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Meta- Analysis of positive and negative symptoms reveals schizophrenia modifier genes

  • Alexis C. Edwards
  • , Tim B. Bigdeli
  • , Anna R. Docherty
  • , Silviu Bacanu
  • , Donghyung Lee
  • , Teresa R. De Candia
  • , Arden Moscati
  • , Dawn L. Thiselton
  • , Brion S. Maher
  • , Brandon K. Wormley
  • , Dermot Walsh
  • , Francis A. O'neill
  • , Kenneth S. Kendler
  • , Brien P. Riley
  • , Ayman H. Fanous
  • Virginia Commonwealth University
  • University of Colorado Boulder
  • Health Diagnostic Laboratory Inc.
  • Johns Hopkins University
  • Health Research Board Ireland
  • Queen's University Belfast
  • VA Medical Center
  • Georgetown University

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

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 overrepresentation 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.

Original languageEnglish
Pages (from-to)279-287
Number of pages9
JournalSchizophrenia Bulletin
Volume42
Issue number2
DOIs
StatePublished - Mar 2016

Keywords

  • Clinical heterogeneity
  • Meta- Analysis
  • Modifier genes
  • Negative symptoms
  • Positive symptoms
  • Schizophrenia

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