Large scale plasma proteomic profiles improve prediction of idiopathic pulmonary fibrosis in general population
Our study characterized early proteomic contributions to IPF, and demonstrated that plasma proteomic data significantly enhance IPF risk prediction beyond traditional risk factors.
Authors
- Xianbo Wu (ORCID: https://orcid.org/0000-0002-2706-9599)
- Jiazhen Zheng (ORCID: https://orcid.org/0000-0003-0163-9175)
- Yingxin Liu (ORCID: https://orcid.org/0000-0002-7185-7023)
- Qi Zhong (ORCID: https://orcid.org/0000-0003-2274-0838)
- Huijuan Huang (ORCID: https://orcid.org/0009-0003-1023-8880)
- Xinyue Li (ORCID: https://orcid.org/0009-0000-9238-0458)
- Rui Zhou (ORCID: https://orcid.org/0000-0003-2263-2159)
- Guowei Li (ORCID: https://orcid.org/0000-0002-1184-1791)
Institutions
- Guangdong Pharmaceutical University (CN)
- Hong Kong University of Science and Technology (HK)
- Bioscience (China) (CN)
- Second Affiliated Hospital of Guangzhou Medical University (CN)
- Impact (CA)
- Southern Medical University (CN)
- Guangzhou Medical University (CN)
- McMaster University (CA)
Publication Details
- Journal
- Respiratory Research
- Published
- 2025-12-08
- DOI
- https://doi.org/10.1186/s12931-025-03418-z
- Primary Topic
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province