Do Corticosteroid Receptor mRNA Levels Predict the Expression of Their Target Genes?
Lisa L KoorneefEva M G VihoLucas F WahlOnno C MeijerPublished in: Journal of the Endocrine Society (2022)
The glucocorticoid stress hormones affect brain function via high-affinity mineralocorticoid receptors (MRs) and lower-affinity glucocorticoid receptors (GRs). MR and GR not only differ in affinity for ligands, but also have distinct, sometimes opposite, actions on neuronal excitability and other cellular and higher-order parameters related to cerebral function. GR and MR messenger RNA (mRNA) levels are often used as a proxy for the responsiveness to glucocorticoids, assuming proportionality between mRNA and protein levels. This may be especially relevant for the MR, which because of its high affinity is already largely occupied at low basal (trough) hormone levels. Here we explore how GR and MR mRNA levels are associated with the expression of a shared target gene, glucocorticoid-induced leucine zipper (GILZ, coded by Tsc22d3 ) with basal and elevated levels of corticosterone in male mice, using in situ hybridization. Depending on the hippocampal subfield and the corticosterone levels, mRNA levels of MR rather than GR mostly correlated with GILZ mRNA in the hippocampus and hypothalamus at the bulk tissue level. At the individual cell level, these correlations were much weaker. Using publicly available single-cell RNA sequencing data, we again observed that MR and GR mRNA levels were only weakly correlated with target gene expression in glutamatergic and GABAergic neurons. We conclude that MR mRNA levels can be limiting for receptor action, but many other cell-specific and region-specific factors ultimately determine corticosteroid receptor action. Altogether, our results argue for caution while interpreting the consequences of changed receptor expression for the response to glucocorticoids.
Keyphrases
- single cell
- binding protein
- gene expression
- magnetic resonance
- contrast enhanced
- poor prognosis
- magnetic resonance imaging
- spinal cord injury
- genome wide
- mass spectrometry
- mesenchymal stem cells
- cerebral ischemia
- deep learning
- big data
- artificial intelligence
- white matter
- brain injury
- small molecule
- capillary electrophoresis
- stress induced
- cognitive impairment
- resting state
- protein protein
- cerebral blood flow
- prefrontal cortex