Akimoto Hayato, Oshima Shinji, Ohara Kousuke, Negishi Akio, Hiroyama Hanako, Nemoto Tadashi, Kobayashi Daisuke
Faculty of Pharmaceutical Sciences, Josai University.
Faculty of Pharmaceutical Sciences, Josai International University.
Biol Pharm Bull. 2017 Jun 1;40(6):789-796. doi: 10.1248/bpb.b16-00783. Epub 2017 Mar 4.
Depressive disorders cause large socioeconomic effects influencing not only the patients themselves but also their family and broader community as well. To better understand the physiologic factors underlying depression, in this study, we performed metabolomics analysis, an omics technique that comprehensively analyzes small molecule metabolites in biological samples. Specifically, we utilized high-resolution magic-angle spinning-H-NMR (HRMAS-H-NMR) spectroscopy to comprehensively analyze the changes in metabolites in the hippocampal tissue of rats exposed to chronic stress (CS) via multi-step principal component analysis (multi-step PCA). The rats subjected to CS exhibited obvious depression-like behaviors. High correlations were observed between the first principal component (PC1) score in the score plot obtained using multi-step PCA and measurements from depression-like behavioral testing (body weight, sucrose preference test, and open field test). Alanine, glutamate, glutamine, and aspartate levels in the hippocampal tissue were significantly lower, whereas N-acetylaspartate, myo-inositol, and creatine were significantly higher in the CS group compared to the control (non-CS) group. As alanine, glutamate, and glutamine are known to be involved in energy metabolism, especially in the tricarboxylic acid cycle, chronic exogenous stress may have induced abnormalities in energy metabolism in the brains of the rats. The results suggest that N-acetylaspartate and creatine levels may have increased in order to complement the loss of energy-producing activity resulting from the development of the depression-like disorder. Multi-step PCA therefore allowed an exploration of the degree of depression-like symptoms as represented by changes in intrinsic metabolites.
抑郁症会造成巨大的社会经济影响，不仅影响患者自身，还会波及他们的家庭以及更广泛的社区。为了更好地理解抑郁症背后的生理因素，在本研究中，我们进行了代谢组学分析，这是一种全面分析生物样本中小分子代谢物的组学技术。具体而言，我们利用高分辨率魔角旋转氢核磁共振波谱（HRMAS-H-NMR），通过多步主成分分析（multi-step PCA）全面分析慢性应激（CS）大鼠海马组织中代谢物的变化。遭受CS的大鼠表现出明显的抑郁样行为。在使用多步PCA获得的得分图中，第一主成分（PC1）得分与抑郁样行为测试（体重、蔗糖偏好测试和旷场试验）的测量值之间观察到高度相关性。与对照组（非CS组）相比，CS组海马组织中的丙氨酸、谷氨酸、谷氨酰胺和天冬氨酸水平显著降低，而N-乙酰天门冬氨酸、肌醇和肌酸则显著升高。由于已知丙氨酸、谷氨酸和谷氨酰胺参与能量代谢，尤其是三羧酸循环，慢性外源性应激可能诱发了大鼠大脑能量代谢异常。结果表明，N-乙酰天门冬氨酸和肌酸水平可能升高，以补充因抑郁样障碍发展而导致的能量产生活动的损失。因此，多步PCA能够探索由内在代谢物变化所代表的抑郁样症状的程度。
