Cai-Chun Liu1, Yan-Fei Wu2, Guang-Ming Feng1, Xiao-Xia Gao1, Yu-Zhi Zhou1, Wen-Jing Hou3, Xue-Mei Qin1, Guan-Hua Du4, Jun-Sheng Tian5. 1. Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, PR China. 2. Department of traditional Chinese medicine, First Hospital of Shanxi Medical University, Taiyuan 030001, PR China. 3. Department of Pharmacy, Beijing Charity Hospital of China Rehabilitation Research Center, Beijing 100068, PR China. 4. Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, PR China; Institute of Materia Medica, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100050, PR China. Electronic address: dugh@imm.ac.cn. 5. Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, PR China. Electronic address: jstian@sxu.edu.cn.
Abstract
BACKGROUND: Depression is one of the most prevalent and serious mental disorders. Xiaoyaosan, a well-known Chinese prescription, has been widely used for the treatment of depression in China. Both clinical studies and animal experiments indicate that Xiaoyaosan has an obvious antidepressant activity. Additionally, a large number of candidate biomarkers have emerged that can be used for early disease detection and for monitoring ongoing treatment response to therapy because of their correlations with the characteristics of the disease. However, there have been few reports on biomarkers that measure the treatment response to the clinical use of Xiaoyaosan using a metabolomics approach. The current study is aimed at discovering biomarkers and biochemical pathways to facilitate the diagnosis of depression and the efficient evaluation of Xiaoyaosan using plasma metabolomics profiles based on (1)H NMR. METHODS: Sixteen depressed patients diagnosed by standard methods (HAMD and CGI-SI) and sixteen healthy volunteers were recruited. (1)H NMR-based metabolomics techniques and multivariate statistical methods were used to analyze the plasma metabolites of the depressed patients before and after treatment and to compare them with healthy controls. RESULTS: The plasma levels of trimethylamine oxide, glutamine and lactate in depressed patients increased significantly (p≤0.05) compared with healthy controls, whereas the levels of phenylalanine, valine, alanine, glycine, leucine, citrate, choline, lipids and glucose decreased significantly (p≤0.05). Additionally, alanine, choline, trimethylamine oxide, glutamine, lactate and glucose were returned to normal levels after Xiaoyaosan treatment. These statistically significant perturbations are involved in energy metabolism, amino acid metabolism and gut microbiota metabolism. LIMITATIONS: Additional experimentation with gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS) is required to confirm our findings. CONCLUSIONS: Application of these biomarkers in clinical practice may help to optimize the diagnosis of depression and to evaluate the efficacy of Xiaoyaosan. Metabolomics is promising as a biomarker discovery tool.
BACKGROUND:Depression is one of the most prevalent and serious mental disorders. Xiaoyaosan, a well-known Chinese prescription, has been widely used for the treatment of depression in China. Both clinical studies and animal experiments indicate that Xiaoyaosan has an obvious antidepressant activity. Additionally, a large number of candidate biomarkers have emerged that can be used for early disease detection and for monitoring ongoing treatment response to therapy because of their correlations with the characteristics of the disease. However, there have been few reports on biomarkers that measure the treatment response to the clinical use of Xiaoyaosan using a metabolomics approach. The current study is aimed at discovering biomarkers and biochemical pathways to facilitate the diagnosis of depression and the efficient evaluation of Xiaoyaosan using plasma metabolomics profiles based on (1)H NMR. METHODS: Sixteen depressedpatients diagnosed by standard methods (HAMD and CGI-SI) and sixteen healthy volunteers were recruited. (1)H NMR-based metabolomics techniques and multivariate statistical methods were used to analyze the plasma metabolites of the depressedpatients before and after treatment and to compare them with healthy controls. RESULTS: The plasma levels of trimethylamine oxide, glutamine and lactate in depressedpatients increased significantly (p≤0.05) compared with healthy controls, whereas the levels of phenylalanine, valine, alanine, glycine, leucine, citrate, choline, lipids and glucose decreased significantly (p≤0.05). Additionally, alanine, choline, trimethylamine oxide, glutamine, lactate and glucose were returned to normal levels after Xiaoyaosan treatment. These statistically significant perturbations are involved in energy metabolism, amino acid metabolism and gut microbiota metabolism. LIMITATIONS: Additional experimentation with gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS) is required to confirm our findings. CONCLUSIONS: Application of these biomarkers in clinical practice may help to optimize the diagnosis of depression and to evaluate the efficacy of Xiaoyaosan. Metabolomics is promising as a biomarker discovery tool.