Dataset Information

Meta-analysis of Positive and Negative Symptoms Reveals Schizophrenia Modifier Genes.

ABSTRACT: BACKGROUND:Evidence suggests that genetic factors may influence both schizophrenia (Scz) and its clinical presentation. In recent years, genome-wide association studies (GWAS) have demonstrated considerable success in identifying risk loci. Detection of "modifier loci" has the potential to further elucidate underlying disease processes. METHODS:We performed GWAS of empirically derived positive and negative symptom scales in Irish cases from multiply affected pedigrees and a larger, independent case-control sample, subsequently combining these into a large Irish meta-analysis. In addition to single-SNP associations, we considered gene-based and pathway analyses to better capture convergent genetic effects, and to facilitate biological interpretation of these findings. Replication and testing of aggregate genetic effects was conducted using an independent European-American sample. RESULTS:Though no single marker met the genome-wide significance threshold, genes and ontologies/pathways were significantly associated with negative and positive symptoms; notably, NKAIN2 and NRG1, respectively. We observed limited overlap in ontologies/pathways associated with different symptom profiles, with immune-related categories over-represented for negative symptoms, and addiction-related categories for positive symptoms. Replication analyses suggested that genes associated with clinical presentation are generalizable to non-Irish samples. CONCLUSIONS:These findings strongly support the hypothesis that modifier loci contribute to the etiology of distinct Scz symptom profiles. The finding that previously implicated "risk loci" actually influence particular symptom dimensions has the potential to better delineate the roles of these genes in Scz etiology. Furthermore, the over-representation of distinct gene ontologies/pathways across symptom profiles suggests that the clinical heterogeneity of Scz is due in part to complex and diverse genetic factors.

SUBMITTER: Edwards AC

PROVIDER: S-EPMC4753595 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Meta-analysis of Positive and Negative Symptoms Reveals Schizophrenia Modifier Genes.

Edwards Alexis C AC Bigdeli Tim B TB Docherty Anna R AR Bacanu Silviu S Lee Donghyung D de Candia Teresa R TR Moscati Arden A Thiselton Dawn L DL Maher Brion S BS Wormley Brandon K BK Walsh Dermot D O'Neill Francis A FA Kendler Kenneth S KS Riley Brien P BP Fanous Ayman H AH

Schizophrenia bulletin 20150827 2

<h4>Background</h4>Evidence suggests that genetic factors may influence both schizophrenia (Scz) and its clinical presentation. In recent years, genome-wide association studies (GWAS) have demonstrated considerable success in identifying risk loci. Detection of "modifier loci" has the potential to further elucidate underlying disease processes.<h4>Methods</h4>We performed GWAS of empirically derived positive and negative symptom scales in Irish cases from multiply affected pedigrees and a larger ...[more]

PMID: 26316594

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Project description:Autism spectrum disorder (ASD) and schizophrenia (SZ) are heterogenous neurodevelopmental disorders that overlap in symptom presentation. The purpose of this study was to specify overlapping symptom domains and to identify symptoms that can reliably differentiate adults with ASD (n = 53), SZ (n = 39), and typical development (TD; n = 40). All participants regardless of diagnosis were administered gold-standard diagnostic assessments of ASD and SZ characteristics including the Autism Diagnostic Observation Schedule (ADOS-2) and the Positive and Negative Syndrome Scale (PANSS). Sensitivity and specificity of the ADOS were assessed using diagnostic cut-off scores. The degree of symptom overlap on these measures between participant groups was analyzed using Analyses of Variance (ANOVAs), Receiver Operating Characteristic (ROC) Curves, and Analyses of Covariance (ANCOVAs) to control for group differences in IQ and sex distributions. The ADOS reliably discriminated ASD and TD adults, but there was a high rate of "false positives" in SZ patients who did not meet the DSM-5 criteria for ASD. To identify the reasons for low specificity in the SZ sample, we categorized ASD and SZ symptoms into 'positive' (presence of atypical behaviors) and 'negative' (absence of typical behaviors) symptoms. ASD and SZ groups overlapped on negative symptoms largely related to the absence of typical social and communicative behaviors, whereas disorder-specific positive symptoms differentiated ASD and SZ. For example, those with ASD scored higher on restricted and repetitive behaviors and stereotyped language, whereas those with SZ scored higher on psychotic symptoms such as delusions and hallucinations. These results suggest that, when making a differential diagnosis between ASD and SZ, clinicians may benefit from focusing on the presence or absence of positive ASD and SZ symptoms. Standardized measures to classify ASD symptoms into positive and negative symptoms have not yet been developed but represent a potentially viable clinical tool.

Dataset Information

Meta-analysis of Positive and Negative Symptoms Reveals Schizophrenia Modifier Genes.

Publications

Meta-analysis of Positive and Negative Symptoms Reveals Schizophrenia Modifier Genes.

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