Department of Endocrinology, Shenzhen People's Hospital (The Second Clinical Medical College of Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, China.
Department of Ophthalmology, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, China.
Front Endocrinol (Lausanne). 2024 May 10;15:1382896. doi: 10.3389/fendo.2024.1382896. eCollection 2024.
Proliferative diabetic retinopathy (PDR), a major cause of blindness, is characterized by complex pathogenesis. This study integrates single-cell RNA sequencing (scRNA-seq), Non-negative Matrix Factorization (NMF), machine learning, and AlphaFold 2 methods to explore the molecular level of PDR.
We analyzed scRNA-seq data from PDR patients and healthy controls to identify distinct cellular subtypes and gene expression patterns. NMF was used to define specific transcriptional programs in PDR. The oxidative stress-related genes (ORGs) identified within Meta-Program 1 were utilized to construct a predictive model using twelve machine learning algorithms. Furthermore, we employed AlphaFold 2 for the prediction of protein structures, complementing this with molecular docking to validate the structural foundation of potential therapeutic targets. We also analyzed protein-protein interaction (PPI) networks and the interplay among key ORGs.
Our scRNA-seq analysis revealed five major cell types and 14 subcell types in PDR patients, with significant differences in gene expression compared to those in controls. We identified three key meta-programs underscoring the role of microglia in the pathogenesis of PDR. Three critical ORGs (ALKBH1, PSIP1, and ATP13A2) were identified, with the best-performing predictive model demonstrating high accuracy (AUC of 0.989 in the training cohort and 0.833 in the validation cohort). Moreover, AlphaFold 2 predictions combined with molecular docking revealed that resveratrol has a strong affinity for ALKBH1, indicating its potential as a targeted therapeutic agent. PPI network analysis, revealed a complex network of interactions among the hub ORGs and other genes, suggesting a collective role in PDR pathogenesis.
This study provides insights into the cellular and molecular aspects of PDR, identifying potential biomarkers and therapeutic targets using advanced technological approaches.
增生性糖尿病视网膜病变（PDR）是失明的主要原因，其发病机制复杂。本研究整合单细胞 RNA 测序（scRNA-seq）、非负矩阵分解（NMF）、机器学习和 AlphaFold 2 方法，从分子水平探讨 PDR。
我们分析了来自 PDR 患者和健康对照的 scRNA-seq 数据，以鉴定不同的细胞亚型和基因表达模式。NMF 用于定义 PDR 中的特定转录程序。在 Meta-Program 1 中鉴定的与氧化应激相关的基因（ORGs）用于使用 12 种机器学习算法构建预测模型。此外，我们使用 AlphaFold 2 进行蛋白质结构预测，并进行分子对接验证潜在治疗靶点的结构基础。我们还分析了蛋白质-蛋白质相互作用（PPI）网络和关键 ORGs 之间的相互作用。
我们的 scRNA-seq 分析显示，PDR 患者中有 5 种主要细胞类型和 14 种亚细胞类型，与对照组相比，其基因表达存在显著差异。我们确定了三个关键的元程序，强调了小胶质细胞在 PDR 发病机制中的作用。鉴定了三个关键的 ORGs（ALKBH1、PSIP1 和 ATP13A2），表现最佳的预测模型显示出较高的准确性（训练队列的 AUC 为 0.989，验证队列的 AUC 为 0.833）。此外，AlphaFold 2 预测结合分子对接表明，白藜芦醇与 ALKBH1 具有很强的亲和力，表明其作为靶向治疗药物的潜力。PPI 网络分析揭示了枢纽 ORGs 与其他基因之间复杂的相互作用网络，表明它们在 PDR 发病机制中具有共同作用。
本研究深入了解了 PDR 的细胞和分子方面，使用先进的技术方法鉴定了潜在的生物标志物和治疗靶点。
