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5. The athlete after COVID-19 infection: what the scientific evidence? What to do? A position statement.

Author

CASTELLETTI, Silvia, GERVASI, Salvatore, BALLARDINI, Enrico, CASASCO, Maurizio, CAVARRETTA, Elena, COLIVICCHI, Furio, CONTURSI, Maurizio, CUCCARO, Francesco, D'ASCENZI, Flavio, GAZALE, Giovanni, MOS, Lucio, NISTRI, Stefano, PALMIERI, Vincenzo, PATRIZI, Giampiero, SCORCU, Marco, SPAMPINATO, Andrea, TIBERI, Monica, ZITO, Giovanni B., ZORZI, Alessandro, and ZEPPILLI, Paolo

Published
2024
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8. Are Football Players More Prone to Muscle Injury after COVID-19 Infection? The “Italian Injury Study” during the Serie a Championship

Author

Corsini, Alessandro, primary, Bisciotti, Andrea, additional, Canonico, Raffaele, additional, Causarano, Andrea, additional, Del Vescovo, Riccardo, additional, Gatto, Pierluigi, additional, Gola, Paolo, additional, Iera, Massimo, additional, Mazzoni, Stefano, additional, Minafra, Paolo, additional, Nanni, Gianni, additional, Pasta, Giulio, additional, Pulcini, Ivo, additional, Salvatori, Stefano, additional, Scorcu, Marco, additional, Stefanini, Luca, additional, Tenore, Fabio, additional, Palermi, Stefano, additional, Casasco, Maurizio, additional, and Calza, Stefano, additional

Published
2023
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10. The Athlete after COVID-19 infection: what the scientific evidence? What to do?

Author

CASTELLETTI, Silvia, primary, GERVASI, Salvatore, additional, BALLARDINI, Enrico, additional, CASASCO, Maurizio, additional, CAVARRETTA, Elena, additional, COLIVICCHI, Furio, additional, CONTURSI, Maurizio, additional, CUCCARO, Francesco, additional, D’ASCENZI, Flavio, additional, GAZALE, Giovanni, additional, MOS, Lucio, additional, NISTRI, Stefano, additional, PALMIERI, Vincenzo, additional, PATRIZI, Giampiero, additional, SCORCU, Marco, additional, SPAMPINATO, Andrea, additional, TIBERI, Monica, additional, ZITO, Giovanni B., additional, ZORZI, Alessandro, additional, ZEPPILLI, Paolo, additional, and SCIARRA, Luigi, additional

Published
2022
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17. Association between the ACE I/D polymorphism and muscle injuries in Italian and Japanese elite football players

Author

Massidda, Myosotis, primary, Miyamoto-Mikami, Eri, additional, Kumagai, Hiroshi, additional, Ikeda, Hayato, additional, Shimasaki, Yu, additional, Yoshimura, Masafumi, additional, Cugia, Paolo, additional, Piras, Francesco, additional, Scorcu, Marco, additional, Kikuchi, Naoki, additional, Calò, Carla Maria, additional, and Fuku, Noriyuki, additional

Published
2020
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19. Association of Monocarboxylate Transporter-1 (MCT1) A1470T Polymorphism (rs1049434) with Forward Football Player Status.

Author

Cięszczyk, Paweł, primary, Calò, Carla Maria, primary, Massidda, Myosotis, additional, Mendez-Villanueva, Alberto, additional, Ginevičienė, Valentina, additional, Proia, Patrizia, additional, Drozdovska, Svitlana, additional, Dosenko, Victor, additional, Scorcu, Marco, additional, Stula, Aleksander, additional, and Sawczuk, Marek, additional

Published
2018
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20. New Genetic Model for Predicting Phenotype Traits in Sports.

Author

Massidda, Myosotis, Scorcu, Marco, and Cal, Carla M.

Subjects
DNA analysis, SALIVA analysis, ALGORITHMS, ANALYSIS of covariance, ANTHROPOMETRY, ATHLETIC ability, CHI-squared test, CONFIDENCE intervals, EXERCISE physiology, FORECASTING, GENES, GENETIC polymorphisms, GENETICS, JUMPING, POLYMERASE chain reaction, REGRESSION analysis, SOCCER, SPORTS sciences, PHENOTYPES, EFFECT sizes (Statistics), ELITE athletes, DATA analysis software, STATISTICAL models, DESCRIPTIVE statistics
Abstract

Purpose: The aim of the current study was to construct a genetic model with a new algorithm for predicting athletic-performance variability based on genetic variations. Methods: The influence of 6 polymorphisms (ACE, ACTN-3, BDKRB2, VDR-ApaI, VDR-BsmI, and VDR-FokI) on vertical jump was studied in top-level male Italian soccer players (n = 90). First, the authors calculated the traditional total genotype score and then determined the total weighting genotype score (TWGS), which accounts for the proportion of significant phenotypic variance predicted by the polymorphisms. Genomic DNA was extracted from saliva samples using a standard protocol. Genotyping was performed using polymerase chain reaction (PCR). Results: The results obtained from the new genetic model (TWGS) showed that only 3 polymorphisms entered the regression equation (ACTN-3, ACE, and BDKRB2), and these polymorphisms explained 17.68-24.24% of the vertical-jump variance. With the weighting given to each polymorphism, it may be possible to identify a polygenic profile that more accurately explains, at least in part, the individual variance of athletic-performance traits. Conclusions: This model may be used to create individualized training programs based on a player's genetic predispositions, as well as to identify athletes who need an adapted training routine to account for individual susceptibility to injury. [ABSTRACT FROM AUTHOR]

Published
2014
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21. Association of Monocarboxylate Transporter-1 (MCT1) A1470T Polymorphism (rs1049434) with Forward Football Player Status.

Author

Massidda, Myosotis, Mendez-Villanueva, Alberto, Ginevičienė, Valentina, Proia, Patrizia, Drozdovska, Svitlana B., Dosenko, Victor, Scorcu, Marco, Stula, Aleksander, Sawczuk, Marek, Cięszczyk, Paweł, and Calò, Carla Maria

Subjects
DNA analysis, ALLELES, ATHLETIC ability, CHI-squared test, DNA, EPITHELIUM, FOOTBALL, GENETIC polymorphisms, LONGITUDINAL method, MEDICAL protocols, ORAL mucosa, POPULATION geography, PROFESSIONAL athletes, MEMBRANE transport proteins, GENOTYPES
Abstract

The aim of this study was to investigate the association between the MCT1 (monocarboxylate transporter 1) A1470T polymorphism and positional roles in a large cohort of professional football players from five different countries. We compared genotype distributions of the MCT1 A1470T polymorphism between football players (n = 694) and non-athlete controls (n = 781) from Italy, Poland, Lithuania, Ukraine and Malta, and we analyzed the MCT1 genotype distributions with respect to the players' positions in the field (e. g. forwards, midfielders, defenders and goalkeepers). Genomic DNA was extracted from either buccal epithelium or peripheral blood using a standard protocol. In the pooled cohort of Italian, Polish, Lithuanian and Ukrainian football players, forwards (n = 148) were more likely than controls (n = 781) to possess the A allele ( χ² = 7.067, p = 0.029, FDR q value 0.116), with a greater likelihood of having the AA genotype compared with the TT genotype (OR = 1.97; C.I. = 1.07-3.64; p = 0.021, FDR q value 0.086). The MCT1 AA genotype was significantly more frequent in forwards then in controls. Further studies are needed to confirm these findings in other professional football player cohorts. [ABSTRACT FROM AUTHOR]

Published
2018
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31. Body composition changes during the lockdown-restart transition due to the SARS-CoV-2 pandemic in a group of professional football players.

Author

Ghiani G, Roberto S, Mura R, Fois F, Scorcu M, and Crisafulli A

Subjects
Adult, Body Composition, Communicable Disease Control, Electric Impedance, Female, Humans, Male, Pandemics, SARS-CoV-2, Water, Young Adult, COVID-19 epidemiology, Football
Abstract

Background: At the beginning of March 2020, because of the ongoing pandemic, all sport events were suspended in Italy. The Italian Serie A league abruptly interrupted all competitions and teams could not train in a group anymore. These containment measures were gradually eased in May. The aim of this study was to ascertain the impact of the lockdown-restart transition on the body composition of a group of Italian footballers of a Serie A team during the pandemic., Methods: The body composition of 18 male football players (age 27.6±4.5 years) from an Italian Serie A team was studied by bioelectrical impedance (BIA). Measures were conducted after lockdown, when they restarted to train in group with the ball (T0), and after the first regular match (T1)., Results: Results show that there were no changes in body mass, body mass index, fat mass, fat-free mass, and total body water between T0 and T1. Differently, intracellular water, extracellular water, and phase angle were changed., Conclusions: We concluded that the lockdown did not have any impact in athletes' body composition as they kept training at home. Moreover, the BIA method was able to detect subtle signals of shift in body water compartments (intra cellular and extra cellular water) likely due to the different kind of training conducted during and after the lockdown.

Published
2022
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