Peripheral exosomal miRNAs as candidate molecular indicators associated with acupuncture at ST36 in an LPS-induced neuroinflammation model.

This study aimed to identify circulating exosomal microRNA (miRNA) candidates showing a control-like expression pattern following ST36 acupuncture treatment in an LPS-induced neuroinflammation model, using empirical Bayes reanalysis of previously published microarray data. Two independent Affymetrix GeneChip miRNA 4.0 microarray datasets from C57BL/6 male mice were reanalysed using the limma empirical Bayes framework with Benjamini-Hochberg false discovery rate (FDR) correction. After detection-call filtering, 286 commonly expressed probes were identified. Control-like pattern candidates were defined by three criteria: FDR < 0.05 for the LPS effect, FDR > 0.05 for the LPS+ST36 vs CON comparison, and logFC direction opposite to the LPS effect. Target gene prediction and pathway enrichment were subsequently performed. Eight miRNA candidates were identified: five upregulated by LPS and showing a control-like pattern following ST36 (let-7d-5p, miR-103-3p, miR-107-3p, miR-451a, miR-7047-5p) and three downregulated by LPS and showing a control-like pattern following ST36 (miR-5128, miR-16-2-3p, miR-101a-5p). None overlapped with candidates from the original fold-change-based analysis. Functional enrichment of 1,596 predicted target genes revealed significant enrichment in MAPK, PI3K-Akt, and Wnt signaling pathways, with Gene Ontology analysis highlighting convergence on neuronal and synaptic processes. Limma-based reanalysis reveals a distinct set of ST36-associated exosomal miRNAs overlooked by threshold-based approaches, providing exploratory candidate molecular indicators for further investigation of acupuncture's peripheral effects in neuroinflammation.