Background
Neuropathic pain (NP) takes a heavy toll on individual life quality, yet gaps in its molecular characterization persist and effective therapy is lacking. This study aimed to provide comprehensive knowledge by combining transcriptomic and proteomic data of molecular correlates of NP in the anterior cingulate cortex (ACC), a cortical hub responsible for affective pain processing.
Conclusion
The present study identified novel pathways in the ACC in addition to confirming previously reported mechanisms for NP etiology, and provided novel mechanistic insights for future research on NP treatment. These findings also imply that mRNA profiling alone fails to provide a complete landscape of molecular pain in the ACC. Therefore, explorations of changes at the level of protein are necessary to understand NP processes that are not transcriptionally modulated.
Methods
The NP model was established by spared nerve injury (SNI) in Sprague-Dawley rats. RNA sequencing and proteomic data from the ACC tissue isolated from sham and SNI rats 2 weeks after surgery were integrated to compare their gene and protein expression profiles. Bioinformatic analyses were performed to figure out the functions and signaling pathways of the differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) enriched in.
Results
Transcriptomic analysis identified a total of 788 DEGs (with 49 genes upregulated) after SNI surgery, while proteomic analysis found 222 DEPs (with 89 proteins upregulated). While Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of the DEGs suggested that most of the altered genes were involved in synaptic transmission and plasticity, bioinformatics analysis of the DEPs revealed novel critical pathways associated with autophagy, mitophagy, and peroxisome. Notably, we noticed functionally important NP-related changes in the protein that occurred in the absence of corresponding changes at the level of transcription. Venn diagram analysis of the transcriptomic and proteomic data identified 10 overlapping targets, among which only three genes (XK-related protein 4, NIPA-like domain-containing 3, and homeodomain-interacting protein kinase 3) showed concordance in the directions of change and strong correlations between mRNA and protein levels.