Transcutaneous auricular vagus nerve stimulation for major depressive disorder: current evidence and future research directions

TL;DR

Transcutaneous auricular vagus nerve stimulation (taVNS) is a non-invasive treatment for depression that shows promise in reducing symptoms through multiple biological pathways.

Contribution

The paper proposes future research directions to standardize taVNS protocols and integrate advanced technologies for precision medicine.

Findings

taVNS significantly alleviates depressive symptoms through anti-inflammatory and autonomic modulation.

Methodological heterogeneity and small sample sizes hinder clinical translation of taVNS.

Multi-omics and machine learning could enhance understanding and application of taVNS for depression.

Abstract

Major depressive disorder (MDD) causes a significant global disease burden, yet existing pharmacological treatments are often limited by side effects and poor adherence. Transcutaneous auricular vagus nerve stimulation (taVNS), a promising non-invasive neuromodulation technique, offers a safe and accessible therapeutic alternative. This narrative review synthesizes current clinical evidence, explores potential mechanisms of action, and outlines future research directions for taVNS in MDD. Clinical studies consistently indicate that taVNS significantly alleviates depressive symptoms. Its therapeutic effects are mediated through multiple pathways, including anti-inflammatory regulation, autonomic modulation, neurotransmitter restoration, functional brain network reorganization, and the gut-brain axis. Despite these promising findings, clinical translation is hindered by methodological heterogeneity, small sample sizes, and a lack of long-term follow-up data. To advance clinical application, future research should prioritize establishing standardized stimulation protocols to reduce methodological heterogeneity, integrating multi-omics approaches to systematically decipher the “neuro-immune-endocrine-gut-brain” regulatory axis, and leveraging machine learning algorithms to identify multimodal predictive biomarkers for precision medicine. By integrating these advanced approaches, taVNS has the potential to become a robust, first-line therapeutic option for depression.

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