Evidence map›Paper›PMID 40164683›Full record

ArticleExperimental & molecular medicine2025

PGC-1α mediates migrasome secretion accelerating macrophage-myofibroblast transition and contributing to sepsis-associated pulmonary fibrosis.

Yawen Peng, Shuya Mei, Xiaohui Qi, Ri Tang, Wenyu Yang, Jinhua Feng, Yang Zhou, Xi Huang, Guojun Qian, Shunpeng Xing and 3 more

Abstract read
In one paragraph

Article in Experimental & molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Yawen Peng *Department of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shuya Mei *Department of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaohui Qi *Department of Cardiovascular Surgery, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ri TangDepartment of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID http://orcid.org/0000-0003-0137-2917
Wenyu YangDepartment of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jinhua FengDepartment of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yang ZhouDepartment of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xi HuangDepartment of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Guojun QianKey Laboratory of Anesthesiology (Shanghai Jiao Tong University), Ministry of Education, Shanghai, China.
Shunpeng XingDepartment of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yuan GaoDepartment of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. rj_gaoyuan@163.com.
Qiaoyi XuDepartment of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. xuqiaoyiyayaya@126.com.
Zhengyu HeDepartment of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. zhengyuheshsmu@163.com.ORCID http://orcid.org/0000-0001-7354-850X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82170072National Natural Science Foundation of China (National Science Foundation of China) 82300086
6 · The paper itself

Abstract

Sepsis-associated pulmonary fibrosis (SAPF) is a critical pathological stage in the progression of sepsis-induced acute respiratory distress syndrome. While the aggregation and activation of lung fibroblasts are central to the initiation of pulmonary fibrosis, the macrophage-myofibroblast transition (MMT) has recently been identified as a novel source of fibroblasts in this context. However, the mechanisms driving MMT remain inadequately understood. Given the emerging role of migrasomes (novel extracellular vesicles mediating intercellular communication), we investigated their involvement in pulmonary fibrosis. Here we utilized a lipopolysaccharide-induced SAPF mouse model and an in vitro co-culture system of fibroblasts and macrophages to observe the MMT process during SAPF. We found that lipopolysaccharide exposure suppresses PGC-1α expression in lung fibroblasts, resulting in mitochondrial dysfunction and the accumulation of cytosolic mitochondrial DNA (mtDNA). This dysfunction promotes the secretion of mtDNA-containing migrasomes, which, in turn, initiate the MMT process and contribute to fibrosis progression. Notably, the activation of PGC-1α mitigates mitochondrial dysfunction, reduces mtDNA-migrasome release, inhibits MMT and alleviates SAPF. In conclusion, our study identifies the suppression of PGC-1α in lung fibroblasts and the subsequent release of mtDNA migrasomes as a novel mechanism driving MMT in SAPF. These findings suggest that targeting the crosstalk between fibroblasts and immune cells mediated by migrasomes could represent a promising therapeutic strategy for SAPF.

Indexed as

Extracellular VesiclesMacrophagesMyofibroblastsPeroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alphaPulmonary FibrosisSepsisAnimalsDisease Models, AnimalDNA, MitochondrialFibroblastsHumansLipopolysaccharidesMaleMiceMice, Inbred C57BLMitochondriaDNA, MitochondrialLipopolysaccharidesPeroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alphaPpargc1a protein, mouse

Identifiers

PMID40164683
PMCPMC12046055

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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.