Abstract：
Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers, and subtle neuroinflammation. Studies further suggest a dysfunctional blood brain barrier (BBB). The endothelial Glycocalyx (GLX) functions as a protective layer in the BBB, and GLX shedding leads to BBB dysfunction. This study aimed to investigate whether a panel of 11 GLX molecules derived from peripheral blood could differentiate antipsychotic-naïve first-episode psychosis patients (n47) from healthy controls (HC, n49) and whether GLX shedding correlated with symptom severity. Blood samples were collected at baseline and serum was isolated for GLX marker detection. Machine learning models were applied to test whether patterns in GLX markers could classify patient groups. Associations between GLX markers and symptom severity were explored. Patients showed significantly increased levels of three GLX markers compared to HC. Based on the panel of 11 GLX markers, machine learning models achieved a significant mean classification accuracy of 81%. Post hoc analysis revealed associations between increased GLX markers and symptom severity. This study demonstrates the potential of GLX molecules as immuno-neuropsychiatric biomarkers for early diagnosis of psychosis, as well as indicate a compromised BBB. Further research is warranted to explore the role of GLX in the early detection of psychotic disorders.
摘要：
精神疾病与免疫系统异常有关,炎症标志物增加，和微妙的神经炎症。研究进一步提示功能失调的血脑屏障(BBB)。内皮糖萼（GLX）在血脑屏障中起保护层的作用，GLX脱落导致BBB功能障碍。这项研究旨在调查一组来自外周血的11个GLX分子是否可以区分抗精神病药初发精神病患者（n47）与健康对照（HC，n49)以及GLX脱落是否与症状严重程度相关。在基线时收集血样,分离血清用于GLX标记物检测。机器学习模型用于测试GLX标记中的模式是否可以对患者组进行分类。研究了GLX标记与症状严重程度之间的关联。与HC相比,患者显示三种GLX标志物的水平显著增加。基于11个GLX标记的面板，机器学习模型实现了81%的显著平均分类准确率。事后分析显示GLX标志物增加与症状严重程度之间存在关联。这项研究证明了GLX分子作为早期诊断精神病的免疫神经精神生物标志物的潜力。以及表明BBB受损。需要进一步的研究来探索GLX在早期发现精神病中的作用。
