Impacts of Aronia on Inflammation and the Gut Microbiome

Determining the Gut Microbiota-dependent Impacts of Anthocyanin-rich Aronia Berries on Obese Individuals of Distinct Inflammatory Phenotypes

The overall goal of this project is to determine the inflammation lowering impact of anthocyanin-rich Aronia berries. Inflammation is an underlying mechanism driving the development of several diseases. While an elevation in immune signals in the systemic circulation is commonly attributed to adipose tissue, inflammation is not present in all obese individuals. Adipose tissue must become inflamed, and the inflammation trigger may come from other sources. Microorganisms (microbiome), host tissues, and immune cells residing in the gastrointestinal tract (GIT) are a key source of pro-inflammatory signals that may cause the host organism to become inflamed. Anthocyanins are bioactive compounds with established anti-inflammatory and microbiome altering properties. We hypothesize that the GIT microbiome is a key determinant of host inflammation than can be manipulated by anthocyanins-rich berries to lower inflammation. We assembled a cohort of individuals, characterized their GIT microbiome and performed anthropometric measurements, basal measures of metabolism and metabolic health, and triglyceridemic, metabolomic, and inflammation responses to a high-fat meal challenge.

Study Overview

• Status: Completed
• Conditions: Inflammation; Obesity; Metabolic Syndrome; Hypertriglyceridemia
• Intervention / Treatment: Dietary supplement: Aronia berry juice; Other: Sham comparator

Detailed Description

Anthropometrics. Measurements were collected from participants using the validated segmental multifrequency bioelectrical impedance analysis (SECA mBCA 515, Hamburg, Germany). Fat mass (%) and estimated visceral adipose (L) were used for analysis.

High-Fat Meal Challenge. The high-fat meal contained salted butter (58.3 g, Tillamook) over 3 pieces of whole wheat toast (127.5 g; Wheat Montana). Total energy content of the meal was 714 kcal, with 43.1% from fat, with a macronutrient breakdown of 50 g fat, 54 g carbohydrate, and 12 g protein. Water was provided with the meal; caffeinated black tea was provided instead for participants who identified as habitual coffee consumers.

Blood Sampling. Participants were instructed to avoid alcohol consumption and strenuous physical activity in the 24 hours before their visit and to complete an overnight fast (10 - 12 hours) before blood collection. Participant blood samples were collected by a certified nurse or physician in the morning before ingestion of the meal and hourly for 4 hours after meal ingestion, totaling five time points. Whole blood in serum separating tubes was allowed to clot for 15 minutes before centrifugation at 1200 RPM for 15 minutes with resulting serum aliquoted and stored at -80ºC until analysis.

Determination of blood markers. Blood markers of metabolic syndrome were determined from whole blood run on Picollo Xpress Chemistry Analyzer lipid panels (Abaxis, Union City, USA). Serum insulin (INS) was determined using an insulin ELISA kit (MP Biomedicals, Solon, OH) performed according to manufacturer instructions. Cytokine measurement was performed using high-sensitivity multiplexing technology (Bio-Rad Bio-Plex 200 HTS) following procedures by Millipore (EMD Millipore Corporation, Billerica, USA). Classic systemic pro-inflammatory cytokines were measured and include granulocyte macrophage colony stimulating factor (GM-CSF), interleukin (IL)-1B, IL-6, tumor necrosis factor (TNF)-α. InterleukinI-17 and IL-23, both of which serve a pro-inflammatory and regulatory role in the gut mucosa, were also measured. Serum samples at each time point during the high-fat meal challenge were run in duplicate.

Stool Sample Collection. Collection kits were provided and participants were asked to follow included instructions for the self-collection of a stool sample in the 24 hours before their blood collection visit. After initial collection into a sterile disposable commode, a small portion of the sample was transferred into a sterile Eppendorf tube and transported to researchers. Samples were prepared and aliquoted in an anaerobic chamber then frozen at -80ºC until analysis.

Genomic DNA Extraction and Microbial Analysis. Extraction of bulk DNA from fecal samples was performed using Powersoil DNA Isolation Kit (Mo Bio Laboratories, Inc.) and bead beating. DNA was shipped overnight to the University of Michigan, Michigan Microbiome Project for Illumina MiSeq amplicon sequencing of the 16S rRNA V4 region. After DNA quantification, V4 amplicon libraries were generated with dual-index barcoded primers, then by library purification, pooling, and MiSeq paired-end sequencing. Raw sequencing reads were processed and curated using MOTHUR software (Version 1.35.1) following the MOTHUR standard operating procedure for the MiSeq platform39. In brief review, paired-end reads were assembled into contiguous sequences and screened for length and quality. The remaining contigs were aligned to the SILVA ribosomal RNA database (Release 132), a comprehensive collection of aligned rRNA sequences. Potentially chimeric sequences were identified and removed using the UCHIME algorithm in MOTHUR. Taxonomic classifications were assigned using the Bayesian classifier of the Ribosomal Database Project. Non-target reads were removed, and operational taxonomic units (OTUs) were assigned using VSEARCH distance-based clustering at the 97% similarity threshold. Alpha-, and β- diversity indices were generated using the vegan package in R40. An OTU-based data matrix was constructed for participants included in the ppTG phenotype.

Metabolomic Analysis. Frozen serum samples were thawed and 20μL was placed in a clean tube. 80μL of HPLC grade methanol was added to the sample after which it was vortexed briefly and placed in a -80 C freezer for 2 hours. After two hours, the sample was centrifuged at 20,000g for 10 minutes. The metabolite supernatant was collected and concentrated in a Speed Vac to dryness while the protein pellet was discarded. Samples were then stored at -80 C until ready for LCMS analysis at which time they were reconstituted with 40μL of methanol:water (50:50) and placed in a clean mass spectrometry vial. Analysis was completed on an Agilent 6538 Q-TOF MS coupled to an Agilent 1290 UHPLC using a 130A, 1.7μm, 2.1mm X 10mm Acquity BEH-HILIC HPLC column. Samples were ionized via electrospray ionization and runs were completed in positive mode. Mobile phase A was 15mmol/L ammonium formate and mobile phase B was ACN using a 10-40% A gradient over 6 minutes. Flow was kept at 400µL/minute and the column compartment temperature was set at 30 C. MSMS analysis was completed using the same LC conditions while targeting specific ions using retention time and m/z values from previous MS runs. After LCMS analysis completion, raw data files were converted to .xml files using MSConvert. Data was then mined with mzMine using an intensity minimum value of 1,000 based on a visual inspection of the total ion chromatogram to remove noise. Blank samples were also ran and the resulting features were removed from the biological data if present at a ratio under 5:1 in the sample compared to the blank. Mined data was then input into MetaboAnalyst for statistical analysis. Tandem MS data was analyzed with Sirius software to identify features.

• Study Type: Interventional
• Enrollment (Actual): 40
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Montana
    • Bozeman, Montana, United States, 59717
      • Montana State University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 55 years (Adult)
• Accepts Healthy Volunteers: Yes

Study Population

Individuals residing in the Bozeman, MT area

Description

Inclusion Criteria:

• BMI 28-35 kg/m^2

Exclusion Criteria:

• Antibiotics up to 90 days prior to enrollment
• Anti-inflammatory medications
• Allergy or intolerance to wheat or dairy
• Hormone-based birth control (with exception of intrauterine device)
• Pregnant
• Heart disease
• Other health conditions or concerns that may interfere with study participation

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Aronia juice (ARO); A juice blend of three different cultivars was used: Viking, MacKenzie and Autumn Magic. Raw juice was heat pasteurized before provided to participants. Participants consumed 100 mL of juice per day for duration of intervention period (28-30 days)	Dietary supplement: Aronia berry juice; A juice blend of three different cultivars was used: Viking, MacKenzie and Autumn Magic. Raw juice was heat pasteurized before provided to participants. Participants consumed 100 mL of juice per day.
Sham Comparator: Placebo juice (PLA); The placebo juice was flavor, color, and carbohydrate-matched to experimental Aronia juice. PLA consisted of 28.8 g black cherry Koolaid mix (no sugar added), 128.5 g sorbitol, 74.5 g glucose, 77.9 g fructose, 4 oz lemon juice, 16 drops of blue food coloring, and enough water to create 1 L of solution. Participants consumed 100 mL of juice per day for duration of intervention period (28-30 days)	Other: Sham comparator; The placebo was flavor, color, and carbohydrate-matched to aronia juice. The placebo consisted of 28.8 g black cherry Koolaid mix (no sugar added), 128.5 g sorbitol, 74.5 g glucose, 77.9 g fructose, 4 oz lemon juice, 16 drops of blue food coloring, and enough water to create 1 L of solution. Participants consumed 100 mL of juice per day.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Gut microbiome	Taxonomic composition of the gut microbiome measured from 16s rRNA sequencing of stool samples	1 day
Gut Metabolome	Stool sample metabolome	1 day
Glycemic control	Hemoglobin A1c (% glycosylation)	1 day
Fasting glucose	Fasting serum glucose (mM)	1 day
Fasting insulin	Fasting serum insulin (pmol/l)	1 day
Lipid panel	Fasting serum TG, LDL, HDL, and total cholesterol	1 day
Fasting metabolites	Serum metabolome measured after an overnight fast	1 day
Self-reported physical activity	Self report of the number of days each week in which aerobic, strength, and stretching type exercises are performed	1 day
Blood pressure	Resting systolic and diastolic blood pressure (mmHg)	1 day
Body composition	Body composition (% fat, %lean)	1 day
Height	Height (m)	1 day
Weight	Weight (kg)	1 day
Waist circumference	Waist circumference (cm)	1 day
Visceral adipose tissue	Volume of visceral adipose tissue (l)	1 day
Inflammation state	Serum levels of a eight cytokine panel: interleukin (IL)-1B, IL-6, IL-10, IL-17, IL-23, tumor necrosis factor-alpha (TNF-a), granulocyte macrophage-colony stimulating factor (GM-CSF), interferon gamma (IFNy)	1 day
Postprandial TG Response to a High-fat Meal Challenge	TG concentrations before, 1, 2, 4, and 6 hours following consumption of a meal containing 50 g of fat (toast with butter)	1 day
Postprandial Inflammation Response to a High-fat Meal Challenge	Cytokine panel (IL-1B, IL-6, IL-10, IL-17, IL-23, TNF-a, GM-CSF, and IFNy) before, 1, 2, 4, and 6 hours following consumption of a meal containing 50 g of fat (toast with butter)	1 day
Postprandial Metabolomic Response to a High-fat Meal Challenge	Serum metabolome before, 1, 2, 4, and 6 hours following consumption of a meal containing 50 g of fat (toast with butter)	1 day

Collaborators and Investigators

• Sponsor: Montana State University
• Investigators: Principal Investigator: Mary P Miles, PhD, Montana State University

Publications and helpful links

General Publications

• Wilson SM, Maes AP, Yeoman CJ, Walk ST, Miles MP. Determinants of the postprandial triglyceride response to a high-fat meal in healthy overweight and obese adults. Lipids Health Dis. 2021 Sep 20;20(1):107. doi: 10.1186/s12944-021-01543-4.

Study record dates

Study Major Dates

• Study Start (Actual): April 27, 2019
• Primary Completion (Actual): September 30, 2019
• Study Completion (Actual): December 27, 2021

Study Registration Dates

• First Submitted: October 14, 2019
• First Submitted That Met QC Criteria: October 15, 2019
• First Posted (Actual): October 16, 2019

Study Record Updates

• Last Update Posted (Estimated): January 15, 2024
• Last Update Submitted That Met QC Criteria: January 12, 2024
• Last Verified: January 1, 2024

More Information

Terms related to this study

• Keywords: gut microbiome; metabolome; postprandial hypertriglyceridemia; low-grade inflammation; visceral adipose tissue
• Additional Relevant MeSH Terms: Pathologic Processes; Glucose Metabolism Disorders; Metabolic Diseases; Insulin Resistance; Hyperinsulinism; Lipid Metabolism Disorders; Hyperlipidemias; Dyslipidemias; Inflammation; Metabolic Syndrome; Hypertriglyceridemia
• Other Study ID Numbers: USDA-NIFA 2017-67018-26367

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No