Personalized Nutrition Through the Gut Microbiome in Metabolic Syndrome and Related Comorbidities
Autor:
Plaza-Diaz, Julio
; Herrera-Quintana, Lourdes
; Olivares-Arancibia, Jorge
; Vazquez-Lorente, Hector
Fecha:
2026Palabra clave:
Revista / editorial:
NutrientsCitación:
Plaza-Diaz, J., Herrera-Quintana, L., Olivares-Arancibia, J., & Vázquez-Lorente, H. (2026). Personalized Nutrition Through the Gut Microbiome in Metabolic Syndrome and Related Comorbidities. Nutrients, 18(2), 290. https://doi.org/10.3390/nu18020290Tipo de Ítem:
Articulo Revista IndexadaDirección web:
https://www.mdpi.com/2072-6643/18/2/290
Resumen:
Background: Metabolic syndrome, a clinical condition defined by central obesity, im-paired glucose regulation, elevated blood pressure, hypertriglyceridemia, and low high-density lipoprotein cholesterol across the lifespan, is now a major public health issue typ-ically managed with lifestyle, behavioral, and dietary recommendations. However, “one-size-fits-all” recommendations often yield modest, heterogeneous responses and poor long-term adherence, creating a clinical need for more targeted and implementable pre-ventive and therapeutic strategies. Objective: To synthesize evidence on how the gut mi-crobiome can inform precision nutrition and exercise approaches for metabolic syndrome prevention and management, and to evaluate readiness for clinical translation. Key find-ings: The gut microbiome may influence cardiometabolic risk through microbe-derived metabolites and pathways involving short-chain fatty acids, bile acid signaling, gut barrier integrity, and low-grade systemic inflammation. Diet quality (e.g., Mediterranean-style patterns, higher fermentable fiber, or lower ultra-processed food intake) consistently re-lates to more favorable microbial functions, and intervention studies show that high-fi-ber/prebiotic strategies can improve glycemic control alongside microbiome shifts. Phys-ical exercise can also modulate microbial diversity and metabolic outputs, although effects are typically subtle and may depend on baseline adiposity and sustained adherence. Emerging “microbiome-informed” personalization, especially algorithms predicting postprandial glycemic responses, has improved short-term glycemic outcomes compared with standard advice in controlled trials. Targeted microbiome-directed approaches (e.g., Akkermansia muciniphila-based supplementation and fecal microbiota transplantation) provide proof-of-concept signals, but durability and scalability remain key limitations. Conclusions: Microbiome-informed personalization is a promising next step beyond ge-neric guidelines, with potential to improve adherence and durable metabolic outcomes. Clinical implementation will require standardized measurement, rigorous external vali-dation on clinically meaningful endpoints, interpretable decision support, and equity-fo-cused evaluation across diverse populations.
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