Null mutations in the PCSK1 gene, encoding the proprotein convertase 1/3 (PC1/3), cause recessive monogenic early onset obesity. Frequent coding variants that modestly impair PC1/3 function mildly increase the risk for common obesity. The aim of this study was to determine the contribution of rare functional PCSK1 mutations to obesity. PCSK1 exons were sequenced in 845 nonconsanguineous extremely obese Europeans. Eight novel nonsynonymous PCSK1 mutations were identified, all heterozygous. Seven mutations had a deleterious effect on either the maturation or the enzymatic activity of PC1/3 in cell lines. Of interest, five of these novel mutations, one of the previously described frequent variants (N221D), and the mutation found in an obese mouse model (N222D), affect residues at or near the structural calcium binding site Ca-1. The prevalence of the newly identified mutations was assessed in 6,233 obese and 6,274 lean European adults and children, which showed that carriers of any of these mutations causing partial PCSK1 deficiency had an 8.7-fold higher risk to be obese than wild-type carriers. These results provide the first evidence of an increased risk of obesity in heterozygous carriers of mutations in the PCSK1 gene. Furthermore, mutations causing partial PCSK1 deficiency are present in 0.83% of extreme obesity phenotypes.

Onset of alcohol use at an early age increases the risk for later alcohol dependence. We investigated the role of the glucocorticoid receptor (GR) gene (NR3C1) in onset of alcohol use and abuse in 14-year-old adolescents (n = 4534). Several NR3C1 polymorphisms were associated with onset of alcohol drinking or drunkenness at this age. Strongest associations were observed in females, with one marker (rs244465) remaining significant after correction for multiple testing (Padj = 0.0067; odds ratio = 1.7, for drunkenness). Our data provide the first evidence that GR modulates initiation of alcohol abuse and reveal a polymorphism that might contribute to susceptibility to addiction.

Phenotype mining is a novel approach for elucidating the genetic basis of complex phenotypic variation. It involves a search of rich phenotype databases for measures correlated with genetic variation, as identified in genome-wide genotyping or sequencing studies. An initial implementation of phenotype mining in a prospective unselected population cohort, the Northern Finland 1966 Birth Cohort (NFBC1966), identifies neurodevelopment-related traits—intellectual deficits, poor school performance and hearing abnormalities—which are more frequent among individuals with large (>500 kb) deletions than among other cohort members. Observation of extensive shared single nucleotide polymorphism haplotypes around deletions suggests an opportunity to expand phenotype mining from cohort samples to the populations from which they derive.

Serum concentrations of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TGs) and total cholesterol (TC) are important heritable risk factors for cardiovascular disease. Although genome-wide association studies (GWASs) of circulating lipid levels have identified numerous loci, a substantial portion of the heritability of these traits remains unexplained. Evidence of unexplained genetic variance can be detected by combining multiple independent markers into additive genetic risk scores. Such polygenic scores, constructed using results from the ENGAGE Consortium GWAS on serum lipids, were applied to predict lipid levels in an independent population-based study, the Rotterdam Study-II (RS-II). We additionally tested for evidence of a shared genetic basis for different lipid phenotypes. Finally, the polygenic score approach was used to identify an alternative genome-wide significance threshold before pathway analysis and those results were compared with those based on the classical genome-wide significance threshold. Our study provides evidence suggesting that many loci influencing circulating lipid levels remain undiscovered. Cross-prediction models suggested a small overlap between the polygenic backgrounds involved in determining LDL-C, HDL-C and TG levels. Pathway analysis utilizing the best polygenic score for TC uncovered extra information compared with using only genome-wide significant loci. These results suggest that the genetic architecture of circulating lipids involves a number of undiscovered variants with very small effects, and that increasing GWAS sample sizes will enable the identification of novel variants that regulate lipid levels.

Background

Complex diseases are associated with altered interactions between thousands of genes. We developed a novel method to identify and prioritize disease genes, which was generally applicable to complex diseases.

Results

We identified modules of highly interconnected genes in disease-specific networks derived from integrating gene-expression and protein interaction data. We examined if those modules were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies. First, we analyzed publicly available gene expression microarray and genome-wide association study (GWAS) data from 13, highly diverse, complex diseases. In each disease, highly interconnected genes formed modules, which were significantly enriched for genes harboring disease-associated SNPs. To test if such modules could be used to find novel genes for functional studies, we repeated the analyses using our own gene expression microarray and GWAS data from seasonal allergic rhinitis. We identified a novel gene, FGF2, whose relevance was supported by functional studies using combined small interfering RNA-mediated knock-down and gene expression microarrays. The modules in the 13 complex diseases analyzed here tended to overlap and were enriched for pathways related to oncological, metabolic and inflammatory diseases. This suggested that this union of the modules would be associated with a general increase in susceptibility for complex diseases. Indeed, we found that this union was enriched with GWAS genes for 145 other complex diseases.

Conclusions

Modules of highly interconnected complex disease genes were enriched for disease-associated SNPs, and could be used to find novel genes for functional studies.

We carried out a genome-wide association study of hemoglobin levels in 16,001 individuals of European and Indian Asian ancestry. The most closely associated SNP (rs855791) results in nonsynonymous (V736A) change in the serine protease domain of TMPRSS6 and a blood hemoglobin concentration 0.13 (95% CI 0.09–0.17) g/dl lower per copy of allele A (P = 1.6 × 10−13). Our findings suggest that TMPRSS6, a regulator of hepcidin synthesis and iron handling, is crucial in hemoglobin level maintenance.

OBJECTIVE

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.

RESEARCH DESIGN AND METHODS

We carried out genome-wide association studies for fasting glucose in 5,089 nondiabetic Indian Asians genotyped with the Illumina Hap610 BeadChip and 2,385 Indian Asians (698 with type 2 diabetes) genotyped with the Illumina 300 BeadChip. Results were compared with findings in 4,462 European Caucasians.

RESULTS

We identified three single nucleotide polymorphisms (SNPs) associated with glucose among Indian Asians at P < 5 × 10−8, all near melatonin receptor MTNR1B. The most closely associated was rs2166706 (combined P = 2.1 × 10−9), which is in moderate linkage disequilibrium with rs1387153 (r2 = 0.60) and rs10830963 (r2 = 0.45), both previously associated with glucose in European Caucasians. Risk allele frequency and effect sizes for rs2166706 were similar among Indian Asians and European Caucasians: frequency 46.2 versus 45.0%, respectively (P = 0.44); effect 0.05 (95% CI 0.01–0.08) versus 0.05 (0.03–0.07 mmol/l), respectively, higher glucose per allele copy (P = 0.84). SNP rs2166706 was associated with type 2 diabetes in Indian Asians (odds ratio 1.21 [95% CI 1.06–1.38] per copy of risk allele; P = 0.006). SNPs at the GCK, GCKR, and G6PC2 loci were also associated with glucose among Indian Asians. Risk allele frequencies of rs1260326 (GCKR) and rs560887 (G6PC2) were higher among Indian Asians compared with European Caucasians.

CONCLUSIONS

Common genetic variation near MTNR1B influences blood glucose and risk of type 2 diabetes in Indian Asians. Genetic variation at the MTNR1B, GCK, GCKR, and G6PC2 loci may contribute to abnormal glucose metabolism and related metabolic disturbances among Indian Asians.

OBJECTIVE

Genome-wide association studies have identified several variants within the MTNR1B locus that are associated with fasting plasma glucose (FPG) and type 2 diabetes. We refined the association signal by direct genotyping and examined for associations of the variant displaying the most independent effect on FPG with isolated impaired fasting glycemia (i-IFG), isolated impaired glucose tolerance (i-IGT), type 2 diabetes, and measures of insulin release and peripheral and hepatic insulin sensitivity.

RESEARCH DESIGN AND METHODS

We examined European-descent participants in the Inter99 study (n = 5,553), in a sample of young healthy Danes (n = 372), in Danish twins (n = 77 elderly and n = 97 young), in additional Danish type 2 diabetic patients (n = 1,626) and control subjects (n = 505), in the Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR) study (n = 4,656), in the North Finland Birth Cohort 86 (n = 5,258), and in the Haguenau study (n = 1,461).

RESULTS

The MTNR1B intronic variant, rs10830963, carried most of the effect on FPG and showed the strongest association with FPG (combined P = 5.3 × 10−31) and type 2 diabetes. The rs10830963 G-allele increased the risk of i-IFG (odds ratio [OR] 1.64, P = 5.5 × 10−11) but not i-IGT. The G-allele was associated with a decreased insulin release after oral and intravenous glucose challenges (P < 0.01) but not after injection of tolbutamide. In elderly twins, the G-allele associated with hepatic insulin resistance (P = 0.017).

CONCLUSIONS

The G-allele of MTNR1B rs10830963 increases risk of type 2 diabetes through a state of i-IFG and not through i-IGT. The same allele associates with estimates of β-cell dysfunction and hepatic insulin resistance.

Background

Motor proficiency is positively associated with physical activity levels. The aim of this study is to investigate associations between the timing of infant motor development and subsequent sports participation during adolescence.

Methods

Prospective observational study. The study population consisted of 9,009 individuals from the Northern Finland Birth Cohort 1966. Motor development was assessed by parental report at age 1 year, using age at walking with support and age at standing unaided. At follow up aged 14 years, data were collected on the school grade awarded for physical education (PE). Self report was used to collect information on the frequency of sports participation and number of different sports reported.

Principal Findings

Earlier infant motor development was associated with improved school PE grade, for age at walking supported (p<0.001) and standing unaided (p = <0.001). Earlier infant motor development, in terms of age at walking supported, was positively associated with the number of different sports reported (p = 0.003) and with a greater frequency of sports participation (p = 0.043). These associations were independent of gestational age and birth weight, as well as father's social class and body mass index at age 14 years.

Conclusions

Earlier infant motor development may predict higher levels of physical activity as indicated by higher school PE grade, participation in a greater number of different types of sports and increased frequency of sports participation. Identification of young children with slower motor development may allow early targeted interventions to improve motor skills and thereby increase physical activity in later life.

Background

We aimed to identify novel genetic variants affecting asthma risk, since these might provide novel insights into molecular mechanisms underlying asthma.

Methods

We performed a genome-wide association study (GWAS) in 2,669 physician-diagnosed asthmatics and 4,528 controls from Australia. Seven loci were prioritised for replication after combining our results with those from the GABRIEL consortium (n=26,475), and these were tested in an additional 25,358 independent samples from four in-silico cohorts. Quantitative multi-SNP scores of genetic load were constructed on the basis of results from the GABRIEL study and tested for association with asthma in our Australian GWAS dataset.

Findings

Two loci were confirmed to associate with asthma risk in the replication cohorts and reached genome-wide significance in the combined analysis of all available studies (n=57,800): rs4129267 (OR=1.09, combined P=2.4×10−8) in the interleukin-6 receptor gene (IL6R) and rs7130588 (OR=1.09, P=1.8×10−8) on chromosome 11q13.5 near the leucine-rich repeat containing 32 gene (LRRC32, also known as GARP). The 11q13.5 locus was significantly associated with atopic status among asthmatics (OR = 1.33, P = 7×10−4), suggesting that it is a risk factor for allergic but not non-allergic asthma. Multi-SNP association results are consistent with a highly polygenic contribution to asthma risk, including loci with weak effects that may be shared with other immune-related diseases, such as NDFIP1, HLA-B, LPP and BACH2.

Interpretation

The IL6R association further supports the hypothesis that cytokine signalling dysregulation affects asthma risk, and raises the possibility that an IL6R antagonist (tocilizumab) may be effective to treat the disease, perhaps in a genotype-dependent manner. Results for the 11q13.5 locus suggest that it directly increases the risk of allergic sensitisation which, in turn, increases the risk of subsequent development of asthma. Larger or more functionally focused studies are needed to characterise the many loci with modest effects that remain to be identified for asthma.

Funding

A full list of funding sources appears at the end of the paper.

The genome-wide association study (GWAS) approach has discovered hundreds of genetic variants associated with diseases and quantitative traits. However, despite clinical overlap and statistical correlation between many phenotypes, GWAS are generally performed one-phenotype-at-a-time. Here we compare the performance of modelling multiple phenotypes jointly with that of the standard univariate approach. We introduce a new method and software, MultiPhen, that models multiple phenotypes simultaneously in a fast and interpretable way. By performing ordinal regression, MultiPhen tests the linear combination of phenotypes most associated with the genotypes at each SNP, and thus potentially captures effects hidden to single phenotype GWAS. We demonstrate via simulation that this approach provides a dramatic increase in power in many scenarios. There is a boost in power for variants that affect multiple phenotypes and for those that affect only one phenotype. While other multivariate methods have similar power gains, we describe several benefits of MultiPhen over these. In particular, we demonstrate that other multivariate methods that assume the genotypes are normally distributed, such as canonical correlation analysis (CCA) and MANOVA, can have highly inflated type-1 error rates when testing case-control or non-normal continuous phenotypes, while MultiPhen produces no such inflation. To test the performance of MultiPhen on real data we applied it to lipid traits in the Northern Finland Birth Cohort 1966 (NFBC1966). In these data MultiPhen discovers 21% more independent SNPs with known associations than the standard univariate GWAS approach, while applying MultiPhen in addition to the standard approach provides 37% increased discovery. The most associated linear combinations of the lipids estimated by MultiPhen at the leading SNPs accurately reflect the Friedewald Formula, suggesting that MultiPhen could be used to refine the definition of existing phenotypes or uncover novel heritable phenotypes.

OBJECTIVE

The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS.

RESEARCH DESIGN AND METHODS

Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected.

RESULTS

Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure.

CONCLUSIONS

Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.

OBJECTIVE

Genome-wide association studies have identified a single nucleotide polymorphism (SNP), rs560887, located in a G6PC2 intron that is highly correlated with variations in fasting plasma glucose (FPG). G6PC2 encodes an islet-specific glucose-6-phosphatase catalytic subunit. This study examines the contribution of two G6PC2 promoter SNPs, rs13431652 and rs573225, to the association signal.

RESEARCH DESIGN AND METHODS

We genotyped 9,532 normal FPG participants (FPG <6.1 mmol/l) for three G6PC2 SNPs, rs13431652 (distal promoter), rs573225 (proximal promoter), rs560887 (3rd intron). We used regression analyses adjusted for age, sex, and BMI to assess the association with FPG and haplotype analyses to assess comparative SNP contributions. Fusion gene and gel retardation analyses characterized the effect of rs13431652 and rs573225 on G6PC2 promoter activity and transcription factor binding.

RESULTS

Genetic analyses provide evidence for a strong contribution of the promoter SNPs to FPG variability at the G6PC2 locus (rs13431652: β = 0.075, P = 3.6 × 10−35; rs573225 β = 0.073 P = 3.6 × 10−34), in addition to rs560887 (β = 0.071, P = 1.2 × 10−31). The rs13431652-A and rs573225-A alleles promote increased NF-Y and Foxa2 binding, respectively. The rs13431652-A allele is associated with increased FPG and elevated promoter activity, consistent with the function of G6PC2 in pancreatic islets. In contrast, the rs573225-A allele is associated with elevated FPG but reduced promoter activity.

CONCLUSIONS

Genetic and in situ functional data support a potential role for rs13431652, but not rs573225, as a causative SNP linking G6PC2 to variations in FPG, though a causative role for rs573225 in vivo cannot be ruled out.

Background

Thymic stromal lymphopoietin (TSLP), an IL7-like cytokine produced by bronchial epithelial cells is upregulated in asthma and induces dendritic cell maturation supporting a Th2 response. Environmental pollutants, including tobacco smoke and diesel exhaust particles upregulate TSLP suggesting that TSLP may be an interface between environmental pollution and immune responses in asthma. Since asthma is prevalent in urban communities, variants in the TSLP gene may be important in asthma susceptibility in these populations.

Objectives

To determine whether genetic variants in TSLP are associated with asthma in an urban admixed population.

Methodology and Main Results

Ten tag-SNPs in the TSLP gene were analyzed for association with asthma using 387 clinically diagnosed asthmatic cases and 212 healthy controls from an urban admixed population. One SNP (rs1898671) showed nominally significant association with asthma (odds ratio (OR) = 1.50; 95% confidence interval (95% CI): 1.09–2.05, p = 0.01) after adjusting for age, BMI, income, education and population stratification. Association results were consistent using two different approaches to adjust for population stratification. When stratified by smoking status, the same SNP showed a significantly increased risk associated with asthma in ex-smokers (OR = 2.00, 95% CI: 1.04–3.83, p = 0.04) but not significant in never-smokers (OR = 1.34; 95% CI: 0.93–1.94, p = 0.11). Haplotype-specific score test indicated that an elevated risk for asthma was associated with a specific haplotype of TSLP involving SNP rs1898671 (OR = 1.58, 95% CI: 1.10–2.27, p = 0.01). Association of this SNP with asthma was confirmed in an independent large population-based cohort consortium study (OR = 1.15, 95% CI: 1.07–1.23, p = 0.0003) and the results stratified by smoking status were also validated (ex-smokers: OR = 1.21, 95% CI: 1.08–1.34, p = 0.003; never-smokers: OR = 1.06, 95% CI: 0.94–1.17, p = 0.33).

Conclusions

Genetic variants in TSLP may contribute to asthma susceptibility in admixed urban populations with a gene and environment interaction.

OBJECTIVE

Common variation in the FTO gene is associated with BMI and type 2 diabetes. Increased BMI is associated with diabetes risk factors, including raised insulin, glucose, and triglycerides. We aimed to test whether FTO genotype is associated with variation in these metabolic traits.

RESEARCH DESIGN AND METHODS

We tested the association between FTO genotype and 10 metabolic traits using data from 17,037 white European individuals. We compared the observed effect of FTO genotype on each trait to that expected given the FTO-BMI and BMI-trait associations.

RESULTS

Each copy of the FTO rs9939609 A allele was associated with higher fasting insulin (0.039 SD [95% CI 0.013–0.064]; P = 0.003), glucose (0.024 [0.001– 0.048]; P = 0.044), and triglycerides (0.028 [0.003– 0.052]; P = 0.025) and lower HDL cholesterol (0.032 [0.008 – 0.057]; P = 0.009). There was no evidence of these associations when adjusting for BMI. Associations with fasting alanine aminotransferase, γ-glutamyl-transferase, LDL cholesterol, A1C, and systolic and diastolic blood pressure were in the expected direction but did not reach P < 0.05. For all metabolic traits, effect sizes were consistent with those expected for the per allele change in BMI. FTO genotype was associated with a higher odds of metabolic syndrome (odds ratio 1.17 [95% CI 1.10 –1.25]; P = 3 × 10−6).

CONCLUSIONS

FTO genotype is associated with metabolic traits to an extent entirely consistent with its effect on BMI. Sample sizes of >12,000 individuals were needed to detect associations at P < 0.05. Our findings highlight the importance of using appropriately powered studies to assess the effects of a known diabetes or obesity variant on secondary traits correlated with these conditions.

OBJECTIVE

A1C is widely considered the gold standard for monitoring effective blood glucose levels. Recently, a genome-wide association study reported an association between A1C and rs7072268 within HK1 (encoding hexokinase 1), which catalyzes the first step of glycolysis. HK1 deficiency in erythrocytes (red blood cells [RBCs]) causes severe nonspherocytic hemolytic anemia in both humans and mice.

RESEARCH DESIGN AND METHODS

The contribution of rs7072268 to A1C and the RBC-related traits was assessed in 6,953 nondiabetic European participants. We additionally analyzed the association with hematologic traits in 5,229 nondiabetic European individuals (in whom A1C was not measured) and 1,924 diabetic patients. Glucose control–related markers other than A1C were analyzed in 18,694 nondiabetic European individuals. A type 2 diabetes case-control study included 7,447 French diabetic patients.

RESULTS

Our study confirms a strong association between the rs7072268–T allele and increased A1C (β = 0.029%; P = 2.22 × 10−7). Surprisingly, despite adequate study power, rs7072268 showed no association with any other markers of glucose control (fasting- and 2-h post-OGTT–related parameters, n = 18,694). In contrast, rs7072268–T allele decreases hemoglobin levels (n = 13,416; β = −0.054 g/dl; P = 3.74 × 10−6) and hematocrit (n = 11,492; β = −0.13%; P = 2.26 × 10−4), suggesting a proanemic effect. The T allele also increases risk for anemia (836 cases; odds ratio 1.13; P = 0.018).

CONCLUSIONS

HK1 variation, although strongly associated with A1C, does not seem to be involved in blood glucose control. Since HK1 rs7072268 is associated with reduced hemoglobin levels and favors anemia, we propose that HK1 may influence A1C levels through its anemic effect or its effect on glucose metabolism in RBCs. These findings may have implications for type 2 diabetes diagnosis and clinical management because anemia is a frequent complication of the diabetes state.

Meta-analyses of population-based genome-wide association studies (GWAS) in adults have recently led to the detection of new genetic loci for obesity. Here we aimed to discover additional obesity loci in extremely obese children and adolescents. We also investigated if these results generalize by estimating the effects of these obesity loci in adults and in population-based samples including both children and adults. We jointly analysed two GWAS of 2,258 individuals and followed-up the best, according to lowest p-values, 44 single nucleotide polymorphisms (SNP) from 21 genomic regions in 3,141 individuals. After this DISCOVERY step, we explored if the findings derived from the extremely obese children and adolescents (10 SNPs from 5 genomic regions) generalized to (i) the population level and (ii) to adults by genotyping another 31,182 individuals (GENERALIZATION step). Apart from previously identified FTO, MC4R, and TMEM18, we detected two new loci for obesity: one in SDCCAG8 (serologically defined colon cancer antigen 8 gene; p = 1.85×10−8 in the DISCOVERY step) and one between TNKS (tankyrase, TRF1-interacting ankyrin-related ADP-ribose polymerase gene) and MSRA (methionine sulfoxide reductase A gene; p = 4.84×10−7), the latter finding being limited to children and adolescents as demonstrated in the GENERALIZATION step. The odds ratios for early-onset obesity were estimated at ∼1.10 per risk allele for both loci. Interestingly, the TNKS/MSRA locus has recently been found to be associated with adult waist circumference. In summary, we have completed a meta-analysis of two GWAS which both focus on extremely obese children and adolescents and replicated our findings in a large followed-up data set. We observed that genetic variants in or near FTO, MC4R, TMEM18, SDCCAG8, and TNKS/MSRA were robustly associated with early-onset obesity. We conclude that the currently known major common variants related to obesity overlap to a substantial degree between children and adults.

Author Summary

Genome-wide association studies (GWAS) have successfully contributed to the detection of genetic variants involved in body-weight regulation. We jointly analysed two GWAS for early-onset extreme obesity in 2,258 individuals of European origin and followed-up the findings in 3,141 individuals. Evidence for association of markers in two new genetic loci was shown (SDCCAG8 on chromosome 1q43–q44 and between TNKS/MSRA on chromosome 8p23.1). We also re-identified variants in or near FTO, MC4R, and TMEM18 to be associated with extreme obesity. In addition, we assessed the effect of the markers in 31,182 obese, lean, normal weight, and unselected individuals from population-based samples and showed that the variants near FTO, MC4R, TMEM18, and SDCCAG8 were consistently associated with obesity. For variants of TNKS/MSRA, the obesity association was limited to children and adolescents. In summary, we detected two new obesity loci and confirmed that the currently known major common variants related to obesity overlap to a substantial degree between children and adults.

Tooth development is a highly heritable process which relates to other growth and developmental processes, and which interacts with the development of the entire craniofacial complex. Abnormalities of tooth development are common, with tooth agenesis being the most common developmental anomaly in humans. We performed a genome-wide association study of time to first tooth eruption and number of teeth at one year in 4,564 individuals from the 1966 Northern Finland Birth Cohort (NFBC1966) and 1,518 individuals from the Avon Longitudinal Study of Parents and Children (ALSPAC). We identified 5 loci at P<5×10−8, and 5 with suggestive association (P<5×10−6). The loci included several genes with links to tooth and other organ development (KCNJ2, EDA, HOXB2, RAD51L1, IGF2BP1, HMGA2, MSRB3). Genes at four of the identified loci are implicated in the development of cancer. A variant within the HOXB gene cluster associated with occlusion defects requiring orthodontic treatment by age 31 years.

Author Summary

Genome-wide association studies have been used to identify genetic variants conferring susceptibility to diseases, intermediate phenotypes, and physiological traits such as height, hair color, and age at menarche. Here we analyze the NFBC1966 and ALSPAC birth cohorts to investigate the genetic determinants of a key developmental process: primary tooth development. The prospective nature of our studies allows us to exploit accurate measurements of age at first tooth eruption and number of teeth at one year, and also provides the opportunity to assess whether genetic variants affecting these traits are associated with dental problems later in the life course. Of the genes that we find to be associated with primary tooth development, several have established roles in tooth development and growth, and almost half have proposed links with the development of cancer. We find that one of the variants is also associated with occlusion defects requiring orthodontic treatment later in life. Our findings should provide a strong foundation for the study of the genetic architecture of tooth development, which as well as its relevance to medicine and dentistry, may have implications in evolutionary biology since teeth represent important markers of evolution.

Context:

Plasma levels of C-reactive protein (CRP) are independently associated with risk of coronary heart disease, but whether CRP is causally associated with coronary heart disease or merely a marker of underlying atherosclerosis is uncertain.

Objective:

To investigate association of genetic loci with CRP levels and risk of coronary heart disease.

Design, setting and participants:

We first carried out a genome-wide association (n=17,967) and replication study (n=14,747) to identify genetic loci associated with plasma CRP concentrations. Data collection took place between 1989 and 2008 and genotyping between 2003 and 2008. We carried out a Mendelian randomisation study of the most closely associated SNP in the CRP locus and published data on other CRP variants involving a total of 28,112 cases and 100,823 controls, to investigate the association of CRP variants with coronary heart disease. We compared our finding with that predicted from meta-analysis of observational studies of CRP levels and risk of coronary heart disease. For the other loci associated with CRP levels, we selected the most closely associated SNP for testing against coronary heart disease among 14,365 cases and 32,069 controls.

Main outcome measure:

Risk of coronary heart disease.

Results:

Polymorphisms in five genetic loci were strongly associated with CRP levels (% difference per minor allele): SNP rs6700896 in LEPR (−14.7% [95% Confidence Interval {CI}], −17.5 – −11.9, P=1.6×10−21), rs4537545 in IL6R (−10.8% [95% CI, −13.8 – −7.7], P=5.1×10−11), rs7553007 in CRP locus (−20.7% [95% CI, −23.5 – −17.9], P=3.3×10−38), rs1183910 in HNF1A (−13.6% [95% CI, −16.4 – −10.6], P=1.2×10−17) and rs4420638 in APOE-CI-CII (−21.8% [95% CI, −25.4 – −18.1], P=2.1×10−25). Association of SNP rs7553007 in the CRP locus with coronary heart disease gave odds ratio (OR) 0.98 (95% CI, 0.94 – 1.01) per 20% lower CRP. Our Mendelian randomisation study of variants in the CRP locus showed no association with coronary heart disease: OR 1.00 (95% CI, 0.97 – 1.02) per 20% lower CRP, compared with OR 0.94 (95% CI, 0.94 – 0.95) predicted from meta-analysis of the observational studies of CRP levels and coronary heart disease (Z-score −3.45, P<.001). SNPs rs6700896 in LEPR (OR 1.06 [95% CI, 1.02 – 1.09] per minor allele), rs4537545 in IL6R (OR 0.94 [95% CI, 0.91 – 0.97]) and rs4420638 in the APOE-CI-CII cluster (OR 1.16 [95% CI, 1.12 – 1.21]) were all associated with risk of coronary heart disease.

Conclusions:

The lack of concordance between the effect on coronary heart disease risk of CRP genotypes and CRP levels argues against a causal association of CRP with coronary heart disease.

Although the introduction of genome-wide association studies (GWAS) have greatly increased the number of genes associated with common diseases, only a small proportion of the predicted genetic contribution has so far been elucidated. Studying the cumulative variation of polymorphisms in multiple genes acting in functional pathways may provide a complementary approach to the more common single SNP association approach in understanding genetic determinants of common disease. We developed a novel pathway-based method to assess the combined contribution of multiple genetic variants acting within canonical biological pathways and applied it to data from 14,000 UK individuals with 7 common diseases. We tested inflammatory pathways for association with Crohn's disease (CD), rheumatoid arthritis (RA) and type 1 diabetes (T1D) with 4 non-inflammatory diseases as controls. Using a variable selection algorithm, we identified variants responsible for the pathway association and evaluated their use for disease prediction using a 10 fold cross-validation framework in order to calculate out-of-sample area under the Receiver Operating Curve (AUC). The generalisability of these predictive models was tested on an independent birth cohort from Northern Finland. Multiple canonical inflammatory pathways showed highly significant associations (p 10−3–10−20) with CD, T1D and RA. Variable selection identified on average a set of 205 SNPs (149 genes) for T1D, 350 SNPs (189 genes) for RA and 493 SNPs (277 genes) for CD. The pattern of polymorphisms at these SNPS were found to be highly predictive of T1D (91% AUC) and RA (85% AUC), and weakly predictive of CD (60% AUC). The predictive ability of the T1D model (without any parameter refitting) had good predictive ability (79% AUC) in the Finnish cohort. Our analysis suggests that genetic contribution to common inflammatory diseases operates through multiple genes interacting in functional pathways.

Epidemiological studies consistently show that circulating sex hormone binding globulin (SHBG) levels are lower in type 2 diabetes patients than non-diabetic individuals, but the causal nature of this association is controversial. Genetic studies can help dissect causal directions of epidemiological associations because genotypes are much less likely to be confounded, biased or influenced by disease processes. Using this Mendelian randomization principle, we selected a common single nucleotide polymorphism (SNP) near the SHBG gene, rs1799941, that is strongly associated with SHBG levels. We used data from this SNP, or closely correlated SNPs, in 27 657 type 2 diabetes patients and 58 481 controls from 15 studies. We then used data from additional studies to estimate the difference in SHBG levels between type 2 diabetes patients and controls. The SHBG SNP rs1799941 was associated with type 2 diabetes [odds ratio (OR) 0.94, 95% CI: 0.91, 0.97; P = 2 × 10−5], with the SHBG raising allele associated with reduced risk of type 2 diabetes. This effect was very similar to that expected (OR 0.92, 95% CI: 0.88, 0.96), given the SHBG-SNP versus SHBG levels association (SHBG levels are 0.2 standard deviations higher per copy of the A allele) and the SHBG levels versus type 2 diabetes association (SHBG levels are 0.23 standard deviations lower in type 2 diabetic patients compared to controls). Results were very similar in men and women. There was no evidence that this variant is associated with diabetes-related intermediate traits, including several measures of insulin secretion and resistance. Our results, together with those from another recent genetic study, strengthen evidence that SHBG and sex hormones are involved in the aetiology of type 2 diabetes.

Recent genome-wide association (GWA) studies of lipids have been conducted in samples ascertained for other phenotypes, particularly diabetes. Here we report the first GWA analysis of loci affecting total cholesterol (TC), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglycerides sampled randomly from 16 population-based cohorts and genotyped using mainly the Illumina HumanHap300-Duo platform. Our study included a total of 17,797-22,562 persons, aged 18-104 years and from geographic regions spanning from the Nordic countries to Southern Europe. We established 22 loci associated with serum lipid levels at a genome-wide significance level (P < 5 × 10-8), including 16 loci that were identified by previous GWA studies. The six newly identified loci in our cohort samples are ABCG5 (TC, P = 1.5 × 10-11; LDL, P = 2.6 × 10-10), TMEM57 (TC, P = 5.4 × 10-10), CTCF-PRMT8 region (HDL, P = 8.3 × 10-16), DNAH11 (LDL, P = 6.1 × 10-9), FADS3-FADS2 (TC, P = 1.5 × 10-10; LDL, P = 4.4 × 10-13) and MADD-FOLH1 region (HDL, P = 6 × 10-11). For three loci, effect sizes differed significantly by sex. Genetic risk scores based on lipid loci explain up to 4.8% of variation in lipids and were also associated with increased intima media thickness (P = 0.001) and coronary heart disease incidence (P = 0.04). The genetic risk score improves the screening of high-risk groups of dyslipidemia over classical risk factors.

Recent genome-wide association (GWA) studies have identified dozens of common variants associated with adult height. However, it is unknown how these variants influence height growth during childhood. We derived peak height velocity in infancy (PHV1) and puberty (PHV2) and timing of pubertal height growth spurt from parametric growth curves fitted to longitudinal height growth data to test their association with known height variants. The study consisted of N = 3,538 singletons from the prospective Northern Finland Birth Cohort 1966 with genotype data and frequent height measurements (on average 20 measurements per person) from 0–20 years. Twenty-six of the 48 variants tested associated with adult height (p<0.05, adjusted for sex and principal components) in this sample, all in the same direction as in previous GWA scans. Seven SNPs in or near the genes HHIP, DLEU7, UQCC, SF3B4/SV2A, LCORL, and HIST1H1D associated with PHV1 and five SNPs in or near SOCS2, SF3B4/SV2A, C17orf67, CABLES1, and DOT1L with PHV2 (p<0.05). We formally tested variants for interaction with age (infancy versus puberty) and found biologically meaningful evidence for an age-dependent effect for the SNP in SOCS2 (p = 0.0030) and for the SNP in HHIP (p = 0.045). We did not have similar prior evidence for the association between height variants and timing of pubertal height growth spurt as we had for PHVs, and none of the associations were statistically significant after correction for multiple testing. The fact that in this sample, less than half of the variants associated with adult height had a measurable effect on PHV1 or PHV2 is likely to reflect limited power to detect these associations in this dataset. Our study is the first genetic association analysis on longitudinal height growth in a prospective cohort from birth to adulthood and gives grounding for future research on the genetic regulation of human height during different periods of growth.

Author Summary

Family studies have shown that adult height is largely genetically determined. Identification of common genetic factors has been expedited with recent advances in genotyping techniques. However, factors regulating childhood height growth remain unclear. We investigated genetic variants of adult height for associations with peak height velocity in infancy (PHV1) and puberty (PHV2) and timing of pubertal growth spurt in a population based sample of 3,538 Finns born in 1966. Most variants studied associated with adult height in this sample. Of the 48 genetic variants tested, seven of them associated with PHV1 and five with PHV2. However, only one of these associated with both, and we found suggestive evidence for differential effects at different stages of growth for some of the variants. In this sample, less than half of the variants associated with adult height had a measurable effect on PHV1 or PHV2. However, these differences may reflect lower statistical power to detect associations with height velocities compared to adult height. This study provides a foundation for further biological investigation into the genes acting at each stage of height growth.

Obesity is a serious international health problem that increases the risk of several common diseases. The genetic factors predisposing to obesity are poorly understood. A genome-wide search for type 2 diabetes–susceptibility genes identified a common variant in the FTO (fat mass and obesity associated) gene that predisposes to diabetes through an effect on body mass index (BMI). An additive association of the variant with BMI was replicated in 13 cohorts with 38,759 participants. The 16% of adults who are homozygous for the risk allele weighed about 3 kilograms more and had 1.67-fold increased odds of obesity when compared with those not inheriting a risk allele. This association was observed from age 7 years upward and reflects a specific increase in fat mass.