Large scale plasma proteomic profiles improve prediction of idiopathic pulmonary fibrosis in general population

Rui Zhou; Guowei Li; Qi Zhong; Xinyue Li; Jiazhen Zheng; Huijuan Huang; Xianbo Wu

doi:10.1186/s12931-025-03418-z

December 8, 2025Respiratory ResearchOpen Access

Large scale plasma proteomic profiles improve prediction of idiopathic pulmonary fibrosis in general population

View Full Paper

Ask AI

Bookmark

Share

Key Points

Improved risk prediction for idiopathic pulmonary fibrosis indicates potential for better clinical outcomes.
Plasma proteomic data enhances risk prediction beyond traditional risk factors, showing a significant advantage.
Observational analysis characterized early proteomic contributions to idiopathic pulmonary fibrosis and its implications.
This highlights the need to integrate proteomic data into routine clinical risk assessments for idiopathic pulmonary fibrosis.

Implication

Analysis shows improved risk prediction for idiopathic pulmonary fibrosis, indicating the importance of plasma proteomic data.

Abstract

Our study characterized early proteomic contributions to IPF, and demonstrated that plasma proteomic data significantly enhance IPF risk prediction beyond traditional risk factors.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Zhou et al. (2025) studied this question.

synapsesocial.com/papers/694020e22d562116f28faa87 https://doi.org/10.1186/s12931-025-03418-z

View Full Paper

Ask AI

Bookmark

Share

Large scale plasma proteomic profiles improve prediction of idiopathic pulmonary fibrosis in general population

Key Points

Implication

Abstract

Discussion

Cite This Study

Large scale plasma proteomic profiles improve prediction of idiopathic pulmonary fibrosis in general population

Key Points

Implication

Abstract

Discussion

Cite This Study

Keep reading

Keep reading