Translational PsychiatryGenomicsPeer-reviewed journal article
Phenotypic and Genetic Markers of Psychopathology in a Population-Based Sample of Older Adults
Arianna M. GardiD, Erin Bakshis WareiD, Luke Williamson HydeiD, Lauren SchmitziD, Jessica D. FauliD, Colter M. MitchelliD
Abstract
Although psychiatric phenotypes are hypothesized to organize into a two-factor internalizing - externalizing structure, few studies have evaluated the structure of psychopathology in older adults, nor explored whether genome-wide polygenic scores (PGSs) are associated with psychopathology in a domain-specific manner. We used data from 6,216 individuals of European ancestry from the Health and Retirement Study, a large population-based sample of older adults in the United States. Confirmatory factor analyses were applied to validated measures of psychopathology and PGSs were derived from well-powered GWAS. Genomic SEM was implemented to construct latent PGSs for internalizing, externalizing, and general psychopathology. Phenotypically, the data were best characterized by a single general factor of psychopathology, a factor structure that was replicated across genders and age groups. Although externalizing PGSs (cannabis use, antisocial behavior, alcohol dependence, ADHD) were not associated with any phenotypes, PGSs for MDD, neuroticism, and anxiety disorders were associated with both internalizing and externalizing phenotypes. Moreover, the latent internalizing PGS and the latent one-factor PGS, derived using weights from Genomic SEM, explained 1% more variance in the general factor of psychopathology than any of the individual PGSs. Results support the following conclusions: genetic risk factors for and phenotypic markers of psychiatric disorders are transdiagnostic in European ancestries, GWAS-derived PGSs fail to capture genetic variation associated with disease specificity in European ancestries, and blunt phenotypic measurement in GWAS may preclude our ability to evaluate the structure and specificity of genetic contributions to psychiatric disorders.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 7
- FWCI
- 0.71
- Field percentile
- top 34%
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