Analysis of brain disorders using DNA microarrays

Recent advances in DNA microarray technology have enabled researchers to simultaneously assess complex gene expression changes for tens of thousands of genes, making this an optimal approach for studying brain diseases. Discovered transcriptome changes are likely to reveal new information about the pathophysiology of disease states and identify novel genes that suggest previously unknown molecular interactions. In the years ahead, gene expression profiling may allow for the individualization of diagnosis, ultimately linking molecular phenotypes to the specific clinical profiles. Defining disease-specific transcriptome changes will also facilitate development of animal models that closely mimic common molecular events associated with schizophrenia, depression, autism or other mental disorders. In turn, this approach will lead to the improved application of pharmacogenomics, where compounds are screened for their ability to modulate the transcripts that are changed in a diagnosis-specific manner. In our recent studies using cDNA microarrays, we uncovered three types of altered gene expression patterns in the prefrontal cortex of individuals with schizophrenia when compared to matched controls. First, functional data mining led to the discovery of consistent decreases in several functional groups consisting of transcripts encoding proteins that regulate presynaptic function, neurotransmitter signaling and a restricted number of metabolic pathways. Second, we identified a number of known genes that showed consistently changed expression in schizophrenia and that had not been previously associated with schizophrenia. Finally, we also identified altered expression of several genes with no known function but with distinct brain expression patterns. Functional studies of these molecules are in progress. The combination of findings reveals the strengths of the gene microarray strategy to guide future studies for deciphering complex molecular defects in mental disorders.