ARTICLES Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa Laramie Duncan, Ph.D., Zeynep Yilmaz, Ph.D., Helena Gaspar, Ph.D., Raymond Walters, Ph.D., Jackie Goldstein, Ph.D., Verneri Anttila, Ph.D., Brendan Bulik-Sullivan, Ph.D., Stephan Ripke, M.D., Ph.D., Eating Disorders Working Group of the Psychiatric Genomics Consortium, Laura Thornton, Ph.D., Anke Hinney, Ph.D., MarkDaly,Ph.D.,PatrickF.Sullivan,M.D.,F.R.A.N.Z.C.P.,EleftheriaZeggini,Ph.D.,GeromeBreen,Ph.D., Cynthia M. Bulik, Ph.D. Objective: The authors conducted a genome-wide associ- fraction of the twin-based heritability arises from common ation study of anorexia nervosa and calculated genetic genetic variation. The authors identified one genome-wide correlations with a series of psychiatric, educational, and significant locus on chromosome 12 (rs4622308) in a region metabolic phenotypes. harboring a previously reported type 1 diabetes and auto- immune disorder locus. Significant positive genetic cor- Method: Following uniform quality control and imputation relations were observed between anorexia nervosa and procedures using the 1000 Genomes Project (phase 3) schizophrenia, neuroticism, educational attainment, and in 12 case-control cohorts comprising 3,495 anorexia high-density lipoprotein cholesterol, and significant negative nervosa cases and 10,982 controls, the authors performed genetic correlations were observed between anorexia standard association analysis followed by a meta-analysis nervosa and body mass index, insulin, glucose, and lipid across cohorts. Linkage disequilibrium score regression phenotypes. was used to calculate genome-wide common variant heritability (single-nucleotide polymorphism [SNP]-based Conclusions: Anorexia nervosa is a complex heritable phe- 2 heritability [h SNP]), partitioned heritability, and genetic notype for which this study has uncovered the first genome- correlations [rg]) between anorexia nervosa and 159 other wide significant locus. Anorexia nervosa also has large and phenotypes. significant genetic correlations with both psychiatric phe- notypes and metabolic traits. The study results encourage a Results: Results were obtained for 10,641,224 SNPs and reconceptualization of this frequently lethal disorder as one insertion-deletion variants with minor allele frequencies .1% with both psychiatric and metabolic etiology. 2 and imputation quality scores .0.6. The h SNP of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial Am J Psychiatry 2017; 00:1–9; doi: 10.1176/appi.ajp.2017.16121402 Anorexia nervosa is a serious eating disorder character- Our aim in the present study was to combine existing ized by restriction of energy intake relative to require- samples to conduct a more powerful GWAS of anorexia ments, resulting in abnormally low body weight. It has a nervosa. To further characterize the nature of the illness, we lifetime prevalence of approximately 1% and dispropor- applied linkage disequilibrium (LD) score regression (8) to tionately affects females (1, 2), and no well-replicated calculate genome-wide common variant heritability (single- 2 evidence of effective pharmacological or psychological nucleotide polymorphism [SNP]-based heritability [h SNP]), treatments for it have been identified, despite high mor- partitioned heritability, and genetic correlations (rg) between bidity and mortality (3, 4). Twin studies consistently anorexia nervosa and other phenotypes. These include the support a genetic basis for the observed familial aggre- other major psychiatric disorders with large GWASs, namely gation in anorexia nervosa, with heritability estimates in schizophrenia, bipolar disorder, major depressive disorder, the range of 48%–74% (5). Although initial genome-wide autism, and attention deficit hyperactivity disorder (ADHD), association studies (GWASs) were underpowered (6, 7), as well as medical, educational, and personality phenotypes. the available evidence strongly suggested that signals for We then used rg estimates between anorexia nervosa and anorexia nervosa would be detected with increased 159 additional phenotypes to characterize the phenome-wide sample size (6). genetic architecture of anorexia nervosa. Am J Psychiatry 00:0, nn 2017 ajp.psychiatryonline.org 1 SIGNIFICANT LOCUS AND METABOLIC CORRELATIONS IN GWAS OF ANOREXIA NERVOSA METHOD combining the U.S. and Canadian cases, we included 11 GCAN/WTCCC3–based data sets plus the CHOP/PFCG Cases and Controls data set in our analyses. For the nine data sets requiring new Our sample included 3,495 anorexia nervosa cases and 10,982 controls, we first evaluated diverse control data sets from controls. Case definition required a lifetime diagnosis of Psychiatric Genomics Consortium collaborators for po- anorexia nervosa (restricting or binge-purge subtype) or tentially suitable controls based on geographic location and fi lifetime eating disorder not otherwise speci ed, anorexia Illumina genotyping. We then performed quality control nervosa subtype (i.e., exhibiting the core features of anorexia steps (see below; additional details are provided in the nervosa). A lifetime history of bulimia nervosa was allowed, data supplement), using visual inspection of principal given the frequency of diagnostic crossover (9). Amenorrhea component plots (comparing cases to controls) as well as was not required, because it does not increase diagnostic quantile-quantile (QQ) and Manhattan plots (for evidence of fi speci city (10) (and it was removed as a diagnostic criterion systematic bias) to identify suitably matched controls. All in DSM-5 [11]). Extensive information on diagnostic and samples in the present study are of European ancestry. As consensus procedures for the samples included in the Child- shown in Figure S1 in the data supplement, all of the data sets ’ ren s Hospital of Philadelphia/Price Foundation Collabo- (except the one from Finland) form a gradient of clusters rative Group (CHOP/PFCG) cohort are available elsewhere when visualized in a scatterplot of the first two principal (7). The cases included from the Genetic Consortium for components, as expected based on known population genetic – Anorexia Nervosa/Wellcome Trust Case Control Consortium 3 features (15). (GCAN/WTCCC3) GWAS came from 12 previously collected clinical or population cohorts. Given that these were archived Quality Control and Analysis samples, the calculation of reliability statistics on diagnoses After uniform quality control and imputation using the was not possible. Mitigating that concern, however, is that 1000 Genomes Project (phase 3) (16) in the anorexia nervosa anorexia nervosa is a highly homogeneous phenotype with case-control cohorts, we performed association analysis with an high interrater agreement for diagnosis (typical kappa values additivemodelusingthedosage(theexpectedcountofoneof range from 0.81 to 0.97 [12]). Moreover, the approach taken the alleles) for each genotype for each individual for each co- here is consistent with successful GWAS meta-analysis ef- hort. After adjustment for unbalanced case and control numbers forts across psychiatric diagnoses, in which larger samples across our 12 strata (see reference 17), our summed effective are used to detect the modest effects of typical single common balanced sample size was 5,082 cases and 5,082 controls. Ac- genetic risk variants. cordingly,ourpowerwas83.1%foragenotyperelativeriskof 2 Individuals with schizophrenia, intellectual disability, and 1.25,atanallelefrequencyof0.2atp,5310 8 (http://zzz.bwh. medical or neurological conditions causing weight loss were harvard.edu/gpc). Analysis within data sets was performed in excluded, as in previous studies (6, 7). All sites had docu- PLINK with the first 10 principal components as covariates. mented permission from local ethical committees, and all METAL (17) was used to conduct fixed-effects meta-analysis participants provided informed consent. across the 12 data sets using inverse-variance weighting. Consistent with procedures established by the Psychiatric Results were obtained for 10,641,224 SNPs and insertion- Genomics Consortium (13, 14), we collected individual-level deletion variants with minor allele frequencies .1% and genotype (GWAS array) and phenotype (binary case-control imputation quality scores .0.6 (for the QQ plot, see Figure status) data from contributing previous GWAS consortia and S2 in the data supplement). The GWAS statistic inflation groups (for a description, see Table S1 in the data supplement factor (l) was 1.080, with a sample-size-adjusted l1000 of that accompanies the online edition of this article). In par- 1.008, consistent with minimal population stratification or ticular, the previous reports on anorexia nervosa GWASs other systematic biases. Plotting was performed in R (18) from CHOP/PFCG data (7) and the GCAN/WTCCC3 (6) and with LocusZoom (19). See the data supplement for provide further details about cohort ascertainment and additional methods and quality control details, and Table S1 participant characteristics not described below or in the for individual study details. online data supplement. Although most of the cases included in the published Statistical Significance anorexia nervosa GWASs were included in this analysis, The primary analysis in this study is the GWAS, which an- many of the controls used in previous GWASs could not be alyzes each SNP for association with phenotype. The in- 2 used for subsequent analyses. To summarize, our analysis ternational standard