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Correspondence between gene expression and neurotransmitter receptor and transporter density in the human brain.

Authors :
Hansen, Justine Y.
Markello, Ross D.
Tuominen, Lauri
Nørgaard, Martin
Kuzmin, Elena
Palomero-Gallagher, Nicola
Dagher, Alain
Misic, Bratislav
Source :
NeuroImage. Dec2022, Vol. 264, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

• We correlate gene expression and protein density for 27 receptors and transporters • Only 5HT1a, CB1, D2, and MOR show consistent expression-density correspondence • Expression-density associations are related to population variance • We replicate results using PET, autoradiography, microarray, and RNAseq data • We recommend being cautious when substituting gene expression for receptor density Neurotransmitter receptors modulate signaling between neurons. Thus, neurotransmitter receptors and transporters play a key role in shaping brain function. Due to the lack of comprehensive neurotransmitter receptor/transporter density datasets, microarray gene expression measuring mRNA transcripts is often used as a proxy for receptor densities. In the present report, we comprehensively test the spatial correlation between gene expression and protein density for a total of 27 neurotransmitter receptors, receptor binding-sites, and transporters across 9 different neurotransmitter systems, using both PET and autoradiography radioligand-based imaging modalities. We find poor spatial correspondences between gene expression and density for all neurotransmitter receptors and transporters except four single-protein metabotropic receptors (5-HT 1 A , CB 1 , D 2 , and MOR). These expression-density associations are related to gene differential stability and can vary between cortical and subcortical structures. Altogether, we recommend using direct measures of receptor and transporter density when relating neurotransmitter systems to brain structure and function. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10538119
Volume :
264
Database :
Academic Search Index
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
160709207
Full Text :
https://doi.org/10.1016/j.neuroimage.2022.119671