title: Innovative approach to interpret the variability of biomarkers after ultra-endurance exercise: the multifactorial analysis.
abstract: OBJECTIVE
  We assessed the inter-relationship that exists between variations of different biochemical and hematological parameters following strenuous endurance exercise in Ironmen by using multiple factor analysis (MFA). MFA was used to estimate the associations among groups of parameters in order to identify concurrent changes in many different biochemical variables.
  
  
  METHODS
  In total, 14 Ironman athletes were followed before and early after a race. MFA was applied to the parameters that showed a significant variation after the race, as we previously described in detail. Specifically, MFA standardizes data in each group and calculates the global axes (GAs), which are the linear combination of original parameters that maximize the global data variance.
  
  
  RESULTS
  MFA identified three global axes (GAs) as significant, explaining approximately 62% of the global data variance. The first GA contained NT-proBNP, IL-1ra, IL-6, IL-8 and the oxidative index. The second and third GAs included calcium, creatinine, potassium, uric acid, hemoglobin, hematocrit and glucose. Analysis of the first two GAs showed that changes in the oxidative index were associated with variations in IL-8 and NT-proBNP.
  
  
  CONCLUSIONS
  Among all the variables considered, MFA evidenced a close relationship between variations in oxidative stress, IL-8 and NT-proBNP, which may have a meaning in the mechanisms related to the physiological response after strenuous acute exercise.
authors.affiliation: CNR Clinical Physiology Institute, Pisa, Italy.
authors.forename: Cristina
authors.initials: C
authors.lastname: Vassalle
authors.forename: Paolo
authors.initials: P
authors.lastname: Piaggi
authors.forename: Nathan
authors.initials: N
authors.lastname: Weltman
authors.forename: Concetta
authors.initials: C
authors.lastname: Prontera
authors.forename: Erika
authors.initials: E
authors.lastname: Garbella
authors.forename: Danilo
authors.initials: D
authors.lastname: Menicucci
authors.forename: Valter
authors.initials: V
authors.lastname: Lubrano
authors.forename: Andrea
authors.initials: A
authors.lastname: Piarulli
authors.forename: Cinzia
authors.initials: C
authors.lastname: Castagnini
authors.forename: Mirko
authors.initials: M
authors.lastname: Passera
authors.forename: Silvia
authors.initials: S
authors.lastname: Pellegrini
authors.forename: Maria Rosa
authors.initials: MR
authors.lastname: Metelli
authors.forename: Remo
authors.initials: R
authors.lastname: Bedini
authors.forename: Angelo
authors.initials: A
authors.lastname: Gemignani
authors.forename: Alessandro
authors.initials: A
authors.lastname: Pingitore
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism; D002118:Calcium / Q000097:blood; D003404:Creatinine / Q000097:blood; D016207:Cytokines / Q000097:blood*; D005260:Female; D006400:Hematocrit; D006454:Hemoglobins / Q000378:metabolism; D006801:Humans; D008297:Male; D020097:Natriuretic Peptide, Brain / Q000097:blood*; D018384:Oxidative Stress / Q000502:physiology*; D010446:Peptide Fragments / Q000097:blood*; D010807:Physical Endurance / Q000502:physiology*; D014527:Uric Acid / Q000097:blood
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D016207:Cytokines; D006454:Hemoglobins; D010446:Peptide Fragments; C109794:pro-brain natriuretic peptide (1-76); D020097:Natriuretic Peptide, Brain; D014527:Uric Acid; D003404:Creatinine; D002118:Calcium
keywords: Ironmen; cytokines; endurance training; inflammation; multiple factor analysis; oxidative stress; triathlon race