Background: Recent evidence suggests that psychiatric symptoms share a common genetic liability across diagnostic categories. The present study investigated the effects of variants within previously identified relevant genes on specific symptom clusters, independently from the diagnosis. Methods: 1550 subjects affected by Schizophrenia (SCZ), Major Depressive Disorder or Bipolar Disorder were included. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Hamilton Depression Rating Scale (HDRS). Principal component analysis and a further clinical refinement were used to define symptom clusters. Clusters scores were tested for association with 46 genetic variants within nine genes previously linked to one or more major psychiatric disorders by large genome wide association studies (ANK3, CACNA1C, CACNB2, FKBP5, FZD3, GRM7, ITIH3, SYNE1, TCF4). Exploratory analyses were performed in each disorder separately to further elucidate the SNPs effects. Results: five PANSS clusters (Negative; Impulsiveness; Cognitive; Psychotic; Depressive) and four HDRS clusters (Core Depressive; Somatic; Psychotic-like; Insomnia) were identified. CACNA1C rs11615998 was associated with HDRS Psychotic cluster in the whole sample. In the SCZ sample, CACNA1C rs11062296 was associated with PANSS Impulsiveness cluster and CACNA1C rs2238062 was associated with PANSS negative cluster. Discussion: CACNA1C rs11615998 was associated with psychotic symptoms (C-allele carriers have decreased psychotic-risk) independently from the diagnosis, in line with the evidence of a cross disorder effect of many risk variants. This gene was previously associated with SCZ and cross-disorder liability to psychiatric disorders. Our findings confirmed that deep phenotyping is pivotal to clarify the role of genetic variants on symptoms patterns.

Genetic variants associated with psychotic symptoms across psychiatric disorders

Calabro M.;Crisafulli C.;
2020

Abstract

Background: Recent evidence suggests that psychiatric symptoms share a common genetic liability across diagnostic categories. The present study investigated the effects of variants within previously identified relevant genes on specific symptom clusters, independently from the diagnosis. Methods: 1550 subjects affected by Schizophrenia (SCZ), Major Depressive Disorder or Bipolar Disorder were included. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Hamilton Depression Rating Scale (HDRS). Principal component analysis and a further clinical refinement were used to define symptom clusters. Clusters scores were tested for association with 46 genetic variants within nine genes previously linked to one or more major psychiatric disorders by large genome wide association studies (ANK3, CACNA1C, CACNB2, FKBP5, FZD3, GRM7, ITIH3, SYNE1, TCF4). Exploratory analyses were performed in each disorder separately to further elucidate the SNPs effects. Results: five PANSS clusters (Negative; Impulsiveness; Cognitive; Psychotic; Depressive) and four HDRS clusters (Core Depressive; Somatic; Psychotic-like; Insomnia) were identified. CACNA1C rs11615998 was associated with HDRS Psychotic cluster in the whole sample. In the SCZ sample, CACNA1C rs11062296 was associated with PANSS Impulsiveness cluster and CACNA1C rs2238062 was associated with PANSS negative cluster. Discussion: CACNA1C rs11615998 was associated with psychotic symptoms (C-allele carriers have decreased psychotic-risk) independently from the diagnosis, in line with the evidence of a cross disorder effect of many risk variants. This gene was previously associated with SCZ and cross-disorder liability to psychiatric disorders. Our findings confirmed that deep phenotyping is pivotal to clarify the role of genetic variants on symptoms patterns.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11570/3163718
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