Identification of leaky gut-related markers as indicators of metabolic health in Dutch adults: The Nutrition Questionnaires plus (NQplus) study

BACKGROUND AND AIM: Chronic inflammation is a primary risk factor for chronic metabolic disease and may be triggered by a “leaky gut.” Several biomarkers have been recognized to indicate intestinal permeability (i.e., leaky gut) and bacterial translocation. Nonetheless, which of these biomarkers exhibit the highest correlation with metabolic health parameters remains unclear. Hence, this study aimed to explore the correlation between leaky gut-related markers and metabolic health. METHODS: Based on waist circumference, plasma fasting glucose, plasma gamma-glutamyl transpeptidase (GGT), and plasma LDL cholesterol, two groups of 40 subjects with the most extreme metabolic health profiles were selected from the NQplus cohort study (n = 2048), which was previously conducted by the Wageningen University’s Division of Human Nutrition. Eight potential leaky gut-related markers were selected from the literature and measured in serum or EDTA plasma samples of these selected individuals. These samples were also obtained from the NQplus cohort study. RESULTS: From the leaky gut markers, levels of zonulin, lipopolysaccharide-binding protein, soluble CD14, bactericidal/permeability-increasing protein, and peptidoglycan were significantly higher in individuals with unhealthy metabolic profiles (p<0.05). No differences in EndoCAb IgM, EndoCAb IgA, and EndoCAb IgG were observed between healthy and unhealthy individuals. Stepwise regression analysis revealed that zonulin was substantially associated with metabolic health parameters such as BMI, blood glucose, triglyceride, GGT, and C-reactive protein levels. C-reactive protein, an inflammation marker, showed the most pronounced association with zonulin. CONCLUSIONS: Biomarkers that link a leaky gut and subsequent bacterial translocation to metabolic health were identified in this study. Especially zonulin may aid in monitoring a leaky gut and detecting individuals at risk for developing chronic metabolic diseases.