Nature CommunicationsNeurosciencePeer-reviewed journal article
Oxytocin gene networks in the human brain: A gene expression and large-scale fMRI meta-analysis study
Daniel S. QuintanaiD, Jaroslav RokickiiD, Dennis van der MeeriD, Dag AlnæsiD, Tobias KaufmanniD, Aldo Córdova‐PalomeraiD, Ingrid DiesetiD, Ole A. AndreasseniD, Lars Tjelta WestlyeiD
Abstract
Oxytocin is a neuropeptide involved in animal and human reproductive and social behaviour, with potential implications for a range of psychiatric disorders. However, the therapeutic potential of oxytocin in mental health care suggested by animal research has not been successfully translated into clinical practice, partly due to a poor understanding of the expression and distribution of the oxytocin signaling pathway in the human brain, and its complex interactions with other biological systems. Among the genes involved in the oxytocin signaling pathway, three genes have been frequently implicated in human social behavior: OXT (structural gene for oxytocin), OXTR (oxytocin receptor), and CD38 (central oxytocin secretion). We characterized the distribution of the OXT, OXTR, and CD38 mRNA across the brain, identified putative gene pathway interactions by comparing gene expression patterns across 29131 genes, and assessed associations between gene expression patterns and cognitive states via large-scale fMRI meta-analysis. In line with the animal literature, oxytocin pathway gene expression was enriched in central, temporal, and olfactory regions. Across the brain, there was high co-expression of the oxytocin pathway genes with both dopaminergic (DRD2) and muscarinic acetylcholine (CHRM4) genes, reflecting an anatomical basis for critical gene pathway interactions. Finally, fMRI meta-analysis revealed that oxytocin pathway maps correspond with motivation and emotion processing, demonstrating the value of probing gene expression maps to identify brain functional targets for future pharmacological trials.
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: spatial domain detection
- approach: statistical model
- Citations
- 355
- FWCI
- 65.61
- Field percentile
- top 1%
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