Investigates RNA interactions affecting pain in diabetic rats, suggesting targets for therapy.
Painful diabetic peripheral neuropathy is recognized as a common and highly disabling complication in diabetes. Its underlying mechanisms remain incompletely understood, and effective therapeutic options are lacking. A growing body of evidence indicates that long noncoding RNAs, microRNAs, and messenger RNAs form complex competing endogenous RNA networks that influence painful diabetic peripheral neuropathy development. Given the central role of the dorsal root ganglion in sensory processing, this study investigated transcriptomic alterations in dorsal root ganglion tissue from a streptozotocin-induced rat model of painful diabetic peripheral neuropathy. Behavioral, electrophysiological, and histopathological assessments confirmed the successful establishment of neuropathic pain phenotypes. Whole-transcriptome RNA sequencing identified 101 messenger RNAs and 184 long non-coding RNAs that were differentially expressed. Key dysregulated genes included the proinflammatory cytokine Ccl3, the neurotrophic factor Igf1, the transcription factor Fosb, and the metabolic enzyme Alox15. Enrichment analyses indicated that these genes were mainly involved in immune-inflammatory responses, regulation of neurotransmission, ion channel activity, and energy metabolism. Construction of a competing endogenous RNA network showed that 1892 positively correlated long non-coding RNA-messenger RNA pairs contributed to a competing endogenous RNA network in which XR_005494971.1 was the most prominent long non-coding RNA regulator. Integration of microRNA predictions further identified rno-miR-466b-3p as a central node linking messenger RNAs and long non-coding RNAs. Reverse transcription-quantitative polymerase chain reaction and western blotting validated the sequencing results. These findings provide an integrated overview of coding and non-coding RNA interactions in a rat model of painful diabetic peripheral neuropathy and highlight molecular targets that may support early diagnosis and precision therapeutic strategies.
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Gao et al. (2026) studied this question.
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