Genetic investigation of the contribution of body composition to anorexia nervosa in an electronic health record setting
Year: 2022
Type: article
Study design: Observational Study
Abstract: 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 PRSBMIand 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 PRSANand 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, PRSBMImay serve as an independent risk factor for weight loss and weight gain during recovery.
Source: Translational Psychiatry
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $4,590
Funders: U.S. Department of Health and Human Services, Vanderbilt University, Vanderbilt University Medical Center, Georgia Clinical and Translational Science Alliance, National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute of Mental Health, National Human Genome Research Institute, National Institute of General Medical Sciences, National Institute of Neurological Disorders and Stroke, National Center for Research Resources, National Center for Advancing Translational Sciences, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G1026292475, G1435936284, Pharmacogenomics of Arrhythmia Therapy, G1531600799, G1766209448, G1846282300, G2103760183, Understanding the genetic risk underlying racial disparities in uterine fibroids, G2615776415, G2683268942, Improving Prediction of Drug Action, G3395468139, G3619590958, G364208108, G3791753988, G3938985443, G4049315607, G4198746417, Automated Storage and Retrieval of Biological Systems, G4395870004, G4410787187, Overall: Eunice Kennedy Shriver Intellectual and Developmental Disabilities Research Center at Vanderbilt, G560889077, G5679716143, G5717004637, Genetic Epidemiology of Multiple Sclerosis, G6173849340, G6589054092, The Vanderbilt Institute for Clinical and Translational Research (VICTR) UL1, VESPA: Vanderbilt Electronic Systems for Pharmacogenomic Assessment, G7163342664, The Vanderbilt Institute for Clinical and Translational Research (VICTR), Vanderbilt Genome Electronic Records Project, Discovering Biology for Neuropsychiatric Diseases Through Omics Studies on Comorbidities, G8098630230, Epidemiologic Architecture for Genes Linked to Environment (EAGLE), G8332127685, Vanderbilt Institute for Clinical and Translational Research (VICTR)
OpenAlex ID: W4309563340