| Literature DB >> 34068353 |
Peter Cronin1,2, Susan A Joyce2,3, Paul W O'Toole2,4, Eibhlís M O'Connor1,2,5.
Abstract
Dietary fibre has long been established as a nutritionally important, health-promoting food ingredient. Modern dietary practices have seen a significant reduction in fibre consumption compared with ancestral habits. This is related to the emergence of low-fibre "Western diets" associated with industrialised nations, and is linked to an increased prevalence of gut diseases such as inflammatory bowel disease, obesity, type II diabetes mellitus and metabolic syndrome. The characteristic metabolic parameters of these individuals include insulin resistance, high fasting and postprandial glucose, as well as high plasma cholesterol, low-density lipoprotein (LDL) and high-density lipoprotein (HDL). Gut microbial signatures are also altered significantly in these cohorts, suggesting a causative link between diet, microbes and disease. Dietary fibre consumption has been hypothesised to reverse these changes through microbial fermentation and the subsequent production of short-chain fatty acids (SCFA), which improves glucose and lipid parameters in individuals who harbour diseases associated with dysfunctional metabolism. This review article examines how different types of dietary fibre can differentially alter glucose and lipid metabolism through changes in gut microbiota composition and function.Entities:
Keywords: dietary fibre; glucose metabolism; lipid metabolism; metabolic health; metabolic syndrome; microbiota; obesity; type II diabetes mellitus
Year: 2021 PMID: 34068353 PMCID: PMC8153313 DOI: 10.3390/nu13051655
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
Figure 1Schematic highlighting the different types of fibre divided by number of monomeric units. Abbreviations: monomeric units (MU), galacto-oligosaccharide (GOS) and fructo-oligosaccharide (FOS).
Different types of dietary fibre cause differential changes to the gut microbiota and metabolic status.
| Author | Study Design | (n) | Study Population | Age (Years) | Duration (Weeks) | Fibre Type | Dose (g/day) | Microbiota | Metabolic Marker |
|---|---|---|---|---|---|---|---|---|---|
| Venktaraman, 2016 [ | Fibre | 20 | Healthy | 19–20 | 3 | RS2 | 24 | ↑ | ↑ Butyrate |
| Zhang, 2019 [ | Randomized, Double-Blind | 19 | Healthy | 18–55 | 4 | RS2 | 40 | ↑ | ↓ Body Fat (%), LDL ↑ GLP-1, Acetate |
| Benítez-Páez, 2019 [ | Randomized Crossover | 30 | Obese | 36–52 | 4 | Arabinoxylan | 10 | ↑ | ↑ SCFA |
| Lu, 2004 [ | Randomized Crossover | 15 | T2D | 30–74 | 5 | Arabinoxylan | 15 | Not measured | ↓ Fasting glucose and insulin |
| Nicolucci, 2017 [ | Double-Blind, Placebo | 22 | Obese | 7–12 | 16 | Inulin | 10 | ↑ | ↓ Body Weight, Body Fat (%), TAG |
| Ramirez-Faris, 2008 [ | Randomized, Crossover | 12 | Healthy | 30–64 | 3 | Inulin | 5 | ↑ | Not measured |
| Wang, 2016 [ | Randomized, Crossover | 30 | Metabolic Syndrome | 27–78 | 5 | ß-glucan | 5 | ↑ | ↓ Total Cholesterol |
| Mitsou, 2010 [ | Randomized, Double-Blind, Placebo | 52 | Healthy | 39–70 | 4 | ß-glucan | 1 | ↑ | No significant change |
| Lappi, 2013 [ | Randomized, Parallel | 52 | Metabolic Syndrome | 40–65 | 12 | Rye | 75 | ↑ | No significant change |
| Lee, 2016 [ | Randomized, Crossover | Healthy | 18–60 | Rye | 40 | Not measured | ↓ Postprandial Glucose and Insulin | ||
| Vitaglione, 2015 [ | Randomized, Parallel, Placebo | 80 | Obese | 19–67 | 8 | Wheat | 70 | ↑ | No significant change |
| Dall’Alba, 2013 [ | Randomized, Parallel | 44 | T2D | 32–75 | 6 | Gum guar | 10 | Not measured | ↓ Waist Circumference, HbA1c, TAG |