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Too much body-fat has been linked to a low-grade inflammation throughout the body. This inflammation is thought to then cause different diseases, like heart disease and diabetes. A lower amount of inflammation is usually seen in people that follow a high fiber diet. A reason for this is the microbes that live in our gut. Fiber is a main food source for these microbes. This allows fiber to actually change the type of microbes that live in our gut. Also, when fiber gets fermented by these microbes, health-promoting waste products get released. We aim to determine how exactly our gut microbes contribute to the health properties of fiber.
We hypothesize that fiber's health properties depend on how the gut microbes respond to the fiber. To test this, we plan to add three different fibers to the diets of healthy overweight and obese individuals for six weeks. We then will determine how the different fibers affect an individuals' health by looking at how established markers of health change from adding the fiber. Following this, we will see how an individual's gut microbes respond to the added fiber. The response will be decided by looking at changes to the microbe community, as well as their ability to ferment the fibers. By connecting health outcomes to the gut microbes' response, we can test if the gut microbes' response to the fiber determines the fiber's ability to effect health. If we can understand how our gut microbes respond to different fibers and the importance of that response. Then we could personalize diets to have a greater impact on improving health.
Being overweight and obese significantly increases the risk of developing numerous diseases, including cardiovascular disease (CVD), type 2 diabetes (T2D), and certain cancers. The microbial community (microbiota) that resides within the gut play a notable role in obesity and its associated pathologies (e.g. CVD, T2D), and is therefore a potential therapeutic target. Diet is known to determine whether the gut microbiota contributions to host metabolism are beneficial or detrimental. A westernized diet high in fat and sugar is associated with systemic inflammation, while fat intake increases lipopolysaccharide translocation through the gut membrane. In addition, gut microbial metabolism of choline and L-carnitine can produce trimethylamine, which has been shown to contribute to atherosclerosis after being oxidized in the liver to trimethylamine N-oxide (TMAO). In contrast, diets high in dietary fiber from fruits, vegetables, and whole grains are inversely associated with inflammation and can potentially reverse effects of a high fat diet. Fermentable fiber types can resist host digestion, but are then subsequently fermented by the gut microbiota to short-chain fatty acids (SCFAs), which are known to have metabolic and immunologic benefits. Accordingly, both epidemiologic associations and human intervention trials suggest an inverse association between fiber intake, reduced systemic inflammation, and improved lipid and glucose metabolism; however, results remain inconsistent. These discrepancies might be partly attributable to (I) the low fiber doses used in most studies, and (II) the high degree of inter-individual variation in the response to fiber, which may stem from the individualized responses of the microbiome to fiber. The emerging evidence that fiber and the gut microbiota interact to influence host physiology warrant human clinical research that investigates the capacity of chemically distinct fibers to modulate host metabolism and inflammation, and the mechanistic role of the gut microbiota in their physiological effects.
Our long-term goal is to contribute to such a framework through clinical research that applies a holistic approach to examining the effect of fiber on both the host and its gut microbiota. We hypothesize that fibers show structure-dependent effects on inflammatory, metabolic, and hormonal markers of obesity-associated pathologies that can be predicted through compositional, functional, and genetic characteristics of an individual's fecal microbiome. We propose the following specific aims:
AIM 1. Perform a parallel-arm exploratory intervention study in overweight and mildly obese individuals to determine the impact of high doses of chemically distinct fibers on host inflammatory markers, measures of insulin sensitivity, and other clinical outcomes.
The effect of two physicochemically distinct fermentable dietary fibers (acacia gum and resistant starch type 4) on clinical markers of metabolic disease will be compared against a relatively non-fermentable dietary fiber (microcrystalline cellulose - control). We will employ a three-arm, parallel-design, single-blind, placebo-controlled, stratified randomized exploratory trial. Fibers will be administered in relative pure form daily over six weeks without any further lifestyle adjustments. Doses used in the trial will be 25 g/day of fiber for women and 35 g/day for men (close to Health Canada's dietary recommendations). Although, the first two days of treatment will use half the daily treatment dose of fiber (women: 12.5 g/day; men: 17.5 g/day), to ease the incorporation of the fiber into the diet. Participants will be advised on how to incorporate the fibers into their diet, as to improve tolerance and compliance.
The impact of dietary fiber on a comprehensive set of well-established obesity-related biomarkers will be determined via quantification at baseline and post-dietary intervention. High sensitive C-reactive protein and other inflammatory markers (e.g. interleukin-6, interleukin-10), as well as established markers for metabolic syndrome (e.g. fasting glucose and triglycerides) will constitute as key endpoints of the exploratory trial. To gain further understanding on the mechanisms that mediate metabolic and inflammatory improvements; five primary gut hormones, including satiety/hunger signaling hormones (e.g. glucagon-like peptide-1, leptin, and ghrelin), will be included. Lifestyle indicators, compliance with treatment, and satiation will be further assessed through self-administered questionnaires.
AIM 2. Evaluate the short- and long-term impacts of chemically distinct types of dietary fiber on gut microbiota composition, genetic characteristics, and production of anti-inflammatory (SCFA) and pathogenic (TMAO) metabolites.
We will utilize Illumina 16S rRNA sequencing and whole metagenomic sequencing to characterize the fecal microbiota (that will be enriched for large bowel bacteria) of our exploratory trial participants at weeks 0, 1, and 6, to explore fiber-induced changes in gut microbiota composition and gene content. These methods will be used as a majority of gut microbiota are not currently culturable. To further investigate gut microbiota function, we will quantify specific bacterial associated metabolites in plasma (TMAO) and in feces (SCFAs and bile acids). In parallel, we will quantify the fecal metabolites after in vitro fermentation, to account for absorption in the human gut. This will allow us to gain insight into fiber-induced changes in gut microbiota composition, metabolism, and functionality that coincide with the physiological effects observed in the host.
AIM 3. Characterize associations between clinical outcomes and microbiome shifts and determine how well individual microbiome configurations predict impacts of dietary fiber.
With the establishment of a robust human exploratory trial, a well-defined set of host phenotypes, and participant microbiome characteristics, Aim 3 will statistically integrate these data to specifically test for associations between diet, the gut microbiome, and host metabolism, and evaluate if microbiome and host phenotypic signatures at baseline can predict clinical outcomes of dietary fibers
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Microcrystalline Cellulose (Control) | Placebo Comparator | Microcrystalline cellulose will be used as a placebo control, as it is known to be an insoluble, non-viscous fiber that is essentially not fermented by the human gut microbiota. However, it is important to note that cellulose does have fermentation potential within the gastrointestinal tract and may be associated with improved health benefits; indicating a role as an active comparator. |
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| Acacia Gum | Experimental | Acacia gum is composed largely of arabinogalactan, and is considered to be a relatively non-viscous, soluble fiber this is highly fermented by the gut microbiota and well tolerated. |
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| Resistant Starch Type 4 | Experimental | Cross-linked phosphorylated resistant starch (type IV) is generally insoluble and with low viscosity; yet it tends to have physiologic properties similar to soluble fibers, such as fermentability. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Microcrystalline Cellulose Supplementation | Other | Fifty overweight and mildly obese subjects will supplement their normal dietary intake with a significant yet tolerable amount of MCC (Females: 25 g; Males: 35 g) daily for six consecutive weeks. |
| Measure | Description | Time Frame |
|---|---|---|
| Prediction of the Clinical Improvements of Dietary Fiber | The primary objective of this study is to determine the ability of the fecal microbiome to predict clinical improvements of dietary fiber treatments relevant to the etiology of obesity-associated pathologies. | 6-week period |
| Measure | Description | Time Frame |
|---|---|---|
| Dietary Fiber Associated Changes in Sub-clinical Inflammation | The markers of sub-clinical inflammation that will be measured are: C-reactive protein, tumor necrosis factor-alpha, interleukin-6, interleukin-8, interleukin-18, interleukin-10, lipopolysaccharide binding protein, and adiponectin. | 6-week period |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Jens Walter, PhD | University of Alberta | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Alberta Diabetes Institute Clinical Research Unit | Edmonton | Alberta | T6G 2E1 | Canada |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 18775919 | Background | Hajer GR, van Haeften TW, Visseren FL. Adipose tissue dysfunction in obesity, diabetes, and vascular diseases. Eur Heart J. 2008 Dec;29(24):2959-71. doi: 10.1093/eurheartj/ehn387. Epub 2008 Sep 5. | |
| 21633181 | Background | Tilg H, Kaser A. Gut microbiome, obesity, and metabolic dysfunction. J Clin Invest. 2011 Jun;121(6):2126-32. doi: 10.1172/JCI58109. Epub 2011 Jun 1. |
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| ID | Term |
|---|---|
| D050177 | Overweight |
| D009765 | Obesity |
| D007249 | Inflammation |
| ID | Term |
|---|---|
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
| D001835 | Body Weight |
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| Acacia Gum Supplementation | Other | Seventy five overweight and mildly obese subjects will supplement their normal dietary intake with a significant yet tolerable amount of AG (Females: 25 g; Males: 35 g) daily for six consecutive weeks. |
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| Resistant Starch Type 4 Supplementation | Other | Seventy five overweight and mildly obese subjects will supplement their normal dietary intake with a significant yet tolerable amount of RS4 (Females: 25 g; Males: 35 g) daily for six consecutive weeks. |
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| Dietary Fiber Associated Changes in Insulin Resistance and Blood Cholesterol. |
Dietary fiber associated changes in fasting glucose, insulin, and glucagon will be quantified; and the homeostatic model assessment-estimated insulin resistance will used to calculate insulin resistance. Changes in incretins (glucose-dependent insulinotropic peptide and glucagon-like peptide-1) and blood cholesterol (triglycerides, low-density lipoprotein, high-density lipoprotein) will also be quantified. |
| 6-week period |
| Dietary Fiber Associated Changes in Satiety and Dietary Intake. | Dietary fiber associated changes in hunger and satiety will be quantified via satiety hormones (ghrelin, leptin, and peptide YY), self-reported satiety, and subsequent dietary intake and anthropometric measurements. | 6-week period |
| Dietary Fiber Associated Changes in Trimethylamine-N-Oxide (TMAO). | Dietary fiber associated changes in TMAO-a relatively new cardiovascular disease biomarker linked to the gut microbiome-will be quantified in plasma. | 6-week period |
| Dietary Fiber Associated Changes in Bile Acid Derivatives. | The influence of dietary fiber on the formation of bile acid derivatives, and its association with the observed clinical outcomes, will be determined. | 6-week period |
| Dietary Fiber Associated Changes in Gut Microbial Structure and Metabolic Function. | Fecal microbial composition will be characterized at baseline (week 0), 6 days (±1 day) post fiber initiation (week 1), and post intervention (week 6) by 16S rRNA sequencing; while fecal microbiota function will be assessed through whole metagenomic sequencing, fecal SCFA concentrations, as well as parallel in vitro fermentations with subsequent SCFA quantification. | 6-week period |
| 21587065 | Background | De Bandt JP, Waligora-Dupriet AJ, Butel MJ. Intestinal microbiota in inflammation and insulin resistance: relevance to humans. Curr Opin Clin Nutr Metab Care. 2011 Jul;14(4):334-40. doi: 10.1097/MCO.0b013e328347924a. |
| 24336217 | Background | David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE, Wolfe BE, Ling AV, Devlin AS, Varma Y, Fischbach MA, Biddinger SB, Dutton RJ, Turnbaugh PJ. Diet rapidly and reproducibly alters the human gut microbiome. Nature. 2014 Jan 23;505(7484):559-63. doi: 10.1038/nature12820. Epub 2013 Dec 11. |
| 25088686 | Background | Hamaker BR, Tuncil YE. A perspective on the complexity of dietary fiber structures and their potential effect on the gut microbiota. J Mol Biol. 2014 Nov 25;426(23):3838-50. doi: 10.1016/j.jmb.2014.07.028. Epub 2014 Aug 1. |
| 17353499 | Background | King DE, Egan BM, Woolson RF, Mainous AG 3rd, Al-Solaiman Y, Jesri A. Effect of a high-fiber diet vs a fiber-supplemented diet on C-reactive protein level. Arch Intern Med. 2007 Mar 12;167(5):502-6. doi: 10.1001/archinte.167.5.502. |
| 18562168 | Background | Ma Y, Hebert JR, Li W, Bertone-Johnson ER, Olendzki B, Pagoto SL, Tinker L, Rosal MC, Ockene IS, Ockene JK, Griffith JA, Liu S. Association between dietary fiber and markers of systemic inflammation in the Women's Health Initiative Observational Study. Nutrition. 2008 Oct;24(10):941-9. doi: 10.1016/j.nut.2008.04.005. Epub 2008 Jun 18. |
| 21059476 | Background | Davis LM, Martinez I, Walter J, Hutkins R. A dose dependent impact of prebiotic galactooligosaccharides on the intestinal microbiota of healthy adults. Int J Food Microbiol. 2010 Dec 15;144(2):285-92. doi: 10.1016/j.ijfoodmicro.2010.10.007. Epub 2010 Oct 14. |
| 21151493 | Background | Martinez I, Kim J, Duffy PR, Schlegel VL, Walter J. Resistant starches types 2 and 4 have differential effects on the composition of the fecal microbiota in human subjects. PLoS One. 2010 Nov 29;5(11):e15046. doi: 10.1371/journal.pone.0015046. |
| 23038174 | Background | Martinez I, Lattimer JM, Hubach KL, Case JA, Yang J, Weber CG, Louk JA, Rose DJ, Kyureghian G, Peterson DA, Haub MD, Walter J. Gut microbiome composition is linked to whole grain-induced immunological improvements. ISME J. 2013 Feb;7(2):269-80. doi: 10.1038/ismej.2012.104. Epub 2012 Oct 4. |
| 41332831 | Derived | Armet AM, Li F, Deehan EC, Nikolaeva DD, Delannoy-Bruno O, Siegwald L, Berger B, Castelli KM, Rodionov DA, Arzamasov AA, Liu J, Seethaler B, Cole JL, Nguyen KN, Jin M, Zhao YY, Sharma AM, Curtis JM, Proctor SD, Bischoff SC, Wismer WV, Osterman AL, Bakal JA, Greiner R, Field CJ, Knights D, Prado CM, Walter J. Mechanistic insights into microbiome-dependent and personalized responses to dietary fibre in a randomized controlled trial. medRxiv [Preprint]. 2025 Nov 21:2025.11.20.25340625. doi: 10.1101/2025.11.20.25340625. |
| 35562794 | Derived | Deehan EC, Zhang Z, Riva A, Armet AM, Perez-Munoz ME, Nguyen NK, Krysa JA, Seethaler B, Zhao YY, Cole J, Li F, Hausmann B, Spittler A, Nazare JA, Delzenne NM, Curtis JM, Wismer WV, Proctor SD, Bakal JA, Bischoff SC, Knights D, Field CJ, Berry D, Prado CM, Walter J. Elucidating the role of the gut microbiota in the physiological effects of dietary fiber. Microbiome. 2022 May 13;10(1):77. doi: 10.1186/s40168-022-01248-5. |
| 32814582 | Derived | Nguyen NK, Deehan EC, Zhang Z, Jin M, Baskota N, Perez-Munoz ME, Cole J, Tuncil YE, Seethaler B, Wang T, Laville M, Delzenne NM, Bischoff SC, Hamaker BR, Martinez I, Knights D, Bakal JA, Prado CM, Walter J. Gut microbiota modulation with long-chain corn bran arabinoxylan in adults with overweight and obesity is linked to an individualized temporal increase in fecal propionate. Microbiome. 2020 Aug 19;8(1):118. doi: 10.1186/s40168-020-00887-w. |
| D012816 |
| Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D010335 | Pathologic Processes |