- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04887584
Pulse Biomarker Discovery
Identifying the Role of Pulses in a Healthful Diet: Metabolomic Signatures of Dietary Pulses and Their Benefits on Cardiometabolic Risk Factors
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Dietary pulses, including beans, chickpeas, and lentils, are high in soluble fiber with potential benefits to human health: Pulses are moderate energy density foods, low in fat and high in dietary protein, fiber, vitamins and minerals. Moderate pulse consumption is associated with improvements in glycemic control and reduced risk of cardiovascular disease, obesity and type 2 diabetes. However, only 5% of the U.S. population currently meet recommended fiber intakes. As pulses are an excellent source of fiber, increasing their levels in the American diet could lead to demonstrable health benefits in the population, including positive influences on glucose regulation. Additionally, pulse impacts on the gut microbiome may be responsible for reported health benefits. While diet has direct impacts on health, these effects can be mediated by the microbiome, and dietary fiber is a key determinant of this interaction. The fermentation of soluble fiber by specific microbial species lead to the production of short chain fatty acids (SCFAs) including propionate and butyrate which are positively associated with insulin sensitivity. In general, elevated colonic SCFA production is associated with improved glucose regulation, appetite modulation, and immune system modulation.
The overall goal of this research is to evaluate how pulse digestion and microbial fermentation influence the circulating and excreted metabolome. To achieve this goal, a randomized controlled feeding study including one week of control, low pulse and high pulse diet will be provided to participants. Metabolomics will be used to identify biomarkers or signatures for pulse enriched diets in urine and plasma. In addition, researchers will investigate dietary pulse related changes in the microbiome community and short chain fatty acid production in fecal samples.
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Contact
- Name: Ellen L Bonnel, PhD
- Phone Number: 530-752-4184
- Email: ellen.bonnel@usda.gov
Study Locations
-
-
California
-
Davis, California, United States, 95616
- USDA ARS Western Human Nutrition Research Center
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Body Mass Index (BMI) 18-30 kg/m2
- Willingness to provide urine and stool and have blood drawn
Exclusion Criteria:
- Active participation in another research study
- Tested positive for severe acute respiratory syndrome (SARS) Coronavirus (COV)-2 within the past 10 days
- Been in close contact with a SARS COV-2 positive person within the past 14 days
- Unwillingness to consume pulses or pulse-related products
- Fasting glucose ≥120 mg/dL
- Fasting triglyceride ≥400 mg/dL
- LDL-cholesterol ≥160 mg/dL
- Blood Pressure (BP): Systolic BP ≥140 mmHg or Diastolic BP ≥90 mmHg
Current use of dietary supplements and/or unwillingness to cease intake of dietary supplements
- Vegan or vegetarian lifestyle or any other dietary restrictions that would interfere with consuming the intervention foods and beverages (including dietary intolerances, allergies and sensitivities)
- Unwillingness to consume intervention foods and beverages
Engage in
- More than moderate drinking (> 1 drink serving per day for women or >2 drink servings per day for men).
- Binge drinking (4 drinks within two hours).
- Excessive intake of caffeine containing products (excessive defined as ≥ 400mg/day)
- Diagnosis of disordered eating or eating disorder
Recent diagnosis of any of the following or measurement on screening lab tests
- Anemia (hemoglobin <11.7g/dL)
- Abnormal liver function
- Liver Enzymes that are >200% of upper limit (alanine aminotransferase (ALT) upper limit is 43 U/L or aspartate aminotransferase (AST) upper limit is 54 U/L)
History of any of the following
- Gastric bypass surgery
- Inflammatory bowel disease (IBD) or other GI conditions that would interfere with consuming the intervention foods
- Active cancer in the past three years excluding squamous or basal cell carcinomas of the skin that have been handled medically by local excision
- Other serious medical conditions
- Recent dental work or have conditions of the oral cavity that would interfere with consuming the intervention foods and beverages
- Long term use of antibiotics
Taking any over the counter or prescribed medication for any of the following
- Elevated lipids or glucose
- High blood pressure
- Weight loss
- Are pregnant, planning to become pregnant within the duration of the study or breastfeeding.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Basic Science
- Allocation: Randomized
- Interventional Model: Crossover Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Experimental: Group 1
Order of treatments: A: Control diet B: Low pulse diet C: High pulse diet |
The control Typical American Diet (TAD) diet pattern will mimic the level of intake of fruits, vegetables, whole grains, added sugars, saturated fats and sodium in the general U.S. population.
This diet will feature no servings of pulses per day.
The Low Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 0.2 cups of pulses per day at 2,000 kilocalories (kcals).
The High Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 1.5 cups of pulses per day at 2,000 kilocalories (kcals).
|
Experimental: Group 2
Order of treatments: A: Control diet C: High pulse diet B: Low pulse diet |
The control Typical American Diet (TAD) diet pattern will mimic the level of intake of fruits, vegetables, whole grains, added sugars, saturated fats and sodium in the general U.S. population.
This diet will feature no servings of pulses per day.
The Low Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 0.2 cups of pulses per day at 2,000 kilocalories (kcals).
The High Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 1.5 cups of pulses per day at 2,000 kilocalories (kcals).
|
Experimental: Group 3
Order of treatments: B: Low pulse diet A: Control diet C: High pulse diet |
The control Typical American Diet (TAD) diet pattern will mimic the level of intake of fruits, vegetables, whole grains, added sugars, saturated fats and sodium in the general U.S. population.
This diet will feature no servings of pulses per day.
The Low Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 0.2 cups of pulses per day at 2,000 kilocalories (kcals).
The High Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 1.5 cups of pulses per day at 2,000 kilocalories (kcals).
|
Experimental: Group 4
Order of treatments: B: Low pulse diet C: High pulse diet A: Control diet |
The control Typical American Diet (TAD) diet pattern will mimic the level of intake of fruits, vegetables, whole grains, added sugars, saturated fats and sodium in the general U.S. population.
This diet will feature no servings of pulses per day.
The Low Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 0.2 cups of pulses per day at 2,000 kilocalories (kcals).
The High Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 1.5 cups of pulses per day at 2,000 kilocalories (kcals).
|
Experimental: Group 5
Order of treatments: C: High pulse diet A: Control diet B: Low pulse diet |
The control Typical American Diet (TAD) diet pattern will mimic the level of intake of fruits, vegetables, whole grains, added sugars, saturated fats and sodium in the general U.S. population.
This diet will feature no servings of pulses per day.
The Low Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 0.2 cups of pulses per day at 2,000 kilocalories (kcals).
The High Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 1.5 cups of pulses per day at 2,000 kilocalories (kcals).
|
Experimental: Group 6
Order of treatments: C: High pulse diet B: Low pulse diet A: Control diet |
The control Typical American Diet (TAD) diet pattern will mimic the level of intake of fruits, vegetables, whole grains, added sugars, saturated fats and sodium in the general U.S. population.
This diet will feature no servings of pulses per day.
The Low Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 0.2 cups of pulses per day at 2,000 kilocalories (kcals).
The High Pulse diet will be designed based on the TAD with substitution of pulses for lean meat and grains.
This diet will feature 1.5 cups of pulses per day at 2,000 kilocalories (kcals).
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Change in urine metabolomics profile
Time Frame: Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr, 6hr, 12hr and 24hr
|
Urine metabolites will be measured by gas chromatography mass spectrometry (GCMS) before and after consumption of control, low pulse or high pulse diets.
|
Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr, 6hr, 12hr and 24hr
|
Change in plasma metabolomics profile
Time Frame: Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr and 6hr
|
Plasma metabolites will be measured by gas chromatography mass spectrometry (GCMS) before and after consumption of control, low pulse or high pulse diets.
|
Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr and 6hr
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Change in fecal microbiome community
Time Frame: Day 7, 14, 21, 28, 35, 42
|
DNA of colonic microbiome will be measured before and after each diet exposure.
|
Day 7, 14, 21, 28, 35, 42
|
Change in fecal short chain fatty acids
Time Frame: Day 7, 14, 21, 28, 35, 42
|
Acetate, propionate and butyrate will be measured by GCMS before and after each diet exposure.
|
Day 7, 14, 21, 28, 35, 42
|
Change in fecal bile acids
Time Frame: Day 7, 14, 21, 28, 35, 42
|
Bile acids will be measured by GCMS before and after each diet exposure.
|
Day 7, 14, 21, 28, 35, 42
|
Change in plasma short-chain fatty acids
Time Frame: Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr and 6hr
|
Plasma acetate, propionate and butyrate will be measured by GCMS before and after consumption of control, low pulse or high pulse diets.
|
Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr and 6hr
|
Change in pro-inflammatory cytokines
Time Frame: Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr and 6hr
|
Cytokines including tumor necrosis factor alpha (TNF-a), interleukin (IL)-1, IL-6 and interferon-gamma will be measured in plasma using multiplex assays.
|
Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr and 6hr
|
Change in anti-inflammatory cytokines
Time Frame: Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr and 6hr
|
Cytokines including interleukin (IL)-1 receptor antagonist, IL-4, IL-10, IL-11, and IL-13 will be measured in plasma using multiplex assays.
|
Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr and 6hr
|
Collaborators and Investigators
Collaborators
Investigators
- Principal Investigator: Brian J Bennett, PhD, USDA ARS Western Human Nutrition Research Center
Publications and helpful links
General Publications
- Anderson JW, Baird P, Davis RH Jr, Ferreri S, Knudtson M, Koraym A, Waters V, Williams CL. Health benefits of dietary fiber. Nutr Rev. 2009 Apr;67(4):188-205. doi: 10.1111/j.1753-4887.2009.00189.x.
- McCrory MA, Hamaker BR, Lovejoy JC, Eichelsdoerfer PE. Pulse consumption, satiety, and weight management. Adv Nutr. 2010 Nov;1(1):17-30. doi: 10.3945/an.110.1006. Epub 2010 Nov 16.
- Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990 Feb;51(2):241-7. doi: 10.1093/ajcn/51.2.241.
- Jenkins DJ, Kendall CW, Augustin LS, Mitchell S, Sahye-Pudaruth S, Blanco Mejia S, Chiavaroli L, Mirrahimi A, Ireland C, Bashyam B, Vidgen E, de Souza RJ, Sievenpiper JL, Coveney J, Leiter LA, Josse RG. Effect of legumes as part of a low glycemic index diet on glycemic control and cardiovascular risk factors in type 2 diabetes mellitus: a randomized controlled trial. Arch Intern Med. 2012 Nov 26;172(21):1653-60. doi: 10.1001/2013.jamainternmed.70.
- McRorie JW Jr, McKeown NM. Understanding the Physics of Functional Fibers in the Gastrointestinal Tract: An Evidence-Based Approach to Resolving Enduring Misconceptions about Insoluble and Soluble Fiber. J Acad Nutr Diet. 2017 Feb;117(2):251-264. doi: 10.1016/j.jand.2016.09.021. Epub 2016 Nov 15.
- Margier M, George S, Hafnaoui N, Remond D, Nowicki M, Du Chaffaut L, Amiot MJ, Reboul E. Nutritional Composition and Bioactive Content of Legumes: Characterization of Pulses Frequently Consumed in France and Effect of the Cooking Method. Nutrients. 2018 Nov 4;10(11):1668. doi: 10.3390/nu10111668.
- Mudryj AN, Yu N, Aukema HM. Nutritional and health benefits of pulses. Appl Physiol Nutr Metab. 2014 Nov;39(11):1197-204. doi: 10.1139/apnm-2013-0557. Epub 2014 Jun 13.
- Threapleton DE, Greenwood DC, Evans CE, Cleghorn CL, Nykjaer C, Woodhead C, Cade JE, Gale CP, Burley VJ. Dietary fibre intake and risk of cardiovascular disease: systematic review and meta-analysis. BMJ. 2013 Dec 19;347:f6879. doi: 10.1136/bmj.f6879.
- Yao B, Fang H, Xu W, Yan Y, Xu H, Liu Y, Mo M, Zhang H, Zhao Y. Dietary fiber intake and risk of type 2 diabetes: a dose-response analysis of prospective studies. Eur J Epidemiol. 2014 Feb;29(2):79-88. doi: 10.1007/s10654-013-9876-x. Epub 2014 Jan 5.
- Quagliani D, Felt-Gunderson P. Closing America's Fiber Intake Gap: Communication Strategies From a Food and Fiber Summit. Am J Lifestyle Med. 2016 Jul 7;11(1):80-85. doi: 10.1177/1559827615588079. eCollection 2017 Jan-Feb.
- Makki K, Deehan EC, Walter J, Backhed F. The Impact of Dietary Fiber on Gut Microbiota in Host Health and Disease. Cell Host Microbe. 2018 Jun 13;23(6):705-715. doi: 10.1016/j.chom.2018.05.012.
- Muller M, Hernandez MAG, Goossens GH, Reijnders D, Holst JJ, Jocken JWE, van Eijk H, Canfora EE, Blaak EE. Circulating but not faecal short-chain fatty acids are related to insulin sensitivity, lipolysis and GLP-1 concentrations in humans. Sci Rep. 2019 Aug 29;9(1):12515. doi: 10.1038/s41598-019-48775-0.
- Wrzosek L, Miquel S, Noordine ML, Bouet S, Joncquel Chevalier-Curt M, Robert V, Philippe C, Bridonneau C, Cherbuy C, Robbe-Masselot C, Langella P, Thomas M. Bacteroides thetaiotaomicron and Faecalibacterium prausnitzii influence the production of mucus glycans and the development of goblet cells in the colonic epithelium of a gnotobiotic model rodent. BMC Biol. 2013 May 21;11:61. doi: 10.1186/1741-7007-11-61.
- Parada Venegas D, De la Fuente MK, Landskron G, Gonzalez MJ, Quera R, Dijkstra G, Harmsen HJM, Faber KN, Hermoso MA. Short Chain Fatty Acids (SCFAs)-Mediated Gut Epithelial and Immune Regulation and Its Relevance for Inflammatory Bowel Diseases. Front Immunol. 2019 Mar 11;10:277. doi: 10.3389/fimmu.2019.00277. eCollection 2019. Erratum In: Front Immunol. 2019 Jun 28;10:1486.
- Garcia-Mantrana I, Selma-Royo M, Alcantara C, Collado MC. Shifts on Gut Microbiota Associated to Mediterranean Diet Adherence and Specific Dietary Intakes on General Adult Population. Front Microbiol. 2018 May 7;9:890. doi: 10.3389/fmicb.2018.00890. eCollection 2018.
- Gibson RS, Charrondiere UR, Bell W. Measurement Errors in Dietary Assessment Using Self-Reported 24-Hour Recalls in Low-Income Countries and Strategies for Their Prevention. Adv Nutr. 2017 Nov 15;8(6):980-991. doi: 10.3945/an.117.016980. Print 2017 Nov.
- Corrigendum for McCullough et al. Metabolomic markers of healthy dietary patterns in US postmenopausal women. Am J Clin Nutr 2019;109:1439-51. Am J Clin Nutr. 2020 Mar 1;111(3):728. doi: 10.1093/ajcn/nqz235. No abstract available.
- Ross AB, Bourgeois A, Macharia HN, Kochhar S, Jebb SA, Brownlee IA, Seal CJ. Plasma alkylresorcinols as a biomarker of whole-grain food consumption in a large population: results from the WHOLEheart Intervention Study. Am J Clin Nutr. 2012 Jan;95(1):204-11. doi: 10.3945/ajcn.110.008508. Epub 2011 Dec 14.
- Brennan L, Hu FB. Metabolomics-Based Dietary Biomarkers in Nutritional Epidemiology-Current Status and Future Opportunities. Mol Nutr Food Res. 2019 Jan;63(1):e1701064. doi: 10.1002/mnfr.201701064. Epub 2018 May 28.
- Madrid-Gambin F, Llorach R, Vazquez-Fresno R, Urpi-Sarda M, Almanza-Aguilera E, Garcia-Aloy M, Estruch R, Corella D, Andres-Lacueva C. Urinary 1H Nuclear Magnetic Resonance Metabolomic Fingerprinting Reveals Biomarkers of Pulse Consumption Related to Energy-Metabolism Modulation in a Subcohort from the PREDIMED study. J Proteome Res. 2017 Apr 7;16(4):1483-1491. doi: 10.1021/acs.jproteome.6b00860. Epub 2017 Mar 16.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- FL115
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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