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Decoding psychotropic-induced metabolic disturbances: gut-brain axis, multi-omics, and nutrition-lifestyle integration

31 March 2026

Dhieb Dhoha, Bastaki Kholoud

Summary

Summary of "Decoding psychotropic-induced metabolic disturbances: gut-brain axis, multi-omics, and nutrition-lifestyle integration"

This review highlights that psychiatric medications often cause significant metabolic side effects like weight gain and insulin resistance, complicating treatment. It identifies the gut-brain-metabolic axis as a key player, suggesting these medications can alter gut bacteria, contributing to these metabolic issues. The authors emphasize the need for integrating diverse data, including lifestyle and diet, using advanced computational methods to develop personalized strategies for managing these challenges.

Key Findings:

Psychotropic medications frequently lead to substantial metabolic adverse effects, such as weight gain, insulin resistance, and dyslipidemia.
The gut-brain-metabolic axis is a critical mechanistic link, where psychotropics can alter gut microbiota and related metabolic pathways, contributing to these complications.
Current research using multi-omics (e.g., genomics, metabolomics) often examines data in isolation, limiting a full understanding of the complex molecular networks involved.
Future precision approaches in psychiatric care require integrating diverse factors – molecular, clinical, environmental, lifestyle, and dietary – using advanced computational strategies like AI to create individualized interventions.

Practical Takeaways for Someone Interested in Nutrition and Longevity:

Prioritize Gut Health: If you are on psychotropic medications, focusing on a diverse, fiber-rich diet that supports a healthy gut microbiome may be particularly important to mitigate metabolic side effects.
Holistic Lifestyle: Emphasize a balanced diet, regular physical activity, and stress management, as these lifestyle factors play an even more critical role in maintaining metabolic health when undergoing psychiatric treatment.
Personalized Care: Work closely with your healthcare provider to monitor metabolic markers and tailor nutrition and lifestyle strategies, as individual responses to medications vary significantly and require a personalized approach for optimal long-term health.

Study Limitations: As a narrative review, this study synthesizes existing research rather than presenting new experimental data. It notes that much of the current multi-omics research in this area still relies on isolated data layers, which limits a complete understanding of the underlying mechanisms.

Abstract

Psychotropic medications remain central to psychiatric treatment, yet their use is frequently accompanied by a substantial metabolic burden. Metabolic adverse effects, including weight gain, insulin resistance, dysglycemia, dyslipidemia, and hypertension, complicated clinical management and undermine long-term adherence. Although evidence-based monitoring and mitigation approaches exist, the molecular determinants of individual susceptibility and the drivers of interindividual variability in metabolic outcomes remain insufficiently defined. Emerging evidence identifies the gut-brain-metabolic axis as a key mechanistic interface, with psychotropic medications altering gut microbiota and associated metabolic pathways that contribute to metabolic complications. Multi-omics strategies are beginning to illuminate the complex molecular networks underlying these adverse effects; however, most findings still arise from isolated omics layers, limiting mechanistic resolution and translational utility. Integrative analytical frameworks, including artificial intelligence, now enable the synthesis of molecular, clinical, environmental, lifestyle, and dietary factors to support more precise and individualized intervention. In this narrative review, we synthesize current clinical and mechanistic advances in understanding psychotropic-induced metabolic dysfunction, with a focus on insulin resistance and the gut–brain–metabolic axis and highlight how multi-omics, environmental factors and computational strategies may advance future precision approaches in psychiatric care.

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