NCT04887584

Brief Summary

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. Measuring pulse consumption in humans is difficult, due to limitations in current methods for dietary assessment which are largely based on dietary recalls that are subject to reporting bias. Robust tools for pulse intake assessment are needed, and biomarkers of dietary pulse intake are one approach to solve this problem. The goal of this human feeding study is evaluate the presence of biomarkers of dietary pulses in human subjects.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
20

participants targeted

Target at below P25 for not_applicable

Timeline
Completed

Started May 2022

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

May 10, 2021

Completed
4 days until next milestone

First Posted

Study publicly available on registry

May 14, 2021

Completed
12 months until next milestone

Study Start

First participant enrolled

May 1, 2022

Completed
1.5 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

November 7, 2023

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

November 7, 2023

Completed
Last Updated

October 26, 2024

Status Verified

October 1, 2024

Enrollment Period

1.5 years

First QC Date

May 10, 2021

Last Update Submit

October 22, 2024

Conditions

Body Weight

Keywords

Dietary pulsesUrine biomarkersMicrobiomeShort chain fatty acidsPlasma biomarkersFecal biomarkersBeansLentilsControlled feedingInterventionChickpeasMetabolomics

Outcome Measures

Primary Outcomes (2)

  • Change in urine metabolomics profile

    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

    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 Outcomes (6)

  • Change in fecal microbiome community

    Day 7, 14, 21, 28, 35, 42

  • Change in fecal short chain fatty acids

    Day 7, 14, 21, 28, 35, 42

  • Change in fecal bile acids

    Day 7, 14, 21, 28, 35, 42

  • Change in plasma short-chain fatty acids

    Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr and 6hr

  • Change in pro-inflammatory cytokines

    Day 14, 28, and 42; fasting and post prandial 0.5hr, 2hr, 3hr and 6hr

  • +1 more secondary outcomes

Study Arms (6)

Group 1

EXPERIMENTAL

Order of treatments: A: Control diet B: Low pulse diet C: High pulse diet

Other: Control dietOther: Low Pulse dietOther: High Pulse diet

Group 2

EXPERIMENTAL

Order of treatments: A: Control diet C: High pulse diet B: Low pulse diet

Other: Control dietOther: Low Pulse dietOther: High Pulse diet

Group 3

EXPERIMENTAL

Order of treatments: B: Low pulse diet A: Control diet C: High pulse diet

Other: Control dietOther: Low Pulse dietOther: High Pulse diet

Group 4

EXPERIMENTAL

Order of treatments: B: Low pulse diet C: High pulse diet A: Control diet

Other: Control dietOther: Low Pulse dietOther: High Pulse diet

Group 5

EXPERIMENTAL

Order of treatments: C: High pulse diet A: Control diet B: Low pulse diet

Other: Control dietOther: Low Pulse dietOther: High Pulse diet

Group 6

EXPERIMENTAL

Order of treatments: C: High pulse diet B: Low pulse diet A: Control diet

Other: Control dietOther: Low Pulse dietOther: High Pulse diet

Interventions

Control dietOTHER

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.

Group 1Group 2Group 3Group 4Group 5Group 6
Low Pulse dietOTHER

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).

Group 1Group 2Group 3Group 4Group 5Group 6
High Pulse dietOTHER

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).

Group 1Group 2Group 3Group 4Group 5Group 6

Eligibility Criteria

Age18 Years - 65 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Body Mass Index (BMI) 18-30 kg/m2
  • Willingness to provide urine and stool and have blood drawn

You may not qualify if:

  • 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)
  • +17 more criteria

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

USDA ARS Western Human Nutrition Research Center

Davis, California, 95616, United States

Location

Related Publications (20)

  • 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.

    PMID: 22043448BACKGROUND

  • 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.

    PMID: 30400385BACKGROUND

  • 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.

    PMID: 25061763BACKGROUND

  • 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.

    PMID: 23089999BACKGROUND

  • 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.

    PMID: 19335713BACKGROUND

  • 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.

    PMID: 24355537BACKGROUND

  • 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.

    PMID: 24389767BACKGROUND

  • 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.

    PMID: 30202317BACKGROUND

  • 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.

    PMID: 29902436BACKGROUND

  • 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.

    PMID: 31467327BACKGROUND

  • 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.

    PMID: 23692866BACKGROUND

  • 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.

    PMID: 27863994BACKGROUND

  • 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.

    PMID: 30915065BACKGROUND

  • 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.

    PMID: 29867803BACKGROUND

  • 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.

    PMID: 29141979BACKGROUND

  • 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.

    PMID: 32115661BACKGROUND

  • 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.

    PMID: 22170369BACKGROUND

  • 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.

    PMID: 29688616BACKGROUND

  • 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.

    PMID: 28067528BACKGROUND

  • 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.

    PMID: 2305711BACKGROUND

MeSH Terms

Conditions

Body Weight

Condition Hierarchy (Ancestors)

Signs and SymptomsPathological Conditions, Signs and Symptoms

Study Officials

  • Brian J Bennett, PhD

    USDA ARS Western Human Nutrition Research Center

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Masking Details
Unblinded
Purpose
BASIC SCIENCE
Intervention Model
CROSSOVER
Sponsor Type
FED
Responsible Party
SPONSOR

Study Record Dates

First Submitted

May 10, 2021

First Posted

May 14, 2021

Study Start

May 1, 2022

Primary Completion

November 7, 2023

Study Completion

November 7, 2023

Last Updated

October 26, 2024

Record last verified: 2024-10

Data Sharing

IPD Sharing
Will not share

Locations

US(1)