Patterns of pain: Meta-analysis of microarray studies of pain

  • Lacroix-Fralish M
  • Austin J
  • Zheng F
 et al. 
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Abstract

Existing microarray gene expression profiling studies of tonic/chronic pain were subjected to meta-analysis to identify genes found to be regulated by these pain states in multiple, independent experiments. Twenty studies published from 2002 to 2008 were identified, describing the statistically significant regulation of 2254 genes. Of those, a total of 79 genes were found to be statistically significant "hits" in 4 or more independent microarray experiments, corresponding to a conservative P < 0.01 overall. Gene ontology-based functional annotation clustering analyses revealed strong evidence for regulation of immune-related genes in pain states. A multi-gene quantitative real-time polymerase chain reaction experiment was run on dorsal root ganglion (DRG) and spinal cord tissue from rats and mice given nerve (sciatic chronic constriction; CCI) or inflammatory (complete Freund's adjuvant) injury. We independently confirmed the regulation of 43 of these genes in the rat-CCI-DRG condition; the genetic correlates in all other conditions were largely and, in some cases, strikingly, independent. However, a handful of genes were identified whose regulation bridged etiology, anatomical locus, and/or species. Most notable among these were Reg3b (regenerating islet-derived 3 beta; pancreatitis-associated protein) and Ccl2 (chemokine [C-C motif] ligand 2), which were significantly upregulated in every condition in the rat. Gene expression profiling (microarray) studies of chronic pain were subjected to meta-analysis. Two genes were identified that are consistently upregulated in chronic pain states. © 2011 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Author-supplied keywords

  • Biomarkers
  • Gene chips
  • Gene expression
  • MCP-1
  • PAP

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Authors

  • Michael L. Lacroix-Fralish

  • Jean Sebastien Austin

  • Felix Y. Zheng

  • Daniel J. Levitin

  • Jeffrey S. Mogil

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