Colo-rectal Cancer, Colon Cancer, Diet Habit
Conditions
Keywords
Colorectal cancer, Microbiome, Urolithins, Walnuts
Brief summary
Briefly, this is a 28-day dietary intervention study participants will be asked to eat 2 ounces (52 grams) of walnuts every day for 3 weeks, and at the end of the study period they will come in for a colonoscopy. Participants will first start a 1-week run-in period where they will be asked to avoid foods high in ellagic acid. In addition, they will be asked to complete food surveys and two sets of 3-day dietary records, and to provide colon biopsies for this study during their routine colonoscopy, as well as a blood, and two urine and stool samples. Urine samples will be used for analysis of urolithin, ellagic acid metabolites. Stool samples will be used to assess gut microbiota changes after walnut consumption. Dietary records will be used for compliance and Food Frequency Questionnaire will be used to assess dietary habits. Lastly, the biopsy samples will be used for analysis of biomarkers and anti-inflammatory in the colon, as well as adherent microbiome to the colonic tissue. Data will be analyzed based on the urolithin phenotypes.
Detailed description
The investigators propose to address the influence of ellagic acid obtained from walnuts and its microbial-derived metabolites (urolithin) on the gut microbiome and inflammation-related biomarkers in a human clinical study. Patients will be enrolled and detailed demographic and dietary information, biopsy specimens through colonoscopies, as well as fecal, blood and urine samples will be collected. The wide range of gut urolithin levels provides the rationale for our proposed studies. Will the specific urolithin phenotypes show a disparate range of chemopreventive (anti-inflammatory) response to walnut consumption? The hypothesis is that walnut ingestion in Phenotype A participants (producing the highest levels of urolithin) will be associated with a beneficial anti-inflammatory response as tested in colonic mucosa and a higher abundance of bacterial species associated with ellagic acid metabolism. Although 16S ribosomal ribonucleic acid gene (rRNA) sequencing allows inexpensive bacterial identification at the genus/species level, a whole genome sequencing (mWGS) will be employed to achieve finer classification (strain level), and identify other microbes (e.g., viruses, fungi, small eukaryotes). Furthermore, mWGS targets the entire genome of each microbe (not just the 16S rRNA gene), allowing for construction of a microbial gene catalogue, including a metabolic pathway description for each sample. This will characterize the functional potential of the microbial community. Ultimately, the proposed studies will inform the application of prebiotic to enhance the formation of urolithin metabolites from ellagic acid for the prevention of inflammation-associated Colorectal Cancer, a development that would have significant translational implications.
Interventions
OTHERWalnuts
Participants will consume 2 ounces of walnuts for 21 days
Sponsors
American Institute for Cancer Research
California Walnut Commission
The Jackson Laboratory
UConn Health
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
PREVENTION
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
50 Years to 65 Years
Healthy volunteers
Yes
Inclusion criteria
* Men or women between the ages of 50-65 years old who are scheduled to undergo a routine screening colonoscopy * English speaking/reading patients willing and able to provide written informed consent for study participation * Patients willing to consume walnuts for 3 weeks * Willingness to comply with all study requirements
Exclusion criteria
* Current active malignancy, previous history of gastrointestinal malignancy, or altered gastrointestinal anatomy * Current evidence or previous history of ulcerative colitis or Crohn's disease * HIV infection, chronic viral hepatitis * Allergy to walnuts or hypersensitivity to tree nuts * Use of antibiotics within the past month * Individuals with blood coagulation disorders or on anti-coagulant therapy * Treated with steroids, immunosuppressive agents or other anti-inflammatory drugs one week prior to starting intervention * Non-English-speaking patients who require an interpreter to give consent * Patients residing in the Department of Correction * Inability to comply with the protocol requirements * Any other condition that, in the opinion of the PI, might interfere with study objectives
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Leve of Urolithin of this Population | 28 days post walnuts | Urolithin will be measure in urine using a mass spectrometer to characterize this population into three know urolithin phenotypes, Uro-A, Uro-B and Uro-0, after walnut consumption. |
| Urolithin Phenotype and Colonic Health | 28 days post walnuts | Assess biomarkers in colonic mucosa from biopsy samples collected at colonoscopy that are associated with the three different urolithin metabotype following walnut consumption. This biomarkers is a total of 287 genes involved in cellular apoptosis and proliferation, inflammation and senescence, including TIMP1 (used for power calculations), cytokine and T cell and B cell signaling genes, as well as markers of lymphocyte subsets and immune checkpoint pathways and targets, providing a wide range of functional annotation groups. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Identify Changes in Microbiota and Microbes Responsible for Urolithin Formation Followed by Walnuts Consumption using Metagenomics Sequencing | Day 7 to Day 28 | Microbiome will be analyzed before and after walnut consumption with the goal to identify microbes responsible for urolithins production. DNA will be extracted from fecal samples and the V1-3 hyper-variable region of bacterial 16S rRNA genes will be sequenced to analyze bacterial community structure. Although 16S rRNA gene sequencing allows inexpensive bacterial identification to the genus/species level, mWGS will be employed in order to achieve finer classification (strain level), and identify other microbes, including viruses, fungi and small eukaryotes. |
Countries
United States
Outcome results
None listed