Genetic investigation of the contribution of body composition to anorexia nervosa in an electronic health record setting

Transl Psychiatry. 2022 Nov 19;12(1):486. doi: 10.1038/s41398-022-02251-y.


Anorexia nervosa (AN) is a psychiatric disorder defined by anthropometric symptoms, such as low body weight, and cognitive-behavioral symptoms, such as restricted eating, fear of weight gain, and distorted body image. Recent studies have identified a genetic association between AN and metabolic/anthropometric factors, including body mass index (BMI). Although the reported associations may be under pleiotropic genetic influences, they may represent independent risk factors for AN. Here we examined the independent contributions of genetic predisposition to low body weight and polygenic risk (PRS) for AN in a clinical population (Vanderbilt University Medical Center biobank, BioVU). We fitted logistic and linear regression models in a retrospective case-control design (123 AN patients, 615 age-matched controls). We replicated the genetic correlations between PRSBMI and AN (p = 1.12 × 10-3, OR = 0.96), but this correlation disappeared when controlling for lowest BMI (p = 0.84, OR = 1.00). Additionally, we performed a phenome-wide association analysis of the PRSAN and found that the associations with metabolic phenotypes were attenuated when controlling for PRSBMI. These findings suggest that the genetic association between BMI and AN may be a consequence of the weight-related diagnostic criteria for AN and that genetically regulated anthropometric traits (like BMI) may be independent of AN psychopathology. If so, individuals with cognitive-behavioral symptomatology suggestive of AN, but with a higher PRSBMI, may be under-diagnosed given current diagnostic criteria. Furthermore, PRSBMI may serve as an independent risk factor for weight loss and weight gain during recovery.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Anorexia Nervosa* / genetics
  • Anorexia Nervosa* / psychology
  • Body Composition
  • Electronic Health Records
  • Humans
  • Retrospective Studies
  • Weight Gain / genetics
  • Weight Loss