Biomedicine and Nutritional Epidemiology: AI-Assisted Personalized Nutrition in the Prevention and Management of Psychiatric Disorders

Abstract

Recent evidence emphasizes the critical importance of diet in the prevention and management of psychiatric diseases, including depression, anxiety, schizophrenia, and bipolar disorder. This review examines the significance of personalized nutrition in mental health care within the frameworks of biomedicine and nutritional epidemiology, highlighting its potential to enhance outcomes for individuals with psychiatric disorders. Psychiatric disorders involve complex interactions among genetic, environmental, and lifestyle factors. Although pharmacological treatments are prevalent, personalized nutrition – customizing dietary interventions according to an individual's genetic composition, microbiome, and metabolic reactions – is gradually recognized as a complementary strategy. Personalized nutrition seeks to enhance cognitive performance and mitigate mental symptoms by using insights from nutrigenomics, epigenetics, and metabolomics. Nutritional epidemiology, which investigates the correlations between diet and health within populations, offers significant insights into dietary patterns and specific nutrients linked to mental health. Epidemiological studies and clinical trials enhance nutritional guidelines for individuals at risk of or managing psychiatric disorders. This review summarizes recent clinical and epidemiological evidence regarding the influence of nutrition on mental health, emphasizing the prospective advantages of personalized nutrition. It also addresses the challenges and future research directions, promoting interdisciplinary methods that integrate biomedicine, nutritional science, and psychiatry to formulate effective, personalized dietary strategies for managing psychiatric disorders.

Received: 16 December 2024 | Revised: 13 March 2025 | Accepted: 14 May 2025

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

The data that support this work are available upon reasonable request to the corresponding author.

Author Contribution Statement

Oluwafikayo Seun Adeyemi-Benson: Methodology, Validation, Writing – original draft, Writing – review & editing, Supervision. Rufus Oluwagbemileke Ajayi: Conceptualization, Methodology, Software, Investigation. Oluwateniola Ajoke Adeyemi-Benson: Methodology, Visualization, Project administration. Taiwo Temitope Ogunjobi: Conceptualization, Methodology, Investigation, Writing – review & editing.