癫痫和非癫痫发作与与神经炎症相关的循环血浆蛋白变化的关联。
Association of Epileptic and Nonepileptic Seizures and Changes in Circulating Plasma Proteins Linked to Neuroinflammation.
机构信息
From Cognizance Biomarkers (J.M.G., E.J.B., R.D.S., T.M.W.), Spring House, PA; Christiana Care (J.R.P.), Newark, DE; and Department of Neurology (P.B.C.), University of Maryland, Baltimore.
出版信息
Neurology. 2021 Mar 9;96(10):e1443-e1452. doi: 10.1212/WNL.0000000000011552. Epub 2021 Jan 25.
OBJECTIVE
To develop a diagnostic test that stratifies epileptic seizures (ES) from psychogenic nonepileptic seizures (PNES) by developing a multimodal algorithm that integrates plasma concentrations of selected immune response-associated proteins and patient clinical risk factors for seizure.
METHODS
Daily blood samples were collected from patients evaluated in the epilepsy monitoring unit within 24 hours after EEG confirmed ES or PNES and plasma was isolated. Levels of 51 candidate plasma proteins were quantified using an automated, multiplexed, sandwich ELISA and then integrated and analyzed using our diagnostic algorithm.
RESULTS
A 51-protein multiplexed ELISA panel was used to determine the plasma concentrations of patients with ES, patients with PNES, and healthy controls. A combination of protein concentrations, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), intercellular adhesion molecule 1 (ICAM-1), monocyte chemoattractant protein-2 (MCP-2), and tumor necrosis factor-receptor 1 (TNF-R1) indicated a probability that a patient recently experienced a seizure, with TRAIL and ICAM-1 levels higher in PNES than ES and MCP-2 and TNF-R1 levels higher in ES than PNES. The diagnostic algorithm yielded an area under the receiver operating characteristic curve (AUC) of 0.94 ± 0.07, sensitivity of 82.6% (95% confidence interval [CI] 62.9-93.0), and specificity of 91.6% (95% CI 74.2-97.7). Expanding the diagnostic algorithm to include previously identified PNES risk factors enhanced diagnostic performance, with AUC of 0.97 ± 0.05, sensitivity of 91.3% (95% CI 73.2-97.6), and specificity of 95.8% (95% CI 79.8-99.3).
CONCLUSIONS
These 4 plasma proteins could provide a rapid, cost-effective, and accurate blood-based diagnostic test to confirm recent ES or PNES.
CLASSIFICATION OF EVIDENCE
This study provides Class III evidence that variable levels of 4 plasma proteins, when analyzed by a diagnostic algorithm, can distinguish PNES from ES with sensitivity of 82.6% and specificity of 91.6%.
目的
通过开发一种整合选定免疫反应相关蛋白的血浆浓度和患者癫痫发作的临床风险因素的多模态算法，开发一种可将癫痫发作（ES）与心因性非癫痫发作（PNES）区分开的诊断测试。
方法
在脑电图确认 ES 或 PNES 后 24 小时内，从癫痫监测病房中评估的患者每天采集一次血液样本，并分离血浆。使用自动化、多重、三明治 ELISA 定量测定 51 种候选血浆蛋白的水平，然后使用我们的诊断算法对其进行整合和分析。
结果
使用 51 种蛋白质多重 ELISA 面板来确定 ES 患者、PNES 患者和健康对照者的血浆浓度。组合蛋白浓度、肿瘤坏死因子相关凋亡诱导配体（TRAIL）、细胞间黏附分子 1（ICAM-1）、单核细胞趋化蛋白-2（MCP-2）和肿瘤坏死因子受体 1（TNF-R1）表明患者最近经历过癫痫发作的可能性，PNES 中 TRAIL 和 ICAM-1 的水平高于 ES，而 ES 中 MCP-2 和 TNF-R1 的水平高于 PNES。诊断算法产生的受试者工作特征曲线（ROC）下面积（AUC）为 0.94±0.07，敏感性为 82.6%（95%置信区间[CI]62.9-93.0），特异性为 91.6%（95% CI 74.2-97.7）。将诊断算法扩展到包括先前确定的 PNES 风险因素可提高诊断性能，AUC 为 0.97±0.05，敏感性为 91.3%（95% CI 73.2-97.6），特异性为 95.8%（95% CI 79.8-99.3）。
结论
这 4 种血浆蛋白可提供一种快速、经济有效的基于血液的诊断测试，以确认近期的 ES 或 PNES。
分类证据
本研究提供 III 级证据，表明通过诊断算法分析时，4 种血浆蛋白的可变水平可将 PNES 与 ES 区分开来，其敏感性为 82.6%，特异性为 91.6%。
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