Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
Transl Psychiatry. 2012 Feb 21;2(2):e82. doi: 10.1038/tp.2012.3.
The current inability of psychiatric medicine to objectively select the most appropriate treatment or to predict imminent relapse are major factors contributing to the severity and clinical burden of schizophrenia. We have previously used multiplexed immunoassays to show that schizophrenia patients have a distinctive molecular signature in serum compared with healthy control subjects. In the present study, we used the same approach to measure biomarkers in a population of 77 schizophrenia patients who were followed up over 25 months with four aims: (1) to identify molecules associated with symptom severity in antipsychotic naive and unmedicated patients, (2) to determine biomarker signatures that could predict response over a 6-week treatment period, (3) to identify molecular panels that could predict the time to relapse in a cross-sectional population of patients in remission and (4) to investigate how the biological relapse signature changed throughout the treatment course. This led to identification of molecular signatures that could predict symptom improvement over the first 6 weeks of treatment as well as predict time to relapse in a subset of 18 patients who experienced recurrence of symptoms. This study provides the groundwork for the development of novel objective clinical tests that can help psychiatrists in the clinical management of schizophrenia.
精神医学目前无法客观选择最合适的治疗方法或预测即将复发，这是导致精神分裂症严重程度和临床负担的主要因素。我们之前使用多重免疫分析方法表明，与健康对照组相比，精神分裂症患者的血清中有独特的分子特征。在本研究中，我们使用相同的方法测量了 77 名精神分裂症患者的生物标志物，这些患者在 25 个月的时间内接受了随访，目的有四个：(1) 确定与未经抗精神病药物治疗和未经药物治疗的患者的症状严重程度相关的分子；(2) 确定可预测 6 周治疗期内反应的生物标志物特征；(3) 确定可预测缓解期横断面患者复发时间的分子谱；(4) 研究生物复发特征在整个治疗过程中如何变化。这导致确定了可以预测治疗前 6 周症状改善的分子特征，以及可以预测 18 名出现症状复发的患者中复发时间的特征。这项研究为开发新的客观临床测试奠定了基础，有助于精神科医生对精神分裂症进行临床管理。
