Mapping anorexia nervosa genes to clinical phenotypes

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Eating Disorders Working Group of the Psychiatric Genomics Consortium - (Author)
  • Jessica S. Johnson - , Icahn School of Medicine at Mount Sinai (Author)
  • Alanna C. Cote - , Icahn School of Medicine at Mount Sinai (Author)
  • Amanda Dobbyn - , Icahn School of Medicine at Mount Sinai (Author)
  • Laura G. Sloofman - , Icahn School of Medicine at Mount Sinai (Author)
  • Jiayi Xu - , Icahn School of Medicine at Mount Sinai (Author)
  • Liam Cotter - , Icahn School of Medicine at Mount Sinai (Author)
  • Alexander W. Charney - , Icahn School of Medicine at Mount Sinai, US Department of Veterans Affairs (Author)
  • Andreas Birgegård - , Karolinska Institutet (Author)
  • Jennifer Jordan - , University of Otago (Author)
  • Martin Kennedy - , University of Otago (Author)
  • Mikaél Landén - , Karolinska Institutet, University of Gothenburg (Author)
  • Sarah L. Maguire - , University of Sydney (Author)
  • Nicholas G. Martin - , Queensland Institute of Medical Research (Author)
  • Preben Bo Mortensen - , The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University (Author)
  • Laura M. Thornton - , University of North Carolina at Chapel Hill (Author)
  • Cynthia M. Bulik - , Karolinska Institutet, University of North Carolina at Chapel Hill (Author)
  • Laura M. Huckins - , Icahn School of Medicine at Mount Sinai, US Department of Veterans Affairs (Author)

Abstract

Background Anorexia nervosa (AN) is a psychiatric disorder with complex etiology, with a significant portion of disease risk imparted by genetics. Traditional genome-wide association studies (GWAS) produce principal evidence for the association of genetic variants with disease. Transcriptomic imputation (TI) allows for the translation of those variants into regulatory mechanisms, which can then be used to assess the functional outcome of genetically regulated gene expression (GReX) in a broader setting through the use of phenome-wide association studies (pheWASs) in large and diverse clinical biobank populations with electronic health record phenotypes. Methods Here, we applied TI using S-PrediXcan to translate the most recent PGC-ED AN GWAS findings into AN-GReX. For significant genes, we imputed AN-GReX in the Mount Sinai BioMe™ Biobank and performed pheWASs on over 2000 outcomes to test the clinical consequences of aberrant expression of these genes. We performed a secondary analysis to assess the impact of body mass index (BMI) and sex on AN-GReX clinical associations. Results Our S-PrediXcan analysis identified 53 genes associated with AN, including what is, to our knowledge, the first-genetic association of AN with the major histocompatibility complex. AN-GReX was associated with autoimmune, metabolic, and gastrointestinal diagnoses in our biobank cohort, as well as measures of cholesterol, medications, substance use, and pain. Additionally, our analyses showed moderation of AN-GReX associations with measures of cholesterol and substance use by BMI, and moderation of AN-GReX associations with celiac disease by sex. Conclusions Our BMI-stratified results provide potential avenues of functional mechanism for AN-genes to investigate further.

Details

Original languageEnglish
Pages (from-to)2619-2633
Number of pages15
JournalPsychological medicine
Volume53
Issue number6
Publication statusPublished - 5 Apr 2023
Peer-reviewedYes

External IDs

WOS 000778891100001
Scopus 85128406545
PubMed 35379376
ORCID /0000-0003-2132-4445/work/192582981

Keywords

Keywords

  • Anorexia nervosa, EHR, pheWAS, PrediXcan, transcriptomic imputation