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Predicting eating disorder and anxiety symptoms using disorder-specific and transdiagnostic polygenic scores for anorexia nervosa and obsessive-compulsive disorder

Published online by Cambridge University Press:  04 March 2022

Zeynep Yilmaz
Affiliation:
National Centre for Register-based Research, Aarhus BSS, Aarhus University, Aarhus, Denmark Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA Department of Genetics, University of North Carolina, Chapel Hill, NC, USA Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
Katherine Schaumberg
Affiliation:
Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA Department of Psychiatry, University of Wisconsin, Madison, WI, USA
Matthew Halvorsen
Affiliation:
Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
Erica L. Goodman
Affiliation:
Department of Psychology, University of North Dakota, Grand Forks, ND, USA
Leigh C. Brosof
Affiliation:
Department of Psychological and Brain Sciences, University of Louisville, Louisville, KY, USA
James J. Crowley
Affiliation:
Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA Department of Genetics, University of North Carolina, Chapel Hill, NC, USA Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
Carol A. Mathews
Affiliation:
Department of Psychiatry, Genetics Institute, University of Florida, Gainesville, FL, USA
Manuel Mattheisen
Affiliation:
Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden Department of Biomedicine, Aarhus University, Høegh-Guldbergs Gade 10, Aarhus, Denmark The Lundbeck Foundation Initiative of Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark Department of Psychiatry, Psychosomatics and Psychotherapy, University of Würzburg, Würzburg, Germany
Gerome Breen
Affiliation:
Institute of Psychiatry, Psychology and Neuroscience, MRC Social, Genetic and Developmental Psychiatry (SGDP) Centre, King's College London, London, UK National Institute for Health Research Biomedical Research Centre, South London and Maudsley National Health Service Trust, London, UK
Cynthia M. Bulik
Affiliation:
Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
Nadia Micali*
Affiliation:
Department of Psychiatry, Faculty of Medicine, University of Geneva, HUG, Geneva, Switzerland Institute of Child Health, University College London, London, UK Department of Paediatrics, Gynecology and Obstetrics, Faculty of Medicine, University of Geneva, HUG, Geneva, Switzerland
Stephanie C. Zerwas
Affiliation:
Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
Anorexia Nervosa Genetics Initiative
Affiliation:
National Centre for Register-based Research, Aarhus BSS, Aarhus University, Aarhus, Denmark
Eating Disorders Working Group of the Psychiatric Genomics Consortium
Affiliation:
National Centre for Register-based Research, Aarhus BSS, Aarhus University, Aarhus, Denmark
Tourette Syndrome/Obsessive-Compulsive Disorder Working Group of the Psychiatric Genomics Consortium
Affiliation:
National Centre for Register-based Research, Aarhus BSS, Aarhus University, Aarhus, Denmark
*
Author for correspondence: Nadia Micali, E-mail: [email protected]
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Abstract

Background

Clinical, epidemiological, and genetic findings support an overlap between eating disorders, obsessive-compulsive disorder (OCD), and anxiety symptoms. However, little research has examined the role of genetics in the expression of underlying phenotypes. We investigated whether the anorexia nervosa (AN), OCD, or AN/OCD transdiagnostic polygenic scores (PGS) predict eating disorder, OCD, and anxiety symptoms in a large developmental cohort in a sex-specific manner.

Methods

Using summary statistics from Psychiatric Genomics Consortium AN and OCD genome-wide association studies, we conducted an AN/OCD transdiagnostic genome-wide association meta-analysis. We then calculated AN, OCD, and AN/OCD PGS in participants from the Avon Longitudinal Study of Parents and Children to predict eating disorder, OCD, and anxiety symptoms, stratified by sex (combined N = 3212–5369 per phenotype).

Results

The PGS prediction of eating disorder, OCD, and anxiety phenotypes differed between sexes, although effect sizes were small. AN and AN/OCD PGS played a more prominent role in predicting eating disorder and anxiety risk than OCD PGS, especially in girls. AN/OCD PGS provided a small boost over AN PGS in the prediction of some anxiety symptoms. All three PGS predicted higher compulsive exercise across different developmental timepoints [β = 0.03 (s.e. = 0.01) for AN and AN/OCD PGS at age 14; β = 0.05 (s.e. = 0.02) for OCD PGS at age 16] in girls.

Conclusions

Compulsive exercise may have a transdiagnostic genetic etiology, and AN genetic risk may play a role in the presence of anxiety symptoms. Converging with prior twin literature, our results also suggest that some of the contribution of genetic risk may be sex-specific.

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

Introduction

Eating disorders and obsessive-compulsive disorder (OCD) are serious psychiatric conditions with high social, psychological, and physical impact (American Psychiatric Association, 2013; Keshaviah et al., Reference Keshaviah, Edkins, Hastings, Krishna, Franko, Herzog and Eddy2014; World Health Organization, 2008). Clinical, epidemiological, and genetic findings support an overlap between eating disorders and anxiety disorders, particularly anorexia nervosa (AN), and OCD (Anttila et al., Reference Anttila, Bulik-Sullivan, Finucane, Walters, Bras, Duncan and Murray2018; Cederlof et al., Reference Cederlof, Thornton, Baker, Lichtenstein, Larsson, Ruck and Mataix-Cols2015; du Toit, van Kradenburg, Niehaus, & Stein, Reference du Toit, van Kradenburg, Niehaus and Stein2001; Godart, Flament, Perdereau, & Jeammet, Reference Godart, Flament, Perdereau and Jeammet2002; Kaye, Bulik, Thornton, Barbarich, & Masters, Reference Kaye, Bulik, Thornton, Barbarich and Masters2004; Lilenfeld et al., Reference Lilenfeld, Kaye, Greeno, Merikangas, Plotnicov, Pollice and Nagy1998; Meier et al., Reference Meier, Bulik, Thornton, Mattheisen, Mortensen and Petersen2015; Rubenstein, Pigott, L'Heureux, Hill, & Murphy, Reference Rubenstein, Pigott, L'Heureux, Hill and Murphy1992; Strober, Freeman, Lampert, & Diamond, Reference Strober, Freeman, Lampert and Diamond2007; Swinbourne & Touyz, Reference Swinbourne and Touyz2007; Watson et al., Reference Watson, Yilmaz, Thornton, Hubel, Coleman, Gaspar and Bulik2019; Yilmaz et al., Reference Yilmaz, Halvorsen, Bryois, Yu, Thornton, Zerwas and Crowley2020). Whilst research on eating disorders and OCD comorbidity has primarily focused on diagnoses, many symptoms and behaviors are common to both diagnoses, spanning diagnostic categories, and their presence often precedes disorder onset (Nolen-Hoeksema & Watkins, Reference Nolen-Hoeksema and Watkins2011; Stice, Reference Stice2016). Little research has examined these associations – or symptom phenotypes – in a developmental context. Premorbid OCD symptoms and anxiety disorders or symptoms are common in patients with AN (Cederlof et al., Reference Cederlof, Thornton, Baker, Lichtenstein, Larsson, Ruck and Mataix-Cols2015; Schaumberg et al., Reference Schaumberg, Zerwas, Goodman, Yilmaz, Bulik and Micali2019). Childhood anxiety may precede eating disorder symptoms and AN in adolescence (Schaumberg et al., Reference Schaumberg, Zerwas, Goodman, Yilmaz, Bulik and Micali2019), and shared genetic and environmental influences play a role in anxiety and disordered eating symptoms (Silberg & Bulik, Reference Silberg and Bulik2005). Though no longer classified as an anxiety disorder (American Psychiatric Association, 2013), OCD is highly comorbid with anxiety disorders and includes anxiety symptoms, especially in children (Anagnostopoulos et al., Reference Anagnostopoulos, Korlou, Sakellariou, Kondyli, Sarafidou, Tsakanikos and Liakopoulou2016). An improved understanding of the overlap among eating disorders, OCD, and intermediate phenotypes such as anxiety symptoms could aid in conceptualizing mechanisms and processes contributing to the clinical and genetic overlap among these disorders. Additionally, symptom dimensions may transmute over development, shifting from childhood obsessive-compulsive symptoms to adolescent eating disorders (Anderluh, Tchanturia, Rabe-Hesketh, & Treasure, Reference Anderluh, Tchanturia, Rabe-Hesketh and Treasure2003; Micali et al., Reference Micali, Hilton, Nakatani, Heyman, Turner and Mataix-Cols2011) and vice versa. Thus, shared and unique risk factors may contribute to the symptoms of OCD and eating disorders across development.

Genome-wide association studies (GWAS) of AN (Watson et al., Reference Watson, Yilmaz, Thornton, Hubel, Coleman, Gaspar and Bulik2019) and OCD [International Obsessive Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC) & OCD Collaborative Genetics Association Studies (OCGAS), 2018] have provided important insights into the highly polygenic architecture of these disorders and their positive genetic correlation (Watson et al., Reference Watson, Yilmaz, Thornton, Hubel, Coleman, Gaspar and Bulik2019). Application of polygenic scores (PGS) – the weighted sum of common risk variants per individual – examine the genetic architecture of complex traits using evidence for association from variants below the stringent threshold for genome-wide significance (Wray et al., Reference Wray, Lee, Mehta, Vinkhuyzen, Dudbridge and Middeldorp2014). The use of PGS has been validated across psychiatric diagnoses and symptom-level measures (Axelrud et al., Reference Axelrud, Santoro, Pine, Talarico, Gadelha, Manfro and Salum2018; Cross-Disorder Group of the Psychiatric Genomics Consortium et al., Reference Smoller, Craddock, Kendler, Lee, Neale and Sullivan2013; Lee et al., Reference Lee, Ripke, Neale, Faraone, Purcell, Perlis and Wray2013; Mistry, Harrison, Smith, Escott-Price, & Zammit, Reference Mistry, Harrison, Smith, Escott-Price and Zammit2018; Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011; Ripke et al., Reference Ripke, O'Dushlaine, Chambert, Moran, Kahler, Akterin and Sullivan2013, Reference Ripke, Neale, Corvin, Walters, Farh, Holmans and Huang2014), demonstrating that genetic variants associated with risk are often shared across diagnostic categories (Mistry et al., Reference Mistry, Harrison, Smith, Escott-Price and Zammit2018). Moreover, transdiagnostic PGS (determined by either AN or OCD case status) of genetically correlated disorders may enhance predictive power for either disorder (Maier et al., Reference Maier, Moser, Chen, Ripke, Coryell, Potash and Lee2015).

Sex differences in the prevalence and presentation of eating disorders, anxiety disorders, and OCD warrant sex-specific examination of risk factors. While the majority of AN cases are female (Hudson, Hiripi, Pope, & Kessler, Reference Hudson, Hiripi, Pope and Kessler2007; Swanson, Crow, Le Grange, Swendsen, & Merikangas, Reference Swanson, Crow, Le Grange, Swendsen and Merikangas2011), AN in males often has an earlier age of onset and is likely to be more severe (El Ghoch, Calugi, Milanese, Bazzani, & Dalle Grave, Reference El Ghoch, Calugi, Milanese, Bazzani and Dalle Grave2017; Kinasz, Accurso, Kass, & Le Grange, Reference Kinasz, Accurso, Kass and Le Grange2016; Voderholzer et al., Reference Voderholzer, Hessler, Naab, Fichter, Graetz, Greetfeld and Schlegl2019). Similarly, the lifetime prevalence of eating disorders is much higher in females than males (Hudson et al., Reference Hudson, Hiripi, Pope and Kessler2007; Swanson et al., Reference Swanson, Crow, Le Grange, Swendsen and Merikangas2011), possibly with the exception of subthreshold binge eating (Hudson et al., Reference Hudson, Hiripi, Pope and Kessler2007). Furthermore, the twin literature has reported differences in the heritability estimates for disordered eating in boys and girls (Klump et al., Reference Klump, Culbert, Slane, Burt, Sisk and Nigg2012). The lifetime prevalence of anxiety disorders is up to 60% higher in women than in men (Kessler, Chiu, Demler, Merikangas, & Walters, Reference Kessler, Chiu, Demler, Merikangas and Walters2005). In the case of OCD, childhood onset is more common among males and adolescent onset is more common among females (Ruscio, Stein, Chiu, & Kessler, Reference Ruscio, Stein, Chiu and Kessler2010). Importantly, sex differences in the presentation of symptoms such as restraint and weight and shape concern in eating disorders (Kinasz et al., Reference Kinasz, Accurso, Kass and Le Grange2016) and contamination/cleaning and sexual/religious symptoms in OCD (Torresan et al., Reference Torresan, Ramos-Cerqueira, Shavitt, do Rosario, de Mathis, Miguel and Torres2013) have also been reported. Given these discrepancies, we could expect: (a) notable sex differences in the role of genetic risk and eating disorders, OCD, and anxiety symptom phenotypes; and (b) that genetic risk may be more impactful and predictive for boys, especially in the case of eating disorders.

This study examined whether the AN, OCD, or AN/OCD PGS predicts eating disorders, OCD, and anxiety symptom dimensions or diagnoses using a developmental framework in male and female participants from a population-based cohort. Our main hypothesis was that AN/OCD PGS would demonstrate better statistical power than AN or OCD PGS, and the transdiagnostic PGS would evidence the most benefit compared with single-trait PGS when predicting intermediate phenotypes shared across the two disorders, such as generalized anxiety or worrying. We also hypothesized that symptom dimensions specific to each disorder would be predicted by disorder-specific PGS (e.g. thin ideal internalization by AN, or symmetry/checking behavior by OCD). Importantly, in light of the differences in lifetime prevalence and/or age of onset of eating disorders, OCD, and anxiety disorders between sexes, we hypothesized that there would be sex-specific differences in the prediction of AN, OCD, and AN/OCD PGS, and high AN genetic risk would play a larger role in predicting eating disorder symptoms in boys than girls.

Methods

Participants

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a longitudinal, population-based study of women and their children (Boyd et al., Reference Boyd, Golding, Macleod, Lawlor, Fraser, Henderson and Davey Smith2013). All pregnant women living in Avon, United Kingdom who were expected to deliver between 1 April 1991 and 31 December 1992 were invited to participate. Children from 14 541 pregnancies were enrolled, 13 988 of whom were alive at one year. An additional 713 children were enrolled at or after age 7 (Boyd et al., Reference Boyd, Golding, Macleod, Lawlor, Fraser, Henderson and Davey Smith2013). The study website contains details of all the data that are available through a fully searchable data dictionary and variable search tool (http://www.bristol.ac.uk/alspac/researchers/our-data/). Ethical approval was obtained from the ALSPAC Ethics and Law Committee and the Local Research Ethics Committees. Briefly, informed consent for the use of data collected via questionnaires and clinics was obtained from participants following the recommendations of the ALSPAC Ethics and Law Committee at the time. Mothers provided written consent for the participation of their children, and children were invited to give assent whenever it was appropriate. Study participants have the right to withdraw their consent for elements of the study or from the study entirely at any time. Full details of the ALSPAC consent procedures are available on the study website (http://www.bristol.ac.uk/alspac/researchers/research-ethics/).

For genetic analyses, we used post-quality control (QC) dosage files for 7977 unrelated participants (Martin, Hamshere, Stergiakouli, O'Donovan, & Thapar, Reference Martin, Hamshere, Stergiakouli, O'Donovan and Thapar2014; Paternoster et al., Reference Paternoster, Zhurov, Toma, Kemp, St Pourcain, Timpson and Evans2012), 7779 of whom passed additional QC performed as a part of this study (3787 girls and 3992 boys; see online Supplementary Information). The final number of participants with genotype and at least one phenotype information was 3270 girls and 3297 boys.

Measures

Table 1 provides a list of all measures, assessment timepoints, and methods of administration. Measures assessing psychopathology at younger ages (before age 14) were primarily assessed via parent-report. Those assessing psychopathology during adolescence (age 14 or older) were primarily assessed via self-report.

Table 1. Eating disorder, obsessive-compulsive disorder, and anxiety diagnostic and symptom-based constructs

Eating disorder symptoms for the previous year were evaluated at ages 14 and 16 using questions adapted from the Youth Risk Behavior Surveillance System Questionnaire (Kann et al., Reference Kann, Warren, Harris, Collins, Williams, Ross and Kolbe1996), validated in a population-based study of adolescents (Field, Taylor, Celio, & Colditz, Reference Field, Taylor, Celio and Colditz2004). Binge-eating, purging, fasting, and compulsive exercise were characterized and categorized as described previously (Micali, Daniel, Ploubidis, & De Stavola, Reference Micali, Daniel, Ploubidis and De Stavola2018; Micali et al., Reference Micali, De Stavola, Ploubidis, Simonoff, Treasure and Field2015) (online Supplementary Information). Eating disorder diagnoses at ages 14 and 16 were derived using DSM-5 criteria (American Psychiatric Association, 2013) as detailed in a previous publication by our group (Schaumberg et al., Reference Schaumberg, Zerwas, Goodman, Yilmaz, Bulik and Micali2019). Eating disorder cognitions, including body image distortion, emotional eating, external eating, body dissatisfaction, thin ideal internalization, dietary restraint, weight concern, and shape concern, were assessed by validated, age-appropriate self-report measurements (online Supplementary Information).

OCD and anxiety symptoms at age 7, 10, 13, and 15 were collected using the Development and Wellbeing Assessment (DAWBA; online Supplementary Information) (Goodman, Ford, Richards, Gatward, & Meltzer, Reference Goodman, Ford, Richards, Gatward and Meltzer2000; Goodman, Heiervang, Collishaw, & Goodman, Reference Goodman, Heiervang, Collishaw and Goodman2011). Probabilities of anxiety disorder diagnoses at ages 7 (specific phobia and separation anxiety), 10 (OCD), 13 (OCD, social phobia, and generalized anxiety disorder), and 15 (generalized anxiety disorder) were determined using computer-generated DAWBA band variables (Goodman et al., Reference Goodman, Heiervang, Collishaw and Goodman2011), which assign the probability of the participant meeting DSM-IV criteria for an anxiety disorder. We defined likely cases as those where likelihood of case status based on response pattern was ⩾50%. We also defined five latent OCD or anxiety factors for ages 10 and 13: (1) OCD-symmetry; (2) OCD-dirt/germs; (3) physical anxiety; (4) worrying; and (5) social phobia (Schaumberg et al., Reference Schaumberg, Zerwas, Goodman, Yilmaz, Bulik and Micali2019) (online Supplementary Information).

Data analysis

We calculated AN, OCD, and AN/OCD PGS to predict 27 eating disorder, six OCD, and 11 anxiety phenotypes in the ALSPAC target sample using PRS-CS (Ge, Chen, Ni, Feng, & Smoller, Reference Ge, Chen, Ni, Feng and Smoller2019). AN PGS was constructed using the Anorexia Nervosa Genetics Initiative & Psychiatric Genomics Consortium (PGC) Eating Disorder Working Group Freeze 2 AN GWAS (Watson et al., Reference Watson, Yilmaz, Thornton, Hubel, Coleman, Gaspar and Bulik2019), and OCD PGS was calculated using the Freeze 1 PGC OCD GWAS [International Obsessive Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC) & OCD Collaborative Genetics Association Studies (OCGAS), 2018]. The AN/OCD summary statistics file was obtained from a GWAS meta-analysis of the AN and OCD datasets (see online Supplementary Information, Table S1, and Fig. S1). All of the discovery samples and the ALSPAC target sample included in our analysis were of European ancestry, determined using genomic ancestry principal components through comparison with a European ancestry (CEU) reference panel. We examined how well each of the eating disorder, OCD, and anxiety symptom phenotypes were predicted by: (1) AN; (2) OCD; and (3) AN/OCD PGS in girls and boys separately to elucidate whether sex-specific differences existed. Additional results for the combined sample with and without sex as a covariate are summarized in online Supplementary Tables S3 and S4. Due to insufficient power, only binary phenotypes with ⩾50 cases are reported.

Results

Eating disorder symptom phenotypes and diagnoses

In girls, AN PGS predicted eating disorders not otherwise specified/purging disorder at age 14 [ß = 0.1130 (0.0552), p = 0.041], presence of a threshold or subthreshold eating disorder at age 14 [ß = 0.1214 (0.0498), p = 0.015], and compulsive exercise at age 14 [ß = 0.0336 (0.0143), p = 0.019] (Table 2). OCD PGS predicted thin ideal internalization at age 14 [ß = 0.1264 (0.0487), p = 0.010] and compulsive exercise at age 16 [ß = 0.0535 (0.0240), p = 0.025]. AN/OCD PGS predicted pressure to lose weight at age 14 [ß = 0.0839 (0.0423), p = 0.047], the presence of a threshold or subthreshold eating disorder at age 14 [ß = 0.1146 (0.0493), p = 0.020], fasting at age 14 [ß = 0.0148 (0.0064), p = 0.020], and compulsive exercise at age 14 [ß = 0.0287 (0.0142), p = 0.043].

Table 2. Prediction of eating disorder, obsessive-compulsive disorder, and anxiety symptom dimensions and diagnoses using polygenic scores in girlsa

Abbreviations: PGS, polygenic score; ß, standardized beta regression coefficient; s.e., standard error; AN, anorexia nervosa; OCD, obsessive-compulsive disorder; AN/OCD, anorexia nervosa/obsessive-compulsive transdiagnostic phenotype.

a Genomic principal components 1–5 were used as covariates to account for population stratification.

b We report t-values for continuous phenotypes and z-values for binary phenotypes.

c Binary phenotype.

d Due to insufficient statistical power, any binary measure with less than 50 cases is not included in the final analysis.

*(also bolded) Statistically significant at p < 0.05.

In boys, emotional eating at age 14 was predicted by AN PGS [ß = 0.2583 (0.1096), p = 0.019] as well as AN/OCD PGS [ß = 0.2371 (0.1109), p = 0.033] (Table 3). None of the eating disorder phenotypes were predicted by OCD PGS in boys.

Table 3. Prediction of eating disorder, obsessive-compulsive disorder, and anxiety symptom dimensions and diagnoses using polygenic scores in boysa

Abbreviations: PGS, polygenic score; ß, standardized beta regression coefficient; s.e., standard error; AN, anorexia nervosa; OCD, obsessive-compulsive disorder; AN/OCD, anorexia nervosa/obsessive-compulsive transdiagnostic phenotype.

a Genomic principal components 1–5 were used as covariates to account for population stratification.

b We report t-values for continuous phenotypes and z-values for binary phenotypes.

c Binary phenotype.

d Due to insufficient statistical power, any binary measure with less than 50 cases is not included in the final analysis.

*(also bolded) Statistically significant at p < 0.05.

OCD and anxiety symptom phenotypes and diagnoses

In girls, AN PGS predicted a higher score for OCD latent factor dirt/germs at age 13 [ß = 0.0281 (0.0129), p = 0.030] and an increased likelihood of separation anxiety at age 7 [ß = 0.4342 (0.1246), p = 0.001] (Table 2). AN/OCD PGS predicted an increased likelihood of separation anxiety [ß = 0.4868 (0.1246), p < 0.001] as well as higher scores for latent factors OCD dirt/germs [ß = 0.0277 (0.0128), p = 0.031], worrying [ß = 0.0334 (0.0164), p = 0.042], and social phobia at age 13 [ß = 0.0367 (0.0155), p = 0.018]. OCD PGS did not predict any of the OCD or anxiety phenotypes.

In boys, AN PGS predicted a higher score for latent factor worrying at age 10 [ß = 0.0292 (0.0133), p = 0.028] but a lower score for OCD latent factor dirt/germs at age 13 [ß = −0.0297 (0.0132), p = 0.025] (Table 3). AN/OCD PGS also negatively predicted OCD latent factor dirt/germs at age 13 [ß = −0.0300 (0.0133), p = 0.025], whereas OCD PGS predicted a lower score for latent factor social phobia at age 10 [ß = −0.0254 (0.0125), p = 0.042].

Discussion

In this exploratory study, we were able to predict eating disorder, OCD, and anxiety phenotypes using AN, OCD, and AN/OCD PGS in girls and boys separately during different developmental points in a large population sample. The majority of phenotypes predicted by AN PGS were also predicted by AN/OCD PGS (e.g. emotional eating at age 14 in boys; separating anxiety at age 7 in girls). However, this overlap was not 100% (e.g. latent factor worrying at age 10 in boys predicted by AN and not AN/OCD PGS), and none of the phenotypes predicted by OCD PGS were also predicted by AN/OCD PGS, suggesting that the genetic risk associated with some phenotypes may be more OCD-specific than being based on a transdiagnostic common factor. Notably, there were no phenotypes predicted separately by both AN and OCD PGS. Considering the notably smaller sample size of the OCD GWAS compared to the AN GWAS (2688 v. 16 992 cases), OCD PGS is likely to be underpowered, and some phenotypes associated with a higher genetic load for OCD may be predicted by the AN/OCD PGS. There were also phenotypes only predicted by the transdiagnostic PGS (e.g. thin ideal internalization at age 14 in girls), further demonstrating the likely boost in statistical power for both AN and OCD with the use of the transdiagnostic genotype.

Compulsive exercise was the only intermediate phenotype that was positively predicted by more than one disorder-specific PGS in girls, suggesting it may be a key intermediate phenotype that, although commonly associated with eating disorders, is influenced by genetic risk for both AN and OCD. Together with evidence for shared genetic risk between a broad AN phenotype and general propensity for physical activity (Watson et al., Reference Watson, Yilmaz, Thornton, Hubel, Coleman, Gaspar and Bulik2019), this finding suggests that genetic factors may be particularly relevant to understanding the development of compulsive exercise in eating disorders. Compulsive exercise encompasses many of the hallmark symptoms of AN (e.g. weight and shape concern) and OCD (e.g. compulsive behavior) (Davis & Kaptein, Reference Davis and Kaptein2006). Furthermore, comorbid OCD symptoms are especially pronounced in the subpopulation of AN patients with compulsive exercise (Błachno et al., Reference Błachno, Bryńska, Tomaszewicz-Libudzic, Jagielska, Srebnicki, Wiśniewski and Wolańczyk2016; Davis & Claridge, Reference Davis and Claridge1998; Davis & Kaptein, Reference Davis and Kaptein2006; Davis, Katzman, & Kirsh, Reference Davis, Katzman and Kirsh1999; Naylor, Mountford, & Brown, Reference Naylor, Mountford and Brown2011), which has significant clinical relevance since the presence of compulsive exercise in AN is an established predictor of treatment outcomes, including higher pathology at discharge from inpatient treatment (Dalle Grave, Calugi, & Marchesini, Reference Dalle Grave, Calugi and Marchesini2008), relapse (Carter, Blackmore, Sutandar-Pinnock, & Woodside, Reference Carter, Blackmore, Sutandar-Pinnock and Woodside2004), and greater energy requirements for weight gain (Kaye, Gwirtsman, Obarzanek, & George, Reference Kaye, Gwirtsman, Obarzanek and George1988). Treatments for this symptom are currently lacking, and our preliminary results point to the need for additional investigation of the habitual and compulsive nature of exercise behavior in girls, which may lead to targeted intervention development for this symptom that derives from a modern biobehavioral understanding of both eating disorders and OCD. It is not clear why this association was not present in boys, but one potential explanation is the lack of statistical power for current PGS to detect such a relationship in males, which may require much larger discovery sample sizes. Alternatively, the risk associated with compulsive exercise may be driven by mechanisms outside of AN or OCD genetic load in men.

Importantly, our findings suggest the presence of both sex and developmental timing influences in the biological pathways and vulnerabilities leading to these symptom phenotypes. Contrary to our hypothesis, our results show that AN genetics may play a more prominent role in risk for eating disorder and related phenotypes in girls, as compared to boys, and especially in early development. In fact, significant eating disorder symptom phenotypes at age 14 – but none at age 16 – were predicted by AN PGS. Variability in genetic influence depending on the stage of development has previously been established, as twin studies have shown changes in the contribution of genetic and environmental risk factors for disordered eating during different stages of adolescence (Fairweather-Schmidt & Wade, Reference Fairweather-Schmidt and Wade2015; O'Connor, Culbert, Mayhall, Burt, & Klump, Reference O'Connor, Culbert, Mayhall, Burt and Klump2020). However, the twin-based heritability estimate for disordered eating has been shown to be much higher in boys than girls prior to puberty (0.52 in boys v. 0 in girls) (Klump et al., Reference Klump, Culbert, Slane, Burt, Sisk and Nigg2012), suggesting that AN genetic load could manifest itself earlier in boys, which is not what we observed in our study. Except for body image distortion at age 10, all eating disorder phenotypic data were collected at age 14 onward, so we cannot rule out the possibility that AN PGS may predict eating disorder phenotypes in boys at an earlier age than we have data available for. Another possible explanation is that the risk for disordered eating in boys could be attributed to a higher genetic load for other eating disorders – for which currently no large GWAS results exist – or other phenotypes independent of AN. Additionally, PGS is designed to account for common genetic variation, therefore genetic risk for eating disorders in males could be potentially driven by other types of variation such as copy number variants, rare variants, epigenetic factors, or other genetic mechanisms that PGS does a poor job of capturing.

Genetic prediction of anxiety symptoms and diagnoses also showed notable differences in boys and girls. For instance, AN PGS predicted separation anxiety at age 7 in girls and increased worrying at age 10 in boys. Epidemiological studies show over a 10-fold increase in AN risk among girls with separation anxiety disorder (Bulik, Sullivan, Fear, & Joyce, Reference Bulik, Sullivan, Fear and Joyce1997), and a twin-based study reported a shared genetic effect influencing liability to AN, separation anxiety, and childhood overanxious disorder (which is very similar to generalized anxiety disorder in adults) during different stages of development (Silberg & Bulik, Reference Silberg and Bulik2005), supporting our findings about the presence of a shared genetic pathway between anxiety and AN. We unexpectedly observed that lower OCD-specific genetic risk predicted lower scores on the latent factor indexing social phobia at age 13 in boys. While anxiety symptoms are common in patients with OCD, OCD is distinct from anxiety disorders phenotypes – in fact it is now a separate diagnostic chapter in DSM – and our results suggest that OCD may be distinct from anxiety disorders at a genetic level, especially for men. Replication of these associations is required to better understand the nature of these relationships and the importance of potential sex differences in the biological pathways associated with anxiety risk.

Notably, significant PGS predictions did not always fall cleanly in accordance with hypothesized disorder-specific symptom phenotypes, especially in the case of anxiety phenotypes. For instance, AN – but not OCD – PGS predicted higher scores for OCD-dirt/germs and worrying during different developmental timepoints in girls. While contamination fears are often associated with OCD, they are not unique to OCD and have a cross-disorder component. In fact, it is not uncommon for individuals with AN to present with food-related contamination fears (Drummond & Kolb, Reference Drummond and Kolb2008). In our previous ALSPAC study, we found that the latent factor worrying significantly predicts eating disorder symptoms at ages 14 and 16 as well as AN diagnosis at age 16 (Schaumberg et al., Reference Schaumberg, Zerwas, Goodman, Yilmaz, Bulik and Micali2019). This may suggest that uncontrolled worrying may be an underlying early symptom of AN and disordered eating that precedes the manifestation of an eating disorder.

Our study has notable strengths that merit consideration. This is the first study to use AN, OCD, or AN/OCD PGS to predict eating disorder and anxiety intermediate phenotypes in a large population sample through a developmental perspective and also to examine how genetic risk may manifest differently in boys and girls. We augmented the diagnostic approach by including intermediate phenotypes measured continuously to capture the full range of these underlying traits in the general population. Furthermore, studying these associations in the general population allows a finer understanding of intermediate phenotypes and broader psychopathology as treatment-seeking individuals might have notable differences from the general population (e.g. increased comorbid psychopathology).

Limitations of our study include reliance on self- or parent-report symptoms instead of clinical diagnoses, phenotype data being available for only a subset of participants with the potential for response bias, and potential Type 2 error due to lack of statistical power for PGS in the prediction of genetic risk. The effect sizes observed were relatively small, and due to the exploratory nature of our study with the aim of elucidating sex differences using transdiagnostic prediction and symptom-level data, we did not correct for multiple testing with the hopes of generating potential hypotheses for future work. Of note, few participants met diagnostic criteria for AN, bulimia nervosa, or binge-eating disorder, whereas we had better statistical power for the non-specific eating disorder statuses (especially in girls), which likely explains why PGS did not predict AN diagnosis in either sex and none of the eating disorder diagnoses in boys. Similarly, a high probability (50% or higher) for anxiety disorder diagnoses was uncommon despite our attempt to increase power through dichotomizing these items, and even with dichotomizing, we did not have enough cases to include OCD diagnosis in our outcomes. Additionally, we did not address the presence of comorbid psychiatric diagnoses, therefore we cannot account for the role of comorbidities or the genetic risk associated with these additional diagnoses. However, as comorbidity is the norm and not the exception, our results are likely to capture associations that are more likely to be present in clinical and population settings, as pure forms of eating disorders and OCD are not common. With the exception of body image distortion at age 10, all eating disorder data were collected at age 14 onward, therefore we were unable to examine the potential association between PGS and eating behavior in early childhood. From a genetic perspective, whether all of the eating disorder-related symptom phenotypes examined as a part of our study actually fall on an etiological continuum with AN is not clear (Dinkler et al., Reference Dinkler, Taylor, Rastam, Hadjikhani, Bulik, Lichtenstein and Lundstrom2021). Finally, the AN PGS was constructed using a much larger GWAS than the OCD GWAS, which may have translated to OCD PGS being underpowered and the AN/OCD transdiagnostic GWAS being more heavily skewed by AN PGS than OCD PGS.

Taken together, results of our study provide preliminary support for utilizing the high positive genetic correlation between AN and OCD (Watson et al., Reference Watson, Yilmaz, Thornton, Hubel, Coleman, Gaspar and Bulik2019), leading to a small boost in predictive power through the use of a transdiagnostic PGS. We anticipate this statistical boost to become more notable as AN and (especially) OCD GWAS sample sizes continue to increase. Furthermore, our findings also point to differences in the manifestation of genetic risk for eating disorder and anxiety symptoms in boys and girls. Genetic risk associated with AN may be a stronger predictor of eating disorder symptoms earlier in development, whereas OCD genetic risk – albeit limited based on current GWAS data – may increase in effect across adolescence. Another significant observation was that compulsive exercise may be an intermediate phenotype or clinical manifestation of shared genetic risk factors for both AN and OCD. Compulsive exercise might be a distinct AN subphenotype, and clinical research should continue to explore habitual and compulsive processes associated with this symptom. Finally, this study opens up new avenues for a clearer understanding of biology of behaviors and intermediate phenotypes in eating disorders.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0033291721005079

Acknowledgements

We are deeply grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, and nurses. The UK Medical Research Council and the Wellcome Trust (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and Dr Micali will serve as guarantor for the contents of this paper. Dr Micali had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Author contributions

ZY was responsible for genetic study design, quality control of genotype data, genetic analyses, and manuscript preparation. KS, ELG, and LCB were responsible for study design, quality control and preparation of phenotype data, statistical analysis of phenotype data, and manuscript preparation. MH was responsible for carrying out the transdiagnostic AN/OCD GWAS. MH, JJC, MM, CAM, and GB were responsible for genetic study design, oversight of genetic analyses, and manuscript preparation. CMB oversaw and contributed to the development of the research question, study design, and manuscript preparation. NM and SCZ were responsible for the development of the research question and provided oversight for all aspects of the study.

Financial support

This research was specifically funded by the National Institute of Mental Health (NIMH) R01MH073842 and R21MH109917. ZY is funded by NIMH (K01MH109782; R01MH105500; R01MH120170) and a Brain and Behavior Research Foundation NARSAD Young Investigator Award (grant # 28799). KS is supported by NIMH K01MH123914 and L30MH120619. JJC and MM acknowledge grant funding from NIMH (R01MH105500; R01MH110427). CMB acknowledges funding from NIMH (R01MH120170; R01MH124871; R01MH119084; R01MH118278), the Swedish Research Council (VR Dnr: 538-2013-8864), and the Klarman Family Foundation. NM acknowledges grant funding from the Medical Research Council (MR/R004803/1), NIMH (R01MH108595; R21MH115397), the Swiss National Fund (320030_182484), and a Brain and Behavior Research Foundation Independent Investigator Award (grant # 24608). SCZ is supported by NIMH K01MH100435. PGC-ED AN and the AN/OCD transdiagnostis GWAS included controls from the iPSYCH Initiative, funded by the Lundbeck Foundation (grant # R102-A9118 and R155-2014-1724). The UK Medical Research Council and the Wellcome Trust (grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors and they will serve as guarantors for the contents of this paper. A comprehensive list of grant funding is available on the ALSPAC website.

Conflict of interest

CAM has received funding for a book contract with W.W. Norton, Inc., serves as the co-chair of the Tourette Association of America scientific advisory board, is a member of the International OCD Foundation scientific and clinical advisory board, as well as a member of the steering committee for the Family Foundation for OCD Research. GB received grant funding and consultancy fees in preclinical genetics from Eli Lilly, consultancy fees from Otsuka, and has received honoraria from Illumina. CMB has received grant support and served on Shire Scientific Advisory Board, is a consultant for Idorsia, and receives author royalties from Pearson. All other authors have no conflicts of interest to disclose.

Footnotes

*

These authors contributed equally to this work.

References

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: American Psychiatric Association.Google Scholar
Anagnostopoulos, D. C., Korlou, S., Sakellariou, K., Kondyli, V., Sarafidou, J., Tsakanikos, E., … Liakopoulou, M. (2016). Comorbid psychopathology and clinical symptomatology in children and adolescents with obsessive-compulsive disorder. Psychiatrike, 27(1), 2736.Google ScholarPubMed
Anderluh, M. B., Tchanturia, K., Rabe-Hesketh, S., & Treasure, J. (2003). Childhood obsessive-compulsive personality traits in adult women with eating disorders: Defining a broader eating disorder phenotype. American Journal of Psychiatry, 160(2), 242247. doi:10.1176/appi.ajp.160.2.242CrossRefGoogle ScholarPubMed
Anttila, V., Bulik-Sullivan, B., Finucane, H. K., Walters, R. K., Bras, J., Duncan, L., … Murray, R. (2018). Analysis of shared heritability in common disorders of the brain. Science (New York, N.Y.), 360(6395). doi:10.1126/science.aap8757Google ScholarPubMed
Axelrud, L. K., Santoro, M. L., Pine, D. S., Talarico, F., Gadelha, A., Manfro, G. G., … Salum, G. A. (2018). Polygenic risk score for Alzheimer's disease: Implications for memory performance and hippocampal volumes in early life. American Journal of Psychiatry, 175(6), 555563. doi:10.1176/appi.ajp.2017.17050529CrossRefGoogle ScholarPubMed
Błachno, M., Bryńska, A., Tomaszewicz-Libudzic, C., Jagielska, G., Srebnicki, T., Wiśniewski, A., & Wolańczyk, T. (2016). Obsessive-compulsive symptoms and physical activity in patients with anorexia nervosa–possible relationships. Psychiatria Polska, 50(1), 5564.CrossRefGoogle ScholarPubMed
Boyd, A., Golding, J., Macleod, J., Lawlor, D. A., Fraser, A., Henderson, J., … Davey Smith, G. (2013). Cohort profile: The ‘children of the 90s’ – the index offspring of the Avon Longitudinal Study of Parents and Children. International Journal of Epidemiology, 42(1), 111127. doi:10.1093/ije/dys064CrossRefGoogle ScholarPubMed
Bulik, C. M., Sullivan, P. F., Fear, J. L., & Joyce, P. R. (1997). Eating disorders and antecedent anxiety disorders: A controlled study. Acta Psychiatrica Scandinavica, 96(2), 101107.CrossRefGoogle ScholarPubMed
Carter, J. C., Blackmore, E., Sutandar-Pinnock, K., & Woodside, D. B. (2004). Relapse in anorexia nervosa: A survival analysis. Psychological Medicine, 34(4), 671679. doi:10.1017/s0033291703001168CrossRefGoogle ScholarPubMed
Cederlof, M., Thornton, L. M., Baker, J., Lichtenstein, P., Larsson, H., Ruck, C., … Mataix-Cols, D. (2015). Etiological overlap between obsessive-compulsive disorder and anorexia nervosa: A longitudinal cohort, multigenerational family and twin study. World Psychiatry, 14(3), 333338. doi:10.1002/wps.20251CrossRefGoogle ScholarPubMed
Dalle Grave, R., Calugi, S., & Marchesini, G. (2008). Compulsive exercise to control shape or weight in eating disorders: Prevalence, associated features, and treatment outcome. Comprehensive Psychiatry, 49(4), 346352. doi:10.1016/j.comppsych.2007.12.007CrossRefGoogle ScholarPubMed
Davis, C., & Claridge, G. (1998). The eating disorders as addiction: A psychobiological perspective. Addictive Behaviors, 23(4), 463475. doi:10.1016/s0306-4603(98)00009-4CrossRefGoogle ScholarPubMed
Davis, C., & Kaptein, S. (2006). Anorexia nervosa with excessive exercise: A phenotype with close links to obsessive-compulsive disorder. Psychiatry Research, 142(2–3), 209217. doi:10.1016/j.psychres.2005.11.006CrossRefGoogle ScholarPubMed
Davis, C., Katzman, D. K., & Kirsh, C. (1999). Compulsive physical activity in adolescents with anorexia nervosa: A psychobehavioral spiral of pathology. Journal of Nervous and Mental Disease, 187(6), 336342. doi:10.1097/00005053-199906000-00002CrossRefGoogle ScholarPubMed
Dinkler, L., Taylor, M. J., Rastam, M., Hadjikhani, N., Bulik, C. M., Lichtenstein, P., … Lundstrom, S. (2021). Association of etiological factors across the extreme end and continuous variation in disordered eating in female Swedish twins. Psychological Medicine, 51(5), 750760. doi:10.1017/s0033291719003672CrossRefGoogle ScholarPubMed
Drummond, L. M., & Kolb, P. (2008). Obsessive–compulsive contamination fears and anorexia nervosa: The application of the new psycho-educational treatment of danger ideation reduction therapy (DIRT). Behaviour Change, 25(1), 4450. doi:10.1375/bech.25.1.44CrossRefGoogle Scholar
du Toit, P. L., van Kradenburg, J., Niehaus, D., & Stein, D. J. (2001). Comparison of obsessive-compulsive disorder patients with and without comorbid putative obsessive-compulsive spectrum disorders using a structured clinical interview. Comprehensive Psychiatry, 42(4), 291300. doi:10.1053/comp.2001.24586CrossRefGoogle ScholarPubMed
El Ghoch, M., Calugi, S., Milanese, C., Bazzani, P. V., & Dalle Grave, R. (2017). Body composition in men with anorexia nervosa: Longitudinal study. International Journal of Eating Disorders, 50(7), 856860. doi:10.1002/eat.22721CrossRefGoogle ScholarPubMed
Fairweather-Schmidt, A. K., & Wade, T. D. (2015). Changes in genetic and environmental influences on disordered eating between early and late adolescence: A longitudinal twin study. Psychological Medicine, 45(15), 32493258. doi:10.1017/s0033291715001257CrossRefGoogle ScholarPubMed
Field, A. E., Taylor, C. B., Celio, A., & Colditz, G. A. (2004). Comparison of self-report to interview assessment of bulimic behaviors among preadolescent and adolescent girls and boys. International Journal of Eating Disorders, 35(1), 8692. doi:10.1002/eat.10220CrossRefGoogle ScholarPubMed
Ge, T., Chen, C. Y., Ni, Y., Feng, Y. A., & Smoller, J. W. (2019). Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nature Communications, 10(1), 1776. doi:10.1038/s41467-019-09718-5CrossRefGoogle ScholarPubMed
Godart, N. T., Flament, M. F., Perdereau, F., & Jeammet, P. (2002). Comorbidity between eating disorders and anxiety disorders: A review. International Journal of Eating Disorders, 32(3), 253270. doi:10.1002/eat.10096CrossRefGoogle ScholarPubMed
Goodman, A., Heiervang, E., Collishaw, S., & Goodman, R. (2011). The ‘DAWBA bands’ as an ordered-categorical measure of child mental health: Description and validation in British and Norwegian samples. Social Psychiatry and Psychiatric Epidemiology, 46(6), 521532. doi:10.1007/s00127-010-0219-xCrossRefGoogle ScholarPubMed
Goodman, R., Ford, T., Richards, H., Gatward, R., & Meltzer, H. (2000). The development and well-being assessment: Description and initial validation of an integrated assessment of child and adolescent psychopathology. Journal of Child Psychology and Psychiatry, 41(5), 645655.CrossRefGoogle ScholarPubMed
Hudson, J. I., Hiripi, E., Pope, H. G. Jr., & Kessler, R. C. (2007). The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication. Biological Psychiatry, 61(3), 348358. doi:10.1016/j.biopsych.2006.03.040CrossRefGoogle ScholarPubMed
International Obsessive Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC), & OCD Collaborative Genetics Association Studies (OCGAS). (2018). Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis. Molecular Psychiatry, 23(5), 11811188. doi:10.1038/mp.2017.154CrossRefGoogle Scholar
Kann, L., Warren, C. W., Harris, W. A., Collins, J. L., Williams, B. I., Ross, J. G., & Kolbe, L. J. (1996). Youth risk behavior surveillance – United States, 1995. Journal of School Health, 66(10), 365377.CrossRefGoogle ScholarPubMed
Kaye, W. H., Bulik, C. M., Thornton, L., Barbarich, N., & Masters, K. (2004). Comorbidity of anxiety disorders with anorexia and bulimia nervosa. American Journal of Psychiatry, 161(12), 22152221. doi:10.1176/appi.ajp.161.12.2215CrossRefGoogle ScholarPubMed
Kaye, W. H., Gwirtsman, H. E., Obarzanek, E., & George, D. T. (1988). Relative importance of calorie intake needed to gain weight and level of physical activity in anorexia nervosa. American Journal of Clinical Nutrition, 47(6), 989994. doi:10.1093/ajcn/47.6.989CrossRefGoogle ScholarPubMed
Keshaviah, A., Edkins, K., Hastings, E. R., Krishna, M., Franko, D. L., Herzog, D. B., … Eddy, K. T. (2014). Re-examining premature mortality in anorexia nervosa: A meta-analysis redux. Comprehensive Psychiatry, 55(8), 17731784. doi:10.1016/j.comppsych.2014.07.017CrossRefGoogle ScholarPubMed
Kessler, R. C., Chiu, W. T., Demler, O., Merikangas, K. R., & Walters, E. E. (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62(6), 617627. doi:10.1001/archpsyc.62.6.617CrossRefGoogle ScholarPubMed
Kinasz, K., Accurso, E. C., Kass, A. E., & Le Grange, D. (2016). Does sex matter in the clinical presentation of eating disorders in youth? Journal of Adolescent Health, 58(4), 410416. doi:10.1016/j.jadohealth.2015.11.005CrossRefGoogle ScholarPubMed
Klump, K. L., Culbert, K. M., Slane, J. D., Burt, S. A., Sisk, C. L., & Nigg, J. T. (2012). The effects of puberty on genetic risk for disordered eating: Evidence for a sex difference. Psychological Medicine, 42(3), 627637. doi:10.1017/s0033291711001541CrossRefGoogle ScholarPubMed
Lee, S. H., Ripke, S., Neale, B. M., Faraone, S. V., Purcell, S. M., Perlis, R. H., … Wray, N. R. (2013). Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nature Genetics, 45(9), 984994. doi:10.1038/ng.2711Google ScholarPubMed
Lilenfeld, L. R., Kaye, W. H., Greeno, C. G., Merikangas, K. R., Plotnicov, K., Pollice, C., … Nagy, L. (1998). A controlled family study of anorexia nervosa and bulimia nervosa: Psychiatric disorders in first-degree relatives and effects of proband comorbidity. Archives of General Psychiatry, 55(7), 603610. doi:10.1001/archpsyc.55.7.603CrossRefGoogle ScholarPubMed
Maier, R., Moser, G., Chen, G. B., Ripke, S., Coryell, W., Potash, J. B., … Lee, S. H. (2015). Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder. American Journal of Human Genetics, 96(2), 283294. doi:10.1016/j.ajhg.2014.12.006CrossRefGoogle ScholarPubMed
Martin, J., Hamshere, M. L., Stergiakouli, E., O'Donovan, M. C., & Thapar, A. (2014). Genetic risk for attention-deficit/hyperactivity disorder contributes to neurodevelopmental traits in the general population. Biological Psychiatry, 76(8), 664671. doi:10.1016/j.biopsych.2014.02.013CrossRefGoogle ScholarPubMed
Meier, S. M., Bulik, C. M., Thornton, L. M., Mattheisen, M., Mortensen, P. B., & Petersen, L. (2015). Diagnosed anxiety disorders and the risk of subsequent anorexia nervosa: A Danish population register study. European Eating Disorders Review, 23(6), 524530. doi:10.1002/erv.2402CrossRefGoogle ScholarPubMed
Micali, N., Daniel, R. M., Ploubidis, G. B., & De Stavola, B. L. (2018). Maternal prepregnancy weight status and adolescent eating disorder behaviors: A longitudinal study of risk pathways. Epidemiology (Cambridge, Mass.), 29(4), 579589. doi:10.1097/ede.0000000000000850CrossRefGoogle ScholarPubMed
Micali, N., De Stavola, B., Ploubidis, G., Simonoff, E., Treasure, J., & Field, A. E. (2015). Adolescent eating disorder behaviours and cognitions: Gender-specific effects of child, maternal and family risk factors. British Journal of Psychiatry, 207(4), 320327. doi:10.1192/bjp.bp.114.152371CrossRefGoogle ScholarPubMed
Micali, N., Hilton, K., Nakatani, E., Heyman, I., Turner, C., & Mataix-Cols, D. (2011). Is childhood OCD a risk factor for eating disorders later in life? A longitudinal study. Psychological Medicine, 41(12), 25072513. doi:10.1017/S003329171100078XCrossRefGoogle ScholarPubMed
Mistry, S., Harrison, J. R., Smith, D. J., Escott-Price, V., & Zammit, S. (2018). The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: A systematic review. Journal of Affective Disorders, 234, 148155. doi:10.1016/j.jad.2018.02.005CrossRefGoogle ScholarPubMed
Naylor, H., Mountford, V., & Brown, G. (2011). Beliefs about excessive exercise in eating disorders: The role of obsessions and compulsions. European Eating Disorders Review, 19(3), 226236. doi:10.1002/erv.1110CrossRefGoogle ScholarPubMed
Nolen-Hoeksema, S., & Watkins, E. R. (2011). A heuristic for developing transdiagnostic models of psychopathology: Explaining multifinality and divergent trajectories. Perspectives on Psychological Science, 6(6), 589609. doi:10.1177/1745691611419672CrossRefGoogle ScholarPubMed
O'Connor, S. M., Culbert, K. M., Mayhall, L. A., Burt, S. A., & Klump, K. L. (2020). Differences in genetic and environmental influences on body weight and shape concerns across pubertal development in females. Journal of Psychiatric Research, 121, 3946. doi:10.1016/j.jpsychires.2019.11.001CrossRefGoogle ScholarPubMed
Paternoster, L., Zhurov, A. I., Toma, A. M., Kemp, J. P., St Pourcain, B., Timpson, N. J., … Evans, D. M. (2012). Genome-wide association study of three-dimensional facial morphology identifies a variant in PAX3 associated with nasion position. American Journal of Human Genetics, 90(3), 478485. doi:10.1016/j.ajhg.2011.12.021CrossRefGoogle ScholarPubMed
Psychiatric GWAS Consortium Bipolar Disorder Working Group. (2011). Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nature Genetics, 43(10), 977983. doi:10.1038/ng.943CrossRefGoogle Scholar
Ripke, S., Neale, B. M., Corvin, A., Walters, J. T., Farh, K.-H., Holmans, P. A., … Huang, H. (2014). Biological insights from 108 schizophrenia-associated genetic loci. Nature, 511(7510), 421.Google Scholar
Ripke, S., O'Dushlaine, C., Chambert, K., Moran, J. L., Kahler, A. K., Akterin, S., … Sullivan, P. F. (2013). Genome-wide association analysis identifies 13 new risk loci for schizophrenia. Nature Genetics, 45(10), 11501159. doi:10.1038/ng.2742CrossRefGoogle ScholarPubMed
Rubenstein, C. S., Pigott, T. A., L'Heureux, F., Hill, J. L., & Murphy, D. L. (1992). A preliminary investigation of the lifetime prevalence of anorexia and bulimia nervosa in patients with obsessive compulsive disorder. Journal of Clinical Psychiatry, 53(9), 309314.Google ScholarPubMed
Ruscio, A. M., Stein, D. J., Chiu, W. T., & Kessler, R. C. (2010). The epidemiology of obsessive-compulsive disorder in the National Comorbidity Survey Replication. Molecular Psychiatry, 15(1), 5363. doi:10.1038/mp.2008.94CrossRefGoogle ScholarPubMed
Schaumberg, K., Zerwas, S., Goodman, E., Yilmaz, Z., Bulik, C. M., & Micali, N. (2019). Anxiety disorder symptoms at age 10 predict eating disorder symptoms and diagnoses in adolescence. Journal of Child Psychology and Psychiatry, 60(6), 686696. doi:10.1111/jcpp.12984CrossRefGoogle ScholarPubMed
Silberg, J. L., & Bulik, C. M. (2005). The developmental association between eating disorders symptoms and symptoms of depression and anxiety in juvenile twin girls. Journal of Child Psychology and Psychiatry, 46(12), 13171326. doi:10.1111/j.1469-7610.2005.01427.xCrossRefGoogle ScholarPubMed
Cross-Disorder Group of the Psychiatric Genomics Consortium, Smoller, J. W., Craddock, N., Kendler, K., Lee, P. H., Neale, B. M., … Sullivan, P. F. (2013). Identification of risk loci with shared effects on five major psychiatric disorders: A genome-wide analysis. Lancet (London, England), 381(9875), 1371. doi:10.1016/s0140-6736(12)62129-1.Google Scholar
Stice, E. (2016). Interactive and mediational etiologic models of eating disorder onset: Evidence from prospective studies. Annual Review of Clinical Psychology, 12, 359381. doi:10.1146/annurev-clinpsy-021815-093317CrossRefGoogle ScholarPubMed
Strober, M., Freeman, R., Lampert, C., & Diamond, J. (2007). The association of anxiety disorders and obsessive compulsive personality disorder with anorexia nervosa: Evidence from a family study with discussion of nosological and neurodevelopmental implications. International Journal of Eating Disorders, 40(Suppl), S46S51. doi:10.1002/eat.20429CrossRefGoogle ScholarPubMed
Swanson, S. A., Crow, S. J., Le Grange, D., Swendsen, J., & Merikangas, K. R. (2011). Prevalence and correlates of eating disorders in adolescents. Results from the national comorbidity survey replication adolescent supplement. Archives of General Psychiatry, 68(7), 714723. doi:10.1001/archgenpsychiatry.2011.22CrossRefGoogle ScholarPubMed
Swinbourne, J. M., & Touyz, S. W. (2007). The co-morbidity of eating disorders and anxiety disorders: A review. European Eating Disorders Review, 15(4), 253274. doi:10.1002/erv.784CrossRefGoogle ScholarPubMed
Torresan, R. C., Ramos-Cerqueira, A. T., Shavitt, R. G., do Rosario, M. C., de Mathis, M. A., Miguel, E. C., & Torres, A. R. (2013). Symptom dimensions, clinical course and comorbidity in men and women with obsessive-compulsive disorder. Psychiatry Research, 209(2), 186195. doi:10.1016/j.psychres.2012.12.006CrossRefGoogle ScholarPubMed
Voderholzer, U., Hessler, J. B., Naab, S., Fichter, M., Graetz, A., Greetfeld, M., … Schlegl, S. (2019). Are there differences between men and women in outcome of intensive inpatient treatment for anorexia nervosa? An analysis of routine data. European Eating Disorders Review, 27(1), 5966. doi:10.1002/erv.2624CrossRefGoogle ScholarPubMed
Watson, H. J., Yilmaz, Z., Thornton, L. M., Hubel, C., Coleman, J. R. I., Gaspar, H. A., … Bulik, C. M. (2019). Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nature Genetics, 51(8), 12071214. doi:10.1038/s41588-019-0439-2CrossRefGoogle ScholarPubMed
World Health Organization. (2008). The Global Burden of Disease: 2004 Update. Retrieved from https://www.who.int/healthinfo/global_burden_disease/GBD_report_2004update_full.pdf.Google Scholar
Wray, N. R., Lee, S. H., Mehta, D., Vinkhuyzen, A. A., Dudbridge, F., & Middeldorp, C. M. (2014). Research review: Polygenic methods and their application to psychiatric traits. Journal of Child Psychology and Psychiatry, 55(10), 10681087. doi:10.1111/jcpp.12295CrossRefGoogle ScholarPubMed
Yilmaz, Z., Halvorsen, M., Bryois, J., Yu, D., Thornton, L. M., Zerwas, S., … Crowley, J. J. (2020). Examination of the shared genetic basis of anorexia nervosa and obsessive-compulsive disorder. Molecular Psychiatry, 25(9), 20362046. doi:10.1038/s41380-018-0115-4CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Eating disorder, obsessive-compulsive disorder, and anxiety diagnostic and symptom-based constructs

Figure 1

Table 2. Prediction of eating disorder, obsessive-compulsive disorder, and anxiety symptom dimensions and diagnoses using polygenic scores in girlsa

Figure 2

Table 3. Prediction of eating disorder, obsessive-compulsive disorder, and anxiety symptom dimensions and diagnoses using polygenic scores in boysa

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