基于核磁共振的脑脊液代谢组学分析可区分中枢神经系统的炎症性疾病。
NMR metabolomics of cerebrospinal fluid differentiates inflammatory diseases of the central nervous system.
机构信息
Department of Nutrition, University of California, Davis, California, United States of America.
Department of Pediatrics, Division of Infectious Disease, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.
出版信息
PLoS Negl Trop Dis. 2018 Dec 17;12(12):e0007045. doi: 10.1371/journal.pntd.0007045. eCollection 2018 Dec.
BACKGROUND
Myriad infectious and noninfectious causes of encephalomyelitis (EM) have similar clinical manifestations, presenting serious challenges to diagnosis and treatment. Metabolomics of cerebrospinal fluid (CSF) was explored as a method of differentiating among neurological diseases causing EM using a single CSF sample.
METHODOLOGY/PRINCIPAL FINDINGS: 1H NMR metabolomics was applied to CSF samples from 27 patients with a laboratory-confirmed disease, including Lyme disease or West Nile Virus meningoencephalitis, multiple sclerosis, rabies, or Histoplasma meningitis, and 25 controls. Cluster analyses distinguished samples by infection status and moderately by pathogen, with shared and differentiating metabolite patterns observed among diseases. CART analysis predicted infection status with 100% sensitivity and 93% specificity.
CONCLUSIONS/SIGNIFICANCE: These preliminary results suggest the potential utility of CSF metabolomics as a rapid screening test to enhance diagnostic accuracies and improve patient outcomes.
背景
多种感染性和非感染性原因均可导致脑脊髓炎（EM），其临床表现相似，给诊断和治疗带来了极大挑战。本研究拟采用脑脊液（CSF）代谢组学方法，通过单次 CSF 样本分析来鉴别引起 EM 的各种神经疾病。
方法/主要发现：本研究采用 1H-NMR 代谢组学方法对 27 例经实验室确诊的疾病患者（包括莱姆病或西尼罗河病毒脑膜脑炎、多发性硬化症、狂犬病或组织胞浆菌性脑膜炎）和 25 例对照者的 CSF 样本进行了分析。聚类分析根据感染状态区分了样本，同时根据病原体也进行了适度区分，不同疾病间存在共同和差异的代谢物模式。CART 分析以 100%的敏感性和 93%的特异性预测了感染状态。
结论/意义：这些初步结果表明，CSF 代谢组学作为一种快速筛选试验，具有提高诊断准确性和改善患者预后的潜在应用价值。
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