Genetic biomarkers in non-contact muscle
injuries in elite soccer players
Ricard Pruna, Rosa Artells, Matilda
Lundblad & Nicola Maffulli
Knee Surgery, Sports Traumatology,
Arthroscopy
ISSN 0942-2056
Knee Surg Sports Traumatol Arthrosc
DOI 10.1007/s00167-016-4081-6
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Knee Surg Sports Traumatol Arthrosc
DOI 10.1007/s00167-016-4081-6
SPORTS MEDICINE
Genetic biomarkers in non‑contact muscle injuries in elite soccer
players
Ricard Pruna1 · Rosa Artells2 · Matilda Lundblad3 · Nicola Maffulli4,5 Received: 19 December 2015 / Accepted: 3 March 2016
© European Society of Sports Traumatology, Knee Surgery, Arthroscopy (ESSKA) 2016
Abstract Purpose Damage to skeletal muscle necessitates regeneration to maintain proper muscle form and function. Interindividual differences in injury severity, recovery time, and
injury rate could be explained by the presence of single
nucleotide polymorphisms (SNPs) in genes involved in
the reparation and regeneration of connective tissue . We
wished to identify new genetic biomarkers that could help
to prevent or minimize the risk of non-contact muscle injuries and are associated with a predisposition to developing
muscle injuries.
The authors Ricard Pruna and Rosa Artells are equally contributed.
* Rosa Artells
[email protected]
Ricard Pruna
[email protected]
Matilda Lundblad
[email protected]
Nicola Maffulli
[email protected]
1
F.C. Barcelona Medical Services, FIFA Medical Center
of Excellence, Barcelona, Spain
2
SM Genomics, Barcelona, Spain
3
Department of Orthopaedics, Sahlgrenska University,
Gothenburg, Sweden
4
Department of Musculoskeletal Disorders, Faculty
of Medicine, Surgery and Dentistry, University of Salerno,
Fisciano, Italy
5
Centre for Sports and Exercise Medicine, Barts and the
London School of Medicine and Dentistry, Mile End
Hospital, Queen Mary University of London, London,
England
Methods Using allelic discrimination techniques, we analysed 12 SNPs in selected genes from the genomic DNA of
74 elite soccer players.
Results SNPs in the hepatocyte growth factor (HGF) gene
showed evidence of a statistically significant association
with injury incidence, severity, and recovery time. SNPs in
the SOX15 gene showed evidence of a statistically significant association with injury incidence. SNPs in the GEFT
and LIF genes showed evidence of a statistically significant
association with recovery time.
Conclusions Genetic profile could explain why some elite
soccer players are predisposed to suffer more injuries than
others and why they need more time to recover from a particular injury. SNPs in HGF genes have an important role
as biomarkers of biological processes fragility within muscle injuries related to injury rate, severity, and long recovery time.
Keywords Connective tissue · Muscle injury · Single
nucleotide polymorphisms · Injury rate · Recovery time
Introduction
Soccer is the most popular sport in the world, and injuries
are the main important adverse event during a soccer player’s career [38]. Injuries affect performance, and teams that
can avoid injuries have greater success by the end of the
competitive season [4, 11, 18].
Muscle injuries account for 20–30 % of all time-loss
injuries at professional level and up to 23 % at amateur
level; approximately, 16 % of muscle injuries are re-injuries [13].
The diagnosis is clinical, and imaging tools are used to
identify the extent and site of injury. This information can be
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used as prognostic factors that could predict recovery time,
return to preinjury sport activity, and risk of recurrence [5, 28].
The multifactorial nature of injuries has led clinicians to
develop exercise and rehabilitation programmes and protocols according to soccer-specific player actions and movements. Programmes are designed to treat and prevent injuries, especially because those players with prior injuries are
susceptible to recurrence. Injuries and re-injuries are important in elite athletes, in whom decisions regarding return to
play and their performance can have significant financial or
strategic consequences for both the players and their team
[3]. The injury rate (IR) for ligament injuries decreased
during the 2000s, but the IR for muscle and severe injuries
remains high despite the prevention protocols [12, 26].
Genetic profiles for non-contact muscle injuries [21,
22] were analysed obtaining information about muscle
injury incidence, degree, and an estimated recovery time.
The presence of SNPs in genes related to connective tissue repair and regeneration could help us to understand the
nature of this kind of injuries and interindividual differences observed in recovery times.
At present, prevention is performed by applying standard protocols. Our work tries to shed light on individualized
prevention with workloads adaptation, since individuals are
biologically different, as are their environment interaction.
The presence of SNPs in genes related to connective tissue repair and regeneration could help us to understand the
nature of this kind of injuries and interindividual differences observed in recovery times.
Knee Surg Sports Traumatol Arthrosc
were classified using a modified UEFA muscle injuries
classification [12, 13] as mild (1–15 days), moderate (16–
30 days), or severe (more than 30 days) [14, 35], according to the number of days that the player was absent from
training or competition. US and MRI were used to classify
injuries by anatomic location. Moreover, US and MRI gave
information about the percentage of tissue damage. From
an imaging viewpoint, a mild injury represents a minimal
damage under 25 %, and in a serious injury more than
50 % of the tissue is affected. In moderate injuries, the
damaged tissue is close to 50 %. Finally, recovery time was
defined as the date of the injury until the date of the players return to full training and competition. Injury incidence
was defined as the number of injuries per exposure time
(per 1000 h) [30].
DNA purification
Genomic DNA was obtained from 4 mL of blood drawn
from an antecubital vein of the forearm using QIAmp
DNA Blood Mini Kit (Qiagen, Valencia, CA) following the
manufacturer’s instructions and was measured with a NanoDrop ND-1000 Spectrophotometer (Thermo Fisher Scientific, Inc., Waltham, MA). Samples were stored at −80º
until analysed.
Single nucleotide polymorphisms (SNP) selection
and primers and probes
The study was approved by the Ethics Committee of the
Hospital Clinic, Barcelona (Registry No. 2012/7117),
according to Declaration of Helsinki, and all players signed
a written informed consent to participate in this study.
In a previous study, we analysed eight SNPs in genes
related to connective tissue regeneration and repair [34]. In
the present study, we focused on 12 further genes. In addition, since we increased the number of muscle injuries,
we also wished to confirm our previous results [34]. The
detailed characteristics of the SNPs analysed are summarized in Table 1. Primers and probes were obtained from
Applied Biosystems (AB, Foster City, CA).
Subjects and injuries
Genotyping
Data were collected from 74 elite soccer players from Futbol
Club Barcelona (Barcelona, Catalunya, Spain). This work
was performed in a very homogeneous population of superelite individuals who were extremely well trained and controlled. We focused on non-contact muscle injuries, which
represent 36 % of all injuries that players suffer [12]. These
players suffered 220 muscle injuries during five consecutive
seasons (2008–2009/2012–2013). The characteristics of the
population under study were previously described [34].
Muscle injuries were diagnosed according to clinical
history, physical examination, and imaging, using colour
Doppler ultrasound (US) and three Teslas magnetic resonance imaging (MRI) 24 h after injury. Muscle injuries
SNP analysis was undertaken using a real-time PCR allelic
discrimination TaqMan assay according to the manufacturer’s (AB) instructions with minor modifications. All
PCRs were run in duplicate and contained 50 ng of DNA,
6.25 μL of TaqMan Universal Master Mix (AB), 0.25 μL
of primers and probes, and water up to a final volume of
13 μL. Appropriate negative controls were also run. Realtime PCR was performed on an ABI Prism 7500 Sequence
Detection System (AB) using the following conditions:
50 °C for 2 min, 95 °C for 10 min, and then 40 cycles of
amplification (95 °C for 15 s and 62 °C for 1 min). For each
cycle, the software measures the fluorescent signal from the
VIC- or FAM-labelled probe.
Materials and methods
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Table 1 Characteristics of the
SNPs included in the study
Gene
Name
Location
rs NCBI db
LIF
Leukaemia inhibitory factor
rs929271
rs737812
CCL2
GEFT
MYF5
DES
Chemokine ligand-2
Rho guanine nucleotide exchange factor
Myogenic factor 5
Desmin
HGF
Hepatocyte growth factor
MMP3
Matrix metalloproteinase 3
UTR3′
UTR3′
Intergenic
Intergenic
Intergenic
Intergenic
Mis-sense mutation
Intron
Intron
Intron
Mis-sense mutation
rs1860189
rs11613457
rs1163263
rs60794845
rs58999456
rs5745678
rs5745697
rs1011694
rs679620
GDF5
Growth differentiation factor-5
Intergenic
rs143383
Statistical analyses
Descriptive statistics of the main demographic variables
was calculated. Frequency tables were used for the distribution of the SNPs for the genes studied (Table 2).
The association between injury rate and SNPs was
determined by analysis of variance. The association
between type and degree of injury and the SNPs was determined by the Chi-square test and Fisher’s exact test when
necessary. The association between injury recovery time
and SNPs was evaluated using multivariate analysis of variance. As a total of only 74 super-elite soccer players who
suffered 220 muscle injuries were studied, the Benjamini–
Hochberg p value corrective test for multiple comparisons
was applied.
All statistical analyses were performed using SPSS version 14.0 for Windows (SPSS Inc., Chicago, IL). Significance was set at p ≤ 0.05.
Results
Population
The main characteristics of the population were summarized in our previous study [34]. There were no significant
differences between ethnic groups for these characteristics
(median age, median weight, median height, and median
workload; Table 2). The treatment protocol for each type of
injury, including medication and physical therapy, was the
same for all the players, and all treatment was supervised
by the same medical team.
During five consecutive seasons, a total of 220 muscle
injuries were recorded; of these, 140 were mild (63.6 %),
76 were moderate (34.5 %), and four were severe (1.9 %).
Table 3 shows all genotypic frequencies obtained in the
studied populations.
Table 2 Main characteristics of the studied population
Characteristic Whites
n = 42
(56.76 %)
Black Africans
Hispanics
n = 12
(16.22 %)
n = 20
(27.03 %)
Age
Weight
Height
% Fat
25.52 (19–35)
29.11 (20–35)
76.44 (64–92)
77.6 (64–92)
179.62 (166–195) 181.3 (172–194)
8.66 (6.9–12.9) 6.5 (6–14.1)
26.16 (25–34)
72.63 (67–78.5)
176.3 (169–189)
10 (6.2–13.6)
Workloada
15,301
16,554.33
16,224.3
a
Minutes in competition and training per player and season
Injury rate
Table 4 shows the association between all SNPs analysed
in HGF with the injury rate (no. of injuries/1000 h of exposure). HGF rs5745697 and rs1011694 showed a statistically significant association, whereby individuals with the
CC (HGF_2) and AA (HGF_3) genotypes in both variants
showed a decreased number of injuries (p = 0.042 and
p = 0.047, respectively). Moreover, the rs4227 SNP in
SOX15 showed a statistically significant association related
to rate of injury (p = 0.020).
Severity of injury and recovery time
Having increased the number of muscle injuries collected,
we wanted to validate our previous results [34]. We confirmed the results obtained with the SNPs analysed in IGF2
(rs3213221), CCL2 (rs2857656), and COL5A1 (rs12722).
Concerning IGF2, the GC genotype was significantly
associated with less severe injuries than those associated
with the CC or GG genotypes (p = 0.043, previous value
p = 0.034). In the SNP analysed in CCL2, the presence of
the C allele (CC/CG) was associated with less severe muscle injuries than the GG genotype (p = 0.008, previous
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Table 3 Genotypic frequencies in the present study and for Caucasians (HapMap CEU), Black African (HapMap YRI), and Hispanic (HISP1)
populations in NCBI dbSNP
Gene
Genotype
Population
White
Present study
Black African
HapMap CEU (%)
n = 42
LIF
rs929271
rs737812
CCL2
rs1860189
GEFT
rs11613457
MYF5
rs1163263
HGF
rs5745678
rs5745697
rs1011694
MMP3
rs679620
Present study
Hispanic
HapMap YRI (%)
n = 12
Present study
HapMap HISP
n = 20
TT
GG
GT
CC
AA
AC
16 (38.1 %)
6 (14.3 %)
20 (47.6 %)
–
30 (71.4 %)
12 (28.6 %)
46.9
9.7
43.4
38.9
18.6
42.5
9 (75 %)
–
3 (25 %)
6 (50 %)
–
6 (50 %)
100
–
–
69.9
3.5
26.5
6 (30 %)
5 (25 %)
9 (45 %)
8 (40 %)
3 (15 %)
9 (45 %)
NA
GG
AA
1 (2.4 %)
24 (57.1 %)
4.3
65.2
–
10 (83.3 %)
–
81.4
1 (5 %)
13 (65 %)
GA
17 (40.5 %)
30.4
2 (16.7 %)
18.6
6 (30 %)
GG
AA
GA
41 (97.6 %)
–
1 (2.4 %)
84.8
–
15.2
–
12 (100 %)
–
100
–
–
19 (95 %)
–
1 (5 %)
NA
GG
AA
36 (85.7 %)
1 (2.4 %)
81.7
–
11 (91.7 %)
–
98.3
–
16(80 %)
–
NA
GA
5 (11.9 %)
18.3
1 (8.3 %)
1.7
4 (20 %)
CC
TT
CT
AA
CC
CA
TT
AA
AT
30 (71.4 %)
–
12 (28.6 %)
–
30 (71.4 %)
12 (28.6 %)
–
29 (69 %)
13 (31 %)
58.3
4.2
37.5
2.7
56.6
40.7
1.7
65
33.3
11 (91.7 %)
–
1 (8.3 %)
–
10 (83.3 %)
2 (16.7 %)
–
10 (83.3 %)
2 (16.7 %)
100
–
–
0.9
99.1
–
100
–
10 (50 %)
1 (5 %)
8 (40 %)
1 (5 %)
12 (60 %)
7 (35 %)
1 (5 %)
12 (60 %)
7 (35 %)
TT
CC
TC
15 (35.7 %)
8 (19 %)
19 (45.3 %)
32.1
14.7
53.2
1 (8.3 %)
4 (33.3 %)
7 (58.3 %)
10.2
32.4
57.4
2 (10 %)
3 (15 %)
15 (75 %)
NA
CC
TT
5 (11.9 %)
22 (52.4 %)
11.7
45
–
1 (8.3 %)
65.2
–
5 (25 %)
7 (35 %)
NA
CT
15 (35.7 %)
43.3
5 (41.7 %)
34.8
8 (40 %)
NA
NA
NA
NA
NA
GDF5
rs143383
value p = 0.026). The COL5A1 TC genotype showed a statistically significant association with more severe injuries
(p = 0.042) [34].
We observed a statistically significant association
between the three SNPs analysed in HGF [rs5745678
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(HGF_1), rs5745697 (HGF_2), and rs1011694 (HGF_3)]
with severity of injury and recovery time. In HGF_1, the
presence of the T allele, both TT or TC, protects against
severe injuries (p = 0.002). Moreover, this group with protection against severe injuries had a mean recovery time
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Table 4 Genotypes related
to injury rate for non-contact
muscle injuries
Gene
SNP
Genotype
Mean no. of injuries/1000 h (95 % CI)
p value
HGF
rs5745678
rs5745697
HGF
rs1011694
8.5 injuries (95 % IC: 6.87–10.13)
12.05 injuries (95 % IC: 7.53–16.58)
8.4 injuries (95 % IC: 6.80–10.06)
12.3 injuries (95 % IC: 7.78–16.73)
8.4 injuries (95 % IC: 6.75–10.08)
12.08 injuries (95 % IC: 7.89–16.28)
ns
HGF
CC
CT/TT
CC
CA/AA
AA
AT/TT
SOX15
rs4227
TT
TG
7.8 injuries (95 % IC: 6.33–9.37)
10.2 injuries (95 % IC: 7.01–13.43)
GG
14.8 injuries (95 % IC: 5.88–23.74)
of 19.8 days instead of 27.7 days in individuals with the
CC genotype (p = 0.009). Injuries associated with the CA/
AA genotypes in HGF_2 were not severe (p = 0.008) and
resulted in a statistically significantly shorter recovery
time [20.7 days instead of 27.5 days in individuals with
TT genotype (p = 0.020)]. Finally, injuries associated with
the AT/TT genotypes in HGF_3 were mild or moderate
(p = 0.019) (Fig. 1).
Finally, SNPs in GEFT (rs11613457) and LIF
(rs9290271) showed an association between muscle injury
and recovery time (Table 5).
Discussion
The most important finding in the present study was the
association between injury rate, severity of injury, and
recovery time for muscle injuries, and the three SNPs
analysed in the HGF gene. Muscle injuries are one of
the most common injuries occurring in sport. The risk
of muscle injuries increases in high-demand sports and
accounts for a high proportion of all acute sports injuries
[10]. It is often difficult to predict the long-term prognosis following a muscle strain, although these injuries may
have a marked impact on the athletes and their teams.
Injury diagnosis is usually clinical, and imaging can help
to better define extension and site of injury that could predict risk of recurrence, recovery time, and return to sport
activity [5, 10, 23]. Although intensive treatment programmes and rehabilitation strategies have been implemented, the number of muscle and other soft tissue injuries remains high [12].
Muscle injuries occur through the interaction of extrinsic and intrinsic factors [15, 29]. Despite rigorous control
of these factors, a wide range of interindividual differences
exists in number and degree of injuries and in recovery
time, suggesting that other factors [8], including genetic
variations, could influence these differences. Indeed, there
are identified genetic risks in the pathogenesis of non-contact muscle injuries [8, 25, 27].
0.04
0.04
0.02
A single nucleotide polymorphism (SNP) is a DNA
sequence variation which occurs when a single nucleotide
in the genome differs between paired chromosomes in a
given individual. SNPs can occur throughout the genome,
both in coding and in non-coding regions, and can affect
the response of an individual to a specific treatment or
other stimuli [34].
The present investigation confirms that [34] the degree of
muscle injury severity showed evidence of a statistically significant association with SNPs in IGF2 (p = 0.034), CCL2
(p = 0.008), and shows that, in our sample of elite professional soccer players, the degree of muscle injury severity
showed evidence of a statistically significant association
with COL5A1 (p = 0.042). Briefly, IGF2 plays a role in soft
tissues growth, and its expression is increased in response
to degeneration and regeneration following an injury, working with other genes to influence satellite cell activation [1].
CCL2 is a small chemokine produced by macrophages and
satellite cells and plays key roles in inflammation. CCL2 also
plays significant roles in muscle damage, repair, and adaptation [19]. Finally, COL5A1 encodes the α1 chain of collagen
type V, which forms in part the extracellular matrix of skeletal muscle. COL5A1 connects with COL1A1 and modulates
fibrillogenesis. In the present study, individuals with the TC
genotype suffer more severe injuries. This is in line with previous studies that show that the process of fibrillogenesis is
only successful when both C alleles are present [9].
A novel finding in our study was the statistically significant association between injury rate, severity of injury, and
recovery time, and the three SNPs analysed in the HGF
gene. HGF participates in skeletal muscle development and
regeneration by activating quiescent satellite cells [17]. HGF
has a dual role, as a scatter factor and a paracrine function,
especially during embryonic development, by regulating the
growth of several epithelial and myogenic precursor cells
during organogenesis [2]. The first association between HGF
and skeletal muscle was described by Tatsumi et al. [37],
where they demonstrated that mRNA HGF and its receptor, c-MET, are co-expressed during satellite cells activation,
and then both are repressed during myoblast differentiation
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Fig. 1 Severity and estimated
recovery time predicted for
muscle injuries
into myotubes. We observed that wild-type (WT) alleles in
the three cases are associated with a statistically significant
decrease in injury rate (Table 4). These data led us to think
that, during the process of organogenesis of skeletal muscle,
muscles develop correctly because the interaction between
HGF and its receptor is well established, and the activation of
the signalling pathway that activates molecules related to cell
polarity, cytoskeleton formation, cell junction development,
and proliferation and migration is correct [16]. A reduction
or absence of c-MET activity results in abnormal formation
of skeletal muscle [16]. Our results indicate a correct interaction between HGF and c-MET, and therefore a normally
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developed muscle, which justifies why individuals with the
WT HGF genotype suffer a decreased incidence of injury.
Despite this, WT HGF individuals exhibit a longer recovery time than those with heterozygous or SNP. HGF has a
scatter factor activity: this molecule is capable of increasing
cell motility [34]. In this instance, the presence of the allelic
variant could perhaps imply, in both SNP homozygotes and
heterozygotes, an increase in motility in cells involved in
muscle repair, and a subsequent reduction in recovery time.
This information could be important in response to regenerative medicine strategies such as platelet-rich plasma (PRP)
in the management of muscle injuries [36]. Platelets produce
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Table 5 Genotypes related to recovery time for non-contact muscle
injuries
Gene
SNP
HGF
rs5745678
Genotype Mean recovery time (days) p value
95 % CI
CC
CT/TT
HGF rs5745697 CC
CA/AA
HGF rs1011694 AA
AT/TT
GEFT rs11613457 GG
GA
LIF_1 rs9290271
TT
TC/CC
27.72 (23.88–31.57)
19.83 (16.57–23.10)
27.53 (23.72–31.36)
20.67 (16.96–24.38)
27.1 (23.11–31.03)
22.01 (18.32–25.70)
24.6 (21.75–27.32)
52 (26.18–77.82)
22 (17.95–25.97)
0.009
0.02
ns
0.004
ns
27.6 (23.64–31.41)
several growth factors, and therefore, these therapies should
exert a beneficial effect on tissue healing [32]. PRP is injected
not in the gap produced by the injury, but into the healthy part
of the muscle close to the injury, where intact muscle fibres
contain satellite cells. PRP contains HGF, which activates
satellite cells participating in the regenerative process [17].
SOX15 showed a statistically significant association with
injury rate (p = 0.026), where individuals with the T allele
(TT/TG) showed a decreased number of injuries. SOX15
plays a role in determination of skeletal muscle cell fate during development [24]. The correct form of SOX15 is required
for the activation of the myogenic programme. Previous studies demonstrated that SOX15 inactivation or incorrect function leads to decreased cell proliferation and perturbed muscle regeneration [31]. Our results indicate that individuals
with the GG genotypes present abnormal formation of skeletal muscle, with an increased injury rate because the presence
of the T allele is necessary for SOX to be fully functional.
Data regarding HGF and IR are in line with a previous
study [33], where 23 elite professional male soccer players
were followed for two consecutive seasons. These elite professional players suffered a mean total injury rate of 18.9 injuries/1000 h of exposure. Our results indicate a low injury rate
index because the sample is composed of elite professional
football players who are under strict supervision regarding
their general health, and in whom prevention strategies are
routinely implemented. Finally, GEFT and LIF showed an
association with recovery time. GEFT is a Rho family member that regulates cytoskeletal-dependent cell function such
as formation of focal adhesions, platelet aggregation, and cell
cycle progression. Moreover, GEFT participates in re-epithelialization after injury [7]. Individuals with the GG wildtype genotype had shorter recovery time than those with the
GA genotype (p = 0.004). Since the Rho-GEFT signalling
pathway regulates muscle regeneration by myogenic cell fate
determination and increasing myogenesis, our results related
to recovery time are in line with previous studies [7].
LIF showed a trend towards significance (p = 0.052),
whereby individuals with the TT wild-type genotype need
less time to recover from injuries. The function of LIF is
associated with an increase in proinflammatory cytokines
and with myogenic differentiation and formation of new
myotubes [20]. LIF is produced during exercise and might
contribute to muscle adaptation following exercise by
stimulating muscle satellite cells proliferation, a process
important for muscle hypertrophy and regeneration [6]. If
the inflammatory cascade is well activated, the process of
skeletal muscle regeneration would progress in the correct
fashion thanks to appropriate activation of the muscle satellite cells, resulting in shorter time to recover from injury.
Since the study of genetic profiles in sports medicine is
still in its early stages, further studies with larger samples are
warranted to validate our findings. It is important to work
with elite samples with a well-defined training and competition profile in an effort to link the biological capabilities of
elite athletes with their ability to adapt to these efforts.
These findings could be useful in the day-to-day clinical
work because it is important for the medical staff to know
the biological predisposition of each athlete in terms to be
subjected to high workloads and stress during trainings and
competitions. Assessing the risk of injury can help to modulate workloads and exposure time of athletes providing the
technical staff with valuable information, in order to reliably select the fittest players for the competition, reducing
the risk of injury and avoid recurrences.
Conclusions
At present, extrinsic factors for sports injuries are well
characterized and can be addressed to diminish the occurrence and severity of injuries. Little is known about intrinsic factors. In the future, genetic profiling could allow to
better define at least some intrinsic risk factors linked to the
aetiology of muscle injuries, allowing to plan preventive
strategies to protect elite professional athletes [12] favouring full recovery and decreasing the number of re-injuries.
Acknowledgments We thank FC Barcelona Medical Services for
all data provided.
Compliance with ethical standards Conflict of interest None.
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