Exposure to Endocrine Disrupting Chemicals in the Dutch general population is associated with adiposity-related traits.

Endocrine Disrupting Chemicals (EDCs) have been linked to a variety of cardiometabolic diseases. Yet, few studies have investigated the exposure to EDCs and cardiometabolic health taking lifestyle into account. We aimed to assess exposure to five parabens, three bisphenols and thirteen metabolites of in total eight phthalates in a general Dutch population and to investigate their association with cardiometabolic traits. In 662 adult subjects from the population-based Lifelines cohort, 21 EDC analytes were measured in 24-hour urine collected in 2012, using LC-MS/MS. Association analyses between cardiometabolic traits and EDC concentrations were performed using multivariate linear models adjusting for age, sex, education, smoking, diabetes, physical activity and caloric intake. Quartile analyses were performed to assess linearity. Bisphenol A, four parabens and eight phthalate metabolites were detected in 84-100% of the samples. Adjusted associations for MiBP and MBzP and adiposity-related traits were robust for multiple testing (Beta's, BMI: 1.12, 2.52; waist circumference: 0.64, 1.56, respectively; FDR < 0.009). Associations for triglyceride, HDL-cholesterol, glucose and blood pressure were not. Linearity was confirmed for significant associations. Exposure to EDCs in the Dutch population is ubiquitous. We found direct associations between phthalates and adiposity-related traits. Prospective studies are needed to confirm these findings.

The effects of bariatric surgery on clinical profile, DNA methylation, and ageing in severely obese patients.

BACKGROUND: Severe obesity is a growing, worldwide burden and conventional therapies including radical change of diet and/or increased physical activity have limited results. Bariatric surgery has been proposed as an alternative therapy showing promising results. It leads to substantial weight loss and improvement of comorbidities such as type 2 diabetes. Increased adiposity is associated with changes in epigenetic profile, including DNA methylation. We investigated the effect of bariatric surgery on clinical profile, DNA methylation, and biological age estimated using Horvath's epigenetic clock. RESULTS: To determine the impact of bariatric surgery and subsequent weight loss on clinical traits, a cohort of 40 severely obese individuals (BMI = 30-73 kg/m2) was examined at the time of surgery and at three follow-up visits, i.e., 3, 6, and 12 months after surgery. The majority of the individuals were women (65%) and the mean age at surgery was 45.1 ± 8.1 years. We observed a significant decrease over time in BMI, fasting glucose, HbA1c, HOMA-IR, insulin, total cholesterol, triglycerides, LDL and free fatty acids levels, and a significant small increase in HDL levels (all p values < 0.05). Epigenome-wide association analysis revealed 4857 differentially methylated CpG sites 12 months after surgery (at Bonferroni-corrected p value < 1.09 × 10-7). Including BMI change in the model decreased the number of significantly differentially methylated CpG sites by 51%. Gene set enrichment analysis identified overrepresentation of multiple processes including regulation of transcription, RNA metabolic, and biosynthetic processes in the cell. Bariatric surgery in severely obese patients resulted in a decrease in both biological age and epigenetic age acceleration (EAA) (mean = - 0.92, p value = 0.039). CONCLUSIONS: Our study shows that bariatric surgery leads to substantial BMI decrease and improvement of clinical outcomes observed 12 months after surgery. These changes explained part of the association between bariatric surgery and DNA methylation. We also observed a small, but significant improvement of biological age. These epigenetic changes may be modifiable by environmental lifestyle factors and could be used as potential biomarkers for obesity and in the future for obesity related comorbidities.

Skin autofluorescence predicts incident type 2 diabetes, cardiovascular disease and mortality in the general population.

AIMS/HYPOTHESIS: Earlier studies have shown that skin autofluorescence measured with an AGE reader estimates the accumulation of AGEs in the skin, which increases with ageing and is associated with the metabolic syndrome and type 2 diabetes. In the present study, we examined whether the measurement of skin autofluorescence can predict 4 year risk of incident type 2 diabetes, cardiovascular disease (CVD) and mortality in the general population. METHODS: For this prospective analysis, we included 72,880 participants of the Dutch Lifelines Cohort Study, who underwent baseline investigations between 2007 and 2013, had validated baseline skin autofluorescence values available and were not known to have diabetes or CVD. Individuals were diagnosed with incident type 2 diabetes by self-report or by a fasting blood glucose ≥7.0 mmol/l or HbA1c ≥48 mmol/mol (≥6.5%) at follow-up. Participants were diagnosed as having incident CVD (myocardial infarction, coronary interventions, cerebrovascular accident, transient ischaemic attack, intermittent claudication or vascular surgery) by self-report. Mortality was ascertained using the Municipal Personal Records Database. RESULTS: After a median follow-up of 4 years (range 0.5-10 years), 1056 participants (1.4%) had developed type 2 diabetes, 1258 individuals (1.7%) were diagnosed with CVD, while 928 (1.3%) had died. Baseline skin autofluorescence was elevated in participants with incident type 2 diabetes and/or CVD and in those who had died (all p < 0.001), compared with individuals who survived and remained free of the two diseases. Skin autofluorescence predicted the development of type 2 diabetes, CVD and mortality, independent of several traditional risk factors, such as the metabolic syndrome, glucose and HbA1c. CONCLUSIONS/INTERPRETATION: The non-invasive skin autofluorescence measurement is of clinical value for screening for future risk of type 2 diabetes, CVD and mortality, independent of glycaemic measures and the metabolic syndrome.

Dietary patterns and physical activity in the metabolically (un)healthy obese: the Dutch Lifelines cohort study.

BACKGROUND: Diversity in the reported prevalence of metabolically healthy obesity (MHO), suggests that modifiable factors may be at play. We evaluated differences in dietary patterns and physical activity between MHO and metabolically unhealthy obesity (MUO). METHODS: Cross-sectional data of 9270 obese individuals (30-69 years) of the Lifelines Cohort Study was used. MHO was defined as obesity and no metabolic syndrome risk factors and no cardiovascular disease history. MUO was defined as obesity and ≥2 metabolic syndrome risk factors. Sex-specific associations of dietary patterns (identified by principal component analysis) and physical activity with MHO were assessed by multivariable logistic regression (reference group: MUO). Analyses were adjusted for multiple covariates. RESULTS: Among 3442 men and 5828 women, 10.2% and 24.4% had MHO and 56.9% and 35.3% MUO, respectively. We generated four obesity-specific dietary patterns. Two were related to MHO, and in women only. In the highest quartile (Q) of 'bread, potatoes and sweet snacks' pattern, odds ratio (OR) (95% CI) for MHO was 0.52 (0.39-0.70). For the healthier pattern 'fruit, vegetables and fish', an OR of 1.36 (1.09-1.71) in Q3 and 1.55 (1.21-1.97) in Q4 was found for MHO. For physical activity, there was a positive association between moderate physical activity and vigorous physical activity in the highest tertile and MHO in women and men, respectively (OR 1.19 (1.01-1.41) and OR 2.02 (1.50-2.71)). CONCLUSION: The healthier diet -characterized by 'fruit, vegetables and fish'- and moderate physical activity in women, and vigorous physical activity in men may be related to MHO. The (refined) carbohydrate-rich 'bread, potatoes and sweet snacks' dietary pattern was found to counteract MHO in women.

Influence of Storage and Inter- and Intra-Assay Variability on the Measurement of Inflammatory Biomarkers in Population-Based Biobanking.

BACKGROUND: In the present study, we examined the effect of sample storage on the reproducibility of several inflammatory biomarkers, including high-sensitivity C-reactive protein (hsCRP), high-sensitivity interleukin-6 (hsIL6), and high-sensitivity tumor necrosis factor alpha (hsTNFα). In addition, we assessed inter- and intra-assay variability between collaborating biobanks. METHODS: In total, 240 fasting plasma samples were obtained from the LifeLines biobank. Samples had been stored for less than 2 or more than 4 years at -80°C. Measurements were performed at three different laboratories. hsCRP was measured by immunonephelometry and ELISA, hsIL6, and hsTNFα samples were measured with ELISAs from two different manufacturers. For confirmation, similar analyses were performed on samples obtained from a subpopulation of 80 obese individuals. Passing-Bablok regression analysis and Bland-Altman plots were used to compare the results. RESULTS: We observed good stability of samples stored at -80°C. hsCRP measured on the day of blood draw was similar to levels measured after more than 4 years of storage. There were small interlaboratory differences with the R&D ELISAs for hsIL6 and hsTNFα. We found a linear correlation between the Bender Medsystems ELISA and the R&D ELISA for hsIL6, with significantly higher levels measured with the R&D ELISA. Over 90% of hsTNFα samples measured with the IBL ELISA were below the detection limit of 0.13 ng/L, rendering this assay unsuitable for large-scale analysis. Similar results were found in the confirmation study. CONCLUSION: In summary, plasma hsCRP showed good stability in samples stored for either less than 2 years or more than 4 years at -80°C. Both the R&D and Bender Medsystems for hsIL6 measurement yielded similar results. The IBL hsTNFα assay is not suited for use in biobanking samples. Assays for the measurement of inflammatory biomarker assays should be rigorously tested before large sample sets are measured.

Thyroid function and metabolic syndrome in the population-based LifeLines cohort study.

BACKGROUND: The metabolic syndrome (MetS) is a combination of unfavourable health factors which includes abdominal obesity, dyslipidaemia, elevated blood pressure and impaired fasting glucose. Earlier studies have reported a relationship between thyroid function and some MetS components or suggested that serum free thyroxine (FT4) or free triiodothyronine (FT3) levels within the normal range were independently associated with insulin resistance. We assessed how thyroid function relates to MetS prevalence in a large population-based study. METHODS: Data of 26,719 people of western European descent, aged 18-80 years from the Dutch LifeLines Cohort study, all with normal thyroid stimulating hormone (TSH), FT4 and FT3 levels (electrochemiluminescent immunoassay, Roche Modular E170 Analyzer), were available. MetS was defined with the revised National Cholesterol Education Programs Adults Treatment Panel III (NCEP ATP III) criteria. We calculated prevalence of all MetS components according to TSH, FT4 and FT3 quartiles. RESULTS: At similar TSH levels and age (mean 45 yrs), men had significantly higher levels of FT4, FT3, blood pressure (BP), heart rate, total and LDL-cholesterol, triglycerides (TG), and creatinine, but lower HDL-cholesterol compared to women (all p < 0.001). In total, 11.8% of women and 20.7% of men had MetS. In men, lower FT4 levels were associated with higher prevalence of MetS and all MetS components. In women, lower FT4 quartile was only associated with a higher prevalence of elevated TG, waist circumference, and MetS. However, when corrected for confounding factors like age, BMI, current smoking and alcohol consumption, a significant relationship was found between FT3 and three MetS components in men, and all five components in women. Moreover, the highest quartiles of FT3 and the FT3FT4 ratio predicted a 49% and 67% higher prevalence of MetS in men, and a 62 and 80% higher prevalence in women. CONCLUSIONS: When corrected for possible confounding factors, higher plasma levels of FT3 are associated with several components of the MetS. Only in men, lower FT4 is related to MetS. In the highest FT3 and FT3FT4 quartiles, there is a 50-80% increased risk of having MetS compared to the lowest quartile. Further studies are needed to assess the possible causality of this relationship.

Genotype-covariate interaction effects and the heritability of adult body mass index.

Obesity is a worldwide epidemic, with major health and economic costs. Here we estimate heritability for body mass index (BMI) in 172,000 sibling pairs and 150,832 unrelated individuals and explore the contribution of genotype-covariate interaction effects at common SNP loci. We find evidence for genotype-age interaction (likelihood ratio test (LRT) = 73.58, degrees of freedom (df) = 1, P = 4.83 × 10-18), which contributed 8.1% (1.4% s.e.) to BMI variation. Across eight self-reported lifestyle factors, including diet and exercise, we find genotype-environment interaction only for smoking behavior (LRT = 19.70, P = 5.03 × 10-5 and LRT = 30.80, P = 1.42 × 10-8), which contributed 4.0% (0.8% s.e.) to BMI variation. Bayesian association analysis suggests that BMI is highly polygenic, with 75% of the SNP heritability attributable to loci that each explain <0.01% of the phenotypic variance. Our findings imply that substantially larger sample sizes across ages and lifestyles are required to understand the full genetic architecture of BMI.

Skin autofluorescence, a non-invasive biomarker for advanced glycation end products, is associated with the metabolic syndrome and its individual components.

BACKGROUND: The metabolic syndrome (MetS) comprises several cardiometabolic risk factors associated with increased risk for both type 2 diabetes and cardiovascular disease. Skin autofluorescence (SAF), a non-invasive biomarker of advanced glycation end products accumulation, is associated with cardiovascular complications in subjects with diabetes. The aim of the present study was to examine the association between SAF and the presence of MetS as well as its individual components in a general population. METHODS: For this cross-sectional analysis, we included 78,671 non-diabetic subjects between 18 and 80 years of age who participated in the LifeLines Cohort Study and had SAF measurement obtained non-invasively using the AGE Reader. MetS was defined according to the revised NCEP ATP III criteria. Students unpaired t test was used to test differences between groups. Both logistic and linear regression analyses were performed in order to test associations between the individual MetS components and SAF. RESULTS: Subjects with MetS had higher SAF (2.07 ± 0.45 arbitrary units, AU) compared to individuals without MetS (1.89 ± 0.42 AU) (p < 0.001). There was a positive association between the number of MetS components and higher SAF Z-scores (p < 0.001). Individuals in the highest SAF tertile had a higher presence of MetS (OR 2.61; 95% CI 2.48-2.75) and some of the individual components compared to subjects in the lowest SAF tertile. After correction for age, gender, creatinine clearance, HbA1c and smoking status, only elevated blood pressure and low HDL cholesterol remained significantly associated with higher SAF (p = 0.002 and p = 0.001 respectively). CONCLUSION: Skin autofluorescence was associated with the presence of MetS and some of its individual components. In addition, increasing SAF Z-scores were observed with a higher number of MetS components. Prospective studies are needed to establish whether SAF can be used as an (additional) screening tool to predict both cardiovascular disease and type 2 diabetes in high-risk populations.

The association between various smoking behaviors, cotinine biomarkers and skin autofluorescence, a marker for advanced glycation end product accumulation.

BACKGROUND: Skin autofluorescence, a biomarker for advanced glycation end products (AGEs) accumulation, has been shown to predict diabetes-related cardiovascular complications and is associated with several environmental and lifestyle factors. In the present study, we examined the association between various smoking behaviors and skin autofluorescence, as well as the association between several cotinine biomarkers and skin autofluorescence, using both epidemiological and metabolomics data. METHODS: In a cross-sectional study, we evaluated participants from the LifeLines Cohort Study and the Qatar Metabolomics Study on Diabetes (QMDiab). In the LifeLines Cohort Study smoking behavior and secondhand smoking were assessed in 8,905 individuals including 309 individuals (3.5%) with type 2 diabetes. In QMDiab, cotinine biomarkers were measured in saliva, plasma and urine in 364 individuals of whom 188 (51%) had type 2 diabetes. Skin autofluorescence was measured non-invasively in all participants using the AGE Reader. RESULTS: Skin autofluorescence levels increased with a higher number of hours being exposed to secondhand smoking. Skin autofluorescence levels of former smokers approached levels of never smokers after around 15 years of smoking cessation. Urinary cotinine N-oxide, a biomarker of nicotine exposure, was found to be positively associated with skin autofluorescence in the QMDiab study (p = 0.03). CONCLUSIONS: In the present study, we have demonstrated that secondhand smoking is associated with higher skin autofluorescence levels whereas smoking cessation has a beneficial effect on skin autofluorescence. Finally, urinary cotinine N-oxide might be used as an alternative way for questionnaires to examine the effect of (environmental) tobacco smoking on skin autofluorescence.

New Locus for Skin Intrinsic Fluorescence in Type 1 Diabetes Also Associated With Blood and Skin Glycated Proteins.

Skin fluorescence (SF) noninvasively measures advanced glycation end products (AGEs) in the skin and is a risk indicator for diabetes complications. N-acetyltransferase 2 (NAT2) is the only known locus influencing SF. We aimed to identify additional genetic loci influencing SF in type 1 diabetes (T1D) through a meta-analysis of genome-wide association studies (N = 1,359) including Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) and Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR). A locus on chromosome 1, rs7533564 (P = 1.9 × 10(-9)), was associated with skin intrinsic fluorescence measured by SCOUT DS (excitation 375 nm, emission 435-655 nm), which remained significant after adjustment for time-weighted HbA1c (P = 1.7 × 10(-8)). rs7533564 was associated with mean HbA1c in meta-analysis (P = 0.0225), mean glycated albumin (P = 0.0029), and glyoxal hydroimidazolones (P = 0.049), an AGE measured in skin biopsy collagen, in DCCT. rs7533564 was not associated with diabetes complications in DCCT/EDIC or with SF in subjects without diabetes (nondiabetic [ND]) (N = 8,721). In conclusion, we identified a new locus associated with SF in T1D subjects that did not show similar effect in ND subjects, suggesting a diabetes-specific effect. This association needs to be investigated in type 2 diabetes.

Lifestyle and clinical determinants of skin autofluorescence in a population-based cohort study.

BACKGROUND: Skin autofluorescence (SAF) is a noninvasive marker of advanced glycation end products (AGEs). In diabetes, higher SAF levels have been positively associated with long-term complications, cardiovascular morbidity and mortality. Because little is known about the factors that influence SAF in nondiabetic individuals, we assessed the association of clinical and lifestyle parameters with SAF as well as their interactions in a large-scale, nondiabetic population and performed the same analysis in a type 2 diabetic subgroup. METHODS: In a cross-sectional study in participants from the LifeLines Cohort Study, extensive clinical and biochemical phenotyping, including SAF measurement, was assessed in 9009 subjects of whom 314 (3·5%) subjects with type 2 diabetes. RESULTS: Mean SAF was 2·04 ± 0·44 arbitrary units (AU) in nondiabetic individuals and 2·44 ± 0·55 AU in type 2 diabetic subjects (P < 0·0001). Multivariate backward regression analysis showed that in the nondiabetic population, SAF was significantly and independently associated with age, BMI, HbA1c, creatinine clearance, genetic polymorphism in NAT2 (rs4921914), current smoking, pack-years of smoking and coffee consumption. In the type 2 diabetic group, a similar set of factors was associated with SAF, except for coffee consumption. CONCLUSIONS: In addition to the established literature on type 2 diabetes, we have demonstrated that SAF levels are associated with several clinical and lifestyle factors in the nondiabetic population. These parameters should be taken into consideration when using SAF as a screening or prediction tool for populations at risk for cardiovascular disease and diabetes.

Combined effects of smoking and alcohol on metabolic syndrome: the LifeLines cohort study.

INTRODUCTION: The development of metabolic syndrome (MetS) is influenced by environmental factors such as smoking and alcohol consumption. We determined the combined effects of smoking and alcohol on MetS and its individual components. METHODS: 64,046 participants aged 18-80 years from the LifeLines Cohort study were categorized into three body mass index (BMI) classes (BMI<25, normal weight; BMI 25-30, overweight; BMI≥30 kg/m2, obese). MetS was defined according to the revised criteria of the National Cholesterol Education Program's Adult Treatment Panel III (NCEP ATP III). Within each BMI class and smoking subgroup (non-smoker, former smoker, <20 and ≥20 g tobacco/day), the cross-sectional association between alcohol and individual MetS components was tested using regression analysis. RESULTS: Prevalence of MetS varied greatly between the different smoking-alcohol subgroups (1.7-71.1%). HDL cholesterol levels in all alcohol drinkers were higher than in non-drinkers (0.02 to 0.29 mmol/L, P values<0.001). HDL cholesterol levels were lower when they were also a former or current smoker (<20 and ≥20 g tobacco/day). Consumption of ≤1 drink/day indicated a trend towards lower triglyceride levels (non-significant). Concurrent use alcohol (>1 drink/day) and tobacco showed higher triglycerides levels. Up to 2 drinks/day was associated with a smaller waist circumference in overweight and obese individuals. Consumption of >2 drinks/day increased blood pressure, with the strongest associations found for heavy smokers. The overall metabolic profile of wine drinkers was better than that of non-drinkers or drinkers of beer or spirits/mixed drinks. CONCLUSION: Light alcohol consumption may moderate the negative associations of smoking with MetS. Our results suggest that the lifestyle advice that emphasizes smoking cessation and the restriction of alcohol consumption to a maximum of 1 drink/day, is a good approach to reduce the prevalence of MetS.

Associations between smoking, components of metabolic syndrome and lipoprotein particle size.

BACKGROUND: The clustering of metabolic and cardiovascular risk factors is known as metabolic syndrome (MetS). The risk of having MetS is strongly associated with increased adiposity and can be further modified by smoking behavior. Apolipoproteins (apo) associated with low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C) may be altered in MetS. This study aimed to examine the association between smoking and the following parameters: MetS and its components, levels of apolipoproteins and estimated lipoprotein particle size, separately for men and women, and in different body mass index (BMI) classes. METHODS: We included 24,389 men and 35,078 women aged between 18 and 80 years who participated in the LifeLines Cohort Study between December 2006 and January 2012; 5,685 men and 6,989 women were current smokers. Participants were categorized into three different body mass index (BMI) classes (BMI <25; BMI 25 to 30; BMI ≥30 kg/m²). MetS was defined according to the National Cholesterol Education Program's Adult Treatment Panel III (NCEP:ATPIII) criteria. Blood pressure, anthropometric and lipid measurements were rigorously standardized, and the large sample size enabled a powerful estimate of quantitative changes. The association between smoking and the individual MetS components, and apoA1 and apoB, was tested with linear regression. Logistic regression was used to examine the effect of smoking and daily tobacco smoked on risk of having MetS. All models were age adjusted and stratified by sex and BMI class. RESULTS: Prevalence of MetS increased with higher BMI levels. A total of 64% of obese men and 42% of obese women had MetS. Current smoking was associated with a higher risk of MetS in both sexes and all BMI classes (odds ratio 1.7 to 2.4 for men, 1.8 to 2.3 for women, all P values <0.001). Current smokers had lower levels of HDL cholesterol and apoA1, higher levels of triglycerides and apoB, and higher waist circumference than non-smokers (all P <0.001). Smoking had no consistent association with blood pressure or fasting blood glucose. In all BMI classes, we found a dose-dependent association of daily tobacco consumption with MetS prevalence as well as with lower levels of HDL cholesterol, higher triglyceride levels and lower ratios of HDL cholesterol/apoA1 and, only in those with BMI <30, LDL cholesterol/apoB (all P <0.001). CONCLUSIONS: Smoking is associated with an increased prevalence of MetS, independent of sex and BMI class. This increased risk is mainly related to lower HDL cholesterol, and higher triglycerides and waist circumference. In addition, smoking was associated with unfavorable changes in apoA1 and apoB, and in lipoprotein particle size. Please see related commentary: http://www.biomedcentral.com/1741-7015/11/196.

Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.

Obesity genes identified in genome-wide association studies are associated with adiposity measures and potentially with nutrient-specific food preference.

BACKGROUND: New genetic loci, most of which are expressed in the brain, have recently been reported to contribute to the development of obesity. The brain, especially the hypothalamus, is strongly involved in regulating weight and food intake. OBJECTIVES: We investigated whether the recently reported obesity loci are associated with measures of abdominal adiposity and whether these variants affect dietary energy or macronutrient intake. DESIGN: We studied 1700 female Dutch participants in the European Prospective Investigation into Cancer and Nutrition (EPIC). Their anthropometric measurements and intake of macronutrients were available. Genotyping was performed by using KASPar chemistry. A linear regression model, with an assumption of an additive effect, was used to analyze the association between genotypes of 12 single nucleotide polymorphisms (SNPs) and adiposity measures and dietary intake. RESULTS: Seven SNPs were associated (P < 0.05) with weight, body mass index (BMI), and waist circumference (unadjusted for BMI). They were in or near to 6 loci: FTO, MC4R, KCTD15, MTCH2, NEGR1, and BDNF. Five SNPs were associated with dietary intake (P < 0.05) and were in or near 5 loci: SH2B1 (particularly with increased fat), KCTD15 (particularly with carbohydrate intake), MTCH2, NEGR1, and BDNF. CONCLUSIONS: We confirmed some of the findings for the newly identified obesity loci that are associated with general adiposity in a healthy Dutch female population. Our results suggest that these loci are not specifically associated with abdominal adiposity but more generally with obesity. We also found that some of the SNPs were associated with macronutrient-specific food intake.