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Depression-associated gut microbes, metabolites and clinical trials.
Wang, Meiling; Song, Zhaoqi; Lai, Shirong; Tang, Furong; Dou, Lijun; Yang, Fenglong.
Afiliação
  • Wang M; Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China.
  • Song Z; Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China.
  • Lai S; Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China.
  • Tang F; Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China.
  • Dou L; Genomic Medicine Institute, Lerner Research Institute, Cleveland, OH, United States.
  • Yang F; Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, China.
Front Microbiol ; 15: 1292004, 2024.
Article em En | MEDLINE | ID: mdl-38357350
ABSTRACT
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 Lactobacillus acidophilus and Bifidobacterium longum, 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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Guideline / Risk_factors_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Guideline / Risk_factors_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article