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Mccullumsmith, R. E.

Publications and source records attributed to Mccullumsmith, R. E..

2 recordsLinked to original sources

Identification of activity-dependent EGR3 target genes reveals genes associated with DNA damage response and schizophrenia

Bioinformatics and network studies have identified the immediate early gene transcription factor early growth response 3 (EGR3) as a master regulator of genes differentially expressed in the brains of patients with neuropsychiatric illnesses ranging from schizophrenia and bipolar disorder to Alzheimers disease. However, few studies have identified and validated Egr3-dependent genes in the mammalian brain. We have previously shown that Egr3 is required for stress-responsive behavior, memory, and hippocampal long-term depression in mice. To identify Egr3-dependent genes that may regulate these processes, we conducted an expression microarray on hippocampi from wildtype (WT) and Egr3-/- mice following electroconvulsive seizure (ECS), a stimulus that induces maximal expression of immediate early genes including Egr3. We identified 71 genes that were differentially expressed between WT and Egr3-/- mice one hour following ECS. Bioinformatic analyses showed that many of these are altered in schizophrenia. Ingenuity pathway analysis revealed the GADD45 (growth arrest and DNA-damage-inducible) family (Gadd45b, Gadd45g) as the leading category of differentially expressed genes. Together with differentially expressed genes in the AP-1 transcription factor family genes (Fos, Fosb), and the centromere organization protein Cenpa, these results revealed that Egr3 is required for activity-dependent expression of genes involved in the DNA damage response. Our findings implicate EGR3 as gene critical for the expression of genes that are disrupted in schizophrenia and reveal a novel requirement for EGR3 in the expression of genes involved in activity-induced DNA damage response.

neuroscience

Integrative Omics for Informed Drug Repurposing: Targeting CNS Disorders

The treatment of CNS disorders, and in particular psychiatric illnesses, lacks disease-altering therapeutics for many conditions. This is likely due to regulatory challenges involving the high cost and slow-pace of drug development for CNS disorders as well as due to limited understanding of disease causality. Repurposing drugs for new indications have lower cost and shorter development timeline compared to that of de novo drug development. Historically, empirical drug-repurposing is a standard practice in psychiatry; however, recent advances in characterizing molecules with their structural and transcriptomic signatures along with ensemble of data analysis approaches, provides informed and cost-effective repurposing strategies that ameliorate the regulatory challenges. In addition, the potential to incorporate ontological approaches along with signature-based repurposing techniques addresses the various knowledge-based challenges associated with CNS drug development. In this review we primarily discuss signature-based in silico approaches to drug repurposing, and its integration with data science platforms for evidence-based drug repurposing. We contrast various in silico and empirical approaches and discuss possible avenues to improve the clinical relevance. These concepts provide a promising new translational avenue for developing new therapies for difficult to treat disorders, and offer the possibility of connecting drug discovery platforms and big data analytics with personalized disease signatures.

neuroscience