Progress in Molecular Mechanisms of Depression Induced by Mother-Infant Separation and Intervention of Traditional Chinese Medicine
Ling-hui Kong , Min Liu , Hui Li , Rui-rui Shang , Shi-Meng Lv , Zhong-lin Wang , Qiang Ren
Alpha Psychiatry ›› 2025, Vol. 26 ›› Issue (4) : 45684
Depression is a serious mental and emotional disorder and is considered to be the greatest cause of non-fatal disease worldwide. Early life stress (ELS) refers to the exposure of an individual to physical and psychological stress events such as neglect or abuse in early life that has a long-term impact on brain development, thus inducing emotional and cognitive disorders in adulthood. It is the main susceptibility and risk factor for depression. Current clinical treatment is primarily based on Western medicines such as fluoxetine, but there can be serious adverse reactions. Therefore, exploring the biochemical mechanism of ELS-induced disorders and how to intervene effectively and safely to prevent and treat depression has become a significant issue. Traditional Chinese medicine (TCM) has the unique advantages of few adverse reactions and high safety and has great potential for the treatment of depression. Maternal separation (MS) is one of the most important and commonly used models for simulating ELS. Many studies have shown that MS-induced depression involves the regulation of multiple pathways and several studies have shown that TCM improves MS-induced depression. However, there is currently a lack of systematic reviews and summaries of the molecular mechanisms of MS-induced depression and traditional Chinese medical interventions. Therefore, the mechanisms of action and traditional Chinese medical interventions for MS-mediated depression were reviewed by searching recent relevant literature and discussing the limitations of current research. The aim was to provide guidance for follow-up basic research and clinical treatment.
depression / maternal separation / early life stress / molecular mechanisms / traditional Chinese medicine / research progress
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