Xiaojuan Luo, Ke Cao, Ruizhi Wang, Weigen Wu, Tao Huang, Yan Zhang, Xiaoying Fu, Defa Li, Meifang He
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Abstract
Differentiating myosin heavy chain 9 (MYH9)-related disease (MYH9-RD) from immune thrombocytopenia (ITP) remains clinically challenging. This study utilized data-independent acquisition (DIA) plasma proteomics to identify distinguishing biomarker signatures. Profiling cohorts of MYH9-RD (n = 10), ITP (n = 10) and healthy controls (n = 14) quantified 2533 proteins, revealing distinct immune and metabolic remodelling. We identified 91 MYH9-RD-specific and 124 ITP-specific proteins, highlighting divergent organ involvement pathways. By integrating protein–protein interaction networks with Boruta and Random Forest machine-learning algorithms, we identified preliminary candidate biomarker panels (MYH9-RD panel: von Willebrand factor [VWF], cholesteryl ester transfer protein [CETP], apolipoprotein A-1 [APOA1], periostin [POSTN]; ITP panel: neutrophil gelatinase-associated lipocalin [NGAL], plasminogen activator inhibitor-1 [PAI-1], carboxypeptidase B2 [CPB2]) that demonstrated excellent apparent discrimination. This exploratory study provides a hypothesis-generating framework, revealing fundamentally distinct molecular landscapes between congenital and acquired macrothrombocytopenia. Pending rigorous future external validation, these preliminary candidate biomarkers offer novel biological insights into the divergent pathophysiologies of MYH9-RD and ITP.
血浆蛋白质组学揭示的儿童myh9相关疾病和免疫性血小板减少症鉴别诊断的新生物标志物
鉴别肌球蛋白重链9 (MYH9)相关疾病(MYH9- rd)与免疫性血小板减少症(ITP)仍然具有临床挑战性。本研究利用数据独立采集(DIA)血浆蛋白质组学来识别不同的生物标志物特征。MYH9-RD (n = 10)、ITP (n = 10)和健康对照(n = 14)的分析队列量化了2533种蛋白质,揭示了不同的免疫和代谢重塑。我们鉴定了91个myh9 - rd特异性蛋白和124个itp特异性蛋白,突出了不同的器官受累途径。通过将蛋白-蛋白相互作用网络与Boruta和随机森林机器学习算法相结合,我们确定了初步的候选生物标志物面板(MYH9-RD面板:血管性血血病因子[VWF],胆固醇酯转移蛋白[CETP],载脂蛋白A-1 [APOA1],骨膜蛋白[POSTN]; ITP面板:中性粒细胞明胶酶相关脂钙蛋白[NGAL],纤溶酶原激活物抑制剂-1 [PAI-1],羧肽酶B2 [CPB2]),表现出良好的明显区别。这项探索性研究提供了一个假设生成框架,揭示了先天性和获得性巨血小板减少症之间根本不同的分子景观。在未来严格的外部验证中,这些初步候选生物标志物为MYH9-RD和ITP的不同病理生理提供了新的生物学见解。
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