Early-life residential green spaces and traffic exposure in association with young adult body composition: a longitudinal birth cohort study of twins.

BACKGROUND: Globally, the rapid increase of obesity is reaching alarming proportions. A new approach to reduce obesity and its comorbidities involves tackling the built environment. Environmental influences seem to play an important role, but the environmental influences in early life on adult body composition have not been thoroughly investigated. This study seeks to fill the research gap by examining early-life exposure to residential green spaces and traffic exposure in association with body composition among a population of young adult twins. METHODS: As part of the East Flanders Prospective Twin Survey (EFPTS) cohort, this study included 332 twins. Residential addresses of the mothers at time of birth of the twins were geocoded to determine residential green spaces and traffic exposure. To capture body composition, body mass index, waist-to-hip ratio (WHR), waist circumference, skinfold thickness, leptin levels, and fat percentage were measured at adult age. Linear mixed modelling analyses were conducted to investigate early-life environmental exposures in association with body composition, while accounting for potential confounders. In addition, moderator effects of zygosity/chorionicity, sex and socio-economic status were tested. RESULTS: Each interquartile range (IQR) increase in distance to highway was found associated with an increase of 1.2% in WHR (95%CI 0.2-2.2%). For landcover of green spaces, each IQR increase was associated with 0.8% increase in WHR (95%CI 0.4-1.3%), 1.4% increase in waist circumference (95%CI 0.5-2.2%), and 2.3% increase in body fat (95%CI 0.2-4.4%). Stratified analyses by zygosity/chorionicity type indicated that in monozygotic monochorionic twins, each IQR increase in land cover of green spaces was associated with 1.3% increase in WHR (95%CI 0.5-2.1%). In monozygotic dichorionic twins, each IQR increase in land cover of green spaces was associated with 1.4% increase in waist-circumference (95%CI 0.6-2.2%). CONCLUSIONS: The built environment in which mothers reside during pregnancy might play a role on body composition among young adult twins. Our study revealed that based on zygosity/chorionicity type differential effects of prenatal exposure to green spaces on body composition at adult age might exist.

Dysregulation of macrophage PEPD in obesity determines adipose tissue fibro-inflammation and insulin resistance.

Resulting from impaired collagen turnover, fibrosis is a hallmark of adipose tissue (AT) dysfunction and obesity-associated insulin resistance (IR). Prolidase, also known as peptidase D (PEPD), plays a vital role in collagen turnover by degrading proline-containing dipeptides but its specific functional relevance in AT is unknown. Here we show that in human and mouse obesity, PEPD expression and activity decrease in AT, and PEPD is released into the systemic circulation, which promotes fibrosis and AT IR. Loss of the enzymatic function of PEPD by genetic ablation or pharmacological inhibition causes AT fibrosis in mice. In addition to its intracellular enzymatic role, secreted extracellular PEPD protein enhances macrophage and adipocyte fibro-inflammatory responses via EGFR signalling, thereby promoting AT fibrosis and IR. We further show that decreased prolidase activity is coupled with increased systemic levels of PEPD that act as a pathogenic trigger of AT fibrosis and IR. Thus, PEPD produced by macrophages might serve as a biomarker of AT fibro-inflammation and could represent a therapeutic target for AT fibrosis and obesity-associated IR and type 2 diabetes.

DECO: decompose heterogeneous population cohorts for patient stratification and discovery of sample biomarkers using omic data profiling.

MOTIVATION: Patient and sample diversity is one of the main challenges when dealing with clinical cohorts in biomedical genomics studies. During last decade, several methods have been developed to identify biomarkers assigned to specific individuals or subtypes of samples. However, current methods still fail to discover markers in complex scenarios where heterogeneity or hidden phenotypical factors are present. Here, we propose a method to analyze and understand heterogeneous data avoiding classical normalization approaches of reducing or removing variation. RESULTS: DEcomposing heterogeneous Cohorts using Omic data profiling (DECO) is a method to find significant association among biological features (biomarkers) and samples (individuals) analyzing large-scale omic data. The method identifies and categorizes biomarkers of specific phenotypic conditions based on a recurrent differential analysis integrated with a non-symmetrical correspondence analysis. DECO integrates both omic data dispersion and predictor-response relationship from non-symmetrical correspondence analysis in a unique statistic (called h-statistic), allowing the identification of closely related sample categories within complex cohorts. The performance is demonstrated using simulated data and five experimental transcriptomic datasets, and comparing to seven other methods. We show DECO greatly enhances the discovery and subtle identification of biomarkers, making it especially suited for deep and accurate patient stratification. AVAILABILITY AND IMPLEMENTATION: DECO is freely available as an R package (including a practical vignette) at Bioconductor repository (http://bioconductor.org/packages/deco/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genes that make you fat, but keep you healthy.

Obesity prevalence continues to rise worldwide, posing a substantial burden on people's health. However, up to 45% of obese individuals do not suffer from cardiometabolic complications, also called the metabolically healthy obese (MHO). Concurrently, up to 30% of normal-weight individuals demonstrate cardiometabolic risk factors that are generally observed in obese individuals, the metabolically obese normal weight (MONW). Besides lifestyle, environmental factors and demographic factors, innate biological mechanisms are known to contribute to the aetiology of the MHO and MONW phenotypes, as well. Experimental studies in animal models have shown that adipose tissue expandability, fat distribution, adipogenesis, adipose tissue vascularization, inflammation and fibrosis, and mitochondrial function are the main mechanisms that uncouple adiposity from its cardiometabolic comorbidities. We reviewed current genetic association studies to expand insights into the biology of MHO/MONW phenotypes. At least four genetic loci were identified through genome-wide association studies for body fat percentage (BF%) of which the BF%-increasing allele was associated with a protective effect on glycemic and lipid outcomes. For some, this association was mediated through favourable effects on body fat distribution. Other studies that characterized the genetic susceptibility of insulin resistance found that a higher susceptibility was associated with lower overall adiposity due to less fat accumulation at hips and legs, suggesting that an impaired capacity to store fat subcutaneously or a preferential storage in the intra-abdominal cavity may be metabolically harmful. Clearly, more work remains to be done in this field, first through gene discovery and subsequently through functional follow-up of identified genes.

GWAS for BMI: a treasure trove of fundamental insights into the genetic basis of obesity.

Muller et al. [1] have provided a strong critique of the Genome-Wide Association Studies (GWAS) of body-mass index (BMI), arguing that the GWAS approach for the study of BMI is flawed, and has provided us with few biological insights. They suggest that what is needed instead is a new start, involving GWAS for more complex energy balance related traits. In this invited counter-point, we highlight the substantial advances that have occurred in the obesity field, directly stimulated by the GWAS of BMI. We agree that GWAS for BMI is not perfect, but consider that the best route forward for additional discoveries will likely be to expand the search for common and rare variants linked to BMI and other easily obtained measures of obesity, rather than attempting to perform new, much smaller GWAS for energy balance traits that are complex and expensive to measure. For GWAS in general, we emphasise that the power from increasing the sample size of a crude but easily measured phenotype outweighs the benefits of better phenotyping.

Trans-ethnic analysis of metabochip data identifies two new loci associated with BMI.

OBJECTIVE: Body mass index (BMI) is commonly used to assess obesity, which is associated with numerous diseases and negative health outcomes. BMI has been shown to be a heritable, polygenic trait, with close to 100 loci previously identified and replicated in multiple populations. We aim to replicate known BMI loci and identify novel associations in a trans-ethnic study population. SUBJECTS: Using eligible participants from the Population Architecture using Genomics and Epidemiology consortium, we conducted a trans-ethnic meta-analysis of 102 514 African Americans, Hispanics, Asian/Native Hawaiian, Native Americans and European Americans. Participants were genotyped on over 200 000 SNPs on the Illumina Metabochip custom array, or imputed into the 1000 Genomes Project (Phase I). Linear regression of the natural log of BMI, adjusting for age, sex, study site (if applicable), and ancestry principal components, was conducted for each race/ethnicity within each study cohort. Race/ethnicity-specific, and combined meta-analyses used fixed-effects models. RESULTS: We replicated 15 of 21 BMI loci included on the Metabochip, and identified two novel BMI loci at 1q41 (rs2820436) and 2q31.1 (rs10930502) at the Metabochip-wide significance threshold (P<2.5 × 10-7). Bioinformatic functional investigation of SNPs at these loci suggests a possible impact on pathways that regulate metabolism and adipose tissue. CONCLUSION: Conducting studies in genetically diverse populations continues to be a valuable strategy for replicating known loci and uncovering novel BMI associations.

The prenatal gut microbiome: are we colonized with bacteria in utero?

The colonization of the gut with microbes in early life is critical to the developing newborn immune system, metabolic function and potentially future health. Maternal microbes are transmitted to offspring during childbirth, representing a key step in the colonization of the infant gut. Studies of infant meconium suggest that bacteria are present in the foetal gut prior to birth, meaning that colonization could occur prenatally. Animal studies have shown that prenatal transmission of microbes to the foetus is possible, and physiological changes observed in pregnant mothers indicate that in utero transfer is likely in humans as well. However, direct evidence of in utero transfer of bacteria in humans is lacking. Understanding the timing and mechanisms involved in the first colonization of the human gut is critical to a comprehensive understanding of the early life gut microbiome. This review will discuss the evidence supporting in utero transmission of microbes from mother to infants. We also review sources of transferred bacteria, physiological mechanisms of transfer and modifiers of maternal microbiomes and their potential role in early life infant health. Well-designed longitudinal birth studies that account for established modifiers of the gut microbiome are challenging, but will be necessary to confirm in utero transfer and further our knowledge of the prenatal microbiome.

Examining the causal association of fasting glucose with blood pressure in healthy children and adolescents: a Mendelian randomization study employing common genetic variants of fasting glucose.

The aim of the study was to determine whether genetically raised fasting glucose (FG) levels are associated with blood pressure (BP) in healthy children and adolescents. We used 11 common genetic variants of FG discovered in genome-wide association studies (GWAS), including the rs560887 single-nucleotide polymorphism (SNP) located in the G6PC2 locus found to be robustly associated with FG in children and adolescents, as an instrument to associate FG with resting BP in 1506 children and adolescents from the European Youth Heart Study (EYHS). Rs560887 was associated with increased FG levels corresponding to an increase of 0.08 mmol l(-1) (P=2.4 × 10(-8)). FG was associated with BP, independent of other important determinants of BP in conventional multivariable analysis (systolic BP z-score: 0.32 s.d. per increase in mmol l(-1) (95% confidence interval (CI) 0.20-0.44, P=1.9 × 10(-7)), diastolic BP z-score: 0.13 s.d. per increase in mmol l(-1) (95% CI 0.04-0.21, P=3.2 × 10(-3)). This association was not supported by the Mendelian randomization approach, neither from instrumenting FG from all 11 variants nor from the rs560887, where non-significant associations of glucose with BP were observed. The results of this study could not support a causal association between FG and BP in healthy children and adolescents; however, it is possible that rs560887 has pleiotropic effects on unknown factors with a BP lowering effect or that these results were due to a lack of statistical power.

Pleiotropic effects of obesity-susceptibility loci on metabolic traits: a meta-analysis of up to 37,874 individuals.

AIMS/HYPOTHESIS: Genetic pleiotropy may contribute to the clustering of obesity and metabolic conditions. We assessed whether genetic variants that are robustly associated with BMI and waist-to-hip ratio (WHR) also influence metabolic and cardiovascular traits, independently of obesity-related traits, in meta-analyses of up to 37,874 individuals from six European population-based studies. METHODS: We examined associations of 32 BMI and 14 WHR loci, individually and combined in two genetic predisposition scores (GPSs), with glycaemic traits, blood lipids and BP, with and without adjusting for BMI and/or WHR. RESULTS: We observed significant associations of BMI-increasing alleles at five BMI loci with lower levels of 2 h glucose (RBJ [also known as DNAJC27], QPTCL: effect sizes -0.068 and -0.107 SD, respectively), HDL-cholesterol (SLC39A8: -0.065 SD, MTCH2: -0.039 SD), and diastolic BP (SLC39A8: -0.069 SD), and higher and lower levels of LDL- and total cholesterol (QPTCL: 0.041 and 0.042 SDs, respectively, FLJ35779 [also known as POC5]: -0.042 and -0.041 SDs, respectively) (all p < 2.4 × 10(-4)), independent of BMI. The WHR-increasing alleles at two WHR loci were significantly associated with higher proinsulin (GRB14: 0.069 SD) and lower fasting glucose levels (CPEB4: -0.049 SD), independent of BMI and WHR. A higher GPS-BMI was associated with lower systolic BP (-0.005 SD), diastolic BP (-0.006 SD) and 2 h glucose (-0.013 SD), while a higher GPS-WHR was associated with lower HDL-cholesterol (-0.015 SD) and higher triacylglycerol levels (0.014 SD) (all p < 2.9 × 10(-3)), independent of BMI and/or WHR. CONCLUSIONS/INTERPRETATION: These pleiotropic effects of obesity-susceptibility loci provide novel insights into mechanisms that link obesity with metabolic abnormalities.

Lipoprotein receptor-related protein 1 variants and dietary fatty acids: meta-analysis of European origin and African American studies.

OBJECTIVE: Low-density lipoprotein-related receptor protein 1 (LRP1) is a multi-functional endocytic receptor and signaling molecule that is expressed in adipose and the hypothalamus. Evidence for a role of LRP1 in adiposity is accumulating from animal and in vitro models, but data from human studies are limited. The study objectives were to evaluate (i) relationships between LRP1 genotype and anthropometric traits, and (ii) whether these relationships were modified by dietary fatty acids. DESIGN AND METHODS: We conducted race/ethnic-specific meta-analyses using data from 14 studies of US and European whites and 4 of African Americans to evaluate associations of dietary fatty acids and LRP1 genotypes with body mass index (BMI), waist circumference and hip circumference, as well as interactions between dietary fatty acids and LRP1 genotypes. Seven single-nucleotide polymorphisms (SNPs) of LRP1 were evaluated in whites (N up to 42 000) and twelve SNPs in African Americans (N up to 5800). RESULTS: After adjustment for age, sex and population substructure if relevant, for each one unit greater intake of percentage of energy from saturated fat (SFA), BMI was 0.104 kg m(-2) greater, waist was 0.305 cm larger and hip was 0.168 cm larger (all P<0.0001). Other fatty acids were not associated with outcomes. The association of SFA with outcomes varied by genotype at rs2306692 (genotyped in four studies of whites), where the magnitude of the association of SFA intake with each outcome was greater per additional copy of the T allele: 0.107 kg m(-2) greater for BMI (interaction P=0.0001), 0.267 cm for waist (interaction P=0.001) and 0.21 cm for hip (interaction P=0.001). No other significant interactions were observed. CONCLUSION: Dietary SFA and LRP1 genotype may interactively influence anthropometric traits. Further exploration of this, and other diet x genotype interactions, may improve understanding of interindividual variability in the relationships of dietary factors with anthropometric traits.

Evaluation of common genetic variants identified by GWAS for early onset and morbid obesity in population-based samples.

BACKGROUND: Meta-analysis of case-control genome-wide association studies (GWAS) for early onset and morbid obesity identified four variants in/near the PRL, PTER, MAF and NPC1 genes. OBJECTIVE: We aimed to validate association of these variants with obesity-related traits in population-based samples. DESIGN: Genotypes and anthropometric traits were available in up to 31 083 adults from the Fenland, EPIC-Norfolk, Whitehall II, Ely and Hertfordshire studies and in 2042 children and adolescents from the European Youth Heart Study. In each study, we tested associations of rs4712652 (near-PRL), rs10508503 (near-PTER), rs1424233 (near-MAF) and rs1805081 (NPC1), or proxy variants (r (2)>0.8), with the odds of being overweight and obese, as well as with body mass index (BMI), percentage body fat (%BF) and waist circumference (WC). Associations were adjusted for sex, age and age(2) in adults and for sex, age, age group, country and maturity in children and adolescents. Summary statistics were combined using fixed effects meta-analysis methods. RESULTS: We had 80% power to detect odds ratios of 1.046 to 1.092 for overweight and 1.067 to 1.136 for obesity. Variants near PRL, PTER and MAF were not associated with the odds of being overweight or obese, or with BMI, %BF or WC after meta-analysis (P>0.15). The NPC1 variant rs1805081 showed some evidence of association with %BF (ß=0.013 s.d./allele, P=0.040), but not with any of the remaining obesity-related traits (P>0.3). CONCLUSION: Overall, these variants, which were identified in a GWAS for early onset and morbid obesity, do not seem to influence obesity-related traits in the general population.

Obesity: lessons from evolution and the environment.

The 9th Stock Conference acknowledged the complex background of genetic, cultural, environmental and evolutionary factors of obesity. Gene-environment interactions underlie the flexibility in body-weight and body-fat regulation, illustrated by the hunter-gatherers' feast and famine lifestyle, the variation in physical activity over the lifespan being highest at reproductive age, the variation in energy intake through 'eating in the absence of hunger', while running the risk of exceeding the capacity of triacylglyceride storage, leading to lipotoxicity and metabolic problems. Perinatal metabolic programming for obesity via epigenetic changes in response to a 'Western diet' results in production of lipid-poor milk and metabolically efficient pups, contributing to the perpetuation of obesity throughout generations. Evolutionary insight from comparative physiology and ecology indicates that over generations activity-induced energy expenditure has remained the same compared to wild mammals, that energy balance might be dependant on protein balance, while the function of taste changed from detection of poison or energy to social drinking and social behaviour. At present, the impact of assortative mating on obesity prevalence is unambiguously positive. The complexity that appeared can only be fully appreciated by setting the data into the context of our evolutionary history.

Genetic predisposition influences plasma lipids of participants on habitual diet, but not the response to reductions in dietary intake of saturated fatty acids.

OBJECTIVE: SNPs identified from genome-wide association studies associate with lipid risk markers of cardiovascular disease. This study investigated whether these SNPs altered the plasma lipid response to diet in the 'RISCK' study cohort. METHODS: Participants (n=490) from a dietary intervention to lower saturated fat by replacement with carbohydrate or monounsaturated fat, were genotyped for 39 lipid-associated SNPs. The association of each individual SNP, and of the SNPs combined (using genetic predisposition scores), with plasma lipid concentrations was assessed at baseline, and on change in response to 24 weeks on diets. RESULTS: The associations between SNPs and lipid concentrations were directionally consistent with previous findings. The genetic predisposition scores were associated with higher baseline concentrations of plasma total (P=0.02) and LDL (P=0.002) cholesterol, triglycerides (P=0.001) and apolipoprotein B (P=0.004), and with lower baseline concentrations of HDL cholesterol (P<0.001) and apolipoprotein A-I (P<0.001). None of the SNPs showed significant association with the reduction of plasma lipids in response to the dietary interventions and there was no evidence of diet-gene interactions. CONCLUSION: Results from this exploratory study have shown that increased genetic predisposition was associated with an unfavourable plasma lipid profile at baseline, but did not influence the improvement in lipid profiles by the low-saturated-fat diets.

Genetic predisposition to obesity leads to increased risk of type 2 diabetes.

AIMS/HYPOTHESIS: Obesity is a major risk factor for type 2 diabetes. Recent genome-wide association (GWA) studies have identified multiple loci robustly associated with BMI and risk of obesity. However, information on their associations with type 2 diabetes is limited. Such information could help increase our understanding of the link between obesity and type 2 diabetes. We examined the associations of 12 obesity susceptibility loci, individually and in combination, with risk of type 2 diabetes in the population-based European Prospective Investigation of Cancer (EPIC) Norfolk cohort. METHODS: We genotyped 12 SNPs, identified by GWA studies of BMI, in 20,428 individuals (aged 39-79 years at baseline) with an average follow-up of 12.9 years, during which 729 individuals developed type 2 diabetes. A genetic predisposition score was calculated by adding the BMI-increasing alleles across the 12 SNPs. Associations with incidence of type 2 diabetes were examined by logistic regression models. RESULTS: Of the 12 SNPs, eight showed a trend with increased risk of type 2 diabetes, consistent with their BMI-increasing effects. Each additional BMI-increasing allele in the genetic predisposition score was associated with a 4% increased odds of developing type 2 diabetes (OR 1.041, 95% CI 1.005-1.078; p = 0.02). Adjustment for BMI completely abolished the association with incident type 2 diabetes (OR 1.003, 95% CI 0.967-1.039; p = 0.89). CONCLUSIONS/INTERPRETATION: The genetic predisposition to obesity leads to increased risk of developing type 2 diabetes, which is completely mediated by its obesity-predisposing effect.

Combined effects of 17 common genetic variants on type 2 diabetes risk in a Han Chinese population.

AIMS/HYPOTHESIS: The recent advent of genome-wide association studies has considerably accelerated the identification of type 2 diabetes loci. We aimed to investigate the combined effects of multiple genetic variants, alone or in combination with conventional risk factors, on type 2 diabetes and diabetes-related traits in Han Chinese. METHODS: We genotyped 17 variants in 17 loci in a population-based Han Chinese cohort including 3,210 unrelated individuals. A genetic risk score (GRS) was calculated on the basis of these variants. The discriminatory ability was assessed by the area under the receiver operating characteristics curve. RESULTS: The odds ratio for type 2 diabetes and hyperglycaemia with each GRS point (per risk allele) was 1.18 (95% CI 1.12-1.23, p = 1.3 x 10(-12)) and 1.12 (95% CI 1.09-1.16, p = 7.5 x 10(-14)), respectively. Compared with participants with GRS < or =11.0 (7.63%), those with GRS > or =19.0 (8.87%) had a 4.58-fold higher risk (95% CI 2.49-8.42) of type 2 diabetes. The GRS also showed a significant association with lower beta cell function estimated by HOMA of beta cell function (p = 8.4 x 10(-10)). In addition, we observed significant interactive effects between GRS and BMI on fasting glucose and HbA(1c) levels (p = 0.04 and p = 0.03 for interaction, respectively). Discrimination of diabetes risk was improved (p < 0.001) when the GRS was added to a model including clinical risk factors. The AUCs were 0.62 and 0.77, respectively, for the GRS and conventional clinic risk factors alone, and 0.79 when the GRS was added. CONCLUSIONS/INTERPRETATION: In this Han Chinese population, the GRS of 17 combined variants modestly but significantly improved discrimination of the conventional risk factors for type 2 diabetes.

Second interlaboratory exercise on non-steroidal anti-inflammatory drug analysis in environmental aqueous samples.

Several interlaboratory exercises were organised within the framework of European FP6 project NORMAN. Among others, non-steroidal anti-inflammatory drugs were investigated in different aqueous samples in two sequential ring studies. The aim of both studies was to evaluate the state-of-art in Europe and to determine possible sources of variation, while also attempting to diminish them. In the present paper we discuss the results of the 2nd Interlaboratory study, while the results of 1st round were presented before. The main scope of the 1st exercise organised within NORMAN project was to assess the laboratory proficiency regardless of the analytical method applied, to evaluate the stability of the target compounds during sample storage, and to define possible sources of variation during sample shipment, storage and analysis. In the 2nd round we primarily aimed to diminish these sources of variation by applying two predetermined analytical protocols based on liquid chromatography-mass spectrometry or gas chromatography-mass spectrometry. The two analytical protocols were compared in terms of their ability to determine individual analytes in matrices of different complexity, i.e. tap water, river water and wastewater. Furthermore, the 2nd exercise addressed also the filtration and compared the influence of different filter material categories on the analysis of non-steroidal anti-inflammatory drugs. Results presented herein evaluate laboratory performance using z-score, bias, proximity and Youden plots. Overall, the laboratory performances were found to be satisfactory for determining NSAIDs in aqueous samples. The two analytical protocols, LC-MS and GC-MS, are assessed according to their sensitivity and measurement uncertainty, where the GC-MS proved superior for the analysis of Ibuprofen, Ketoprofen and Naproxen in matrices with higher complexity. Finally, neither the filtration itself, nor the filter materials were shown to significantly affect the determination of NSAIDs.

Association between serotonin 5-HT-2C receptor gene (HTR2C) polymorphisms and obesity- and mental health-related phenotypes in a large population-based cohort.

OBJECTIVE: Studies have shown that common single-nucleotide polymorphisms (SNPs) in the serotonin 5-HT-2C receptor (HTR2C) are associated with antipsychotic agent-induced weight gain and the development of behavioural and psychological symptoms. We aimed to analyse whether variation in the HTR2C is associated with obesity- and mental health-related phenotypes in a large population-based cohort. METHOD: Six tagSNPs, which capture all common genetic variation in the HTR2C gene, were genotyped in 4978 men and women from the European Prospective Investigation into Cancer (EPIC)-Norfolk study, an ongoing prospective population-based cohort study in the United Kingdom. To confirm borderline significant associations, the -759C/T SNP (rs3813929) was genotyped in the remaining 16 003 individuals from the EPIC-Norfolk study. We assessed social and psychological circumstances using the Health and Life Experiences Questionnaire. Genmod models were used to test associations between the SNPs and the outcomes. Logistic regression was performed to test for association of SNPs with obesity- and mental health- related phenotypes. RESULTS: Of the six HTR2C SNPs, only the T allele of the -759C/T SNP showed borderline significant associations with higher body mass index (BMI) (0.23 kg m(-2); (95% confidence interval (CI): 0.01-0.44); P=0.051) and increased risk of lifetime major depressive disorder (MDD) (Odds ratio (OR): 1.13 (95% CI: 1.01-1.22), P=0.02). The associations between the -759C/T and BMI and lifetime MDD were independent. As associations only achieved borderline significance, we aimed to validate our findings on the -759C/T SNP in the full EPIC-Norfolk cohort (n=20 981). Although the association with BMI remained borderline significant (beta=0.20 kg m(-2); 95% CI: 0.04-0.44, P=0.09), that with lifetime MDD (OR: 1.01; 95% CI: 0.94-1.09, P=0.73) was not replicated. CONCLUSIONS: Our findings suggest that common HTR2C gene variants are unlikely to have a major role in obesity- and mental health-related traits in the general population.

Parent-of-origin specific linkage and association of the IGF2 gene region with birth weight and adult metabolic risk factors.

OBJECTIVE: The maternally imprinted insulin-like growth factor 2 (IGF2) gene is an important fetal growth factor and is also suggested to have postnatal metabolic effects. In this study, we examined whether common polymorphisms in IGF2 (6815_6819delAGGGC, 1156T>C and 820G>A (ApaI)) and a microsatellite marker in the close vicinity of IGF2 were linked to or associated with birth weight and adult metabolic risk factors. DESIGN AND PARTICIPANTS: Polymorphisms were genotyped in 199 monozygotic complete twin pairs, 109 dizygotic complete twin pairs, 15 single twins, 231 mothers and 228 fathers recruited from the East Flanders Prospective Twin Survey. Conventional and parent-of-origin specific linkage and association analyses were carried out with birth weight, adult body height and parameters quantifying obesity, insulin sensitivity and dyslipidaemia measured at adult age (mean age 25 years). RESULTS: In the parent-of-origin specific association analysis, in which only the paternally inherited allele was incorporated, the 1156T>C SNP (single nucleotide polymorphism) showed significant association with IGF-binding protein 1 (IGFBP1) levels (T and C (mean (95% CI)): 13.2 (12.1-14.3) and 16.2 (14.6-18.0) ng ml(-1), P=0.002). No linkage was observed in either the conventional or in the parent-of-origin specific linkage analysis. CONCLUSION: This study suggests that paternally inherited alleles of a common polymorphism in the IGF2 gene affect IGFBP1 levels.

Common genetic variation in the melatonin receptor 1B gene (MTNR1B) is associated with decreased early-phase insulin response.

AIMS/HYPOTHESIS: We investigated whether variation in MTNR1B, which was recently identified as a common genetic determinant of fasting glucose levels in healthy, diabetes-free individuals, is associated with measures of beta cell function and whole-body insulin sensitivity. METHODS: We studied 1,276 healthy individuals of European ancestry at 19 centres of the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study. Whole-body insulin sensitivity was assessed by euglycaemic-hyperinsulinaemic clamp and indices of beta cell function were derived from a 75 g oral glucose tolerance test (including 30 min insulin response and glucose sensitivity). We studied rs10830963 in MTNR1B using additive genetic models, adjusting for age, sex and recruitment centre. RESULTS: The minor (G) allele of rs10830963 in MTNR1B (frequency 0.30 in HapMap Centre d'Etude du Polymorphisme [Utah residents with northern and western European ancestry] [CEU]; 0.29 in RISC participants) was associated with higher levels of fasting plasma glucose (standardised beta [95% CI] 0.17 [0.085, 0.25] per G allele, p = 5.8 x 10(-5)), consistent with recent observations. In addition, the G-allele was significantly associated with lower early insulin response (-0.19 [-0.28, -0.10], p = 1.7 x 10(-5)), as well as with decreased beta cell glucose sensitivity (-0.11 [-0.20, -0.027], p = 0.010). No associations were observed with clamp-assessed insulin sensitivity (p = 0.15) or different measures of body size (p > 0.7 for all). CONCLUSIONS/INTERPRETATION: Genetic variation in MTNR1B is associated with defective early insulin response and decreased beta cell glucose sensitivity, which may contribute to the higher glucose levels of non-diabetic individuals carrying the minor G allele of rs10830963 in MTNR1B.