Wang Meiling, Song Zhaoqi, Lai Shirong, Tang Furong, Dou Lijun, Yang Fenglong
Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China.
Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China.
Front Microbiol. 2024 Jan 31;15:1292004. doi: 10.3389/fmicb.2024.1292004. eCollection 2024.
Depression is one of the most prevalent mental disorders today. Over the past decade, there has been considerable attention given to the field of gut microbiota associated with depression. A substantial body of research indicates a bidirectional communication pathway between gut microbiota and the brain. In this review, we extensively detail the correlation between gut microbiota, including and , and metabolites such as short-chain fatty acids (SCFAs) and 5-hydroxytryptamine (5-HT) concerning depression. Furthermore, we delve into the potential health benefits of microbiome-targeted therapies, encompassing probiotics, prebiotics, and synbiotics, in alleviating depression. Lastly, we underscore the importance of employing a constraint-based modeling framework in the era of systems medicine to contextualize metabolomic measurements and integrate multi-omics data. This approach can offer valuable insights into the complex metabolic host-microbiota interactions, enabling personalized recommendations for potential biomarkers, novel drugs, and treatments for depression.
抑郁症是当今最普遍的精神障碍之一。在过去十年中，肠道微生物群与抑郁症相关的领域受到了相当多的关注。大量研究表明肠道微生物群与大脑之间存在双向通信途径。在这篇综述中，我们详细阐述了包括[具体微生物名称未给出]和[具体微生物名称未给出]在内的肠道微生物群与短链脂肪酸（SCFAs）和5-羟色胺（5-HT）等代谢物与抑郁症之间的相关性。此外，我们深入探讨了以微生物群为靶点的疗法，包括益生菌、益生元及合生元，在缓解抑郁症方面的潜在健康益处。最后，我们强调在系统医学时代采用基于约束的建模框架来解释代谢组学测量结果并整合多组学数据的重要性。这种方法可以为复杂的宿主-微生物群代谢相互作用提供有价值的见解，从而为抑郁症的潜在生物标志物、新型药物和治疗方法提供个性化建议。
