To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

Haptoglobin is an acute phase inflammatory marker. Its main function is to bind hemoglobin released from erythrocytes to aid its elimination, and thereby haptoglobin prevents the generation of reactive oxygen species in the blood. Haptoglobin levels have been repeatedly associated with a variety of inflammation-linked infectious and non-infectious diseases, including malaria, tuberculosis, human immunodeficiency virus, hepatitis C, diabetes, carotid atherosclerosis, and acute myocardial infarction. However, a comprehensive genetic assessment of the inter-individual variability of circulating haptoglobin levels has not been conducted so far.We used a genome-wide association study initially conducted in 631 French children followed by a replication in three additional European sample sets and we identified a common single nucleotide polymorphism (SNP), rs2000999 located in the Haptoglobin gene (HP) as a strong genetic predictor of circulating Haptoglobin levels (P(overall) = 8.1 × 10(-59)), explaining 45.4% of its genetic variability (11.8% of Hp global variance). The functional relevance of rs2000999 was further demonstrated by its specific association with HP mRNA levels (β = 0.23 ± 0.08, P = 0.007). Finally, SNP rs2000999 was associated with decreased total and low-density lipoprotein cholesterol in 8,789 European children (P(total cholesterol) = 0.002 and P(LDL) = 0.0008).Given the central position of haptoglobin in many inflammation-related metabolic pathways, the relevance of rs2000999 genotyping when evaluating haptoglobin concentration should be further investigated in order to improve its diagnostic/therapeutic and/or prevention impact.

Prevention of obesity should start as early as possible after birth. We aimed to build clinically useful equations estimating the risk of later obesity in newborns, as a first step towards focused early prevention against the global obesity epidemic.

There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8x10(-57)), CCL4L1 (p = 3.9x10(-21)), IL18 (p = 6.8x10(-13)), LPA (p = 4.4x10(-10)), GGT1 (p = 1.5x10(-7)), SHBG (p = 3.1x10(-7)), CRP (p = 6.4x10(-6)) and IL1RN (p = 7.3x10(-6)) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8x10(-40)), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways.

Adults who were born preterm with a very low birth weight have higher blood pressure and impaired glucose regulation later in life compared with those born at term. We investigated cardiometabolic risk factors in young adults who were born at any degree of prematurity in the Preterm Birth and Early Life Programming of Adult Health and Disease (ESTER) Study, a population-based cohort study of individuals born in 1985-1989 in Northern Finland. In 2009-2011, 3 groups underwent clinical examination: 134 participants born at less than 34 gestational weeks (early preterm), 242 born at 34-36 weeks (late preterm), and 344 born at 37 weeks or later (controls). Compared with controls, adults who were born preterm had higher body fat percentages (after adjustment for sex, age, and cohort (1985-1986 or 1987-1989), for those born early preterm, difference = 6.2%, 95% confidence interval (CI): 0.4, 13.2; for those born late preterm, difference = 8.0%, 95% CI: 2.4, 13.8), waist circumferences, blood pressure (for those born early preterm, difference = 3.0 mm Hg, 95% CI: 0.9, 5.1; for those born late preterm, difference = 1.7, 95% CI: -0.1, 3.4), plasma uric acid levels (for those born early preterm, difference = 20.1%, 95% CI: 7.9, 32.3; for those born late preterm, difference = 20.2%, 95% CI: 10.7, 30.5), alanine aminotransferase levels, and aspartate transaminase levels. They were also more likely to have metabolic syndrome (for those born early preterm, odds ratio = 3.7, 95% CI: 1.6, 8.2; for those born late preterm, odds ratio = 2.5, 95% CI: 1.2, 5.3). Elevated levels of conventional and emerging risk factors suggest a higher risk of cardiometabolic disease later in life. These risk factors are also present in the large group of adults born late preterm.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the 'missing heritability'. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR≥25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2×10(-4) (95% confidence interval [9.6×10(-5)-3.1×10(-4)]); accounts overall for 0.5% [0.19%-0.82%] of severe childhood obesity cases (P = 3.8×10(-10); odds ratio = 25.0 [9.9-60.6]); and results in a mean body mass index (BMI) increase of 5.8 kg.m(-2) [1.8-10.3] in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for the identification of variants making an appreciable contribution to complex disease.

The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.

African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.

Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8 × 10(-106)), PRMT6 (rs17496332, 1p13.3, p = 1.4 × 10(-11)), GCKR (rs780093, 2p23.3, p = 2.2 × 10(-16)), ZBTB10 (rs440837, 8q21.13, p = 3.4 × 10(-09)), JMJD1C (rs7910927, 10q21.3, p = 6.1 × 10(-35)), SLCO1B1 (rs4149056, 12p12.1, p = 1.9 × 10(-08)), NR2F2 (rs8023580, 15q26.2, p = 8.3 × 10(-12)), ZNF652 (rs2411984, 17q21.32, p = 3.5 × 10(-14)), TDGF3 (rs1573036, Xq22.3, p = 4.1 × 10(-14)), LHCGR (rs10454142, 2p16.3, p = 1.3 × 10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7 × 10(-08)), and UGT2B15 (rs293428, 4q13.2, p = 5.5 × 10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5 × 10(-08), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ~15.6% and ~8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

Fasting plasma glucose and risk of type 2 diabetes are higher among Indian Asians than among European and North American Caucasians. Few studies have investigated genetic factors influencing glucose metabolism among Indian Asians.