Gene-centric meta-analyses for central adiposity traits in up to 57 412 individuals of European descent confirm known loci and reveal several novel associations.

Waist circumference (WC) and waist-to-hip ratio (WHR) are surrogate measures of central adiposity that are associated with adverse cardiovascular events, type 2 diabetes and cancer independent of body mass index (BMI). WC and WHR are highly heritable with multiple susceptibility loci identified to date. We assessed the association between SNPs and BMI-adjusted WC and WHR and unadjusted WC in up to 57 412 individuals of European descent from 22 cohorts collaborating with the NHLBI's Candidate Gene Association Resource (CARe) project. The study population consisted of women and men aged 20-80 years. Study participants were genotyped using the ITMAT/Broad/CARE array, which includes ∼50 000 cosmopolitan tagged SNPs across ∼2100 cardiovascular-related genes. Each trait was modeled as a function of age, study site and principal components to control for population stratification, and we conducted a fixed-effects meta-analysis. No new loci for WC were observed. For WHR analyses, three novel loci were significantly associated (P < 2.4 × 10(-6)). Previously unreported rs2811337-G near TMCC1 was associated with increased WHR (ß ± SE, 0.048 ± 0.008, P = 7.7 × 10(-9)) as was rs7302703-G in HOXC10 (ß = 0.044 ± 0.008, P = 2.9 × 10(-7)) and rs936108-C in PEMT (ß = 0.035 ± 0.007, P = 1.9 × 10(-6)). Sex-stratified analyses revealed two additional novel signals among females only, rs12076073-A in SHC1 (ß = 0.10 ± 0.02, P = 1.9 × 10(-6)) and rs1037575-A in ATBDB4 (ß = 0.046 ± 0.01, P = 2.2 × 10(-6)), supporting an already established sexual dimorphism of central adiposity-related genetic variants. Functional analysis using ENCODE and eQTL databases revealed that several of these loci are in regulatory regions or regions with differential expression in adipose tissue.

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.

Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci.

To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with ∼2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 × 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p < 2.4 × 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 × 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 × 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 × 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups.

Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height.

Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.

Dietary patterns and the risk of type 2 diabetes in overweight and obese individuals.

PURPOSE: Although overweight is an important determinant of diabetes risk, it remains unclear whether food choices can still influence the risk for type 2 diabetes in overweight persons. In this paper, we aim to clarify the role of dietary patterns in the development of type 2 diabetes in overweight and obese individuals. METHODS: We studied 20,835 overweight and obese participants in the Dutch part of the European Investigation into Cancer and Nutrition (EPIC-NL) study. Dietary intake was measured using a validated food frequency questionnaire, and dietary patterns were generated using factor analysis. Incident type 2 diabetes was verified against medical records. Cox proportional hazards models were used to assess the association between the dietary patterns (factor scores categorized in quartiles) and incident type 2 diabetes. RESULTS: Scoring on Pattern 1, characterized by fish, wine, chicken, raw vegetables and fruit juices, was not associated with type 2 diabetes risk after confounder adjustment. A high score on Pattern 2, characterized by soft drinks, fries and snacks, was associated with higher risk of type 2 diabetes (HR Q4 vs. Q1 (95 % CI): 1.70 (1.31; 2.20), P(trend) ≤ 0.0001), particularly among less active individuals [less active: HR Q4 vs. Q1 (95 % CI): 2.14 (1.48; 3.09), P(trend) = 0.00004, more active: HR Q4 vs. Q1 (95 % CI): 1.35 (0.93; 1.97), P(trend) = 0.01; P(interaction) = 0.02]. CONCLUSIONS: A high score on a pattern high in soft drinks, fries and snacks and low in fruit and vegetables was associated with higher risk of type 2 diabetes in overweight and obese subjects especially among physically less active individuals.

Genetic variation and effects on human eating behavior.

Feeding is a physiological process, influenced by genetic factors and the environment. In recent years, many studies have been performed to unravel the involvement of genetics in both eating behavior and its pathological forms: eating disorders and obesity. In this review, we provide a condensed introduction on the neurological aspects of eating and we describe the current status of research into the genetics of eating behavior, primarily focused on specific traits such as taste, satiation, and hunger. This is followed by an overview on the genetic studies done to unravel the heritable background of obesity and eating disorders. We examine the discussion currently taking place in the field of genetics of complex disorders and phenotypes on how to perform good and powerful studies, with the use of large-scale whole-genome association studies as one of the possible solutions. In the final part of this review, we give our view on the latest developments, including endophenotype approaches and animal studies. Studies of endophenotypes of eating behavior may help to identify core traits that are genetically influenced. Such studies would yield important knowledge on the underlying biological scaffold on which diagnostic criteria for eating disorders could be based and would provide information to influence eating behavior toward healthier living.

PTPN1 polymorphisms are associated with total and low-density lipoprotein cholesterol.

BACKGROUND: The protein tyrosine phosphatase nonreceptor type 1 (PTPN1) gene encodes for the protein tyrosine phosphatase 1B, which suppresses the signaling pathway of insulin. Variations in PTPN1 may lead to changes in insulin sensitivity and consequent changes in protein tyrosine phosphatase 1B activity may also contribute to the development of metabolic endophenotypes. Our aim was to investigate the association between single nucleotide polymorphisms (SNPs) of the PTPN1 gene and metabolic endophenotypes and insulin sensitivity. DESIGN AND METHODS: We used data from a population-based cross-sectional study of 382 Dutch Caucasian men aged between 40-80 years, in whom we genotyped and analyzed four tag SNPs in PTPN1. RESULTS: We show that the minor alleles of three tag SNPs of the PTPN1 gene (rs6067484, rs6020611, rs1060402) are associated with higher levels of total plasma cholesterol and low-density lipoprotein (LDL) cholesterol in men with a body mass index (BMI) below 26 kg/m2 (P<0.05). We also show that men with a BMI below 26 kg/m2 and carrying the rs3487348 T allele tend to have a more beneficial profile for total plasma cholesterol and LDL cholesterol (P<0.05). Haplotypes that comprised these alleles were also borderline statistically significant associated with higher levels of LDL and total cholesterol in men with BMI below 26 kg/m2. CONCLUSION: Our results suggest that SNPs in the PTPN1 gene are associated with total plasma and LDL cholesterol levels.

Are recently identified genetic variants regulating BMI in the general population associated with anorexia nervosa?

The influence of body mass index (BMI) on susceptibility to anorexia nervosa (AN) is not clear. Recently published genome-wide association (GWA) studies of the general population identified several variants influencing BMI. We genotyped these variants in an AN sample to test for association and to investigate a combined effect of BMI-increasing alleles (as determined in the original GWA studies) on the risk of developing the disease. Individual single nucleotide polymorphisms (SNPs) were tested for association with AN in a sample of 267 AN patients and 1,636 population controls. A logistic regression for the combined effect of BMI-increasing alleles included 225 cases and 1,351 controls. We found no significant association between individual SNPs and AN. The analysis of a combined effect of BMI-increasing alleles showed absence of association with the investigated condition. The percentages of BMI-increasing alleles were equal between cases and controls. This study found no evidence that genetic variants regulating BMI in the general population are significantly associated with susceptibility to AN.

Common variants in the type 2 diabetes KCNQ1 gene are associated with impairments in insulin secretion during hyperglycaemic glucose clamp.

BACKGROUND: Genome-wide association studies in Japanese populations recently identified common variants in the KCNQ1 gene to be associated with type 2 diabetes. We examined the association of these variants within KCNQ1 with type 2 diabetes in a Dutch population, investigated their effects on insulin secretion and metabolic traits and on the risk of developing complications in type 2 diabetes patients. METHODOLOGY: The KCNQ1 variants rs151290, rs2237892, and rs2237895 were genotyped in a total of 4620 type 2 diabetes patients and 5285 healthy controls from the Netherlands. Data on macrovascular complications, nephropathy and retinopathy were available in a subset of diabetic patients. Association between genotype and insulin secretion/action was assessed in the additional sample of 335 individuals who underwent a hyperglycaemic clamp. PRINCIPAL FINDINGS: We found that all the genotyped KCNQ1 variants were significantly associated with type 2 diabetes in our Dutch population, and the association of rs151290 was the strongest (OR 1.20, 95% CI 1.07-1.35, p = 0.002). The risk C-allele of rs151290 was nominally associated with reduced first-phase glucose-stimulated insulin secretion, while the non-risk T-allele of rs2237892 was significantly correlated with increased second-phase glucose-stimulated insulin secretion (p = 0.025 and 0.0016, respectively). In addition, the risk C-allele of rs2237892 was associated with higher LDL and total cholesterol levels (p = 0.015 and 0.003, respectively). We found no evidence for an association of KCNQ1 with diabetic complications. CONCLUSIONS: Common variants in the KCNQ1 gene are associated with type 2 diabetes in a Dutch population, which can be explained at least in part by an effect on insulin secretion. Furthermore, our data suggest that KCNQ1 is also associated with lipid metabolism.

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.

Variants in neuropeptide Y receptor 1 and 5 are associated with nutrient-specific food intake and are under recent selection in Europeans.

There is a large variation in caloric intake and macronutrient preference between individuals and between ethnic groups, and these food intake patterns show a strong heritability. The transition to new food sources during the agriculture revolution around 11,000 years ago probably created selective pressure and shaped the genome of modern humans. One major player in energy homeostasis is the appetite-stimulating hormone neuropeptide Y, in which the stimulatory capacity may be mediated by the neuropeptide Y receptors 1, 2 and 5 (NPY1R, NPY2R and NPY5R). We assess association between variants in the NPY1R, NPY2R and NPY5R genes and nutrient intake in a cross-sectional, single-center study of 400 men aged 40 to 80 years, and we examine whether genomic regions containing these genes show signatures of recent selection in 270 HapMap individuals (90 Africans, 90 Asians, and 90 Caucasians) and in 846 Dutch bloodbank controls. Our results show that derived alleles in NPY1R and NPY5R are associated with lower carbohydrate intake, mainly because of a lower consumption of mono- and disaccharides. We also show that carriers of these derived alleles, on average, consume meals with a lower glycemic index and glycemic load and have higher alcohol consumption. One of these variants shows the hallmark of recent selection in Europe. Our data suggest that lower carbohydrate intake, consuming meals with a low glycemic index and glycemic load, and/or higher alcohol consumption, gave a survival advantage in Europeans since the agricultural revolution. This advantage could lie in overall health benefits, because lower carbohydrate intake, consuming meals with a low GI and GL, and/or higher alcohol consumption, are known to be associated with a lower risk of chronic diseases.

No association of PTPN1 polymorphisms with macronutrient intake and measures of adiposity.

The protein tyrosine phosphatase nonreceptor type1 (PTPN1) gene encodes for the protein tyrosine phosphatase 1B, which suppresses the signaling pathway of leptin. Variations of the PTPN1 gene may lead to changes in leptin sensitivity and thereby influence eating behavior and measures of obesity. This study investigated the association between single-nucleotide polymorphisms (SNPs) of the PTPN1 gene and eating behavior and different measures of obesity, including visceral fat. We used data from a population-based, cross-sectional study of 382 Dutch white men aged 40-80 years. Self-reported macronutrient intake was collected with a food frequency questionnaire. Anthropometrical measurements included BMI, waist and hip circumference, total lean and fat mass measured with dual-energy X-ray absorptiometry, and visceral and subcutaneous fat measured with ultrasound. Associations were studied using linear regression analysis. There were no statistically significant associations of SNPs in the PTPN1 gene with dietary phenotypes or measures of obesity.