Wound Healing Capacity as a Biomarker of Aging Resilience: Behavioral and Transcriptomic Characterization of High and Low Responder Phenotypes

Abstract

Age-related decline in physiological resilience manifests across cognitive, physical, and metabolic domains, yet validated early biomarkers capable of predicting individual aging trajectories before functional decline occurs remain lacking. Wound healing capacity represents a promising candidate biomarker because successful tissue repair requires coordinated function of the same immune, vascular, metabolic, and cellular stress response systems whose deterioration underlies broader aging vulnerability. To test this, aged C57BL/6J mice (n=80, 40 male, 40 female, 18 months) underwent a standardized 2mm ear punch biopsy and were stratified by median wound closure at Day 16 into high responders (n=32) and low responders (n=32). Cognitive and physical function were assessed at 24 to 25 months across four behavioral assays, followed by tissue collection for RNA sequencing of hippocampus and liver and immunohistochemical analysis of brain tissue. No statistically significant behavioral differences were detected between groups, though rotarod performance showed the strongest directional trend favoring high responders. Hippocampal RNA sequencing identified the Hallmark Interferon Alpha Response as significantly enriched in high responders by gene set enrichment analysis, with stress axis genes Fkbp5 and Klf9 trending downward in the resilient phenotype. Liver transcriptomics identified 14 differentially expressed genes, with high responders showing upregulation of stress response and detoxification genes including Gadd45g and Gstm3 and strong downregulation of the circadian clock repressor Ciart. Low responder livers were significantly enriched for hallmarks of systemic inflammaging including IL6/JAK/STAT3 signaling, complement activation, interferon gamma response, and markers of elevated cellular stress and hepatocyte turnover. These findings demonstrate that wound healing capacity stratifies aged mice into biologically distinct molecular phenotypes, supporting its utility as a tractable, minimally invasive biomarker for early identification of vulnerable aging phenotypes. Identified transcriptomic signatures provide candidate targets for future resilience-promoting interventions.