Impact of Aronia Berry Consumption on Inflammation, Metabolites, and the Gut Microbiome

• ClinicalTrials.gov Identifier: NCT05255718
• Recruitment Status: Completed
• First Posted: February 24, 2022
• Last Update Posted: March 13, 2024
• Sponsor: Montana State University
• Information provided by (Responsible Party): Montana State University

Study Description

Brief Summary:

The goal of this project is to elucidate interactions between the gut microbiome, anti-inflammatory/anti-oxidant food metabolomic signatures, and human inflammation phenotypes. Inflammation plays both direct and indirect roles in the development of type 2 diabetes (T2D), atherogenic cardiovascular diseases, and other causes of morbidity and mortality. Aronia melanocarpa (Aronia berries) are rich in bioactive polyphenolic compounds, which have been shown to lower inflammation and favorably impact metabolism. However, there is tremendous inter-individual variability in the bioavailability of polyphenolics and production of bioactive phenolic metabolites in the colon that depends, at least in part, on digestive metabolism by the gut microbiota. Little is known about the complex interactions among the gut microbiome, anti-inflammatory food metabolomic signatures, and human inflammation phenotypes. This study will utilize a systems-level approach to disentangle these complex interactions. The specific study objectives are as follows:

1. to determine the impact of Aronia supplementation on inflammation, metabolic health, and gut microbiome composition
2. to determine the static and dynamic metabolomic signature of Aronia based on an Aronia supplementation period and responses to a high-fat meal challenge

Condition or disease	Intervention/treatment	Phase
Inflammation; Metabolic Disorder; Hypertriglyceridemia	Dietary Supplement: Aronia juice; Other: Placebo	Not Applicable

Detailed Description:

To meet these objectives, a randomized, double-blind, placebo-controlled clinical trial of Aronia versus placebo treatment for 28-30 days in human adults will be conducted. Pre- and post-intervention assessments will be made for the following variables: makeup of the gut microbiome (microbial species and relative abundance), gut metabolome, postprandial response of TG, inflammatory cytokines, and serum metabolome to a high-fat meal challenge (established inflammation stimulus), fasting serum glucose, lipid, insulin, inflammation markers and metabolome, blood pressure, and anthropometric measures including weight, body composition, waist circumference, and quantity of visceral adipose tissue. Physical activity, sedentary behavior, and habitual diet will be measured so that these variables can be used to characterize participants and aid in analysis and interpretation of data.

Procedures:

Postprandial lipidemic and inflammation responses: High-fat meal challenges with 40 to 100 g of dietary fat are an established laboratory test to measure both postprandial triglyceridemic and inflammation responses. Investigators have used a 50 g dose of fat delivered in the form of butter on toast on > 50 individuals because this particular dose is effective at discriminating between low versus high TG and inflammation responders. In brief, participants will report to the laboratory after an overnight fast, and blood samples will be collected before, and 1, 2, 4, and 6 hours following ingestion of the high-fat meal. Samples will be analyzed in real time for TG (and full lipid panel plus glucose) using a clinical chemistry analyzer (Piccolo xpress), while serum samples will be aliquoted and stored at -80 C until analysis for inflammatory cytokines, metabolomics, and insulin. Investigators will measure inflammatory cytokines (TNF-α, interleukin(IL)-1β, IL-6 IL-17, IL-23, and granulocyte macrophage colony stimulating factor (GM-CSF)) using high-sensitivity Luminex multiplexing technology (Bio-RadBio-Plex® 200 HTS) prepared by Millipore.

Dietary intervention: Participants will be randomized to either experimental (Aronia) or placebo-matched control group. The experimental supplement will consist of a once daily dose of 100 mL of Aronia juice. The placebo-matched control supplement will have no polyphenol content and will consist of 100 mL of the following mixture: black cherry Koolaid, blue and red food coloring, sucrose and sorbitol. This placebo will match the sugar content of the chokeberry juice. The daily dose of 100 mL for both groups is consumed once daily for duration of 28-30 day supplementation period. All participants will be instructed to avoid consumption of foods with polyphenolic content for the duration of the supplementation period. A list of disallowed foods will be provided for participants to reference.

Gut microbiome analysis: Bulk DNA will be extracted from fecal samples using the Powersoil® DNA Isolation Kit (Mo Bio Laboratories Inc.). DNA will be shipped overnight to the University of Michigan, Center for Microbial Systems, for Illumina MiSeq amplicon sequencing of the 16S V4 variable region. Raw sequencing reads will be processed and curated using the mothur (v.1.39.5) software package, following the mothur MiSeq standard operating procedure, potentially chimeric sequences will be identified and removed using the Uchime (v4.2.40) algorithm, and taxonomic classifications will be assigned using the Bayesian classifier of the Ribosomal Database Project, and operational taxonomic units (OTUs) will be assigned in mothur using the VSEARCH distance-based clustering algorithm at the 97% sequence similarity threshold.

Metabolomic analysis: Samples will be analyzed by high resolution liquid chromatography mass spectrometry (LCMS). Hydrophilic interaction chromatography (HILIC) and reverse-phase (RP) columns will be used for deep coverage. Metabolite identification will use fragmentation pattern matching, authentic standards and database matching with METLIN and the Human Metabome Database (HDB). Novel features of significant interest will be characterized with liquid chromatography mass spectrometry solid phase extraction nuclear magnetic resonance (LCMS-SPE-NMR). Pathway analysis will use XCMS and mummichog.

Dietary analysis: Long-term dietary habits may create adaptations that influence the response to the short-term supplementation of Aronia. This study will use the most recent version (2018) of the web-based Diet History Questionnaire (DHQ III), a food frequency questionnaire designed for adults 19 and older, developed by staff at the Risk Factor Monitoring and Methods Branch (RFMMB) of the NIH National Cancer Institute. The outputs of the DHQ III include carbohydrate constituents, carotenoids and tocopherols, dietary constituents from supplements, fats, fatty acids and cholesterol, macronutrients and energy, minerals, protein constituents, and vitamins are dietary constituents and food groups available in the DHQ III output files.

Statistical analysis: Two-sample t-tests to compare the difference between pre- and post-intervention assessments. Investigators will identify changes in the gut microbiome using the methods utilized in our preliminary research to identify characteristics of the gut microbiome that differentiate low versus high TG responders, and then use regression analysis to determine the level of variability in changes to the Aronia and control treatments explained by changes in relative abundance of gut microbial species. Investigators will identify changes in the gut and serum metabolomes, and then determine the metabolic pathways associated with the metabolomic changes to identify potential mechanisms underlying health impacts of Aronia supplementation.

Study Design

• Study Type: Interventional (Clinical Trial)
• Actual Enrollment: 13 participants
• Allocation: Randomized
• Intervention Model: Parallel Assignment
• Intervention Model Description: Double-blind, parallel, control trial with participant randomization to control versus intervention groups.
• Masking: Double (Participant, Investigator)
• Masking Description: Use of placebo juice matched in flavor, color, and macronutrient content to interventional Aronia juice. Assignment of participants to placebo versus intervention treatments performed by independent researcher and masked until completion of study.
• Primary Purpose: Prevention
• Official Title: Antioxidant-rich Aronia Supplementation Impacts Human Metabolism and Immune Response as Well as Gut Microbiome Metabolism
• Actual Study Start Date: April 27, 2019
• Actual Primary Completion Date: August 18, 2019
• Actual Study Completion Date: August 18, 2019

Arms and Interventions

Arm	Intervention/treatment
Placebo Comparator: Control; The placebo supplement will have no polyphenol content and will consist of 100 mL of the following mixture: black cherry Koolaid, blue and red food coloring, sucrose and sorbitol. This placebo will match the sugar content of the chokeberry juice. Dose of 100 mL is consumed once daily for duration of 28-30 day supplementation period.	Other: Placebo; Once daily dose of 100 mL of placebo juice containing no polyphenols and matched to experimental Aronia juice in color, taste, and macronutrient content
Experimental: Aronia; 100 mL of Aronia juice. Dose of 100 mL is consumed once daily for duration of 28-30 day supplementation period.	Dietary Supplement: Aronia juice; Once daily dose of 100 mL of aronia juice

Outcome Measures

Primary Outcome Measures :

1. Postprandial Serum Inflammatory Cytokine (tumor necrosis factor-alpha, interleukin-(IL)1beta, IL-6, IL-10, IL-17, IL-23, interferon-gamma, and granulocyte macrophage-colony stimulating factor; all in pg/ml) Response to High-fat Meal [ Time Frame: 4 weeks ]
   Area under the curve for inflammatory cytokine (tumor necrosis factor-alpha, interleukin-(IL)1beta, IL-6, IL-10, IL-17, IL-23, interferon-gamma, and granulocyte macrophage-colony stimulating factor; all in pg/ml) concentrations after consuming a meal containing 50 g of fat
2. Peak Serum Cytokine (tumor necrosis factor-alpha, interleukin-(IL)1beta, IL-6, IL-10, IL-17, IL-23, interferon-gamma, and granulocyte macrophage-colony stimulating factor; all in pg/ml) Response to High-fat Meal [ Time Frame: 4 weeks ]
   Greatest change in inflammatory cytokine (tumor necrosis factor-alpha, interleukin-(IL)1beta, IL-6, IL-10, IL-17, IL-23, interferon-gamma, and granulocyte macrophage-colony stimulating factor; all in pg/ml) concentration after consuming a meal containing 50 g of fat
3. Postprandial Serum Metabolomic Response to a High-fat Meal [ Time Frame: 4 weeks ]
   Serum metabolome analysis before and 1, 2, 4, and 6 hours after consuming meal containing 50 g fat
4. Postprandial Serum Metabolite (untargeted) Response to High-fat Meal [ Time Frame: 4 weeks ]
   Changes in concentrations of metabolites measured with untargeted liquid chromatography mass spectrometry (LCMS) metabolomic analysis after consuming a meal containing 50 g of fat
5. Fasting serum metabolites (untargeted) [ Time Frame: 4 weeks ]
   Serum metabolome measured after an overnight fast
6. Gut microbiome composition [ Time Frame: 4 weeks ]
   Relative abundance (operational taxonomic units/10,000 reads) of microbial taxa measured from fecal samples
7. Fasting Serum Triglycerides [ Time Frame: 4 weeks ]
   Concentration of triglycerides in the serum after an overnight fast
8. Peak Serum Triglyceride Response to High-fat Meal [ Time Frame: 4 weeks ]
   Greatest change in triglyceride concentration after consuming a meal containing 50 g of fat
9. Postprandial Serum Triglyceride Response to High-Fat Meal [ Time Frame: 4 weeks ]
   Area under the curve for triglyceride concentration after consuming a meal containing 50 g of fat

Secondary Outcome Measures :

1. Blood pressure [ Time Frame: 4 weeks ]
   Resting systolic and diastolic blood pressure (mmHg)
2. Weight [ Time Frame: 4 weeks ]
   Weight (kg)
3. Height [ Time Frame: 4 weeks ]
   Height (m)
4. Body composition [ Time Frame: 4 weeks ]
   Body composition (% fat, % lean)
5. Waist circumference [ Time Frame: 4 weeks ]
   Waist circumference (cm_)
6. Visceral adipose tissue [ Time Frame: 4 weeks ]
   Volume of visceral adipose tissue (L)
7. Habitual Diet [ Time Frame: 4 weeks ]
   Habitual dietary intake from past month report through a food frequency questionnaire for food, beverage, and supplement intake

Eligibility Criteria

• Ages Eligible for Study: 18 Years to 60 Years (Adult)
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes

Criteria

Inclusion Criteria:

- 18-60 years

Exclusion Criteria:

• Individuals who are pregnant or have other health conditions that might make it difficult to participate in the study, including heart disease, diabetes, and hypertension
• Individuals who are unwilling or unable to complete multiple venipuncture collections.
• Individuals who have food allergies or sensitivities to berry fruits
• Individuals unwilling or unable to avoid foods on provided food list for the duration of the supplementation period.
• Individuals who have food allergies or dietary restrictions to any of the foods being used, including wheat, dairy, or Aronia berries (chokeberries)
• Individuals taking blood pressure, lipid-lowering, or anti-inflammatory medications
• Individuals who have taken antibiotics in previous 90 days
• Individuals who have food allergy or intolerance to red food dye

Contacts and Locations

Locations

United States, Montana

Nutrition Research Laboratory

Bozeman, Montana, United States, 59717

Sponsors and Collaborators

Montana State University

Investigators

• Principal Investigator: Mary P Miles; Montana State University

More Information

• Responsible Party: Montana State University
• ClinicalTrials.gov Identifier: NCT05255718
• Other Study ID Numbers: NIFA 2017-67018-26367; MC010819 ( Other Identifier: Institutional Review Board )
• First Posted: February 24, 2022
• Last Update Posted: March 13, 2024
• Last Verified: March 2024

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: No

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Montana State University:

gut microbiome; metabolome; postprandial hypertriglyceridemia

Additional relevant MeSH terms:

Hypertriglyceridemia; Metabolic Diseases; Inflammation; Pathologic Processes; Hyperlipidemias; Dyslipidemias; Lipid Metabolism Disorders