A genome-wide association study of anorexia nervosa.

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.

optiCall: a robust genotype-calling algorithm for rare, low-frequency and common variants.

MOTIVATION: Existing microarray genotype-calling algorithms adopt either SNP-by-SNP (SNP-wise) or sample-by-sample (sample-wise) approaches to calling. We have developed a novel genotype-calling algorithm for the Illumina platform, optiCall, that uses both SNP-wise and sample-wise calling to more accurately ascertain genotypes at rare, low-frequency and common variants. RESULTS: Using data from 4537 individuals from the 1958 British Birth Cohort genotyped on the Immunochip, we estimate the proportion of SNPs lost to downstream analysis due to false quality control failures, and rare variants misclassified as monomorphic, is only 1.38% with optiCall, in comparison to 3.87, 7.85 and 4.09% for Illuminus, GenoSNP and GenCall, respectively. We show that optiCall accurately captures rare variants and can correctly account for SNPs where probe intensity clouds are shifted from their expected positions. AVAILABILITY AND IMPLEMENTATION: optiCall is implemented in C++ for use on UNIX operating systems and is available for download at http://www.sanger.ac.uk/resources/software/opticall/.