Role of whole grains versus fruits and vegetables in reducing subclinical inflammation and promoting gastrointestinal health in individuals affected by overweight and obesity: a randomized controlled trial

Abstract

Background: Whole grains (WG) and fruits and vegetables (FV) have been shown to reduce the risk of metabolic disease, possibly via modulation of the gut microbiota. The purpose of this study was to determine the impact of increasing intake of either WG or FV on inflammatory markers and gut microbiota composition.

Methods: A randomized parallel arm feeding trial was completed on forty-nine subjects with overweight or obesity and low intakes of FV and WG. Individuals were randomized into three groups (3 servings/d provided): WG, FV, and a control (refined grains). Stool and blood samples were collected at the beginning of the study and after 6 weeks. Inflammatory markers [tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), lipopolysaccharide binding protein (LBP), and high sensitivity C-reactive protein (hs-CRP)] were measured. Stool sample analysis included short/branched chain fatty acids (S/BCFA) and microbiota composition.

Results: There was a significant decrease in LBP for participants on the WG (- 0.2 μg/mL, p = 0.02) and FV (- 0.2 μg/mL, p = 0.005) diets, with no change in those on the control diet (0.1 μg/mL, p = 0.08). The FV diet induced a significant change in IL-6 (- 1.5 pg/mL, p = 0.006), but no significant change was observed for the other treatments (control, - 0.009 pg/mL, p = 0.99; WG, - 0.29, p = 0.68). The WG diet resulted in a significant decrease in TNF-α (- 3.7 pg/mL; p < 0.001), whereas no significant effects were found for those on the other diets (control, - 0.6 pg/mL, p = 0.6; FV, - 1.4 pg/mL, p = 0.2). The treatments induced individualized changes in microbiota composition such that treatment group differences were not identified, except for a significant increase in α-diversity in the FV group. The proportions of Clostridiales (Firmicutes phylum) at baseline were correlated with the magnitude of change in LBP during the study.

Conclusions: These data demonstrate that WG and FV intake can have positive effects on metabolic health; however, different markers of inflammation were reduced on each diet suggesting that the anti-inflammatory effects were facilitated via different mechanisms. The anti-inflammatory effects were not related to changes in gut microbiota composition during the intervention, but were correlated with microbiota composition at baseline.

Trial registration: ClinicalTrials.gov , NCT02602496 , Nov 4, 2017.

Keywords: C-reactive protein; Gut microbiota; Interleukin-6; Lipopolysaccharide; Metabolic syndrome; Short chain fatty acids; Tumor necrosis factor-α.

Conflict of interest statement

Ethics approval and consent to participate

The University of Nebraska Institutional Review Board approved all study protocols (Approval Number: 20141214525FB). All subjects completed an informed consent form to participate in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1

Participant flow diagram of the current study

Fig. 2

Changes in inflammatory markers during the treatment period. a) Lipopolysaccharide binding protein (LBP); b) tumor necrosis factor (TNF)-α; c) interleukin (IL)-6; and d) high sensitivity C-reactive protein (hs-CRP); * p < 0.05, ** p < 0.01, *** p < 0.001 for change across time = 0; all analyses corrected for baseline concentrations, age, gender, and body mass index; one subject was excluded from the control group in the IL-6 analysis due to an outlying value (15.7 pg/mL)

Fig. 3

Changes in fecal microbiota during the treatment period. a) α-Diversity; b) β-diversity; and c) operational taxonomic unit (OTU) fold-change; * p < 0.05, for change across time = 0; diversity measures corrected for baseline concentrations, age, gender, and body mass index

Fig. 4

Change in dominant bacteria in fecal samples from baseline to the end of the treatment. Treatment groups are clustered using hierarchical clustering (Ward’s method); taxa are ordered by absolute change in abundance across all subjects; uncl, unclassified; C, control; FV, fruits and vegetables; WG, whole grain

Fig. 5

Correlations between change in plasma markers during the study and microbiota composition. a) Baseline abundance; b) end of study abundance; and c) log2 fold-change during the study of stool microbiota; d) scatterplot of baseline abundance of Firmicutes and change in lipopolysaccharide binding protein (LBP) during the study; LBP lipopolysaccharide binding protein, TNF-α tumor necrosis factor, IL-6 interleukin-6, hs-CRP high sensitivity C-reactive protein, WG whole grain, FV fruits and vegetables; partial variables were treatment group, age, gender, and body mass index; N = 49 except IL-6 where N = 48; p-values were corrected for false discovery rate; * adjusted p < 0.05