Integrative network toxicology and machine learning reveal the potential role of 5-hydroxymethylfurfural in exacerbating pulmonary fibrosis
- 1Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
- 2Department of Respiratory Disease, Chongqing Jiulongpo Science City People's Hospital, Chongqing, China.
Abstract
Background: 5-Hydroxymethylfurfural (5-HMF), a ubiquitous furan derivative formed during the thermal processing of carbohydrate-rich foods, represents a widespread dietary exposure. However, its potential contribution to idiopathic pulmonary fibrosis (IPF) remains unclear. This study investigated the molecular links between 5-HMF and IPF using an integrated computational and experimental approach. Methods: IPF-related genes were identified through transcriptomic analysis combining differential expression analysis and weighted gene co-expression network analysis. Candidate targets were obtained by intersecting IPF-associated genes with predicted 5-HMF targets. Functional enrichment analysis, ensemble machine learning, and SHAP interpretation were performed to prioritize candidate targets, while molecular docking was used to explore potential 5-HMF–target interactions. A bleomycin-induced mouse model of pulmonary fibrosis was further used to evaluate the effects of 5-HMF on fibrotic lung injury and the transcriptional expression of prioritized candidate genes. Results: A total of 1,776 IPF-associated genes and 143 predicted 5-HMF targets were identified, yielding 12 overlapping candidate targets. Enrichment analysis implicated these genes in fibrosis-related pathways, including chemical carcinogenesis–receptor activation and estrogen signaling. Machine learning analysis prioritized seven core targets (CA2, CA4, ESR2, F10, HSP90AA1, PLA2G1B, and PTPRB), all of which accommodated 5-HMF in their orthosteric pockets in blind docking, albeit with weak, non-selective Vina scores (−4.5 to −5.4 kcal/mol). In vivo, 5-HMF significantly exacerbated bleomycin-induced pulmonary fibrosis, as demonstrated by aggravated lung injury, increased collagen deposition, and elevated expression of Hsp90aa1, Pla2g1b, Ca4, F10, Acta2, and Col1a1. Conclusion: Our findings suggest that 5-HMF may exacerbate fibrotic lung injury through multiple fibrosis-related molecular targets and pathways. These findings provide preliminary evidence for a potential association between 5-HMF exposure and the aggravation of pulmonary fibrosis, while further studies are required to determine whether 5-HMF can independently initiate fibrotic pathology.
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BibTeX
@article{yang2026integrative,
title = {{Integrative network toxicology and machine learning reveal the potential role of 5-hydroxymethylfurfural in exacerbating pulmonary fibrosis}},
author = {Qinghuan Yang and Fuli Li and Jiani Li and Ting Qin},
journal = {PLOS One},
year = {2026},
month = nov,
doi = {10.1371/journal.pone.0361700},
url = {https://doi.org/10.1371/journal.pone.0361700},
note = {CC BY},
}
RIS
TY - JOUR
TI - Integrative network toxicology and machine learning reveal the potential role of 5-hydroxymethylfurfural in exacerbating pulmonary fibrosis
AU - Qinghuan Yang
AU - Fuli Li
AU - Jiani Li
AU - Ting Qin
PY - 2026
DA - 2026/11/02
JO - PLOS One
DO - 10.1371/journal.pone.0361700
UR - https://doi.org/10.1371/journal.pone.0361700
AB - Background: 5-Hydroxymethylfurfural (5-HMF), a ubiquitous furan derivative formed during the thermal processing of carbohydrate-rich foods, represents a widespread dietary exposure. However, its potential contribution to idiopathic pulmonary fibrosis (IPF) remains unclear. This study investigated the molecular links between 5-HMF and IPF using an integrated computational and experimental approach. Methods: IPF-related genes were identified through transcriptomic analysis combining differential expression analysis and weighted gene co-expression network analysis. Candidate targets were obtained by intersecting IPF-associated genes with predicted 5-HMF targets. Functional enrichment analysis, ensemble machine learning, and SHAP interpretation were performed to prioritize candidate targets, while molecular docking was used to explore potential 5-HMF–target interactions. A bleomycin-induced mouse model of pulmonary fibrosis was further used to evaluate the effects of 5-HMF on fibrotic lung injury and the transcriptional expression of prioritized candidate genes. Results: A total of 1,776 IPF-associated genes and 143 predicted 5-HMF targets were identified, yielding 12 overlapping candidate targets. Enrichment analysis implicated these genes in fibrosis-related pathways, including chemical carcinogenesis–receptor activation and estrogen signaling. Machine learning analysis prioritized seven core targets (CA2, CA4, ESR2, F10, HSP90AA1, PLA2G1B, and PTPRB), all of which accommodated 5-HMF in their orthosteric pockets in blind docking, albeit with weak, non-selective Vina scores (−4.5 to −5.4 kcal/mol). In vivo, 5-HMF significantly exacerbated bleomycin-induced pulmonary fibrosis, as demonstrated by aggravated lung injury, increased collagen deposition, and elevated expression of Hsp90aa1, Pla2g1b, Ca4, F10, Acta2, and Col1a1. Conclusion: Our findings suggest that 5-HMF may exacerbate fibrotic lung injury through multiple fibrosis-related molecular targets and pathways. These findings provide preliminary evidence for a potential association between 5-HMF exposure and the aggravation of pulmonary fibrosis, while further studies are required to determine whether 5-HMF can independently initiate fibrotic pathology.
SN - 1932-6203
ER -