ArticlePloS one2026
Integrative bioinformatic analysis prioritizes TIMP1 and FN1 as angiogenesis-related candidate genes in diabetic foot ulcers.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDiabetic foot ulcers (DFUs) represent a severe chronic complication of diabetes and are characterized by persistent impairment of wound healing, accompanied by defective angiogenesis, chronic inflammation, and dysregulated extracellular matrix remodeling. Although impaired angiogenesis is widely recognized as a key pathological feature of DFUs, its associated molecular alterations have not been systematically characterized at the transcriptomic and cellular levels.
methodsIn this study, bulk transcriptomic data were analyzed in combination with machine learning-based gene prioritization and single-cell RNA sequencing to investigate molecular features associated with angiogenesis impairment in DFUs. Differential expression analysis was performed using the GSE199939 and GSE134431 datasets, followed by GO and KEGG enrichment analyses. Angiogenesis-related genes were retrieved from the MSigDB HALLMARK_ANGIOGENESIS and GO:0001525, and intersected with the DEGs to generate a candidate gene set. A LASSO logistic regression model was then constructed in the discovery cohort and evaluated in a replication cohort, yielding a five-gene signature consisting of APLN, ENG, FN1, SERPINA5, and TIMP1. Single-cell transcriptomic data were subsequently used to examine the cellular expression patterns of these feature genes.
resultsAmong the five feature genes, FN1 and TIMP1 showed relatively clear expression localization at the single-cell level. Single-cell RNA sequencing analysis revealed that FN1 was mainly enriched in fibroblasts and stromal-related cell populations, including pericytes/smooth muscle cells, whereas TIMP1 exhibited a multicellular expression pattern, with relatively high expression in fibroblasts, inflammatory myeloid cells, macrophages, and proliferating cells. In vivo experiments further showed that TIMP1 and EGFR mRNA expression levels were significantly decreased, whereas MMP9 mRNA expression was significantly increased in wound tissues from the model group. FN1 mRNA showed a downward trend, although the difference did not reach statistical significance.
conclusionThis integrative bioinformatic analysis provides an exploratory characterization of molecular features potentially related to restricted angiogenesis and impaired repair in DFUs and suggests that TIMP1 may represent a more robust candidate linked to proteolysis-related dysregulation, whereas FN1 may more likely reflect stromal extracellular matrix remodeling.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.