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Article Abstract

Objective: To investigate the effect of phase polarity and charge balance of spinal cord stimulation (SCS) waveforms on pain behavior and gene expression in a neuropathic pain rodent model. We hypothesized that differing waveforms will result in diverse behavioral and transcriptomics expression due to unique mechanisms of action.

Materials And Methods: Rats were implanted with a four-contact cylindrical mini-lead and randomly assigned to two control (no-pain and pain model) and five test groups featuring monophasic, as well as charge-unbalanced and charge-balanced biphasic SCS waveforms. Mechanical and cold allodynia were assessed to measure efficacy. The ipsilateral dorsal quadrant of spinal cord adjacent to the lead was harvested post-stimulation and processed to determine gene expression via real-time reverse-transcriptase polymerase chain reaction (RT-PCR). Gene expression, SCS intensity (mA), and behavioral score as percent of baseline (BSPB) were statistically analyzed and used to generate correlograms using R-Studio. Statistical analysis was performed using SPSS22.0, and p < 0.05 was considered significant.

Results: As expected, BSPB was significantly lower for the pain model group compared to the no-pain group. BSPB was significantly improved post-stim compared to pre-stim using cathodic, anodic, symmetric biphasic, or asymmetric biphasic 1:2 waveforms; however, BSPB was not restored to Sham levels. RT-PCR analysis showed that eight genes demonstrated a significant difference between the pain model and SCS waveforms and between waveforms. Correlograms reveal a linear correlation between regulation of expression of a given gene in relation to mA, BSPB, or other genes.

Conclusions: Our results exhibit that specific SCS waveforms differentially modulate several key transcriptional pathways that are relevant in chronic pain conditions. These results have significant implications for SCS: whether to move beyond traditional paradigm of neuronal activation to focus also on modulating immune-driven processes.

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http://dx.doi.org/10.1111/ner.12964DOI Listing

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