ArticlePloS one2022
Genetic profiles to identify talents in elite endurance athletes and professional football players.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 7 of them syntheses that pooled it.
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Who cites it
23 citing papers in PubMed, 7 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Polygenic scores and physical fitness prediction: a systematic review.Human genetics · 2026Pooled it
- ACTN3 c.1729C>T Polymorphism Might Not Be a Standalone Factor in Non-contact Musculoskeletal Injury: A Systematic Review and Meta-analysis.Sports medicine (Auckland, N.Z.) · 2026Pooled it
- Socceromics: A Systematic Review of Omics Technologies to Optimize Performance and Health in Soccer.International journal of molecular sciences · 2026Pooled it
- Effect Size and Replicability in Genetic Studies of Athletic Performance: A Meta-Analytical Review.Genes · 2025Pooled it
- Association Between the c.34C > T (rs17602729) Polymorphism of the AMPD1 Gene and the Status of Endurance and Power Athletes: A Systematic Review and Meta-Analysis.Sports medicine (Auckland, N.Z.) · 2025Pooled it
- Association between theFrontiers in physiology · 2025Pooled it
- Examining the relationship between genetic polymorphisms (BDKRB2, GNB3, HIF1A, MCT1, NOS3) and endurance athlete status.European journal of applied physiology · 2024Pooled it
- Trial
- Observational
- EPAS1 is associated with human muscle fiber composition and endurance phenotypes.Physiological reports · 2026Article
- Artificial intelligence and sports genomics: advancing precision sports science and athletic performance.Frontiers in sports and active living · 2026Review
- Muscle AMP deaminase activity was lower in Neandertals than in modern humans.Nature communications · 2025Article
- Article
- Article
- Hybrid performances in sport: Cybathlon spectatorship for critically imagining technologies for disability futures.Medical humanities · 2025Article
- Role of theGenes · 2024Review
- Influence of genetic polymorphism on sports talent performance versus non-athletes: a systematic review and meta-analysis.BMC sports science, medicine & rehabilitation · 2024Article
- Article
- The Association of Genetic Markers Involved in Muscle Performance Responding to Lactate Levels during Physical Exercise Therapy by Nordic Walking in Patients with Long COVID Syndrome: A Nonrandomized Controlled Pilot Study.International journal of molecular sciences · 2024Article
- Dietary Patterns, Gut Microbiota and Sports Performance in Athletes: A Narrative Review.Nutrients · 2024Review
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The genetic profile that is needed to identify talents has been studied extensively in recent years. The main objective of this investigation was to approach, for the first time, the study of genetic variants in several polygenic profiles and their role in elite endurance and professional football performance by comparing the allelic and genotypic frequencies to the non-athlete population. In this study, genotypic and allelic frequencies were determined in 452 subjects: 292 professional athletes (160 elite endurance athletes and 132 professional football players) and 160 non-athlete subjects. Genotyping of polymorphisms in liver metabolisers (CYP2D6, GSTM1, GSTP and GSTT), iron metabolism and energy efficiency (HFE, AMPD1 and PGC1a), cardiorespiratory fitness (ACE, NOS3, ADRA2A, ADRB2 and BDKRB2) and muscle injuries (ACE, ACTN3, AMPD1, CKM and MLCK) was performed by Polymerase Chain Reaction-Single Nucleotide Primer Extension (PCR-SNPE). The combination of the polymorphisms for the "optimal" polygenic profile was quantified using the genotype score (GS) and total genotype score (TGS). Statistical differences were found in the genetic distributions between professional athletes and the non-athlete population in liver metabolism, iron metabolism and energy efficiency, and muscle injuries (p<0.001). The binary logistic regression model showed a favourable OR (odds ratio) of being a professional athlete against a non-athlete in liver metabolism (OR: 1.96; 95% CI: 1.28-3.01; p = 0.002), iron metabolism and energy efficiency (OR: 2.21; 95% CI: 1.42-3.43; p < 0.001), and muscle injuries (OR: 2.70; 95% CI: 1.75-4.16; p < 0.001) in the polymorphisms studied. Genetic distribution in professional athletes as regards endurance (professional cyclists and elite runners) and professional football players shows genetic selection in these sports disciplines.
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