Original Article

Neuropsychopharmacology (2010) 35, 473–482; doi:10.1038/npp.2009.151; published online 14 October 2009

The Stanley Neuropathology Consortium Integrative Database: a Novel, Web-Based Tool for Exploring Neuropathological Markers in Psychiatric Disorders and the Biological Processes Associated with Abnormalities of Those Markers

Sanghyeon Kim1 and Maree J Webster1

1Stanley Brain Research Laboratory, Stanley Medical Research Institute, Medical Center Drive, Rockville, MD, USA

Correspondence: Dr MJ Webster, Laboratory of Brain Research, Stanley Medical Research Institute, 9800 Medical Center Drive, Rockville, MD 20850, USA, Tel: +1 240 499 1171, Fax: +1 301 251 8602, E-mail: websterm@stanleyresearch.org

Received 28 May 2009; Revised 17 August 2009; Accepted 17 August 2009; Published online 14 October 2009.

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Abstract

An integrative database, Stanley Neuropathology Consortium Integrative Database (SNCID) (http://sncid.stanleyresearch.org), has been developed to facilitate psychiatric research. The SNCID includes 1749 neuropathological markers measured in 12 different brain regions in 60 human subjects (15 each schizophrenia, bipolar disorder, depression, and unaffected controls). Genome-wide expression microarray datasets from three independent studies are also included. Statistical analysis tools such as variance analysis, correlation analysis, and functional annotation tools have been integrated into the database. In this report, we first replicate an earlier correlation analysis between genome-wide expression profiles and an abnormal cytoarchitectural marker using the SNCID. We then show the potential for identifying neuropathological markers that are abnormal in subjects with psychiatric disorders. We also identify biological pathways associated with several abnormal neuropathological markers, including those in the dopamine, glutamate, Reelin, and italic gamma-aminobutyric acid (GABA)ergic systems. Data exploration using the SNCID may provide insights into the biological pathways associated with the neurotransmitter abnormalities identified in subjects with major psychiatric disorders.

Keywords:

database, schizophrenia, bipolar disorder, depression, expression profile, molecular mechanisms

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