蛋白质组
脑脊液
生物标志物
蛋白质组学
医学
生物标志物发现
神经炎症
疾病
帕金森病
发病机制
生物信息学
病理
生物
免疫学
基因
遗传学
作者
Özge Karayel,Sebastian Virreira Winter,Shalini Padmanabhan,Yuliya I. Kuras,Duc Tung Vu,Idil Tuncali,Kalpana Merchant,Anne‐Marie Wills,Clemens R. Scherzer,Matthias Mann
标识
DOI:10.1016/j.xcrm.2022.100661
摘要
Summary
Parkinson's disease (PD) is a growing burden worldwide, and there is no reliable biomarker used in clinical routines to date. Cerebrospinal fluid (CSF) is routinely collected in patients with neurological symptoms and should closely reflect alterations in PD patients' brains. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomics workflow for CSF proteome profiling. From two independent cohorts with over 200 individuals, our workflow reproducibly quantifies over 1,700 proteins from minimal CSF amounts. Machine learning determines OMD, CD44, VGF, PRL, and MAN2B1 to be altered in PD patients or to significantly correlate with clinical scores. We also uncover signatures of enhanced neuroinflammation in LRRK2 G2019S carriers, as indicated by increased levels of CTSS, PLD4, and HLA proteins. A comparison with our previously acquired urinary proteomes reveals a large overlap in PD-associated changes, including lysosomal proteins, opening up new avenues to improve our understanding of PD pathogenesis.
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