Enhancing the Benefits of Blueberry Polyphenols With Protein

June 5, 2024 updated by: Colorado State University

Enhancing the Benefits of Blueberry Polyphenols With Plant and Whey Proteins

The purpose of this randomized crossover trial is determine whether acute consumption of blueberries with different proteins from plants (hemp or pea) or dairy (whey) impact the absorption of blueberry phytochemicals, which could impact the health benefits of blueberries. A secondary purpose is to understand the role that the gut microbiome may play, as well as the impact on urine polyphenol metabolites and potential implications for cardiometabolic health. Researchers will compare four arms: 1) Blueberries; 2) Blueberries + whey protein; 3) Blueberries + pea protein; and 4) Blueberries + hemp protein.

Study Overview

Detailed Description

Polyphenols are a structurally diverse class of secondary metabolites found in plants, with numerous documented benefits for human health including, but not limited to, anti-inflammatory, antioxidative and cardiovascular-protective effects. Dietary intake of polyphenols in the United States is low in comparison to other developed countries due to low intake of fruits and vegetables. Recent studies suggest fruit and vegetable intake should be increased by incorporating those foods into snacks and mixed meals as ingredients rather than standalone food items. Presently, berries comprise 10% of the total fruit intake and 7% of the total polyphenol intake of American adults. As a versatile food ingredient, berries can easily be added to foods like smoothies and yogurts as an ingredient to increase intake.

Low polyphenol intake is an issue exacerbated by poor bioavailability. Consumption does not necessarily mean that these beneficial compounds are delivered to body tissues, as evidenced by low levels of detection in blood and accumulation in the lower gastrointestinal tract after feeding. Bioavailability can be enhanced through the complexation of polyphenols with proteins, a phenomenon which occurs naturally in complex mixtures including both classes of nutrients. It has been shown that the complexation of polyphenols with proteins in cow's milk, known as a "matrix effect", enhances the polyphenol stability and uptake throughout digestion. The incorporation of berries into complex food mixtures may not only be an opportunity for improved health outcomes due to increased polyphenol intake, but also an effective strategy for ensuring that consumers receive the benefits of the nutrients they consume.

It is unknown whether the beneficial matrix effects observed when polyphenols interact with dairy proteins are exclusive to dairy proteins due to characteristics of high digestibility or structures which favor phenolic interaction, or if similar effects would be observed with proteins from other sources. Increasing consumer demand for alternative protein sources for reasons pertaining to human health and environmental sustainability has introduced a variety of novel plant-based proteins to the American diet, which may elicit similarly advantageous matrix effects on the bioavailability of polyphenols depending on their digestibility and structural characteristics. Understanding protein-polyphenol interactions in novel food matrices is necessary for the development of food products that promote polyphenol consumption and bioavailability with the aim to improve human health.

Study Type

Interventional

Enrollment (Actual)

19

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Colorado
      • Fort Collins, Colorado, United States, 80523-1571
        • Food and Nutrition Clinical Research Laboratory - CSU Gifford Building

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Aged 18 years or older

Exclusion Criteria:

  • • Blood levels of HbA1c ≥ 6.5%, total cholesterol ≥ 240 mg/dL, LDL cholesterol ≥ 130 mg/dL, triglycerides ≥ 200 mg/dL

    • Are anemic (hemoglobin less than 13.5 g/dL in men and 12.0 g/dL in women)
    • Have an average blood pressure greater than or equal to 130/80 mmHg, or have diagnosed hypertension, hyperlipidemia, cardiovascular disease, diabetes, cancer, kidney, liver, gastrointestinal or pancreatic disease
    • Taking blood pressure-, lipid- or glucose-lowering, or hormone replacement medications
    • Are pregnant or are trying to become pregnant
    • Have a body mass index < 18.5 or > 30 kg/m2
    • >3 days/week vigorous exercise
    • Are not willing to maintain your normal eating/drinking and exercise habits over the duration of the study
    • History of smoking cigarettes in past 12 months
    • Binge and/or heavy drinker (>3 drinks on any given occasion and/or >7 drinks/week for women, and >4 drinks on any given occasion and/or >14 drinks/week for men)
    • Have allergies or contraindication to study treatments, procedures, or procedure supplies
    • Unable to attend study visits.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Basic Science
  • Allocation: Randomized
  • Interventional Model: Crossover Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Blueberries
Freeze-dried blueberry powder
22 g freeze-dried blueberry powder mixed with water
Active Comparator: Blueberries and Whey Protein
Freeze-dried blueberry powder and whey protein
22 g freeze-dried blueberry powder mixed with whey protein and water
Active Comparator: Blueberries and Pea Protein
Freeze-dried blueberry powder and pea protein
22 g freeze-dried blueberry powder mixed with pea protein and water
Active Comparator: Blueberries and Hemp Protein
Freeze-dried blueberry powder and hemp protein
22 g freeze-dried blueberry powder mixed with hemp protein and water

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Plasma polyphenol metabolites
Time Frame: Change from 0 hours (pre-treatment consumption) to 1 hour post-treatment consumption
Plasma polyphenol metabolite analysis using mass spectrometry
Change from 0 hours (pre-treatment consumption) to 1 hour post-treatment consumption
Plasma polyphenol metabolites
Time Frame: Change from 0 hours (pre-treatment consumption) to 2 hours post-treatment consumption
Plasma polyphenol metabolite analysis using mass spectrometry
Change from 0 hours (pre-treatment consumption) to 2 hours post-treatment consumption
Plasma polyphenol metabolites
Time Frame: Change from 0 hours (pre-treatment consumption) to 4 hours post-treatment consumption
Plasma polyphenol metabolite analysis using mass spectrometry
Change from 0 hours (pre-treatment consumption) to 4 hours post-treatment consumption
Plasma polyphenol metabolites
Time Frame: Change from 0 hours (pre-treatment consumption) to 6 hours post-treatment consumption
Plasma polyphenol metabolite analysis using mass spectrometry
Change from 0 hours (pre-treatment consumption) to 6 hours post-treatment consumption
Plasma polyphenol metabolites
Time Frame: Change from 0 hours (pre-treatment consumption) to 24 hours post-treatment consumption
Plasma polyphenol metabolite analysis using mass spectrometry
Change from 0 hours (pre-treatment consumption) to 24 hours post-treatment consumption

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Urine polyphenol metabolites
Time Frame: 0 hours (pre-treatment consumption) and 24 hours post-treatment consumption
Urine polyphenol metabolite analysis using mass spectrometry
0 hours (pre-treatment consumption) and 24 hours post-treatment consumption

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
Gut microbial analysis
Time Frame: 0 hours (pre-treatment consumption) and 24 hours post-treatment consumption
16S rRNA gene sequencing
0 hours (pre-treatment consumption) and 24 hours post-treatment consumption
Blood pressure
Time Frame: 0 hours (pre-treatment consumption) and 1, 2, 4, and 6 hours post-treatment consumption
Brachial blood pressure parameters (systolic, diastolic, and pulse pressure)
0 hours (pre-treatment consumption) and 1, 2, 4, and 6 hours post-treatment consumption
Aortic pressure
Time Frame: 0 hours (pre-treatment consumption) and 1, 2, 4, and 6 hours post-treatment consumption
Aortic pressure parameters (systolic pressure, aortic pressure, pulse pressure)
0 hours (pre-treatment consumption) and 1, 2, 4, and 6 hours post-treatment consumption
Augmentation index
Time Frame: 0 hours (pre-treatment consumption) and 1, 2, 4, and 6 hours post-treatment consumption
Augmentation index measured via SphygmoCor Xcel
0 hours (pre-treatment consumption) and 1, 2, 4, and 6 hours post-treatment consumption
Glucose
Time Frame: 0 hours (pre-treatment consumption) and 1, 2, 4, 6, and 24 hours post-treatment consumption
Blood glucose will be assessed using standard assays
0 hours (pre-treatment consumption) and 1, 2, 4, 6, and 24 hours post-treatment consumption
Insulin
Time Frame: 0 hours (pre-treatment consumption) and 1, 2, 4, 6, and 24 hours post-treatment consumption
Blood insulin will be assessed using standard assays
0 hours (pre-treatment consumption) and 1, 2, 4, 6, and 24 hours post-treatment consumption
Nitric oxide metabolites
Time Frame: 0 hours (pre-treatment consumption) and 1, 2, 4, 6, and 24 hours post-treatment consumption
Blood nitric oxide metabolites will be assessed using standard assays
0 hours (pre-treatment consumption) and 1, 2, 4, 6, and 24 hours post-treatment consumption

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Sarah A Johnson, PhD, RDN, Colorado State University, Department of Food Science and Human Nutrition
  • Principal Investigator: Charlene Van Buiten, PhD, Colorado State University, Department of Food Science and Human Nutrition

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

March 9, 2023

Primary Completion (Actual)

July 26, 2023

Study Completion (Actual)

June 1, 2024

Study Registration Dates

First Submitted

June 22, 2023

First Submitted That Met QC Criteria

July 20, 2023

First Posted (Actual)

August 1, 2023

Study Record Updates

Last Update Posted (Actual)

June 6, 2024

Last Update Submitted That Met QC Criteria

June 5, 2024

Last Verified

June 1, 2024

More Information

Terms related to this study

Other Study ID Numbers

  • 3647

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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