Zezhi Li1, Chen Zhang1, Jinbo Fan1, Chengmei Yuan1, Jia Huang1, Jun Chen1, Zhenghui Yi1, Zuowei Wang1, Wu Hong1, Yong Wang1, Weihong Lu1, Yangtai Guan1, Zhiguo Wu1, Yousong Su1, Lan Cao1, Yingyan Hu1, Yong Hao1, Mingyuan Liu1, Shunying Yu1, Donghong Cui1, Lin Xu1, Yanyan Song1, Yiru Fang1. 1. 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
Abstract
BACKGROUND: 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. AIMS: To explore whether BDNF levels can differentiate between MDD and bipolar disorder in the first depressive episode. METHOD: 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. RESULTS: 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). CONCLUSIONS: Our findings suggest that BDNF levels may serve as a potential differential diagnostic biomarker for bipolar disorder in a patient's first depressive episode. Royal College of Psychiatrists.
BACKGROUND: 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. AIMS: To explore whether BDNF levels can differentiate between MDD and bipolar disorder in the first depressive episode. METHOD: 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. RESULTS: 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). CONCLUSIONS: Our findings suggest that BDNF levels may serve as a potential differential diagnostic biomarker for bipolar disorder in a patient's first depressive episode. Royal College of Psychiatrists.
Authors: A K Leonpacher; D Liebers; M Pirooznia; D Jancic; D F MacKinnon; F M Mondimore; B Schweizer; J B Potash; P P Zandi; F S Goes Journal: Psychol Med Date: 2015-04-08 Impact factor: 7.723
Authors: Brisa S Fernandes; Marc L Molendijk; Cristiano A Köhler; Jair C Soares; Cláudio Manuel G S Leite; Rodrigo Machado-Vieira; Thamara L Ribeiro; Jéssica C Silva; Paulo M G Sales; João Quevedo; Viola Oertel-Knöchel; Eduard Vieta; Ana González-Pinto; Michael Berk; André F Carvalho Journal: BMC Med Date: 2015-11-30 Impact factor: 8.775
Authors: Noriko Yoshimi; Takashi Futamura; Keiji Kakumoto; Alireza M Salehi; Carl M Sellgren; Jessica Holmén-Larsson; Joel Jakobsson; Erik Pålsson; Mikael Landén; Kenji Hashimoto Journal: BBA Clin Date: 2016-04-03