A Three-Day Intervention With Granola Containing Cereal Beta-Glucan Improves Glycemic Response and Changes the Gut Microbiota in Healthy Individuals: A Crossover Study

Abstract

Intake of soluble fibers including beta-glucan, is known to improve post-prandial glycemic response. The mechanisms have been attributed to the viscous gel forming in the stomach and small intestine, giving a longer absorption time. However, recent evidence suggests a link between intake of beta-glucan and improved glycemic regulation at subsequent meals through the gut microbiota. We investigated the short-term effect of granola with different amounts of cereal beta-glucan on glycemic response and gut microbiota. After a two-week run-in period (baseline), fourteen healthy, normal weight adults completed a dose-response dietary crossover study. Different amounts of cereal beta-glucan (low: 0.8 g, medium: 3.2 g and high: 6.6 g) were provided in granola and eaten with 200 ml low-fat milk as an evening meal for three consecutive days. Blood glucose and insulin were measured fasted and after an oral glucose tolerance test (OGTT) the following day, in addition to peptide YY (PYY) and glucagon-like peptide (GLP-2), fasting short chain fatty acids (SCFA) in blood, breath H2, and gut microbiota in feces. Only the intervention with medium amounts of beta-glucan decreased blood glucose and insulin during OGTT compared to baseline. Fasting PYY increased with both medium and high beta-glucan meal compared to the low beta-glucan meal. The microbiota and SCFAs changed after all three interventions compared to baseline, where acetate and butyrate increased, while propionate was unchanged. Highest positive effect size after intake of beta-glucan was found with Haemophilus, followed by Veillonella and Sutterella. Furthermore, we found several correlations between different bacterial taxa and markers of glycemic response. In summary, intake of granola containing 3.2 g cereal beta-glucan as an evening meal for three consecutive days reduced the glycemic response after an OGTT 0-180 min and changed gut microbiota composition. Since we cannot rule out that other fiber types have contributed to the effect, more studies are needed to further explore the effect of cereal beta-glucan on glycemic regulation.

Clinical trial registration: [www.clinicaltrials.gov], identifier [NCT03293693].

Keywords: beta-glucan; crossover study; dietary intervention; fiber; glycemic response; gut microbiota; humans; soluble fiber.

Conflict of interest statement

The study was performed in collaboration with the food industry (Mills AS) represented by MGB, and Mills AS partially funded the study. VHT-H has been employed at Mills AS. VHT-H does not own any stocks in the company, and the work performed in this manuscript was done after she left the company. VHT-H collaborates with and/or has received research grants from Mills AS, Mesterbakeren, Det Glutenfrie Verksted and Norwegian Celiac Disease Association, none of which are related to the content of this manuscript. SMU has received research grants from TINE, Mills AS, Nortura and Olympic Seafood, none of which are related to the content of this manuscript. KBH has received research grants and/or personal fees from TINE, Mills AS, Amgen, Sanofi and Olympic Seafood, none of which are related to the content of this manuscript. MGB is employed at Mills AS. MGB does not own any stocks in the company and was not involved in the collection or analysis of the data. MCWM is involved in projects with research grants from Tine, Olympic Seafood, Mesterbakeren and Det Glutenfrie Verksted, none of which are related to the content of this manuscript. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2022 Telle-Hansen, Gaundal, Høgvard, Ulven, Holven, Byfuglien, Måge, Knutsen, Ballance, Rieder, Rud and Myhrstad.

Figures

FIGURE 1

Study design. BG: beta-glucan, FFQ: food frequency questionnaire; h: hours; N: number of participants; OGTT: oral glucose tolerance test.

FIGURE 2

Flow-chart of the participants.

FIGURE 3

Postprandial blood glucose response after intake of granola with cereal beta-glucan. The postprandial glucose response from 0–180 min (A) and the incremental area under the curve (B) after an OGTT at baseline and after consuming low, medium and high amount of beta-glucan for three days. Data is given as median (25th–75th). Significant differences are calculated with Friedman’s Anova followed by Wilcoxon signed rank test. Significant differences are indicated with * (A) or with a p-value(B).

FIGURE 4

Postprandial serum insulin response after intake of granola with cereal beta-glucan. The postprandial insulin response from 0–120 min (A) and the incremental area under the curve (B) after an OGTT at baseline and after consuming low, medium and high amount of beta-glucan for three days. Data is given as median (25th–75th). Significant differences are calculated with Friedman’s Anova followed by Wilcoxon signed rank test. #Fasting insulin after medium and high beta-glucan significant different from baseline. *Insulin response at 60 min after medium beta-glucan significant different from baseline, low and high beta-glucan.

FIGURE 5

Fasting and postprandial response of PYY and GLP-2 after intake of granola with cereal beta-glucan. Fasting values (A,C) and the incremental area under the curve (B,D) after an OGTT after consuming low, medium and high amount of beta-glucan for three days. Data is given as median (25th–75th). Significant differences are calculated with Friedman’s Anova followed by Wilcoxon signed rank test. Significant differences are presented with p-values.

FIGURE 6

Fasting and postprandial response of H2 breath after intake of granola with cereal beta-glucan. The postprandial response from 0 to 180 min (A) and the incremental area under the curve (B) after an OGTT at baseline and after consuming low, medium and high amount of beta-glucan for three days. Data is given as median (25th–75th). Significant differences are calculated with Friedman’s Anova followed by Wilcoxon signed rank test. *H2 response (0–180 min) after low, medium, and high beta-glucan significant different from baseline. #H2 response (0–180 min) after high beta-glucan significant different from low and medium beta-glucan.

FIGURE 7

Fasting SCFA after intake of granola with cereal beta-glucan. The fasting levels of Acetate (A), Butyrate (B) and Propionate (C) at baseline and after consuming low, medium and high amount of beta-glucan for three days. Data is given as median (25th–75th). Significant differences are calculated with Friedman’s Anova followed by Wilcoxon signed rank test and are presented with p-values.

FIGURE 8

Bacterial taxa after intake of granola with cereal beta-glucan. The taxa order is sorted from high to low effect size independent on test meal. The effect sizes were calculated as the difference in log ratio group means of test meals vs representative baseline after adjusting for individual differences. Asterisk indicates significant relationship (VIP > 1). Bars are colored according to dose of beta-glucan. Dominating genera (average abundance > 1%) are indicated in bold. Phyla are indicated within parentheses, A: Actinobacteria, B: Bacteroidetes, F: Firmicutes, P: Proteobacteria, V: Verrucomicrobia.

FIGURE 9

Heatmap of Spearman’s rank correlation coefficient between bacterial taxa and metabolic parameters. The bacterial taxa are sorted from negative (blue) to positive (red) correlation toward insulin iAUC, and those affected by the test meals are indicated in bold. Significant relationship was set to VIP > 1 and indicated by asterisk. No relationship was determined between the bacteria and glucose fasting, GLP-2 iAUC or H2 iAUC. Phyla are indicated within parentheses. A: Actinobacteria; B: Bacteroidetes; F: Firmicutes; Glu: Glucose; GLP-2: Glucagon-like peptide 2; H2: Hydrogen; iAUC: Incremental area under the curve; Ins: Insulin; P: Proteobacteria; PYY: Peptide YY; V: Verrucomicrobia.