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Scientific Studies

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The gut microbiota metabolism of pomegranate or walnut ellagitannins yields two urolithin-metabotypes that correlate with cardiometabolic risk biomarkers: comparison between normoweight, overweight-obesity and metabolic syndrome.

Authors: Selma, M. V., González-Sarrías, A., Salas-Salvadó, J., Andrés-Lacueva, C., Alasalvar, C., Örem, A., ... & Espín, J. C. Journal: Clin Nutr Obesity Cholesterol Metabolic syndrome Gut microbiota Year: 2017 Pages: Volume:
Fruits: Walnuts
Subject: Cardiovascular

BACKGROUND & AIMS: Urolithins are microbial metabolites produced after consumption of ellagitannin-containing foods such as pomegranates and walnuts. Parallel to isoflavone-metabolizing phenotypes, ellagitannin-metabolizing phenotypes (urolithin metabotypes A, B and 0; UM-A, UM-B and UM-0, respectively) can vary among individuals depending on their body mass index (BMI), but correlations between urolithin metabotypes (UMs) and cardiometabolic risk (CMR) factors are unexplored. We investigated the association between UMs and CMR factors in individuals with different BMI and health status. METHODS: UM was identified using UPLC-ESI-qToF-MS in individuals consuming pomegranate or nuts. The associations between basal CMR factors and the urine urolithin metabolomic signature were explored in 20 healthy normoweight individuals consuming walnuts (30 g/d), 49 healthy overweight-obese individuals ingesting pomegranate extract (450 mg/d) and 25 metabolic syndrome (MetS) patients consuming nuts (15 g-walnuts, 7.5 g-hazelnuts and 7.5 g-almonds/d). RESULTS: Correlations between CMR factors and urolithins were found in overweight-obese individuals. Urolithin-A (mostly present in UM-A) was positively correlated with apolipoprotein A-I (P ≤ 0.05) and intermediate-HDL-cholesterol (P ≤ 0.05) while urolithin-B and isourolithin-A (characteristic from UM-B) were positively correlated with total-cholesterol, LDL-cholesterol (P ≤ 0.001), apolipoprotein B (P ≤ 0.01), VLDL-cholesterol, IDL-cholesterol, oxidized-LDL and apolipoprotein B:apolipoprotein A-I ratio (P ≤ 0.05). In MetS patients, urolithin-A only correlated inversely with glucose (P ≤ 0.05). Statin-treated MetS patients with UM-A showed a lipid profile similar to that of healthy normoweight individuals while a poor response to lipid-lowering therapy was observed in MB patients. CONCLUSIONS: UMs are potential CMR biomarkers. Overweight-obese individuals with UM-B are at increased risk of cardiometabolic disease, whereas urolithin-A production could protect against CMR factors. Further research is warranted to explore these associations in larger cohorts and whether the effect of lipid-lowering drugs or ellagitannin-consumption on CMR biomarkers depends on individuals' UM.

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