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This is a randomized, 2-period crossover study aimed at assessing the effect of taking a food supplement containing a blend of microbial accessible carbohydrates on the diversity of the gut microbiome. Impacts to the skin, scalp and oral microbiomes; blood inflammatory biomarkers; quality and quantity of sleep; gastrointestinal quality of life; bowel habits, and facial skin features will also be evaluated.
The human body is home to trillions of microbes, which have been shown to play important roles in many aspects of human biology, such as immune function and metabolism. Research in this area has primarily focused on the role that dietary factors have in modulating the gastrointestinal (GI) microbiota with associated changes in host health parameters. Specifically, dietary microbiota accessible carbohydrates (MACs), which include compounds such as resistant starches and other dietary fibers that are typically resistant to digestion, have been shown to serve as a primary source of energy for the distal gut microbiota. Metabolism of MACs by the GI microbiota is important in shaping this microbial ecosystem. A Western diet, typically low in MAC content (e.g., dietary fiber), is associated with a marked reduction in microbial diversity and depletion of specific types of potentially beneficial microbes.
Until only recently, the bulk of microbiota studies have been conducted in animals, and human studies on the GI microbiota have focused primarily on delineating the gut bacterial composition and corresponding changes in taxonomy in response to a particular dietary intervention (e.g., with prebiotics). Additionally, investigations on dietary factors influencing the skin (or scalp) and oral cavity microbiomes have only recently garnered attention. Human intervention studies that increase consumption of dietary MACs are needed to better understand how changes in the composition and function of these bacteria influence host parameters.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Dietary MACs | Experimental | Dietary fiber supplement (blend of resistant starch and dietary fiber food ingredients providing 15g of microbiota accessible carbohydrate/1 scoop serving) will be provided in a powder that will be mixed with 6-10 oz of water (depending on desired thickness) and consumed as a chocolate shake. |
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| Control | Other | No Intervention |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Dietary MACs | Dietary Supplement | All subjects will have a dose-escalation period when randomized to the active arm that will occur as follows: Day 1: 1 scoop of product (morning, in the clinic) Day 2: 1 scoop of product (morning) Day 3: 2 scoops of product (morning and evening) Day 4: 2 scoops of product (morning and evening) Days 5-60: 3 scoops of product (morning, afternoon, evening) Other Names: Dietary fiber supplement |
| Measure | Description | Time Frame |
|---|---|---|
| Change from Baseline in Fecal Microbiome Shannon Diversity Index | The Shannon Diversity Index of the fecal microbiome will be measured at each of the time points via taxonomic profiling using 16S ribosomal RNA gene amplicon sequencing | Baseline, 2, 4 and 8 Weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Change from Baseline in Fecal Microbiome Composition | The fecal microbial composition will be measured via taxonomic profiling using 16S ribosomal RNA gene amplicon sequencing | Baseline, 2, 4 and 8 Weeks |
| Change from Baseline in Forehead Skin Microbiome Composition |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Andrea Lawless, MD | Biofortis Innovation Research | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Biofortis Innovation Services | Addison | Illinois | 60101 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23165832 | Background | Beresniak A, de Linares Y, Krueger GG, Talarico S, Tsutani K, Duru G, Berger G. Validation of a new international quality-of-life instrument specific to cosmetics and physical appearance: BeautyQoL questionnaire. Arch Dermatol. 2012 Nov;148(11):1275-82. doi: 10.1001/archdermatol.2012.2696. | |
| 20679230 | Background |
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This is a randomized, 2-period crossover study.
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Outcomes Assessors will be blind to who is on Arm1 and who is on Arm 2.
|
| Control | Other | No Intervention for 8 weeks |
|
The forehead skin microbial composition will be measured via taxonomic profiling using 16S ribosomal RNA gene amplicon sequencing |
| Baseline, 2, 4 and 8 Weeks |
| Change from Baseline in Scalp Skin Microbiome Composition | The scalp skin microbial composition will be measured via taxonomic profiling using 16S ribosomal RNA gene amplicon sequencing | Baseline, 2, 4 and 8 Weeks |
| Change from Baseline in Oral (Buccal) Microbiome Composition | The oral microbial composition will be measured via taxonomic profiling using 16S ribosomal RNA gene amplicon sequencing | Baseline, 2, 4 and 8 Weeks |
| Change from Baseline in Fecal Short Chain Fatty Acids (Butyrate) | Fecal short chain fatty acids (e.g., butyrate) will be measured at each of the time points. | Baseline, 2, 4 and 8 Weeks |
| Change from Baseline in Blood Inflammatory Marker (C-Reactive Protein) | The inflammatory marker C-Reactive Protein in the blood will be measured at each of the time points. | Baseline, 4 and 8 Weeks |
| Change from Baseline in Blood Inflammatory Marker (IL-10) | The inflammatory marker IL-10 in the blood will be measured at each of the time points. | Baseline, 4 and 8 Weeks |
| Change from Baseline in Blood Inflammatory Marker (IL-6) | The inflammation marker IL-6 in the blood will be measured at each of the time points. | Baseline, 4 and 8 Weeks |
| Change from Baseline in Blood Inflammatory Marker (TNF-Alpha) | The inflammation marker TNF-alpha in the blood will be measured at each of the time points. | Baseline, 4 and 8 Weeks |
| Change from Baseline in Blood Inflammatory Marker (Lipopolysaccharides) | The inflammation marker lipopolysaccharides in the blood will be measured at each of the time points. | Baseline, 4 and 8 Weeks |
| Change from Baseline in Blood Testosterone Hormone Levels | Blood Testosterone Levels (free and total) will be measured at each of the time points. | Baseline and 8 Weeks |
| Change from Baseline in Blood Estradiol Levels | Blood Estradiol Levels will be measured at each of the time points | Baseline and 8 Weeks |
| Change from Baseline in Fasting Blood Lipid Profiles | Blood lipid profiles (including total cholesterol, HDL-cholesterol, non-HDL-cholesterol, calculated LDL-cholesterol, and triglycerides) will be measured at each of the time points | Baseline and 8 Weeks |
| Change from Baseline in Satiety | An appetite questionnaire will be used to measure satiety at each of the time points | Baseline, 2, 4 and 8 Weeks |
| Change from Baseline in Heart Rate Variance | Heart Rate Variance will be measured using a standardized method at each of the time points | Baseline, 4 and 8 Weeks |
| Change from Baseline in Bowel habits | Bowel habits will be recorded using a diary at each of the time points. | Baseline, 2, 4 and 8 weeks |
| Change from Baseline in Stool Quality | Subjects will record the quality of their stool using the Bristol Stool Scale at each of the time points | Baseline, 2, 4 and 8 Weeks |
| Change in Gastrointestinal Quality of Life (GIQOL) | The electronic GIQOL Instrument will be used to asses GI QoL at each of the time points. | 4 and 8 Weeks |
| Change in Sleep Quantity | Each subject will wear an activity tracker (Actigraph) to measure the amount of sleep obtained from baseline to 8 weeks. | Baseline through 8 Weeks |
| Change from Baseline in Sleep Quality | The electronic Pittsburgh Sleep Quality Index Instrument will be used to measure the change from baseline in Sleep Quality Index | Baseline, 4 and 8 Weeks |
| Change from Baseline in Facial Wrinkling | Standardized facial images will be captured using the VISIA CR facial imaging system under multiple lighting modalities. Images will be analyzed using quantitative image analysis to assess facial wrinkling around the eye (crow's feet wrinkles). | Baseline, 4 and 8 Weeks |
| Change from Baseline in Facial Hyperpigmentation | Standardized facial images will be captured using the VISIA CR facial imaging system under multiple lighting modalities. Images will be analyzed using quantitative image analysis to assess facial hyperpigmentation around the eyes and on the left and right cheeks. | Baseline, 4 and 8 Weeks |
| Change from Baseline in Facial Redness | Standardized facial images will be captured using the VISIA CR facial imaging system under multiple lighting modalities. Images will be analyzed using quantitative image analysis to assess facial red features on the left and right cheeks. | Baseline, 4 and 8 Weeks |
| Change from Baseline in Facial Porphyrins | Standardized facial images will be captured using the VISIA CR facial imaging system under multiple lighting modalities. Images will be analyzed using quantitative image analysis to assess facial porphyrins on the forehead, nose and on the left and right cheeks. | Baseline, 4 and 8 Weeks |
| Change from Baseline in Facial Skin Texture | Standardized facial images will be captured using the VISIA CR facial imaging system under multiple lighting modalities. Images will be analyzed using quantitative image analysis to assess facial skin texture on the left and right cheeks. | Baseline, 4 and 8 Weeks |
| Change from Baseline in Facial Skin Pores | Standardized facial images will be captured using the VISIA CR facial imaging system under multiple lighting modalities. Images will be analyzed using quantitative image analysis to assess facial skin pores on the left and right cheeks. | Baseline, 4 and 8 Weeks |
| Beauty Quality of Life | The electronic Beauty Quality of Life Instrument will be used to measure BeautyQOL at 8 Weeks | 8 Weeks |
| Test Product Likability | An electronic product likability questionnaire will be used to measure the subjects response to how much they liked the test product at 8 weeks. Product attributes will include flavor, sweetness, texture, thickness, and ease of consumption. | 8 Weeks |
| De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB, Massart S, Collini S, Pieraccini G, Lionetti P. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci U S A. 2010 Aug 17;107(33):14691-6. doi: 10.1073/pnas.1005963107. Epub 2010 Aug 2. |
| 23748339 | Background | El Kaoutari A, Armougom F, Gordon JI, Raoult D, Henrissat B. The abundance and variety of carbohydrate-active enzymes in the human gut microbiota. Nat Rev Microbiol. 2013 Jul;11(7):497-504. doi: 10.1038/nrmicro3050. Epub 2013 Jun 10. |
| 7749697 | Background | Eypasch E, Williams JI, Wood-Dauphinee S, Ure BM, Schmulling C, Neugebauer E, Troidl H. Gastrointestinal Quality of Life Index: development, validation and application of a new instrument. Br J Surg. 1995 Feb;82(2):216-22. doi: 10.1002/bjs.1800820229. |
| 22674334 | Background | Hooper LV, Littman DR, Macpherson AJ. Interactions between the microbiota and the immune system. Science. 2012 Jun 8;336(6086):1268-73. doi: 10.1126/science.1223490. Epub 2012 Jun 6. |
| 24065795 | Background | Karlsson F, Tremaroli V, Nielsen J, Backhed F. Assessing the human gut microbiota in metabolic diseases. Diabetes. 2013 Oct;62(10):3341-9. doi: 10.2337/db13-0844. |
| 25671414 | Background | McGill CR, Fulgoni VL 3rd, Devareddy L. Ten-year trends in fiber and whole grain intakes and food sources for the United States population: National Health and Nutrition Examination Survey 2001-2010. Nutrients. 2015 Feb 9;7(2):1119-30. doi: 10.3390/nu7021119. |
| 25156449 | Background | Sonnenburg ED, Sonnenburg JL. Starving our microbial self: the deleterious consequences of a diet deficient in microbiota-accessible carbohydrates. Cell Metab. 2014 Nov 4;20(5):779-786. doi: 10.1016/j.cmet.2014.07.003. Epub 2014 Aug 21. |