Abstract
Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network.
Highlights
Schizophrenia is a severe mental disorder, affecting about 1% of the population worldwide
In this study we utilize gene expression data to identify genes involved in schizophrenia
We identified 2 co-expression modules that consistently relate to schizophrenia status in two independent data sets
Summary
Schizophrenia is a severe mental disorder, affecting about 1% of the population worldwide. Largescale, genome-wide studies have identified rare genomic microdeletions as well as common variants associated with the disease [2,3,4]. Purcell and colleagues demonstrated that data from genome-wide association studies (GWAS) for schizophrenia are compatible with a very large number of loci with common alleles (N.3,000), each with very small odds ratios (,1.05) contributing to disease susceptibility [5]. Additional approaches may be necessary to decipher the genetic basis of schizophrenia and related disorders [6]. Gene expression is an intermediate phenotype between gene sequence and complex traits and can facilitate the study of genetic variation and disease susceptibility [7]. Genome-wide gene expression profiling has been used to aid in the discovery of genes involved in human diseases and to discriminate between disease subtypes [8]
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