Evaluation of common gene expression patterns in the rat nervous system

Abstract

In the postgenomic era, integrating data obtained from array technologies (e.g., oligonucleotide microarrays) with published information on eukaryotic genomes is beginning to yield biomarkers and therapeutic targets that are key for the diagnosis and treatment of disease. Nevertheless, identifying and validating these drug targets has not been a trivial task. Although a plethora of bioinformatics tools and databases are available, major bottlenecks for this approach reside in the interpretation of vast amounts of data, its integration into biologically representative models, and ultimately the identification of pathophysiologically and therapeutically useful information. In the field of neuroscience, accomplishing these goals has been particularly challenging because of the complex nature of nerve tissue, the relatively small adaptive nature of induced-gene expression changes, as well as the polygenic etiology of most neuropsychiatric diseases. This report combines published data sets from multiple transcript profiling studies that used GeneChip microarrays to illustrate a postanalysis approach for the interpretation of data from neuroscience microarray studies. By defining common gene expression patterns triggered by diverse events (administration of psychoactive drugs and trauma) in different nerve tissues (telencephalic brain areas and spinal cord), we broaden the conclusions derived from each of the original studies. In addition, the evaluation of the identified overlapping gene lists provides a foundation for generating hypotheses relating alterations in specific sets of genes to common physiological processes. Our approach demonstrates the significance of interpreting transcript profiling data within the context of common pathways and mechanisms rather than specific to a given tissue or stimulus. We also highlight the use of gene expression patterns in predictive biology (e.g., in toxicogenomics) as well as the utility of combining data derived from multiple microarray studies that examine diverse biological events for a broader interpretation of data from a particular microarray study.

Gene expression profiling of experimental traumatic spinal cord injury as a function of distance from impact site and injury severity

“…An association was derived by initially comparing expression profiles of two potassium channel genes [Kcncl2 (M59980), Kcnk1 (AF022819)] that were previously associated with CNS injuries in multiple array studies (25) with that of two potassium channel genes that showed marked downregulation in our data set [Kcnc2 (X62829), Kcnc1 (X62840); Kcnc1 was also selected for RT-PCR analysis, described below] (Fig. 4).…”

Metabotropic glutamate receptor‐mediated signaling in neuroglia

“…The expression of mGlu receptors is also altered by CNS trauma; group II mGlu receptors are reduced after spinal cord injury (SCI) and traumatic brain injury (TBI) (28, 103, 104), whereas mGlu1 receptors are increased rostral and caudal to the injury site following SCI and mGlu5 receptors are increased at the lesion site following TBI (52, 103). Recently, multipotential treatments have become more attractive therapeutic strategies for CNS injuries because the mechanism of such injuries is multi-factorial; therefore, therapies that serve to modulate multiple pathophysiological pathways may prove more effective than those directed at a single target(105).…”

Metabotropic Glutamate Receptors as Targets for Multipotential Treatment of Neurological Disorders

“…The expression of mGluRs are also altered by CNS trauma; Group II mGluRs are reduced after SCI and traumatic brain injury (TBI),6–8 whereas mGluR1 is increased rostral and caudal to the injury site following SCI, and mGluR5 remains unchanged 7…”