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开发一种基于血液的分子生物标志物检测方法,用于在疾病发作前识别精神分裂症。

Development of a blood-based molecular biomarker test for identification of schizophrenia before disease onset.

作者信息

Chan M K, Krebs M-O, Cox D, Guest P C, Yolken R H, Rahmoune H, Rothermundt M, Steiner J, Leweke F M, van Beveren N J M, Niebuhr D W, Weber N S, Cowan D N, Suarez-Pinilla P, Crespo-Facorro B, Mam-Lam-Fook C, Bourgin J, Wenstrup R J, Kaldate R R, Cooper J D, Bahn S

机构信息

Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.

1] INSERM UMR 894, Centre of Psychiatry and Neurosciences, Lab Pathophysiology of Psychiatric Disorders, Institut de Psychiatrie (GDR 3557) Paris, France [2] University Paris Descartes, Sorbonne Paris Cité, Faculty of Medicine Paris Descartes, Service Hospitalo-Universitaire, Centre hospitalier Sainte-Anne, Paris, France.

出版信息

Transl Psychiatry. 2015 Jul 14;5(7):e601. doi: 10.1038/tp.2015.91.

Abstract

Recent research efforts have progressively shifted towards preventative psychiatry and prognostic identification of individuals before disease onset. We describe the development of a serum biomarker test for the identification of individuals at risk of developing schizophrenia based on multiplex immunoassay profiling analysis of 957 serum samples. First, we conducted a meta-analysis of five independent cohorts of 127 first-onset drug-naive schizophrenia patients and 204 controls. Using least absolute shrinkage and selection operator regression, we identified an optimal panel of 26 biomarkers that best discriminated patients and controls. Next, we successfully validated this biomarker panel using two independent validation cohorts of 93 patients and 88 controls, which yielded an area under the curve (AUC) of 0.97 (0.95-1.00) for schizophrenia detection. Finally, we tested its predictive performance for identifying patients before onset of psychosis using two cohorts of 445 pre-onset or at-risk individuals. The predictive performance achieved by the panel was excellent for identifying USA military personnel (AUC: 0.90 (0.86-0.95)) and help-seeking prodromal individuals (AUC: 0.82 (0.71-0.93)) who developed schizophrenia up to 2 years after baseline sampling. The performance increased further using the latter cohort following the incorporation of CAARMS (Comprehensive Assessment of At-Risk Mental State) positive subscale symptom scores into the model (AUC: 0.90 (0.82-0.98)). The current findings may represent the first successful step towards a test that could address the clinical need for early intervention in psychiatry. Further developments of a combined molecular/symptom-based test will aid clinicians in the identification of vulnerable patients early in the disease process, allowing more effective therapeutic intervention before overt disease onset.

摘要

最近的研究工作已逐渐转向预防性精神病学以及在疾病发作前对个体进行预后识别。我们描述了一种血清生物标志物检测方法的开发,该方法基于对957份血清样本的多重免疫分析谱分析来识别有患精神分裂症风险的个体。首先,我们对五个独立队列进行了荟萃分析,这些队列包括127例首次发病、未使用过药物的精神分裂症患者和204例对照。使用最小绝对收缩和选择算子回归,我们确定了一个由26种生物标志物组成的最佳组合,该组合能最好地区分患者和对照。接下来,我们使用93例患者和88例对照的两个独立验证队列成功验证了该生物标志物组合,其在精神分裂症检测中的曲线下面积(AUC)为0.97(0.95 - 1.00)。最后,我们使用两个由445名发病前或有风险个体组成的队列测试了其在识别精神病发作前患者方面的预测性能。该组合在识别美国军事人员(AUC:0.90(0.86 - 0.95))和寻求帮助的前驱个体(AUC:0.82(0.71 - 0.93))方面表现出色,这些个体在基线采样后长达2年发展为精神分裂症。在将CAARMS(高危精神状态综合评估)阳性子量表症状评分纳入模型后,使用后一个队列时性能进一步提高(AUC:0.90(0.82 - 0.98))。目前的研究结果可能代表了朝着能够满足精神病学早期干预临床需求的检测迈出的第一个成功步骤。基于分子/症状的联合检测的进一步发展将有助于临床医生在疾病过程早期识别易患患者,从而在明显疾病发作前进行更有效的治疗干预。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd26/5068725/88b7b6b1f6da/tp201591f1.jpg

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