Evaluating the comparability of gene expression in blood and brain

Am J Med Genet B Neuropsychiatr Genet. 2006 Apr 5;141B(3):261-8. doi: 10.1002/ajmg.b.30272.

Abstract

The availability of an accessible tissue whose gene expression profile is similar to more inaccessible CNS tissues has the potential to advance research in neuropsychiatric disorders. We conducted secondary data analysis of transcriptional profiling of 79 human tissues for 33,698 genes using the Affymetrix U133A microarray augmented with a custom microarray (Affymetrix GNF1H), which were produced by the Genomics Institute of the Novartis Research Foundation (http://symatlas.gnf.org). Our analyses suggested that: (a) on a transcriptome level, whole blood shares significant gene expression similarities with multiple CNS tissues; (b) the median non-parametric correlation between transcripts present in both whole blood and CNS was around 0.5; (c) this correlation of 0.5 was intermediate relative to all tissues in the Novartis data set--less than for the maximum achievable value of 0.85, less than a set of immune tissues (0.64), comparable to a heterogeneous set of somatic tissues (0.57) but greater than muscle (0.48) and peripheral nervous system tissues (0.36); (d) about half of a set of candidate genes relevant to schizophrenia were expressed in both whole blood and prefrontal cortex; and (e) the expression levels of many classes of biologically relevant processes were not significantly different between whole blood and prefrontal cortex. These analyses suggest that gene expression in whole blood is neither perfectly correlated and useful nor perfectly uncorrelated and useless with gene expression in multiple brain tissues. This suggests that the cautious and thoughtful use of peripheral gene expression may be a useful surrogate for gene expression in the CNS when it has been determined that the relevant gene is expressed in both.

Publication types

  • Comparative Study

MeSH terms

  • Brain / metabolism*
  • Central Nervous System / metabolism
  • Cluster Analysis
  • Gene Expression Profiling*
  • Humans
  • Lymphocytes / metabolism*
  • Oligonucleotide Array Sequence Analysis / methods