Is the COL5A1 rs12722 Gene Polymorphism Associated
with Running Economy?
Roˆ mulo Bertuzzi1,2*, Leonardo A. Pasqua2, Saloma˜o Bueno2, Adriano Eduardo Lima-Silva3,
Monique Matsuda4, Monica Marquezini1, Paulo H. Saldiva1
1 Laboratory of Experimental Air Pollution, Department of Pathology, School of Medicine, University of Sa˜o Paulo, Sa˜o Paulo, Brazil, 2 Endurance Sports Research Group,
School of Physical Education and Sport, University of Sa˜o Paulo, Sa˜o Paulo, Brazil, 3 Sports Science Research Group, Academic Center of Vitoria, Federal University of
Pernambuco, Vitoria de Santo Anta˜o, Brazil, 4 Faculty of Medicine, University of Sa˜o Paulo, Sa˜o Paulo, Brazil
Abstract
The COL5A1 rs12722 polymorphism is considered to be a novel genetic marker for endurance running performance. It has
been postulated that COL5A1 rs12722 may influence the elasticity of tendons and the energetic cost of running. To date,
there are no experimental data in the literature supporting the relationship between range of motion, running economy,
and the COL5A1 rs12722 gene polymorphism. Therefore, the main purpose of the current study was to analyze the influence
of the COL5A1rs12722 polymorphism on running economy and range of motion. One hundred and fifty (n = 150) physically
active young men performed the following tests: a) a maximal incremental treadmill test, b) two constant-speed running
tests (10 kmNh21 and 12 kmNh21) to determine the running economy, and c) a sit-and-reach test to determine the range of
motion. All of the subjects were genotyped for the COL5A1 rs12722 single-nucleotide polymorphism. The genotype
frequencies were TT = 27.9%, CT = 55.8%, and CC = 16.3%. There were no significant differences between COL5A1 genotypes
for running economy measured at 10 kmNh21 (p = 0.232) and 12 kmNh21 (p = 0.259). Similarly, there were no significant
differences between COL5A1 genotypes for range of motion (p = 0.337). These findings suggest that the previous
relationship reported between COL5A1 rs12722 genotypes and running endurance performance might not be mediated by
the energetic cost of running.
Citation: Bertuzzi R, Pasqua LA, Bueno S, Lima-Silva AE, Matsuda M, et al. (2014) Is the COL5A1 rs12722 Gene Polymorphism Associated with Running
Economy? PLoS ONE 9(9): e106581. doi:10.1371/journal.pone.0106581
Editor: Mikko Lammi, University of Eastern Finland, Finland
Received January 30, 2014; Accepted August 8, 2014; Published September 4, 2014
Copyright:  2014 Bertuzzi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Romulo Bertuzzi is supported by CAPES (grant 23038.000486/2011-15). Leonardo A. Pasqua is supported by FAPESP (grant 2010/13913-6). Saloma˜o
Bueno is supported by CAPES (grant 1182744). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the
manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* Email: bertuzzi@usp.br
Introduction
It is well known that athletic performance is dependent on a
multifactorial phenotype resulting from a complex interaction
between environmental [1,2] and genetic [3,4] factors. In the past
few years, researchers have analyzed the influence of some genes
that encode proteins that are involved in metabolic pathways [5]
or skeletal muscle structure [4,6], which are important to athletic
performance. More recently, Posthumus et al. [7] reported that
endurance running performance is associated with a gene, named
COL5A1, which encodes a structural protein of the extracellular
matrix. These authors observed that the TT genotype was
overrepresented in runners with faster performances during the
42.2-km running portion of the Ironman triathlon, suggesting
thatCOL5A1 might be a novel genetic marker for endurance
running performance.
It is believed that the relationship between COL5A1 and
endurance running performance might be mediated by the energy
storage capacity of the connective tissues [7,8]. COL5A1 encodes
the a1 (V) chain of type V collagen [9], which plays a crucial role
in the regulation of the size and configuration of other abundant
fibrillar collagens supporting many tissues in the body, such as
tendons, ligaments, and muscles [10]. A mutation in the COL5A1
gene, which causes haploinsufficiency, results in a 50% reduction
of type V collagen, and leads to poorly organized fibrils, decreased
tensile strength, and reduced stiffness of connective [9]. It has been
demonstrated that a common C to T single nucleotide polymor-
phism within the COL5A1 39 untranslated region (rs12722) may
alter COL5A1 mRNA stability and thereby reduce the production
of type V collagen [11]. Thus, it was hypothesised that individuals
with a TT genotype of this variant would have increased type V
collagen production and thus favorably altered mechanical
properties of tendons, which enhances endurance running ability
[7,8].
Running economy (RE), which has been defined as the energy
cost or oxygen uptake for a given submaximal running speed
[12,13], is considered to be an important determinant of
endurance performance [14,15]. It has been indicated that the
inter-individual variation in RE is approximately 10–25% between
homogeneous subjects for maximal oxygen uptake ( :VO2 max )
[15]. The cause of this variation is not well understood, but it
might be partially explained by the energy storage capacity of the
tendons [14]. Indeed, elastic energy is generated by the passive
stretch of the muscle elastic elements, and this energy is converted
to kinetic energy free of metabolic cost during a running bout [16].
Thus, the most economical runners have a higher compliance of
the tendons and aponeuroses compared to their less economical
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counterparts [14]. Because of this reported association between
RE and the energy storage capacity of the tendons, it has been
proposed that individuals with a TT genotype would have less
extensible tendon structures, resulting in a lower range of motion
(ROM) and greater RE when compared with individuals with at
least one copy of the C allele [8]. However, to date there are no
experimental data in the literature supporting this relationship
among RE, ROM, and the COL5A1 rs12722 gene polymorphism.
Consequently, it is difficult to determine whether the association
previously reported between the COL5A1 gene and endurance
performance was due to a reduced running energy cost.
Therefore, the main objective of the present study was to
analyze the influence of the COL5A1 gene polymorphism on RE.
In light of past studies that reported a relation between the
COL5A1 gene (rs12722) and endurance running performance
[7,8], it was hypothesized that individuals with a TT genotype
would have a greater RE and a lower ROM when compared to
individuals with the TC and CC genotypes.
Materials and Methods
Participants
One hundred and fifty (n = 150) physically active men (age
25.264.0 years, body mass 77.8613.9 kg, height 173.9621.4 cm,
and body fat 13.364.2%) volunteered to participate in this study.
All subjects were medication-free, nonsmokers, and free of
neuromuscular disorders and cardiovascular dysfunctions. The
subjects had been involved in recreational sports in the past year,
but they had not engaged in flexibility and strength training for at
least six months before the study. The participants received a
verbal
explanation
about
the
possible
benefits,
risks,
and
discomforts associated with the study and signed a written
informed consent before participation in the study. The proce-
dures were in accordance with the Helsinki declaration of 1975,
and the study was approved by the Ethics Committee for Human
Studies of the School of Physical Education and Sport of the
University of Sa˜o Paulo.
Experimental design
All of the subjects were required to visit the laboratory on three
occasions separated by at least 72 h over a 2-week period. In the
first visit, the subjects were asked to perform mouthwashes for
genomic DNA extraction, to perform a sit-and-reach test for
ROM measurement, and to fill out a short version of the physical
activity questionnaire (IPAQ-short version) to estimate their
physical activity levels. In the second visit, anthropometric
measurements (height, body mass, and body composition) were
recorded and a maximal incremental treadmill test was performed.
A constant-speed, treadmill running familiarization test was
conducted at the end of the first and second visits after a 20-min
passive recovery. In the third session, the subjects performed two
submaximal constant-speed tests. All of the tests were performed at
the same time of day in a controlled-temperature room (20–24uC)
and 2–3 h after the last meal. All of the subjects were asked to
refrain from any exhaustive or unaccustomed exercise for 48 h
preceding the test. They also were instructed to wear standard
running shoes and asked from taking off nutritional supplements
six months before the experimental period.
Anthropometric measurements
All of the anthropometric measurements were made according
to the procedures described by Norton and Olds [17]. The
subjects were weighed using an electronic scale to the nearest
0.1 kg. Height was measured with a stadiometer to the nearest
0.1 cm. Skinfold thickness was measured at seven sites (chest,
axilla, triceps, subscapular, abdominal, suprailiac, and thigh) with
a Harpenden caliper (West Sussex, UK) to the nearest 0.2 mm.
The seven skinfold thickness values were obtained on the right side
of the body in a serial fashion, and the median of three values was
used for data analysis. When the difference between these three
values was higher than 10%, a fourth measurement was obtained.
All measurements were made by the same experienced investiga-
tor. Body density was estimated using the generalized equation of
Jackson and Pollock [18], and body fat was estimated using the
equation of Brozek et al. [19].
Maximal incremental treadmill test
The subjects performed a maximal incremental test on a motor-
driven treadmill (model TK35, CEFISE, Nova Odessa) to
determine maximal oxygen uptake ( :VO2 max ). After a 3-min
warm-up at 8 km?h21, the velocity was increased by 1 km?h21
every minute until exhaustion. The participants received strong
verbal encouragement to ensure attainment of maximal values.
Gas exchange was measured breath-by-breath using a gas analyzer
(Cortex Metalyzer 3B, Cortex Biophysik, Leipzig, Germany) and
was subsequently averaged over 20 s intervals throughout the test.
Before each test, the gas analyzer was calibrated according to the
recommendations of the manufacturer. Maximal heart rate
(HRMAX) was defined as the highest value obtained at the end
of the test. Blood samples (25 ml) were collected from the ear lobe
one, three, and five minutes after the test to determine the peak
blood lactate. Lactate concentrations were measured spectropho-
tometrically (EONC, Biotek Instruments, USA) using a wave-
length of 546 nm. :VO2 max was determined when two or more of
the following criteria were met: an increase in oxygen uptake of
less than 2.1 ml?kg21?min21 between two consecutive stages, a
respiratory exchange ratio greater than 1.1, and a 610 bpm of the
predicted maximal heart rate (i.e., 220-age) [20].
Running economy
The subjects performed two constant-speed running tests on a
treadmill to determine RE. Because it has been reported that a
subject who is economical at a given speed will not be necessarily
economical at other speeds [21], we measured the RE at10
km?h21 and 12 km?h21 speeds. These intensities corresponded to
78.866.7% and 89.767.9% of the :VO2 max , respectively. Due
the different percentage values required of the :VO2 max , it was
assumed that these intensities represented the RE at low
(RELW = 10 km?h21) and high (REHG = 12 km?h21) intensities.
Before the tests, the participants performed a standardized warm-
up consisting of a 5 min run at 8 km?h21 followed by a 5-min of
passive recovery. RE was determined by measuring breath-by-
breath oxygen uptake for 10 minutes at each running speed. RE
was defined by averaging the oxygen uptake values during the last
20 s for each running speed. Recovery time between these two
constant-speeds running tests was 10 min.
Range of motion
Range of motion (ROM) was measured using a sit-and-reach
test [22,23]. This test has been used in previous studies
investigating the effects of the COL5A1 genotypes on lower limb
flexibility because it represents an indirect measure of both
hamstring musculotendinous unit length and lumbar ROM
[25,26]. The subjects sat with their bare feet pressed against the
sit-and-reach box. The knees were extended and the right hand
was positioned over the left. Then, the subjects were asked to push
a ruler transversally located over the box as far as possible on the
COL5A1 and Running Economy
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fourth bobbing movement. Three trials were performed, and the
best trial was used for statistical analysis.
Physical activity level determination
Because the RE may be influenced by the training status of
the subjects [27], the short version of the International Physical
Activity Questionnaire (IPAQ-SV) was used to identify the
physical activity level of the participants. This questionnaire was
developed with a multi-cultural adaptation and is considered to
be one of the most widely utilized instruments due to the
quickness of data collection, low operating cost, and non-
invasive characteristics [28]. In addition, it has recently been
shown that IPAQ-SV outcomes are associated with flexibility
and cardiorespiratory fitness levels in healthy men [29]. The
participants answered the questionnaire in a classroom setting
after a detailed description of the IPAQ-SV. An assistant
remained in the classroom setting for eventual doubts. The
major aim of the IPAQ-SV is to sum up walking, moderate and
vigorous PA and to generate a total PA score for weekly
expenditure, expressed in metabolic equivalent task units (METs
min/wk). We used the following recommended METs min/wk
estimates of the IPAQ-SF: walking PA = 3.3 METs min/wk,
moderate PA = 4.0 METs min/wk, vigorous PA = 8.0 METs
min/wk. The total PA was calculated assuming: 3.36walking
PA+4.06moderate PA+8.06vigorous PA. The PA level was
classified as low, moderate or high. Low activity represented
individuals who do not meet the criteria for moderate and
vigorous intensity categories (,599 METs min/wk). Moderate
activity represented moderate or vigorous intensity activities
achieving a minimum of at least 600 METs min/wk. High
activity represented participants achieving a minimum of at least
3000 METs min/wk (http://www.ipaq.ki.se/scoring.htm).
Genotype assessment
Cells from the mouthwashes were submitted to an overnight
digestion with proteinase K. Nucleotides were separated from
the cellular debris by density gradient centrifugation using
chloroform. Genomic DNA was then precipitated with isopropyl
alcohol, isolated by centrifugation and resuspended in TE
buffer. DNA quantification was performed using a spectropho-
tometer (NanoDrop, ND 2000, USA), and the concentration
was adjusted to 1 mg/mL for subsequent storage in 220uC.
COL5A1 rs12722 gene polymorphisms were determined by
conventional 2-primer PCR (F: 59-GCAGTCAGCAGCGTGG-
GTCTGGTTATCT-39 and R: 59-TTTGGGGTGGCACTTG-
CAGCACT GGTCG-39). This assay resulted in the amplifica-
tion of a 637-bp fragment of the COL5A1 gene that includes
the polymorphic region. The reaction conditions were as follow:
initial hold at 94uC for 3 min, 35 cycles of denaturation at
94uC for 60 s, annealing at 53uC for 60 s and extension at
72uC for 60 s, and a final extension step of 8 min at 72uC. The
amplified fragment was subsequently digested using BstUI (New
England, Biolabs, Beverly, MA, USA), following the supplier’s
recommendations. The digested products were then separated
on a 3% agarose gel. To ensure proper internal control, for
each batch of analysis, we used positive and negative controls
from different DNA aliquots that were previously genotyped by
the same method, according to recent recommendations for
replicating genotype-phenotype association studies [30]. The
restriction fragment length polymorphism (RFLP) results were
scored by three experienced and independent investigators who
were blinded to the participant’s data.
Statistical analysis
Data normality was assessed using the Kolmogorov-Smirnov
test, and all of the variables showed a normal distribution. The
results are reported as means and standard deviations (6SD). A
X2 test was used to verify that the genotype frequencies were in
Hardy-Weinberg
equilibrium.
The
effects
of
the
COL5A1
genotypes in the analyzed variables were tested using a one-way
analysis of variance (ANOVA). The significance level was set at
p,0.05. All of the statistical analyses were performed using
Statistica 8 (StataSoft Inc., Tulsa, OK, USA).
Results
Genotype distribution and sample characteristics
The
genotype
distribution
attained
the
Hardy-Weinberg
Equilibrium,
as
evidenced
by
the
X2
test.
The
genotype
frequencies were TT = 27.9%, CT = 55.8% and CC = 16.3%.
The
genotype
distribution
of
the
COL5A1
rs12722
gene
polymorphism was similar to the distribution reported in the
public databases for Caucasian populations (http://opensnp.org/
snps/rs12722). In accordance with the mean values of the IPAQ-
SV outcomes, the subjects of the three groups were classified as
moderately active [31]. There were no differences in age,
anthropometric characteristics, or physical activity levels among
the CC, CT, and TT genotypes of the COL5A1 gene (p.0.05)
(table 1).
Maximal incremental, running economy, and range of
motion tests
Table 2 shows the mean values of the physiological variables
measured during the maximal incremental test. There were no
significant differences in
:VO2 max , HRMAX, and [La]peak
between individuals with different COL5A1 genotypes (p.0.05).
Figure 1 shows the results of the constant-speed running and sit-
and-reach
tests.
The
RELW
(p = 0.232)
(panel
A),
REHG
(p = 0.259) (panel B), and ROM (p = 0.337) (panel C) were not
Table 1. Anthropometric characteristics and physical activity levels of the subjects in the three genotype groups.
CC (n = 24)
CT (n = 84)
TT (n = 42)
P values
Age (years)
25.763.7
21.364.2
23.865.0
0.873
Body mass (kg)
80.5610.7
76.169.9
75.2610.4
0.230
Height (cm)
177.865.4
172.666.5
174.265.8
0.243
Body fat (%)
14.363.8
13.264.2
13.964.6
0.584
IPAQ-SV (score)
12916237
13566289
13336301
0.605
Data are means 6 standard deviations. IPAQ-SV: short version of the international physical activity questionnaire. There were no differences between the groups.
doi:10.1371/journal.pone.0106581.t001
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statistical
different
between
the
CC
(RELW = 35.976
3.18 ml?kg21?min21; REHG=40.9864.59 ml?kg21?min21; ROM=
26.1468.34 cm), CT (RELW=36.0362.93 ml?kg21?min21; REHG=
41.8063.36 ml?kg21?min21;
ROM=27.8568.22 cm),
and
TT
(RELW=37.6563.37 ml?kg21?min21; REHG=42.6663.79 ml?kg21?min21;
ROM = 27.0866.88 cm) COL5A1 genotypes groups.
Discussion
Previous findings suggested that the COL5A1 gene might be a
marker of endurance running performance [24,7]. It has been
speculated that the superior running ability of individuals with a
TT genotype could be explained by a greater RE when compared
with individuals with at least a C allele [8]. However, it is
important to notice that these studies did not investigate the
relationship between the energetic cost of running and COL5A1-
genotypes because the subjects did not perform constant-speed
tests to measure the RE. To the best of our knowledge, this is the
first study designed to analyze the relationship between a common
C to T single-nucleotide polymorphism gene within COL5A1 gene
(rs12722) and RE. The major findings of this study show that
theCOL5A1 genotypes were not associated with either RE or
ROM.
It has been proposed that mechanical properties of connective
tissues are responsible for converting elastic energy to kinetic
energy free of metabolic cost [14]. It was demonstrated that more
economical subjects have a higher contractile strength and
compliance of the tendons and aponeuroses when compared with
their less economical counterparts [14]. Some studies have
suggested that the mechanical properties of tendons and ligaments,
which largely consists of collagen fibrils, may be genetically
determined [32,10]. In particular, the genetic variation in the
COL5A1 gene, which encodes type V collagen, may affect the
mechanical properties of tendons and ligaments through altering
the mechanical properties. It has previously been shown that the
COL5A1 gene variant investigated in this study was associated
with endurance running ability. Although the specific mechanisms
remain largely unknown, we hypothesised in this study that this
gene variant improves endurance running ability through an
improving running economy. However, the present findings did
not confirm the relationship between COL5A1 genotypes and RE.
Our results showed no significant differences in RELW between
individuals with different COL5A1 genotypes. This finding
suggests that the superior performance observed in individuals
with a TT genotype in the COL5A1gene (rs12722) cannot be
explained by a lower energy cost during running at a low
percentage of :VO2 max.
In the present study, we considered that a subject who is
economical at low relative running intensity might not be
economical at high relative running intensity. Our results
demonstrated that COL5A1 genotypes were not associated with
the energetic cost of running regardless of running intensity. An
alternative explanation for the relationship between COL5A1
genotypes and endurance running performance might be the
ability to produce force rather than a reduced energetic cost.
Recently, Kubo et al. [33] demonstrated that individuals with a T
allele had a higher stiffness of the knee extensors compared to
those individuals with at least one copy of the C allele. It was
previously
demonstrated
that
dynamic
muscle
actions
are
positively related to stiffness, possibly due a more effective force
transmission from the contractile elements to the bone [34]. In
turn, the ability to produce force has been considered an essential
determinant of endurance performance without being necessarily
related to RE [35,36]. This occurs because the horizontal
component of ground reaction force is fundamental for endurance
runners to attain high-intensity running speeds [35]. Thus,
individuals with a TT genotype may be able to maintain higher
running speeds during long-distance events than their counterparts
with a CT or CC genotype by applying greater forces to the
ground. Nevertheless, this hypothesis should be analyzed with
caution because we were unable to obtain ground reaction forces
Figure 1. Running economy, range of motion, and COL5A1
(rs12722) genotypes. Panel A: running economy at low intensity,
Panel B: running economy at high intensity, Panel C: range of motion.
There were no differences between the groups.
doi:10.1371/journal.pone.0106581.g001
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in the present study. Thus, further research is needed to examine
the underlying mechanisms determining the relationship between
COL5A1 genotypes and endurance running performance.
It has also been postulated that COL5A1 rs12722 genotypes
could alter the elasticity of tendons [10] and contribute to
explaining the inter-individual variation in ROM [36] additionally
to other polymorphisms (i.e. COL5A1 rs71746744) of this gene
[37]. However, conflicting results were reported in the literature
regarding the relationship between COL5A1 gene polymorphisms
and ROM. Some studies found that the CC genotype was
overrepresented in individuals with greater ROM [24], while
others found no relationship [25]. In the present study, the ROM
values between individuals with CC, CT, and TT genotypes were
not significantly different. This result is in agreement with the
earlier findings of Brown et al. [25] who found that COL5A1
genotypes in a South African cohort were not associated with
ROM in young subjects (,35 years). However, these authors
found a positive correlation between COL5A1genotypes and
ROM in older subjects (.38 years old) [26]. It is important to note
that besides our cohort consisting of younger subjects (25.264.0
years), a significant difference was not detected for age between
individuals with different COL5A1 genotypes. Taken together,
these findings reinforce the suggestion that COL5A1 rs12722
genotypes might interact with age for ROM in physically active
subjects [26].
It is important to acknowledge some of the limitations of the
present study. First, the subjects in the present investigate on were
characterized as physically active, as evidenced by the IPAQ-SV
outcomes. This would imply that our subjects might have a lower
capacity for endurance exercise than the trained endurance
runners that were previously studied [24,7]. Thus, caution should
be exercised in extrapolating these findings for highly-trained
endurance runners. Second, the present study was conducted on a
relatively small sample size. Therefore, our findings need to be
confirmed in a larger cohort of subjects. On the other hand, it is
important to notice that in the present study no differences for
physical activity levels, age, and anthropometric measurements
were observed among the three COL5A1 (rs12722) genotypes
(Table 1). In addition, our cohort was composed exclusively of
men. This seems to be especially important because training status
[38], age [39], body weight [27], and sex [36] all influence RE.
Therefore, it is reasonable to assume that most of the potential
confounding variables were controlled in the current study.
In conclusion, the results of the current study demonstrated that
variants within the COL5A1gene were not associated with RE and
ROM. This indicates that the previous relationship reported
between COL5A1 genotypes and endurance running performance
may not be mediated by the energetic cost of running. Therefore,
further studies are needed to examine the causal relationship
between COL5A1 gene and endurance running performance.
Author Contributions
Conceived and designed the experiments: RB LAP SB AEL-S PHS.
Performed the experiments: RB SB LAP M. Matsuda M. Marquezini.
Analyzed the data: M. Matsuda M. Marquezini RB SB LAP. Contributed
reagents/materials/analysis tools: M. Matsuda M. Marquezini PHS.
Wrote the paper: RB LAP SB AEL-S M. Matsuda M. Marquezini PHS.
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Table 2. Physiological variables measured during the maximal incremental test in the three genotype groups.
CC (n = 24)
CT (n = 84)
TT (n = 42)
P values
:VO2 max
(mL.kg21.min21)
47.165.2
47.466.1
47.665.8
0.966
HRMAX (bpm)
190610
18969
18967
0.940
[La]peak
(mmol.L21)
9.963.7
9.463.9
9.664.1
0.781
Data are means 6 standard deviations. :VO2 max: maximal oxygen uptake, HRMAX = maximal heart rate, [La]peak: peak of blood lactate accumulation. There were no
differences between the groups.
doi:10.1371/journal.pone.0106581.t002
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Is the COL5A1 rs12722 gene polymorphism associated with running economy?
Bertuzzi, Rômulo,Pasqua, Leonardo A,Bueno, Salomão,Lima-Silva, Adriano Eduardo,Matsuda, Monique,Marquezini, Monica,Saldiva, Paulo H