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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].

Background: Metabolic diseases have been related to gut microbiota, and new knowledge indicates that diet impacts host metabolism through the gut microbiota. Identifying specific gut bacteria associated with both diet and metabolic risk markers may be a potential strategy for future dietary disease prevention. However, studies investigating the association between the gut microbiota, diet, and metabolic markers in healthy indi-viduals are scarce.Objective: We explored the relationship between a panel of gut bacteria, dietary intake, and metabolic and anthropometric markers in healthy adults.Design: Forty-nine volunteers were included in this cross-sectional study. Measures of glucose, serum tri-glyceride, total cholesterol, hemoglobin A1c (HbA1c), blood pressure (BP), and body mass index (BMI) were collected after an overnight fast, in addition to fecal samples for gut microbiota analyzes using a targeted approach with a panel of 48 bacterial DNA probes and assessment of dietary intake by a Food Frequency Questionnaire (FFQ). Correlations between gut bacteria, dietary intake, and metabolic and anthropometric markers were assessed by Pearson’s correlation. Gut bacteria varying according to dietary intake and metabolic markers were assessed by a linear regression model and adjusted for age, sex, and BMI.Results: Of the 48 gut bacteria measured, 24 and 16 bacteria correlated significantly with dietary intake and metabolic and/or anthropometric markers, respectively. Gut bacteria including Alistipes, Lactobacillus spp., and Bacteroides stercoris differed according to the intake of the food components, fiber, sodium, saturated fatty acids, and dietary indices, and metabolic markers (BP and total cholesterol) after adjustments. Notably, Bacteroides stercoris correlated positively with the intake of fiber, grain products, and vegetables, and higher Bacteroides stercoris abundance was associated with higher adherence to Healthy Nordic Food Index (HNFI) and lower diastolic BP after adjustment.Conclusion: Our findings highlight the relationship between the gut microbiota, diet, and metabolic mark-ers in healthy individuals. Further investigations are needed to address whether these findings are causally linked and whether targeting these gut bacteria can prevent metabolic diseases.

The long-term cholesterol-lowering effect of replacing intake of SFA with PUFA is well established, but has not been fully explained mechanistically. We examined the postprandial response of meals with different fat quality on expression of lipid genes in peripheral blood mononuclear cells (PBMC) in subjects with and without familial hypercholesterolaemia (FH). Thirteen subjects with FH (who had discontinued lipid-lowering treatment ≥4 weeks prior to both test days) and fourteen normolipidaemic controls were included in a randomised controlled double-blind crossover study with two meals, each with 60 g of fat either mainly SFA (about 40% energy) or n-6 PUFA (about 40% energy). PBMC were isolated in fasting, and 4 and 6 h postprandial blood samples. Expression of thirty-three lipid genes was analysed by reverse transcription quantitative PCR. A linear mixed model was used to assess postprandial effects between meals and groups. There was a significant interaction between meal and group for MSR1 (P = 0·03), where intake of SFA compared with n-6 PUFA induced a larger reduction in gene expression in controls only (P = 0·01). Intake of SFA compared with n-6 PUFA induced larger reductions in gene expression levels of LDLR and FADS1/2, smaller increases of INSIG1 and FASN, and larger increases of ABCA1 and ABCG1 (P = 0·01 for all, no group interaction). Intake of SFA compared with n-6 PUFA induced changes in gene expression of cholesterol influx and efflux mediators in PBMC including lower LDLR and higher ABCA1/G1, potentially explaining the long-term cholesterol-raising effect of a high SFA intake.