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Investigating the genetic architecture of general and specific psychopathology in adolescence

Research output: Contribution to journalArticle

Original languageEnglish
Article number145
Number of pages11
JournalTranslational Psychiatry
DateAccepted/In press - 15 Jun 2018
DatePublished (current) - 8 Aug 2018


Whilst associations between polygenic risk scores (PRSs) for schizophrenia and various phenotypic outcomes have been reported, an understanding of developmental pathways can only be gained by modelling comorbidity across psychopathology. We examine how genetic risk for schizophrenia relates to adolescent psychosis-related and internalizing psychopathology using a latent modelling approach, and compare this to genetic risk for other psychiatric disorders, to gain a more comprehensive understanding of the developmental pathways at this age. PRSs for schizophrenia, major depressive disorder, neuroticism and bipolar disorder were generated for individuals in the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. Multivariate linear regression was used to examine the relationships of these PRSs with psychopathology factors modelled within (i) a correlated factors structure and (ii) a bifactor structure. The schizophrenia PRS was associated with an increase in factors describing psychotic experiences, negative dimension, depression and anxiety, but, when modelling a general psychopathology factor based on these measures, specific effects above this persisted only for the negative dimension. Similar factor relationships were observed for the neuroticism PRS, with a (weak) specific effect only for anxiety once modelling general psychopathology. Psychopathology during adolescence can be described by a general psychopathology construct that captures common variance as well as by specific constructs capturing remaining non-shared variance. Schizophrenia risk genetic variants identified through genome-wide association studies mainly index negative rather than positive symptom psychopathology during adolescence. This has potentially important implications both for research and risk prediction in high-risk samples.

    Research areas

  • ALSPAC, Psychiatric epidemiology, Bifactor model, Structural equation model, Polygenic risk scores

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