Metabolomics Clinical Trial
— PROTEOMETOfficial title:
Evaluation of the Relationship Between Training Load and the Levels of Lactate and Other Metabolites Analyzed in Blood and Saliva Samples Using Metabolomic and Proteomic Techniques in Federated Basketball Players: Quasi-experimental Study
NCT number | NCT06365320 |
Other study ID # | PROTEOMET |
Secondary ID | |
Status | Not yet recruiting |
Phase | N/A |
First received | |
Last updated | |
Start date | April 2024 |
Est. completion date | July 2024 |
Physical exercise induces numerous changes in the body in a complex signalling network caused by or in response to increased metabolic activity of contracting skeletal muscles. The application of omics analytical techniques such as proteomics and metabolomics in the field of sport allows us to understand how the human body responds to exercise and how sports results can be improved by optimising nutrition and training. Both omics techniques offer a quantitative measurement of the metabolic profiles associated with exercise and are able to identify metabolic signatures of athletes from different sports disciplines. Basketball is a high-intensity exercise modality interspersed with low-intensity. The performance requirements of basketball include aerobic and anaerobic metabolism, with anaerobic metabolism being considered the main energy system. Therefore, basketball players need great athletic ability to produce a successful performance during competition. For optimal sports performance it is important to adjust the training load, i.e. the degree of effort that the player can withstand in a single training session. Coaches require effective and objective load monitoring tools that allow them to make decisions about training plans based on the needs of each player. Microsampling systems emerge as an alternative to venipuncture by facilitating self-sampling, which can be carried out outside healthcare centres, in a comfortable and precise way from a small finger prick that the user can perform. These systems are less expensive and can be effective in measuring the levels of glucose metabolism products, such as lactate, through the application of metabolomics and proteomics. On the other hand, the use of non-invasive methods of measuring lactate levels is becoming increasingly popular in sports medicine. The use of saliva as an alternative fluid to the blood shows promise for identifying the concentrations of metabolites that occur during and after sports training.
Status | Not yet recruiting |
Enrollment | 70 |
Est. completion date | July 2024 |
Est. primary completion date | July 2024 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years to 40 Years |
Eligibility | Inclusion Criteria: - Men and women, active players of the Catalan Basketball Federation and the Spanish Basketball Federation between 18 and 40 years old (both included). - Sign the informed consent. Exclusion Criteria: - Present any metabolic disorder that may interfere with the objectives of the study (high blood pressure, diabetes, hypercholesterolemia or obesity; Body Mass Index (BMI) values = 35 Kg/m2. - Suffer from disorders of glucose metabolism that may alter lactate synthesis, such as lactic acidosis, hyperlactatemia, or other metabolic acidosis. - Taking any type of medication that may alter metabolite or lactate levels. - Having belonephobia (phobia of needles). - Take ergogenic aids or supplements based on sucrose or glucose polymers before, during, or after training. - Being a smoker. - Being pregnant. - Breastfeeding. |
Country | Name | City | State |
---|---|---|---|
Spain | Fundació Eurecat, Center for Omic Sciences | Reus | Tarragona |
Lead Sponsor | Collaborator |
---|---|
Fundació Eurecat | University Rovira i Virgili |
Spain,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Correlation between blood lactate levels and the subjective sensation of perceived effort | Lactate concentration (µM) measured in capillary blood pre- and post- training. Four drops of capillary blood will be collected pre- and post-training by means of a puncture with a retractable lancet on the index, middle or ring finger, and deposited on a dried blood spot (DBS) "HemaXis DB10" card for analysis.
The subjective sensation of perceived effort will be assessed with the Perceived Exertion Index (RPE) measured post-training. This tool is used to monitor perceived effort during sports practice. It consists of a graduated scale from 0 to 10 where 0 is rest and 10 is maximum perceived effort. |
Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Change in saliva lactate levels | A 15 mL Falcon tube will be used to collect the saliva sample by passive salivation. The lactate concentration in saliva will be analysed using the GC-qTOF technique. | Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Change in blood lactate levels | Lactate concentration (µM) measured in capillary blood collected in a dried blood spot card (DBS). The dried blood samples will be shipped to the analytical laboratory and analysed using combined analysis of liquid chromatography (UHPLC) coupled to triple quadrupole mass spectrometry (QqQ/MS) or quadrupole-time-of-flight mass spectrometry (qTOF/MS). | Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Change in levels of lipid metabolic markers determined in capillary blood samples | Lipid metabolic marker levels (described below) will be measured in capillary blood samples using the same DBS device as in the case of the primary outcome. Liquid chromatography (UHPLC 1290 Infinity II Series, Agilent Technologies) coupled to quadrupole - time of flight mass spectrometry (qTOF/MS 6546 Series, Agilent Technologies) will be used as metabolomic techniques.
Measured lipids: phosphatidylcholines, lysophosphatidylcholines, sphingomyelins, diglycerides, triglycerides, cholesterol esters, phosphatidylethanolamine and lysophosphatidylethanolamines. All lipid metabolic markers in capillary bood will be reported in micromol (µM). |
Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Change in levels of other lipid metabolic markers determined in capillary blood samples | Lipid metabolic marker levels (described below) will be measured in capillary blood samples using the same DBS device as in the case of the primary outcome. Liquid chromatography (UHPLC 1290 Infinity II Series, Agilent Technologies) coupled to triple quadrupole mass spectrometry (QqQ/MS 6490 Series, Agilent Technologies) will be used as metabolomic techniques.
Measured lipids: oxylipins, non-esterified fatty acids, hormones, and acetylcarnitines. All lipid metabolic markers in capillary blood will be reported in micromol (µM). |
Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Change in levels of polar metabolites determined in capillary blood samples | Polar metabolites (described below) will be measured in capillary blood samples using the same DBS device as in the case of the primary outcome. Gas chromatography coupled to quadrupole - time of flight mass spectrometry (GC-qTOF 7200 Series, Agilent Technologies) will be used as metabolomic techniques.
Measured polar metabolites: organic acids, amino acids, compounds related to energy metabolism and sugars. All polar metabolites in capillary blood will be reported in micromol (µM). |
Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Change in levels of lipid metabolic markers determined in saliva samples | Lipid metabolic markers (described below) will be measured in saliva samples using a collection tube (15 mL Falcon tube). Gas chromatography coupled to quadrupole - time of flight mass spectrometry (GC-qTOF 7200 Series, Agilent Technologies) will be used as metabolomic techniques.
Measured lipids: phosphatidylcholines, lysophosphatidylcholines, sphingomyelins, diglycerides, triglycerides, cholesterol esters, phosphatidylethanolamine and lysophosphatidylethanolamines. All lipid metabolic markers in saliva will be reported in micromol (µM). |
Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Change in levels of other lipid metabolic markers determined in saliva samples | Lipid metabolic marker levels (described below) will be measured in saliva samples using a collection tube (15 mL Falcon tube). Liquid chromatography (UHPLC 1290 Infinity II Series, Agilent Technologies) coupled to triple quadrupole mass spectrometry (QqQ/MS 6490 Series, Agilent Technologies) will be used as metabolomic techniques.
Measured lipids: oxylipins, non-esterified fatty acids, hormones, and acetylcarnitines. All lipid metabolic markers in saliva will be reported in micromol (µM). |
Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Change in levels of polar metabolites determined in saliva samples | Polar metabolites (described below) will be measured in saliva samples using a collection tube (15 mL Falcon tube). Gas chromatography coupled to quadrupole - time of flight mass spectrometry (GC-qTOF 7200 Series, Agilent Technologies) will be used as metabolomic techniques.
Measured polar metabolites: organic acids, amino acids, compounds related to energy metabolism and sugars. All polar metabolites in saliva will be reported in micromol (µM). |
Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Change in levels of proteomic markers determined in capillary blood samples | Proteomic marker levels will be determined using the same DBS device as in the case of the primary outcome. The proteins in blood will be digested with trypsin to obtain peptides. The peptides will be analyzed by liquid nanochromatography coupled to mass spectrometry. The identification of the proteins will be carried out using the UniProt Homo Sapiens database using the Proteome Discoverer software (ThermoFisher Scientific).
All proteomic markers in capillary blood will be reported in arbitrary units as a relative unit of measurement. |
Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Change in levels of proteomic markers determined in saliva samples | The proteins in saliva will be digested with trypsin to obtain peptides. The peptides will be analyzed by liquid nanochromatography coupled to mass spectrometry. The identification of the proteins will be carried out using the UniProt Homo Sapiens database using the Proteome Discoverer software (ThermoFisher Scientific).
All proteomic markers in saliva will be reported in arbitrary units as a relative unit of measurement. |
Pre-training (baseline) and post-training (immediately after the training) | |
Secondary | Pittsburgh Sleep Quality Index | It is a validated scale that measures the usual sleep habits during the past month. It consists of 7 areas: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. It contains a total of 19 items, grouped into 10 questions where each of the areas evaluated is scored between 0 and 3. The scores from the seven areas are finally added up to give an overall score. The component scores are summed to produce a global score (range 0 to 21). Higher scores indicate worse sleep quality. | Pre-training (baseline) | |
Secondary | Heart rate variations | It will be measured, in bpm, in real time throughout training using an optical heart rate sensor (Polar Verity Sense) fitted to the left arm of each player with a textile elastic armband. The device monitors heart rate in real time. The average heart rate will be calculated with the data collected throughout the training. | During the training | |
Secondary | Sociodemographic data: age and birth date | Age will be recorded in years, and birth date in the format DD/MM/YYYY. It will be recorded in the case report form. | Pre-training (baseline) | |
Secondary | Sociodemographic data: sex | Sex will be recorded as male or female in the case report form. | Pre-training (baseline) | |
Secondary | Lifestyle data: weekly training load | Weekly training load will be recorded as hours/week in the case report form. | Pre-training (baseline) | |
Secondary | Lifestyle data: playing position | Playing position, will be recorded as base, shooting guard, small forward, power forward or center in the case report form. | Pre-training (baseline) | |
Secondary | Clinical data: use of supplementation | Use of supplementation will be recorded in the case report form. | Pre-training (baseline) | |
Secondary | Clinical data: use of medication | Use of medication will be recorded in the case report form. | Pre-training (baseline) | |
Secondary | Clinical data: previous muscle injuries | Previous muscle injuries will be recorded in the case report form. | Pre-training (baseline) | |
Secondary | Physiological data | Physiological data, including presence of current menstruation in women, will be recorded in the case report form. | Pre-training (baseline) | |
Secondary | Anthropometric data: weight | Weight will be measured in kg with a portable digital scale (Beuer b180) and recorded in the case report form. | Pre-training (baseline) | |
Secondary | Anthropometric data: height | Height will be measured in cm with a portable stadiometer and recorded in the case report form. | Pre-training (baseline) | |
Secondary | Anthropometric data: body mass index | Body mass index will be recorded in kg/m² in the case report form. | Pre-training (baseline) | |
Secondary | Anthropometric data: fat mass percentage | Fat mass percentage (%) will be measured with a portable digital scale (Beuer b180) and recorded in the case report form. | Pre-training (baseline) | |
Secondary | Anthropometric data: muscle mass percentage | Muscle mass percentage (%) will be measured with a portable digital scale (Beuer b180) and recorded in the case report form. | Pre-training (baseline) |
Status | Clinical Trial | Phase | |
---|---|---|---|
Active, not recruiting |
NCT04807998 -
Risk Factors for Pediatric Emergence Agitation and Analysis of Serum or Urine Metabonomics in Children With Agitation
|
||
Recruiting |
NCT03810768 -
Metabolomics Study on Postoperative Intensive Care Acquired Muscle Weakness
|
||
Recruiting |
NCT05582824 -
Lactate Metabolism in the Hypoperfused Critically Ill
|
||
Recruiting |
NCT06094439 -
Targeted Metabolomics and Spent Embryo Culture Medium
|
||
Not yet recruiting |
NCT05834426 -
Omic Technologies Applied to the Study of B-cell Lymphoma for the Discovery of Diagnostic and Prognosis Biomarkers
|
||
Terminated |
NCT02948114 -
The Effect of Feeding Infant Formula Containing Prebiotics and/or Probiotics
|
N/A | |
Recruiting |
NCT05891886 -
Supplemental Oxygen in Pulmonary Embolism (SO-PE)
|
Early Phase 1 | |
Completed |
NCT04042519 -
The Research of Metabolomics on COPD
|
||
Completed |
NCT03450746 -
Metabolic and Physiological Changes During Minor Orthopaedic Surgery in Otherwise Healthy Patients
|
||
Recruiting |
NCT03742843 -
A Multi-omics Study of Adenomyosis
|
||
Recruiting |
NCT03742856 -
A Multi-omics Study of Epithelial Ovarian Cancer
|
||
Terminated |
NCT02948192 -
The Reproductive Microbiome & Perinatal Health Outcomes
|
||
Recruiting |
NCT05243173 -
Biomarkers of Response to Systemic Treatments in FH-deficient RCC
|
||
Completed |
NCT02145572 -
Metabolomic Profiling in Adolescents With Obesity and Diabetes
|
||
Active, not recruiting |
NCT04781036 -
Foot-skin Microbiome and Metabolomics of Pitted Keratolysis
|
N/A | |
Completed |
NCT04137042 -
Metabolomics of Intraoperative Saline and Balanced Crystalloid Infusion
|
N/A | |
Completed |
NCT03819959 -
Metabolomics Study on Intensive Care Acquired Muscle Weakness in Polytrauma
|
||
Completed |
NCT01436383 -
Oxidative Stress in Hypobaric Hypoxia
|
N/A | |
Active, not recruiting |
NCT03137628 -
Effect of General Anesthesia and Mechanical Ventilation on Plasma Metabolite in Patient With Colorectal Cancer Resection
|
N/A | |
Recruiting |
NCT06102655 -
Effect and Mechanism of Jiajian Guishen Formulation on Premature Ovarian Insufficiency Based on Metabolomics
|
Early Phase 1 |