Prioritizing extracellular miRNA candidates in asthma: transparent in silico integration, literature-based concordance, and mechanistic network analysis.

BACKGROUND: Extracellular microRNAs (miRNAs) are promising asthma biomarker candidates, but database-derived panels require literature assessment. OBJECTIVE: To prioritize extracellular asthma-associated miRNAs and evaluate literature-based concordance, specificity and target-network structure. METHODS: RNADisease v4.0, miEAA, miRPathDB 2.0, miRDB v6.0, MSigDB v7.4 C3 MIR:MIRDB, Reactome, and Gene Ontology were integrated. Formal concordance required an exact mature-arm identifier and a clearly interpretable asthma contrast in a separate published human extracellular-miRNA study; arm-unspecified names were retained only as contextual evidence. Predicted targets were analyzed using unique MIR:MIRDB target-set counting, Reactome over-representation testing, and Benjamini-Hochberg correction across 1,217 pathways. RESULTS: Sixty-three extracellular candidates were identified; 60 had an EV/exosome/microvesicle annotation and 53 had at least two localization/transport annotations. Three published studies supported six formally concordant candidates, while four additional candidates had only arm-unspecified contextual support. GSE280322 showed no exact mature-arm overlap. Raw-read reprocessing was feasible but not undertaken; this represented published-result concordance rather than sample-level validation. Fifty-nine candidates mapped to 57 unique target sets and 7,092 genes; four were unmapped, including formally concordant hsa-miR-126-3p, so concordance and network sets were non-identical. The analysis yielded 108 hubs and one FDR-significant, parameter-contingent Reactome pathway: regulation of MECP2 expression and activity. CONCLUSION: This framework supports prioritization, but no validated or asthma-specific signature was established.