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Clustering Patients with Pulmonary Hypertension Using the Plasma Proteome
Athénaïs Boucly1,2, Shanshan Song1, Merve Keles1
1National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London, United Kingdom.
Summary
Pulmonary hypertension plasma proteomic profiling identified four distinct patient clusters with varying survival rates. These clusters, linked to molecular pathways like PDGF and TGF-β, may guide targeted therapies.
Area of Science:
- Biochemistry
- Molecular Biology
- Cardiology
Background:
- Pulmonary hypertension (PH) classification guides treatment, but molecular insights could refine therapeutic choices.
- Understanding the molecular drivers of PH is crucial for personalized medicine.
Purpose of the Study:
- To identify distinct molecular subtypes of pulmonary hypertension using plasma proteomic profiling.
- To correlate these subtypes with clinical outcomes and potential therapeutic targets.
Main Methods:
- Assayed plasma protein levels in 470 PH patients, 136 disease controls, and 59 healthy controls using the SomaScan 7K platform.
- Utilized unsupervised clustering (k-means on UMAP dimensions) of 7288 proteins to identify PH-specific clusters.
- Validated cluster distinctions and clinical relevance in independent UK and French cohorts.
Main Results:
- Identified 156 plasma proteins distinguishing PH from controls, forming 4 distinct clusters.
- Clusters exhibited significantly different 5-year survival rates (78%, 62%, 44%, 33%).
- Confirmed cluster association with survival in validation cohorts; identified PDGF and TGF-β pathway dysregulation in specific clusters.
Conclusions:
- Plasma proteomic profiling effectively categorizes PH patients into 4 novel clusters, independent of current clinical classifications.
- These proteomic clusters may serve as theragnostic biomarkers for developing targeted therapies.
- Potential therapeutic strategies could focus on the identified PDGF and TGF-β pathways.
