CClinicalTrials.gg
Status unknownNCT03279380GE-EXUpdated Sep 12, 2017

Gene-Exercise Interactions in Athletes

An interventional study of SNP and High Intensity Interval Training (HIIT) in Exercise, sponsored by University of Primorska. Status unknown at 1 site in Slovenia. Open to participants aged 18 Years to 40 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2017-09-12.

Sponsored by University of Primorska · Not applicable, Interventional, and Treatment

The sponsor has not verified this record recently (last verified Sep 2017), so the status shown — last known as Recruiting — may be out of date.
Phase
Not applicable
Study type
Interventional
Enrollment
500
Allocation
Randomized
Ages
18 Years to 40 Years
Sex
All
01

Study summary

Athlete status is a heritable trait that could be explained with a number of potentially important DNA polymorphisms contributing to predisposition to success in certain types of sport.

The first aim of the study is to determine the genetic profile of Slovenian athletes. The associations of 30 common gene polymorphisms with aerobic and anaerobic athlete status will be investigated as a single and polygenic profile.

The second aim is to investigate the impact of the genetic variants contributing to different acute response to low vs. high intensity exercise. Physiological and biochemical measurements will be carried out. Variability in physiological adaptation in response to exercise will provides an opportunity to study the relationship between the molecular response to exercise and the extent of physiological changes in athletes. Currently, it is not yet clear whether different genetic variant associated with exercise responses remains uniform, with different exercise intensities, structure and duration of exercise.

Read the detailed description

Slovenian athletes (n = 300; 18-40 years) of regional or national competitive standard will be recruited from the endurance oriented and power oriented sports disciplines. Healthy unrelated individuals without any competitive sport experience will serve as controls (n= 200; 18-40 years). After completing the questionnaire (for athletes: covering demographics, geographic ancestry, sports classification, discipline, and history, as well as frequency and volume of training; for control group: demographics, geographic ancestry habits of daily living), genotyping analyses will be performed. The athletes and controls will be genotyped for 30 candidate gene polymorphisms considered likely to influence endurance performance. Molecular genetic analysis will be performed with DNA samples obtained from the capillary whole blood. Genotyping for 30 gene polymorphisms will be performed by Real-Time PCR on LightCycler® 96 Instrument (Roche) and KASP (Kompetitive Allele Specific PCR) genotyping technology.

In addition, 40 athletes with endurance genetic variant will be selected to participate in the acute exercise study. In order to investigate the acute effects of low and high intensity exercise the concentration of circulating myokines will be measured.

Three distinct experimental sessions scheduled 96 h apart, at the same time of the day and in random order will be applied to this sub-group of athletes.

In the first session, aerobic power will be determined using an incremental test to exhaustion on a cycling ergometer (Velodyn, Racermate ™, USA). Oxygen consumption (VO2) will be determined breath by breath using a Quark gas analysis system (Quark, Cosmed, Rim, Italy). The interventions during the other two experimental session will consist of cycling exercise with continuous 60 min cycling at 50% PPO (low intensity), and 8 x 5 min at 80% PPO (between intervals 1.5 min at 75 W) exercise (high intensity).

The participants will be asked to follow the prescribed diet regime, to avoid the intake of alcohol and to not perform any physical activity in the 24 hours prior to the experimental sessions. The experimental sessions will be performed from 8 to 11 am, in random order and scheduled 96 h apart.

Before each intervention, the individuals will remain seated in the laboratory for a period of 20 minutes with a room temperature between 22-24ºC. During this period, resting blood samples will be collected. Two more samples of blood will be collected, immediately post-exercise intervention and 2h post-exercise. Venous blood will be collected into EDTA tubes, centrifuge at 2500-3000g for 20 minutes, and a separate plasma will be stored at -80 ° C for the further analysis.

The quantification of biomarkers will be done using the MAGPIX® system, magnetic bead-based multi-analyte panels and MILLIPLEX® Analyst 5.1 software (MAGPIX®, Merck Millipore). For the myokine analysis a commercial kit HMYOMAG-56K will be used.

Genotype distribution and allele frequencies between each of the two groups of athletes (endurance and power) and controls will be compared using χ2 tests. Endurance genotype score (EGS) will be construct. First, each genotype will be scored within each polymorphism. Thus, a genotype score (GS) of 2, 1 and 0 to each individual genotype theoretically associated to highest, medium or lowest potential of endurance phenotypes will be assigned. Second, the GS of each single genotype will be summed ∑(i=1)\^nSNPi. Third, the EGS will be transformed to a 0-100 scale for easier interpretation, as follows: EGS=(100/2n)∑_(i=1)\^nSNPi. An EGS of 100 represents an 'optimal' polygenic profile for endurance athlete-that is, that all GS are 2. In contrast, an EGS of 0 represents the 'worst' possible profile for endurance athlete, that is, all GS are 0. The mean the EGS obtained in the three study groups will be calculated. The EGS of endurance, power athletes and non-athletes (controls) will be compared with one-way analysis of variance (ANOVA), and Tukey post hoc test will be used for between-group comparisons. We will also performed ANOVA to compare the EGS between elite- and national-level athletes within each group of endurance and power athletes. Data normality was verified through an exploratory analysis using the Shapiro-Wilk test. Two-way mixed ANOVA will be applied to check the main interaction effects of time by exercise session (time*session) and of time (time) on myokine plasma concentration. For statistically significant effects, a post-hoc Tukey test will be adopted for multiple comparisons. All values will be expressed as mean and standard deviation (SD). P values of \<0.05 will be considered statistically significant. Bonferroni's correction for multiple testing will be performed by multiplying the P value with the number of tests where appropriate. Statistical analyses will be carried out using the SPSS program, version 21 (Chicago, IL).

02

Conditions studied

  • Exercise

Keywords

  • genetic polymorphism
  • sport performance
  • myokines
03

Who can participate

Ages eligible
18 Years to 40 Years
Sexes eligible
All
Accepts healthy volunteers
Yes

Inclusion criteria

  • Slovenian residents
  • Healthy individuals
  • endurance athlete (categorization: world, international, national or youth class)
  • power athlete (categorization: world, international, national or youth class)

Exclusion criteria

Exclusion Criteria:

  • corticosteroids
  • hormone therapy
04

Study design

Phase
Not applicable
Primary purpose
Treatment
Allocation
Randomized
Intervention model
Crossover assignment
Masking
Single (Outcomes assessor)
Enrollment
500 participants (estimated)

Study arms

  • Experimental
    Single-nucleotide polymorphisms (SNPs)

    In the first part the Case-control study design will be used to estimate the association between multiple single-nucleotide polymorphisms (SNPs) and the endurance/power athlete status.

    Other: SNP

  • Active comparator
    High Intensity Interval Training (HIIT)

    High intensity interval exercise on the cycling ergometer (Velodyn, Racermate ™, USA). Protocol: 8 x 5 min at 80% PPO (between intervals 1.5 min at 75 W). Baseline measurements will include the V̇O2peak test and peak power output. Monitoring of physiological responses with spirometry and analysis of expired air (oxygen and carbon dioxide output) (Quark, Cosmed, Rim, Italy).

    Other: High Intensity Interval Training (HIIT)

  • Active comparator
    Low Intensity Continuous Training

    Low intensity continuous exercise on the cycling ergometer (Velodyn, Racermate ™, USA). Protocol: continuous 60 min cycling at 50% PPO. Baseline measurements will include the V̇o2peak test and peak power output. Monitoring of physiological responses with spirometry and analysis of expired air (oxygen and carbon dioxide output) (Quark, Cosmed, Rim, Italy).

    Other: Low Intensity Continuous Training

Interventions

  • OtherSNP

    Screening 150 endurance, 150 power athletes, and 200 healthy control individuals for genetic variant associated to sport performance.

  • OtherHigh Intensity Interval Training (HIIT)

    The subgroup (n = 40) of the athletes will participate in the acute exercises (HIIT Training). In order to investigate the acute effects of the exercise the concentration of circulating myokines will be measured (before, post-exercise and 2 h post-exercise). All participants will visit the laboratory at least three times, scheduled 96 h apart. Exercise will be carried out on the cycling ergometer with simultaneous monitoring of physiological responses. Participants will be asked to follow the prescribed diet regime and not to perform any physical activities / trainings the day before measurements. Baseline measurements will include the V̇o 2 peak test. Then the participants will be randomly divided into two groups. The specific acute exercises will be accomplish in the next two visits.

  • OtherLow Intensity Continuous Training

    The subgroup (n = 40) of the athletes will participate in the acute exercises (LIT Continuous Training). In order to investigate the acute effects of the exercise the concentration of circulating myokines will be measured (before, post-exercise and 2 h post-exercise). All participants will visit the laboratory three times, scheduled 96 h apart. Exercise will be carried out on the cycling ergometer with simultaneous monitoring of physiological responses. Participants will be asked to follow the prescribed diet regime and not to perform any physical activities / trainings the day before measurements. Baseline measurements will include the V̇o 2 peak test. Then the participants will be randomly divided into two groups. The specific acute exercises will be accomplish in the next two visits.

05

What researchers measure

Primary outcomes

  1. Genetic markers associated with endurance performance

    Comparing the frequencies of the alleles of the candidate genes between endurance athletes and opposite cohorts (controls, power athletes).

    Time frame: 12 weeks

Secondary outcomes

  1. Concentration of circulating myokines

    The effect of exercise on expression of myokine between different exercise (high and low intensity exercise).

    Time frame: 12 weeks

06

Study locations

1 of 1 sites recruiting
  • University of Primorska, Faculty Health Sciences AND Faculty of Mathematics, Natural Sciences and Information Technologies
    Koper, 6000, Slovenia
    Recruiting
07

References and documents

Publications

  • Ahmetov II, Williams AG, Popov DV, Lyubaeva EV, Hakimullina AM, Fedotovskaya ON, Mozhayskaya IA, Vinogradova OL, Astratenkova IV, Montgomery HE, Rogozkin VA. The combined impact of metabolic gene polymorphisms on elite endurance athlete status and related phenotypes. Hum Genet. 2009 Dec;126(6):751-61. doi: 10.1007/s00439-009-0728-4. PubMed 19653005 ↗
  • Ahmetov II, Fedotovskaya ON. Current Progress in Sports Genomics. Adv Clin Chem. 2015;70:247-314. doi: 10.1016/bs.acc.2015.03.003. Epub 2015 Apr 11. PubMed 26231489 ↗
  • Booth FW, Neufer PD (2012) Exercise genomics and proteomics. In: Farrrell PA, Joyner MJ, Caiozzo VJ, editors. ACSM's Advanced Exercise Physiology. Baltimore, MD: Lippincott Williams & Wilkins. pp. 669-698
  • Bouchard C, Sarzynski MA, Rice TK, Kraus WE, Church TS, Sung YJ, Rao DC, Rankinen T. Genomic predictors of the maximal O(2) uptake response to standardized exercise training programs. J Appl Physiol (1985). 2011 May;110(5):1160-70. doi: 10.1152/japplphysiol.00973.2010. Epub 2010 Dec 23. PubMed 21183627 ↗
  • Bouchard C. Genomic predictors of trainability. Exp Physiol. 2012 Mar;97(3):347-52. doi: 10.1113/expphysiol.2011.058735. Epub 2011 Oct 3. PubMed 21967902 ↗
  • De Moor MH, Spector TD, Cherkas LF, Falchi M, Hottenga JJ, Boomsma DI, De Geus EJ. Genome-wide linkage scan for athlete status in 700 British female DZ twin pairs. Twin Res Hum Genet. 2007 Dec;10(6):812-20. doi: 10.1375/twin.10.6.812. PubMed 18179392 ↗
  • Egan B, O'Connor PL, Zierath JR, O'Gorman DJ. Time course analysis reveals gene-specific transcript and protein kinetics of adaptation to short-term aerobic exercise training in human skeletal muscle. PLoS One. 2013 Sep 12;8(9):e74098. doi: 10.1371/journal.pone.0074098. eCollection 2013. PubMed 24069271 ↗
  • Eynon N, Ruiz JR, Meckel Y, Moran M, Lucia A. Mitochondrial biogenesis related endurance genotype score and sports performance in athletes. Mitochondrion. 2011 Jan;11(1):64-9. doi: 10.1016/j.mito.2010.07.004. Epub 2010 Jul 18. PubMed 20647061 ↗
  • Pedersen BK. Muscles and their myokines. J Exp Biol. 2011 Jan 15;214(Pt 2):337-46. doi: 10.1242/jeb.048074. PubMed 21177953 ↗
  • Pitsiladis YP, Tanaka M, Eynon N, Bouchard C, North KN, Williams AG, Collins M, Moran CN, Britton SL, Fuku N, Ashley EA, Klissouras V, Lucia A, Ahmetov II, de Geus E, Alsayrafi M; Athlome Project Consortium. Athlome Project Consortium: a concerted effort to discover genomic and other "omic" markers of athletic performance. Physiol Genomics. 2016 Mar;48(3):183-90. doi: 10.1152/physiolgenomics.00105.2015. Epub 2015 Dec 29. PubMed 26715623 ↗
  • Rankinen T, Fuku N, Wolfarth B, Wang G, Sarzynski MA, Alexeev DG, Ahmetov II, Boulay MR, Cieszczyk P, Eynon N, Filipenko ML, Garton FC, Generozov EV, Govorun VM, Houweling PJ, Kawahara T, Kostryukova ES, Kulemin NA, Larin AK, Maciejewska-Karlowska A, Miyachi M, Muniesa CA, Murakami H, Ospanova EA, Padmanabhan S, Pavlenko AV, Pyankova ON, Santiago C, Sawczuk M, Scott RA, Uyba VV, Yvert T, Perusse L, Ghosh S, Rauramaa R, North KN, Lucia A, Pitsiladis Y, Bouchard C. No Evidence of a Common DNA Variant Profile Specific to World Class Endurance Athletes. PLoS One. 2016 Jan 29;11(1):e0147330. doi: 10.1371/journal.pone.0147330. eCollection 2016. PubMed 26824906 ↗
  • Timmons JA, Knudsen S, Rankinen T, Koch LG, Sarzynski M, Jensen T, Keller P, Scheele C, Vollaard NB, Nielsen S, Akerstrom T, MacDougald OA, Jansson E, Greenhaff PL, Tarnopolsky MA, van Loon LJ, Pedersen BK, Sundberg CJ, Wahlestedt C, Britton SL, Bouchard C. Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans. J Appl Physiol (1985). 2010 Jun;108(6):1487-96. doi: 10.1152/japplphysiol.01295.2009. Epub 2010 Feb 4. PubMed 20133430 ↗
  • Trayhurn P, Drevon CA, Eckel J. Secreted proteins from adipose tissue and skeletal muscle - adipokines, myokines and adipose/muscle cross-talk. Arch Physiol Biochem. 2011 May;117(2):47-56. doi: 10.3109/13813455.2010.535835. Epub 2010 Dec 15. PubMed 21158485 ↗
  • Yang Y, Creer A, Jemiolo B, Trappe S. Time course of myogenic and metabolic gene expression in response to acute exercise in human skeletal muscle. J Appl Physiol (1985). 2005 May;98(5):1745-52. doi: 10.1152/japplphysiol.01185.2004. Epub 2004 Dec 23. PubMed 15618316 ↗

Individual participant data

Plan to share: No

08

Registry details

Key details

Study ID
NCT03279380
Lead sponsor
University of Primorska
Collaborators
S2P, Science to Practice, Ltd.
Responsible party
Nejc Sarabon (Assoc. Prof. Dr. Sc., University of Primorska) — Principal investigator
First posted
Sep 12, 2017
Start date
Oct 1, 2017 (estimated)
Primary completion
Dec 31, 2017 (estimated)
Completion
Jun 30, 2018 (estimated)
Last update
Sep 12, 2017

Study contacts

Felicita Urzi, MSc
Contact
felicita.urzi@upr.si
0038631801692
Elena Buzan, PhD
Contact
elena.buzan@upr.si
0038641350957
Nejc Sarabon, PhD
principal investigator · University of Primorska, Faculty of Health Studies, Izola, Slovenia

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
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