Abstract:
Reversible cerebral vasoconstriction syndrome (RCVS) is a complex neurovascular disorder characterized by repetitive thunderclap headaches and reversible cerebral vasoconstriction. The pathophysiological mechanism of this mysterious syndrome remains underexplored and there is no clinically available molecular biomarker. To provide insight into the pathogenesis of RCVS, this study reported the first landscape of dysregulated proteome of cerebrospinal fluid (CSF) in patients with RCVS (n = 21) compared to the age- and sex-matched controls (n = 20) using data-independent acquisition mass spectrometry. Protein-protein interaction and functional enrichment analysis were employed to construct functional protein networks using the RCVS proteome. An RCVS-CSF proteome library resource of 1054 proteins was established, which illuminated large groups of upregulated proteins enriched in the brain and blood-brain barrier (BBB). Personalized RCVS-CSF proteomic profiles from 17 RCVS patients and 20 controls reveal proteomic changes involving the complement system, adhesion molecules, and extracellular matrix, which may contribute to the disruption of BBB and dysregulation of neurovascular units. Moreover, an additional validation cohort validated a panel of biomarker candidates and a two-protein signature predicted by machine learning model to discriminate RCVS patients from controls with an area under the curve of 0.997. This study reveals the first RCVS proteome and a potential pathogenetic mechanism of BBB and neurovascular unit dysfunction. It also nominates potential biomarker candidates that are mechanistically plausible for RCVS, which may offer potential diagnostic and therapeutic opportunities beyond the clinical manifestations.
摘要:
可逆性脑血管收缩综合征(RCVS)是一种复杂的神经血管疾病,其特征是反复雷击头痛和可逆性脑血管收缩。这种神秘综合征的病理生理机制仍未被探索,并且没有临床上可用的分子生物标志物。为深入了解RCVS的发病机制,本研究采用数据无关采集质谱(DIA-MS),与年龄和性别匹配的对照组(n=20)相比,首次报道了RCVS患者(n=21)脑脊液(CSF)蛋白质组失调的情况.蛋白质-蛋白质相互作用和功能富集分析用于使用RCVS蛋白质组构建功能蛋白质网络。建立了1,054种蛋白质的RCVS-CSF蛋白质组文库资源,它照亮了大量富含大脑和血脑屏障(BBB)的上调蛋白质。来自17名RCVS患者和20名对照的个性化RCVS-CSF蛋白质组学图谱揭示了涉及补体系统的蛋白质组学变化,粘附分子,和细胞外基质,这可能有助于BBB的破坏和神经血管单位的失调。此外,另一个验证队列验证了一组生物标志物候选物和通过机器学习模型预测的双蛋白特征,以区分RCVS患者和对照组,曲线下面积为0.997.这项研究揭示了第一个RCVS蛋白质组以及BBB和神经血管单元功能障碍的潜在发病机制。它还提名了潜在的生物标志物候选人,这些候选人在机械上对RCVS是合理的,这可能提供超出临床表现的潜在诊断和治疗机会。