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Connectivity mapping uncovers small molecules that modulate neurodegeneration in Huntington's disease models.

journal contribution
posted on 01.08.2019, 15:52 by JL Smalley, C Breda, RP Mason, G Kooner, R Luthi-Carter, TW Gant, F Giorgini
Huntington's disease (HD) is a genetic disease caused by a CAG trinucleotide repeat expansion encoding a polyglutamine tract in the huntingtin (HTT) protein, ultimately leading to neuronal loss and consequent cognitive decline and death. As no treatments for HD currently exist, several chemical screens have been performed using cell-based models of mutant HTT toxicity. These screens measured single disease-related endpoints, such as cell death, but had low 'hit rates' and limited dimensionality for therapeutic detection. Here, we have employed gene expression microarray analysis of HD samples--a snapshot of the expression of 25,000 genes--to define a gene expression signature for HD from publically available data. We used this information to mine a database for chemicals positively and negatively correlated to the HD gene expression signature using the Connectivity Map, a tool for comparing large sets of gene expression patterns. Chemicals with negatively correlated expression profiles were highly enriched for protective characteristics against mutant HTT fragment toxicity in in vitro and in vivo models. This study demonstrates the potential of using gene expression to mine chemical activity, guide chemical screening, and detect potential novel therapeutic compounds. KEY MESSAGES: Single-endpoint chemical screens have low therapeutic discovery hit-rates. In the context of HD, we guided a chemical screen using gene expression data. The resulting chemicals were highly enriched for suppressors of mutant HTT fragment toxicity. This study provides a proof of concept for wider usage in all chemical screening.

Funding

Medical Research Council (MRC) Toxicology Unit and MRC New Investigator award (FG - G0700090).

History

Citation

Journal of Molecular Medicine, 2016, 94 (2), pp. 235-245

Author affiliation

/Organisation/COLLEGE OF LIFE SCIENCES/Biological Sciences/Neuroscience, Psychology and Behaviour

Version

VoR (Version of Record)

Published in

Journal of Molecular Medicine

eissn

1432-1440

Acceptance date

09/09/2015

Copyright date

2015

Available date

01/08/2019

Language

en