Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Department of Cardiology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Mol Med. 2024 Oct 26;30(1):189. doi: 10.1186/s10020-024-00963-z.
Pulmonary arterial hypertension (PAH) is a progressive and rapidly fatal disease with an intricate etiology. Identifying biomarkers for early PAH lesions based on the exploration of subtle biological processes is significant for timely diagnosis and treatment. In the present study, nine distinct cell populations identified based on gene expression profiles revealed high heterogeneity in cell composition ratio, biological function, distribution preference, and communication patterns in PAH. Notably, compared to other cells, endothelial cells (ECs) showed prominent variation in multiple perspectives. Further analysis demonstrated the endothelial-to-mesenchymal transition (EndMT) in ECs and identified a subgroup exhibiting a contrasting phenotype. Based on these findings, a machine-learning integrated program consisting of nine learners was developed to create a PAH Endothelial-to-mesenchymal transition Signature (PETS). This study identified cell populations underlying EndMT and furnished a potential tool that might be valuable for PAH diagnosis and new precise therapies.
肺动脉高压（PAH）是一种进展迅速且致命的疾病，其病因复杂。基于对细微生物学过程的探索，寻找早期 PAH 病变的生物标志物，对于及时诊断和治疗具有重要意义。在本研究中，基于基因表达谱鉴定的 9 种不同细胞群揭示了 PAH 中细胞组成比例、生物学功能、分布偏好和通信模式的高度异质性。值得注意的是，与其他细胞相比，内皮细胞（ECs）在多个方面表现出明显的变化。进一步的分析表明内皮细胞向间充质转化（EndMT）的存在，并鉴定出一个具有相反表型的亚群。基于这些发现，开发了一个由九个学习者组成的机器学习综合程序，以创建 PAH 内皮-间充质转化特征（PETS）。本研究鉴定了潜在的 EndMT 细胞群，并提供了一种潜在的工具，可能对 PAH 的诊断和新的精确治疗具有重要价值。
