Precision Nutritional Genomics, Gut Microbiota and Artificial Intelligence in Chronic Kidney Disease.

Abstract

Chronic kidney disease (CKD) is a prevalent global health issue, and nutritional management of CKD is an integral component through all stages of the disease. However, response to dietary interventions varies, potentially due to genetic variations influencing metabolic pathways. This review highlights key gene-diet interactions relevant to CKD management, including risk factors and comorbidities such as hypertension, diabetes, and proteinuria. Variants in the ACE gene influence salt sensitivity and blood pressure responses, while TCF7L2 polymorphisms affect the relationship between dietary glycemic load and diabetes risk, impacting kidney complications. Protein intake, a key modifier of CKD, correlates with proteinuria risk, moderated by a PPM1K polymorphism. Dietary bioactives, such as caffeine, may also alter the progression rate of proteinuria and hypertension, with effects contingent upon CYP1A2 genotype. Additional markers of cardiovascular disease, CKD-associated bone-mineral disease, and CKD anemia are also discussed as well as role of the gut microbiome in nutrition modulation and vice versa. The review concludes with the potential of artificial intelligence as a clinical tool to refine precision nutrition, enabling clinicians to adopt targeted approaches, stratified by genetic-metabolic patient profiles that match best nutritional interventions for prevention and management of CKD. Vitamin D is used as a model nutrient to illustrate a simulated framework for precision nutrition, incorporating molecular mechanisms, genetic variation, epigenetic modifications, and translational tools applicable to both population health and clinical practice.