We have developed a multimodal biosensing platform for the in situ monitoring of exosomal RNAs without cell lysis. This system employs a cascade of aptamer recognition, rolling circle amplification (RCA), and G-quadruplex/hemin signal transduction. Electrochemical and colorimetric outputs are seamlessly integrated using an inverse-variance-weighted data fusion algorithm, achieving ultrasensitive and precise detection. Applying this method to oxidative stress-induced cellular senescence, we successfully constructed a comprehensive RNA dynamic map. This analysis revealed time-resolved molecular logic: miRNA-21 displayed transient early upregulation as an adaptive response, while miRNA-29c and miRNA-34a accumulated progressively at later stages, driving irreversible senescence. Clinical validation further demonstrated the platform's efficacy in staging Alzheimer's disease (AD), where the integrated trimodal signals effectively distinguished between mild cognitive impairment (MCI) and progressive AD stages. Detailed statistical analysis identified exosomal miRNA-21 and miRNA-34a as significant independent risk factors, establishing a robust molecular signature for precision AD diagnostics. This work establishes an amplified, multimodal biosensing framework for profiling exosomal RNA communication during aging, offering a powerful tool for stage-resolved biomolecular mapping in precision geroscience.
