Wang Tan, Chen Huan, Li Ningning, Zhang Bao, Min Hanyi
Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No.1 Shuai Fu Yuan, Dongcheng District, Beijing, 100730, China.
Key Laboratory of Ocular Fundus Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Clin Proteomics. 2024 May 19;21(1):36. doi: 10.1186/s12014-024-09481-w.
To comprehend the complexities of pathophysiological mechanisms and molecular events that contribute to proliferative diabetic retinopathy (PDR) and evaluate the diagnostic value of aqueous humor (AH) in monitoring the onset of PDR.
A cohort containing 16 PDR and 10 cataract patients and another validation cohort containing 8 PDR and 4 cataract patients were studied. AH was collected and subjected to proteomics analyses. Bioinformatics analysis and a machine learning-based pipeline called inference of biomolecular combinations with minimal bias were used to explore the functional relevance, hub proteins, and biomarkers.
Deep profiling of AH proteomes revealed several insights. First, the combination of SIAE, SEMA7A, GNS, and IGKV3D-15 and the combination of ATP6AP1, SPARCL1, and SERPINA7 could serve as surrogate protein biomarkers for monitoring PDR progression. Second, ALB, FN1, ACTB, SERPINA1, C3, and VTN acted as hub proteins in the profiling of AH proteomes. SERPINA1 was the protein with the highest correlation coefficient not only for BCVA but also for the duration of diabetes. Third, "Complement and coagulation cascades" was an important pathway for PDR development.
AH proteomics provides stable and accurate biomarkers for early warning and diagnosis of PDR. This study provides a deep understanding of the molecular mechanisms of PDR and a rich resource for optimizing PDR management.
为了解增殖性糖尿病视网膜病变（PDR）的病理生理机制和分子事件的复杂性，并评估房水（AH）在监测PDR发病中的诊断价值。
对一个包含16例PDR患者和10例白内障患者的队列以及另一个包含8例PDR患者和4例白内障患者的验证队列进行研究。收集房水并进行蛋白质组学分析。使用生物信息学分析和一种名为最小偏差生物分子组合推断的基于机器学习的流程来探索功能相关性、枢纽蛋白和生物标志物。
对房水蛋白质组的深度分析揭示了几个见解。首先，SIAE、SEMA7A、GNS和IGKV3D - 15的组合以及ATP6AP1、SPARCL1和SERPINA7的组合可作为监测PDR进展的替代蛋白质生物标志物。其次，ALB、FN1、ACTB、SERPINA1、C3和VTN在房水蛋白质组分析中充当枢纽蛋白。SERPINA1不仅是与最佳矫正视力（BCVA）相关性最高的蛋白质，也是与糖尿病病程相关性最高的蛋白质。第三，“补体和凝血级联反应”是PDR发展的重要途径。
房水蛋白质组学为PDR的早期预警和诊断提供了稳定且准确的生物标志物。本研究深入了解了PDR的分子机制，并为优化PDR管理提供了丰富的资源。
