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Genome-wide expression profiling of schizophrenia using a large combined cohort
Borealis
Mistry, Meeta; Gillis, Jesse; Pavlidis, Paul — 2019-03-05 Numerous studies have examined gene expression profiles in post-mortem human brain samples from individuals with schizophrenia compared to healthy controls, to gain insight into the molecular mechanisms of the disease. While some findings have been replicated across studies,there is a general lack of consensus of which genes or pathways are affected. It has been unclear if these differences are due to the underlying cohorts, or methodological considerations. Here we present the most comprehensive analysis to date of expression patterns in the prefrontal cortex of schizophrenic compared to unaffected controls. Using data from seven independent studies, we assembled a data set of 153 affected and 153 control individuals. Remarkably, we identified expression differences in the brains of schizophrenics that are validated by up to seven laboratories using independent cohorts. Our combined analysis revealed a signature of 39 probes that are up-regulated in schizophrenia and 86 down-regulated. Some of these genes were previously identified in studies that were not included in our analysis, while others are novel to our analysis. In particular, we observe gene expression changes associated with various aspects of neuronal communication, and alterations of processes affected as a consequence of changes in synaptic functioning. A gene network analysis predicted previously unidentified functional relationships among the signature genes. Our results provide evidence for a common underlying expression signature in this heterogeneous disorder.
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A cross-laboratory comparison of expression profiling data from normal human postmortem brain
Borealis
Mistry, Meeta; Pavlidis, Paul — 2019-03-11 Expression profiling of post-mortem human brain tissue has been widely used to study molecular changes associated with neuropsychiatric diseases as well as normal processes such as aging. Changes in expression associated with factors such as age, gender or postmortem interval are often more pronounced than changes associated with disease. Therefore in addition to being of interest in their own right, careful consideration of these effects are important in the interpretation of disease studies. We performed a large meta-analysis of genome-wide expression studies of normal human cortex to more fully catalogue the effects of age, gender, postmortem interval and brain pH, yielding a "meta-signature" of gene expression changes for each factor. We validated our results by showing a significant overlap with independent gene lists extracted from the literature. Importantly, meta-analysis identifies genes which are not significant in any individual study. Finally, we show that many schizophrenia candidate genes appear in the meta-signatures, reinforcing the idea that studies must be carefully controlled for interactions between these factors and disease. In addition to the inherent value of the meta-signatures, our results provide critical information for future studies of disease effects in the human brain.

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(Author: Mistry, Meeta)

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