Novel Directions in Antipsychotic Target Identification using Gene Arrays

Authors: Palfreyman M.G.; Hook D.J.; Klimczak L.J.; Brockman J.A.; Evans D.M.; Altar C.Anthony

Source: Current Drug Targets-CNS & Neurological Disorders, Volume 1, Number 2, April 2002 , pp. 227-238(12)

Publisher: Bentham Science Publishers

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Abstract:

Schizophrenia is a major health problem that affects 2 million individuals in the United States. Antipsychotics offer considerable symptomatic relief and, although commonly discovered by screening with single biological targets, most interact with multiple receptors and signaling pathways. Considerable evidence from family and twin studies demonstrates genetic components and multiple chromosomal regions associated with schizophrenia. The polygenic nature of schizophrenia and multiple mechanisms for most effective agents indicate the need for broader approaches to target identification. Gene expression profiling of post-mortem human brain tissue simultaneously reveals the expression of many thousands of genes. A comparison of tissue from normals and patients provides a ‘disease signature’ of aberrantly expressed genes. ‘Drug signatures’ are the gene expression changes of cultured human or animal neurons treated with psychiatric drugs, and from animals chronically treated with these drugs. A selection of genes from disease and drug signatures can create a set of targets whose changes may better predict disease and its treatment by effective agents. This multi-parameter high throughput screening (MPHTSSM) approach evaluates the mRNA expression pattern of cultured cells exposed to candidate compounds. Compounds that normalize genes altered in schizophrenia may better address its underlying causes. Drugs that mimic gene expression changes that are consistently altered by effective antipsychotic agents provide a drug improvement strategy if efficacy is enhanced or side effects are attenuated.

Keywords: antipsychotic target; schizophrenia; gene expression; gene markers; gene mapping; gene signatures; linkage disequilibrium; microarray; snps

Language: English

Document Type: Review article

DOI: 10.2174/1568007024606203

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