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Get Free AccessThis review synthesizes the evidence on associations between antidepressant use and gut microbiota composition and function, exploring the microbiota's possible role in modulating antidepressant treatment outcomes. Antidepressants exert an influence on measures of gut microbial diversity. The most consistently reported differences were in β-diversity between those exposed to antidepressants and those not exposed, with longitudinal studies supporting a potential causal association. Compositional alterations in antidepressant users include an increase in the Bacteroidetes phylum, Christensenellaceae family, and Bacteroides and Clostridium genera, while a decrease was found in the Firmicutes phylum, Ruminococcaceae family, and Ruminococcus genus. In addition, antidepressants attenuate gut microbial differences between depressed and healthy individuals, modulate microbial serotonin transport, and influence microbiota's metabolic functions. These include lyxose degradation, peptidoglycan maturation, membrane transport, and methylerythritol phosphate pathways, alongside gamma-aminobutyric acid metabolism. Importantly, baseline increased α-diversity and abundance of the Roseburia and Faecalibacterium genera, in the Firmicutes phylum, are associated with antidepressant response, emerging as promising biomarkers. This review highlights the potential for gut microbiota as a predictor of treatment response and emphasizes the need for further research to elucidate the mechanisms underlying antidepressant-microbiota interactions. More homogeneous studies and standardized techniques are required to confirm these initial findings.
Gianluca Borgiani, Chiara Possidente, Chiara Fabbri, Vincenzo Oliva, Mirjam Bloemendaal, Alejandro Arias Vásquez, Timothy G. Dinan, Eduard Vieta, Marco Menchetti, Diana De Ronchi, Alessandro Serretti, Giuseppe Fanelli (2024). The bidirectional interaction between antidepressants and the gut microbiota: are there implications for treatment response?. , 40(1), DOI: https://doi.org/10.1097/yic.0000000000000533.
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Type
Article
Year
2024
Authors
12
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1097/yic.0000000000000533
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