Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen (UMCG), University of Groningen, Groningen, The Netherlands.
Transl Psychiatry. 2022 Oct 30;12(1):457. doi: 10.1038/s41398-022-02229-w.
A significant proportion of the personal and economic burden of schizophrenia can be attributed to the late diagnosis or misdiagnosis of the disorder. A novel, objective diagnostic approaches could facilitate the early detection and treatment of schizophrenia and improve patient outcomes. In the present study, we aimed to identify robust schizophrenia-specific blood biomarkers, with the goal of developing an accurate diagnostic model. The levels of selected serum and peripheral blood mononuclear cell (PBMC) markers relevant to metabolic and immune function were measured in healthy controls (n = 26) and recent-onset schizophrenia patients (n = 36) using multiplexed immunoassays and flow cytometry. Analysis of covariance revealed significant upregulation of insulin receptor (IR) and fatty acid translocase (CD36) levels in T helper cells (F = 10.75, P = 0.002, Q = 0.024 and F = 21.58, P = 2.8 × 10, Q = 0.0004, respectively), as well as downregulation of glucose transporter 1 (GLUT1) expression in monocytes (F = 21.46, P = 2.9 × 10, Q = 0.0004). The most robust predictors, monocyte GLUT1 and T helper cell CD36, were used to develop a diagnostic model, which showed a leave-one-out cross-validated area under the receiver operating characteristic curve (AUC) of 0.78 (95% CI: 0.66-0.92). The diagnostic model was validated in two independent datasets. The model was able to distinguish first-onset, drug-naïve schizophrenia patients (n = 34) from healthy controls (n = 39) with an AUC of 0.75 (95% CI: 0.64-0.86), and also differentiated schizophrenia patients (n = 22) from patients with other neuropsychiatric conditions, including bipolar disorder, major depressive disorder and autism spectrum disorder (n = 68), with an AUC of 0.83 (95% CI: 0.75-0.92). These findings indicate that PBMC-derived biomarkers have the potential to support an accurate and objective differential diagnosis of schizophrenia.
精神分裂症患者的个人和经济负担很大程度上可归因于该疾病的诊断延迟或误诊。新的客观诊断方法可以促进精神分裂症的早期发现和治疗，并改善患者的预后。本研究旨在鉴定稳健的精神分裂症特异性血液生物标志物，以开发准确的诊断模型。使用多重免疫测定法和流式细胞术测量了 26 名健康对照者和 36 名首发精神分裂症患者的选定血清和外周血单个核细胞（peripheral blood mononuclear cell，PBMC）标志物的水平。协方差分析显示，T 辅助细胞中胰岛素受体（insulin receptor，IR）和脂肪酸转运蛋白（fatty acid translocase，CD36）水平显著上调（F=10.75，P=0.002，Q=0.024 和 F=21.58，P=2.8×10，Q=0.0004），单核细胞中葡萄糖转运蛋白 1（glucose transporter 1，GLUT1）表达下调（F=21.46，P=2.9×10，Q=0.0004）。使用最稳健的预测因子，即单核细胞 GLUT1 和 T 辅助细胞 CD36，开发了一个诊断模型，该模型的受试者工作特征曲线（receiver operating characteristic curve，ROC）下面积在留一法交叉验证中为 0.78（95%置信区间：0.66-0.92）。该诊断模型在两个独立数据集得到了验证。该模型能够区分首发、未经药物治疗的精神分裂症患者（n=34）和健康对照者（n=39），其 AUC 为 0.75（95%置信区间：0.64-0.86），也能区分精神分裂症患者（n=22）和其他神经精神疾病患者（包括双相情感障碍、重性抑郁障碍和自闭症谱系障碍），其 AUC 为 0.83（95%置信区间：0.75-0.92）。这些发现表明，PBMC 衍生的生物标志物具有支持精神分裂症准确客观的鉴别诊断的潜力。
