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Schizophr Bull. 2016 Mar;42(2):279-87. doi: 10.1093/schbul/sbv119. Epub 2015 Aug 27.

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

Author information

1
Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA; alexis.edwards@vcuhealth.org.
2
Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA;
3
Department of Psychology and Neuroscience, University of Colorado, Boulder, CO; Institute for Behavioral Genetics, University of Colorado, Boulder, CO;
4
Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD;
5
Health Research Board, Dublin, Ireland;
6
Centre for Public Health, Institute of Clinical Sciences, Queen's University Belfast, Belfast, UK;
7
Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA; Mental Health Service Line, Washington VA Medical Center, Washington, DC; Department of Psychiatry, Georgetown University School of Medicine, Washington, DC.

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.

KEYWORDS:

clinical heterogeneity; meta-analysis; modifier genes; negative symptoms; positive symptoms; schizophrenia

PMID:
26316594
PMCID:
PMC4753595
[Available on 2017-03-01]
DOI:
10.1093/schbul/sbv119
[Indexed for MEDLINE]
Free PMC Article

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