Omic Sciences and Nutrition: A Systematic Review of Precision Nutrition, Multi-Omics Integration, Gut Microbiome Research, and Artificial Intelligence

Abstract Introduction: Omic sciences have transformed nutritional research by enabling the integrated analysis of genomic, epigenomic, transcriptomic, proteomic, metabolomic, microbiomic, and exposomic data. These approaches provide a biological basis for understanding interindividual variability in dietary responses and support the development of precision nutrition. Objective: To systematically review current evidence on the relationship between omic sciences and nutrition, focusing on multi-omics integration, precision nutrition, nutrigenomics, nutrigenetics, metabolomics, gut microbiome research, exposomics, and artificial intelligence-assisted nutritional strategies. Methods: A systematic review was conducted according to PRISMA 2020 guidelines. Searches were performed in PubMed/MEDLINE, Scopus, Web of Science, Embase, and the Cochrane Library for studies published between January 2020 and June 2026. Eligible studies evaluated one or more omic sciences in relation to nutrition in human populations. Due to methodological heterogeneity, a qualitative synthesis was performed. Results: A total of 259 records were identified. After removing 34 duplicates, 225 articles were screened, 80 full-text articles were assessed, and 48 studies were included in the final synthesis. The most frequently represented domains were microbiomics (n=15), metabolomics (n=10), precision nutrition (n=10), multi-omics integration (n=6), artificial intelligence (n=6), nutrigenomics/epigenomics (n=4), and exposomics (n=1). Evidence showed that genetic variability, metabolic phenotypes, gut microbiome composition, and environmental exposures influence individual dietary responses. Metabolomics and microbiome research emerged as particularly relevant for biomarker discovery and personalized nutritional assessment. Conclusions: Omic sciences are redefining nutrition by supporting the transition from population-based dietary recommendations toward individualized, biologically informed strategies. Multi-omics integration and artificial intelligence may accelerate the implementation of precision nutrition in disease prevention and personalized healthcare.