Background: The value of the nosological distinction between non-affective and affective psychosis has consistently been challenged. Indeed, psychotic syndromes are composed of dimensions of psychopathology cutting across diagnostic boundaries. Such transdiagnostic symptom dimensions might be enhanced phenotypes to test for association with common genetic variants for Major Mental Disorders (MMDs) as summarized by Polygenic Risk Scores (PRSs) for Schizophrenia (SZ), Bipolar Disorder (BP), and Major Depressive Disorder (MDD). The objectives of this study were to: 1) identify the symptom dimension structure at First Episode Psychosis (FEP); 2) examine the extent to which MMDs PRSs explain the phenotypic variance due to symptom dimensions. Methods: OPCRIT psychopathology items were analysed using multidimensional item response modelling in Mplus to estimate unidimensional, multidimensional, and bi-factor models of psychosis. Model fit statistics included LogLikelihood, and Akaike and Bayesian Information Criteria to compare these models. SZ, BP, and MDD PRSs were built using the results from large mega-analyses from the Working Groups of the Psychiatric Genomics Consortium. In PRSice, individuals’ number of risk alleles in the target sample was weighted by the log odds ratio from the discovery samples, and summed into the three PRSs for SZ, BP, and MDD. These PRSs were calculated at a fixed 0.05 P-value SNP threshold. Regression models were fitted to predict symptom dimensions’ scores as continuous outcomes from the three PRSs. These model, conducted in STATA14, were adjusted for age, gender, and 20 principal components for population stratification. Results: The best model fit statistics was observed for the bi-factor model including one general and five specific dimensions of positive, negative, disorganization, manic and depressive symptoms. A positive linear association was observed between SZ PRS and the positive dimension t(789)=2.04, p<0.05); and between BIP PRS and the manic dimension t(789)=2.46, p<0.05). A negative association was observed between MDD PRS and the manic dimension t(789)=2.14, p<0.05). Discussion: Our results suggest that: a) the symptom dimension structure at FEP is best represented by the bi-factor model; b) positive symptoms are more common among FEP patients with a high SZ PRS; c) manic symptoms are more common in FEP patients with a high BP PRS, and less common in FEP patients with high MDD PRS; c) no associations were observed between PRSs and the general dimension. Despite the need to both replicate these findings also using PGC new released GWAS to build better powered PRSs,psychosis symptom dimensions have been shown to be useful and valid enhanced phenotypes across the psychosis spectrum.

Quattrone, D., Reininghaus, U., Vassos, E., Sham, P., Ferraro, L., Tripoli, G., et al. (2019). F115POLYGENIC RISK SCORES FOR SCHIZOPHRENIA, BIPOLAR, AND MAJOR DEPRESSIVE DISORDERS PREDICT TRANSDIAGNOSTIC SYMPTOM DIMENSIONS AT FIRST EPISODE PSYCHOSIS. EUROPEAN NEUROPSYCHOPHARMACOLOGY, 29, S1172-S1173 [10.1016/j.euroneuro.2018.08.195].

F115POLYGENIC RISK SCORES FOR SCHIZOPHRENIA, BIPOLAR, AND MAJOR DEPRESSIVE DISORDERS PREDICT TRANSDIAGNOSTIC SYMPTOM DIMENSIONS AT FIRST EPISODE PSYCHOSIS

Ferraro, Laura;Tripoli, Giada;
2019

Abstract

Background: The value of the nosological distinction between non-affective and affective psychosis has consistently been challenged. Indeed, psychotic syndromes are composed of dimensions of psychopathology cutting across diagnostic boundaries. Such transdiagnostic symptom dimensions might be enhanced phenotypes to test for association with common genetic variants for Major Mental Disorders (MMDs) as summarized by Polygenic Risk Scores (PRSs) for Schizophrenia (SZ), Bipolar Disorder (BP), and Major Depressive Disorder (MDD). The objectives of this study were to: 1) identify the symptom dimension structure at First Episode Psychosis (FEP); 2) examine the extent to which MMDs PRSs explain the phenotypic variance due to symptom dimensions. Methods: OPCRIT psychopathology items were analysed using multidimensional item response modelling in Mplus to estimate unidimensional, multidimensional, and bi-factor models of psychosis. Model fit statistics included LogLikelihood, and Akaike and Bayesian Information Criteria to compare these models. SZ, BP, and MDD PRSs were built using the results from large mega-analyses from the Working Groups of the Psychiatric Genomics Consortium. In PRSice, individuals’ number of risk alleles in the target sample was weighted by the log odds ratio from the discovery samples, and summed into the three PRSs for SZ, BP, and MDD. These PRSs were calculated at a fixed 0.05 P-value SNP threshold. Regression models were fitted to predict symptom dimensions’ scores as continuous outcomes from the three PRSs. These model, conducted in STATA14, were adjusted for age, gender, and 20 principal components for population stratification. Results: The best model fit statistics was observed for the bi-factor model including one general and five specific dimensions of positive, negative, disorganization, manic and depressive symptoms. A positive linear association was observed between SZ PRS and the positive dimension t(789)=2.04, p<0.05); and between BIP PRS and the manic dimension t(789)=2.46, p<0.05). A negative association was observed between MDD PRS and the manic dimension t(789)=2.14, p<0.05). Discussion: Our results suggest that: a) the symptom dimension structure at FEP is best represented by the bi-factor model; b) positive symptoms are more common among FEP patients with a high SZ PRS; c) manic symptoms are more common in FEP patients with a high BP PRS, and less common in FEP patients with high MDD PRS; c) no associations were observed between PRSs and the general dimension. Despite the need to both replicate these findings also using PGC new released GWAS to build better powered PRSs,psychosis symptom dimensions have been shown to be useful and valid enhanced phenotypes across the psychosis spectrum.
Settore MED/25 - Psichiatria
World Congress of Psychiatric Genetics (WCPG)
Glasgow, SCOTLAND
OCT 11-15, 2018
26th
Quattrone, D., Reininghaus, U., Vassos, E., Sham, P., Ferraro, L., Tripoli, G., et al. (2019). F115POLYGENIC RISK SCORES FOR SCHIZOPHRENIA, BIPOLAR, AND MAJOR DEPRESSIVE DISORDERS PREDICT TRANSDIAGNOSTIC SYMPTOM DIMENSIONS AT FIRST EPISODE PSYCHOSIS. EUROPEAN NEUROPSYCHOPHARMACOLOGY, 29, S1172-S1173 [10.1016/j.euroneuro.2018.08.195].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/401323
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