基于细胞外囊泡的 L1CAM 阳性生物标志物有望成为帕金森病的预测指标

Brain-X Pub Date : 2024-06-24 DOI:10.1002/brx2.66
Minchao Lai, Keying Guo, Yongzhi Huang, Dian Wang, Yanhong Duo, Junliang Yuan, Bowen Shu
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引用次数: 0

摘要

总之,L1EV α-突触核蛋白被鉴定为一种血清生物标记物,可通过血液检测将极易罹患帕金森病的人与正常人区分开来,这是帕金森病早期诊断领域的一项重大突破。虽然还需要进一步的研究来验证和完善这一生物标记物的效用,但它在改变帕金森病早期检测方面的潜力是一项重大进步。通过促进以患者为中心的协作方法,将前沿研究、创新技术、高/低通量筛查、检测技术工具箱、数据算法4、5和社区参与结合起来,科学界和医学界可以开发出有效的个性化方法来管理和治疗帕金森病:构思、写作--原稿。Keying Guo:构思、写作--原稿。黄永志:撰写-原稿。Dian Wang:写作--审稿&amp; 编辑。多艳红督导、写作--审阅和编辑。袁俊良督导、写作--审阅和编辑。舒博文:构思、项目管理、指导、写作--审阅和编辑。所有作者声明无利益冲突。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The L1CAM-positive extracellular vesicle-based biomarker as a promising predictor of Parkinson's disease

Parkinson's disease (PD) is a multifaceted neurodegenerative disorder characterized by a prolonged prodromal phase followed by the onset of clinical motor symptoms. The development of reliable biomarkers for individuals at risk of developing PD during this prodromal phase is a central focus of research in the field, to enable early interventions that could potentially modify the disease progression and improve patient outcomes.1, 2

Yan et al., have made significant progress by examining the potential of serum L1CAM-positive extracellular vesicle (L1EV) associated α-synuclein as a biomarker for identification of at-risk individuals for developing PD.3 Their cross-sectional study involved a cohort of 576 subjects (from the Parkinson's Progression Markers Initiative (PPMI) and a German cohort) and aimed to evaluate the efficacy of serum L1EV derived α-synuclein in distinguishing individuals at risk of developing PD from healthy control (HC) subjects.

The findings of this study were encouraging, revealing the potential of serum L1EV α-synuclein as a promising indicator for screen out the ones with high risk of developing PD. By carefully establishing a threshold for serum L1EV α-synuclein levels, the researchers were able to distinguish subjects with independent rapid eye movement and sleep behavior disorder (iRBD) from healthy subjects with an impressive degree of accuracy, as demonstrated by an area under the curve (AUC) value of 0.88 using receiver operating characteristic (ROC) model. Furthermore, when applying the method to a multicenter cohort, this biomarker differentiated individuals with over 80% probability of occurrence of prodromal PD from individuals with <5% probability of developing prodromal PD or healthy controls, both with AUC values of 0.80. The robust predictive power of α-synuclein from L1EV for distinguishing high-risk subjects from healthy controls was further underscored by an AUC value of 0.90.3

In addition, the study demonstrated that subjects with multiple prodromal markers expressed higher levels of L1EV derived α-synuclein, especially in those with an abnormal dopamine transporter single-photon emission computed tomography (DAT- SPECT), suggesting that the simultaneous measurement of L1EV α-synuclein and specific prodromal markers could improve the stratification of at-risk individuals. Remarkably, the study also found that approximately 80% of the cases that eventually phenoconverted to PD or related Lewy body diseases exhibited L1EV α-synuclein levels higher than the derived threshold, further emphasizing the potential utility of this biomarker to discover the individuals at the highest risk of developing PD.

In addition to its diagnostic potential, the study highlighted the positive correlation between increased L1EV α-synuclein levels and positive results from cerebrospinal fluid α-synuclein seed amplification assays. This suggested that serum L1EV α-synuclein could serve as a viable proxy biomarker for underlying brain pathology, reflecting the presence of abnormal α-synuclein aggregation. Furthermore, this study also revealed that elevated L1EV α-synuclein was correlated with a prolonged time to phenoconversion to PD. This association may imply a protective efflux role for α-synuclein outside neurons in response to lysosome inhibition induced by disease.

The study provides a promising framework for establishing accessible and cost-effective screening methods for individuals at risk of developing PD. By highlighting the potential of serum L1EV derived α-synuclein as a reliable biomarker, this research has established a solid basis for future research and clinical trials dedicated to refining and validating the utility of this biomarker. Beyond the scope of biomarker, the findings are relevant to the broader paradigm shift towards patient-centric, data-driven healthcare, emphasizing the necessity of tailored, personalized approaches that consider the specific genetic, and prodromal markers influencing PD susceptibility and progression. By harnessing the capabilities of big data algorithm, artificial intelligence, and machine learning, researchers and clinicians can gain valuable insights into the complex interplay among various factors contributing to PD pathophysiology, paving the way for timely interventions and personalized treatment approaches during the early stages of disease evolution.

While the study represents a significant step forward in the quest for a viable biomarker for early detection of PD, obstacles remain. Further longitudinal validation in huger and more diverse populations is necessary to carefully examine the clinical utility of the biomarker as a widely applicable diagnostic tool. Nevertheless, this study offers a promising approach to the development of effective screening and diagnostic methodologies for identifying at-risk individuals during the prodromal phase of PD.

In conclusion, the identification of L1EV α-synuclein as a serum biomarker in blood test for distinguishing individuals with high tendency of developing PD from normal ones represents a significant breakthrough in the field of early PD diagnostics. While further research is needed to validate and refine the utility of this biomarker, its potential to transform early detection for PD represents as a substantial advancement. By fostering a collaborative, patient-centric approach that integrates cutting-edge research, innovative technology, high-/low-throughput screening, detection technology toolboxes, data algorithms,4, 5 and community engagement, the scientific and medical community can develop effective and personalized approaches to managing and treating PD.

Minchao Lai: Conceptualization, Writing – original draft. Keying Guo: Conceptualization, Writing – original draft. Yongzhi Huang: Writing – original draft. Dian Wang: Writing – review & editing. Yanhong Duo: Supervision, Writing – review & editing. Junliang Yuan: Supervision, Writing – review & editing. Bowen Shu: Conceptualization, Project administration, Supervision, Writing – review & editing.

All authors declare no conflicts of interest.

Ethics approval was not needed in this study.

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