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Deciphering age‑related differences in wound healing: Insights from the interaction between endothelial cells and fibroblasts

  • Authors:
    • Jianjun Li
    • Dongzhen Zhu
    • Mengde Zhang
    • Zhao Li
    • Liting Liang
    • Yuyan Huang
    • Xu Guo
    • Yi Kong
    • Xiaobing Fu
    • Sha Huang
  • View Affiliations / Copyright

    Affiliations: Research Center for Tissue Repair and Regeneration Affiliated to the Medical Innovation Research Department, PLA General Hospital and PLA Medical College, PLA Key Laboratory of Tissue Repair and Regenerative Medicine, Beijing 100853, P.R. China, Research Center for Tissue Repair and Regeneration Affiliated to the Medical Innovation Research Department, PLA General Hospital and PLA Medical College, PLA Key Laboratory of Tissue Repair and Regenerative Medicine, Beijing 100853, P.R. China, College of Graduate, Tianjin Medical University, Tianjin 300050 P.R. China
    Copyright: © Li et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 278
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    Published online on: August 4, 2025
       https://doi.org/10.3892/mmr.2025.13643
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Abstract

Aging impairs wound healing, primarily because of alterations in cell phenotypes and interactions, particularly between endothelial cells (ECs) and fibroblasts (Fibs). The present study investigated the dynamics of EC‑Fib interactions in aged wounds using a mouse model and single‑cell transcriptomics, supplemented by CellChat analysis and functional validation using in vitro co‑culture systems. Aged mice exhibited markedly reduced wound healing efficiency and impaired angiogenesis when compared with younger mice, as indicated by hematoxylin and eosin and immunohistochemical staining. Single‑cell transcriptomic analysis revealed that the regeneration of ECs and Fibs was delayed in aged wounds. Furthermore, key genes involved in angiogenesis and tissue repair were downregulated, whereas those related to inflammation and aging were upregulated. Integrating CellChat analysis with in vitro co‑culture validation, it was found that the bidirectional communication between ECs and Fibs, predominantly mediated via the transforming growth factor β pathway, was markedly reduced in aged wounds. These findings underscored the critical role of disrupted cell‑cell communication in age‑related impaired wound healing, providing mechanistic evidence for potential therapeutic strategies to enhance wound healing in the elderly.
View Figures

Figure 1

Decreased vascularization in wound
healing associated with aging. (A) Representative images of
cutaneous wounds in two age groups (aged vs. young) of mice on days
0, 2, 4 and 7; and the blood capillaries at the wound site at day
7. (B) Quantification of the wound healing rate after injures in
young and aged mice. (young: n=5, aged: n=3), (C) H&E staining
and immunohistochemical profiles of CD31 and α-SMA in young vs.
aged wounds at day 7 post-injury. (D and E) Quantification of
subcutaneous blood vessels length (D) and density (E) in aged vs.
young wounds, *P<0.05, **P<0.01, ***P<0.001. H&E,
hematoxylin and eosin; CD, cluster of differentiation; α-SMA,
α-smooth muscle actin.

Figure 2

The visualization and analysis of the
single-cell transcriptional atlas. (A) Schematic diagram
illustrating the study workflow for single-cell RNA sequencing
datasets (GSA: CRA010641) across different time points. (B) Cirlize
plot visualizing the UMAP of cell types in young and aged wounds
across four time points. Colors represent cell types. (C-E)
Expression of maker genes used for identification of cell types in
(B). (F) Heatmap of top three differentially expressed marker genes
of cell types in (B). GSA, Genome Sequence Archive; UMAP, uniform
manifold approximation and projection.

Figure 3

Cellular composition alterations
between young and aged wounds. (A) Proportion of all cell types in
wounds from the integrated datasets. (B) UMAP of each cell types in
aged wound over four time points. (C) Proportion of cell types in
young and aged wounds over time points. (D) UMAP of each cell types
in young wound over four time points (E) Quantification of the Ec
in young and aged wounds over time points. (F) Quantification of
the Fib in young and aged wounds over time points. Volcano plots of
differentially expression genes of EC in aged compared with young
wounds at day (G) 0, (H) 2, (I) 4 and (J) 7. UMAP, uniform manifold
approximation and projection; OD0, aged wound at day 0; OD2, aged
wound at day 2; OD4, aged wound at day 4; OD7. aged wound at day 7;
YD0, young wound at day 0; YD2, young wound at day 2; YD4, young
wound at day 4; YD7, young wound at day 7; Ec, endothelial cell;
Fib, fibroblast.

Figure 4

Differential expression genes
analysis of Fib in age compared with young wounds. Volcano plots of
DEGs at days (A) 0, (B) 2, (C) 4 and (D) 7. (E) Venn diagrams
showing the overlap of downregulated DEGs at days 0, 2, 4 and 7.
Each section displays the number of DEGs. (F) Expression patterns
of Meg3, Sparc, Nrp1 and Pdgfrl. GO term analysis of downregulated
DEGs at days (G) 0, (H) 2, (I) 4 and (J) 7. Fib, fibroblast; DEGs,
differentially expression genes; GO, Gene Ontology.

Figure 5

Differential intercellular
communication patterns between aged and young wounds. (A)
Clustering signaling pathways from aged and young wounds at day 7
into a shared two-dimensional manifold. (B) Magnified view of each
pathway cluster. (C) The overlapping signaling pathways between
aged and young wounds at day 7 were ordered in accordance with
their pairwise Euclidean distance in the shared two-dimensional
manifold. (D) The depiction of all signaling pathways within the
overall information flow of the inferred networks between aged and
young wounds at day 7. The signaling pathways colored red are more
enriched in aged wound. The signaling pathways colored green are
more enriched in young wound. The signaling pathways colored black
are equally enriched between aged and young wounds at day 7. (E)
Interaction analysis across all cell types in the aged wound at day
7 identifying prominent signaling sources and targets. (F)
Interaction analysis across all cell types in the young wound at
day 7 identifying prominent signaling sources and targets. (G)
Altered signaling pathways across all cell types in aged compared
with young wounds at day 7. (H) Heatmap of all signaling pathways
across all cell types between aged and young wounds at day 7,
focusing on outgoing signaling patterns. (I) Heatmap of all
signaling pathways among all cell types between aged and young
wounds at day 7, emphasizing incoming signaling patterns. (J)
Heatmap of all signaling pathways among all cell types in aged vs.
young wounds at day 7. OD7. aged wound at day 7; YD7, young wound
at day 7.

Figure 6

Altered signaling interaction between
Fib and Ec in aged vs. young wounds. (A) Differences in interaction
numbers and strength across all cell types in aged compared with
young wounds at day 7. (B) Altered signaling pathways associated
with Fib in aged compared with young wounds at day 7. (C)
Difference in interaction numbers and strength specifically between
Fib and Ec in aged vs. young wounds at day 7. (D) Circle plot of
TGF-β pathway-associated interaction network across all cell types
in aged and young wounds at day 7. (E) Chord diagrams of TGF-β
pathway-associated interaction network across all cell types in
aged and young wounds at day 7. (F) The strength of interaction
from Ec to Fib via TGF-β pathway in in aged and young wounds at day
7. The thickness of the connecting line indicates the level of
communication probability. (G) Significant ligand-receptor pairs
that contribute to the signaling sent from EC via TGF-β pathway in
in aged and young wounds at day 7. (H) The distribution of gene
expression related to the TGF-β pathway across all cell types in in
aged and young wounds at day 7. OD7. aged wound at day 7; YD7,
young wound at day 7; TGF-β, transforming growth factor β; Ec,
endothelial cell; Fib, fibroblast.

Figure 7

Gene and protein expression profiling
in fibroblasts under high-glucose induction and co-culture system.
Gene expression level of (A) P16, (B) P21 and (C)
Ki67 in fibroblasts under different glucose concentrations.
(n=3) Quantification of fluorescence intensity for (D) P16, (E) P21
and (F) Ki67 in fibroblasts under different glucose concentrations
following (G) Immunofluorescence staining. (H) TGF-β1 gene
expression in young fibroblasts co-cultured with ECs. (I)
TGF-β1 gene expression in old fibroblasts co-cultured with
ECs. (J) Smad2 gene expression in young fibroblasts
co-cultured with ECs. (K) Smad2 gene expression in old
fibroblasts co-cultured with ECs. Smad3 gene expression in
(L) young fibroblasts co-cultured with ECs. (M) Smad3 gene
expression in old fibroblasts co-cultured with ECs. (N-R)
Immunofluorescence staining and quantification of fluorescence
intensity for TGF-β1 and Smad2+3 in fibroblasts under different
co-culture system. *P<0.05, **P<0.01, ***P<0.001,
****P<0.0001.
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Copy and paste a formatted citation
Spandidos Publications style
Li J, Zhu D, Zhang M, Li Z, Liang L, Huang Y, Guo X, Kong Y, Fu X, Huang S, Huang S, et al: Deciphering age‑related differences in wound healing: Insights from the interaction between endothelial cells and fibroblasts. Mol Med Rep 32: 278, 2025.
APA
Li, J., Zhu, D., Zhang, M., Li, Z., Liang, L., Huang, Y. ... Huang, S. (2025). Deciphering age‑related differences in wound healing: Insights from the interaction between endothelial cells and fibroblasts. Molecular Medicine Reports, 32, 278. https://doi.org/10.3892/mmr.2025.13643
MLA
Li, J., Zhu, D., Zhang, M., Li, Z., Liang, L., Huang, Y., Guo, X., Kong, Y., Fu, X., Huang, S."Deciphering age‑related differences in wound healing: Insights from the interaction between endothelial cells and fibroblasts". Molecular Medicine Reports 32.4 (2025): 278.
Chicago
Li, J., Zhu, D., Zhang, M., Li, Z., Liang, L., Huang, Y., Guo, X., Kong, Y., Fu, X., Huang, S."Deciphering age‑related differences in wound healing: Insights from the interaction between endothelial cells and fibroblasts". Molecular Medicine Reports 32, no. 4 (2025): 278. https://doi.org/10.3892/mmr.2025.13643
Copy and paste a formatted citation
x
Spandidos Publications style
Li J, Zhu D, Zhang M, Li Z, Liang L, Huang Y, Guo X, Kong Y, Fu X, Huang S, Huang S, et al: Deciphering age‑related differences in wound healing: Insights from the interaction between endothelial cells and fibroblasts. Mol Med Rep 32: 278, 2025.
APA
Li, J., Zhu, D., Zhang, M., Li, Z., Liang, L., Huang, Y. ... Huang, S. (2025). Deciphering age‑related differences in wound healing: Insights from the interaction between endothelial cells and fibroblasts. Molecular Medicine Reports, 32, 278. https://doi.org/10.3892/mmr.2025.13643
MLA
Li, J., Zhu, D., Zhang, M., Li, Z., Liang, L., Huang, Y., Guo, X., Kong, Y., Fu, X., Huang, S."Deciphering age‑related differences in wound healing: Insights from the interaction between endothelial cells and fibroblasts". Molecular Medicine Reports 32.4 (2025): 278.
Chicago
Li, J., Zhu, D., Zhang, M., Li, Z., Liang, L., Huang, Y., Guo, X., Kong, Y., Fu, X., Huang, S."Deciphering age‑related differences in wound healing: Insights from the interaction between endothelial cells and fibroblasts". Molecular Medicine Reports 32, no. 4 (2025): 278. https://doi.org/10.3892/mmr.2025.13643
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