| Title: | Multi-Omics Identification of Biomarkers for High-Altitude Pulmonary Hypertension |
| Journal: | Journal of Cardiovascular Development and Disease |
| Published: | 30 Apr 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42188081/ |
| DOI: | https://doi.org/10.3390/jcdd13050195 |
Publication 20205
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
(1) Aim: The incidence of high-altitude pulmonary hypertension (HAPH) has risen in recent years and is expected to continue increasing; however, its diagnosis remains challenging. In this study, we employed proteomics and metabolomics to identify the proteins and metabolic biomarkers that contribute to the development of HAPH. (2) Methods: We applied integrated proteomics and metabolomics to match blood samples from 40 HAPH patients and 40 healthy controls in Yunnan's high-altitude regions to characterize molecular profiles, identify biomarkers, and develop a predictive model. (3) Results: Proteomic analysis identified four proteins (A2IPH7, K1C14, PSME2, SERPINE2) commonly dysregulated in HAPH patients from two high-altitude regions. SERPINE2 was notably downregulated and showed a negative correlation with clinical severity, which was further validated in HAPH rat lung tissues and supported by UK Biobank data for idiopathic PAH. Concurrent metabolomics uncovered 11 shared metabolites, largely acyl fatty acids, enriched in pathways such as unsaturated fatty acid synthesis. Integration of these multi-omics data enabled the development of a robust predictive model. (4) Conclusion: Our study identified key protein and metabolic biomarkers involved in HAPH development, which were validated in animal models. Based on these findings, a predictive model was developed, highlighting SERPINE2 and 11 metabolites as promising targets for the prediction and prevention of HAPH.</p>
14 Authors
- Zhe Chen
- Linhong Pang
- Yidan Zheng
- Li Xu
- Mingjing Tang
- Ziwen Zhao
- Tianyu Wang
- Jin Li
- Yunfei Zhou
- Lin Duo
- Wenlong Zhu
- Zhiling Luo
- Fei Li
- Da Zhu
1 Application
| Application ID | Title |
|---|---|
| 105945 | the risk factor and underlying mechanism of Clonal Hematopoiesis Indeterminate Potential (CHIP) in cardiocerebrovascular diseases and renal diseases |
Enabling scientific discoveries that improve human health