Correlation of receptor density and mRNA expression patterns in the human cerebral cortex

Neuroimage. 2022 Aug 1:256:119214. doi: 10.1016/j.neuroimage.2022.119214. Epub 2022 Apr 19.

Abstract

Changes in distribution of associated molecular targets have been reported across several neuropsychiatric disorders. However, the high-resolution topology of most proteins is unknown and simultaneous in vivo measurement in multi-receptor systems is complicated. To account for the missing proteomic information, messenger ribonucleic acid (mRNA) transcripts are typically used as a surrogate. Nonetheless, post-transcriptional and post-translational processes might cause the discrepancy between the final distribution of proteins and gene expression patterns. Therefore, this study aims to investigate ex vivo links between mRNA expression and corresponding receptor density in the human cerebral cortex. To this end, autoradiography data on the density of 15 different receptors in 38 brain regions were correlated with the expression patterns of 50 associated genes derived from microarray data (mA), RNA sequencing data (RNA-Seq) provided by the Allen Human Brain Atlas and predicted mRNA expression patterns (pred-mRNA). Spearman's rank correlation was used to evaluate the possible links between proteomic data and mRNA expression patterns. Correlations between mRNA and protein density varied greatly between targets: Positive associations were found for e.g. the serotonin 1A (pred-mRNA: rs = 0.708; mA: rs = 0.601) or kainate receptor (pred-mRNA: rs = 0.655; mA: rs = 0.601; RNA-Seq: rs = 0.575) as well as a few negative associations e.g. γ-Aminobutyric acid (GABA) A receptor subunit α3 (pred-mRNA: rs = -0.638; mA: rs = -0.619) or subunit α5 (pred-mRNA: rs = -0.565; mA: rs = -0.563), while most of the other investigated target receptors showed low correlations. The high variability in the correspondence of mRNA expression and receptor spatial distribution warrants caution when inferring the topology of molecular targets in the brain from transcriptome data. This not only highlights the longstanding value of molecular imaging but also indicates a need for comprehensive proteomic studies.

Keywords: Allen human brain atlas; Gene expression topology; Receptor autoradiography; Transcriptome.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Autoradiography
  • Brain / metabolism
  • Cerebral Cortex* / diagnostic imaging
  • Cerebral Cortex* / metabolism
  • Gene Expression Profiling
  • Humans
  • Proteomics* / methods
  • RNA, Messenger* / genetics
  • RNA, Messenger* / metabolism
  • Receptors, Cell Surface / genetics
  • Receptors, Cell Surface / metabolism
  • Receptors, GABA-A / metabolism

Substances

  • RNA, Messenger
  • Receptors, Cell Surface
  • Receptors, GABA-A