Precision nutrition and chronic disease: Integrating genomics, microbiome, and digital health for personalized dietary interventions.

Chronic non-communicable diseases (NCDs), including cardiovascular disease, type 2 diabetes, obesity, and metabolic syndrome, account for more than 70% of global mortality and impose a disproportionate burden on low- and middle-income countries. Traditional, population-level dietary guidelines often fail to address population-level dietary guidelines often fail to account for the considerable inter-individual variability in metabolic responses to food. Personalized nutrition (PN), informed by genomics, metabolomics, gut microbiome composition, and behavioral factors, has emerged as an effective strategy for optimizing dietary interventions for chronic disease prevention and management. This review synthesizes the current evidence on the conceptual foundations, clinical applications, and technological advancements of PN. Important findings from landmark studies have shown that integrating multi-omics profiling, continuous glucose monitoring, and machine-learning algorithms improves the prediction of postprandial glycemic and lipidemic responses, enhances weight-loss outcomes, and supports targeted interventions for type 2 diabetes, obesity, cardiovascular disease, and metabolic syndrome. Phenotype-based approaches, including metabotyping and tissue-specific insulin resistance profiling, further refine dietary recommendations, resulting in superior improvements compared with generic guidelines. Personalized nutrition is an emerging approach with growing evidence suggesting its potential benefits, although its routine clinical application remains limited. Personalized nutrition is a transformative and clinically relevant method with the potential to improve metabolic health and reduce the global burden of chronic diseases.