[Show abstract][Hide abstract] ABSTRACT: Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome-wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2907 cases with AN from 14 countries (15 sites) and 14 860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery data sets. Seventy-six (72 independent) single nucleotide polymorphisms were taken forward for in silico (two data sets) or de novo (13 data sets) replication genotyping in 2677 independent AN cases and 8629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication data sets comprised 5551 AN cases and 21 080 controls. AN subtype analyses (1606 AN restricting; 1445 AN binge–purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P=3.01 × 10−7) in SOX2OT and rs17030795 (P=5.84 × 10−6) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P=5.76 × 10−6) between CUL3 and FAM124B and rs1886797 (P=8.05 × 10−6) near SPATA13. Comparing discovery with replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P=4 × 10−6), strongly suggesting that true findings exist but our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field.
[Show abstract][Hide abstract] ABSTRACT: Barrett's esophagus is an increasingly common disease that is strongly associated with reflux of stomach acid and usually a hiatus hernia, and it strongly predisposes to esophageal adenocarcinoma (EAC), a tumor with a very poor prognosis. We report the first genome-wide association study on Barrett's esophagus, comprising ,852 UK cases and 5,72 UK controls in the discovery stage and 5,986 cases and 2,825 controls in the replication stage. Variants at two loci were associated with disease risk: chromosome 6p2, rs9257809 (P combined = 4.09 × 0 −9 ; odds ratio (OR) = .2, 95% confidence interval (CI) =.3–.28), within the major histocompatibility complex locus, and chromosome 6q24, rs9936833 (P combined = 2.74 × 0 −0 ; OR = .4, 95% CI = .0–.9), for which the closest protein-coding gene is FOXF1, which is implicated in esophageal development and structure. We found evidence that many common variants of small effect contribute to genetic susceptibility to Barrett's esophagus and that SNP alleles predisposing to obesity also increase risk for Barrett's esophagus. Barrett's esophagus is one of the most common premalignant lesions in the western world. It affects over 2% of the adult population and, unlike bowel polyps, lacks any proven effective therapy 1 . In the major-ity of cases, Barrett's esophagus is associated with chronic gastro-esophageal reflux disease (GERD), including esophagitis 2,3 . Over 80% of affected individuals have a hiatus hernia in the lower esophagus that facilitates the reflux of acid and bile into the esophagus 4 . The measured annual risk of EAC in individuals with Barrett's esophagus varies widely but is approximately 0.4–1% (refs. 5–7). Notably, the incidence of EAC has been rising by 3% each year for the last 30 years; it is now the fifth most common cancer in the UK 8 . Despite modern multimodality therapy, the prog-nosis for EAC remains poor, with a 9–15% 5-year survival rate 9,10 . The etiology of Barrett's esophagus is not well characterized. Environmental factors, such as diet, are weakly associated with GERD, Barrett's esophagus and EAC, and obesity is a known risk factor for all three conditions 11 . There is also evidence implicating genetic factors: relative risks are increased by 2-to 4-fold for GERD, Barrett's esophagus and EAC when one first-degree relative is affected 12–17 . A segregation analysis of 881 pedigrees of familial Barrett's esophagus supports an incompletely dominant inheritance model with a polygenic component 18 . Extensive candidate gene and linkage searches have to date been unsuccessful in identifying genetic variants that are associated with risk of Barrett's esophagus 19 . As part of the Wellcome Trust Case Control Consortium 2 (WTCCC2) study of 15 common disorders and traits, we present the results of the first genome-wide association study of Barrett's esophagus susceptibility. Using a discovery cohort from the UK (with case samples from the Aspirin and Esomeprazole Chemoprevention Trial of Cancer in Barrett's esophagus (AspECT)) 20 and five repli-cation cohorts (including case samples from CHemoprevention Of Premalignant Intestinal Neoplasia (ChOPIN) and Esophageal Adenocarcinoma GenEtics Consortium (EAGLE) studies 9,20), we identified two variants associated with Barrett's esophagus, each with combined evidence at P < 5 × 10 −8 . The analysis workflow is outlined in Supplementary Figure 1, and characteristics of the case and con-trol samples that were included can be found in the Online Methods and Supplementary Table 1. For the discovery analysis, cases with histologically confirmed Barrett's esophagus (Online Methods) were recruited from sites across the UK (Supplementary Table 2). Population controls were taken from the WTCCC2 common set of 1958 Birth Cohort (58C) and National Blood Service (UKBS) samples as previously described 21 .
[Show abstract][Hide abstract] ABSTRACT: The standard paradigm for the analysis of genome-wide association studies involves carrying out association tests at both typed and imputed SNPs. These methods will not be optimal for detecting the signal of association at SNPs that are not currently known or in regions where allelic heterogeneity occurs. We propose a novel association test, complementary to the SNP-based approaches, that attempts to extract further signals of association by explicitly modeling and estimating both unknown SNPs and allelic heterogeneity at a locus. At each site we estimate the genealogy of the case-control sample by taking advantage of the HapMap haplotypes across the genome. Allelic heterogeneity is modeled by allowing more than one mutation on the branches of the genealogy. Our use of Bayesian methods allows us to assess directly the evidence for a causative SNP not well correlated with known SNPs and for allelic heterogeneity at each locus. Using simulated data and real data from the WTCCC project, we show that our method (i) produces a significant boost in signal and accurately identifies the form of the allelic heterogeneity in regions where it is known to exist, (ii) can suggest new signals that are not found by testing typed or imputed SNPs and (iii) can provide more accurate estimates of effect sizes in regions of association. Comment: Published in at http://dx.doi.org/10.1214/09-STS311 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)
[Show abstract][Hide abstract] ABSTRACT: There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.