Abstract

Personalized nutrition is emerging as a promising approach to optimize health outcomes by accounting for individual genetic and metabolic differences. This review examines the current methods and approaches for integrating genetics and metabolomics into personalized nutrition strategies. We discuss the importance of understanding an individual's genetic makeup, including single nucleotide polymorphisms (SNPs), and their effects on nutrient metabolism and health outcomes. Additionally, we explore the role of metabolomics in elucidating individual metabolic profiles and identifying biomarkers for personalized dietary interventions. We also discuss the application of computational and machine learning techniques in data integration and analysis, as well as the ethical and regulatory considerations surrounding personalized nutrition. The ultimate goal is to provide a comprehensive overview of the current state of the field and identify future research opportunities to improve the implementation of personalized nutrition for disease prevention and overall health promotion.

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