Abstract
Psychosis spectrum disorder is a heterogeneous, multifactorial clinical phenotype, known to have a high heritability, only a minor portion of which can be explained by molecular measures of genetic variation. This study proposes that the identification of genetic variation underlying psychotic disorder may have suffered due to issues in the psychometric conceptualization of the phenotype. Here we aim to open a new line of research into the genetics of mental disorders by explicitly incorporating genes into symptom networks. Specifically, we investigate whether links between a polygenic risk score (PRS) for schizophrenia and measures of psychosis proneness can be identified in a network model. We analyzed data from n = 2180 subjects (controls, patients diagnosed with a non-affective psychotic disorder, and the first-degree relatives of the patients). A network structure was computed to examine associations between the 42 symptoms of the Community Assessment of Psychic Experiences (CAPE) and the PRS for schizophrenia. The resulting network shows that the PRS is directly connected to the spectrum of positive and depressive symptoms, with the items conspiracy and no future being more often located on predictive pathways from PRS to other symptoms. To our knowledge, the current exploratory study provides a first application of the network framework to the field of behavior genetics research. This allows for a novel outlook on the investigation of the relations between genome-wide association study-based PRSs and symptoms of mental disorders, by focusing on the dependencies among variables.
Highlights
Psychosis spectrum disorder is a potentially severe, heterogeneous, and multifactorial disorder (Keshavan et al, 2011; Guloksuz and van Os, 2017)
One possibility that has received scant attention is that the conceptualization of the phenotype may be suboptimal: typically, genetic studies use symptom counts or case–control designs that define cases and controls as polythetic functions of symptom data, defining the phenotype in a highly simplified fashion
Here we investigate whether links between polygenic risk score (PRS) for schizophrenia and measures of psychosis proneness can be identified in a network model, by including the PRS as a variable in the symptom network for psychosis spectrum disorder
Summary
Psychosis spectrum disorder is a potentially severe, heterogeneous, and multifactorial disorder (Keshavan et al, 2011; Guloksuz and van Os, 2017). One possibility that has received scant attention is that the conceptualization of the phenotype may be suboptimal: typically, genetic studies use symptom counts (e.g. total scores defined on questionnaire data) or case–control designs that define cases and controls as polythetic functions of symptom data (i.e. the definition of cases corresponds to many distinct symptom profiles), defining the phenotype in a highly simplified fashion These approaches assume that such compound scores are estimates of a single underlying dimension (e.g. a liability spectrum) that partly stands under genetic control (Franić et al, 2013). The current exploratory study provides a first application of the network framework to the field of behavior genetics research This allows for a novel outlook on the investigation of the relations between genome-wide association study-based PRSs and symptoms of mental disorders, by focusing on the dependencies among variables
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