CClinicalTrials.gg
CompletedNCT03990259PTSWUpdated Jun 18, 2019

Penyagolosa Trail Saludable Women

An observational study in Physical Exertion, sponsored by Universitat Jaume I. Completed at 1 site in Spain. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2019-06-18.

Sponsored by Universitat Jaume I · Observational

Study type
Observational
Model
Cohort
Time perspective
Cross-sectional
Enrollment
50
Ages
18 Years and older
Sex
All
01

Study summary

This study has as main objective to asses different genetic, biochemical and physiological biomarkers affecting performance and health status in ultraendurance runners according to individual's sex.

Read the detailed description

Ultraendurance races has been shown to impact on several health-related biomarkers, and therefore they may have detrimental effects on runners' health. In this study, we aim to analyze the impact of running a 107,6 km mountain race in ultraendurance runners splitting our sample by individual's sex.

To do this, baseline measurements of the runners have been collected through stress tests and biochemical analyses of blood and urine samples. Indeed, a saliva sample was collected to isolated a genomic DNA sample of each runner.

During the race anthropometrical, ventilatory and strength data was collected in three different moments and after crossing the finish line. Indeed, after completed the ultraendurance mountain race, blood and urine samples were taken at the finish line, as well as 24h and 48h post-race.

02

Conditions studied

  • Physical Exertion

Keywords

  • Ultraendurance
  • Sex differences
  • Performance
  • Genetics
  • Physiological damage
03

In context

Lead sponsor

Universitat Jaume I is the lead sponsor of 79 studies on the registry; 19 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
Yes
Sampling method
Probability sample

Study population

50 ultraendurance amateur runners, 19 females and 31 males.

Inclusion criteria

  • Healthy adults (>18 years old)
  • Volunteers should be finish at least one ultraendurance mountain race (>60km).

Exclusion criteria

Exclusion Criteria:

  • Having heart disease
  • Having kidney disease
  • Taking a medication on an ongoing basis
05

Study design

Observational model
Cohort
Time perspective
Cross-sectional
Enrollment
50 participants (actual)
Target follow-up
6 Weeks
Patient registry
Yes
Biospecimen retention
Samples with dna

Groups and cohorts

  • Male

    The male individuals of the study population

    Other: Running the CSP Mountain Race

  • Female

    The female individuals of the study population

    Other: Running the CSP Mountain Race

Interventions

  • OtherRunning the CSP Mountain Race

    The runners completed a 107,6 km mountain race

06

What researchers measure

Primary outcomes

  1. Change in the biochemical parameters related to kidney injury, dehydration, inflammation, and cardiac damage

    Blood concentration of estradiol, testosterone, progesterone, creatinine, troponin, C-reactive protein, hemoglobin, sodium, potassium, chlorine, iron, and ferritin. Concentration of all these parameters is expressed in mass per volume (i.e. nanograms per milliliter)

    Time frame: 12 hours before the race, 15 minutes after the race, 24 hours after the race and 48 hours after the race

  2. Change in the biochemical parameters related to muscle damage

    Blood concentration of lactate dehydrogenase and creatine kinase. The enzyme concentration is expressed in units per volume (enzyme units per milliliter)

    Time frame: 12 hours before the race, 15 minutes after the race, 24 hours after the race and 48 hours after the race

  3. Change in the biochemical parameters related to immunological response

    Blood concentration of erythrocytes, hematocrit, leukocytes, neutrophils, lymphocytes, monocytes, eosinophils, basophils, and platelet volume. The concentration of each cell type is expressed in number of cells per volume (cells per liter)

    Time frame: 12 hours before the race, 15 minutes after the race, 24 hours after the race and 48 hours after the race

  4. Change in the power level

    Squat Jump (high of the jump measured in centimeters)

    Time frame: 12 hours before the race, 15 minutes after the race

  5. Change in the lung function

    Pulmonary function test by spirometry. The parameters measured are vital capacity (VC), forced vital capacity (FVC), maximal mid-expiratory flow (MEF) and total lung capacity. Outcome data of all these parameters are expressed in liters.

    Time frame: 12 hours before the race, and 15 minutes after the race

  6. Change in the lung function related to time

    Pulmonary function test by spirometry. The parameters measured are forced expiratory volume in 1 second (FEV1) and in 6 seconds (FEV6) and peak expiratory flow (PEF). Outcome data of all these parameters are expressed in liters per second.

    Time frame: 12 hours before the race, and 15 minutes after the race

  7. Change in the Strength level

    Hand grip (pressure in kilograms)

    Time frame: 12 hours before the race, in three moments during the race (after running 33km, 65km and 94 km), and 15 minutes after the race

  8. Change in the Ventilatory Flow

    Ventilatory Flow measurement (liters per minute)

    Time frame: 60 minutes before the race, in three moments during the race (after running 33km, 65km and 94 km), and 15 minutes after the race

  9. Change in the biochemical parameters related to dehydration and kidney injury

    Urine test to measure the concentration of sodium and creatinine, as well as urine density

    Time frame: 60 minutes before the race and 15 minutes after the race

  10. Analysis of tne changes in the Physical activity data

    Physical activity measured by wearing accelerometer devices. Physical activity defined as sedentary, light, moderate, vigorous, very vigorous and extremely vigorous. The aim to wear accelerometers devices is to monitor individuals.

    Time frame: From 9 hours before starting the race to 48 hours after crossing the finish line.

  11. Analysis of the presence or absence of genetic markers related to endurance performance and ability to muscle damage recovery

    Analysis of different polymorphisms in genomic DNA samples, which were isolated from the saliva sample of each participant.

    Time frame: 12 hours before the race

  12. Telomere length, genetic marker related to biological aging

    Analysis of the telomere length in genomic DNA samples, which were isolated from saliva samples of each participant

    Time frame: 12 hours before the race

Secondary outcomes

  1. Self-reported questionnaire about social and health status

    Personal questionnaire asking for social status. Multiple-choice questions. Participants choose one of the different possible answers. Data is encoded as a factor variable with different levels.

    Time frame: One month before the race day

  2. Self-reported questionnaire about training habits

    Personal questionnaire asking for training habits. Multiple-choice questions. Participants choose one of the different possible answers. Data is encoded as a factor variable with different levels.

    Time frame: One month before the race day

  3. Self-reported questionnaire about menstrual cycle (only for females)

    Personal questionnaire asking for training habits. Open-ended questions. Females answer questions regarding menstrual cycle (duration, dates, regularity, quantity of bleeding, pregnancy history, dysmenorrhea).

    Time frame: One month before the race day

  4. Assesment of physical condition by cardiopulmonary test

    Maximal oxygen consumption (milliliters of oxygen used in one minute per kilogram of body weight)

    Time frame: One month before the race day

  5. Analysis of body composition (proportion of body fat, fat-free mass and water) per body areas (trunk, arms and legs)

    Bioimpedance analysis (percentage of body fat, fat-free mass and water)

    Time frame: 12 hours before the race, and 15 minutes after the race,

  6. Heart rate

    Recording the number of contractions of the heart per minute (bpm) by using a heart rate monitor during the race

    Time frame: Through race completion (the time that a runner is performing the 107 kilometers of the race, an average of 25 hours)

  7. Evaluation of effort subjective perception

    Borg ratings of perceived exertion (CR10). Scale with ten levels (0-Nothing at all, and 10-Extremely)

    Time frame: 60 minutes before the race, in three moments during the race (after running 33km, 65km and 94 km), and 15 minutes after the race

  8. Evaluation of muscle damage subjective perception per body areas

    Evaluation of perceived muscle damage in a 10-level scale. Scale with ten levels (0-Nothing at all, and 10-Extremely)

    Time frame: 12 hours before the race, 15 minutes after the race, and 48 hours after the race

  9. Change in the body mass

    Body mass measurement (weight in kilograms)

    Time frame: 60 minutes before the race, in three moments during the race (after running 33km, 65km and 94 km), and 15 minutes after the race,

07

Study locations

1 site
  • Universitat Jaume I
    Castellón De La Plana, 12071, Spain
08

References and documents

Publications

  • Cheuvront SN, Carter R, Deruisseau KC, Moffatt RJ. Running performance differences between men and women:an update. Sports Med. 2005;35(12):1017-24. doi: 10.2165/00007256-200535120-00002. PubMed 16336006 ↗
  • Eichenberger E, Knechtle B, Rust CA, Rosemann T, Lepers R. Age and sex interactions in mountain ultramarathon running - the Swiss Alpine Marathon. Open Access J Sports Med. 2012 Jul 31;3:73-80. doi: 10.2147/OAJSM.S33836. eCollection 2012. PubMed 24198590 ↗
  • Gimenez P, Kerherve H, Messonnier LA, Feasson L, Millet GY. Changes in the energy cost of running during a 24-h treadmill exercise. Med Sci Sports Exerc. 2013 Sep;45(9):1807-13. doi: 10.1249/MSS.0b013e318292c0ec. PubMed 23524515 ↗
  • Hernando C, Hernando C, Collado EJ, Panizo N, Martinez-Navarro I, Hernando B. Establishing cut-points for physical activity classification using triaxial accelerometer in middle-aged recreational marathoners. PLoS One. 2018 Aug 29;13(8):e0202815. doi: 10.1371/journal.pone.0202815. eCollection 2018. PubMed 30157271 ↗
  • Joyner MJ. Physiological limits to endurance exercise performance: influence of sex. J Physiol. 2017 May 1;595(9):2949-2954. doi: 10.1113/JP272268. Epub 2017 Feb 9. PubMed 28028816 ↗
  • Knechtle B, Knechtle P, Rosemann T, Lepers R. Personal best marathon time and longest training run, not anthropometry, predict performance in recreational 24-hour ultrarunners. J Strength Cond Res. 2011 Aug;25(8):2212-8. doi: 10.1519/JSC.0b013e3181f6b0c7. PubMed 21642857 ↗
  • Knechtle B, Knechtle P, Wirth A, Alexander Rust C, Rosemann T. A faster running speed is associated with a greater body weight loss in 100-km ultra-marathoners. J Sports Sci. 2012;30(11):1131-40. doi: 10.1080/02640414.2012.692479. Epub 2012 Jun 6. PubMed 22668199 ↗
  • Ahmetov I, Kulemin N, Popov D, Naumov V, Akimov E, Bravy Y, Egorova E, Galeeva A, Generozov E, Kostryukova E, Larin A, Mustafina Lj, Ospanova E, Pavlenko A, Starnes L, Zmijewski P, Alexeev D, Vinogradova O, Govorun V. Genome-wide association study identifies three novel genetic markers associated with elite endurance performance. Biol Sport. 2015 Mar;32(1):3-9. doi: 10.5604/20831862.1124568. Epub 2014 Oct 21. PubMed 25729143 ↗
  • Borghini A, Giardini G, Tonacci A, Mastorci F, Mercuri A, Mrakic-Sposta S, Moretti S, Andreassi MG, Pratali L. Chronic and acute effects of endurance training on telomere length. Mutagenesis. 2015 Sep;30(5):711-6. doi: 10.1093/mutage/gev038. Epub 2015 May 22. Erratum In: Mutagenesis. 2016 Mar;31(2):231. doi: 10.1093/mutage/gew006. PubMed 26001753 ↗
  • Martinez-Navarro I, Aparicio I, Priego-Quesada JI, Perez-Soriano P, Collado E, Hernando B, Hernando C. Effects of wearing a full body compression garment during recovery from an ultra-trail race. Eur J Sport Sci. 2021 Jun;21(6):811-818. doi: 10.1080/17461391.2020.1783369. Epub 2020 Jun 30. PubMed 32538286 ↗

Individual participant data

Plan to share: No — It is not planned to share participant's data

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jun 18, 2019, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT03990259
Lead sponsor
Universitat Jaume I
Collaborators
Club Deportivo Marató i Mitja Castelló-Penyagolosa, Fundación Vithas-Nisa, Hospital Vithas-Nisa 9 de Octubre
Responsible party
Sponsor
First posted
Jun 18, 2019
Start date
Feb 25, 2019
Primary completion
Apr 4, 2019
Completion
Apr 16, 2019
Last update
Jun 18, 2019

Study contacts

Carlos Hernando, PhD
principal investigator · Universitat Jaume I

Oversight

FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is completed, as verified in Jun 2019. You cannot join it, but the record below documents what was studied.

Follow this study

Get an email when the registry record changes — status, dates, results — or when someone posts here.

Sign in to follow

Discussion

Questions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.

Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.

Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.

Start the discussion