Michael N. Weedon

Replication of Genome-Wide Association Signals in UK Samples Reveals Risk Loci for Type 2 Diabetes

The molecular mechanisms involved in the development of type 2 diabetes are poorly understood. Starting from genome-wide genotype data for 1924 diabetic cases and 2938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3757 additional cases and 5346 controls and by integration of our findings with equivalent data from other international consortia. We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B, and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8. Our findings provide insight into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect. The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes.

Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and ∼2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 × 10−14), CDC123-CAMK1D (P = 1.2 × 10−10), TSPAN8-LGR5 (P = 1.1 × 10−9), THADA (P = 1.1 × 10−9), ADAMTS9 (P = 1.2 × 10−8) and NOTCH2 (P = 4.1 × 10−8) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.

Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits

We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.

A common variant of HMGA2 is associated with adult and childhood height in the general population

Human height is a classic, highly heritable quantitative trait. To begin to identify genetic variants influencing height, we examined genome-wide association data from 4,921 individuals. Common variants in the HMGA2 oncogene, exemplified by rs1042725, were associated with height (P = 4 × 10−8). HMGA2 is also a strong biological candidate for height, as rare, severe mutations in this gene alter body size in mice and humans, so we tested rs1042725 in additional samples. We confirmed the association in 19,064 adults from four further studies (P = 3 × 10−11, overall P = 4 × 10−16, including the genome-wide association data). We also observed the association in children (P = 1 × 10−6, N = 6,827) and a tall/short case-control study (P = 4 × 10−6, N = 3,207). We estimate that rs1042725 explains ∼0.3% of population variation in height (∼0.4 cm increased adult height per C allele). There are few examples of common genetic variants reproducibly associated with human quantitativetraits; these results represent, to our knowledge, the first consistently replicated association with adult and childhood height.

Common variants in WFS1 confer risk of type 2 diabetes

We studied genes involved in pancreatic β cell function and survival, identifying associations between SNPs in WFS1 and diabetes risk in UK populations that we replicated in an Ashkenazi population and in additional UK studies. In a pooled analysis comprising 9,533 cases and 11,389 controls, SNPs in WFS1 were strongly associated with diabetes risk. Rare mutations in WFS1 cause Wolfram syndrome; using a gene-centric approach, we show that variation in WFS1 also predisposes to common type 2 diabetes.

A genome-wide association study identifies protein quantitative trait loci (pQTLs)

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 = 1.8×10−57), CCL4L1 (p = 3.9×10−21), IL18 (p = 6.8×10−13), LPA (p = 4.4×10−10), GGT1 (p = 1.5×10−7), SHBG (p = 3.1×10−7), CRP (p = 6.4×10−6) and IL1RN (p = 7.3×10−6) 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 = 6.8×10−40), 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.

Common variation in the FTO gene alters diabetes-related metabolic traits to the extent expected, given its effect on BMI

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.

Assessing the combined impact of 18 common genetic variants of modest effect sizes on type 2 diabetes risk

OBJECTIVES—Genome-wide association studies have dramatically increased the number of common genetic variants that are robustly associated with type 2 diabetes. A possible clinical use of this information is to identify individuals at high risk of developing the disease, so that preventative measures may be more effectively targeted. Here, we assess the ability of 18 confirmed type 2 diabetes variants to differentiate between type 2 diabetic case and control subjects. RESEARCH DESIGN AND METHODS—We assessed index single nucleotide polymorphisms (SNPs) for the 18 independent loci in 2,598 control subjects and 2,309 case subjects from the Genetics of Diabetes Audit and Research Tayside Study. The discriminatory ability of the combined SNP information was assessed by grouping individuals based on number of risk alleles carried and determining relative odds of type 2 diabetes and by calculating the area under the receiver-operator characteristic curve (AUC). RESULTS—Individuals carrying more risk alleles had a higher risk of type 2 diabetes. For example, 1.2% of individuals with >24 risk alleles had an odds ratio of 4.2 (95% CI 2.11–8.56) against the 1.8% with 10–12 risk alleles. The AUC (a measure of discriminative accuracy) for these variants was 0.60. The AUC for age, BMI, and sex was 0.78, and adding the genetic risk variants only marginally increased this to 0.80. CONCLUSIONS—Currently, common risk variants for type 2 diabetes do not provide strong predictive value at a population level. However, the joint effect of risk variants identified subgroups of the population at substantially different risk of disease. Further studies are needed to assess whether individuals with extreme numbers of risk alleles may benefit from genetic testing.

Association Analysis of 6,736 U.K. Subjects Provides Replication and Confirms TCF7L2 as a Type 2 Diabetes Susceptibility Gene With a Substantial Effect on Individual Risk

Recent data suggest that common variation in the transcription factor 7-like 2 (TCF7L2) gene is associated with type 2 diabetes. Evaluation of such associations in independent samples provides necessary replication and a robust assessment of effect size. Using four TCF7L2 single nucleotide polymorphisms (SNPs; including the two most associated in the previous study), we conducted a case-control study in 2,158 type 2 diabetic subjects and 2,574 control subjects and a family-based association analysis in 388 parent-offspring trios all from the U.K. All SNPs showed powerful associations with diabetes in the case-control analysis, with strongest effects at rs7903146 (allele-wise relative risk 1.36 [95% CI 1.24–1.48], P = 1.3 × 10−11). Data were consistent with a multiplicative model. The family-based analyses provided independent evidence for association at all loci (e.g., rs4506565, 62% transmission, P = 7 × 10−5) with no parent-of-origin effects. The frequency of diabetes-associated TCF7L2 genotypes was greater in cases ascertained for positive family history and early onset (rs4606565, P = 0.02); the population-attributable risk, estimated from the least-selected cases, is ∼16%. The overall evidence for association for these variants (P = 4.4 × 10−14 combining case-control and family-based analyses for rs4506565) exceeds genome-wide significance criteria and clearly establishes TCF7L2 as a type 2 diabetes susceptibility gene of substantial importance.

Common Variants of the Novel Type 2 Diabetes Genes CDKAL1 and HHEX/IDE Are Associated With Decreased Pancreatic β-Cell Function

OBJECTIVE— Type 2 diabetes is characterized by impaired pancreatic β-cell function and decreased insulin sensitivity. Genome-wide association studies have identified common, novel type 2 diabetes susceptibility loci within the FTO, CDKAL1, CDKN2A/CDKN2B, IGF2BP2, HHEX/IDE, and SLC30A8 gene regions. Our objective was to explore the relationships between the diabetes-associated alleles and measures of β-cell function and whole-body insulin sensitivity. RESEARCH DESIGN AND METHODS— A total of 1,276 healthy subjects of European ancestry were studied at 19 centers. Indexes of β-cell function (including 30-min insulin response and glucose sensitivity) were derived from a 75-g oral glucose tolerance test, and whole-body insulin sensitivity (M/I) was assessed by hyperinsulinemic-euglycemic clamp. Genotype/phenotype relationships were studied by linear trend analysis correcting for age, sex, and recruitment center. RESULTS— CDKAL1 and HHEX/IDE diabetes-associated alleles were both associated with decreased 30-min insulin response (both P = 0.0002) and decreased pancreatic β-cell glucose sensitivity (P = 9.86 × 10−5 and 0.009, respectively), and these relationships remained after correction for M/I. The FTO susceptibility allele showed a weak but consistent association with increased adiposity, which in turn was linked to a decrease in M/I. However, none of the other novel diabetes susceptibility alleles were associated with insulin sensitivity. CONCLUSIONS— CDKAL1 and HHEX/IDE diabetes-associated alleles are associated with decreased pancreatic β-cell function, including decreased β-cell glucose sensitivity that relates insulin secretion to plasma glucose concentration. We confirmed the association between the FTO allele and increased adiposity, but none of the other novel susceptibility alleles were associated with whole-body insulin sensitivity.