标题： 优化血小板纯化方法：提升临床应用的蛋白质组学研究 显示英文标题

标题： Refining Platelet Purification Methods: Enhancing Proteomics for Clinical Applications

摘要： 背景：血小板蛋白质组学为临床研究提供了宝贵的见解，但分离高纯度的血小板仍是一项挑战。现有的方法常常导致污染或血小板丢失，从而影响数据质量和可重复性。 目的：本研究旨在优化一种血小板分离技术，以获得高纯度样本且损失最小，并确定最有效的基于质谱的蛋白质组学方法，以实现最佳覆盖和灵敏度的血小板蛋白分析。 方法：我们通过调整离心时间来改进分离方案，以减少血液体积需求，同时保持血小板产量和纯度。使用优化后的方案，我们评估了三种蛋白质组学方法： 无标记定量与数据非依赖采集（LFQ-DIA）， 无标记定量与数据依赖采集（LFQ-DDA），以及串联质量标签标记与DDA（TMT-DDA）。 结果：LFQ-DIA在蛋白覆盖范围和灵敏度上优于LFQ-DDA和TMT-DDA。优化后的分离协议有效减少了污染和血小板丢失。此外，观察到与年龄相关的血小板蛋白组成差异，强调了在生物标志物发现研究中使用匹配年龄对照的重要性。 结论：优化的血小板分离方案提供了一种经济有效且可靠的方法，用于制备蛋白质组学所需的高纯度样本。LFQ-DIA是全面分析血小板蛋白的最佳方法。血小板蛋白质组的年龄相关变异突显了在临床蛋白质组学研究中进行人口统计学匹配的重要性。 显示英文摘要

摘要： Background: Platelet proteomics offers valuable insights for clinical research, yet isolating high-purity platelets remains a challenge. Current methods often lead to contamination or platelet loss, compromising data quality and reproducibility. Objectives: This study aimed to optimize a platelet isolation technique that yields high-purity samples with minimal loss and to identify the most effective mass spectrometry-based proteomic method for analyzing platelet proteins with optimal coverage and sensitivity. Methods: We refined an isolation protocol by adjusting centrifugation time to reduce blood volume requirements while preserving platelet yield and purity. Using this optimized method, we evaluated three proteomic approaches: Label-free Quantification with Data-Independent Acquisition (LFQ-DIA), Label-free Quantification with Data-Dependent Acquisition (LFQ-DDA), and Tandem Mass Tag labeling with DDA (TMT-DDA). Results: LFQ-DIA demonstrated superior protein coverage and sensitivity compared to LFQ-DDA and TMT-DDA. The refined isolation protocol effectively minimized contamination and platelet loss. Additionally, age-related differences in platelet protein composition were observed, highlighting the importance of using age-matched controls in biomarker discovery studies. Conclusions: The optimized platelet isolation protocol provides a cost-effective and reliable method for preparing high-purity samples for proteomics. LFQ-DIA is the most suitable approach for comprehensive platelet protein analysis. Age-related variation in platelet proteomes underscores the need for demographic matching in clinical proteomic research.