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 × 106) between CUL3 and FAM124B and rs1886797 (P=8.05 × 106) 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.


Anorexia nervosa (AN) is a perplexing biologically influenced psychiatric disorder characterized by the maintenance of dangerously low body weight, fear of weight gain and seeming indifference to the seriousness of the illness.1 AN affects ~1% of the population.2,3 Females are disproportionately afflicted, although males also develop the condition.4 The most common age of onset is 15–19 years;5 however, the incidence appears to be increasing in the pre-pubertal period6 and in older adults.7 AN is often comorbid with major depressive disorder, anxiety disorders and multiple somatic complications.8, 9, 10, 11, 12 Although most individuals recover, ~25% develop a chronic and relapsing course.13 AN ranks among the ten leading causes of disability among young women14 and has one of the highest mortality rates of any psychiatric disorder.15, 16, 17, 18, 19 The evidence base for treatment of AN has been described as weak,20,21 and treatment and extended inpatient hospitalizations for weight restoration are costly.22,23 In sum, the public health impact of AN is considerable, and AN carries substantial morbidity, mortality, and personal, familial and societal costs.

As with most idiopathic psychiatric disorders, the inheritance of AN is complex. The core features of AN (i.e., the ability and determination to maintain low body mass index (BMI)) are remarkably homogeneous across time and cultures.24,25 Genetic epidemiological studies have documented the familiality of AN (relative risk 11.3 in first-degree relatives of AN probands)26,27 and the estimated twin-based heritability of AN ranges from 33 to 84%.28, 29, 30, 31, 32 Genome-wide linkage studies did not narrow the genomic search space in a compelling manner.33, 34, 35 Findings from candidate gene studies of AN resemble those for most complex biomedical diseases—initial intriguing findings diminished by the absence of rigorous replication.36, 37, 38

Given the centrality of weight dysregulation to AN, genes implicated in the regulation of body weight might also be involved in the etiology of AN.39,40 Therefore genetic variants with a profound effect on BMI are worthy of consideration.38

Two genome-wide association studies (GWAS) of AN have been conducted. One study that used DNA pooling and genotyping with a modest number of microsatellite markers with follow-up genotyping detected evidence for association with rs2048332 on chromosome 1, but this finding did not reach genome-wide significance.41 A GWAS of 1033 AN cases from USA, Canada and Europe compared with 3733 pediatric controls yielded no genome-wide significant findings.42 Recently, a sequencing and genotyping study of 152 candidate genes in 1205 AN cases and 1948 controls suggested a novel association of cholesterol metabolism influencing EPHX2 gene with susceptibility to AN.43

In recognition of the need for large-scale sample collections to empower GWAS, we established the Genetic Consortium for Anorexia Nervosa (GCAN) in 2007—a worldwide collaboration combining existing DNA samples of AN patients into a single resource. As part of the Wellcome Trust Case Control Consortium 3 (WTCCC3), we have conducted the largest GWAS for AN to date.

Materials and methods

Discovery data set

We conducted a GWAS across 15 discovery data sets, comprising a total of 2907 AN cases and 14 860 ancestrally matched controls of European origin (Table 1). All AN cases were female. Diagnostic determination was via semi-structured or structured interview or population assessment strategy based on DSM diagnostic criteria. Cases met DSM-IV criteria for lifetime AN (restricting or binge–purge subtype) or lifetime DSM-IV eating disorders ‘not otherwise specified’ AN-subtype (i.e., exhibiting the core features of AN). We did not require the presence of amenorrhea as this criterion does not increase diagnostic specificity.44,45 Given the frequency of diagnostic crossover, a lifetime history of bulimia nervosa was allowed.46 Exclusion criteria included the diagnosis of medical or psychiatric conditions that might have confounded the diagnosis of AN (e.g., psychotic disorders, mental retardation, or a medical or neurological condition causing weight loss). Controls were carefully selected to match for ancestry within each site and chosen primarily from existing GWAS genotypes through collaboration and genotyping repository (dbGAP) access. Each site obtained ethical approval from the local ethics committee, and all participants provided written informed consent in accordance with the Declaration of Helsinki.

Table 1 List of ethnicities and numbers of samples for main case control and anorexia nervosa (AN) subtype analyses across discovery and replication data sets

Genotyping, imputation and quality control

AN cases from the 15 sites were genotyped using Illumina 660 W-Quad arrays (Illumina Inc., San Diego, CA, USA) at the Wellcome Trust Sanger Institute. Funding was available only for genotyping AN cases. Thus, control genotypes were selected from existing data sets matched as closely as possible to the ancestry of cases and Illumina arrays as similar as possible to the 660 W array (Supplementary Table S1). Quality control (QC) of directly typed variants was performed within each of the 15 case-control data sets (Supplementary Table S2, Supplementary Information).

Phasing and imputation were performed separately for each of the 15 data sets using a common set of single nucleotide polymorphisms (SNPs) passing QC (Supplementary Table S2) using the program Impute2 v2.1.2 (Supplementary Information).47 The imputation reference panel was HapMap 3 release 2. We used all available HapMap3 populations for imputation as it was shown that the increase in the reference panel decreases error.48,49 Post-imputation filters were applied to remove SNPs with INFO scores <0.4 or with MAF <0.05. We observed high imputation accuracy (as captured by the INFO score) across a range of minor allele frequencies (Supplementary Figure S1). There was high concordance between directly genotyped variants with imputed dosages of the same variants after masking (Supplementary Figure S2).

Statistical analysis

Single-SNP association analyses were performed under an additive genetic model separately within each of the 15 data sets (Supplementary Information). We tested for association across the autosomes and the non-pseudoautosomal region of the X chromosome. Imputation and association analysis of the non-pseudoautosomal region of the chromosome X data were based on females (2907 AN cases and 10 594 controls). Association analyses were performed using SNPTEST v2.2.049 under an additive model and using a score test. To guard against false positives due to population stratification, we carried out association analysis within each data set and then combined the results using meta-analysis (for the French data set, the first principal component was added as a covariate). Fixed-effects meta-analyses were performed using GWAMA.50 All 15 discovery data sets were corrected for the genomic control inflation factor prior to performing meta-analysis (Supplementary Table S2; Supplementary Information).


We prioritized directly genotyped and imputed SNPs for replication based on statistical significance (P<104), robust QC metrics and vicinity to plausible candidate genes. In total, 96 SNPs (95 autosomal and one on chromosome X) in 66 genomic regions showed nominal evidence for association. We selected 72 independent, uncorrelated variants representing each of the 66 associated genomic regions and added 4 proxies for the most-associated SNPs resulting in 76 SNPs for replication. Cluster plots of all prioritized SNPs were examined using Evoker51 in cases and controls separately to minimize the possibility of spurious association due to genotyping error. We included 27 ancestry-informative markers (AIMs) for genotyping in the replication data sets, to guard against population stratification (Supplementary Information).52

Our replication data included 15 data sets—two existing in silico data sets and 13 data sets for de novo genotyping (Table 1). The in silico data set from the USA came from an existing GWAS of AN genotyped using the Illumina HumanHap610 platform (Illumina, San Diego, CA, USA)53 and the other in silico data set came from Estonian Genome Center (www.biobank.ee) and was genotyped using the Illumina OmniExpress array. De novo-genotyped samples included newly collected AN cases and controls from members of the GCAN and samples from the same sites as the discovery samples that had failed GWAS QC (including saliva and whole-genome amplified samples). De novo SNP genotyping was carried out using the iPLEX Gold Assay (Sequenom Inc., San Diego, CA, USA). SNPs with poor Sequenom design metrics were replaced with high-LD proxies. Sample and SNP QC were performed within each replication data set. QC included checking for sex inconsistencies and exclusions based on sample call rate <80%, SNP call rate <90% and exact Hardy–Weinberg Equilibrium, P<0.0001. In total, replication genotypes (in silico and de novo) of 76 prioritized SNPs and 27 AIMs were available from 2677 AN cases and 8629 controls of European ancestry and 458 AN cases and 421 controls from Japan.

Association analyses of prioritized SNPs were performed under an additive genetic model within each replication data set with and without adjustment for AIMs. AIMs that showed nominally significant P-values for allele frequency differences between de novo-typed cases and controls were used for conditional analysis (Supplementary Table S3). As there were no qualitative differences between these results, the main text reports the unadjusted results. The USA replication data set contained individuals who were related to individuals from the USA discovery data set. As such, those samples were excluded from the discovery data set and combined with replication USA samples to correctly account for relatedness between samples for the final global meta-analysis and sign test. Software packages GenABEL54 and GEMMA55 were used for replication analysis of the USA data set. Fixed-effects meta-analysis across the replication data sets was performed using GWAMA50 (with and without adjustment for AIMs and in samples of European ancestry only, i.e., excluding Japan, also with and without adjustment for AIMs). We also performed meta-analyses across the discovery and replication data sets, comprising a total of 5551 AN cases and 21 080 controls (USA discovery samples were included only once as part of the replication phase). We calculated the power of the final global meta-analysis using QUANTO.56

Seventy-two independent SNPs were used to compare the direction of effects between the discovery and replication meta-analyses using R.57 For this analysis, the USA samples were used only once as part of the replication meta-analysis.

Additional analyses

We performed three additional analyses: a genome-wide complex trait analysis designed to estimate the proportion of phenotypic variance explained by genome-wide SNPs for complex traits,58 a network analysis and a gene-based association test (Supplementary Information).

AN subtype analyses

Two subtype (Supplementary Information) association analyses were performed for the 76 prioritized SNPs across the discovery and replication data sets (Table 1). In total, the AN restricting subtype global meta-analysis included 1606 cases and the AN binge–purge subtype analysis included 1445 cases. Both analyses used the same set of 16 303 controls (Supplementary Information).

Related traits

Using the discovery meta-analysis, we investigated evidence for association using SNP results from published studies: 9 SNPs with nominal evidence of association with AN,42 14 SNPs suggestively associated with eating disorder-related symptoms, behaviors or personality traits,59,60 89 SNPs with genome-wide significance in studies of BMI or obesity,61,62 and 15 SNPs related to morbid obesity.61 We also investigated evidence for association across the 72 replication SNPs using published GWAS results from the Psychiatric Genomics Consortium (https://pgc.unc.edu) for attention-deficit hyperactivity disorder (ADHD), schizophrenia, bipolar disorder and major depressive disorder.63, 64, 65, 66

Expression studies

We prioritized the top 20 SNPs in terms of statistical significance and quantified the expression of the two nearest genes per SNP (Supplementary Table S4) in 12 inbred strains of mice. We obtained publicly available RNAseq data from whole-brain tissue samples and used standard software to map and count the sequence reads (Supplementary Information).


Main association results

Of 1 185 559 imputed SNPs that passed QC, 287 showed evidence for association in the discovery stage with P<10−4. These variants represented 66 independent signals and had frequencies and effect sizes commensurate with observations in other common complex diseases. One variant, not surrounded by other SNPs achieving low p-values and for which genotypes were only available in two of the 15 initial study groups, surpassed genome-wide significance (rs4957798, P=1.67 × 10−12) but was not subsequently replicated in the global meta-analysis across discovery and replication samples. The overall genomic control inflation factor was 1.03 (Supplementary Figures S3 and S4). Seventy-six SNPs (of which 72 were independent) were prioritized for follow-up through in silico and de novo replication (Supplementary Table S5). Nine SNPs showed association with P<0.05 (minimum p-value was 0.003) in the replication data set meta-analysis (binomial P=0.0135) (Supplementary Table S5). On the basis of 72 independent SNPs taken forward, we would expect 0.05 × 72=3.6 SNPs to reach P=0.05 by chance. The 0.0135 P-value reflects this enrichment in signal. No signals surpassed genome-wide significance (P=5 × 10−8) in the final global meta-analysis across all discovery and replication samples (Supplementary Table S5) or in the AN subtype analyses (Supplementary Tables S6-S7).

Of critical importance, we observed significant evidence of SNP effect sizes in the replication data in the same direction as the discovery set (55/72 signals, sign test binomial P=4 × 10−6). This enrichment was also observed for the AN restricting (58/72, P=8 × 10−8) and binge–purge (56/72, P=1 × 10−6) subtype analyses. These results strongly indicate that the prioritized set of variants is likely to contain true positive signals for AN but that the current sample size is insufficient to detect these effects.

Our analysis revealed two notable variants: rs9839776 (P=3.01 × 107) in SOX2OT (SOX2 overlapping transcript) and rs17030795 (P=5.84 × 10−6) in PPP3CA (protein phosphatase 3, catalytic subunit, alpha isozyme) (Table 2). Two additional signals emerged from the analysis focused on European replication samples only: rs1523921 (P=5.76 × 106) located between CUL3 (cullin 3) and FAM124B (family with sequence similarity 124B) and rs1886797 (P=8.05 × 10−6) located 18 kb from SPATA13 (spermatogenesis associated 13) (Supplementary Table S5). Four signals were in neurodevelopmental genes regulating synapse and neuronal network formation (SYN2, NCAM2, CNTNAP2 and CTNNA2; Table 2).

Table 2 Global meta-analysis results of SNPs with the greatest evidence of association for the main anorexia nervosa (AN) case-control analysis

AN subtype analyses

In the AN restricting subtype analyses, the two most significant signals were rs1523921 (as in the main analysis, P=8.39 × 10−5) and rs10777211 (P=8.95 × 10−5) located 333 kb from ATP2B1 (ATPase, calcium transporting, plasma membrane 1), both detected in the European-only analysis (Supplementary Table S6). The most significant result for AN binge–purge analysis was rs9839776 (as in the main analysis, P=3.97 × 104) in SOX2OT, also in Europeans only (Supplementary Table S7). Overall, signals from the main AN case-control analysis display similar levels of association across both AN subtypes (Supplementary Table S8).

Additional analyses

Genome-wide complex trait analysis is technically challenging when synthesizing data across multiple strata with small individual sample sizes. When we applied it to our data, we saw great variability in the estimates of variance and did not judge the results reliable. Results of the gene-based association test and network analysis are presented in their entirety in Supplementary Information and Supplementary Figure S5, both of which were unremarkable.

Related traits

Nine out of the 11 previously reported variants suggestively associated with AN42 were found in our discovery meta-analysis, and six of these nine SNPs had the same direction of effect as originally reported (P=0.508) (Supplementary Table S9). Twelve out of 14 variants previously reported to be associated with eating disorder-related symptoms, behaviors and personality traits59,60 were found in our discovery meta-analysis and seven had the same direction of effect (P=0.774) (Supplementary Table S10), with one SNP (inside RUFY1) having P<0.05 (binomial P=0.459). We did not find evidence for signal enrichment in the 60 independent SNPs found in the Psychiatric Genomics Consortium data for ADHD, schizophrenia, bipolar disorder or major depressive disorder63, 64, 65, 66 (Supplementary Table S11).

When we compared 76 (53 independent) SNPs from the AN results with 89 established BMI/obesity SNPs,61,62 five SNPs (inside NEGR1, PTBP2, TMEM18, FTO and MC4R) had P<0.05 (binomial P=0.1906). Twenty-six of these 53 SNPs had the same direction of effect as originally reported (binomial P-value=1) (Supplementary Table S12). Thirteen of 15 SNPs associated with extreme obesity were extracted from our data set and nine of these were independent. Four of these nine SNPs had the same direction of effect as originally reported (binomial P-value=1) (Supplementary Table S13). Three SNPs (in TMEM18, FTO and MC4R) had P<0.05 (binomial P-value=0.0084), indicating modest enrichment of nominally associated SNPs from extreme obesity in our discovery data set.

Expression studies

We analyzed RNAseq data for whole-brain tissue obtained from 12 different mouse strains (Figure 1). We performed this analysis for 32 mouse orthologs of the 34 human genes identified (Supplementary Table S4). All 32 genes were expressed in the brain, above an average of two FPKM (Fragments Per Kilobase of exon per Million fragments mapped). Specifically, we found extremely high expression levels for Ppp3ca (FPKM value 36.40). Further, we found high expression for Sox2ot, with an FPKM value of 8.02, and similar expression values for Cul3 (10.01) and Ctnna2 (10.79).

Figure 1

Analysis of RNAseq data for whole-brain tissue obtained from 12 different mouse strains for 32 mouse orthologs of the 34 human genes for which association to anorexia nervosa (AN) was identified. The average FPKM (Fragments Per Kilobase of exon per Million fragments mapped) values for 32 genes across 12 mouse strains are shown.

PowerPoint slide


Given that the evidence base for the treatment of AN remains weak and that no effective medications for its treatment exist,20,67 advances in our understanding of the underlying biology of the disorder are essential in order to develop novel therapeutics and to reduce the loss of life and diminution of quality of life associated with the disorder. The GCAN/WTCCC3 investigation represents an unprecedented international genetic collaboration in the study of AN, which sets the foundation for further genetic studies.

Our final global meta-analysis had 80% power to detect SNPs with allele frequency of 0.35 and genotypic relative risk of 1.15 (α=5 × 10−8, additive model).68 The AN subtype meta-analysis had 80% power to detect SNPs with allele frequency of 0.35 and genotypic relative risk 1.27 for the AN restricting subtype and 1.28 for the AN binge–purge subtype. Given these limitations in power, our strongest indicator that larger sample sizes could detect genetic variants associated with AN was revealed in the sign tests. The strong and significant evidence for SNP effect sizes in the same direction between discovery and replication sets (P=4 × 10−6) clearly suggests that larger sample sizes could successfully identify variants associated with AN and with the AN subtypes potentially enabling differentiation on a genetic level between restricting and binge–purge subtypes.

Several genetic variants were suggestively associated with AN (P<10−5) (Table 2). Two variants, rs9839776 in SOX2OT and rs17030795 in PPP3CA, were identified through analysis of all discovery and replication data sets. Two additional variants with P<10−5, rs1523921 located between CUL3 and FAM124B and rs1886797 located near SPATA13, were identified through analysis of individuals of European descent only (Supplementary Table S5), suggesting either heterogeneity in the effects of these SNPs by ancestry or low power. The genes displayed in Table 2 are discussed in greater detail in the Supplementary Information; however, we highlight that four of these variants are neurodevelopmental genes that regulate synapse and neuronal network formation (SYN2, NCAM2, CNTNAP2 and CTNNA2) and two have been associated with Alzheimer’s disease (SOX2OT and PPP3CA). In addition, one of our prioritized SNPs (rs6558000) (Supplementary Table S5) is located in close vicinity (9 kb upstream) of the EPHX2 gene that was recently identified as a susceptibility locus to AN through candidate gene sequencing study of early-onset severe AN cases and controls.43

Our expression studies further extend the GWAS findings. It is reasonable, although perhaps not essential, to expect that genes implicated in AN be expressed in the brain. Supporting this assumption, 32 mouse orthologs of 34 human genes identified as being of interest were expressed at least at a low level in mouse brain. Moreover, genes corresponding to the more strongly associated genetic variants tended to be more highly expressed. For example, high FPKM values for Ppp3ca, Cul3 and Sox2ot underscore that these genes may have a neuropsychiatric role.

AN subtype analyses were included to determine whether differences might exist between the classic restricting subtype of AN and the subtype marked by dysregulation characterized by binge eating and/or purging behavior. These analyses had lower power due to the smaller sample sizes. Only two SNPs, rs1523921 (also found to be suggestively associated in the main case-control analysis) and rs10777211 located 333 kb upstream of ATP2B1, showed association at the 10−5 significance level (Supplementary Table S6). Similarly, subsequent analyses pertaining to associated phenotypes (weight regulation: BMI/obesity loci,40,61,69,70 and loci for extreme obesity;61,71,72 psychiatric comorbidities: ADHD, schizophrenia, bipolar disorder and major depressive disorder) or previous equivocal association findings for AN or eating disorders (AN variants,42 eating disorder-related symptoms, behaviors and personality trait variants59,60) did not reveal significant findings. More adequately powered analyses that could allow us to detect variants that can distinguish between these two subtypes could be clinically meaningful in predicting clinical course and outcome and eventually in designing targeted therapeutics.

Our understanding of the fundamental genetic architectures of complex medical diseases and psychiatric disorders has expanded rapidly.73 It has also become manifestly clear that genomic searches for common variation via GWAS can successfully uncover biological pathways of etiological relevance. The major limitation to discovery is sample size.74 A recent GWAS for schizophrenia reported the identification of 22 genome-wide significant loci for schizophrenia (21 000 cases and 38 000 controls), and the results yielded multiple themes of clear biological and translational significance (e.g., calcium biology and miR-137 regulation).75 Moreover, given that cases and controls were derived from multiple sources and genotyped on multiple platforms, imputation was essential. Although effective, the preferred approach will always be to have samples genotyped on the same platform to maximize comparability and the capacity to identify genomic associations.

Although the underlying biology of AN remains incompletely understood, the relative homogeneity of the phenotype, replicated heritability estimates and encouraging results of the sign tests presented herein strongly encourage continuing this path of discovery. Phenotypic refinement and the identification of biomarkers of illness (independent of biomarkers of starvation) could assist with identification of risk loci. We believe that the surest and fastest path to fundamental etiological knowledge about the biological basis of AN is via GWAS in larger samples.74 This path is notably safe given that it relies on off-the-shelf technology whose utility has been proven in empirical results for multiple biomedical and psychiatric disorders. This approach is cost-effective due to recent sharp decreases in genotyping pricing. Therefore, we believe that accrual of large genotyped AN case-control samples should be an immediate priority for the field.


  1. 1

    Klump KL, Bulik CM, Kaye WH, Treasure J, Tyson E . Academy for Eating Disorders position paper: eating disorders are serious mental illnesses. Int J Eat Disord 2009; 42: 97–103.

    Article  Google Scholar 

  2. 2

    Hudson JI, Hiripi E, Pope HG Jr, Kessler RC . The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication. Biol Psychiatry 2007; 61: 348–358.

    Article  Google Scholar 

  3. 3

    Hoek H, van Hoeken D . Review of the prevalence and incidence of eating disorders. Int J Eat Disord 2003; 34: 383–396.

    Article  Google Scholar 

  4. 4

    American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. Fourth Edition. Text Revision American Psychiatric Press: Washington, DC, USA, 2000.

  5. 5

    Lucas AR, Beard CM, O'Fallon WM, Kurland LT . 50-year trends in the incidence of anorexia nervosa in Rochester, Minn.: a population-based study. Am J Psychiatry 1991; 148: 917–922.

    CAS  Article  Google Scholar 

  6. 6

    Nicholls DE, Lynn R, Viner RM . Childhood eating disorders: British National Surveillance Study. Br J Psychiatry 2011; 198: 295–301.

    Article  Google Scholar 

  7. 7

    Bueno B, Krug I, Bulik CM, Jiménez-Murcia S, Granero R, Thornton L et al. Late onset eating disorders in Spain: clinical characteristics and therapeutic implications. J Clin Psychol 2014, 70: 1–17.

    CAS  Article  Google Scholar 

  8. 8

    Katzman D . Medical complications in adolescents with anorexia nervosa: a review of the literature. Int J Eat Disord 2005; 37: S52–S59.

    Article  Google Scholar 

  9. 9

    Sharp C, Freeman C . The medical complications of anorexia nervosa. Br J Psychiatry 1993; 162: 452–462.

    CAS  Article  Google Scholar 

  10. 10

    Kaye W, Bulik C, Thornton L, Barbarich BS, Masters K Price Foundation Collaborative Group. Comorbidity of anxiety disorders with anorexia and bulimia nervosa. Am J Psychiatry 2004; 161: 2215–2221.

    Article  Google Scholar 

  11. 11

    Godart N, Flament M, Perdereau F, Jeammet P . Comorbidity between eating disorders and anxiety disorders: a review. Int J Eat Disord 2002; 32: 253–270.

    CAS  Article  Google Scholar 

  12. 12

    Fernandez-Aranda F, Pinheiro AP, Tozzi F, Thornton LM, Fichter MM, Halmi KA et al. Symptom profile of major depressive disorder in women with eating disorders. Aust N Z J Psychiatry 2007; 41: 24–31.

    Article  Google Scholar 

  13. 13

    Berkman ND, Lohr KN, Bulik CM . Outcomes of eating disorders: a systematic review of the literature. Int J Eat Disord 2007; 40: 293–309.

    Article  Google Scholar 

  14. 14

    Mathers CD, Vos ET, Stevenson CE, Begg SJ . The Australian Burden of Disease Study: measuring the loss of health from diseases, injuries and risk factors. Med J Aust 2000; 172: 592–596.

    CAS  PubMed  Google Scholar 

  15. 15

    Sullivan PF . Mortality in anorexia nervosa. Am J Psychiatry 1995; 152: 1073–1074.

    CAS  Article  Google Scholar 

  16. 16

    Arcelus J, Mitchell AJ, Wales J, Nielsen S . Mortality rates in patients with anorexia nervosa and other eating disorders. A meta-analysis of 36 studies. Arch Gen Psychiatry 2011; 68: 724–731.

    Article  Google Scholar 

  17. 17

    Birmingham C, Su J, Hlynsky J, Goldner E, Gao M . The mortality rate from anorexia nervosa. Int J Eat Disord 2005; 38: 143–146.

    Article  Google Scholar 

  18. 18

    Millar HR, Wardell F, Vyvyan JP, Naji SA, Prescott GJ, Eagles JM . Anorexia nervosa mortality in Northeast Scotland, 1965-1999. Am J Psychiatry 2005; 162: 753–757.

    Article  Google Scholar 

  19. 19

    Zipfel S, Lowe B, Reas DL, Deter HC, Herzog W . Long-term prognosis in anorexia nervosa: lessons from a 21-year follow-up study. Lancet 2000; 355: 721–722.

    CAS  Article  Google Scholar 

  20. 20

    Bulik CM, Berkman ND, Brownley KA, Sedway JA, Lohr KN . Anorexia nervosa treatment: a systematic review of randomized controlled trials. Int J Eat Disord 2007; 40: 310–320.

    Article  Google Scholar 

  21. 21

    Eating Disorders: Core Interventions in the Treatment and Management of Anorexia Nervosa, Bulimia Nervosa and Related Eating Disorders. http://www.nice.org.uk/page.aspx?o=1012392004, Accessed 15 November 2013.

  22. 22

    McKenzie JM, Joyce PR . Hospitalization for anorexia nervosa. Int J Eat Disord 1992; 11: 235–241.

    Article  Google Scholar 

  23. 23

    Krauth C, Buser K, Vogel H . How high are the costs of eating disorders - anorexia nervosa and bulimia nervosa - for German society? Eur J Health Econ 2002; 3: 244–250.

    CAS  Article  Google Scholar 

  24. 24

    Striegel-Moore RH, Bulik CM . Risk factors for eating disorders. Am Psychol 2007; 62: 181–198.

    Article  Google Scholar 

  25. 25

    Kas M, Kaye W, Mathes W, Bulik C . Interspecies genetics of eating disorders traits. Am J Med Genet B Neuropsychiatr Genet 2009; 150B: 318–327.

    CAS  Article  Google Scholar 

  26. 26

    Strober M, Freeman R, Lampert C, Diamond J, Kaye W . Controlled family study of anorexia nervosa and bulimia nervosa: evidence of shared liability and transmission of partial syndromes. Am J Psychiatry 2000; 157: 393–401.

    CAS  Article  Google Scholar 

  27. 27

    Lilenfeld L, Kaye W, Greeno C, Merikangas K, Plotnikov K, Pollice C et al. A controlled family study of restricting anorexia and bulimia nervosa: comorbidity in probands and disorders in first-degree relatives. Arch Gen Psychiatry 1998; 55: 603–610.

    CAS  Article  Google Scholar 

  28. 28

    Bulik C, Sullivan P, Tozzi F, Furberg H, Lichtenstein P, Pedersen N . Prevalence, heritability and prospective risk factors for anorexia nervosa. Arch Gen Psychiatry 2006; 63: 305–312.

    Article  Google Scholar 

  29. 29

    Klump KL, Miller KB, Keel PK, McGue M, Iacono WG . Genetic and environmental influences on anorexia nervosa syndromes in a population-based twin sample. Psychol Med 2001; 31: 737–740.

    CAS  Article  Google Scholar 

  30. 30

    Wade TD, Bulik CM, Neale M, Kendler KS . Anorexia nervosa and major depression: shared genetic and environmental risk factors. Am J Psychiatry 2000; 157: 469–471.

    CAS  Article  Google Scholar 

  31. 31

    Kortegaard LS, Hoerder K, Joergensen J, Gillberg C, Kyvik KO . A preliminary population-based twin study of self-reported eating disorder. Psychol Med 2001; 31: 361–365.

    CAS  Article  Google Scholar 

  32. 32

    Bulik CM, Thornton LM, Root TL, Pisetsky EM, Lichtenstein P, Pedersen NL . Understanding the relation between anorexia nervosa and bulimia nervosa in a Swedish national twin sample. Biol Psychiatry 2010; 67: 71–77.

    Article  Google Scholar 

  33. 33

    Grice DE, Halmi KA, Fichter MM, Strober M, Woodside DB, Treasure JT et al. Evidence for a susceptibility gene for anorexia nervosa on chromosome 1. Am J Hum Genet 2002; 70: 787–792.

    CAS  Article  Google Scholar 

  34. 34

    Devlin B, Bacanu S, Klump K, Bulik C, Fichter M, Halmi K et al. Linkage analysis of anorexia nervosa incorporating behavioral covariates. Hum Mol Genet 2002; 11: 689–696.

    CAS  Article  Google Scholar 

  35. 35

    Bacanu S, Bulik C, Klump K, Fichter M, Halmi K, Keel P . Linkage analysis of anorexia and bulimia nervosa cohorts using selected behavioral phenotypes as quantitative traits or covariates. Am J Med Genet B Neuropsychiatr Genet 2005; 139: 61–68.

    Article  Google Scholar 

  36. 36

    Slof-Op 't Landt M, van Furth E, Meulenbelt I, Slagboom P, Bartels M, Boomsma D et al. Eating disorders: From twin studies to candidate genes and beyond. Twin Res Hum Genet 2005; 16: 467–482.

    Article  Google Scholar 

  37. 37

    Bulik CM, Slof-Op't Landt MC, van Furth EF, Sullivan PF . The genetics of anorexia nervosa. Ann Rev Nutr 2007; 27: 263–275.

    CAS  Article  Google Scholar 

  38. 38

    Hinney A, Scherag S, Hebebrand J . Genetic findings in anorexia and bulimia nervosa. Prog Mol Biol Transl Sci 2010; 94: 241–270.

    CAS  Article  Google Scholar 

  39. 39

    Hebebrand J, Remschmidt H . Anorexia nervosa viewed as an extreme weight condition: genetic implications. Hum Genet 1995; 95: 1–11.

    CAS  Article  Google Scholar 

  40. 40

    Muller TD, Greene BH, Bellodi L, Cavallini MC, Cellini E, Di Bella D et al. Fat mass and obesity-associated gene (FTO) in eating disorders: evidence for association of the rs9939609 obesity risk allele with bulimia nervosa and anorexia nervosa. Obes Facts 2012; 5: 408–419.

    Article  Google Scholar 

  41. 41

    Nakabayashi K, Komaki G, Tajima A, Ando T, Ishikawa M, Nomoto J et al. Identification of novel candidate loci for anorexia nervosa at 1q41 and 11q22 in Japanese by a genome-wide association analysis with microsatellite markers. J Hum Genet 2009; 54: 531–537.

    CAS  Article  Google Scholar 

  42. 42

    Wang K, Zhang H, Bloss CS, Duvvuri V, Kaye W, Schork NJ et al. A genome-wide association study on common SNPs and rare CNVs in anorexia nervosa. Mol Psychiatry 2011; 16: 949–959.

    CAS  Article  Google Scholar 

  43. 43

    Scott-Van Zeeland AA, Bloss CS, Tewhey R, Bansal V, Torkamani A, Libiger O et al. Evidence for the role of EPHX2 gene variants in anorexia nervosa. Mol Psychiatry 2013.

  44. 44

    Gendall K, Joyce P, Carter F, McIntosh V, Jordan J, Bulik C . The psychobiology and diagnostic significance of amenorrhea in patients with anorexia nervosa. Fertil Steril 2006; 85: 1531–1535.

    Article  Google Scholar 

  45. 45

    Pinheiro A, Thornton L, Plotonicov K, Tozzi T, Klump K, Berrettini W et al. Patterns of menstrual disturbance in eating disorders. Int J Eat Disord 2007; 40: 424–434.

    Article  Google Scholar 

  46. 46

    Tozzi F, Thornton L, Klump K, Bulik C, Fichter M, Halmi K et al. Symptom fluctuation in eating disorders: correlates of diagnostic crossover. Am J Psychiatry 2005; 162: 732–740.

    Article  Google Scholar 

  47. 47

    Howie BN, Donnelly P, Marchini J . A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 2009; 5: e1000529.

    Article  Google Scholar 

  48. 48

    Altshuler DM, Gibbs RA, Peltonen L, Dermitzakis E, Schaffner SF, Yu F et al. Integrating common and rare genetic variation in diverse human populations. Nature 2010; 467: 52–58.

    CAS  Article  Google Scholar 

  49. 49

    Marchini J, Howie B . Genotype imputation for genome-wide association studies. Nat Rev Genet 2010; 11: 499–511.

    CAS  Article  Google Scholar 

  50. 50

    Magi R, Morris AP . GWAMA: software for genome-wide association meta-analysis. BMC Bioinformatics 2010; 11: 288.

    Article  Google Scholar 

  51. 51

    Morris JA, Randall JC, Maller JB, Barrett JC . Evoker: a visualization tool for genotype intensity data. Bioinformatics 2010; 26: 1786–1787.

    CAS  Article  Google Scholar 

  52. 52

    Huckins L, Boraska V, Franklin C, Floyd J, Southam L, Genetic Consortium for Anorexia Nervosa et al. Using ancestry-informative markers to identify fine structure across 15 populations of European origin. Eur J Hum Genet (in press).

  53. 53

    Wang K, Zhang H, Bloss CS, Duvvuri V, Kaye W, Schork NJ et al. Price Foundation Collaborative Group A genome-wide association study on common SNPs and rare CNVs in anorexia nervosa. Mol Psychiatry 2011; 16: 949–959.

    CAS  Article  Google Scholar 

  54. 54

    Aulchenko YS, Ripke S, Isaacs A, van Duijn CM . GenABEL: an R library for genome-wide association analysis. Bioinformatics 2007; 23: 1294–1296.

    CAS  Article  Google Scholar 

  55. 55

    Zhou X, Stephens M . Genome-wide efficient mixed-model analysis for association studies. Nat Genet 2012; 44: 821–824.

    CAS  Article  Google Scholar 

  56. 56

    Gauderman WJ . Candidate gene association analysis for a quantitative trait, using parent-offspring trios. Genet Epidemiol 2003; 25: 327–338.

    Article  Google Scholar 

  57. 57

    R: A language and environment for statistical computing.. http://www.R-project.org. 2008.

  58. 58

    Yang J, Lee SH, Goddard ME, Visscher PM . GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet 2011; 88: 76–82.

    CAS  Article  Google Scholar 

  59. 59

    Boraska V, Davis OS, Cherkas LF, Helder SG, Harris J, Krug I et al. Genome-wide association analysis of eating disorder-related symptoms, behaviors, and personality traits. Am J Med Genet B Neuropsychiatr Genet 2012; 159B: 803–811.

    Article  Google Scholar 

  60. 60

    Wade T, Gordon S, Medland S, Bulik CM, Heath A, Montgomery GW et al. Genetic variants associated with disordered eating. Int J Eat Disord 2013; 46: 594–608.

    Article  Google Scholar 

  61. 61

    Fall T, Ingelsson E . Genome-wide association studies of obesity and metabolic syndrome. Mol Cell Endocrinol 2014; 382 (): 740–757.

    CAS  Article  Google Scholar 

  62. 62

    Guo Y, Lanktree MB, Taylor KC, Hakonarson H, Lange LA, Keating BJ . Gene-centric meta-analyses of 108 912 individuals confirm known body mass index loci and reveal three novel signals. Hum Mol Genet 2013; 22: 184–201.

    CAS  Article  Google Scholar 

  63. 63

    Neale BM, Medland SE, Ripke S, Asherson P, Franke B, Lesch KP et al. Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry 2010; 49: 884–897.

    Article  Google Scholar 

  64. 64

    Sklar P, Ripke S, Scott LJ, Andreassen OA, Cichon S, Craddock N et al. Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nat Genet 2011; 43: 977–983.

    CAS  Article  Google Scholar 

  65. 65

    Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium Genome-wide association study identifies five new schizophrenia loci. Nat Genet 2011; 43: 969–976.

    Article  Google Scholar 

  66. 66

    Ripke S, Wray NR, Lewis CM, Hamilton SP, Weissman MM, Breen G et al. A mega-analysis of genome-wide association studies for major depressive disorder. Molecular psychiatry 2013; 18: 497–511.

    CAS  Article  Google Scholar 

  67. 67

    Watson HJ, Bulik CM . Update on the treatment of anorexia nervosa: review of clinical trials, practice guidelines and emerging interventions. Psychol Med 2012; 43 (): 2477–2500.

    Article  Google Scholar 

  68. 68

    Gauderman WJ . Sample size requirements for association studies of gene-gene interaction. Am J Epidemiol 2002; 155: 478–484.

    Article  Google Scholar 

  69. 69

    Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 2010; 42: 937–948.

    CAS  Article  Google Scholar 

  70. 70

    Hinney A, Hebebrand J . Three at one swoop! Obes Facts 2009; 2: 3–8.

    Article  Google Scholar 

  71. 71

    Bradfield JP, Taal HR, Timpson NJ, Scherag A, Lecoeur C, Warrington NM et al. A genome-wide association meta-analysis identifies new childhood obesity loci. Nat Genet 2012; 44: 526–531.

    CAS  Article  Google Scholar 

  72. 72

    Scherag A, Dina C, Hinney A, Vatin V, Scherag S, Vogel CI et al. Two new loci for body-weight regulation identified in a joint analysis of genome-wide association studies for early-onset extreme obesity in French and German study groups. PLoS Genet 2010; 6: e1000916.

    Article  Google Scholar 

  73. 73

    Visscher PM, Brown MA, McCarthy MI, Yang J . Five years of GWAS discovery. Am J Hum Genet 2012; 90: 7–24.

    CAS  Article  Google Scholar 

  74. 74

    Sullivan PF, Daly MJ, O'Donovan M . Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat Rev Genet 2012; 13: 537–551.

    CAS  Article  Google Scholar 

  75. 75

    Ripke S, O'Dushlaine C, Chambert K, Moran J, Kähler A, Akterin S et al. Genome-wide association analysis identifies 13 new risk loci for schizophrenia. Nat Genet 2013; 45: 1150–1159.

    CAS  Article  Google Scholar 

Download references



This work was funded by a grant from the WTCCC3 WT088827/Z/09 entitled ‘A genomewide association study of anorexia nervosa’.


1 This work was supported by the WellcomeTrust (098051).

2 Eleftheria Zeggini is supported by the Wellcome Trust (098051).

3 Vesna Boraska is supported by Unity Through Knowledge Fund CONNECTIVITY PROGRAM (‘Gaining Experience’ Grant 2A), The National Foundation for Science, Higher Education and Technological Development of the Republic of Croatia (BRAIN GAIN- Postdoc fellowship) and the Wellcome Trust (098051).

4 Christopher S Franklin is supported by the WTCCC3 project, which is supported by the Wellcome Trust (WT090355/A/09/Z, WT090355/B/09/Z).

5 James A B Floyd is supported by the WTCCC3 project, which is supported by the Wellcome Trust (WT090355/A/09/Z, WT090355/B/09/Z).

6 Lorraine Southam is supported by the Wellcome Trust (098051).

7 William N Rayner is supported by the Wellcome Trust (098051).

8 The Wellcome Trust Case Control Consortium 3 project is supported by the Wellcome Trust (WT090355/A/09/Z, WT090355/B/09/Z).

9 We acknowledge use of data from the British 1958 Birth Cohort and the UK National Blood Service.

10 We obtained High Density SNP Association Analysis of Melanoma: Case-Control and Outcomes Investigation data set through dbGaP (dbGaP Study Accession: phs000187.v1.p1). Research support to collect data and develop an application to support this project was provided by 3P50CA093459, 5P50CA097007, 5R01ES011740 and 5R01CA133996.

11 Laura Huckins acknowledges Wellcome Trust (098051) and the MRC (MR/J500355/1) and Ximena Ibarra-Soria for advice on RNA-seq analysis.


Austria, Medical University of Vienna: The study was partly supported by the European Commission, Framework 5 research program, Integrated Project QLK1-CT-1999-00916 ‘Factors in Healthy Eating’ given to the consortium lead by Professor J Treasure and Professor D Collier, London. We thank Gerald Nobis, Dr Maria Haidvogl and Dr Julia Philipp for help with data collection and interview work.

Canada, Canadian Institutes of Health Research (CIHR): Zeynep Yilmaz was supported by a CIHR Doctoral Research Award (Genetic Determinants of Low Body Weight in Anorexia Nervosa; funding reference: GSD-111968). The Toronto authors thank Sajid Shaikh, Maria Tampakeras and Natalie Freeman for DNA preparation and laboratory support.

Canada, The Ontario Mental Health Foundation (OMHF): The collection of the Toronto DNA samples was supported by a grant from the OMHF, awarded to Allan S Kaplan and Robert D Levitan (Polymorphism in Serotonin System Genes: Putative Role in Increased Eating Behaviour in Seasonal Affective Disorder and Bulimia Nervosa).

Czech Republic, Charles University: The study was supported by Grants IGA MZ ČR NS/10045-4 and IGA NT 14094/3 from the Czech Ministry of Education and Health and PRVOUK P24/LF1/3 and P26/LF1/4 Charles University, Prague, and from the Marie Curie Research Training Network INTACT (MRTN-CT-2006-035988).

Finland, University of Helsinki: Academy of Finland Center of Excellence in Complex Disease Genetics (Grant numbers: 213506, 129680), ENGAGE—European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, Grant agreement number 201413. Data collection in the Finnish Twin studies has been supported by the National Institute of Alcohol Abuse and Alcoholism (Grants AA-12502, AA-00145 and AA-09203 to RJ Rose and AA15416 and K02AA018755 to DM Dick), the Academy of Finland (Grants 100499, 205585, 118555 and 141054, 265240 and 264146 to JK). AR and LK were supported by the Academy of Finland, Grants 259764 and 28327, respectively.

France, Institut National de la Santé et de la Recherche Médicale (INSERM), France: This French cohort was recruited with grants from EC Framework V ‘Factors in Healthy Eating’ (a consortium coordinated by Janet Treasure and David Collier, King’s College London), and from INRA/INSERM (4M406D), and the participation of Audrey Versini’s work was supported by grants from ‘Région Ile-de-France’. Cases were ascertained from Sainte-Anne Hospital (Paris) and Robert Debre Hospital (Paris).

Genetics of Anorexia Nervosa (GAN), National Institute of Mental Health: The data and collection of biomaterials for the GAN study have been supported by the National Institutes of Health Grants (MH066122, MH066117, MH066145, MH066296, MH066147, MH0662, MH066193, MH066287, MH066288 and MH066146). The principal investigators and co-investigators of this study were University of Pittsburgh, Pittsburgh, PA: Walter Kaye, M.D., Bernie Devlin, Ph.D.; University of North Carolina at Chapel Hill, Chapel Hill, NC: Cynthia M Bulik, Ph.D.; Roseneck Hospital for Behavioral Medicine, Prien and Department of Psychiatry, University of Munich, Germany: Manfred M Fichter, M.D.; Kings College London, Institute of Psychiatry, London, UK: Janet Treasure, M.D.; Toronto General Hospital, Toronto, Ontario, Canada: Allan Kaplan, M.D., D. Blake Woodside, M.D.; Laureate Psychiatric Hospital, Tulsa, OK: Craig L. Johnson, Ph. D.; Weill Cornell Medical College, White Plains, NY: Katherine Halmi, M.D.; Sheppard Pratt Health System, Towson: Harry A. Brandt, M.D., Steve Crawford, M.D.; Neuropsychiatric Research Institute, Fargo, ND; James E. Mitchell, M.D.; University of California at Los Angeles, Los Angeles, CA: Michael Strober, Ph.D.; University of Pennsylvania, Philadelphia, PA: Wade Berrettini, M.D., Ph.D.; and University of Birmingham, England: Ian Jones, M.D. We are indebted to the participating families for their contribution of time and effort in support of this study. We thank the Price Foundation for sponsoring the earlier work of this collaboration and also thank the study managers and clinical interviewers for their efforts in participant screening and clinical assessments.

Germany, University of Duisburg-Essen: Sample collection was funded by grants from the German Federal Ministry of Education and Research (BMBF; EDNET 01GV0602, 01GV0624, 01GV0623 and 01GV0905, NGFNplus: 01GS0820) and the IFORES program of the University of Duisburg-Essen. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Germany, Professor Ehrlich’s work is supported by DFG Grant EH 367/5-1 and the SFB 940.

GlaxoSmithKline (GSK), Leeds (Yorkshire Centre for Eating Disorders): We acknowledge the support of the Medical Research Council and GlaxoSmithKline for providing financial support of this project. The support of the Carnegie Trust in the form of a travel award is also acknowledged. We also acknowledge the help and support of the Discovery and Pipeline Genetics, and Translational Medicine and Genetics departments at GSK for their contributions to this study. In particular, they also acknowledge Mike Stubbins, Julia Perry, Sarah Bujac, David Campbell (at GSK currently or at the time when the study was performed), John Blundell (Leeds University) and Evleen Mann (Yorkshire Centre for Eating Disorders), for their fundamental contribution to the realization of this study.

Greece, Eating Disorders Unit, 1st Department of Psychiatry, Athens University, Medical School. Special thanks goes to Associate Professor Varsou E, Head of Eating Disorders Unit, and Professor Papadimitriou G, Chairman and Director of 1st Department of Psychiatry, Athens University, Medical School, for their advice and support.

Italy, Padua (BIOVEDA): BIOVEDA was funded thanks to a Grant of Veneto Region in 2009. Samples were collected at Padua, Verona, Treviso, Vicenza and Portogruaro hospitals.

Netherlands, Department of Translational Neuroscience, The Rudolf Magnus Institute of Neuroscience, University Medical Center, Utrecht and Rintveld, Center for Eating Disorders, Altrecht in Zeist: Marek K. Brandys was supported by funding from the Marie Curie Research Training Network INTACT (Individually tailored stepped care for women with eating disorders; reference number: MRTN-CT-2006-035988). Martien Kas was supported by a ZonMW VIDI-Grant (91786327) from The Netherlands Organization for Scientific Research (NWO).

Norway, The National Institute of Public Health Twin Panel (NIPHTP): The NIPHTP was supported in part by grants from The Norwegian Research Council, The Norwegian Foundation for Health and Rehabilitation, The Norwegian Council for Mental Health and The European Commission under the program ‘Quality of Life and Management of the Living Resources’ of 5th Framework Program (no. QLG2-CT-2002-01254).

Poland, Poznan University of Medical Sciences (PUMS): PUMS study was sponsored by KBN scientific Grant no. PO5B 12823

Spain, Center for Genomic Regulation (CRG), Barcelona. Spanish Plan Nacional SAF2008-00357 (NOVADIS); the Generalitat de Catalunya AGAUR 2009 SGR-1502; the Instituto de Salud Carlos III (FIS/FEDER PI11/00733); and the European Commission 7th Framework Program, Project N. 261123 (GEUVADIS), and Project N. 262055 (ESGI).

Spain, Department of Psychiatry University Hospital of Bellvitge-IDIBELL, Barcelona: Financial support was received from Fondo de Investigación Sanitaria—FIS (PI11/210) and AGAUR (2009SGR1554). CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn) is an initiative of ISCIII.

Sweden, Karolinska Institutet, Stockholm: The Swedish Twin Registry is supported by the Swedish Department of Higher Education. The STR was supported by grants from the Ministry for Higher Education, the Swedish Research Council (M-2005-1112 and 2009-2298), GenomEUtwin (EU/QLRT-2001-01254; QLG2-CT-2002-01254), NIH Grant DK U01-066134, The Swedish Foundation for Strategic Research (SSF; ICA08-0047), the Swedish Heart-Lung Foundation, the Royal Swedish Academy of Science, and ENGAGE (within the European Union Seventh Framework Programme, HEALTH-F4-2007-201413).

United Kingdom, King’s College London: Financial support was received from the European Union (Framework-V Multicentre Research Grant, QLK1–1999-916), a Multicentre EU Marie Curie Research Training Network Grant, INTACT (MRTN-CT-2006-035988) and a Marie-Curie Intra-European Fellowship (FP-7-People-2009-IEF, No. 254774). Oliver Davis is supported by a Sir Henry Wellcome Fellowship from the Wellcome Trust (WT088984). Cathryn Lewis is partly supported by the National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health at South London and Maudsley NHS Foundation Trust and Institute of Psychiatry, King’s College London.

United States, McLean Hospital/Harvard Medical School, Cambridge, MA: The collection of DNA from participants at the McLean Hospital/Harvard Medical School site was supported in part by an investigator-initiated grant from Ortho-McNeil Janssen Scientific Affairs (principal investigator: Dr Hudson).

United States, University of North Carolina: Sample collection was funded by a grant from the Foundation of Hope, Raleigh, North Carolina. Sara Trace, Jin Szatkiewicz and Jessica Baker were funded by T32 MH076694 (PI: Bulik). Sara Trace was funded by a 2012–2015 Hilda and Preston Davis Foundation Postdoctoral Fellowship Program in Eating Disorders Research Award. Stephanie Zerwas was funded by a UNC BIRWCH award K12HD001441. The Clinical and Translational Science Award (CTSA) program at UNC-Chapel Hill provided additional assistance UL1TR000083.

United States, Vanderbilt University School of Medicine, Nashville TN, and the Kartini Clinic for Disordered Eating, Portland, OR: Cases were ascertained from the Kartini Clinic, Portland Oregon. Sample collection and processing was funded by a Bristol-Myers Squibb Freedom to Discover Unrestricted Metabolic Diseases Research grant to RDC.


Children’s Hospital of Philadelphia/Price Foundation: We gratefully thank all the patients and their families who were enrolled in this study, as well as all the control subjects who donated blood samples to Children’s Hospital of Philadelphia (CHOP) for genetic research purposes. We thank the Price Foundation for their support of the Collaborative Group effort that was responsible for recruitment of patients, collection of clinical information and provision of the DNA samples used in this study. We also thank the Klarman Family Foundation for supporting the study. We thank the technical staff at the Center for Applied Genomics at CHOP for producing the genotypes used for analyses and the nursing, medical assistant and medical staff for their invaluable help with sample recruitments. CTB and NJS are funded in part by the Scripps Translational Sciences Institute Clinical Translational Science Award (Grant Number U54 RR0252204-01). All genome-wide genotyping was funded by an Institute Development Award to the Center for Applied Genomics from the CHOP. 2011–2014 Davis Foundation Postdoctoral Fellowship Program in Eating Disorders Research Award, Yiran Guo; 2012–2015 Davis Foundation Postdoctoral Fellowship Program in Eating Disorders Research Award, Dong Li.

Estonia, Estonian Genome Center of the University of Tartu (EGCUT): EGCUT received targeted financing from Estonian Government SF0180142s08, Center of Excellence in Genomics (EXCEGEN) and University of Tartu (SP1GVARENG). We acknowledge EGCUT technical personnel, especially Mr V Soo and S Smit. Data analyses were carried out in part in the High Performance Computing Center of University of Tartu.

Japan, National Institute of Mental Health, National Center of Neurology and Psychiatry: The data and sample collection have been supported by Grants-in-Aid for Scientific Research 20390201 and 23390201 to G Komaki from the Ministry of Education, Culture, Sports, Science, and Technology, Japan. We are indebted to the members of the Japanese Genetic Research Group For Eating Disorders for their contribution of time and effort in collecting samples and clinical data.

The Price Foundation Collaborative Group: Harry Brandt, Steve Crawford, Scott Crow, Manfred M Fichter, Katherine A Halmi, Craig Johnson, Allan S Kaplan, Maria La Via, James Mitchell, Michael Strober, Alessandro Rotondo, Janet Treasure, D Blake Woodside, Cynthia M Bulik, Pamela Keel, Kelly L Klump, Lisa Lilenfeld, Laura M Thornton, Kathy Plotnicov, Andrew W Bergen, Wade Berrettini, Walter Kaye and Pierre Magistretti.


Austria: Controls in Vienna were collected with support to Harald Aschauer by Österreichische Nationalbank (ÖNB Project No. 5777 and 13198), Austrian Science Fund (Project No. P7639), European Science Foundation (ESF Programme MNMI) and European Commission (Biomed 1, J1182E25A).

Canada: NIH Grant No. U24 CA074783 to S Gallinger. This work was made possible through collaboration and cooperative agreements with the Colon Cancer Family Registry and PIs. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating institutions or investigators in the Colon CFR, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government or the Colon CFR.

Czech Republic: Support came from the European Regional Development Fund and the State Budget of the Czech Republic (RECAMO, CZ.1.05/2.1.00/03.0101).

dbGAP DAC: Research support to collect data and develop an application to support this project was provided by 3P50CA093459, 5P50CA097007, 5R01ES011740 and 5R01CA133996.

Germany: We thank all probands from the community-based cohorts of PopGen, KORA and the Heinz Nixdorf Recall (HNR) study. This study was supported by the German Federal Ministry of Education and Research (BMBF), within the context of the National Genome Research Network plus (NGFNplus), and the MooDS-Net (Grant 01GS08144 to SC). The KORA research platform was initiated and financed by the Helmholtz Center Munich, German Research Center for Environmental Health, which is funded by the BMBF and by the State of Bavaria. The Heinz Nixdorf Recall cohort was established with the support of the Heinz Nixdorf Foundation.

Greece: This research has been co-financed by the European Union (European Social Fund –ESF) and Greek national funds through the Operational Program ‘Education and Lifelong Learning’ of the National Strategic Reference Framework (NSRF)—Research Funding Program: Heracleitus II. Investing in knowledge society through the European Social Fund.

Italy (North), Verona: The INCIPE study was co-sponsored by Fondazione Cassa di Risparmio di Verona, Azienda Ospedaliera di Verona, and University of Verona. Samples were collected in Verona, Padua, Monselice and Dolo. Co-principal investigators were Antonio Lupo and Giovanni Gambaro.

Netherlands: Genotyping of controls was funded by NIH/NIMH R01 MH078075, granted to Roel Ophoff.

Sweden: The Swedish Research Council (2006-7481 and 2009-6189), and the Swedish Council of Working Life and Social Research (2008-0567).

Author information




Corresponding author

Correspondence to C M Bulik.

Ethics declarations

Competing interests

Patrick F Sullivan was on the SAB of Expression Analysis (Durham, NC, USA). Cynthia Bulik was a consultant for Shire Pharmaceuticals at the time the manuscript was written. Federica Tozzi was a full-time employee of GSK at the time when the study was performed. David A Collier was employed by Eli Lilly, UK for a portion of the time that this study was performed. James L Kennedy has received honoraria from Eli Lilly and Roche. Robert D Levitan has received honorarium from Astra-Zeneca. The remaining authors declare no conflict of interest.

Additional information

WELLCOME TRUST SANGER INSTITUTE: THE WTCCC3 Data Analysis Group: Carl A Anderson1, Jeffrey C Barrett1, James AB Floyd1, Christopher S Franklin1, Ralph McGinnis1, Nicole Soranzo1, Eleftheria Zeggini1. UK Blood Services Controls: Jennifer Sambrook2, Jonathan Stephens2, Willem H Ouwehand2. 1958 Birth Cohort Controls: Wendy L McArdle3, Susan M Ring3, David P Strachan4. Management Committee: Graeme Alexander5, Cynthia M Bulik6, David A Collier7, Peter J Conlon8, Anna Dominiczak9, Audrey Duncanson10, Adrian Hill11, Cordelia Langford1, Graham Lord12, Alexander P Maxwell13, Linda Morgan14, Leena Peltonen1, Richard N Sandford15, Neil Sheerin12, Nicole Soranzo1, Fredrik O Vannberg11, Jeffrey C Barrett1 (chair). DNA, Genotyping, and Informatics Group: Hannah Blackburn1, Wei-Min Chen16, Sarah Edkins1, Mathew Gillman1, Emma Gray1, Sarah E Hunt1, Cordelia Langford1, Suna Onengut-Gumuscu16, Simon Potter1, Stephen S Rich16, Douglas Simpkin1, Pamela Whittaker1.

Supplementary Information accompanies the paper on the Molecular Psychiatry website



Data Analysis Group: Carl A Anderson1, Jeffrey C Barrett1, James AB Floyd1, Christopher S Franklin1, Ralph McGinnis1, Nicole Soranzo1, Eleftheria Zeggini1.

UK Blood Services Controls: Jennifer Sambrook2, Jonathan Stephens2, Willem H Ouwehand2.

1958 Birth Cohort Controls: Wendy L McArdle3, Susan M Ring3, David P Strachan4.

Management Committee: Graeme Alexander5, Cynthia M Bulik6, David A Collier7, Peter J Conlon8, Anna Dominiczak9, Audrey Duncanson10, Adrian Hill11, Cordelia Langford1, Graham Lord12, Alexander P Maxwell13, Linda Morgan14, Leena Peltonen1, Richard N Sandford15, Neil Sheerin12, Nicole Soranzo1, Fredrik O Vannberg11, Jeffrey C Barrett1 (chair).

DNA, Genotyping, and Informatics Group: Hannah Blackburn1, Wei-Min Chen16, Sarah Edkins1, Mathew Gillman1, Emma Gray1, Sarah E Hunt1, Cordelia Langford1, Suna Onengut-Gumuscu16, Simon Potter1, Stephen S Rich16, Douglas Simpkin1, Pamela Whittaker1.

  1. 1

    The Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK

  2. 2

    Division of Transfusion Medicine, Department of Haematology, University of Cambridge, NHSBT Cambridge Centre, Long Road, Cambridge, CB2 0PT, UK

  3. 3

    Department of Social Medicine, University of Bristol, Bristol BS8 2BN, UK

  4. 4

    St. George’s University, Division of Community Health Sciences, London SW19 0RE, UK

  5. 5

    Department of Hepatology, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK

  6. 6

    Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

  7. 7

    Institute of Psychiatry, King’s College London, London SE5 8AF

  8. 8

    Department of Nephrology, Beaumont Hospital, Dublin, Ireland; and Royal College of Surgeons Dublin, Dublin, Ireland

  9. 9

    BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow G12 8TA, UK

  10. 10

    Wellcome Trust, Gibbs Building, 215 Euston Road, London NW1 2BE, UK

  11. 11

    Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX1 2JA, UK

  12. 12

    MRC Centre for Transplantation, King’s College London, London SE1 9RT, UK

  13. 13

    Belfast City Hospital, Lisburn Road, Belfast BT9 7AB, UK

  14. 14

    School of Molecular Medical Sciences, University of Nottingham, Nottingham NG7 2UH, UK

  15. 15

    Academic Department of Medical Genetics, Cambridge University, Cambridge CB2 0QQ, UK

  16. 16

    Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA

PowerPoint slides

PowerPoint slide for Fig. 1

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Boraska, V., Franklin, C., Floyd, J. et al. A genome-wide association study of anorexia nervosa. Mol Psychiatry 19, 1085–1094 (2014). https://doi.org/10.1038/mp.2013.187

Download citation


  • anorexia nervosa
  • body mass index
  • eating disorders
  • genome-wide association study
  • GWAS
  • metabolic

Further reading