Can certain genetic markers be incorporated into an individual’s training programme, in order to improve athletic performance? By Zoe Skells

March 2015

1

Table of Contents

1: Improving Athletic Performance ............................................................................................... 2

2: Nature vs. Nurture ..................................................................................................................... 2

2.1: The 10,000 hour Theory ................................................................................................. 2

2.2: Case Study – Men’s High Jump Final, Osaka 2007 ......................................................... 4

3: Power Endurance Marker Genes ............................................................................................... 6

3.1: ACE gene ......................................................................................................................... 8

3.2: ADRB2 ........................................................................................................................... 10

3.3: ADRB1 ........................................................................................................................... 12

3.4: NRF1 ............................................................................................................................. 14

4: Injury Risk Genetics ................................................................................................................. 16

4.1: GDF5 ............................................................................................................................. 17

4.2: COL1A1 ......................................................................................................................... 18

5: Recovery Genetics ................................................................................................................... 21

5.1: NOS3 ............................................................................................................................. 24

5.2: IL-6 ................................................................................................................................ 25

6: Discussion ................................................................................................................................ 28

References ................................................................................................................................... 29

2

1: Improving Athletic Performance

Athletes are continuously looking for methods to develop and enhance their performance in

order to achieve their goals. As a consequence the enhancement of athletic performance is a

constantly changing field, with ideas and procedures being continuously introduced from areas

as diverse as; sports psychology, clothing and equipment, sports nutrition and hydration,

ergogenic aids and types of training.

Currently, many athletes are seeing the benefits on their performance from the use of

nutritional advice. An example that has made the headlines is Novak Djokovic, a tennis player

from Serbia who is currently ranked number 1 in the world and a winner of multiple grand

slams. In 2010, Djokovic changed his diet based on the advice given to him by Dr Igor

Cetojevic; up until this point he was world number 3 (and had been for two years) and only

had one grand slam title to his name (ATP, 2014). Djokovic was experiencing symptoms such as

nausea, shortness of breath and fatigue, similar to the individual in Leone et al (2005) case

study. Dr Cetojevic suggested that Djokovic should have a gluten-free diet; the results of

continuing with the diet were clear, Djokovic felt more energetic and more mentally focussed

than he had ever been (Mancini et al, 2011). Furthermore, as well as just feeling better in

himself, he is now comfortably world number one and has won an additional six grand slams.

Later blood tests demonstrated that Djokovic was indeed intolerant to wheat as well as dairy

products (Newman, 2013).

2: Nature vs. Nurture

The argument of nature vs. nurture in sporting ability and performance has been well debated

over the years (Davids & Baker, 2007). Initially, it was presumed that dedication and training

alone were the factors that made an athlete successful (Kalinowski, 1985; Monsaas, 1985;

Helson et al, 1998). However, since the human genome was sequenced, scientists and

researchers have begun to uncover certain genes that are substantial markers for elevated

sporting performance. It is now widely accepted that it isn’t one or the other, but a

combination and balance between an athlete’s natural talent and their training environment

(Myburgh, 2003).

2.1: The 10,000 hour Theory

Ericsson et al (1993) introduced the concept of deliberate practice and the 10,000 hour

theory. The concept behind it is that to become an expert in a particular field an individual

3

should undertake 10,000 hours of dedicated training on their specific area. Ericsson et al

(1993) carried out a retrospective study that focussed on three groups of young violinists –

with a mean age of 23.1 years old. The first group comprised of those with the potential to be

world-class soloists, the second those who were deemed to be good and the third those who

probably wouldn’t play professionally (likely to become music teachers). Their results showed

that all individuals from each of the three groups started playing at the age of 7.9 years old.

But, as they grew older the students from the first group started to practice for longer when

compared to the other two groups. By the age of 20, the performers from the first group had

totalled an average 10,000 hours of practice, individuals from the second group had totalled

8,000 hours and the students from the third group reached just over 4,000 hours. On the other

hand, Baker & Cote (2003) showed using a retrospective study that the average number of

practice hours for athletes involved in team ball sports to reach the their national team was

3,939 hours – where basketball players had completed more training hours (5,908.5)

compared to netball players who spent on average 2,260 hours in practice. This demonstrates

that an individual doesn’t necessarily have to complete 10,000 hours of deliberate practice to

become an expert.

More refined theories have since been published; Cote et al (2003) proposed that there are

three stages of sport involvement prior to the achievement of expert level performance –

sampling years, specializing years and investment years. During these stages, an individual’s

participation evolves from play-like to more structured, dedicated training sessions. The

foundation for this theory was based on a previous study carried out by Bloom (1985); he

observed that individuals go through three distinct periods to become experts in a particular

field – the early years, middles years and the later years. The early years consist of discovery

and exploration of the chosen field, which involves playing and external motivation; this stage

can last up to secondary school. The middle years are when individuals enhance their

understanding of the skills and the rules and regulations involved; they start to practice drills

and the use of tools or algorithms. Also, the individual’s motivation starts to become more

internal and usually lasts through secondary school. Finally, the later years is when individuals

start working towards becoming an expert in their chosen area, developing their own style and

interpretation. This particular stage usually commences in the later stages of secondary school

or into the start of university. This particular study focussed on six groups; Olympic swimmers,

world-class tennis players, concert pianists, sculptors, research mathematicians and research

neurologists. The individuals that participated in the study were at the top of their respective

4

fields; for instance the swimmers were members of the US Olympic team and the tennis

players had all achieved a top ten world ranking.

2.2: Case Study – Men’s High Jump Final, Osaka 2007

Stefan Holm is a Swedish high jumper and was Olympic champion in 2004. Holm was a firm

believer in the 10,000 hour rule and trained religiously for two decades. For a high-jumper

Holm was rather short at just 1.80m, therefore he spent hours in the gym and many more

perfecting his technique. At the 2007 world athletic championships high jump final in Osaka

Holm was the favourite, but among his competitors was Donald Thomas from the Bahamas

who had a very different build-up to the championships. Thomas got into high jump through

pure chance after taking on a bet from a fellow university student in America. Thomas was

offered a scholarship to Auburn University, where he started to complete dedicated high jump

training. A year later, Thomas also found himself at the final of the 2007 world championships.

Both men made it to what would be the final height of 2.35m along with two other

competitors. Thomas with his unorthodox technique and very short run-up managed to clear

the height at his first attempt. Thomas became world champion while Holm had to settle for

4th place (IAAF, 2014c).

A year later, it was shown that Thomas had abnormally long Achilles tendon for an individual

of his height, which would ultimately give him a slim advantage in an event like high jump. The

longer an Achilles tendon, the more power an athlete can gain from the ‘stretch-shortening

cycle’ (Kubo et al, 2000) (Komi, 2003) – so they can propel themselves further into the air.

Although Holm had an average length Achilles, his tendon became four times stiffer than an

average man’s through extensive training; meaning that his tendon was unusually powerful.

Strength and endurance training have been shown to elicit mechanical changes in tendons;

specifically and increase in the stiffness and the tensile strength of the tendon (Buchanan &

Marsh, 2002). However, regardless of the amount of training an individual may complete they

will not be able to change the length of their tendon significantly, only the stiffness of it.

Therefore, Thomas was always going to have a genetic advantage over someone like Holm.

Having said this, whilst Holm steadily improved his personal best over his career, Thomas even

with six more years of training couldn’t increase his personal best height above 2.35m, as

figure 1 demonstrates below.

5

Figure 1: Charting the best heights that both men achieved each year whilst competing (Adapted from

IAAF, 2014a & IAAF, 2014b).

This particular case study highlights some of the key aspects in the debate nature vs. nurture;

Thomas representing nature and Holm representing nurture at a simplistic level. It shows that

while ideal genetics gives an athlete a great foundation, training and hard-work is needed to

maintain the level as well as improving athletic performance.

2.05

2.1

2.15

2.2

2.25

2.3

2.35

2.4

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

Mar

k

Season

Holm

Thomas

6

3: Power Endurance Marker Genes

Endurance performance has been traditionally and will continue to be associated with three

key performance markers; maximal oxygen uptake, ventilatory anaerobic threshold and

running economy (Larsen, 2003). Maximal oxygen uptake is a measurement of the highest rate

at which the body can take up and utilise oxygen during prolonged and intense exercise

(Bassett & Howley, 2000) and is also known as maximal oxygen consumption or VO₂max. It is

considered as one of the key measurements of cardiovascular fitness (Taylor et al, 1955) and

unsurprisingly is highly influenced by the both the respiratory and cardiovascular systems. The

limiting factor to maximal oxygen uptake is the capacity of the cardiovascular and respiratory

systems to take in and transport oxygen, a process which is highly influenced by a variety of

factors; including alveolar ventilation, the rate of oxygen diffusion and the degree of blood

flow. Furthermore, the VO₂max value is highly dependent on the ability of exercising muscles

to receive and then utilise oxygen (Bassett & Howley, 2000).

Although a superior VO₂max is beneficial to an endurance athlete, it is vital for an individual to

maintain a high fraction of maximal oxygen uptake (%VO₂max) for a longer period of time

during exercise. An athlete with the capacity to sustain a high fraction of VO₂max for longer

postpones the metabolic acidosis that results from the accumulation of lactic acid in the

bloodstream. The ventilatory anaerobic threshold (%VO₂max) can be improved through

exercise training; these improvements are more significant than changes in VO₂max, as

VO₂max remains relatively constant regardless of the levels of training (Davies et al, 1981).

Burke et al (1994) demonstrated this with twenty-one physical education students; each

individual participated in a seven week training programme where the intensity of the exercise

increased every two weeks. At each session the subjects exercised to voluntary exhaustion.

Burke and colleagues observed a mean increase of 5.5% in VO₂max after the training

programme and a mean increase of 19% and 20.9% in ventilatory threshold and lactate

threshold, respectively; an increase in these variables results in enhanced aerobic capacity.

This study also showed a significant correlation between the ventilatory and lactate threshold,

regardless of training. Lactate production in the muscles increases in a curvilinear correlation

with increasing fractional utilisation of VO₂max; the level at which blood lactate increases

substantially is described as the individual’s lactate threshold (Ghosh, 2004). The lactate

threshold is widely considered has a key measure of endurance performance (Londeree, 1997;

Jones, 2006) and has been shown to be a better predictor compared to VO₂max in assessing

endurance performance in athletes (Coyle et al, 1988).

7

Running economy is defined as the required energy for a given velocity of submaximal

running, and is ascertained by measuring the steady-state of oxygen consumption and the

respiratory exchange ratio. It is an influential factor of endurance performance; as locomotion

during exercise induces an oxygen debt (Foster & Lucia, 2007). Di Prampero et al (1993)

observed that when individuals improved their running economy by 5%, it was accompanied

by a 3.8% increase in endurance running performance on average. Athletes with a better

running economy utilise less oxygen at the same steady-state speed when compared to

runners with poor running economy (Saunders, 2004); therefore they are considered more

efficient runners. In elite athletes with similar a VO₂max, running economy appears to be a

better marker for enhanced endurance performance (Conley & Krahenbuhl, 1980; Morgan et

al, 1989). Daniels (1985) found that runners with similar levels of VO₂max varied up to 30% in

their running economy. Figure 2 demonstrates the difference between an athlete with good

running economy and an athlete with poor running economy – both of whom were

international standard and possessed a similar VO₂max. The more efficient runner proved to

be a minute faster over 10km when compared to the individual with poor running economy.

Running economy is influenced by a number of factors including; maximal oxygen uptake,

training and technique, an individual’s biomechanics and their genetic composition (Saunders,

2004).

In recent times, it has become evident that African runners are dominant in middle to long-

distance running events (Figure 3); the East Africans, especially Kenyans have excelled in

middle-distance events (800–1500 m) and steeplechase, also alongside the Ethiopians in long-

distance races (5000m—marathon). Due to these results enquiries arise into which

mechanisms allow them to perform more efficiently in endurance based disciplines; it is

hypothesised that the athlete’s environment both during their upbringing and throughout

Figure 2: Comparison of oxygen

uptake (V˙O2) [mL/kg/min] in two

international calibre 10km runners,

one with good running economy

(subject 1) and the other with poor

running economy (subject 2)

(Saunders, 2004).

8

training, as well as their genetic composition are the foundation to the dominance observed.

Therefore, there is a need to understand which factors influence the three markers previously

mentioned.

Weston et al (2000) showed that African 10km runners had a significantly higher lactate

threshold and enhanced running economy when compared to their Caucasian counterparts in

sub-elite runners. Saltin et al (1995) have shown that there isn’t a significant difference in

maximal oxygen uptake between Kenyan and non-African athletes. This was also apparent in

untrained adolescents; Larsen et al (2003) showed that the average VO₂max in Kenyan boys

was 52.65mlKg ̄¹min ¹̄ compared with 51.7 mlKg ¹̄min ¹̄ observed in Danish adolescents

(Andersen et al, 1987). In addition Skinner et al (2001) demonstrated that there was similar

improvement in VO₂max following training in both white and black North Americans;

moreover, Weston et al (2000) showed black South African runners with similar 10km race

times to white South African runners had a lower VO₂max when compared to the white

runners. These findings suggest that whilst an increased VO₂max is important for improved

endurance performance, it is not necessarily the determining factor between elite endurance

athletes.

3.1: ACE gene

The ACE (Angiotensin 1-Converting Enzyme) gene was the first gene to be identified as a

marker for elevated performance over 15 years ago (Montgomery et al, 1998). The gene is

located on the long arm of chromosome 17 (17q23.3); it is 21Kb long and contains twenty-six

exons. The polymorphism of the ACE gene occurs at intron 16; in the insertion allele there are

287 extra base pairs, whereas in the deletion allele these base pairs are not present (Rigat et

al, 1990; Rieder et al, 1999). This particular polymorphism has been comprehensively

researched and shown to be a reliable marker of either power or endurance related

performance (Alvarez et al, 2000; Williams et al, 2000; Nazarov et al, 2001; Collins et al, 2004).

All-Time Top 20 (%) Asia

Kenya

South America

Africa (excl. Kenya)

Europe

Figure 3: Relative distribution (%) between the

continents of the all-time top 20 performances in

middle- and long-distance running for men in the

six major distances from 800 m to marathon

including steeplechase in June 2003. Black

Americans are regarded as Africans excluding

Kenyans (Adapted from Larsen, 2003).

9

As figure 4 demonstrates this particular gene encodes for an enzyme that catalyses the

conversion of angiotensin I to angiotensin II; which is a powerful vasoconstrictor and so

restricts the blood flow to the peripheral muscles (Ehlers & Riordan, 1989). Furthermore, there

is evidence that it also breaks downs bradykinin, which is an important vasodilator and has

contrasting effects to angiotensin II (Murphey et al, 2000).

Angiotensinogen

Renin

Angiotensin I Bradykinin Arterial Vasodilation

ACE Increased Muscle Glucose Uptake

Angiotensin II Inactive Fragments

Arterial Vasoconstriction

Increased Sympathetic Activity

Figure 4: The renin angiotensin system particularly showing (red arrows) the actions of ACE on

Angiotensin I and Bradykinin (Adapted from Rosendorff, 1996; Jones et al, 2002).

In the insertion (I) allele, due to the extra base pairs this allele is associated with lower ACE

activity (Danser et al, 1995). Reduced ACE activity levels means an increase in blood flow - as

the blood vessels are less constricted; there is also more efficient mitochondrial respiration

and improved contraction in both skeletal and cardiac muscle (Jones et al, 2002). These

changes are more beneficial to endurance athletes and the insertion allele has been shown to

be present at a higher frequency in endurance swimmers (Tsianos et al, 2004), rowers

(Gayagay et al, 1998) and long-distance runners (Myerson et al, 1999).

On the other hand, the deletion (D) allele doesn’t contain the extra base pairs; therefore ACE

activity is higher in cardiac tissue (Danser et al, 1995). Individuals with the DD genotype have

higher serum ACE levels when compared to both heterozygotes and those homozygous for the

I polymorphism; the I/D polymorphism accounted for 47% of the total variance observed

(Rigat et al, 1990). Higher serum ACE levels are a result of increased ACE activity in endothelial

cells, which secrete plasma ACE. Although the precise mechanism of the control of ACE

synthesis is yet to be determined, it is thought that genetic control is at the transcriptional

level (Costerousse et al, 1993). The increase in ACE activity causes exercise induced

hypertrophy of the left ventricle and an increase in left ventricular mass (Montgomery et al,

1997; Fatini et al, 2000). Furthermore, the D allele is associated with higher VO₂ max and

10

further strength gain in skeletal muscles with training (Folland et al, 2000). This associates the

D allele with more power-based sports (Williams et al, 2000) such as short-distance swimming

(Woods et al, 2001; Costa et al, 2009). Having said this, some studies (Taylor et al, 1999;

Rankinen et al, 2000) show that there isn’t any significant association between the ACE

polymorphism and athletic performance. Amir et al (2007) found there to be an association

between the DD genotype and elite endurance athletes from Israel, which contradicts the

findings of the studies previously mentioned. One reason behind the differing results from

Rankinen et al (2000) study could be due to some of the participants; 42 individuals compete

in either Nordic combined or the biathlon. Both these sports comprise of an aerobic element –

cross-country skiing but also ski-jumping or rifle shooting respectively. Undoubtedly the

competitors for these events need a large aerobic capacity; but these sports are not pure

endurance disciplines, as they require other qualities in order to achieve success during the

ski-jumping or rifle shooting phases. Therefore, this could explain why their particular alleles

are not demonstrating similar patterns to models previously mentioned (Myerson et al, 1999;

Jones et al, 2002).

3.2: ADRB2

The adrenergic receptor 2 (ADRB2) gene belongs to the G protein-coupled receptor

superfamily and codes for beta-2 adrenergic receptor. The gene is located on chromosome five

at position q31-q32; it is just over 2Kb long and contains one exon. ADRB2 binds primarily to

epinephrine and regulates vasodilation along with ventricular function (Snyder et al, 2008). It

also plays an important role in conserving blood glucose levels via stimulating glycogenolysis

during sustained exercise (Wolfarth et al, 2007). The ADRB2 are prone to desensitisation

following prolonged stimulation; this is hypothesised to be a protective mechanism against

possible organ damage through stress from over-activity of the receptor (Snyder et al, 2008).

Stimulation of ADRB2 can activate the mechanisms that regulate cardiac growth and

remodelling; therefore, possibly influencing cardiovascular functions and structure. ADRB2 can

also be found in type I and type II alveolar cells; they play a vital role in bronchodilation and

lung fluid clearance. It was hypothesised that during prolonged, heavy exercise these

mechanisms are enhanced; leading to improved alveolar ventilation (Snyder et al, 2006b).

There are 4 different variants of the gene that have been studied. The first of these is an

arginine (Arg)-to-glycine (Gly) substitution at codon 16, where a substitution from G to A

(rs1042713; +46G/A) can occur (Snyder et al, 2008). Individuals homozygous for Arg16 are

hypothesised to have lower baseline receptor function (Snyder et al, 2006a). The Arg16 variant

11

is associated with a decrease in blood pressure and an increase in VO₂max (Wolfarth et al,

2007), which are good markers for elite endurance performance; however, pulmonary

recovery to resting levels after exercise is relatively slow. Furthermore, the Arg allele has been

associated with an increased resistance to agonist-mediated desensitisation when compared

to the Gly allele (Snyder et al, 2008). Also, Snyder et al (2006c) observed that individuals who

were homozygous for Arg16 had 29% lower lymphocyte ADRB2 density when compared to

Gly16 subjects. Moreover, they found that ADRB2 density on lymphocytes was positively

correlated with cardiac function at rest in both the Arg16 and Gly16 groups. Individuals

homozygous for Gly16 have been shown to have an increased stroke volume and cardiac

output when compared to Arg variants in normal, healthy populations (Eisenach et al, 2005;

Snyder et al, 2006a). This trend was seen at rest, during exercise and following exercise during

the immediate recovery period; with both isometric (Eisenach et al, 2005) and isotonic

exercise (Snyder et al, 2006a). Moreover, Tang et al (2003) showed that individuals with the

Gly16 variant had an enhanced left ventricular function, explaining the increase in cardiac

function observed in the studies previously mentioned. In addition, individuals with the Gly16

variant observed prolonged bronchodilation following heavy exercise in comparison to the

Arg16 variants (Snyder et al, 2006b).

Furthermore, the second variant is a glutamine (Gln)-to-glutamate (Glu) substitution at codon

27, where there can be a substitution from C to G (rs1042714; +79C/G). Gln27 is associated

with fat burning, a higher VO₂max and therefore endurance. This is the opposite of Glu27,

which is associated with improved ADRB2 responsiveness and resistance to desensitisation

(Dishy et al, 2001) and much more closely linked with muscle growth and power (Ferec, 2014).

Significant linkage disequilibrium exists between the two polymorphisms described

previously; when Arg16 is present, normally at position 27 only glutamine is observed

(D’amato et al, 1998; Drysdale et al, 2000; Taylor & Kennedy, 2001). Dishy et al (2001)

propositioned that Gly16-Glu27 is the ideal haplotype combination for cardiovascular response

during short-term exercise; as this haplotype demonstrates enhanced stroke volume, cardiac

output and raised blood pressure. Sawczuk et al (2013) demonstrated this in a Polish

population; the Gly16-Glu27 was identified in 52.5% of the top-elite power athletes and 50% in

the sub-elite power athletes, compared to the elite endurance athletes and controls – 43.9%

and 41.5% respectively.

12

3.3: ADRB1

This gene encodes for an adrenergic receptor; which is also a G protein-coupled receptor that

is primarily located in cardiac tissue. The 1-adrenergic receptor (ADRB1) gene is located on

chromosome ten at position q25.3; the gene is 2.8Kb long and contains one exon. In a similar

way to ADRB2, ADRB1 mediates the physiological effects of both epinephrine and

norepinephrine. Stimulation of ADRB1 increases heart rate and ventricular performance

through enhancing myocardial contractility. 1-adrenergic receptors are vital components in

the regulation of the cardiac system and specifically cardiac output; therefore, ADRB1 has the

potential to influence aerobic capacity (Mason et al, 1999; Defoor et al, 2006).

At amino acid position 389, an arginine (Arg)-to-glycine (Gly) substitution can occur

(rs1801253; +1165C>G) (Maqbool et al, 1999). Subjects with the Arg389 variant showed

greater coupling to G-proteins resulting in better activation of the effector mechanisms

(Mason et al, 1999); which could increase cardiac output by stimulating contractile activity of

the heart. In 2004, La Rosée et al (2004) supported this observation by demonstrating an

increase in cardiac contractility in response to catecholamines in subjects with the Arg389

allele. Mason et al (1999) also observed that subjects with the Gly389 variant had significantly

lower levels of agonist stimulated activity. Furthermore, as figure 5 illustrates Arg389

homozygotes had increased peak VO₂ and consequently increased exercise time in heart

failure patients (Wagoner et al, 2002). Although this particular investigation was not carried

out in healthy population, the polymorphisms observed in the ADRB1 gene occur within the

general population as regularly as they do in heart failure patients; therefore, there is still

potential for the gene to be a potential marker for endurance performance.

Figure 5: Showing the different

responses to exercise in heart failure

patients with regards to the

polymorphism at amino acid position

389. Asterisk, P=0.006; dagger,

P=0.04 versus homozygous Gly389

(Wagoner et al, 2002)

13

A second polymorphism at amino acid position 49 (rs1801252; +145A/G) a serine (Ser)-to-

glycine (Gly) substitution occurs (Maqbool et al, 1999); affecting expression of the receptor.

Rathz et al (2002) observed that the Gly49 variant was more susceptible to agonist-promoted

down-regulation. Furthermore, Defoor et al (2006) demonstrated that in coronary artery

disease (CAD) patients those who were Gly49 homozygotes had a significantly higher peak

oxygen uptake at baseline when compared to heterozygotes and the homozygous Ser49

individuals. After three months of physical training, on average all three groups improved from

their initial values, but the Gly49 homozygous group still had a higher peak oxygen uptake.

Following on from this particular finding, Sawczuk et al (2012) showed that the presence of the

49Gly allele was significantly higher in endurance athletes than in the control group in a Polish

population. In addition, the Ser49Gly polymorphism is significantly associated with resting

heart rate; Ranade et al (2002) showed that individuals homozygous for the Ser49 allele had a

higher mean heart rate when compared to both heterozygotes and Gly49 homozygotes (Figure

6).

Figure 6: Cumulative distributions of heart rate, by Ser49Gly genotype. The solid line represents the

values for Ser49 homozygotes, the dotted line indicates results for Ser49Gly heterozygotes, and the

dashed line shows results for Gly49 homozygotes. The percentage of individuals with heart rates

lower than a certain value can be read off the Y-axis (Ranade et al, 2002).

In addition, haplotypes of ADRB1 have been studied; Defoor et al (2006) found that the most

common haplotype in their population was Ser49Arg389 (53.1%). Patients with the

homozygous Gly49Arg389 allele combination had significantly elevated aerobic power at

baseline when compared to individuals with the Ser49Gly389 and Ser49Arg389 homozygous

allele combinations. In agreement with this, the Gly49Arg389 haplotype was significantly over-

14

represented in the endurance athletes’ subgroup when compared to the controls (Sawczuk et

al, 2012).

Based on the physiological evidence and the related medical studies (Wagoner et al, 2002;

Defoor et al, 2006; Brodde, 2008), it is theorised that endurance athletes could benefit from

harbouring the Gly49Arg389 haplotype. As the haplotype combination enhances the

mechanisms that cause an increase in cardiac output and reduction in peripheral vascular

resistance, resulting in improved blood flow to the exercising muscles. These characteristics

are all highly influential in determining the duration and quality of performance over a

prolonged period of exertion.

3.4: NRF1

The Nuclear Respiratory Factor 1 (NRF1) gene is located on chromosome seven at position

q32; it is 145.4Kb and contains twelve exons. NRF1 stimulates the increase in skeletal muscle

mitochondria; this allows an increased capability to produce ATP as well as enhancing an

individual’s respiratory capacity (Hood, 2001; Baar, 2004). NRF1 (along with NRF2) directly

regulates the expression of several electron transport chain proteins and therefore increases

the capacity for oxidative phosphorylation; this results in a higher rate of ATP production

(especially during exercise). It has been shown that an overexpression of NRF1 is associated

with an increase in the levels of cytochrome c and GLUT4 protein (Baar et al, 2003).

Cytochrome c is a vital component of the electron transport chain in the mitochondria, where

it transports an electron; therefore, it is an important protein for the correct functioning of

aerobic respiration. An increase in the expression of GLUT4 was unexpected, as there was no

known NRF1 recognition sites; Baar et al (2003) did find a significant increase in myocyte

enhancer factor 2A (MEF2A) in NRF1 transgenic muscle, which could help to explain the

increase observed in the levels of GLUT4. The increase with GLUT4 protein levels correlated

with increase in blood glucose levels observed in the study; both increased 2 fold.

To date, three polymorphisms have been researched, two of which have shown promising

findings. There is a SNP in the 5’ untranslated region (rs6949152) where an A to G substitution

can occur. In addition, within intron 11 (rs240790) there is a C to T substitution. He et al (2008)

observed that individuals with the CC genotype (rs240790) had an increased VO₂max at

ventilatory threshold both at baseline and after training; also individuals with the AA genotype

(rs6949152) had increased VO₂max at ventilatory threshold in response to exercise training.

As well as the ventilatory threshold responses, both the homozygous CC genotype at rs240790

and AA genotype at rs6949152 are beneficial for increased lean body (He et al, 2008). Even

15

though this study found no association between NRF1 genotype and overall VO₂max, the

findings could still prove useful. In individuals that participate in endurance training, aerobic

adaptations occur; this includes improvements in the ventilatory threshold. Furthermore,

VO₂max is largely influenced by the delivery of oxygen to muscles rather than the ability of

muscle mitochondria to utilise oxygen (Wagner, 2000); therefore providing a possible

explanation for the lack of association between NRF1 and VO₂max. Furthermore, the CC

genotype is associated with more efficient running economy; which as previously mentioned is

an influential factor in enhanced endurance performance.

16

4: Injury Risk Genetics

Reducing the prevalence and incidence of injuries in sport has become one of areas at the

forefront of sports medicine research. In 2001, Jacques Rogge, the president of the

International Olympic Committee (IOC) stated that ‘‘the most important goal of the IOC

Medical Commission is to protect the health of the athlete’’ (Renstrom et al, 2008). Commonly

sporting injuries come from overuse and exerting excessive force upon certain parts of the

body; many of which are caused by tendinopathies. Tendinopathy is a term that encompasses

inflammation and small tears in the tendon; these are frequently caused by overuse and

ageing. These injuries are often debilitating and can cause athletes to retire early from their

respective sports; out of nine athletes with Achilles tendinopathy (two competitive and seven

recreational athletes) included in a study (de Mos et al, 2007), three of them reduced their

sporting activities while the other six had to stop completely. The tendons usually more

vulnerable to overuse injuries are the cruciate ligaments, Achilles, posterior tibialis and rotator

cuff (Maffulli et al, 2003; Rees et al, 2006). Marshall et al (2007) showed that approximately

200,000 individuals in the USA alone suffer from anterior cruciate ligament (ACL) ruptures

annually and that the risk of ACL rupture in elite athletes is up to ten times higher when

compared to recreational athletes.

Previous studies have alluded to the possible genetic factor to the risk of developing

tendinopathy. Hakim et al (2003) estimated a heritability of 40% for tendinopathy at the

lateral epicondyle using a twin study; comprising of monozygotic twin pairs and dizygotic twin

pairs. Heritability was estimated using logistic regression analysis based on DeFries–Fulker

regression model (Sham et al, 1994). The lateral epicondyle is an important structure in the

elbow and provides attachment for ligaments and tendons. Furthermore, it is one of the

structures that can be badly damaged through overuse and is frequently associated with the

injury colloquially known as tennis elbow (Hakim et al, 2003). Harvie et al (2004) identified a

strong genetic influence over rotator cuff tears using a sibling study; where an individual was

five times more likely to develop symptoms associated with a rotator cuff tear if their sibling

had previously presented the symptoms, which could not be clarified by environmental factors

alone. The controls used in the study were the patient’s spouses, as they share similar

environmental risk factors with the patient during adulthood; whereas, the siblings

experienced the same environment during childhood. The use of controls helps to minimise

the effect of environmental factors.

17

There are currently treatments available to athletes in order to help stimulate recovery from

tendinopathy, particularly heavy load exercise (Kountouris & Cook, 2007). Bahr & Krosshaug

(2005) put forward the concept of personalised training programmes in order to reduce the

risk of injury, especially at the joints. Having said this, in order for the training to be successful

a multi-factorial approach should be undertaken to incorporate all factors that could increase

the incidence of an injury; therefore understanding genetic markers associated with the

prevalence of sporting injuries is important to the success of a personalised training

programme.

4.1: GDF5

Growth Differentiation Factor 5 is a member of the TGF- superfamily and closely associated

with the bone morphogenetic protein (BMP) family. GDF5 is located on chromosome 20 at

q11.2; the gene is 8.04Kb in length with four exons. GDF5 is involved in the regulation of the

growth and development of cartilage and bone (Chapman et al, 2008). More importantly in

this case, it plays a role in the healing of joint and soft tissue; therefore it holds an influence

over the liability of an individual becoming injured and their ability to recuperate from them. A

known SNP in the 5’ untranslated region (+140T/C; rs143383) has been identified as a possible

marker for osteoarthritis (OA) and sporting injuries – Achilles tendon pathology and anterior

cruciate ligament (ACL) damage. There is evidence to suggest that this polymorphism affects

the expression levels of GDF5 in numerous connective tissues (Egli et al, 2009) through

decreasing transcriptional activity by significantly reducing promoter activity (Miyamoto et al,

2007).

The T allele (rs143383) has been linked with a decreased expression of the GDF5 protein –

27% lower expression when compared to the C allele (Southam et al, 2007). Posthumus et al

(2010) demonstrated that an individual with the TT genotype has double the risk of acquiring

Achilles tendon pathology (Achilles tendinopathy and/or Achilles tendon rupture) in Australian

and South African populations. This agrees with Wolfman et al (1997) who first suggested a

possible role for GDF5 in ligament and tendon biology. They theorised that GDF5 (along with

GDF6 and GDF7) influence the differentiation of connective tissue precursors into soft tissue

forming cells; therefore, GDF5 could potentially aid in the repair and regeneration of ligament

and tendon injuries. Studies carried out in different populations around the globe show that

this particular SNP has relevance world-wide; both Asian (Miyamoto et al, 2007;

Tawonsawatruk et al, 2011) and European (Southam et al, 2007; Evangelou et al, 2009; Valdes

et al, 2009) cohorts have shown significant association between the SNP (rs143383, +140T/C )

18

and osteoarthritis (OA) susceptibility. Egli et al (2009) broadened the analysis of the SNP

association with OA risk to other soft tissues within the synovial joint, presenting similar

results. Their findings demonstrate that osteoarthritis risk mediated by this particular locus

isn’t just restricted to cartilage but potentially joint-wide. Pan et al (2014) carried out the

largest meta-analysis to date, compromising of 20 different studies and 23,995 subjects in

total; their findings were consistent with previous studies showing a significant association

between the T allele and OA risk. As well as statistical association of the GDF5 SNP, there is

also evidence of mechanistic involvement with this particular SNP (rs143883). Mikic et al

(2001) demonstrated that GDF5-deficient tendons contained 40% less collagen and were

therefore significantly weaker in mice; they also observed impaired tendon healing.

In contrast, Raleigh et al (2013) found no association between the SNP (rs143883) and

anterior cruciate ligament (ACL) rupture. Having said this, the data obtained could prove useful

in other aspects. As previously mentioned the SNP has been associated with Achilles tendon

pathology (Posthumus et al, 2010) and decreased collagen content in tendons (Mikic et al,

2001); possibly highlighting a vital difference between tendon and ligaments and their relation

to the predisposition of sport related injury. This indicates that alterations in the expression of

GDF5 are not as influential on ACL rupture risk in Caucasians. Although further studies should

investigate this lack of association in other ethnic groups to confirm the findings; the research

gathered could be invaluable for designing injury prevention models in the future, specific to

ligament and/or tendon injuries.

In addition, the T allele (rs143883) has also been associated with a small decrease in overall

height (Sanna et al, 2008). In Finnish and American populations, the presence of a C allele

equated to an increase in height by 0.697cm; along with an increase in height of 0.546cm per C

allele in an Italian population. In all three populations the allele frequency was between 0.4

and 0.5 for the C allele. This follows on logically from the decreased GDF5 expression observed

in the T allele, which would lead to decreased limb bone growth; therefore, resulting in

decreased stature. Currently, decreased stature is seen as a disadvantage in most sporting

disciplines, especially in sports where stride length is important.

4.2: COL1A1

Collagen Type-1 Alpha-1 is located on chromosome 17 at q21.33 and is 18,344 bases long

consisting of 51 exons. COL1A1 encodes for an important protein that makes up type 1

collagen, which is the most copious form of collagen in the body (Garcia-Giralt et al, 2002).

COL1A1 along with COL1A2 encode collagen I1 and collagen I2 polypeptides respectively;

19

these polypeptides then associate in a 2:1 ratio to establish collagen type 1, which provides

structural stability to ligaments and tendons (Khoschnau et al, 2008). Within the first intron in

the COL1A1 gene a functional Sp1 binding site polymorphism (rs1800012; -1997G/T) can occur

(Mann et al, 2001).

The T allele enhances the affinity for the transcription factor Sp1 resulting in increased

transcription and therefore higher expression of COL1A1; which increases the production of

collagen type-1 alpha-1 (Collins & Raleigh, 2009). This over production of COL1A1 hinders the

formation of collagen type 1, as the ratio is no longer 2:1; resulting in weaker bone and soft

tissue formation. Khoschnau et al (2008) found that individuals with the TT genotype were

underrepresented in the injury group, both in cruciate ligament (CL) ruptures and shoulder

dislocations in a Swedish population; by identifying only one individual with the TT genotype in

both of the groups. They found that individuals with the rare TT genotype had a reduced risk of

injury of up to 85% when compared to the GG genotype. A similar study, obtained results

consistent with Khoschnau et al (2008) findings in a South African population demonstrating

an association between the SNP and ACL ruptures (Posthumus et al, 2009a). As figure 7

demonstrates the TT genotype is not present in the ACL or Achilles rupture (RUP) group,

suggesting that the TT genotype has a role in the protection against soft tissue ruptures.

Moreover, comparable TT genotype frequencies were observed in the control subjects from

both of the studies - South African (4.7%, n = 256) and Swedish (3.7%, n = 325), this is in

agreement with the genotype frequencies reported in larger control populations (Mann et al,

2001). Whereas, the G allele is highly represented in all categories this implies that carriers of

the G allele are at an increased risk of developing ligament injuries. Ficek et al (2013)

demonstrated that the GT genotype is associated with a reduced risk for anterior cruciate

ligament rupture. Furthermore, the study showed that the TT genotype is less frequent in the

anterior cruciate ligament rupture group – although this result was not statistically significant.

20

Figure 7: The relative genotype frequencies of the functional sp1 binding site polymorphism within

intron 1 of the COL1A1 gene (a) in the South African control (CON), ACL rupture (ACL), chronic Achilles

tendiopathy (TEN), Achilles rupture (RUP); (b) Swedish control (CON), cruciate ligament rupture (CL),

shoulder dislocations (Shoulder) groups (Collins & Raleigh, 2009).

Having said this, although Posthumus et al (2009b) identified no association between the

polymorphism (rs1800012) and Achilles tendiopathy; they couldn’t exclude the possibility that

other polymorphisms within the gene were associated. Other studies have demonstrated a

connection between over expression of type 1 collagen and tendinotic tissue (Ireland et al,

2001; de Mos et al, 2007); both studies used paired tendon specimens from patients

undergoing surgery for Achillles tendinopathy. One tissue sample was from the affected

tendinotic lesion and the other from adjacent healthy tissue; moreover, de Mos et al (2007)

used three healthy controls. Ireland et al (2001) only reports an up-regulation in gene

expression if the difference from normal tissue was equal or greater than a two-fold increase.

In addition, Bell et al (2012) observed an association between the TT genotype and Genu

Recurvatum (knee hyperextension). GR is caused by ligamentous laxity, especially in the ACL

and can lead to knee OA. This finding is inconsistent with the previously discovered protective

role and currently there is no accepted explanation. One theory is that the alteration in the

ratio of collagen I1 and collagen I2 polypeptides has differing effects on ligament strength

and density when compared to bone.

21

5: Recovery Genetics

As well as identifying genes that act as direct markers for endurance and power ability; genes

that are associated with recovery from injury are also important. Currently in most sporting

disciplines the number and length of competitions and tournaments has increased significantly

over recent years; adding to the intensity of training regimes, and reducing or shortening rest

periods. It is vital that an athlete and their coaching team manage the training schedules

carefully, anticipating the goal of multiple and long term performance peaks Therefore, it is

vital that an athlete and their coaching team manage the time they have sensibly; this means

allowing adequate time for recovery.

Sporting activities frequently cause direct (mechanical) trauma to the skeletal muscles

through a number of mechanisms; including strains, contusions and in some cases lacerations.

After injury the muscle goes through three distinct phases of healing; 1) degeneration and

inflammation, 2) regeneration and 3) fibrosis – the formation of scar tissue (Figure 8) (Huard et

al, 2002). The first phase commences within minutes of the trauma and can continue for over

a week. During the phase localised swelling and necrosis of muscle tissue occurs, as well as the

infiltration of activated macrophages and T-lymphocytes into the injured tissue. This then

stimulates the secretion of substances such as cytokines to accelerate the inflammation

response (Hurme et al, 1991). The regeneration phase initiates the release of growth factors,

which stimulate the activity of satellite cells; these cells are vital components in the process of

muscle regeneration after injury. The satellite cells are located between the basal lamina and

the sarcolemma, these structures often loose integrity through mechanical trauma; as a

consequence satellite cells proliferate (Huard et al, 2002). The mechanism is localised, where

the proliferated satellite cells generate myoblasts that eventually mature into mature muscle

fibres; this process can continue for up to ten days depending on the severity of the injury

(Hurme & Kalimo, 1992). Once regeneration has reached its peak activity, the formation of scar

tissue commences (Figure 8).

22

1 2 3 4

Weeks after Injury

Figure 8: The different stages of muscle healing after muscle injury. The initial phase is muscle

degeneration and inflammation, which occurs within the first minutes and continues for up to one to

two weeks after injury. Muscle regeneration begins in the first week post-injury and peaks at two

weeks post-injury. Fibrosis commonly commences at two weeks post-injury and increases gradually

for up to four weeks post-injury (Adapted from Huard et al, 2002).

Exercise itself (other than injury) induces a number of responses from different metabolic

processes, both short-term and long-term in response to acute and chronic exercise training

(Figure 9). Short-term responses usually consist of hypertrophic growth and the provision of

substrates to modulate contractile force during acute bouts of exercise (Williams & Neufer,

1996). Hypertrophic growth involves a non-specific increase in the abundance of most protein

components in the muscle fibres; allowing the muscle a greater capacity for peak force

generation. Whereas, long-term adaptations include an increase in the transcription and

mRNA content of specific genes; increasing the synthesis rate of certain proteins involved in

metabolism. Peroxisome proliferator activated receptor co-activator 1alpha (PGC-1) is a

transcription coactivator that plays a central role in the regulation of cellular energy

metabolism; with increased transcription levels observed following exhaustive exercise

(Pilegaard et al, 2003). This finding suggests that PGC-1 may play a crucial role in coordinating

the activation of metabolic genes in human muscle in response to exercise; as PGC-1 induces

mitochondrial biogenesis through interaction with NRF-1 and PPARs (Baar, 2004).

Mitochondrial biogenesis in skeletal muscle is thought to be a consequence of the cumulative

effects of brief increases in mRNA levels that encode mitochondrial proteins after successive

exercise sessions (Williams & Neufer, 1996; Pilegaard et al, 2000). In agreement with this,

Perry et al (2010) demonstrated that mitochondrial DNA increased after 24 hours following a

third session of exercise and continued to increase; whilst PGC-1α mRNA levels increased more

than 10-fold within four hours following exercise but then returned to pre-exercise levels 24

hours into recovery. Mitochondrial biogenesis leads to an increase in the muscle’s respiratory

and ATP production capacity, enhancing the efficiency of muscular contraction. Mitochondrial

Re

lati

ve A

mo

un

t o

f Ti

ssu

e

Red Area = Inflammation

Green Area = Regeneration

Blue Area = Fibrosis

23

biogenesis aids in the process of re-modelling in skeletal muscles; where myofibrils do not

enlarge but are reorganised, through selective activation or repression of genes. These

mechanisms result in a muscle that is more resistant to fatigue during prolonged periods of

repetitive contractions (Williams & Neufer, 1996). The molecular responses often remain

elevated or increase continually for a number of hours after the cessation of exercise;

furthermore, they are highly influenced by the duration and the intensity of the exercise

(Hildebrandt et al, 2003). These continued raised levels of proteins suggest that this is the

duration of time needed for molecular adaptations in skeletal muscles towards exercise to

take place. These adaptations are vital for improvement in athletic performance, as they lead

to an increase in the muscle’s capacity to produce ATP among the other improvements

previously mentioned; therefore allowing time for the molecular adaptations to occur is

beneficial to the athlete. Furthermore, the molecular recovery from exercise is affected by

other metabolic alterations in skeletal muscle; including muscle glycogen content. By reducing

the content of muscle glycogen before the start of exercise, there appears to be an elevation

of exercise-induced transcriptional activation in exercise responsive genes (Keller et al, 2001).

Figure 9: Schematic representation of changes in mRNA expression (bottom panel) and protein

content in skeletal muscle (middle panel) over time as a consequence of acute exercise and chronic

(repetitive) exercise training. Training-induced changes in protein content or enzyme function alter

metabolic responses to exercise at the level of substrate metabolism, resulting in improved exercise

performance (upper panel) (Egan & Zierath, 2013).

24

The processes of recovery are closely linked with the concept of injury susceptibility and a

recovery period is often utilised by coaches and athletes to either help repair the damaged

caused or to aid in preventing the occurrence of injury. Research into this area isn’t as

advanced as in other topics related to sports performance, but some genes have been

identified that show an association with the ability of an individual to recover from exercise.

5.1: NOS3

The NOS3 (Nitric Oxide Synthase 3) gene also known as the endothelial nitric oxide synthase

(eNOS) gene, is located on chromosome 7 (position q36); it is approximately 23.5Kb long and

contains twenty-nine exons. NOS3 synthesises nitric oxide (NO) from the amino acid L-arginine

in the endothelial cells (Ignarro, 1989). At rest, nitric oxide is continually released at small

levels from the endothelium; it aids in the maintenance of basal vascular tone and structure in

both the coronary and peripheral circulation (Maiorana et al, 2003). Nitric oxide is a potent

vasodilator with a short half-life in the blood of a few seconds (Ignarro, 1989); NO is lipid

soluble and rapidly diffuses into the tunica media, where it binds to the enzyme guanylate

cyclase (Moncada et al, 1988). The activation of soluble guanylate cyclase stimulates the

production of cyclic guanosine monophosphate (cGMP); the increase in cGMP causes the

increase in smooth muscle relaxation and therefore vascular dilation (Ignarro, 1989; Maiorana

et al, 2003). Nitric oxide is a central cellular signalling molecule and mechanical stimuli; nitric

oxide signalling is greatly involved in maintaining muscle integrity and correct signalling

systems while metabolic adaptations occur. During exercise, there is a significant increase in

muscle blood flow and vascular laminar shear stress; both these factors are important stimuli

for the adaptation in the endothelium. Stress exerted on endothelial cells stimulates up-

regulation of NOS3 activity, resulting in increased NO production and bioavailability (Haram et

al, 2008; Francescomarino et al, 2009). The bioavailability of NO depends on the sensitivity of

the target tissue as well as oxidative stress-mediated destruction of NO (Higashi & Yoshizumi

2004; Rush et al, 2005). After moderate bouts of exercise over weeks and months the

responsiveness of the endothelium-dependent vasodilator function can be enhanced; mostly

resulting from the increased expression of NOS3 (Maiorana et al, 2003). Nitric oxide is also

involved in the modulation of oxygen consumption in skeletal muscles (Wilkerson et al, 2004)

and human skeletal muscle glucose uptake during exercise (McConell et al, 2006). In addition,

NO enhances vascular dilation further by suppressing the production of potent

vasoconstrictors – including endothelin and angiotensin II; these vasoconstrictors stimulate

vascular smooth muscle cell proliferation. Therefore, if there is a reduction in NO production,

25

the activity of vasoconstrictors increases leading to heightened vessel reactivity (Duncker &

Bache, 2008).

There is a SNP at position -786T/C (rs2070744) of the NOS3 gene; individuals with the T allele

leads to higher gene transcription; individuals carrying the C allele showed a 52% reduction in

promoter activity (Nakayama et al, 1999); therefore reducing endothelial production of NO in

coronary arteries. Dosenko et al (2006) demonstrated further that the C allele was associated

with reduced levels of NOS3 mRNA, resulting in 2.1times lower NOS3 enzyme activity in

isolated platelets. The T allele has been linked with elite performance in power-based events in

Spanish (Gomez-Gallego et al, 2009) Italian (Sessa et al, 2011) and Ukrainian (Drozdovska et al,

2013) populations. As previously mentioned the C allele is associated with a decrease in

promoter activity; therefore contributing to an increase in blood pressure. Hyndman et al

(2002) observed that subjects with the CC genotype had significantly elevated systolic blood

pressure compared to the TT genotype group (P<0.05) and estimated that individuals with the

CC genotype were 2.16 times more likely to be hypertensive when compared to homozygous

TT individuals. In one study (Eynon et al, 2012) the C allele was found to be more common in

elite football players, when compared to sedentary individuals, as well as endurance and

power athletes.

In contrast, the C allele has been associated with improved aerobic capacity in hypertensive

men; as patients with the C allele demonstrated an increase of 7.6mmHg less in systolic blood

pressure from baseline after moderate exercise (60% of VO₂max) when compared to non-

exercising controls (Augeri et al, 2009). A potential explanation for this finding could be the

improvement seen in endothelial function following exercise; it is widely accepted that

improvement in vascular dilation is more enhanced in (and potentially limited to) subjects with

pre-existing endothelial dysfunction (Rush et al, 2005; Haram et al, 2008). It has been

identified that endurance athletes tend to have slightly lower blood pressure when compared

to strength trained athletes. Berge et al (2015) carried out a systematic review on studies

reporting blood pressure in athletes (both elite and recreational) and normal controls. The

group demonstrated that on average strength trained athletes’ blood pressure was

131.3mmHg, whereas in endurance trained individuals mean blood pressure was 118.6mmHg;

but overall found no significant difference in blood pressure between athletes and controls.

5.2: IL-6

The IL-6 (Interleukin-6) is multifunctional cytokine. The gene is located on chromosome seven

(position p21); it is 4.8Kb long and contains five exons. Along with other cytokines and growth

26

factors, IL-6 is an important part of the inflammation response induced through exercise; IL-6

released from contracting skeletal muscle fibres possess anti-inflammatory properties that aid

in muscle repair after acute exercise (Ruiz et al, 2010). IL-6 mRNA levels were significantly

elevated in human quadriceps muscle immediately after a marathon race when compared to

pre-exercise levels (Ostrowski et al, 1998). This finding was then replicated in rat muscle,

where IL-6 mRNA levels were elevated following electrically stimulated contractions – both

concentric and eccentric (Jonsdottir et al, 2000). Moreover, Steensberg et al (2000) observed a

gradual increase in the arterial plasma IL-6 concentration with exercise; although a more

significant increase in IL-6 concentration was recorded after three hours of exercise. The

maximal net release of IL-6 from the exercising muscle was ~100 fold higher than before the

exercise commenced. Furthermore, Helge et al (2003) found that the amount of IL-6 released

from working skeletal muscle was positively correlated to the intensity of exercise and glucose

uptake, as well as stimulating hepatic glucose production. This suggests that IL-6 improves

muscle glucose delivery and therefore has a role in glucose homeostasis during exercise

(Gleeson, 2000; Steensberg et al, 2000; Febbraio et al, 2004).

A functional SNP occurs at position -174 (rs1800795) in the promoter region of IL-6, involving

a C to G substitution first described by Fishman et al (1998). The G allele is linked with

increased transcriptional activity (Bennermo et al, 2004) and therefore higher expression of IL-

6 protein (Fishman et al, 1998). As a consequence, the G allele is associated with higher plasma

IL-6 levels in response to inflammatory stimuli (Bennermo et al, 2004) and more efficient

muscle repair following exercise (Serrano et al, 2008). On the other hand, individuals with the

CC genotype have raised muscle damage following exercise. Yamin et al (2008) observed a

strong association between the C allele and higher levels of total serum creatine kinase activity

(an indicator of skeletal muscle damage) resulting from eccentric contractions of the elbow

flexor muscles in young adults. Therefore, a link with fatigue for the duration of exercise has

been identified; in addition with the ability of an individual to recover from competitions and

training sessions. Skeletal muscle damage occurs frequently during exercise, as the working

muscles are under continual stress for the duration of the exercise. In this case the harm

caused doesn’t necessarily have a negative impact; as the damage doesn’t always lead to

muscle injury but influences muscular adaptations. It has also been suggested that the G allele

of this particular polymorphism may facilitate power performance in sport. Ruiz et al (2010)

observed that the G allele occurred more frequently in elite power athletes when compared to

both the control and elite endurance athletes. This accords well with the previous observations

of Taaffe et al (2000); who reported a negative association between the levels of IL-6 and

27

muscle strength. Furthermore, this group reported that the G allele does not appear to be

linked to endurance sports performance, as both the G allele and homozygous GG genotype

frequencies were similar between endurance and control groups.

Furthermore, Robson-Ansley et al (2004) suggested that IL-6 can impair endurance

performance through increasing the feeling of fatigue by varying central nervous system’s

serotonergic activity. They demonstrated this by administering a small dose of recombinant lL-

6 (rhlL-6) to elite male runners; this caused a significant impairment to the athletes 10km

running time trial when compared to the placebo group.

28

6: Discussion

The findings collected here could provide useful information and direction towards designing

training programmes for individual athletes. By analysing the current data in injury risk and

recovery genetics in particular, it is feasible that more efficient and personalised training plans

can be created, in order to get the best performance out of the athlete.

Both the T allele of GDF5 (+140T/C; rs143383) and the G allele of COL1A1 (rs1800012; -

1997G/T) were associated with a raised risk of injury in the soft tissues (Wolfman et al, 1997;

Collins & Raleigh, 2009; Posthumus et al, 2010). The COL1A1 G allele was shown to be

overrepresented in ACL ruptures and Achilles tendiopathy (Khoschnau et al, 2008; Posthumus

et al, 2009a); therefore individuals with the G allele should be adapting their training regime to

incorporate strength and resistance exercises. These exercises help to promote the strength

and stability of ligaments and tendons; so the structures can tolerate higher levels of stress.

Furthermore, the ACL is essential for changing direction quickly; therefore by including

exercises that improve rotational agility it can help reduce the risk of injury. In addition,

making nutritional changes can greatly enhance the reduction in injury risk; commencing a diet

promoting anti-inflammatory effects will help to compensate for the weaker soft tissue

formations observed in GDF5 T variants and COL1A1 G variants.

In addition, the IL-6 C allele (-174C/G; rs1800795) was associated with decreased IL-6 levels

and raised muscle damage following exercise (Yamin et al, 2008). As a consequence of this,

individuals with the C allele should increase their rest period to allow the muscles to recover

properly. Furthermore, it has been recommended that these individuals should periodically

check inflammatory biomarkers to regulate exercise intensity and duration (Ferec, 2014).

The field of genetics is gradually moving to the forefront of sport and exercise medicine, with

numerous potential applications; from incorporating the field into training programmes briefly

discussed here to genetic screening and gene doping. Sport and exercise genomics is becoming

a widely accepted component of the multi-disciplinary approach in sports and exercise science.

Myburgh (2003) proposed that current exercise scientists should at the minimum understand

the contributions that the fields of genetics and molecular biology offer, if not incorporate

them into their research. The margins between success and failure at the elite level of world

sport are commonly minute; with athletes utilising similar training programmes within their

sporting disciplines, there is considerable potential of genetics to have the answers for these

small but significant differences seen in elite sporting performance.

29

References

Alvarez R., Terrados N., Ortolano R., Iglesias-Cubero G., Reguero J.R., Batalla A., Cortina A.,

Fernández-García B., Rodríguez C., Braga S., Alvarez V., Coto E. (2000) Genetic variation in the

renin-angiotensin system and athletic performance. European Journal of Applied Physiology

82, 117–120.

Amir O., Amir R., Yamin C., Attias E., Eynon N., Sagiv M., Sagiv M., Meckel Y. (2007) The ACE

deletion allele is associated with Israeli elite endurance athletes. Experimental Physiology 92

(5), 881–886.

Andersen L.B., Henckel P., Saltin B. (1987) Maximal oxygen uptake in Danish adolescents

16-19 years of age. European Journal of Applied Physiology and Occupational Physiology 56,

74-82.

ATP World Tour (2014) Novak Djokovic. Retrieved on 01/11/2014 from

http://www.atpworldtour.com/Tennis/Players/Top-Players/Novak-Djokovic.aspx?t=rh

Augeri A.L., Tsongalis G.J., Van Heest J.L., Maresh C.M., Thompson P.D., Pescatello L.S.

(2009) The endothelial nitric oxide synthase -786 T>C polymorphism and the exercise-induced

blood pressure and nitric oxide responses among men with elevated blood pressure.

Atherosclerosis 204 (2), e28-34.

Baar K. (2004) Involvement of PPARg co-activator-1, nuclear respiratory factors 1 and 2, and

PPARa in the adaptive response to endurance exercise. Proceedings of the Nutrition Society 63,

269–273.

Baar K., Song Z., Semenkovich C.F., Jones T.E., Han D.H., Nolte L.A., Ojuka E.O., Chen M.,

Holloszy J.O. (2003) Skeletal muscle overexpression of nuclear respiratory factor 1 increases

glucose transport capacity. FASEB Journal 17 (12), 1666-1673.

Bahr R., Krosshaug T. (2005) Understanding injury mechanisms: a key component of

preventing injuries in sport. British Journal of Sports Medicine 39 (6), 324-329.

Baker J., Cote J. (2003) Sport Specific Practice and the Development of Expert Decision-

Making in Team Ball Sports. Journal of Applied Sport Psychology 15, 12-25.

Bassett D.R. Jr., Howley E.T. (2000) Limiting factors for maximum oxygen uptake and

determinants of endurance performance. Medicine and Science in Sports and Exercise 32, 70-

84.

Bell R.D., Shultz S.J., Wideman L., Henrich V.C. (2012) Collagen gene variants previously

associated with anterior cruciate ligament injury risk are also associated with joint laxity.

Sports Health 4 (4), 312-318.

Bennermo M., Held C., Stemme S., Ericsson C.G., Silveira A., Green F., Tornvall P. (2004)

Genetic predisposition of the interleukin-6 response to inflammation: implications for a variety

of major diseases? Clinical Chemistry 50 (11), 2136-2140.

30

Berge H.M., Isern C.B., Berge E. (2015) Blood pressure and hypertension in athletes: a

systematic review. The British Journal of Sports Medicine Published Online First: 28th January

2015. doi: 10.1136/bjsports-2014-093976.

Bloom B. S. (1985) Developing talent in young people. New York: Ballantine

Brodde O.E. (2008) 1- and 2-Adrenoceptor polymorphisms and cardiovascular diseases.

Fundamental & Clinical Pharmacology 22 (2), 107-125.

Buchanan C.I., Marsh R.L. (2002) Effects of exercise on the biomechanical, biochemical and

structural properties of tendons. Comparative Biochemistry and Physiology 133 (4), 1101-1107.

Burke J., Thayer R. Belcamino M. (1994) Comparison of effects of two interval-training

programmes on lactate and ventilatory thresholds. The British Journal of Sports Medicine 28,

18-21.

Chapman K., Takahashi A., Meulenbelt I., Watson C., Rodriguez-Lopez J., Egli R., Tsezou A.,

Malizos K.N., Kloppenburg M., Shi D., Southam L., van der Breggen R., Donn R., Qin J., Doherty

M., Slagboom P.E., Wallis G., Kamatani N., Jiang Q., Gonzalez A., Loughlin J., Ikegawa S. (2008)

A meta-analysis of European and Asian cohorts reveals a global role of a functional SNP in the

5′ UTR of GDF5 with osteoarthritis susceptibility. Human Molecular Genetics 17 (10), 1497-

1504

Collins M., Xenophontos S.L., Cariolou M.A., Mokone G.G., Hudson D.E., Anastasiades L.,

Noakes T.D. (2004) The ACE gene and endurance performance during the South African

Ironman Triathlons. Medicine and Science in Sports and Exercise 36(8), 1314-1320.

Collins M., Raleigh S.M. (2009) Genetic Risk Factors for Musculoskeletal Soft Tissue Injuries.

In: Collins M (ed) Genetics and Sports, Medicine and Sports Science 54. Basel: Karger. 136-149.

Conley D.L., Krahenbuhl G.S. (1980) Running economy and distance running performance of

highly trained athletes. Medicine and Science in Sports and Exercise 12 (5), 357-360.

Costa A.M., Silva A.J., Garrido N.D., Louro H., de Oliveira R.J., Breitenfeld L. (2009)

Association between ACE D allele and elite short distance swimming. European Journal of

Applied Physiology 106, 785–790.

Costerousse O., Allegrini J., Lopez M., Alhenc-Gelas F. (1993) Angiotensin I-converting

enzyme in human circulating mononuclear cells: genetic polymorphism of expression in T-

lymphocytes. The Biochemical Journal 290, 33-40.

Cote J., Baker J., Abernethy B. (2003). From play to practice: A developmental framework

for the acquisition of expertise in team sports. In Starkes J., Ericsson K.A. (Eds.), Expert

performance in sports: Advances in research on sport expertise. Champaign, IL: Human Kinetics.

89-114.

Coyle E.F., Coggan A.R., Hopper M.K., Walters T.J. (1988) Determinants of endurance in

well-trained cyclists. The Journal of Applied Physiology 64 (6), 2622-2630.

31

D'amato M., Vitiani L.R., Petrelli G., Ferrigno L., di Pietro A., Trezza R., Matricardi P.M.

(1998) Association of persistent bronchial hyper-responsiveness with beta2-adrenoceptor

(ADRB2) haplotypes. A population study. American Journal of Respiratory and Critical Care

Medicine 158 (6), 1968-1973.

Daniels J.T. (1985) A physiologist's view of running economy. Medicine and Science in Sports

and Exercise 17 (3), 332-338.

Danser A.H., Schalekamp M.A., Bax W.A., Van den Brink A.M., Saxena P.R., Riegger G.A.,

Schunkert H. (1995) Angiotensin converting enzyme in the human heart. Effect of the

deletion/insertion polymorphism. Circulation 92, 1387–1388.

Davids K., Baker J. (2007) Genes, environment and sport performance: why the nature-

nurture dualism is no longer relevant. Sports Medicine 37 (11), 961-980.

Davies K.J.A., Packer L., Brooks G.A. (1981) Biochemical Adaptation of Mitochondria, Muscle

and Whole-Animal Respiration to Endurance Training. Archives of Biochemistry and Biophysics

209 (2), 539-554.

Defoor J., Martens K., Zielinska D., Matthijs G., Van Nerum H., Schepers D., Fagard R.,

Vanhees L. (2006) The CAREGENE study: polymorphisms of the beta1-adrenoceptor gene and

aerobic power in coronary artery disease. The European Heart Journal 27 (7), 808-816.

Di Prampero P.E., Capelli C., Pagliaro P., Antonutto G., Girardis M., Zamparo P., Soule R.G.

(1993) Energetics of best performances in middle-distance running. Journal of Applied

Physiology 74 (5), 2318-2324.

Dishy V., Sofowora G.G., Xie H.G., Kim R.B., Byrne D.W., Stein C.M., Wood A.J. (2001) The

effect of common polymorphisms of the beta2-adrenergic receptor on agonist-mediated

vascular desensitization. The New England Journal of Medicine 345 (14), 1030-1035.

Dosenko V.E., Zagoriy V.Y., Haytovich N.V., Gordok O.A., Moibenko A.A. (2006) Allelic

polymorphism of endothelial NO-synthase gene and its functional manifestations. Acta

Biochimica Polonica 53 (2), 299-302.

Drozdovska S.B., Dosenko V.E., Ahmetov I.I, Ilyin V.N. (2013) The Association Of Gene

Polymorphisms With Athlete Status In Ukrainians. Biology of Sport 30 (3), 163–167.

Drysdale C.M., McGraw D.W., Stack C.B., Stephens J.C., Judson R.S., Nandabalan K., Arnold

K., Ruano G., Liggett S.B. (2000) Complex promoter and coding region beta 2-adrenergic

receptor haplotypes alter receptor expression and predict in vivo responsiveness. Proceedings

of the National Academy of Sciences of the United States of America 97 (19), 10483-10488.

Duncker D.J., Bache R.J. (2008) Regulation of Coronary Blood Flow During Exercise.

Physiology Review 88 (3), 1009-1086.

Egan B., Zierath J.R. (2013) Exercise Metabolism and the Molecular Regulation of Skeletal

Muscle Adaptation. Cell Metabolism 17 (2), 162–184.

32

Egli R.J., Southam L., Wilkins J.M., Lorenzen I., Pombo-Suarez M., Gonzalez A., Carr A.,

Chapman K., Loughlin J. (2009) Functional Analysis of the Osteoarthritis Susceptibility-

Associated GDF5 Regulatory Polymorphism. Arthritis & Rheumatism 60 (7), 2055-2064.

Ehlers M.R.W., Riordan J.F. (1989) Angiotensin-Converting Enzyme: New Concepts

Concerning Its Biological Role. Biochemistry 28 (13), 5311-5317.

Eisenach J.H., Barnes S.A., Pike T.L., Sokolnicki L.A., Masuki S., Dietz N.M., Rehfeldt K.H.,

Turner S.T., Joyner M.J. (2005) Arg16/Gly beta2-adrenergic receptor polymorphism alters the

cardiac output response to isometric exercise. Journal of Applied Physiology 99 (5), 1776-1781.

Ericsson, K.A., Krampe, R.T., Tesch-Romer C. (1993). The Role of Deliberate Practice in the

Acquisition of Expert Performance. Psychological Review 100 (3), 363-406.

Evangelou E., Chapman K., Meulenbelt I., Karassa F.B., Loughlin J., Carr A., Doherty M.,

Doherty S., Gómez-Reino J.J., Gonzalez A., Halldorsson B.V., Hauksson V.B., Hofman A., Hart

D.J., Ikegawa S., Ingvarsson T., Jiang Q., Jonsdottir I., Jonsson H., Kerkhof H.J., Kloppenburg M.,

Lane N.E., Li J., Lories R.J., van Meurs J.B., Näkki A., Nevitt M.C., Rodriguez-Lopez J., Shi D.,

Slagboom P.E., Stefansson K., Tsezou A., Wallis G.A., Watson C.M., Spector T.D., Uitterlinden

A.G., Valdes A.M., Ioannidis J.P. (2009) Large-Scale Analysis of Association Between GDF5 and

FRZB Variants and Osteoarthritis of the Hip, Knee, and Hand. Arthritis & Rheumatism 60 (6),

1710-1721.

Eynon N., Ruiz J.R., Yvert T., Santiago C., Gomez-Gallego F., Lucia A., Birk R. (2012) The C

allele in NOS3 -786 T/C polymorphism is associated with elite soccer player’s status.

International Journal of Sports Medicine 33 (7), 521-524.

Fatini C., Guazzelli R., Manetti P., Battaglini B., Gensini F., Vono R., Toncelli L., Zilli P.,

Capalbo A., Abbate R., Gensini G.F., Galanti G. (2000) RAS genes influence exercise-induced left

ventricular hypertrophy: an elite athletes study. Medicine & Science in Sports & Exercise 32

(11), 1868–1872.

Febbraio M.A., Hiscock N., Sacchetti M., Fischer C.P., Pedersen B.K. (2004) Interleukin-6 Is a

Novel Factor Mediating Glucose Homeostasis During Skeletal Muscle Contraction. Diabetes 53

(7), 1643-1648.

Ferec A. (2014) GENETICS FOR TRAINERS Decoding the Sports Gene. Los Angeles: AFSP LLC.

Ficek K., Cieszczyk P., Kaczmarczyk M., Maciejewska-Karłowskad A., Sawczuk M.,

Cholewinskia J., Leonska-Duniec A., Stepien-Slodkowskab M., Zarebskac A., Steptof N.K.,

Bishop D.J., Eynon N. (2013) Gene variants within the COL1A1 gene are associated with

reduced anterior cruciate ligament injury in professional soccer players. Journal of Science and

Medicine in Sport 16, 396-400.

Fishman D., Faulds G., Jeffery R., Mohamed-Ali V., Yudkin J.S., Humphries S., Woo P. (1998)

The effect of novel polymorphisms in the interleukin-6 (IL-6) gene on IL-6 transcription and

plasma IL-6 levels, and an association with systemic-onset juvenile chronic arthritis. The

Journal of Clinical Investigation 102 (7), 1369-1376.

33

Folland J., Leach B., Little T., Hawker K., Myerson S., Montgomery H., Jones D. (2000)

Angiotensin-converting enzyme genotype affects the response of human skeletal muscle to

functional overload. Experimental Physiology 85 (5), 575-579.

Foster C., Lucia A. (2007) Running Economy: The Forgotten Factor in Elite Performance.

Sports Medicine 37 (4), 316-319.

Di Francescomarino S., Sciartilli A., Di Valerio V., Di Baldassarre A., Gallina S. (2009) The

Effect of Physical Exerciseon Endothelial Function. Sports Medicine 39 (10), 797-812.

Garcia-Giralt N., Nogués X., Enjuanes A., Puig J., Mellibovsky L., Bay-Jensen A., Carreras R.,

Balcells S., Díez-Pérez A., Grinberg D. (2002) Two New Single-Nucleotide Polymorphisms in the

COL1A1 Upstream Regulatory Region and Their Relationship to Bone Mineral Density. Journal

of Bone and Mineral Research 17 (3), 384–393.

Gayagay G., Yu B., Hambly B., Boston T., Hahn A., Celermajer D.S., Trent R.J. (1998) Elite

endurance athletes and the ACE I allele–the role of genes in athletic performance. Human

Genetics 103, 48–50.

Ghosh A.K. (2004) Anaerobic Threshold: Its Concept and Role in Endurance Sport.

Malaysian Journal of Medical Sciences 11, 24-36.

Gleeson M. (2000) Interleukins and exercise. The Journal of Physiology 529, 1.

Gomez-Gallego F., Ruiz J.R., Buxons A., Artieda M., Arteta D., Santiago C., Rodriquez-Romo

G., Lao JI., Lucia A. (2009) The -786 T/C polymorphism of the NOS3 gene is associated with elite

performance in elite power sports. European Journal of Applied Physiology 107 (5), 565-569.

Hakim A.J., Cherkas L.F., Spector T.D., MacGregor A.J. (2003) Genetic associations between

frozen shoulder and tennis elbow: a female twin study. Rheumatology 42, 739–742.

Haram P.M., Kemi O.J., Wisloff U. (2008) Adaptation of endothelium to exercise training:

insights from experimental studies. Frontiers in Bioscience 13, 336-346.

Harvie P., Ostlere S.J., Teh J., McNally E.G., Clipsham K., Burston B.J., Pollard T.C.B., Carr A.J.

(2004) Genetic influences in the aetiology of tears of the rotator cuff: Sibling risk of a full-

thickness tear. The Journal of Bone & Joint Surgery (Br) 86, 696–700.

He Z., Hu Y., Feng L., Li Y., Liu G., Xi Y., Wen L., Lucia A. (2008) NRF-1 genotypes and

endurance exercise capacity in young Chinese men. British Journal of Sports Medicine 42 (5),

361-366.

Helge J.W., Stallknecht B., Pedersen B.K., Galbo H., Kiens B., Richter E.A. (2003) The effect

of graded exercise on IL-6 release and glucose uptake in human skeletal muscle. The Journal of

Physiology 546, 299-305.

Helson W.F., Starkes J.L., Hodges N.J. (1998) Team Sports and the Theory of Deliberate

Practice. Journal of Sport & Exercise Psychology 20, 12-34.

34

Higashi Y., Yoshizumi M. (2004) Exercise and endothelial function: Role of endothelium-

derived nitric oxide and oxidative stress in healthy subjects and hypertensive patients.

Pharmacology & Therapeutics 102, 87-96.

Hildebrandt A.L., Pilegaard H., Neufer P.D. (2003) Differential transcriptional activation of

select metabolic genes in response to variations in exercise intensity and duration. American

Journal of Physiology: Endocrinology and Metabolism 285 (5), e1021-1027.

Hood D.A. (2001) Plasticity in Skeletal, Cardiac, and Smooth Muscle Invited Review:

Contractile activity-induced mitochondrial biogenesis in skeletal muscle. The Journal of Applied

Physiology 90, 1137–1157.

Huard J., Li Y., Fu F.H. (2002) Muscle Injuries and Repair: Current Trends in Research. The

The Journal of Joint & Bone Surgery 84 (5), 822 -832.

Hurme T., Kalimo H. (1982) Activation of myogenic precursor cells after muscle injury.

Medicine and Science in Sports and Exercise 24 (2), 197-205.

Hurme T., Kalimo H., Lehto M., Järvinen M. (1991) Healing of skeletal muscle injury: an

ultrastructural and immunohistochemical study. Medicine and Science in Sports and Exercise

23 (7), 801-810.

Hyndman M.E., Parsons H.G., Verma S., Bridge P.J., Edworthy S., Jones C., Lonn E.,

Charbonneau F., Anderson T.J. (2002) The T-7863C Mutation in Endothelial Nitric Oxide

Synthase is Associated with Hypertension. Hypertension 39 (4), 919-922.

IAAF Athletics (2014a) Athlete Profile: Donald Thomas. Retrieved on 01/11/2014 from

http://www.iaaf.org/athletes/bahamas/donald-thomas-221630#progression

IAAF Athletics (2014b) Athlete Profile: Stefan Holm. Retrieved on 01/11/2014 from

http://www.iaaf.org/athletes/sweden/stefan-holm-20596#progression

IAAF Athletics (2014c) 11th IAAF World Championships in Athletics: High Jump – men.

Retrieved on 01/11/2014 from http://www.iaaf.org/results/iaaf-world-championships-in-

athletics/2007/11th-iaaf-world-championships-in-athletics-3653/men/high-jump/final/result

Ignarro L.J. (1989) Endothelium-derived nitric oxide: actions and properties. The FASEB

Journal 3, 31-36.

Ireland D., Harrall R., Curry V., Holloway G., Hackney R., Hazleman B., Riley G. (2001)

Multiple changes in gene expression in chronic human Achilles tendinopathy. Matrix Biology

20 (3), 159-169.

Jones A.M. (2006) The Physiology of the World Record Holder for the Women’s Marathon.

International Journal of Sports Science & Coaching 1 (2), 101-116.

Jones A., Montgomery H.E., Woods D.R. (2002) Human performance: A role for the ACE

genotype? Exercise and Sport Science Reviews 30 (4), 184–190.

35

Jonsdottir I.H., Schjerling P., Ostrowski K., Asp S., Richter E.A., Pedersen B.K. (2000) Muscle

contractions induce interleukin-6 mRNA production in rat skeletal muscles. The Journal of

Physiology 528, 157–163.

Kalinowski A.G. (1985) The Development of Olympic Swimmers. In Bloom B.S. (Ed)

Developing Talent in Young People. New York: Ballantine. 139-192.

Keller C., Steensberg A., Pilegaard H., Osada T., Saltin B., Pedersen B.K., Neufer P.D. (2001)

Transcriptional activation of the IL-6 gene in human contracting skeletal muscle: influence of

muscle glycogen content. FASEB Journal 15 (14), 2748-2750.

Khoschnau S., Melhus H., Jacobson A., Rahme H., Bengtsson H., Ribom E., Grundberg E.,

Mallmin H., Michaëlsson K. (2008) Type I Collagen α1 Sp1 Polymorphism and the Risk of

Cruciate Ligament Ruptures or Shoulder Dislocations. The American Journal of Sports Medicine

36 (12), 2432-2436.

Komi P.V. (2003) In: Komi P.V. (Ed) Strength and Power in Sport 3. 2nd edn. Oxford: Blackwell

Science Ltd. 184-202.

Kountouris A., Cook J. (2007) Rehabilitation of Achilles and patellar tendinopathies. Best

Practice & Research Clinical Rheumatology 21 (2), 295-316.

Kubo K., Kanehisa H., Takeshita D., Kawakami Y., Fukashiro S., Fukunaga T. (2000) In vivo

dynamics of human medial gastrocnemius muscle-tendon complex during stretch-shortening

cycle exercise. Acta Physiologica Scandinavica 170, 127-135.

La Rosée K., Huntgeburth M., Rosenkranz S., Böhm M., Schnabel P. (2004) The Arg389Gly

beta1-adrenoceptor gene polymorphism determines contractile response to catecholamines.

Pharmacogenetics 14 (11), 711-716.

Larsen H.B. (2003) Kenyan dominance in distance running. Comparative Biochemistry and

Physiology 136, 161–170.

Larsen H.B., Christensen D.L., Nolan T., Søndergaard H. (2004) Body dimensions, exercise

capacity and physical activity level of adolescent Nandi boys in western Kenya. Annals of

Human Biology 31 (2), 159-173.

Leone J.E., Gray K.A., Massie J.E., Rossi J.M. (2005) Celiac Disease Symptoms in a Female

Collegiate Tennis Player: A Case Report. Journal of Athletic Training 40 (4), 365–369.

Londeree B.R. (1997) Effect of training on lactate/ventilatory thresholds: a meta-analysis.

Medicine and Science in Sports and Exercise 29 (6), 837-843.

Maffulli N., Wong J., Almekinders L.C. (2003). Types and epidemiology of tendinopathy.

Clinical Journal of Sport Medicine 22 (4), 675-692.

Maiorana A., O'Driscoll G., Taylor R., Green D. (2003) Exercise and the Nitric Oxide

Vasodilator System. Sports Medicine 33 (14), 1013-1035.

36

Mancini L.A., Trojian T., Mancini A.C. (2011) Celiac Disease and the Athlete. Current Sports

Medicine Reports 10 (2), 105-108.

Mann V., Hobson E.E., Li B., Stewart T.L., Grant S.F., Robins S.P., Aspden R.M., Ralston S.H.

(2001) A COL1A1 Sp1 binding site polymorphism predisposes to osteoporotic fracture by

affecting bone density and quality. The Journal of Clinical Investigation 107 (7), 899-907.

Maqbool A., Hall A.S., Ball S.G., Balmforth A.J. (1999) Common polymorphisms of beta1-

adrenoceptor: identification and rapid screening assay. The Lancet 353 (9156), 897.

Marshall S.W., Padua D., McGrath M. (2007) Incidence of ACL injuries, Chapter 1. In: Hewett

T.E., Schultz S.J., Griffin L.Y. (Eds) Understanding and Preventing Noncontact ACL Injury.

Champaign: Human Kinetics.

Mason D.A., Moore J.D., Green S.A., Liggett S.B. (1999) A Gain-of-function Polymorphism in

a G-protein Coupling Domain of the Human b1-Adrenergic Receptor. The Journal of Biological

Chemistry 274 (18), 12670-12674.

Mikic B., Schalet B.J., Clark R.T., Gaschen V., Hunziker E.B. (2001) GDF-5 deficiency in mice

alters the ultrastructure, mechanical properties and composition of the Achilles tendon.

Journal of Orthopaedic Research 19 (3), 365-371.

Miyamoto Y., Mabuchi A., Shi D., Kubo T., Takatori Y., Saito S., Fujioka M., Sudo A., Uchida

A., Yamamoto S., Ozaki K., Takigawa M., Tanaka T., Nakamura Y., Jiang Q., Ikegawa S. (2007) A

functional polymorphism in the 5' UTR of GDF5 is associated with susceptibility to

osteoarthritis. Nature Genetics 39 (4), 529-533.

Moncada S., Radomski M.W., Palmer R.M. (1988) Endothelium-derived relaxing factor:

Identification as nitric oxide and role in the control of vascular tone and platelet function.

Biochemical Pharmacology 37 (13), 2495-2501.

Monsaas G.T. (1985) Learning to be a world-class tennis player. In Bloom B.S. (Ed)

Developing Talent in Young People. New York: Ballantine. 211-269.

Montgomery H.E., Clarkson P., Dollery C.M., Prasad K., Losi M.A., Hemingway H., Statters

D., Jubb M., Girvain M., Varnava A., World M., Deanfield J., Talmud P., McEwan J.R., McKenna

W.J., Humphries S. (1997) Association of angiotensin-converting enzyme gene I/D

polymorphism with change in left ventricular mass in response to physical training. Circulation

96 (3), 741-747.

Montgomery H.E., Marshall R., Hemingway H., Myerson S., Clarkson P., Dollery C., Hayward

M., Holliman D.E., Jubb M., World M., Thomas E.L., Brynes A.E., Saeed N., Barnard M., Bell J.D.,

Prasad K., Rayson M., Talmud P.J., Humphries S.E. (1998) Human gene for physical

performance. Nature 393, 221-222.

Morgan D.W., Baldini F.D., Martin P.E., Kohrt W.M. (1989) Ten kilometer performance and

predicted velocity at VO2max among well-trained male runners. Medicine and Science in

Sports and Exercise 21, 78-83.

37

de Mos M., van El B., DeGroot J., Jahr H., van Schie H.T., van Arkel E.R., Tol H., Heijboer R.,

van Osch G.J., Verhaar J.A. (2007) Achilles tendinosis: changes in biochemical composition and

collagen turnover rate. The American Journal of Sports Medicine 35 (9), 1549-1556.

Murphey L.J., Gainer J.V., Vaughan D.E., Brown N.J. (2000) Angiotensin-Converting Enzyme

Insertion/Deletion Polymorphism Modulates the Human In Vivo Metabolism of Bradykinin.

Circulation 102, 829-832.

Myburgh K.H. (2003) What makes an endurance athlete world-class? Not simply a

physiological conundrum. Comparative Biochemistry and Physiology Part A 136, 171–190.

Myerson S., Hemingway H., Budget R., Martin J., Humphries S., Montgomery H. (1999)

Human angiotensin I-converting enzyme gene and endurance performance. Journal of Applied

Physiology 87, 1313–1316.

Nakayama M., Yasue H., Yoshimura M., Shimasaki Y., Kugiyama K., Ogawa H., Motoyama T.,

Saito Y., Ogawa Y., Miyamoto Y., Nakao K. (1999) T-786-->C mutation in the 5'-flanking region

of the endothelial nitric oxide synthase gene is associated with coronary spasm. Circulation 99

(22), 2864-2870.

Nazarov I.B., Woods D.R., Montgomery H.E., Shneider O.V., Kazakov V.I., Tomilin N.V.,

Rogozkin V.A. (2001) The angiotensin converting enzyme I/D polymorphism in Russian

athletes. European Journal of Human Genetics 9, 797-801.

Newman, P. (2013) Revealed: The diet that saved Novak Djokovic. The Independent.

Retrieved on 7 October 2014 from http://www.independent.co.uk/sport/tennis/revealed-the-

diet-that-saved-novak-djokovic-8775333.html

Ostrowski K., Rohde T., Zacho M., Asp S., Pedersen B.K. (1998) Evidence that interleukin-6 is

produced in human skeletal muscle during prolonged running. The Journal of Physiology 508,

949–953.

Pan F., Tian J., Winzenberg T., Ding C., Jones G. (2014) Association between GDF5 rs143383

polymorphism and knee osteoarthritis: an updated meta-analysis based on 23,995 subjects.

BMC Musculoskeletal Disorders 15 (404).

Perry C.G., Lally J., Holloway G.P., Heigenhauser G.J., Bonen A., Spriet L.L. (2010) Repeated

transient mRNA bursts precede increases in transcriptional and mitochondrial proteins during

training in human skeletal muscle. The Journal of Physiology 588 (23), 4795-4810.

Pilegaard H., Saltin B., Neufer P.D. (2003) Exercise induces transient transcriptional

activation of the PGC-1alpha gene in human skeletal muscle. The Journal of Physiology 546 (3),

851-858.

Posthumus M., September A.V., Keegan M., O'Cuinneagain D., Van der Merwe W.,

Schwellnus M.P., Collins M. (2009a) Genetic risk factors for anterior cruciate ligament

ruptures: COL1A1 gene variant. British Journal of Sports Medicine 43 (5), 352-356.

38

Posthumus M., September A.V., Schwellnus M.P., Collins M. (2009b) Investigation of the

Sp1-binding site polymorphism within the COL1A1 gene in participants with Achilles tendon

injuries and controls. Journal of Science and Medicine in Sport 12, 184—189.

Posthumus M., Collins M., Cook J., Handley C.J., Ribbans W.J., Smith R.K.W., Schwellnus

M.P., Raleigh S.M. (2010) Components of the transforming growth factor-b family and the

pathogenesis of human Achilles tendon pathology—a genetic association study. Rheumatology

49, 2090–2097.

Raleigh S.M., Posthumus M., O'Cuinneagain D., van der Merwe W., Collins M. (2013) The

GDF5 Gene and Anterior Cruciate Ligament Rupture. International Journal of Sports Medicine

34 (4), 364-367.

Ranade K., Jorgenson E., Sheu W. H.-H., Pei D., Hsiung C. A., Chiang F., Chen Y.I., Pratt R.,

Olshen R.A., Curb D., Cox D.R., Botstein D., Risch N. (2002). A Polymorphism in the β1

Adrenergic Receptor Is Associated with Resting Heart Rate. American Journal of Human

Genetics 70 (4), 935–942.

Rankinen T., Wolfarth B., Simoneau J., Maier-Lenz D., Rauramaa R., Rivera M.A., Boulay

M.R., Chagnon Y.C., Pe´russe L., Keul J., Bouchard C. (2000) No association between the

angiotensin-converting enzyme ID polymorphism and elite endurance athlete status. Journal of

Applied Physiology 88, 1571–1575.

Rathz D.A., Brown K.M., Kramer L.A., Liggett S.B. (2002) Amino acid 49 polymorphisms of

the human beta1-adrenergic receptor affect agonist-promoted trafficking. The Journal of

Cardiovascular Pharmacology 39 (2), 155-160.

Rees J.D., Wilson A.M., Wolman R.L. (2006). Current concepts in the management of

tendon disorders. Rheumatology (Oxford) 45 (5), 508-521.

Renstrom P., Ljungqvist A., Arendt E., Beynnon B., Fukubayashi T., Garrett W., Georgoulis T.,

Hewett T.E., Johnson R., Krosshaug T., Mandelbaum B., Micheli L., Myklebust G., Roos E., Roos

H., Schamasch P., Shultz S., Werner S., Wojtys E., Engebretsen L. (2008) Non-contact ACL

injuries in female athletes: an International Olympic Committee current concepts statement.

British Journal of Sports Medicine 42, 394–412.

Rieder M.J., Taylor S.L., Clark A.G., Nickerson D.A. (1999) Sequence variation in the human

angiotensin converting enzyme. Nature Genetics 22(1), 59-62.

Rigat B., Hubert C., Alhenc-Gelas F., Cambien F., Corvol P., Soubrier F. (1990) An

insertion/deletion polymorphism in the angiotensin I-converting enzyme gene accounting for

half the variance of serum enzyme levels. The Journal of Clinical Investigation 86 (4), 1343–

1346.

Robson-Ansley P., Barwood M., Canavan J., Hack S., Eglin C., Davey S., Hewitt J., Hull J.,

Ansley L. (2009) The effect of repeated endurance exercise on IL-6 and sIL-6R and their

relationship with sensations of fatigue at rest. Cytokine 45, 111–116.

39

Robson-Ansley P.J., de Milander L., Collins M., Noakes T.D. (2004) Acute interleukin-6

administration impairs athletic performance in healthy, trained male runners. The Canadian

Journal of Applied Physiology 29 (4), 411-8.

Rosendorff C. (1996) The Renin-Angiotensin System and Vascular Hypertrophy. Journal of

the American College of Cardiology 28 (4), 803-812.

Ruiz J.R., Buxens A., Artieda M., Arteta D., Santiago C., Rodríguez-Romo G., Laoe J.I., Gómez-

Gallego F., Lucia A. (2010) The −174 G/C polymorphism of the IL6 gene is associated with elite

power performance. The Journal of Science and Medicine in Sport 13, 549–553.

Rush J.W., Denniss S.G., Graham D.A. (2005) Vascular Nitric Oxide and Oxidative Stress:

Determinants of Endothelial Adaptations to Cardiovascular Disease and to Physical Activity.

The Canadian Journal of Applied Physiology 30 (4), 442-474.

Saltin B., Kim C.K., Terrados N., Larsen H., Svedenhag J., Rolf C.J. (1995) Morphology,

enzyme activities and buffer capacity in leg muscles of Kenyan and Scandinavian runners.

Scandinavian Journal of Medicine & Science in Sports 5 (4), 222-230.

Sanna S., Jackson A.U., Nagaraja R., Willer C.J., Chen W.M., Bonnycastle L.L., Shen H.,

Timpson N., Lettre G., Usala G., Chines P.S., Stringham H.M., Scott L.J., Dei M., Lai S., Albai G.,

Crisponi L., Naitza S., Doheny K.F., Pugh E.W., Ben-Shlomo Y., Ebrahim S., Lawlor D.A., Bergman

R.N., Watanabe R.M., Uda M., Tuomilehto J., Coresh J., Hirschhorn J.N., Shuldiner A.R.,

Schlessinger D., Collins F.S., Davey Smith G., Boerwinkle E., Cao A., Boehnke M., Abecasis G.R.,

Mohlke K.L. (2008) Common variants in the GDF5-UQCC region are associated with variation in

human height. Nature Genetics 40 (2), 198-203.

Sawczuk M., Maciejewska-Karlowska A., Cieszczyk P., Skotarczak B., Ficek K.(2013)

Association of the ADRB2 Gly16Arg and Glu27Gln polymorphisms with athlete status. Journal

of Sports Sciences 31 (14), 1535-1544.

Sawczuk M., Maciejewska-Karlowska A., Cieszczyk P., Zarebska A. (2012) Ser49Gly and

Arg389Gly polymorphisms of the ADRB1 gene and endurance performance. Central European

Journal of Biology 7 (5), 794-800.

Serrano A.L., Baeza-Raja B., Perdiguero E., Jardí M., Muñoz-Cánoves P. (2008) Interleukin-6

is an essential regulator of satellite cell-mediated skeletal muscle hypertrophy. Cell

Metabolism 7, 33-44.

Sessa F., Chetta M., Petito A., Franzetti M., Bafunno V., Pisanelli D., Sarno M., Iuso S.,

Margaglione M. (2011) Gene Polymorphisms and Sport Attitude in Italian Athletes. Genetic

Testing and Molecular Biomarkers 15 (4), 285-290.

Sham P.C., Walters E.E., Neale M.C., Heath A.C., MacLean C.J., Kendler K.S. (1994) Logistic

regression analysis of twin data: estimation of parameters of the multifactorial liability-

threshold model. Behaviour Genetics 24 (3), 229-238.

40

Skinner J.S., Jaskólski A., Jaskólska A., Krasnoff J., Gagnon J., Leon A.S., Rao D.C., Wilmore

J.H., Bouchard C. (2001) Age, sex, race, initial fitness, and response to training: the HERITAGE

Family Study. The Journal of Applied Physiology 90 (5), 1770-1776.

Snyder E.M., Beck K.C., Dietz N.M., Eisenach J.H., Joyner M.J., Turner S.T., Johnson B.D.

(2006a) Arg16Gly polymorphism of the beta2-adrenergic receptor is associated with

differences in cardiovascular function at rest and during exercise in humans. The Journal of

Physiology 571, 121–130.

Snyder E.M., Beck K.C., Dietz N.M., Joyner M.J., Turner S.T., Johnson B.D. (2006b) Influence

of 2-Adrenergic Receptor Genotype on Airway Function During Exercise in Healthy Adults.

Chest 129 (3), 762-770.

Snyder E.M., Hulsebus M.L., Turner S.T., Joyner M.J., Johnson B.D. (2006c) Genotype related

differences in beta2 adrenergic receptor density and cardiac function. Medicine and Science in

Sports and Exercise 38 (5), 882-886.

Snyder E.M., Johnson B.D., Joyner M.J. (2008) Genetics of β2-Adrenergic Receptors and the

Cardiopulmonary Response to Exercise. Exercise and Sport Science Reviews 36 (2), 98–105.

Southam L., Rodriguez-Lopez J., Wilkins J.M., Pombo-Suarez M., Snelling S., Gomez-Reino

J.J., Chapman K., Gonzalez A., Loughlin J. (2007) A SNP in the 5’ -UTR of GDF5 is associated with

osteoarthritis in Europeans and within vivo differences in allelic expression in articular

cartilage. Human Molecular Genetics 16 (18), 2226–2232.

Steensberg A., van Hall G., Osada T., Sacchetti M., Saltin B., Klarlund Pedersen B. (2000)

Production of interleukin-6 in contracting human skeletal muscles can account for the

exercise-induced increase in plasma interleukin-6. The Journal of Physiology 529, 237-242.

Taaffe D.R., Harris T.B., Ferrucci L., Rowe J., Seeman T.E. (2000) Cross-sectional and

prospective relationships of interleukin-6 and C-reactive protein with physical performance in

elderly persons: MacArthur studies of successful aging. The Journals of Gerontology. Series A,

Biological Sciences and Medical Sciences 55 (12), 709-715.

Tang W., Devereux R.B., Kitzman D.W., Province M.A., Leppert M., Oberman A., Hopkins

P.N., Arnett D.K. (2003) The Arg16Gly polymorphism of the beta2-adrenergic receptor and left

ventricular systolic function. American Journal of Hypertension 11, 945-951.

Tawonsawatruk T., Changthong T., Pingsuthiwong S., Trachoo O., Sura T., Wajanavisit W.

(2011) A genetic association study between growth differentiation factor 5 (GDF 5)

polymorphism and knee osteoarthritis in Thai population. Journal of Orthopaedic Surgery and

Research 6 (47).

Taylor H.L., Buskirk E., Henschel A. (1955) Maximal oxygen intake as an objective measure

of cardio-respiratory performance. The Journal of Applied Physiology 8, 73-80.

Taylor D.R., Kennedy M.A. (2001) Genetic Variation of the β2-Adrenoceptor: Its Functional

and Clinical Importance in Bronchial Asthma. American Journal of Pharmacogenomics 1 (3),

165-174.

41

Taylor R.R., Mamotte C.D.S, Fallon K., van Bockxmeer F.M. (1999) Elite athletes and the

gene for angiotensin-converting enzyme. Journal of Applied Physiology 87, 1035-1037.

Tsianos G., Sanders J., Dhamrait S., Humphries S., Grant S., Montgomery H. (2004) The ACE

gene insertion/deletion polymorphism and elite endurance swimming. European Journal of

Applied Physiology 92, 360-362.

Valdes A.M., Spector T.D., Doherty S., Wheeler M., Hart D.J., Doherty M. (2009) Association

of the DVWA and GDF5 polymorphisms with osteoarthritis in UK populations. Annals of the

Rheumatic Diseases: The Eular Journal 68 (12), 1916-1920.

Wagner P.D. (2000) New ideas on limitations to VO2max. Exercise and Sports Science

Reviews 28, 10-14.

Wagoner L.E., Craft L.L., Zengel P., McGuire N., Rathz D.A., Dorn G.W. 2nd, Liggett S.B. (2002)

Polymorphisms of the beta1-adrenergic receptor predict exercise capacity in heart failure.

American Heart Journal 144 (5), 840-846.

Weston A.R., Mbambo Z., Myburgh K.H. (2000) Running economy of African and Caucasian

distance runners. Medicine and Science in Sports and Exercise 32 (6), 1130-1134.

Williams R.S., Neufer P.D. (1996) Regulation of gene expression in skeletal muscle by

contractile activity. In: Rowell L.B., Shepherd J.T. (eds). The Handbook of Physiology. Exercise:

regulation and integration of multiple systems. Bethesda (Md): American Physiological Society,

1124- 1150.

Williams A.G., Rayson M.P., Jubb M., World M., Woods D.R., Hayward M., Martin J.,

Humphries S.E., Montgomery H.E. (2000) Physiology: The ACE gene and muscle performance.

Nature 403, 614.

Wolfarth B., Rankinen T., Mühlbauera S., Scherra J., Boulay M.R., Pérussec L., Rauramaad

R., Bouchard C. (2007) Association between a β2-adrenergic receptor polymorphism and elite

endurance performance. Metabolism Clinical and Experimental 56, 1649–1651.

Wolfman N.M., Hattersley G., Cox K., Celeste A.J., Nelson R., Yamaji N., Dube J.L., DiBlasio-

Smith E., Nove J., Song J.J., Wozney J.M., Rosen V. (1997) Ectopic Induction of Tendon and

Ligament in Rats by Growth and Differentiation Factors 5, 6, and 7, Members of the TGF Gene

Family. Journal of Clinical Investigation 100 (2), 321-330.

Woods D., Hickman M., Jamshidi Y., Brull D., Vassiliou V., Jones A., Humphries S.,

Montgomery H.E. (2001) Elite swimmers and the D allele of the ACE I/D polymorphism. Human

Genetics 108, 230-232.

Yamin C., Duarte J.A., Oliveira J.M., Amir O., Sagiv M., Eynon N., Sagiv M., Amir R.E. (2008)

IL6 (-174) and TNFA (-308) promoter polymorphisms are associated with systemic creatine

kinase response to eccentric exercise. European Journal of Applied Physiology 104 (3), 579-586.