Zezhi Li, MD, PhD, Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, and Department of Neurology, Shanghai Changhai Hospital, Secondary Military Medical University, Shanghai, China; Chen Zhang, MD, PhD, Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, and Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, China; Jinbo Fan, PhD, Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, USA; Chengmei Yuan, MD, PhD, Jia Huang, MD, Jun Chen, MD, PhD, Zhenghui Yi, MD, PhD, Zuowei Wang, MD, PhD, Wu Hong, MD, PhD, Yong Wang, MD, PhD, Weihong Lu, MD, PhD, Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Yangtai Guan, MD, PhD, Department of Neurology, Shanghai Changhai Hospital, Secondary Military Medical University, Shanghai, China; Zhiguo Wu, MD, PhD, Yousong Su, MD, Lan Cao, MD, Yingyan Hu, MD, Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Yong Hao, MD, PhD, Mingyuan Liu, MD, PhD, Department of Neurology, Shanghai Changhai Hospital, Secondary Military Medical University, Shanghai, China; Shunying Yu, MD, PhD, Donghong Cui, MD, PhD, Department of Genetics, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Lin Xu, PhD, Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming, Yunnan, China; Yanyan Song, PhD, Department of Pharmacology and Biostatistics, Institute of Medical Sciences, Shanghai Jiaotong University School of Medicine, Shanghai, China; Yiru Fang, MD, PhD, Division of Mood Disorders, Shanghai Mental Health Cente
Br J Psychiatry. 2014 Jul;205(1):29-35. doi: 10.1192/bjp.bp.113.134064. Epub 2014 Apr 24.
Early identification of patients with bipolar disorder during their first depressive episode is beneficial to the outcome of the disorder and treatment, but traditionally this has been a great challenge to clinicians. Recently, brain-derived neurotrophic factor (BDNF) has been suggested to be involved in the pathophysiology of bipolar disorder and major depressive disorder (MDD), but it is not clear whether BDNF levels can be used to predict bipolar disorder among patients in their first major depressive episode.
To explore whether BDNF levels can differentiate between MDD and bipolar disorder in the first depressive episode.
A total of 203 patients with a first major depressive episode as well as 167 healthy controls were recruited. After 3 years of bi-annual follow-up, 164 patients with a major depressive episode completed the study, and of these, 21 were identified as having bipolar disorder and 143 patients were diagnosed as having MDD. BDNF gene expression and plasma levels at baseline were compared among the bipolar disorder, MDD and healthy control groups. Logistic regression and decision tree methods were applied to determine the best model for predicting bipolar disorder at the first depressive episode.
At baseline, patients in the bipolar disorder and MDD groups showed lower BDNF mRNA levels (P<0.001 and P = 0.02 respectively) and plasma levels (P = 0.002 and P = 0.01 respectively) compared with healthy controls. Similarly, BDNF levels in the bipolar disorder group were lower than those in the MDD group. These results showed that the best model for predicting bipolar disorder during a first depressive episode was a combination of BDNF mRNA levels with plasma BDNF levels (receiver operating characteristics (ROC) = 0.80, logistic regression; ROC = 0.84, decision tree).
Our findings suggest that BDNF levels may serve as a potential differential diagnostic biomarker for bipolar disorder in a patient's first depressive episode.
在首次抑郁发作期间尽早识别双相障碍患者有利于疾病的转归和治疗，但传统上这对临床医生来说是一个巨大的挑战。最近，脑源性神经营养因子（BDNF）被认为与双相障碍和重性抑郁障碍（MDD）的病理生理学有关，但尚不清楚 BDNF 水平是否可用于预测首次重性抑郁发作患者中的双相障碍。
探讨 BDNF 水平是否可在首次抑郁发作时区分 MDD 和双相障碍。
共招募 203 例首发重性抑郁发作患者和 167 例健康对照者。在 3 年的双年度随访后，164 例重性抑郁发作患者完成了研究，其中 21 例被诊断为双相障碍，143 例被诊断为 MDD。比较了双相障碍、MDD 和健康对照组的 BDNF 基因表达和基线时的血浆水平。应用逻辑回归和决策树方法确定预测首次抑郁发作时双相障碍的最佳模型。
基线时，双相障碍和 MDD 组患者的 BDNF mRNA 水平（P<0.001 和 P = 0.02）和血浆水平（P = 0.002 和 P = 0.01）均低于健康对照组。同样，双相障碍组的 BDNF 水平低于 MDD 组。这些结果表明，预测首次抑郁发作时双相障碍的最佳模型是 BDNF mRNA 水平与血浆 BDNF 水平的组合（ROC = 0.80，逻辑回归；ROC = 0.84，决策树）。
我们的研究结果表明，BDNF 水平可能成为首次抑郁发作时双相障碍的潜在鉴别诊断生物标志物。
