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. 2017 May 27;9(6):551.
doi: 10.3390/nu9060551.

Different Intestinal Microbial Profile in Over-Weight and Obese Subjects Consuming a Diet with Low Content of Fiber and Antioxidants

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Different Intestinal Microbial Profile in Over-Weight and Obese Subjects Consuming a Diet with Low Content of Fiber and Antioxidants

Tania Fernández-Navarro et al. Nutrients. .

Abstract

Obesity has been related to an increased risk of multiple diseases in which oxidative stress and inflammation play a role. Gut microbiota has emerged as a mediator in this interaction, providing new mechanistic insights at the interface between fat metabolism dysregulation and obesity development. Our aim was to analyze the interrelationship among obesity, diet, oxidative stress, inflammation and the intestinal microbiota in 68 healthy adults (29.4% normal-weight). Diet was assessed through a food frequency questionnaire and converted into nutrients and dietary compounds using food composition tables. The intestinal microbiota was assessed by quantitative PCR, fecal short chain fatty acids by gas chromatography and serum biomarkers by standard protocols. Higher levels of malondialdehyde (MDA), C reactive protein (CRP), serum leptin, glucose, fat percentage and the intestinal Lactobacillus group were found in the obese people. Cluster analysis of body mass index, fat mass, glucose, LDL/HDL ratio, leptin, MDA and CRP classified the subjects into two groups. The levels of the intestinal Bacteroides-Prevotella-Porphyromonas group were lower in the cluster and linked to a higher pro-oxidant and pro-inflammatory status, whose individuals also had lower intake of fruits, dried fruits, and fish. These results could be useful for designing strategies targeted to obesity prevention.

Keywords: antioxidant; microbiota; obesity; oxidative stress; western diet.

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Conflict of interest statement

The authors declared no potential competing financial interests concerning this study. Funders had no role in study conception, design, analysis of the results or decision to publish.

Figures

Figure 1
Figure 1
Dendogram clustering based on individual body composition, serum glucose, lipid profile, and oxidative stress biomarkers. The heatmap shows the dendrogram classification for clusters, based on C reactive protein (CRP), malondialdehyde (MDA), LDL/HDL ratio, serum leptin, Body Mass Index (BMI), body fat percentage and serum glucose (columns). Colors in the vertical bar at the left of the heatmap identify Cluster I (red) and Cluster II (blue).
Figure 2
Figure 2
Radar plot representing differences in the daily intake of (A) major food groups (g/day); (B) macronutrient and fiber (g/day) and (C) detailed carbohydrate and fibers (g/day) among clusters. Cluster I (n = 38), Cluster II (n = 26). Multivariate regression analyses were adjusted by energy intake (Kcal/day). * p ≤ 0.05.
Figure 3
Figure 3
Differences in blood parameters related to obesity according to the levels of Bacteroides-Prevotella-Porphyromonas tertiles (log nº cells/gram of feces). Bars represent mean and whiskers standard error derived from univariate analysis adjusted by energy. MDA, malondialdehyde.

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