Microbial Determinants of Antidepressant Response: Insights into the Gut–Brain

Microbial Determinants of Antidepressant Response: Insights into the Gut–Brain–Drug Axis in MDD
Zahra seifi,^1,* Zahra Navazesh,²
1. Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran
2. Islamic Azad University, Sanandaj, Iran
Introduction: Major depressive disorder (MDD) is a common and disabling psychiatric illness, marked by high rates of morbidity, suicide, relapse, and disability, along with low levels of diagnosis and treatment. Among treatment approaches—pharmacological, psychological, and physical—medications are the primary option. Selective serotonin reuptake inhibitors (SSRIs) are widely used due to their effectiveness and safety profile; however, around 30% of patients show inadequate responses and remain vulnerable to relapse. Emerging evidence highlights a strong link between gut microbiota and neuropsychiatric conditions like MDD. Altered gut microbial composition in MDD patients correlates with symptom severity and treatment outcomes. Imbalances in the gut microbiota, known as dysbiosis, may contribute to disease development and impact the efficacy of antidepressants. Since SSRIs act mainly through 5-HT receptors to influence neurotransmitter release, the gut microbiota may modulate their effectiveness and side effects, indicating its crucial role in therapeutic responses.
Methods: A review was performed by searching PubMed, Scopus, and Web of Science for English-language articles published from 2010 to 2025. Keywords included “gut microbiota,” “major depressive disorder,” “SSRIs,” and “antidepressant response.” Studies were selected based on relevance to the interaction between gut microbiota and SSRI treatment outcomes in MDD. Additional articles were identified through reference screening
Results: Our review highlights significant differences in gut microbiota composition and function between SSRI-responsive and non-responsive patients with MDD. Overall microbial diversity was found to be higher in the non-responsive group, a finding that aligns with prior studies suggesting diversity may influence treatment outcomes. Notably, the relative abundance of Bifidobacterium, Subdoligranulum, Faecalibacterium, and Blautia was increased in responsive patients, while Dialister, Streptococcus, and Escherichia-Shigella were more prevalent in non-responsive individuals. These microbial shifts may impact inflammatory processes and gut homeostasis. Functional pathway analysis revealed notable upregulation of acetate degradation and neurotransmitter synthesis pathways in the responsive group. Key contributors to acetate metabolism, such as Micrococcus and Pseudonocardia, may play roles in modulating intestinal pH and suppressing pathogenic bacteria, contributing to a healthier gut environment. Enhanced neurotransmitter-related pathways observed in responders may support the pharmacological action of SSRIs, whereas their reduced activity in non-responders could lead to impaired serotonergic signaling. Additionally, the vagus nerve appears to be a key mediator between gut microbiota and the central nervous system. It influences mood regulation by modulating gut motility, immune function, and serotonin levels. Evidence suggests that vagal activity may enhance SSRI efficacy through anti-inflammatory effects and improved neurochemical balance. These findings underscore the importance of gut microbiota composition and function in shaping antidepressant response, suggesting that targeting the gut-brain axis may be a promising strategy to optimize treatment outcomes in MDD.
Conclusion: The findings reveal notable differences in both the diversity and functionality of gut microbiota between groups receiving effective versus ineffective treatments, with certain microbiota and metabolic pathways closely linked to the effectiveness of SSRIs. Future studies could investigate interventions like dietary changes and probiotic supplements to modulate gut microbiota, potentially increasing the efficacy of SSRIs. Additionally, machine learning-based predictive tools might be applied in clinical settings to create personalized treatment strategies, which could enhance treatment outcomes and improve patient prognosis.
Keywords: Gut microbiota, Major depressive disorder (MDD), Selective serotonin reuptake inhibitors (SSRIs)