Associations of FTO and MC4R Variants with Obesity Traits in Indians and the Role of Rural/Urban Environment as a Possible Effect Modifier

Exploring Rural-Urban Differences in Polygenic Associations for Health among Older Adults in the United States

This paper contributes to research on health disparities among rural and urban residents by considering differences in the magnitude of genetic associations for physical health, mental health, and health behaviors across the two settings. Previous research has shown reduced genetic associations in rural compared to urban settings but none have utilized current genome-wide polygenic scores and none have focused on older adults. Using a sample of 14,994 adults from the 1992 to 2016 waves of the Health and Retirement Study our results suggest genetic associations for BMI (p<.018) and heart conditions (p < .023) are significantly reduced in rural compared to urban settings and we find weak evidence in support of this association for depression (p. < .065) and no evidence for smoking (p < 461). In sum, the weaker genetic associations in rural areas highlights the centrality of the social, economic, and built environment as a determinant of disparities.

Pharmacogenomics and Personalized Medicine in Type 2 Diabetes Mellitus: Potential Implications for Clinical Practice

Type 2 diabetes mellitus (T2DM) is the most common form of diabetes, and is rising in incidence with widespread prevalence. Multiple gene variants are associated with glucose homeostasis, complex T2DM pathogenesis, and its complications. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Pharmacogenomics has made precision medicine possible by allowing for individualized drug therapy based on a patient's genetic and genomic information. T2DM is treated with various classes of oral hypoglycemic agents, such as biguanides, sulfonylureas, thiazolidinediones, meglitinides, DPP4 inhibitors, SGLT2 inhibitors, α-glucosidase inhibitors, and GLP1 analogues, which exhibit various pharmacogenetic variants. Although genomic interventions in monogenic diabetes have been implemented in clinical practice, they are still in the early stages for complex polygenic disorders, such as T2DM. Precision DM medicine has the potential to be effective in personalized therapy for those suffering from various forms of DM, such as T2DM. With recent developments in genetic techniques, the application of candidate-gene studies, large-scale genotyping investigations, genome-wide association studies, and "multiomics" studies has begun to produce results that may lead to changes in clinical practice. Enhanced knowledge of the genetic architecture of T2DM presents a bigger translational potential. This review summarizes the genetics and pathophysiology of T2DM, candidate-gene approaches, genome-wide association studies, personalized medicine, clinical relevance of pharmacogenetic variants associated with oral hypoglycemic agents, and paths toward personalized diabetology.

Effect of interaction between obesity-promoting genetic variants and behavioral factors on the risk of obese phenotypes

The studies investigating gene-gene and gene-environment (or gene-behavior) interactions provide valuable insight into the pathomechanisms underlying obese phenotypes. The Pakistani population due to its unique characteristics offers numerous advantages for conducting such studies. In this view, the current study was undertaken to examine the effects of gene-gene and gene-environment/behavior interactions on the risk of obesity in a sample of Pakistani population. A total of 578 adult participants including 290 overweight/obese cases and 288 normal-weight controls were involved. The five key obesity-associated genetic variants namely MC4R rs17782313, BDNF rs6265, FTO rs1421085, TMEM18 rs7561317, and NEGR1 rs2815752 were genotyped using the TaqMan allelic discrimination assays. The data related to behavioral factors, such as eating pattern, diet consciousness, the tendency toward fat-dense food (TFDF), sleep duration, sleep-wake cycle (SWC), shift work (SW), and physical activity levels were collected via a questionnaire. Gene-gene and gene-behavior interactions were analyzed by multifactor dimensionality reduction and linear regression, respectively. In our study, only TMEM18 rs7561317 was found to be significantly associated with anthropometric traits with no significant effect of gene-gene interactions were observed on obesity-related phenotypes. However, the genetic variants were found to interact with the behavioral factors to significantly influence various obesity-related anthropometric traits including BMI, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio, and percentage of body fat. In conclusion, the interaction between genetic architecture and behavior/environment determines the outcome of obesity-related anthropometric phenotypes. Thus, gene-environment/behavior interaction studies should be promoted to explore the risk of complex and multifactorial disorders, such as obesity.

Quantile-dependent heritability of computed tomography, dual-energy x-ray absorptiometry, anthropometric, and bioelectrical measures of adiposity

Background/Objectives:

Quantile-dependent expressivity occurs when a gene’s phenotypic expression depends upon whether the trait (e.g., BMI) is high or low relative to its distribution. We have previously shown that the obesity effects of a genetic risk score (GRS_BMI) increased significantly with increasing quantiles of BMI. However, BMI is an inexact adiposity measure and GRS_BMI explains <3% of the BMI variance. The purpose of this paper is to test BMI for quantile-dependent expressivity using a more inclusive genetic measure (h², heritability in the narrow sense), extend the result to other adiposity measures, and demonstrate its consistency with purported gene-environment interactions.

Subjects/Methods:

Quantile-specific offspring-parent regression slopes (β_OP) were obtained from quantile regression for height (ht) and computed tomography (CT), dual-energy x-ray absorptiometry (DXA), anthropometric, and bioelectrical impedance (BIA) adiposity measures. Heritability was estimated by 2β_OP/(1+r_spouse) in 6,227 offspring-parent pairs from the Framingham Heart Study, where r_spouse is the spouse correlation.

Results:

Compared to h² at the 10^th percentile, genetic heritability was significantly greater at the 90^th population percentile for BMI (3.14-fold greater, P<10⁻¹⁵), waist girth/ht (3.27-fold, P<10⁻¹⁵), hip girth/ht (3.12-fold, P=6.3×10⁻¹⁴), waist-to-hip ratio (1.75-fold, P=0.01), sagittal diameter/ht (3.89-fold, P=3.7×10⁻⁷), DXA total fat/ht² (3.62-fold, P=0.0002), DXA leg fat/ht² (3.29-fold, P=2.0×10⁻¹¹), DXA arm fat/ht² (4.02-fold, P=0.001), CT-visceral fat/ht² (3.03-fold, P=0.002), and CT-subcutaneous fat/ht² (3.54-fold, P=0.0004). External validity was suggested by the phenomenon’s consistency with numerous published reports. Quantile-dependent expressivity potentially explains precision medicine markers for weight gain from overfeeding or antipsychotic medications, and the modifying effects of physical activity, sleep, diet, polycystic ovary syndrome, socioeconomic status, and depression on gene-BMI relationships.

Conclusion:

Genetic heritabilities of anthropometric, CT, and DXA adiposity measures increase with increasing adiposity. Some gene-environment interactions may arise from analyzing subjects by characteristics that distinguish high vs. low adiposity rather than the effects of environmental stimuli on transcriptional and epigenetic processes.

The interaction between dietary Non-Enzymatic Antioxidant Capacity (NEAC) with variants of Melanocortin-4 receptor (MC4R) 18q21.23-rs17782313 locus on hypothalamic hormones and cardio-metabolic risk factors in obese individuals from Iran

Background: In the current study, we aimed to evaluate the interaction between dietary Non-Enzymatic Antioxidant Capacity (NEAC) and rs17782313 polymorphism on hypothalamic hormones and cardio-metabolic risk factors. Methods: A total of 287 subjects (aged 20-50 years, 147 males and 140 females) enrolled in the cross-sectional study. Dietary NEAC was assessed using databases of NEAC measurements compiled from outcomes for three different analyses: oxygen radical absorbance capacity (ORAC), ferric reducing-antioxidant power (FRAP), and total radical-trapping antioxidant parameter (TRAP) and genotyping for the near MC4R rs17782313 was carried out by Polymerase chain reaction-restriction fragments length polymorphism (PCR-RFLP) method. Results: The significant interactions were found between adherence to the dietary NEAC and MC4R rs17782313 in relation to high-density lipoprotein-cholesterol (HDL-C), glucose, α-melanocyte stimulating hormone (α-MSH), insulin and quantitative insulin sensitivity check index (QUICKI) (P _Interaction = 0.03, 0.01, 0.04, 0.04 and 0.04, respectively). In homozygous subjects for the minor allele, the serum insulin level and QUICKI in participants with the highest adherence to TRAP were significantly higher than those with the lowest adherence (p < 0.001). There was a significant inverse association between high ORAC score and risk of metabolic syndrome even after adjusting for potential confounders (OR: 0.33; 95%CI:0.13-0.81) and also a significant inverse association between high NEAC (ORAC, FRAP and TRAP assays) score and high triglyceride (TG) level was found in obese adults. Conclusion: In conclusion, our study found for the first time that the NEAC significantly interacts with the rs17782313 genotypes to influence several metabolic risk factors in obesity.

Dietary quality indices modifies the effects of melanocortin-4 receptor (MC4R) rs17782313 polymorphism on cardio-metabolic risk factors and hypothalamic hormones in obese adults

BACKGROUND

Although the Melanocortin-4 Receptor (MC4R) gene rs17782313 C/T has been consistently related to obesity risk, the interaction between MC4R polymorphism and diet quality indices on cardio-metabolic risk factors has not yet investigated. Therefore we aimed to test this hypothesis.

METHODS

This cross-sectional study recruited 188 (96 males and 92 females) healthy obese adults aged 20-50 years. Diet quality indices including Healthy Eating Index-2015 (HEI-2015) and Diet Quality Index-International (DQI-I) were constructed using data from a validated food frequency questionnaire. MC4R s17782313 were genotyped by Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP). The interaction between MC4R polymorphism and diet quality indices was tested by Analysis of covariance (ANCOVA) multivariate interaction model.

RESULTS

There were significant gene-diet interactions between rs17782313 and HEI-2015 (P Interaction < 0.05) in modulating low-density lipoprotein cholesterol (LDL-C) levels among female group; rare allele heterozygotes of rs17782313 had highest mean of LDL-C concentration when placed in second tertile of HEI (P < 0.05). Moreover, rs17782313 and both indices (HEI and DQI-I) had significant interaction on serum glucose concentrations, systolic and diastolic blood pressure (SBP, DBP) in males (P Interaction < 0.05); when adherence to these indices was low, the obesity risk allele was associated with serum glucose concentrations, SBP and DBP. These gene-diet interactions remained significant even after adjustment for potential confounders.

CONCLUSION

Our study showed that MC4R rs17782313 interacts with adherence to the dietary quality indices (HEI and DQI-I) to influence several cardio-metabolic risk factors in obese male and females. Further large prospective studies are warranted to confirm our findings.

Assessment of FTO Gene Polymorphism and its Association with Type 2 Diabetes Mellitus in North Indian Populations

FTO gene polymorphism related to type 2 diabetes and obesity was studied in this north Indian population. This study was done, due to a continuous increase in the risk of obesity and type 2 diabetes in north Indian population, because of lifestyle and genetic variations. Clinically diagnosed subjects of type 2 diabetes mellitus (as per ADA criteria) were taken as cases and age and sex matched subjects without any associated illness were taken as controls. Obesity was estimated by calculating waist circumference and BMI in the study cases and controls. For genetic variation, DNA was isolated with Quaigen kit method and isolated DNA was amplified with PCR. Amplified DNA was resolved in 1% agarose gel electrophoresis. The Hardy-Weinberg equilibrium, OR, CI and P value were calculated using standard protocols. FTO gene polymorphism (SNP 9940128) was found to be significantly correlated with type 2 diabetes mellitus and obesity. The AG genotype frequency was observed to be higher (13.09%) with (P < 0.0001) in the cases as compared to controls. Logistic regression analysis was conducted for AG and GG genotypes with respect to AA. In this novel study genetic co-relation was observed between FTO gene polymorphisms and type 2 diabetes and obesity in the north Indian population.

Genetics of obesity and its measures in India

Obesity is one of the largest global health problems associated with increased morbidity and mortality mediated by its association with several other metabolic disorders. The interaction between the genes and environment plays an important role in the manifestation of obesity. Despite a high heritability (40-70%) of obesity, the search for genetic variants associated with obesity susceptibility has been a challenging task. To date, limited studies have been conducted in India, restricted to the validation of few genetic variants identified by genomewide association studies. In this critical review, we sought to examine the current knowledge of genetic basis of obesity and its measures in the Indian population. A comprehensive literature search was performed using 'PubMed', 'Medline' and 'IndMed' databases to search for citations published until 31st May 2017, using the key terms as 'Genetics' AND 'obesity' AND 'India'. We identified 48 potential studies which fulfilled the eligibility criteria. The findings indicated that FTO, MC4R, TNF-α, PPAR-γ , UCP1, UCP2, LPL, LEPR, AMD1, IL6, APOE, ADIPOQ, DOK5, INSIG2, PBEF1, IL6R, Myostatin, CXCR4, HHEX, IRX3, POMC, NGN3, FOXA2, MTR, TCN and CHDH are some of the important genes studied among the Indian population. Importantly, the role of sexual dimorphism in the genetic regulation of obesity and body fat distribution was also reported in a few studies. Further, seven biological pathways have been identified that contribute to obesity pathogenesis in India. In conclusion, further exploration of pathway-based research on genetics of obesity can be useful for better understanding the pathophysiology of obesity in India.

Obesity genetics: insights from the Pakistani population

The Pakistani population is extensively diverse, indicating a genetic admixture of European and Central/West Asian migrants with indigenous South Asian gene pools. Pakistanis are organized in different ethnicities/castes based on cultural, linguistic and geographical origin. While Pakistan is facing a rapid nutritional transition, the rising prevalence of obesity is driving a growing burden of health complications and mortality. This represents a unique opportunity for the research community to study the interplay between obesogenic environmental changes and obesity predisposing genes in the time frame of one generation. This review recapitulates the ancestral origins of Pakistani population, the societal determinants of the rise in obesity and its governmental management. We describe the contribution of syndromic, monogenic non-syndromic and polygenic obesity genes identified in the Pakistani population. We then discuss the utility of gene identification approaches based on large consanguineous families and original gene × environment interaction study designs in discovering new obesity genes and causal pathways. Elucidation of the genetic basis of obesity in the Pakistani population may result in improved methods of obesity prevention and treatment globally.

Genetics of obesity: what genetic association studies have taught us about the biology of obesity and its complications

Genome-wide association studies (GWAS) for BMI, waist-to-hip ratio, and other adiposity traits have identified more than 300 single-nucleotide polymorphisms (SNPs). Although there is reason to hope that these discoveries will eventually lead to new preventive and therapeutic agents for obesity, this will take time because such developments require detailed mechanistic understanding of how an SNP influences phenotype (and this information is largely unavailable). Fortunately, absence of functional information has not prevented GWAS findings from providing insights into the biology of obesity. Genes near loci regulating total body mass are enriched for expression in the CNS, whereas genes for fat distribution are enriched in adipose tissue itself. Gene by environment and lifestyle interaction analyses have revealed that our increasingly obesogenic environment might be amplifying genetic risk for obesity, yet those at highest risk could mitigate this risk by increasing physical activity and possibly by avoiding specific dietary components. GWAS findings have also been used in mendelian randomisation analyses probing the causal association between obesity and its many putative complications. In supporting a causal association of obesity with diabetes, coronary heart disease, specific cancers, and other conditions, these analyses have clinical relevance in identifying which outcomes could be preventable through weight loss interventions.

MC4R variant rs17782313 and manifestation of obese phenotype in Pakistani females

MC4R represents a key player involved in melanocortin-mediated control of energy balance. Recently identified near MC4R variant rs17782313 (T > C) can serve as a contributing factor for obese phenotype but its association with obesity has never been sought in a sample of the Pakistani population. The role of genetic variants as causal factors varies across populations. Association studies in a specific population can help us to distinguish global from local gene–gene and gene–environment interactions. This is the first study that investigated the association of rs17782313 with obesity and various obesity-linked anthropometric, metabolic, physical, and behavioural traits in Pakistani subjects including 306 OW/OB (overweight and obese) and 300 NW (normal weight) individuals. The comparison of various aforementioned obesity-linked continuous and categorical variables between OW/OB and NW subjects revealed that almost all variables were found significantly aberrant (p < 0.05) in OW/OB subjects as compared to their age- and gender-matched NW controls indicating greater risk of developing various cardio-metabolic disorders. The genotyping of rs17782313 showed significant association of this variant with obesity and obesity-linked anthropometric traits in females suggesting the gender-specific effect of this variant in our population. The minor allele C increased the risk of obesity by 1.55 times (95% CI = 1.1–2.18, p = 0.01) whereas homozygous CC genotype increased the risk by 2.43 times (95% CI = 1.19–4.96, p = 0.015) in females. However, no association of rs17782313 was observed with any of the obesity-linked metabolic, physical, and behavioural traits except random eating timings. In conclusion, the current study significantly contributes to the knowledge of the genetic proneness to obesity in Pakistani females. This could also be helpful for forthcoming meta-analysis studies elucidating which variants are truly associated with the susceptibility to develop an obese phenotype.

The current study significantly contributes to the knowledge of the genetic proneness to obesity in Pakistani females and could also be helpful for forthcoming meta-analysis studies.

Ethnic and population differences in the genetic predisposition to human obesity

Obesity rates have escalated to the point of a global pandemic with varying prevalence across ethnic groups. These differences are partially explained by lifestyle factors in addition to genetic predisposition to obesity. This review provides a comprehensive examination of the ethnic differences in the genetic architecture of obesity. Using examples from evolution, heritability, admixture, monogenic and polygenic studies of obesity, we provide explanations for ethnic differences in the prevalence of obesity. The debate over definitions of race and ethnicity, the advantages and limitations of multi-ethnic studies and future directions of research are also discussed. Multi-ethnic studies have great potential to provide a better understanding of ethnic differences in the prevalence of obesity that may result in more targeted and personalized obesity treatments.

Interaction between TCF7L2 polymorphism and dietary fat intake on high density lipoprotein cholesterol

Recent evidence suggests that lifestyle factors influence the association between the Melanocortin 4 receptor (MC4R) and Transcription Factor 7-Like 2 (TCF7L2) gene variants and cardio-metabolic traits in several populations; however, the available research is limited among the Asian Indian population. Hence, the present study examined whether the association between the MC4R single nucleotide polymorphism (SNP) (rs17782313) and two SNPs of the TCF7L2 gene (rs12255372 and rs7903146) and cardio-metabolic traits is modified by dietary factors and physical activity. This cross sectional study included a random sample of normal glucose tolerant (NGT) (n = 821) and participants with type 2 diabetes (T2D) (n = 861) recruited from the urban part of the Chennai Urban Rural Epidemiology Study (CURES). A validated food frequency questionnaire (FFQ) was used for dietary assessment and self-reported physical activity measures were collected. The threshold for significance was set at P = 0.00023 based on Bonferroni correction for multiple testing [(0.05/210 (3 SNPs x 14 outcomes x 5 lifestyle factors)]. After Bonferroni correction, there was a significant interaction between the TCF7L2 rs12255372 SNP and fat intake (g/day) (P_interaction = 0.0001) on high-density lipoprotein cholesterol (HDL-C), where the ‘T’ allele carriers in the lowest tertile of total fat intake had higher HDL-C (P = 0.008) and those in the highest tertile (P = 0.017) had lower HDL-C compared to the GG homozygotes. In a secondary analysis of SNPs with the subtypes of fat, there was also a significant interaction between the SNP rs12255372 and polyunsaturated fatty acids (PUFA, g/day) (P_interaction<0.0001) on HDL-C, where the minor allele carriers had higher HDL-C in the lowest PUFA tertile (P = 0.024) and those in the highest PUFA tertile had lower HDL-C (P = 0.028) than GG homozygotes. In addition, a significant interaction was also seen between TCF7L2 SNP rs12255372 and fibre intake (g/day) on HDL-C (P_interaction<0.0001). None of the other interactions between the SNPs and lifestyle factors were statistically significant after correction for multiple testing. Our findings indicate that the association between TCF7L2 SNP rs12255372 and HDL-C may be modified by dietary fat intake in this Asian Indian population.

The importance of gene-environment interactions in human obesity

The worldwide obesity epidemic has been mainly attributed to lifestyle changes. However, who becomes obese in an obesity-prone environment is largely determined by genetic factors. In the last 20 years, important progress has been made in the elucidation of the genetic architecture of obesity. In parallel with successful gene identifications, the number of gene-environment interaction (GEI) studies has grown rapidly. This paper reviews the growing body of evidence supporting gene-environment interactions in the field of obesity. Heritability, monogenic and polygenic obesity studies provide converging evidence that obesity-predisposing genes interact with a variety of environmental, lifestyle and treatment exposures. However, some skepticism remains regarding the validity of these studies based on several issues, which include statistical modelling, confounding, low replication rate, underpowered analyses, biological assumptions and measurement precision. What follows in this review includes (1) an introduction to the study of GEI, (2) the evidence of GEI in the field of obesity, (3) an outline of the biological mechanisms that may explain these interaction effects, (4) methodological challenges associated with GEI studies and potential solutions, and (5) future directions of GEI research. Thus far, this growing body of evidence has provided a deeper understanding of GEI influencing obesity and may have tremendous applications in the emerging field of personalized medicine and individualized lifestyle recommendations.

Western diet in the perinatal period promotes dysautonomia in the offspring of adult rats

The present study investigated the impact of a western diet during gestation and lactation on the anthropometry, serum biochemical, blood pressure and cardiovascular autonomic control on the offspring. Male Wistar rats were divided into two groups according to their mother's diet received: control group (C: 18% calories of lipids) and westernized group (W: 32% calories of lipids). After weaning both groups received standard diet. On the 60th day of life, blood samples were collected for the analysis of fasting glucose and lipidogram. Cardiovascular parameters were measured on the same period. Autonomic nervous system modulation was evaluated by spectrum analysis of heart rate (HR) and systolic arterial pressure (SAP). The W increased glycemia (123±2 v. 155±2 mg/dl), low-density lipoprotein (15±1 v. 31±2 mg/dl), triglycerides (49±1 v. 85±2 mg/dl), total cholesterol (75±2 v. 86±2 mg/dl), and decreased high-density lipoprotein (50±4 v. 38±3 mg/dl), as well as increased body mass (209±4 v. 229±6 g) than C. Furthermore, the W showed higher SAP (130±4 v. 157±2 mmHg), HR (357±10 v. 428±14 bpm), sympathetic modulation to vessels (2.3±0.56 v. 6±0.84 mmHg2) and LF/HF ratio (0.15±0.01 v. 0.7±0.2) than C. These findings suggest that a western diet during pregnancy and lactation leads to overweight associated with autonomic misbalance and hypertension in adulthood.

Effect of interactions of polymorphisms in the Melanocortin-4 receptor gene with dietary factors on the risk of obesity and Type 2 diabetes: a systematic review

AIM

To perform a systematic review of the effect of interaction between Melanocortin-4 receptor (MC4R) single nucleotide polymorphisms and diet on the development of obesity and Type 2 diabetes.

BACKGROUND

Environmental factors, such as nutrient intakes or feeding behaviours, can modulate the association of polymorphism in the MC4R gene with obesity and Type 2 diabetes mellitus.

METHODS

A systematic literature search was conducted in the PubMed, Scopus and Google Scholar databases, with a combination of the following keywords: Diet*, nutr*, melanocortin receptor, melanocortin 4 receptor and MC4R. To assess the quality of observational studies, we used a 12-item quality checklist, derived from the STREGA statement.

RESULTS

A total of 14 articles were selected based on the inclusion and exclusion criteria. Consumption of highly salty foods and adherence to a Mediterranean dietary pattern can modulate the association between MC4R polymorphisms and the risk of obesity or Type 2 diabetes. Despite the highly contradictory results of intervention studies, after short-term lifestyle interventions, children with variant alleles of MC4R single nucleotide polymorphisms can lose more body weight, compared with non-carriers, although they may have difficulty in maintaining this weight loss in the long-term. To interpret the results of studies on adults, we need further studies.

CONCLUSIONS

The interaction between MC4R genes with dietary factors plays a significant role in the development of obesity or Type 2 diabetes phenotypes. Early detection of MC4R risk alleles in individuals and modification of their diet based on these results could be an efficient strategy to prevent obesity or diabetes in these subgroups.

The Elevated Susceptibility to Diabetes in India: An Evolutionary Perspective

India has rapidly become a "diabetes capital" of the world, despite maintaining high rates of under-nutrition. Indians develop diabetes at younger age and at lower body weights than other populations. Here, we interpret these characteristics in terms of a "capacity-load" model of glucose homeostasis. Specifically, we assume that glycemic control depends on whether the body's "metabolic capacity," referring to traits, such as pancreatic insulin production and muscle glucose clearance, is able to resolve the "metabolic load" generated by high levels of body fat, high dietary glycemic load, and sedentary behavior. We employ data from modern cohorts to support the model and the interpretation that elevated diabetic risk among Indian populations results from the high metabolic load imposed by westernized lifestyles acting on a baseline of low metabolic capacity. We attribute this low metabolic capacity to the low birth weight characteristic of Indian populations, which is associated with short stature and low lean mass in adult life. Using stature as a marker of metabolic capacity, we review archeological and historical evidence to highlight long-term declines in Indian stature associated with adaptation to several ecological stresses. Underlying causes may include increasing population density following the emergence of agriculture, the spread of vegetarian diets, regular famines induced by monsoon failure, and the undermining of agricultural security during the colonial period. The reduced growth and thin physique that characterize Indian populations elevate susceptibility to truncal obesity, and increase the metabolic penalties arising from sedentary behavior and high glycemic diets. Improving metabolic capacity may require multiple generations; in the meantime, efforts to reduce the metabolic load will help ameliorate the situation.

Interaction between FTO gene variants and lifestyle factors on metabolic traits in an Asian Indian population

Background

Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity–associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D).

Methods

The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model.

Results

There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (P_interaction = 0.04), where the ‘A’ allele carriers had 2.46 times increased risk of obesity than those with ‘CC’ genotype (P = 3.0 × 10⁻⁵) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (P_interaction = 0.0008), where individuals with AA genotype who are in the 3^rd tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with ‘T’ allele carriers (P = 0.02). Furthermore, among those who were physically inactive, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with ‘CC’ genotype (P = 4.0 × 10⁻⁵).

Conclusions

This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population.

Electronic supplementary material

The online version of this article (doi:10.1186/s12986-016-0098-6) contains supplementary material, which is available to authorized users.

Genetic association studies of obesity in Africa: a systematic review

Obesity is increasing in Africa, but the underlying genetic background largely remains unknown. We assessed existing evidence on genetic determinants of obesity among populations within Africa. MEDLINE and EMBASE were searched and the bibliographies of retrieved articles were examined. Included studies had to report on the association of a genetic marker with obesity indices and the presence/occurrence of obesity/obesity trait. Data were extracted on study design and characteristics, genetic determinants and effect estimates of associations with obesity indices. According to this data, over 300 polymorphisms in 42 genes have been studied in various population groups within Africa mostly through the candidate gene approach. Polymorphisms in genes such as ACE, ADIPOQ, ADRB2, AGRP, AR, CAPN10, CD36, C7orf31, DRD4, FTO, MC3R, MC4R, SGIP1 and LEP were found to be associated with various measures of obesity. Of the 36 polymorphisms previously validated by genome-wide association studies (GWAS) elsewhere, only FTO and MC4R polymorphisms showed significant associations with obesity in black South Africans, Nigerians and Ghanaians. However, these data are insufficient to establish the true nature of genetic susceptibility to obesity in populations within Africa. There has been recent progress in describing the genetic architecture of obesity among populations within Africa. This effort needs to be sustained via GWAS studies.

Is vulnerability to cardiometabolic disease in Indians mediated by abdominal adiposity or higher body adiposity

Background

Indians may be particularly vulnerable to cardiometabolic disease, potentially due to higher body fat for a given BMI, or a tendency towards depositing abdominal adiposity. The aim of the study is to assess whether different measures of the distribution of adiposity (abdominal versus whole body) or amount of adiposity (DXA versus traditional anthropometric) are better at predicting prevalent cardiometabolic risk markers in an Indian population.

Methods

Participants were recruited from the Indian Migration Study (IMS) and the Andhra Pradesh Children and Parent Study (APCAPS). Participants attended a clinic in Hyderabad, India, January 2009-December 2010. Adiposity was measured by conventional anthropometry (including weight, height, waist) and DXA scanning (whole body and abdominal). Blood samples were taken and assessed for fasting plasma glucose, insulin, cholesterol, and triglycerides and blood pressure was measured. Lifestyle data were collected by questionnaire.

Results

We invited 4 617 participants to the clinic (1 995 IMS; 2 622 APCAPS) and examined 918 from IMS (46%) and 1 451 from APCAPS (55%). There were strong and consistent relationships between adiposity and cardiometabolic risk factors. Cardiometabolic risk factors did not appear to be more strongly associated with DXA measures as opposed to BMI, or skinfold measures of body fat. There was some evidence that WHR was more closely related to diabetes than total body adiposity, but this was not apparent for the other measures of abdominal adiposity (DXA measures, waist circumference) or other cardiometablic risk factors.

Conclusions

No strong evidence supports that DXA measures or abdominal measures of adiposity are better at predicting the prevalence of cardiometabolic risk factors in comparison to BMI.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2458-14-1239) contains supplementary material, which is available to authorized users.

Gene-environment dependence creates spurious gene-environment interaction

Gene-environment interactions have the potential to shed light on biological processes leading to disease and to improve the accuracy of epidemiological risk models. However, relatively few such interactions have yet been confirmed. In part this is because genetic markers such as tag SNPs are usually studied, rather than the causal variants themselves. Previous work has shown that this leads to substantial loss of power and increased sample size when gene and environment are independent. However, dependence between gene and environment can arise in several ways including mediation, pleiotropy, and confounding, and several examples of gene-environment interaction under gene-environment dependence have recently been published. Here we show that under gene-environment dependence, a statistical interaction can be present between a marker and environment even if there is no interaction between the causal variant and the environment. We give simple conditions under which there is no marker-environment interaction and note that they do not hold in general when there is gene-environment dependence. Furthermore, the gene-environment dependence applies to the causal variant and cannot be assessed from marker data. Gene-gene interactions are susceptible to the same problem if two causal variants are in linkage disequilibrium. In addition to existing concerns about mechanistic interpretations, we suggest further caution in reporting interactions for genetic markers.

FTO genetic variants, dietary intake and body mass index: insights from 177,330 individuals

FTO is the strongest known genetic susceptibility locus for obesity. Experimental studies in animals suggest the potential roles of FTO in regulating food intake. The interactive relation among FTO variants, dietary intake and body mass index (BMI) is complex and results from previous often small-scale studies in humans are highly inconsistent. We performed large-scale analyses based on data from 177,330 adults (154 439 Whites, 5776 African Americans and 17 115 Asians) from 40 studies to examine: (i) the association between the FTO-rs9939609 variant (or a proxy single-nucleotide polymorphism) and total energy and macronutrient intake and (ii) the interaction between the FTO variant and dietary intake on BMI. The minor allele (A-allele) of the FTO-rs9939609 variant was associated with higher BMI in Whites (effect per allele = 0.34 [0.31, 0.37] kg/m(2), P = 1.9 × 10(-105)), and all participants (0.30 [0.30, 0.35] kg/m(2), P = 3.6 × 10(-107)). The BMI-increasing allele of the FTO variant showed a significant association with higher dietary protein intake (effect per allele = 0.08 [0.06, 0.10] %, P = 2.4 × 10(-16)), and relative weak associations with lower total energy intake (-6.4 [-10.1, -2.6] kcal/day, P = 0.001) and lower dietary carbohydrate intake (-0.07 [-0.11, -0.02] %, P = 0.004). The associations with protein (P = 7.5 × 10(-9)) and total energy (P = 0.002) were attenuated but remained significant after adjustment for BMI. We did not find significant interactions between the FTO variant and dietary intake of total energy, protein, carbohydrate or fat on BMI. Our findings suggest a positive association between the BMI-increasing allele of FTO variant and higher dietary protein intake and offer insight into potential link between FTO, dietary protein intake and adiposity.

Evaluation of MC4R [rs17782313, rs17700633], AGRP [rs3412352] and POMC [rs1042571] Polymorphisms with Obesity in Northern India

OBJECTIVE

Genetic variants of the melanocortin-4 receptor gene (MC4R), agouti related protein (AGRP) and proopiomelanocortin (POMC) are reported to be associated with obesity. Therefore, the aim of this study is to examine MC4R rs17782313, MC4R rs17700633, AGRP rs3412352 and POMCrs1042571 for any association with obesity in North Indian subjects.

METHODS

The variants were investigated for association in 300 individuals with BMI ≥30 kg/m(2) and 300 healthy non-obese individuals BMI <30 kg/m(2.) The genotyping were analyzed by Taqman probes. The statistical analysis was performed by the SPSS software, ver.19 and p≤0.05 was considered statistically significant.

RESULTS

The genotypes of MC4R rs17782313 and POMC rs1042571 were significantly associated with obesity (C), (p=0.02; OR=1.7 and p=0.01; OR=1.6, respectively); however, MC4Rrs17700633 (p=0.001; OR=0.55) was associated with low risk. In addition, AGRPrs3412352 (p=0.93; OR=0.96) showed no association with obesity (BMI ≥30 kg/m(2)) in North Indian subjects.

CONCLUSION

This study provides the report about the significant association of MC4R (rs17782313) and POMC (rs1042571) with morbid obesity (BMI ≥30 kg/m(2)), but MC4R (rs17700633) and AGRP (rs34123523) did not show any association with obesity in the studied North Indian population.

FTO genetic variants and risk of obesity and type 2 diabetes: a meta-analysis of 28,394 Indians

OBJECTIVE

To investigate the magnitude of association of FTO variants with obesity, type 2 diabetes (T2DM), and related traits among Asian Indians.

METHODS

Random-effect meta-analysis was performed on pooled data from eight studies (n = 28,394) for obesity and related traits and six studies (n = 24,987) for assessment of T2DM risk in Indians where FTO variants were reported.

RESULTS

The minor A-allele of the FTO variant rs9939609 was associated with increased risk of obesity (OR 1.15, 95% CI 1.08-1.21, p = 2.14 × 10(-) (5) ), BMI (β = 0.30 kg/m2, 95% CI 0.21-0.38, p = 4.78 × 10(-) (11) ) and other regional adiposity measurements [waist (β = 0.74 cm, 95% CI 0.49-0.99), HC (β = 0.52, 95% CI 0.26-0.78), and waist-hip ratio (WHR) (β = 0.002, 95% CI 0.001-0.004)] in Indians (p ≤ 0.001). An increased risk for T2DM (OR 1.11; 95% CI 1.04-1.19, p = 0.002) was observed, which attenuated when adjusted for age, gender, and BMI (OR 1.09; 95%CI 1.02-1.16, p = 0.01).

CONCLUSIONS

Our study provides evidence of association between common FTO variant and obesity risk among Indians with comparable effect sizes as in Caucasians. The attenuation of FTO-T2DM risk on BMI adjustment reinforces that BMI does not fully account for the adiposity effects among Asian Indians who are more centrally obese.

Etiology of Obesity Over the Life Span: Ecological and Genetic Highlights from Asian Countries

Obesity is a worldwide pandemic, and the prevalence rate has doubled since the 1980s. Asian countries are also experiencing the global epidemic of obesity with its related health consequences. The prevalence of overweight and obesity are increasing at an alarming rate across all age groups in Asia. These increases are mainly attributed to rapid economic growth, which leads to socio-economic, nutrition and lifestyle transitions, resulting in a positive energy balance. In addition, fat mass and obesity-associated gene variants, copy number variants in chromosomes and epigenetic modifications have shown positive associations with the risk of obesity among Asians. In this review highlights of prevalence and related ecological and genetic factors that could influence the rapid rise in obesity among Asian populations are discussed.

Genotype-environment interactions for quantitative traits in Korea Associated Resource (KARE) cohorts

Background

Due to the lack of statistical power and confounding effects of population structure in human population data, genotype-environment interaction studies have not yielded promising results and have provided only limited knowledge for exploring how genotype and environmental factors interact to in their influence onto risk.

Results

We analyzed 49 human quantitative traits in 7,170 unrelated Korean individuals on 326,262 autosomal single nucleotide polymorphisms (SNPs) collected from the KARE (Korean Association Resource) project, and we estimated the statistically significant proportion of variance that could be explained by genotype-area interactions in the supra-iliac skinfold thickness trait (hGE2 = 0.269 and P = 0.00032), which is related to abdominal obesity. Data suggested that the genotypes could have different effects on the phenotype (supra-iliac skinfold thickness) in different environmental settings (rural vs. urban areas). We then defined the genotype groups of individuals with similar genetic profiles based on the additive genetic relationships among individuals using SNPs. We observed the norms of reaction, and the differential phenotypic response of a genotype to a change in environmental exposure. Interestingly, we also found that the gene clusters responsible for cell-cell and cell-extracellular matrix interactions were enriched significantly for genotype-area interaction.

Conclusions

This significant heritability estimate of genotype-environment interactions will lead to conceptual advances in our understanding of the mechanisms underlying genotype-environment interactions, and could be ultimately applied to personalized preventative treatments based on environmental exposures.

The bigger picture of FTO: the first GWAS-identified obesity gene

Single nucleotide polymorphisms (SNPs) that cluster in the first intron of fat mass and obesity associated (FTO) gene are associated obesity traits in genome-wide association studies. The minor allele increases BMI by 0.39 kg/m(2) (or 1,130 g in body weight) and risk of obesity by 1.20-fold. This association has been confirmed across age groups and populations of diverse ancestry; the largest effect is seen in young adulthood. The effect of FTO SNPs on obesity traits in populations of African and Asian ancestry is similar or somewhat smaller than in European ancestry populations. However, the BMI-increasing allele in FTO is substantially less prevalent in populations with non-European ancestry. FTO SNPs do not influence physical activity levels; yet, in physically active individuals, FTO's effect on obesity susceptibility is attenuated by approximately 30%. Evidence from epidemiological and functional studies suggests that FTO confers an increased risk of obesity by subtly changing food intake and preference. Moreover, emerging data suggest a role for FTO in nutrient sensing, regulation of mRNA translation and general growth. In this Review, we discuss the genetic epidemiology of FTO and discuss how its complex biology might link to the regulation of body weight.

Variation at diabetes- and obesity-associated Loci may mirror neutral patterns of human population diversity and diabetes prevalence in India

South Asian populations harbor a high degree of genetic diversity, due in part to demographic history. Two studies on genome-wide variation in Indian populations have shown that most Indian populations show varying degrees of admixture between ancestral north Indian and ancestral south Indian components. As a result of this structure, genetic variation in India appears to follow a geographic cline. Similarly, Indian populations seem to show detectable differences in diabetes and obesity prevalence between different geographic regions of the country. We tested the hypothesis that genetic variation at diabetes- and obesity-associated loci may be potentially related to different genetic ancestries. We genotyped 2977 individuals from 61 populations across India for 18 SNPs in genes implicated in T2D and obesity. We examined patterns of variation in allele frequency across different geographical gradients and considered state of origin and language affiliation. Our results show that most of the 18 SNPs show no significant correlation with latitude, the geographic cline reported in previous studies, or by language family. Exceptions include KCNQ1 with latitude and THADA and JAK1 with language, which suggests that genetic variation at previously ascertained diabetes-associated loci may only partly mirror geographic patterns of genome-wide diversity in Indian populations.

Obesity genomics: assessing the transferability of susceptibility loci across diverse populations

The prevalence of obesity has nearly doubled worldwide over the past three decades, but substantial differences exist between nations. Although these differences are partly due to the degree of westernization, genetic factors also contribute. To date, little is known about whether the same genes contribute to obesity-susceptibility in populations of different ancestry. We review the transferability of obesity-susceptibility loci (identified by genome-wide association studies) using both single nucleotide polymorphism (SNP) and locus-wide comparisons. SNPs in FTO and near MC4R, obesity-susceptibility loci first identified in Europeans, replicate widely across other ancestries. SNP-to-SNP comparisons suggest that more than half of the 36 body mass index-associated loci are shared across European and East Asian ancestry populations, whereas locus-wide analyses suggest that the transferability might be even more extensive. Furthermore, by taking advantage of differences in haplotype structure, populations of different ancestries can help to narrow down loci, thereby pinpointing causal genes for functional follow-up. Larger-scale genetic association studies in ancestrally diverse populations will be needed for in-depth and locus-wide analyses aimed at determining, with greater confidence, the transferability of loci and allowing fine-mapping. Understanding similarities and differences in genetic susceptibility across populations of diverse ancestries might eventually contribute to a more targeted prevention and customized treatment of obesity.

Association between milk and milk product consumption and anthropometric measures in adult men and women in India: a cross-sectional study

BACKGROUND

The nutritional aetiology of obesity remains unclear, especially with regard to the role of dairy products in developing countries.

OBJECTIVE

To examine whether milk/milk product consumption is associated with obesity and high waist circumference among adult Indians.

METHODS

Information on plain milk, tea, curd and buttermilk/lassi consumption assessed using a Food Frequency Questionnaire was obtained from the cross-sectional sib-pair designed Indian Migration Study (3698 men and 2659 women), conducted at four factory locations across north, central and south India. The anthropometric measures included were Body Mass Index (BMI) and Waist Circumference (WC). Mixed-effect logistic regression models were conducted to accommodate sib-pair design and adjust for potential confounders.

RESULTS

After controlling for potential confounders, the risk of being obese (BMI ≥ 25 kg/m(2)) was lower among women (OR = 0.57;95%CI:0.43-0.76;p ≤ 0.0001) and men (OR = 0.67;95%CI: 0.51-0.87;p = 0.005), and the risk of a high WC (men: >90 cm; women: >80 cm) was lower among men (OR = 0.71;95%CI:0.54-0.93;p = 0.005) and women (OR = 0.79;95%CI:0.59-1.05;p>0.05) who consume ≥1 portions of plain milk daily than those who do not consume any milk. The inverse association between daily plain milk consumption and obesity was also confirmed in sibling-pair analyses. Daily tea consumption of ≥ 1 portion was associated with obesity (OR = 1.51;95%CI:1.00-2.25;p>0.050) and high WC (OR = 1.65;95%CI:1.08-2.51;p>0.019) among men but not among women but there was no strong evidence of association of curd and buttermilk/lassi consumption with obesity and high waist circumference among both men and women.

CONCLUSIONS

The independent, inverse association of daily plain milk consumption with the risk of being obese suggests that high plain milk intake may lower the risk of obesity in adult Indians. However, this is an observational finding and uncontrolled confounding cannot be excluded as an explanation for the association. Therefore, confirmatory studies are needed to clarify this relationship.

Migration and DNA methylation: a comparison of methylation patterns in type 2 diabetes susceptibility genes between indians and europeans

Background

Type 2 diabetes is a global problem that is increasingly prevalent in low and middle income countries including India, and is partly attributed to increased urbanisation. Genotype clearly plays a role in type 2 diabetes susceptibility. However, the role of DNA methylation and its interaction with genotype and metabolic measures is poorly understood. This study aimed to establish whether methylation patterns of type 2 diabetes genes differ between distinct Indian and European populations and/or change following rural to urban migration in India.

Methods

Quantitative DNA methylation analysis in Indians and Europeans using Sequenom^® EpiTYPER^® technology was undertaken in three genes: ADCY5, FTO and KCNJ11. Metabolic measures and genotype data were also analysed.

Results

Consistent differences in DNA methylation patterns were observed between Indian and European populations in ADCY5, FTO and KCNJ11. Associations were demonstrated between FTO rs9939609 and BMI and between ADCY5rs17295401 and HDL levels in Europeans. However, these observations were not linked to local variation in DNA methylation levels. No differences in methylation patterns were observed in urban-dwelling migrants compared to their non-migrant rural-dwelling siblings in India.

Conclusions

Analysis of DNA methylation at three type 2 diabetes susceptibility loci highlighted geographical and ethnic differences in methylation patterns. These differences may be attributed to genetic and/or region-specific environmental factors.

Association study of 25 type 2 diabetes related Loci with measures of obesity in Indian sib pairs

Obesity is an established risk factor for type 2 diabetes (T2D) and they are metabolically related through the mechanism of insulin resistance. In order to explore how common genetic variants associated with T2D correlate with body mass index (BMI), we examined the influence of 25 T2D associated loci on obesity risk. We used 5056 individuals (2528 sib-pairs) recruited in Indian Migration Study and conducted within sib-pair analysis for six obesity phenotypes. We found associations of variants in CXCR4 (rs932206) and HHEX (rs5015480) with higher body mass index (BMI) (β=0.13, p=0.001) and (β=0.09, p=0.002), respectively and weight (β=0.13, p=0.001) and (β=0.09, p=0.001), respectively. CXCR4 variant was also strongly associated with body fat (β=0.10, p=0.0004). In addition, we demonstrated associations of CXCR4 and HHEX with overweight/obesity (OR=1.6, p=0.003) and (OR=1.4, p=0.002), respectively, in 1333 sib-pairs (2666 individuals). We observed marginal evidence of associations between variants at six loci (TCF7L2, NGN3, FOXA2, LOC646279, FLJ39370 and THADA) and waist hip ratio (WHR), BMI and/or overweight which needs to be validated in larger set of samples. All the above findings were independent of daily energy consumption and physical activity level. The risk score estimates based on eight significant loci (including nominal associations) showed associations with WHR and body fat which were independent of BMI. In summary, we establish the role of T2D associated loci in influencing the measures of obesity in Indian population, suggesting common underlying pathophysiology across populations.

Statistical and biological gene-lifestyle interactions of MC4R and FTO with diet and physical activity on obesity: new effects on alcohol consumption

Background

Fat mass and obesity (FTO) and melanocortin-4 receptor (MC4R) and are relevant genes associated with obesity. This could be through food intake, but results are contradictory. Modulation by diet or other lifestyle factors is also not well understood.

Objective

To investigate whether MC4R and FTO associations with body-weight are modulated by diet and physical activity (PA), and to study their association with alcohol and food intake.

Methods

Adherence to Mediterranean diet (AdMedDiet) and physical activity (PA) were assessed by validated questionnaires in 7,052 high cardiovascular risk subjects. MC4R rs17782313 and FTO rs9939609 were determined. Independent and joint associations (aggregate genetic score) as well as statistical and biological gene-lifestyle interactions were analyzed.

Results

FTO rs9939609 was associated with higher body mass index (BMI), waist circumference (WC) and obesity (P<0.05 for all). A similar, but not significant trend was found for MC4R rs17782313. Their additive effects (aggregate score) were significant and we observed a 7% per-allele increase of being obese (OR = 1.07; 95%CI 1.01–1.13). We found relevant statistical interactions (P<0.05) with PA. So, in active individuals, the associations with higher BMI, WC or obesity were not detected. A biological (non-statistical) interaction between AdMedDiet and rs9939609 and the aggregate score was found. Greater AdMedDiet in individuals carrying 4 or 3-risk alleles counterbalanced their genetic predisposition, exhibiting similar BMI (P = 0.502) than individuals with no risk alleles and lower AdMedDiet. They also had lower BMI (P = 0.021) than their counterparts with low AdMedDiet. We did not find any consistent association with energy or macronutrients, but found a novel association between these polymorphisms and lower alcohol consumption in variant-allele carriers (B+/−SE: −0.57+/−0.16 g/d per-score-allele; P = 0.001).

Conclusion

Statistical and biological interactions with PA and diet modulate the effects of FTO and MC4R polymorphisms on obesity. The novel association with alcohol consumption seems independent of their effects on BMI.

The impact of intronic single nucleotide polymorphisms and ethnic diversity for studies on the obesity gene FTO

In 2007, the first common genetic variants were identified, which undoubtedly affect our susceptibility to obesity. These variants are located in the fat mass and obesity-associated gene FTO. Since then, over 50 loci for common obesity have been identified. As the research on these loci is still at an early stage, there is a great need to review, for clarification purposes, the current research on FTO, as this is likely to influence future studies. Based on the current knowledge, FTO seems to be directly involved in the regulation of energy intake, but there is an urgent need for the identification of regulatory polymorphisms. Thus, herein, we discuss current knowledge and highlight putative functional regions in FTO based on published data and computer-based analysis.

Associations of variants in FTO and near MC4R with obesity traits in South Asian Indians

Recent genome-wide association studies show that loci in FTO and melanocortin 4 receptor (MC4R) associate with obesity-related traits. Outside Western populations the associations between these variants have not always been consistent and in Indians it has been suggested that FTO relates to diabetes without an obvious intermediary obesity phenotype. We investigated the association between genetic variants in FTO (rs9939609) and near MC4R (rs17782313) with obesity- and type 2 diabetes (T2DM)-related traits in a longitudinal birth cohort of 2,151 healthy individuals from the Vellore birth cohort in South India. The FTO locus displayed significant associations with several conventional obesity-related anthropometric traits. The per allele increase is about 1% for BMI, waist circumference (WC), hip circumference (HC), and waist-hip ratio. Consistent associations were observed for adipose tissue-specific measurements such as skinfold thickness reinforcing the association with obesity-related traits. Obesity associations for the MC4R locus were weak or nonsignificant but a signal for height (P < 0.001) was observed. The effect on obesity-related traits for FTO was seen in adulthood, but not at younger ages. The loci also showed nominal associations with increased blood glucose but these associations were lost on BMI adjustment. The effect of FTO on obesity-related traits was driven by an urban environmental influence. We conclude that rs9939609 variant in the FTO locus is associated with measures of adiposity and metabolic consequences in South Indians with an enhanced effect associated with urban living. The detection of these associations in Indians is challenging because conventional anthropometric obesity measures work poorly in the Indian "thin-fat" phenotype.

Genetic determinants of common obesity and their value in prediction

Genome-wide association studies (GWAS) have revolutionised the discovery of genes for common traits and diseases, including obesity-related traits. In less then four years time, 52 genetic loci were identified to be unequivocally associated with obesity-related traits. This vast success raised hope and expectations that genetic information would become soon an integral part of personalised medicine. However, these loci have only small effects on obesity-susceptibility and explain just a fraction of the total variance. As such, their accuracy to predict obesity is poor and not competitive with the predictive ability of traditional risk factors. Nevertheless, some of these loci are being used in commercially available personal genome tests to estimate individuals' lifetime risk of obesity. While proponents believe that personal genome profiling could have beneficial effects on behaviour, early reports do not support this hypothesis. To conclude, the most valuable contribution of GWAS-identified loci lies in their contribution to elucidating new physiological pathways that underlie obesity-susceptibility.

Developments in obesity genetics in the era of genome-wide association studies

Obesity is an important factor contributing to the global burden of morbidity and mortality. By identifying obesity susceptibility genes, scientists aim to elucidate some of its aetiology. Early studies used candidate gene and genome-wide linkage approaches to search for such genes with limited success. However, the advent of genome-wide association studies (GWAS) has dramatically increased the pace of gene discovery. So far, GWAS have identified at least 50 loci robustly associated with body mass index (BMI), waist-to-hip ratio, body fat percentage and extreme obesity. Some of these have been shown to replicate in non-white populations and in children and adolescents. Furthermore, for some loci interaction studies have shown that the BMI-increasing effect is attenuated in physically active individuals. Despite many successful discoveries, the effect sizes of the established loci are small, and combined they explain only a fraction of the inter-individual variation in BMI. The low predictive value means that their value in mainstream health care is limited. However, as most of these newly established loci were not previously linked to obesity, they may provide new insights into body weight regulation. Continued efforts in gene discovery, using a range of approaches, will be needed to increase our understanding of obesity.