the associations of rs9939609 (fat mass obesity-associated (FTO)), rs17782313 (melanocortin 4 receptor (MC4R)) and rs6548238 (transmembrane protein 18 (TMEM18)) SNP with obesity and metabolic risk factors. Overweight and obesity prevalence was 19·8 and 19·1 %, respectively. FTO, MC4R and TMEM18 risk allele frequency was 17, 9·8 and 89·5 %, respectively. A significant association between FTO homozygous and MC4R heterozygous risk alleles and obesity was found (OR 3·9; 95 % CI 1·46, 10·22, and OR 2·1; 95 % CI 1·22, 3·71; respectively). The FTO heterozygous subjects showed higher systolic and diastolic blood pressures, compared with the homozygous for the ancestral allele subjects. These results remain significant after considering adiposity as a covariate. The FTO and MC4R genotypes were not significantly associated with total cholesterol, HDL-cholesterol and insulin concentration. No association was found between TMEM18 risk allele and obesity and/or metabolic alterations. Our results show that, in addition to a higher BMI, there is also an association of the risk genotype with blood pressure in the presence of the FTO risk genotype. The possible presence of a risk genotype in obese children must be considered to offer a more comprehensive therapeutic approach in order to delay and/or prevent the development of chronic diseases.

Genomic Variants Associated with Resistance to High Fat Diet Induced Obesity in a Primate Model

Maternal obesity contributes to an increased risk of lifelong morbidity and mortality for both the mother and her offspring. In order to better understand the molecular mechanisms underlying these risks, we previously established and extensively characterized a primate model in Macaca fuscata (Japanese macaque). In prior studies we have demonstrated that a high fat, caloric dense maternal diet structures the offspring’s epigenome, metabolome, and intestinal microbiome. During the course of this work we have consistently observed that a 36% fat diet leads to obesity in the majority, but not all, of exposed dams. In the current study, we sought to identify the genomic loci rendering resistance to obesity despite chronic consumption of a high fat diet in macaque dams. Through extensive phenotyping together with exon capture array and targeted resequencing, we identified three novel single nucleotide polymorphisms (SNPs), two in apolipoprotein B (APOB) and one in phospholipase A2 (PLA2G4A) that significantly associated with persistent weight stability and insulin sensitivity in lean macaques. By application of explicit orthogonal modeling (NOIA), we estimated the polygenic and interactive nature of these loci against multiple metabolic traits and their measures (i.e., serum LDL levels) which collectively render an obesity resistant phenotype in our adult female dams.

Pharmacogenetic Associations of Antipsychotic Drug-Related Weight Gain: A Systematic Review and Meta-analysis

Although weight gain is a serious but variable adverse effect of antipsychotics that has genetic underpinnings, a comprehensive meta-analysis of pharmacogenetics of antipsychotic-related weight gain is missing. In this review, random effects meta-analyses were conducted for dominant and recessive models on associations of specific single nucleotide polymorphisms (SNP) with prospectively assessed antipsychotic-related weight or body mass index (BMI) changes (primary outcome), or categorical increases in weight or BMI (≥7%; secondary outcome). Published studies, identified via systematic database search (last search: December 31, 2014), plus 3 additional cohorts, including 222 antipsychotic-naïve youth, and 81 and 141 first-episode schizophrenia adults, each with patient-level data at 3 or 4 months treatment, were meta-analyzed. Altogether, 72 articles reporting on 46 non-duplicated samples (n = 6700, mean follow-up = 25.1wk) with 38 SNPs from 20 genes/genomic regions were meta-analyzed (for each meta-analysis, studies = 2-20, n = 81-2082). Eleven SNPs from 8 genes were significantly associated with weight or BMI change, and 4 SNPs from 2 genes were significantly associated with categorical weight or BMI increase. Combined, 13 SNPs from 9 genes (Adrenoceptor Alpha-2A [ADRA2A], Adrenoceptor Beta 3 [ADRB3], Brain-Derived Neurotrophic Factor [BDNF], Dopamine Receptor D2 [DRD2], Guanine Nucleotide Binding Protein [GNB3], 5-Hydroxytryptamine (Serotonin) Receptor 2C [HTR2C], Insulin-induced gene 2 [INSIG2], Melanocortin-4 Receptor [MC4R], and Synaptosomal-associated protein, 25kDa [SNAP25]) were significantly associated with antipsychotic-related weight gain (P-values < .05-.001). SNPs in ADRA2A, DRD2, HTR2C, and MC4R had the largest effect sizes (Hedges' g's = 0.30-0.80, ORs = 1.47-1.96). Less prior antipsychotic exposure (pediatric or first episode patients) and short follow-up (1-2 mo) were associated with larger effect sizes. Individual antipsychotics did not significantly moderate effect sizes. In conclusion, antipsychotic-related weight gain is polygenic and associated with specific genetic variants, especially in genes coding for antipsychotic pharmacodynamic targets.

Association of the melanocortin 4 receptor gene rs17782313 polymorphism with rewarding value of food and eating behavior in Chilean children

Studies conducted in monozygotic and dizygotic twins have established a strong genetic component in eating behavior. Rare mutations and common variants of the melanocortin 4 receptor (MC4R) gene have been linked to obesity and eating behavior scores. However, few studies have assessed common variants in MC4R gene with the rewarding value of food in children. The objective of the study was to evaluate the association between the MC4R rs17782313 polymorphism with homeostatic and non-homeostatic eating behavior patterns in Chileans children. This is a cross-sectional study in 258 Chilean children (44 % female, 8-14 years old) showing a wide variation in BMI. Anthropometric measurements (weight, height, Z-score of BMI and waist circumference) were performed by standard procedures. Eating behavior was assessed using the Eating in Absence of Hunger Questionnaire (EAHQ), the Child Eating Behavior Questionnaire (CEBQ), the Three-Factor Eating Questionnaire (TFEQ), and the Food Reinforcement Value Questionnaire (FRVQ). Genotype of the rs17782313 nearby MC4R was determined by a Taqman assay. Association of the rs17782313 C allele with eating behavior was assessed using non-parametric tests. We found that children carrying the CC genotype have higher scores of food responsiveness (p value = 0.02). In obese girls, carriers of the C allele showed lower scores of satiety responsiveness (p value = 0.02) and higher scores of uncontrolled eating (p value = 0.01). Obese boys carrying the C allele showed lower rewarding value of food in relation to non-carriers. The rs17782313 C allele is associated with eating behavior traits that may predispose obese children to increased energy intake and obesity.