Global, in situ analysis of the structural proteome in individuals with Parkinson's disease to identify a new class of biomarker
Global, in situ analysis of the structural proteome in individuals with Parkinson's disease to identify a new class of biomarker
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DOI：
10.1038/s41594-022-00837-0
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发表时间：
2022-10-12
影响因子：
16.8
通讯作者：
Picotti, Paola
中科院分区：
文献类型：
--
作者：
Mackmull, Marie-Therese;Nagel, Luise;Picotti, Paola
帕金森病 (PD) 是一种流行的神经退行性疾病，需要强大的生物标志物。由于蛋白质结构反映了功能，我们测试了蛋白质结构变化的整体原位分析是否可以提供对 PD 病理生理学的深入了解，并可以为结构性疾病生物标志物的新概念提供信息。使用有限蛋白水解质谱 (LiP-MS)，我们在帕金森病患者的脑脊液 (CSF) 中相对于健康捐赠者鉴定出了 76 种结构改变的蛋白质。这些蛋白质在帕金森病中失调的过程中富集，并且一些蛋白质还在帕金森病脑样本中表现出结构变化。 CSF 蛋白质结构信息在区分健康参与者和 PD 患者方面优于丰度信息，并改善了 CSF 标志性 PD 蛋白 α-突触核蛋白测量的区分性能。我们还首次对健康个体中结构蛋白质组的个体间变异进行了分析，识别了可变蛋白质区域的生物物理特征。尽管需要独立验证，但我们的数据表明，人类结构蛋白质组的整体分析将指导疾病的新型结构生物标志物的开发，并能够生成关于潜在疾病过程的假设。
Parkinson's disease (PD) is a prevalent neurodegenerative disease for which robust biomarkers are needed. Because protein structure reflects function, we tested whether global, in situ analysis of protein structural changes provides insight into PD pathophysiology and could inform a new concept of structural disease biomarkers. Using limited proteolysis-mass spectrometry (LiP-MS), we identified 76 structurally altered proteins in cerebrospinal fluid (CSF) of individuals with PD relative to healthy donors. These proteins were enriched in processes misregulated in PD, and some proteins also showed structural changes in PD brain samples. CSF protein structural information outperformed abundance information in discriminating between healthy participants and those with PD and improved the discriminatory performance of CSF measures of the hallmark PD protein alpha-synuclein. We also present the first analysis of inter-individual variability of a structural proteome in healthy individuals, identifying biophysical features of variable protein regions. Although independent validation is needed, our data suggest that global analyses of the human structural proteome will guide the development of novel structural biomarkers of disease and enable hypothesis generation about underlying disease processes.