Senescence-Associated Transcriptome Reversal Prioritizes Repurposing Candidates for Diabetic Kidney Disease: A Computational Study

Background/Objectives: Diabetic kidney disease (DKD) is a leading cause of end-stage kidney disease, and cellular senescence is a tractable therapeutic target; yet prioritizing credible repurposing candidates is difficult because bulk-tissue senescence signals are weak, single-dataset analyses are unstable, and transcriptome-reversal screens overstate novelty. The objective was to build a senescence-anchored, multi-evidence computational prioritization of repurposing candidates for DKD entirely from open data.

Methods

Per-sample senescence activity was quantified by single-sample gene set enrichment across three DKD kidney cohorts, and consensus signatures were reversed against 45,956 LINCS L1000 signatures. Candidates were ranked by reversal strength, mechanism, ChEMBL stage, and ClinicalTrials.gov novelty, then assessed for robustness by senotherapeutic enrichment, an external senolytic benchmark, leave-one-cohort-out analysis, drug-target Mendelian randomization, and single-nucleus profiling.