- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05220657
Exploring the Relationship Between the Gut Microbiome, Physical Fitness Levels and Metabolic Responses to Exercise (EXOMIC)
Exploring the Relationship Between the Gut Microbiome Based Metagenomic Signature, Physical Fitness Levels and Metabolic Responses to Exercise: a Pilot Study on 50 Healthy Male Volunteers
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Gut microbiota are all microorganisms including bacteria, archaea and microscopic eukaryotes that live in the digestive tracts of humans or mammals. All these microorganisms live in homeostasis in the gastrointestinal tract and provide a variety of benefits to the host immune system and energy metabolism in a state called eubiosis. On contrary, a state of dysbiosis occurs when the diversity of commensal bacteria is reduced especially in some chronic diseases including obesity, cancer or gastrointestinal diseases. During the last decade, substantial studies highlighted that a link exists between gut microbiota composition and sport performance. Research team especially identified a direct link between gut microbiota and skeletal muscle, a key organ in sport performance (Nay et al. 2019). Using rodent models, They observed that 1) the endurance performance was reduced in mice for which the gut microbiome had been experimentally destructed (Nay et al. 2019), and 2) the reduction of endurance performance was due to lower muscle glycogen levels, a key energy substrate for muscle endurance.
Complementary researches have been conducted in humans to characterize the impact of physical activity on gut microbiota composition and function. A study conducted in large American cohort of 1500 individuals have thus highlighted that the gut microbiota diversity was much more important in individuals performing regular physical activity (3-5 times/week or more) compared to physically inactive people. The few studies conducted in top-level athletes are in accordance with these results. Indeed, it has been demonstrated that international Irish rugby players exhibited a clear higher microbial diversity than inactive and sedentary populations associated to higher production of short-chain fatty acids (SCFA), some key energy substrates produced by commensal bacteria (Clarke et al. 2014; Barton et al. 2018). Conversely, when people are completely physically deconditioned such as astronauts under microgravity or bedridden patients, a clear modification of gut microbiota composition occurs in the gastrointestinal tract (Voorhies and al. 2019). Such differences between top-level athletes, inactive or extremely inactive individuals cannot be only explained to lifestyle, especially diet. Indeed, longitudinal studies have clearly showed that a several weeks training period can increase the gut microbial diversity in humans suggesting an increased capacity of gut microbiota to extract energy from food, especially from dietary fibers (Allen et al. 2018). All together, these data support that the gut microbiota could adapt to the energy needs of the body, really higher in top-level athletes or considerably lower in extremely inactive individuals (e.g. astronauts or bedridden patients). These data also suggest that gut microbiota could punctually inform of the body's metabolic state of an individual.
In this context, this clinical study aims to characterize the bacterial metagenome of gut microbiota from populations located in a continuum from sedentary people to top-level athletes with high (i.e. soccer players), even very high energy needs (i.e. cyclists). The finality of this project is thus to determine if it exists some bacterial profile allowing to characterize, even to predict, the energy metabolism of an athlete and so the probability to be performant in competition.
For this purpose, we will assess the metabolic responses to exercise from different athletic populations (i.e. elite cyclists and soccer players) and non-active of moderately active populations. All the volunteers (n=50) will perform 3 visits in the M2S lab: 1) an inclusion visit including anthropometric measures, dietary and physical activity surveys, and after which the volunteer will leave the lab with a Nahibu kit allowing to send us a fecal sample in the next 7 days, 2) a second visit to perform the incremental cycling test, 3) a last visit to perform metabolic measures in fasted condition in basal and during submaximal exercises. The metabolic parameters measured during these tests (e.g. VO2max, power in aerobic and anaerobic thresholds, maximal carbohydrates and lipids oxidation) will be then related to the metagenomic shotgun data obtained in fecal samples.
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
-
-
Brittany
-
Bruz, Brittany, France, 35170
- University Rennes 2 - Laboratory "Movement, Sport and health Sciences"
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- BMI between 18 and 25 kg/m²
- Non-smoker
- Written informed consent
Exclusion Criteria:
- Cardiovascular risks
- Metabolic diseases (e.g. diabetes)
- Use of antibiotics, anti-fungi or anti-parasites in the last 3 months or during participation in the study
- Use of prebiotics and / or probiotics in the form of supplements in the 7 days preceding the start of the study (greater than or equal to 100000000 Colony Forming Units or organisms per day)
- Taking drug treatment for chronic pain management (paracetamol, vasodilator, homeopathy, aspirin greater than 500 mg per day)
- Simultaneous participation in another research involving the human person or having recently participated in another research for which the exclusion period has not been completed.
Study Plan
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Cross-Sectional
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
Low active subjects
No intervention
|
Gas exchanges are measured during all the test on ergocycle until oxygen consumption reach its maximum value
A 25-min submaximal exercise test on ergocycle under fasting condition.
Gas exchanges are measured during all the test.
|
Moderately active subjects
No intervention
|
Gas exchanges are measured during all the test on ergocycle until oxygen consumption reach its maximum value
A 25-min submaximal exercise test on ergocycle under fasting condition.
Gas exchanges are measured during all the test.
|
Elite soccer players
No intervention
|
Gas exchanges are measured during all the test on ergocycle until oxygen consumption reach its maximum value
A 25-min submaximal exercise test on ergocycle under fasting condition.
Gas exchanges are measured during all the test.
|
Elite cyclists
No intervention
|
Gas exchanges are measured during all the test on ergocycle until oxygen consumption reach its maximum value
A 25-min submaximal exercise test on ergocycle under fasting condition.
Gas exchanges are measured during all the test.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Gut microbiota composition
Time Frame: week 1
|
Whole metagenomic sequencing using shotgun approach
|
week 1
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Gut microbiota function
Time Frame: Week 1
|
Whole metagenomic sequencing using shotgun approach
|
Week 1
|
Short chain fatty acids levels in stools
Time Frame: week 1
|
Quantification of gut microbiota metabolites will be performed in frozen stool suspension using Ultra Performance Liquid Chromatography - Mass spectrometry.
|
week 1
|
Amino acids levels in stools
Time Frame: week 1
|
Quantification of gut microbiota metabolites will be performed in frozen stool suspension using Ultra Performance Liquid Chromatography - Mass spectrometry.
|
week 1
|
Maximal oxygen consumption (VO2max)
Time Frame: Week 2
|
Maximal oxygen consumption (ml/min/kg) will be determined during maximal incremental ergocycle test.
Gas exchanges will be measured throughout the test.
|
Week 2
|
Lipid oxidation during physical exercise
Time Frame: week 3
|
A submaximal ergocyle test will be performed under fasting condition.
After 4 min of warm-up (60W), subjects will perform 10 min at 50% VO2max and a second 10 min step at 90% of the anaerobic threshold.
Measurements of respiratory gas exchange will be used to estimate the type and amount of substrate oxidized and the amount of energy produced during exercise (kcal/min).
|
week 3
|
Carbohydrate oxidation during physical exercise
Time Frame: week 3
|
A submaximal ergocyle test will be performed under fasting condition.
After 4 min of warm-up (60W), subjects will perform 10 min at 50% VO2max and a second 10 min step at 90% of the anaerobic threshold.
Measurements of respiratory gas exchange will be used to estimate the type and amount of substrate oxidized and the amount of energy produced during exercise (kcal/min).
|
week 3
|
Collaborators and Investigators
Sponsor
Collaborators
Publications and helpful links
General Publications
- Clarke SF, Murphy EF, O'Sullivan O, Lucey AJ, Humphreys M, Hogan A, Hayes P, O'Reilly M, Jeffery IB, Wood-Martin R, Kerins DM, Quigley E, Ross RP, O'Toole PW, Molloy MG, Falvey E, Shanahan F, Cotter PD. Exercise and associated dietary extremes impact on gut microbial diversity. Gut. 2014 Dec;63(12):1913-20. doi: 10.1136/gutjnl-2013-306541. Epub 2014 Jun 9.
- Nay K, Jollet M, Goustard B, Baati N, Vernus B, Pontones M, Lefeuvre-Orfila L, Bendavid C, Rue O, Mariadassou M, Bonnieu A, Ollendorff V, Lepage P, Derbre F, Koechlin-Ramonatxo C. Gut bacteria are critical for optimal muscle function: a potential link with glucose homeostasis. Am J Physiol Endocrinol Metab. 2019 Jul 1;317(1):E158-E171. doi: 10.1152/ajpendo.00521.2018. Epub 2019 Apr 30.
- Barton W, Penney NC, Cronin O, Garcia-Perez I, Molloy MG, Holmes E, Shanahan F, Cotter PD, O'Sullivan O. The microbiome of professional athletes differs from that of more sedentary subjects in composition and particularly at the functional metabolic level. Gut. 2018 Apr;67(4):625-633. doi: 10.1136/gutjnl-2016-313627. Epub 2017 Mar 30.
- Voorhies AA, Mark Ott C, Mehta S, Pierson DL, Crucian BE, Feiveson A, Oubre CM, Torralba M, Moncera K, Zhang Y, Zurek E, Lorenzi HA. Study of the impact of long-duration space missions at the International Space Station on the astronaut microbiome. Sci Rep. 2019 Jul 9;9(1):9911. doi: 10.1038/s41598-019-46303-8.
- Allen JM, Mailing LJ, Niemiro GM, Moore R, Cook MD, White BA, Holscher HD, Woods JA. Exercise Alters Gut Microbiota Composition and Function in Lean and Obese Humans. Med Sci Sports Exerc. 2018 Apr;50(4):747-757. doi: 10.1249/MSS.0000000000001495.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Estimate)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Other Study ID Numbers
- 2021-A02496-35
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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