bioRxivImmunologyPreprint
Multi-omics identification of activated T cells and spatial PD-1/PD-L1 signaling as biomarkers of diabetic foot ulcer healing
Sophie M. BilikiD, Caroline DodsoniD, Katelyn Rivas, Nathan C. BalukoffiD, Anthony J. GriswoldiD, Jamie Lee BurgessiD, Andrew Phillip SawayaiD, Irena PastariD, Nataša ŠtrboiD, María I. MorassoiD, Marjana Tomic‐CaniciD, Rivka C. StoneiD
Abstract
Diabetic foot ulcers (DFUs) are a common and debilitating complication of diabetes, and amputations from non-healing ulcers carry high morbidity and mortality. A critical need exists for biomarkers that can identify healing potential early and guide targeted interventions. To address this, we applied an integrated multi-omics approach across four patient cohorts comprising 51 DFUs (29 Healing, 22 Non-healing). Bulk RNA-sequencing revealed marked activation of Th1 and Th2 pathways (activation z-score +4.8, p = 3.8x10-{superscript 1}), and immune cell deconvolution predicted higher proportions of T cell populations in Healers. Spatial proteomics in a second cohort identified elevated CD3 T cell density and selective enrichment of PD-1 and PD-L1 expression in vascular niches of the papillary dermis in Healers (p < 0.001). Flow cytometry in a third cohort further demonstrated higher proportions of CD3PD-1 and CD3PD-L1 T cells in Healers compared with Non-healers. Single-cell RNA-sequencing from a fourth cohort showed upregulation of PD-1 and PD-L1 within CD4 T cells from Healers. Complementary immunofluorescence and serological profiling confirmed that both PD-1 and PD-L1 are elevated in tissue and circulating serum of healing DFUs, supporting their potential use as systemic biomarkers. Taken together, vascular-enriched PD-1/PD-L1 signaling and T cell activation were observed in association with healing DFUs, supporting PD-1/PD-L1 as candidate biomarkers in both tissue and blood with potential translational relevance for predicting DFU outcomes and informing precision therapies.
- organism: human
- assay: bulk RNA-seq
- assay: spatial transcriptomics
- assay: proteomics
- assay: flow cytometry
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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