Health StatusNCT04829396
Effect of Fibre Supplementation on Mixed-meal Challenge Response
A study testing Fibre mixture in people with Health Status, run by Centre for Human Drug Research, Netherlands at 1 site in Netherlands.
Trial summary
Improving healthy physiological processes through nutritional intervention, as opposed to restoring physiology after disease occurrence, is an important new avenue for the reduction of disease burden in the population. A relatively new target for interventions is the gut microbiome. Read more about this study
- Who is it for?
- Ages 45 to 70 yearsHealthy volunteers can take part
- Conditions the study is for
- Health Status
- What is being tested?
- Fibre mixture
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 64 participants
- Where
- 1 siteNetherlands
- Study dates
- 23 Dec 2019to 4 Jul 2021
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 45 to 70 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Signed informed consent prior to any study-mandated procedure.
- Healthy male or female subjects, between 45 and 70 years of age, inclusive.
- Female subjects must be of non-childbearing potential (postmenopausal for at least 12 months prior to screening or documented surgically sterile).
- BMI 25-30 kg/m2, inclusive
- Fibre intake below recommended limits as assessed by dietary fibre intake short food frequency questionnaire (DFI-FFQ) (16).
- Has the ability to communicate well with the Investigator in the Dutch language and willing to comply with the study restrictions.
Who cannot join
- Evidence of any active or chronic disease or condition that could interfere with, or for which the treatment of might interfere with, the conduct of the study, or that would pose an unacceptable risk to the subject in the opinion of the investigator (following a detailed medical history, physical examination, vital signs (systolic and diastolic blood pressure, pulse rate, body temperature) and 12-lead electrocardiogram (ECG)). Minor deviations from the normal range may be accepted, if judged by the Investigator to have no clinical relevance.
- Chronic diseases that can affect study parameters, including but not limited to metabolic syndrome, chronic obstructive pulmonary disease, diabetes mellitus, auto-immune disease, cardiovascular disease, cerebrovascular disease, gastrointestinal disease or history of abdominal surgery with removal of (part of) small or large intestine, or any known condition that can interfere with treatment compliance such as psychiatric disease or drug dependence.
- Positive Hepatitis B surface antigen (HBsAg), Hepatitis C antibody (HCV Ab), or human immunodeficiency virus antibody (HIV Ab) at screening.
- Systolic blood pressure (SBP) greater than 180 or less than 90 mm Hg, and diastolic blood pressure (DBP) greater than 120 or less than 50 mm Hg at screening.
- Abnormal findings in the resting ECG at screening defined as:
- QTcF> 450 for males or QTcF>470 for females or QTcF < 300 ms;
Show all 16Show fewer
- Personal or family history of congenital long QT syndrome or sudden death;
- Evidence of atrial fibrillation, atrial flutter, complete branch block, Wolf-Parkinson-White Syndrome, or history of cardiac pacemaker.
- Use of antibiotics, antacids, laxatives, statins, anti-diarrheal, immunomodulatory or antidiabetic medication <3 months before start of study.
- Use of any medication or vitamin, mineral, herbal, and dietary supplements within 7 days of study product administration, or less than 5 half-lives (whichever is longer). Exceptions will only be made if the rationale is clearly documented by the investigator.
- Vegan, macrobiotic, slimming or medically prescribed diet up to 3 months prior to the first administration.
- History of food allergies or intolerances or any confirmed significant allergic reactions (urticarial or anaphylaxis) against any drug or multiple documented drug allergies.
- Participation in an investigational drug or device study within 3 months prior to first dosing.
- History of abuse of addictive substances (alcohol, illegal substances) or current use of more than 21 units alcohol per week, drug abuse, or regular user of sedatives, hypnotics, tranquillisers, or any other addictive agent, or positive test for drugs of abuse at screening or pre-dose.
- Active smoker up to 15 years prior to the screening visit.
- Loss or donation of blood over 500 mL within three months (males) or four months (females) prior to screening or intention to donate blood or blood products during the study.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: A Randomized, Double-blind, Placebo-controlled Crossover Study to Assess the Effect of 12-week Fibre Supplementation on Mixed-meal Challenge Response in Adults
Improving healthy physiological processes through nutritional intervention, as opposed to restoring physiology after disease occurrence, is an important new avenue for the reduction of disease burden in the population. A relatively new target for interventions is the gut microbiome. Dietary fibre is a nutritional intervention shown to alter gut microbiome and function. The present study aims to elucidate the relationship between microbiome modulation with dietary fibre and health. In order to assess health improvement, a meal challenge will be given to characterize the physiological processes and their resilience to challenge in healthy volunteers before and after microbiome modulation.
Read the detailed description
The gut microbiome has been extensively implicated as an organ involved in various physiological processes such as nutrient and drug metabolism, microbial protection and immunomodulation. The gut microbiome educates the host immune system, promotes homeostasis and protects against systemic inflammation, among other things through production of short-chain fatty acids (SCFAs). An altered microbiome is also involved in inducing low-grade systemic inflammation by translocation of bacterial lipopolysaccharide (LPS) through the intestinal lining. Additionally, the gut microbiome produces trimethylamine (TMA), which when oxidized to trimethylamine N-oxide (TMAO) is documented as an indicator of endothelial dysfunction and cardiovascular health risk. The goal of the present study is to further clarify the relationship between the gut microbiome, homeostasis, immunity and health. This will be achieved by introducing an intervention known to alter gut microbiome characteristics, dietary fibre, and measuring its effect on the gut microbiome on the one hand and the response to metabolic challenge on the other.
Fibre mixtures consisting of indigestible carbohydrates have been shown to alter the composition and function of the gut microbiome. Fibre functions as a substrate for fermentation, creating SCFAs, and as a food source for bacterial commensals regarded as beneficial. Thus, fibre can shift the balance of microbial species in the gut towards beneficial commensals and away from potential pathogens. Moreover, these changes in composition and function of the microbiome can feasibly affect integrity of intestinal lining, TMA production and various other processes, therefore exerting an effect on low-grade inflammation, cardiovascular and metabolic health. The gut microbiome can be analysed using 16s RNA sequencing, quantifying the relative abundance of various bacterial species, and by measuring SCFAs in human plasma, quantifying their production by bacteria in the gut. In this study, we will integrate a third method to measure the gut microbiome. The I-screen, developed by TNO, is a platform in which the in vivo microbiome composition can be mimicked in an in vitro system, allowing for experimental analysis of the effects of compounds and ingredients on the microbiome. With this method, the processes and conditions affecting microbiome composition can be assessed more closely, possibly clarifying specific relationships between intervention and microbiome composition.
The present study aims to assess the effects of this microbiome modulation by evaluating the response to a metabolic challenge, quantified through measurement of a metabolic and inflammatory biomarker panel to create a composite outcome called 'resilience'. This phenotypical flexibility test (PhenFlex, PFT), consisting of a mixed meal with protein, fat and glucose, induces a systemic response which when analysed allows for sensitive assessment of subtle health benefits in otherwise healthy subjects. Results of the PFT are presented as a composite of multiple biomarkers grouped by physiological processes such as inflammation and liver metabolism, creating the 'axes' of a 'health space'. Earlier research shows that selected dietary products affected inflammatory processes, oxidative stress and metabolism, based on dynamic responses after fat load. Other research has shown that the challenge test concept is able to reveal previously unidentified correlations between specific nutrients and health-related processes, and that decreased phenotypic flexibility as measured by PFT can be used to identify people that might benefit from health interventions. Finally, in a human volunteer study with whole grain wheat products researchers were able to show a positive effect on diverse composite markers of resilience, including low grade inflammation, after 12 weeks of exchange of refined wheat for whole grain wheat consumption.
By measuring the effect of our intervention on the gut microbiome with several tools, as well as using the challenge concept for quantifying health, this study is well positioned to provide insight in the specific mechanisms of interaction between microbiome and host, as well as create new evidence-based avenues for the improvement of health.
- Conditions
- Health Status
- Being tested
- placebo, Fibre mixture
- Keywords
- Fibre, Gut microbiome, Meal challenge, Microvasculature
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
placeboOther
Powder consisting of 13 g of digestible carbohydrates with similar appearance as the investigational fibre mixture.
Fibre mixtureDietary supplement
The study product is a fibre mixture consisting of a mix of 10 g of Acacia Gum and 3 g of carrot fibre taken p.o. o.d. in powder form for a total of approximately 10 g of dietary fibre per day.
| Study group | Role | What they receive |
|---|---|---|
| Fibre mixture | Experimental | Dietary supplement. A mixture of fibres will be administered consisting of 10g of acacia gum powder and 3g of carrot powder.
The study product is a fibre mixture consisting of a mix of 10 g of Acacia Gum and 3 g of carrot fibre taken p.o. o.d. in powder form for a total of approximately 10 g of dietary fibre per day. Receives: Dietary Supplement: Fibre mixture |
| Placebo for Fibre mixture | Placebo comparator | A placebo of the mixture of fibres will be administered. Receives: Other: placebo |
What is being measured
The primary outcome is the main question the study is designed to answer.
Microbiome changes
Microbiome changes measured using 16S rRNA sequencing
Measured: Change from Baseline microbiome changes at week 4
Microbiome changes
Microbiome changes measured using 16S rRNA sequencing
Measured: Change from Baseline microbiome changes at week 8
Microbiome changes
Microbiome changes measured using 16S rRNA sequencing
Measured: Change from Baseline microbiome changes at week 12
Microbiome changes
Microbiome changes measured using 16S rRNA sequencing
Measured: Change from Baseline microbiome changes at week 16
Microbiome changes
Microbiome changes measured using 16S rRNA sequencing
Measured: Change from Baseline microbiome changes at week 20
Microbiome changes
Microbiome changes measured using 16S rRNA sequencing
Measured: Change from Baseline microbiome changes at week 24
Microbiome changes
Microbiome changes measured using 16S rRNA sequencing
Measured: Change from Baseline microbiome changes at week 28
Microbiome changes
Microbiome changes measured using 16S rRNA sequencing
Measured: Change from Baseline microbiome changes at week 32
Non-esterified fatty acids (NEFAs)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to non-esterified fatty acids (NEFAs)
Measured: Change from Baseline at week 12
Non-esterified fatty acids (NEFAs)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to non-esterified fatty acids (NEFAs)
Measured: Change from Baseline at week 20
Non-esterified fatty acids (NEFAs)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to non-esterified fatty acids (NEFAs)
Measured: Change from Baseline at week 32
Glucose
Response to challenge of metabolic and inflammatory biomarkers including but not limited to glucose
Measured: Change from Baseline at week 12
Glucose
Response to challenge of metabolic and inflammatory biomarkers including but not limited to glucose
Measured: Change from Baseline at week 20
Glucose
Response to challenge of metabolic and inflammatory biomarkers including but not limited to glucose
Measured: Change from Baseline at week 32
Insulin
Response to challenge of metabolic and inflammatory biomarkers including but not limited to insulin
Measured: Change from Baseline at week 12
Insulin
Response to challenge of metabolic and inflammatory biomarkers including but not limited to insulin
Measured: Change from Baseline at week 20
Insulin
Response to challenge of metabolic and inflammatory biomarkers including but not limited to insulin
Measured: Change from Baseline at week 32
Triglycerides (TG)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to triglycerides (TG)
Measured: Change from Baseline at week 12
Triglycerides (TG)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to triglycerides (TG)
Measured: Change from Baseline at week 20
Triglycerides (TG)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to triglycerides (TG)
Measured: Change from Baseline at week 32
High-density lipoprotein (HDL)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-density lipoprotein (HDL)
Measured: Change from Baseline at week 12
High-density lipoprotein (HDL)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-density lipoprotein (HDL)
Measured: Change from Baseline at week 20
High-density lipoprotein (HDL)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-density lipoprotein (HDL)
Measured: Change from Baseline at week 32
Low-density lipoprotein (LDL)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to low-density lipoprotein (LDL)
Measured: Change from Baseline at week 12
Low-density lipoprotein (LDL)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to low-density lipoprotein (LDL)
Measured: Change from Baseline at week 20
Low-density lipoprotein (LDL)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to low-density lipoprotein (LDL)
Measured: Change from Baseline at week 32
Total cholesterol
Response to challenge of metabolic and inflammatory biomarkers including but not limited to total cholesterol.
Measured: Change from Baseline at week 12
Total cholesterol
Response to challenge of metabolic and inflammatory biomarkers including but not limited to total cholesterol.
Measured: Change from Baseline at week 20
Total cholesterol
Response to challenge of metabolic and inflammatory biomarkers including but not limited to total cholesterol.
Measured: Change from Baseline at week 32
Interleukin-6
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-6
Measured: Change from Baseline at week 32
Interleukin-6
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-6
Measured: Change from Baseline at week 12
Interleukin-6
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-6
Measured: Change from Baseline at week 20
Interleukin-8
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-8
Measured: Change from Baseline at week 12
Interleukin-8
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-8
Measured: Change from Baseline at week 20
Interleukin-8
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-8
Measured: Change from Baseline at week 32
Interleukin-10
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-10
Measured: Change from Baseline at week 12
Interleukin-10
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-10
Measured: Change from Baseline at week 20
Interleukin-10
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-10
Measured: Change from Baseline at week 32
Tumour necrosis factor alpha (TNF-α)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to tumour necrosis factor alpha (TNF-α).
Measured: Change from Baseline at week 12
Tumour necrosis factor alpha (TNF-α)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to tumour necrosis factor alpha (TNF-α).
Measured: Change from Baseline at week 20
Tumour necrosis factor alpha (TNF-α)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to tumour necrosis factor alpha (TNF-α).
Measured: Change from Baseline at week 32
High-sensitivity C-reactive protein (hs-CRP)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-sensitivity C-reactive protein (hs-CRP)
Measured: Change from Baseline at week 12
High-sensitivity C-reactive protein (hs-CRP)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-sensitivity C-reactive protein (hs-CRP)
Measured: Change from Baseline at week 20
High-sensitivity C-reactive protein (hs-CRP)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-sensitivity C-reactive protein (hs-CRP)
Measured: Change from Baseline at week 32
Serum amyloid A (SAA)
Response to challenge of metabolic and inflammatory biomarkers including but not limited serum amyloid A (SAA)
Measured: Change from Baseline at week 12
Serum amyloid A (SAA)
Response to challenge of metabolic and inflammatory biomarkers including but not limited serum amyloid A (SAA)
Measured: Change from Baseline at week 20
Serum amyloid A (SAA)
Response to challenge of metabolic and inflammatory biomarkers including but not limited serum amyloid A (SAA)
Measured: Change from Baseline at week 32
Alanine aminotransferase (ALT)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to alanine aminotransferase (ALT)
Measured: Change from Baseline at week 12
Alanine aminotransferase (ALT)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to alanine aminotransferase (ALT)
Measured: Change from Baseline at week 20
Alanine aminotransferase (ALT)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to alanine aminotransferase (ALT)
Measured: Change from Baseline at week 32
Aspartate aminotransferase (AST)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to aspartate aminotransferase (AST)
Measured: Change from Baseline at week 12
Aspartate aminotransferase (AST)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to aspartate aminotransferase (AST)
Measured: Change from Baseline at week 20
Aspartate aminotransferase (AST)
Response to challenge of metabolic and inflammatory biomarkers including but not limited to aspartate aminotransferase (AST)
Measured: Change from Baseline at week 32
Gamma-glutamyltransferase (GGT).
Response to challenge of metabolic and inflammatory biomarkers including but not limited to gamma-glutamyltransferase (GGT).
Measured: Change from Baseline at week 12
Gamma-glutamyltransferase (GGT).
Response to challenge of metabolic and inflammatory biomarkers including but not limited to gamma-glutamyltransferase (GGT).
Measured: Change from Baseline at week 20
Gamma-glutamyltransferase (GGT).
Response to challenge of metabolic and inflammatory biomarkers including but not limited to gamma-glutamyltransferase (GGT).
Measured: Change from Baseline at week 32
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Apr 2021
- Study start23 Dec 2019
- Primary completion4 Jul 2021
- Study completion4 Jul 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Health StatusStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Crossover
- Model description
- Placebo or intervention, wash-out, intervention or placebo
- Masking
- Triple blind
- Who is masked
- Participant, Care provider, Investigator
- Enrolment
- 64 participants (actual)
Sponsor and investigators
- Lead sponsor
- Centre for Human Drug Research, Netherlands
- Sponsor type
- University, hospital or other
- Collaborators
- Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek (TNO)
- Responsible party
- Sponsor
- Investigators
- M. Moerland, PhD, Principal investigator, Centre for Human Drug Research
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04829396
- Sponsor's protocol ID
- CHDR1901
- Other IDs
- NL71723.056.19
- Status last verified
- Aug 2021
- First submitted
- 3 Dec 2020
- Last updated
- 3 Aug 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Eveleens Maarse BC, Eggink HM, Warnke I, Bijlsma S, van den Broek TJ, Oosterman JE, Caspers MPM, Sybesma W, Gal P, van Kraaij SJW, Schuren FHJ, Moerland M, Hoevenaars FPM. Impact of fibre supplementation on microbiome and resilience in healthy participants: A randomized, placebo-controlled clinical trial. Nutr Metab Cardiovasc Dis. 2024 Jun;34(6):1416-1426. doi: 10.1016/j.numecd.2024.01.028. Epub 2024 Feb 6.
PubMed 38499450
Study at a glance
From the registry record, last updated by the sponsor on 3 Aug 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Randomized, Double-blind, Placebo-controlled Crossover Study to Assess the Effect of 12-week Fibre Supplementation on Mixed-meal Challenge Response in Adults
- ClinicalTrials.gov ID
- NCT04829396
- Acronym / sponsor ID
- CHDR1901
- Conditions
- Health Status
- Keywords
- Fibre, Gut microbiome, Meal challenge, Microvasculature
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 64 participants (actual)
- Lead sponsor
- Centre for Human Drug Research, NetherlandsUniversity, hospital or other
- Collaborators
- Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek (TNO)
- Study start
- 23 Dec 2019 (actual)
- Primary completion
- 4 Jul 2021 (actual)
- Study completion
- 4 Jul 2021 (actual)
- First posted
- 2 Apr 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Improving healthy physiological processes through nutritional intervention, as opposed to restoring physiology after disease occurrence, is an important new avenue for the reduction of disease burden in the population. A relatively new target for interventions is the gut microbiome. Dietary fibre is a nutritional intervention shown to alter gut microbiome and function. The present study aims to elucidate the relationship between microbiome modulation with dietary fibre and health. In order to assess health improvement, a meal challenge will be given to characterize the physiological processes and their resilience to challenge in healthy volunteers before and after microbiome modulation.
Detailed description
The gut microbiome has been extensively implicated as an organ involved in various physiological processes such as nutrient and drug metabolism, microbial protection and immunomodulation. The gut microbiome educates the host immune system, promotes homeostasis and protects against systemic inflammation, among other things through production of short-chain fatty acids (SCFAs). An altered microbiome is also involved in inducing low-grade systemic inflammation by translocation of bacterial lipopolysaccharide (LPS) through the intestinal lining. Additionally, the gut microbiome produces trimethylamine (TMA), which when oxidized to trimethylamine N-oxide (TMAO) is documented as an indicator of endothelial dysfunction and cardiovascular health risk. The goal of the present study is to further clarify the relationship between the gut microbiome, homeostasis, immunity and health. This will be achieved by introducing an intervention known to alter gut microbiome characteristics, dietary fibre, and measuring its effect on the gut microbiome on the one hand and the response to metabolic challenge on the other.
Fibre mixtures consisting of indigestible carbohydrates have been shown to alter the composition and function of the gut microbiome. Fibre functions as a substrate for fermentation, creating SCFAs, and as a food source for bacterial commensals regarded as beneficial. Thus, fibre can shift the balance of microbial species in the gut towards beneficial commensals and away from potential pathogens. Moreover, these changes in composition and function of the microbiome can feasibly affect integrity of intestinal lining, TMA production and various other processes, therefore exerting an effect on low-grade inflammation, cardiovascular and metabolic health. The gut microbiome can be analysed using 16s RNA sequencing, quantifying the relative abundance of various bacterial species, and by measuring SCFAs in human plasma, quantifying their production by bacteria in the gut. In this study, we will integrate a third method to measure the gut microbiome. The I-screen, developed by TNO, is a platform in which the in vivo microbiome composition can be mimicked in an in vitro system, allowing for experimental analysis of the effects of compounds and ingredients on the microbiome. With this method, the processes and conditions affecting microbiome composition can be assessed more closely, possibly clarifying specific relationships between intervention and microbiome composition.
The present study aims to assess the effects of this microbiome modulation by evaluating the response to a metabolic challenge, quantified through measurement of a metabolic and inflammatory biomarker panel to create a composite outcome called 'resilience'. This phenotypical flexibility test (PhenFlex, PFT), consisting of a mixed meal with protein, fat and glucose, induces a systemic response which when analysed allows for sensitive assessment of subtle health benefits in otherwise healthy subjects. Results of the PFT are presented as a composite of multiple biomarkers grouped by physiological processes such as inflammation and liver metabolism, creating the 'axes' of a 'health space'. Earlier research shows that selected dietary products affected inflammatory processes, oxidative stress and metabolism, based on dynamic responses after fat load. Other research has shown that the challenge test concept is able to reveal previously unidentified correlations between specific nutrients and health-related processes, and that decreased phenotypic flexibility as measured by PFT can be used to identify people that might benefit from health interventions. Finally, in a human volunteer study with whole grain wheat products researchers were able to show a positive effect on diverse composite markers of resilience, including low grade inflammation, after 12 weeks of exchange of refined wheat for whole grain wheat consumption.
By measuring the effect of our intervention on the gut microbiome with several tools, as well as using the challenge concept for quantifying health, this study is well positioned to provide insight in the specific mechanisms of interaction between microbiome and host, as well as create new evidence-based avenues for the improvement of health.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- Triple blind (participant, care provider, investigator)
- Number of arms
- 2
- Model description
- Placebo or intervention, wash-out, intervention or placebo
| Arm | Type | Receives |
|---|---|---|
| Fibre mixture | Experimental | Dietary Supplement: Fibre mixtureDietary supplement. A mixture of fibres will be administered consisting of 10g of acacia gum powder and 3g of carrot powder. The study product is a fibre mixture consisting of a mix of 10 g of Acacia Gum and 3 g of carrot fibre taken p.o. o.d. in powder form for a total of approximately 10 g of dietary fibre per day. |
| Placebo for Fibre mixture | Placebo comparator | Other: placeboA placebo of the mixture of fibres will be administered. |
Who may qualify
- Ages
- 45 to 70 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Signed informed consent prior to any study-mandated procedure.
- Healthy male or female subjects, between 45 and 70 years of age, inclusive.
- Female subjects must be of non-childbearing potential (postmenopausal for at least 12 months prior to screening or documented surgically sterile).
- BMI 25-30 kg/m2, inclusive
- Fibre intake below recommended limits as assessed by dietary fibre intake short food frequency questionnaire (DFI-FFQ) (16).
Key exclusion criteria (16 listed)
- Evidence of any active or chronic disease or condition that could interfere with, or for which the treatment of might interfere with, the conduct of the study, or that would pose an unacceptable risk to the subject in the opinion of the investigator (following a detailed medical history, physical examination, vital signs (systolic and diastolic blood pressure, pulse rate, body temperature) and 12-lead electrocardiogram (ECG)). Minor deviations from the normal range may be accepted, if judged by the Investigator to have no clinical relevance.
- Chronic diseases that can affect study parameters, including but not limited to metabolic syndrome, chronic obstructive pulmonary disease, diabetes mellitus, auto-immune disease, cardiovascular disease, cerebrovascular disease, gastrointestinal disease or history of abdominal surgery with removal of (part of) small or large intestine, or any known condition that can interfere with treatment compliance such as psychiatric disease or drug dependence.
- Positive Hepatitis B surface antigen (HBsAg), Hepatitis C antibody (HCV Ab), or human immunodeficiency virus antibody (HIV Ab) at screening.
- Systolic blood pressure (SBP) greater than 180 or less than 90 mm Hg, and diastolic blood pressure (DBP) greater than 120 or less than 50 mm Hg at screening.
- Abnormal findings in the resting ECG at screening defined as:
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| placeboPowder consisting of 13 g of digestible carbohydrates with similar appearance as the investigational fibre mixture. | Other | Placebo for Fibre mixture |
| Fibre mixtureThe study product is a fibre mixture consisting of a mix of 10 g of Acacia Gum and 3 g of carrot fibre taken p.o. o.d. in powder form for a total of approximately 10 g of dietary fibre per day. | Dietary supplement | Fibre mixture |
Primary outcome
Microbiome changes
Time frame: Change from Baseline microbiome changes at week 4
Microbiome changes measured using 16S rRNA sequencing
Microbiome changes
Time frame: Change from Baseline microbiome changes at week 8
Microbiome changes measured using 16S rRNA sequencing
Microbiome changes
Time frame: Change from Baseline microbiome changes at week 12
Microbiome changes measured using 16S rRNA sequencing
Microbiome changes
Time frame: Change from Baseline microbiome changes at week 16
Microbiome changes measured using 16S rRNA sequencing
Microbiome changes
Time frame: Change from Baseline microbiome changes at week 20
Microbiome changes measured using 16S rRNA sequencing
Microbiome changes
Time frame: Change from Baseline microbiome changes at week 24
Microbiome changes measured using 16S rRNA sequencing
Microbiome changes
Time frame: Change from Baseline microbiome changes at week 28
Microbiome changes measured using 16S rRNA sequencing
Microbiome changes
Time frame: Change from Baseline microbiome changes at week 32
Microbiome changes measured using 16S rRNA sequencing
Non-esterified fatty acids (NEFAs)
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to non-esterified fatty acids (NEFAs)
Non-esterified fatty acids (NEFAs)
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to non-esterified fatty acids (NEFAs)
Non-esterified fatty acids (NEFAs)
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to non-esterified fatty acids (NEFAs)
Glucose
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to glucose
Glucose
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to glucose
Glucose
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to glucose
Insulin
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to insulin
Insulin
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to insulin
Insulin
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to insulin
Triglycerides (TG)
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to triglycerides (TG)
Triglycerides (TG)
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to triglycerides (TG)
Triglycerides (TG)
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to triglycerides (TG)
High-density lipoprotein (HDL)
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-density lipoprotein (HDL)
High-density lipoprotein (HDL)
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-density lipoprotein (HDL)
High-density lipoprotein (HDL)
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-density lipoprotein (HDL)
Low-density lipoprotein (LDL)
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to low-density lipoprotein (LDL)
Low-density lipoprotein (LDL)
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to low-density lipoprotein (LDL)
Low-density lipoprotein (LDL)
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to low-density lipoprotein (LDL)
Total cholesterol
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to total cholesterol.
Total cholesterol
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to total cholesterol.
Total cholesterol
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to total cholesterol.
Interleukin-6
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-6
Interleukin-6
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-6
Interleukin-6
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-6
Interleukin-8
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-8
Interleukin-8
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-8
Interleukin-8
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-8
Interleukin-10
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-10
Interleukin-10
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-10
Interleukin-10
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to interleukin-10
Tumour necrosis factor alpha (TNF-α)
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to tumour necrosis factor alpha (TNF-α).
Tumour necrosis factor alpha (TNF-α)
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to tumour necrosis factor alpha (TNF-α).
Tumour necrosis factor alpha (TNF-α)
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to tumour necrosis factor alpha (TNF-α).
High-sensitivity C-reactive protein (hs-CRP)
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-sensitivity C-reactive protein (hs-CRP)
High-sensitivity C-reactive protein (hs-CRP)
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-sensitivity C-reactive protein (hs-CRP)
High-sensitivity C-reactive protein (hs-CRP)
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to high-sensitivity C-reactive protein (hs-CRP)
Serum amyloid A (SAA)
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited serum amyloid A (SAA)
Serum amyloid A (SAA)
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited serum amyloid A (SAA)
Serum amyloid A (SAA)
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited serum amyloid A (SAA)
Alanine aminotransferase (ALT)
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to alanine aminotransferase (ALT)
Alanine aminotransferase (ALT)
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to alanine aminotransferase (ALT)
Alanine aminotransferase (ALT)
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to alanine aminotransferase (ALT)
Aspartate aminotransferase (AST)
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to aspartate aminotransferase (AST)
Aspartate aminotransferase (AST)
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to aspartate aminotransferase (AST)
Aspartate aminotransferase (AST)
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to aspartate aminotransferase (AST)
Gamma-glutamyltransferase (GGT).
Time frame: Change from Baseline at week 12
Response to challenge of metabolic and inflammatory biomarkers including but not limited to gamma-glutamyltransferase (GGT).
Gamma-glutamyltransferase (GGT).
Time frame: Change from Baseline at week 20
Response to challenge of metabolic and inflammatory biomarkers including but not limited to gamma-glutamyltransferase (GGT).
Gamma-glutamyltransferase (GGT).
Time frame: Change from Baseline at week 32
Response to challenge of metabolic and inflammatory biomarkers including but not limited to gamma-glutamyltransferase (GGT).
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Aug 2021.
- Derived from this study: PubMed 38499450Eveleens Maarse BC, Eggink HM, Warnke I, Bijlsma S, van den Broek TJ, Oosterman JE, Caspers MPM, Sybesma W, Gal P, van Kraaij SJW, Schuren FHJ, Moerland M, Hoevenaars FPM. Impact of fibre supplementation on microbiome and resilience in healthy participants: A randomized, placebo-controlled clinical trial. Nutr Metab Cardiovasc Dis. 2024 Jun;34(6):1416-1426. doi: 10.1016/j.numecd.2024.01.028. Epub 2024 Feb 6.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
M. Moerland, PhD principal investigator
Centre for Human Drug Research
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Fibre mixture in people with Health Status, run by Centre for Human Drug Research, Netherlands at 1 site in Netherlands.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 16 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 3 Aug 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Netherlands. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. Some participants in this study may receive a placebo. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Microbiome changes (time frame: Change from Baseline microbiome changes at week 4). The study lists 56 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04829396, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 3 Aug 2021.