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Genes and Athletic Performance: An Update

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Humans vary in their ability to achieve success in sports, and this variability mostly depends on genetic factors. The main goal of this work was to review the current progress in the understanding of genetic determinism of athlete status and to describe some novel and important DNA polymorphisms that may underlie differences in the potential to be an elite athlete. In the past 19 years, at least 155 genetic markers (located within almost all chromosomes and mtDNA) were found to be linked to elite athlete status (93 endurance-related genetic markers and 62 power/strength-related genetic markers). Importantly, 41 markers were identified within the last 2 years by performing genome-wide association studies (GWASs) of African-American, Jamaican, Japanese, and Russian athletes, indicating that GWASs represent a promising and productive way to study sports-related phenotypes. Of note, 31 genetic markers have shown positive associations with athlete status in at least 2 studies and 12 of them in 3 or more studies. Conversely, the significance of 29 markers was not replicated in at least 1 study, raising the possibility that several findings might be false-positive. Future research, including multicentre GWASs and whole-genome sequencing in large cohorts of athletes with further validation and replication, will substantially contribute to the discovery of large numbers of the causal genetic variants (mutations and DNA polymorphisms) that would partly explain the heritability of athlete status and related phenotypes.
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Posthumus M, Collins M (eds): Genetics and Sports, ed 2, revised, extended.
Med Sport Sci. Basel, Karger, 2016, vol 61, pp 41–54 (DOI: 10.1159/000445240)
Abstract
Humans vary in their ability to achieve success in sports, and this variability mostly depends on ge-
netic factors. The main goal of this work was to review the current progress in the understanding of
genetic determinism of athlete status and to describe some novel and important DNA polymor-
phisms that may underlie differences in the potential to be an elite athlete. In the past 19 years, at
least 155 genetic markers (located within almost all chromosomes and mtDNA) were found to be
linked to elite athlete status (93 endurance-related genetic markers and 62 power/strength-related
genetic markers). Importantly, 41 markers were identified within the last 2 years by performing ge-
nome-wide association studies (GWASs) of African-American, Jamaican, Japanese, and Russian ath-
letes, indicating that GWASs represent a promising and productive way to study sports-related phe-
notypes. Of note, 31 genetic markers have shown positive associations with athlete status in at least
2 studies and 12 of them in 3 or more studies. Conversely, the significance of 29 markers was not
replicated in at least 1 study, raising the possibility that several findings might be false-positive. Fu-
ture research, including multicentre GWASs and whole-genome sequencing in large cohorts of ath-
letes with further validation and replication, will substantially contribute to the discovery of large
numbers of the causal genetic variants (mutations and DNA polymorphisms) that would partly ex-
plain the heritability of athlete status and related phenotypes. © 2016 S. Karger AG, Basel
Genetic factors are considered to play a key role in athletic performance and related
phenotypes such as power, strength, aerobic capacity, flexibility, coordination, and
temperament. Despite a relatively high heritability of athlete status (up to 70% de-
pending on sport discipline)
[1] and intermediate phenotypes [2, 3] , the search for
genetic variants contributing to predisposition to success in certain types of sport has
Genes and Athletic Performance: An Update
IldusI.Ahmetov a–c · EmiliyaS.Egorova b · LeysanJ.Gabdrakhmanova a ·
OlgaN.Fedotovskaya
d
a Sport Technology Research Center, Volga Region State Academy of Physical Culture, Sport and Tourism,
and
b Laboratory of Molecular Genetics, Kazan State Medical University, Kazan , and
c Department of Molecular
Biology and Genetics, Research Institute for Physical-Chemical Medicine, Moscow , Russia;
d Department of
Physiology and Pharmacology, Karolinska Institutet, Stockholm , Sweden
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42 Ahmetov · Egorova · Gabdrakhmanova · Fedotovskaya
been a challenging task. Sports genomics is a relatively new scientific discipline focus-
ing on the organization and functioning of the genome of elite athletes
[4] . The era of
sports genomics began in the early 2000s with the discovery of the first genetic mark-
ers associated with athletic performance (e.g. ACE , ACTN3 , AMPD1 , and PPARGC1A
gene polymorphisms). With genotyping, sequencing and the use of DNA microarray
becoming widely available, a large number of genetic studies evaluating candidate
gene variants have been published with largely unconfirmed associations with elite
athlete status
[4] .
Case-control studies remain the most common study design in sports genomics
and generally involve determining whether one allele of a DNA sequence (gene or
non-coding region of DNA) is more common in a group of elite athletes than it is in
the general population, thus implying that the allele boosts performance. To avoid
false-positive results, case-control studies should have at least 1 replication with ad-
ditional athletic and non-athletic cohorts from different populations (external repli-
cation) or subgroups of the same cohort (internal replication)
[5–7] . Another way to
identify sports-related genetic markers is to compare genotype and allelic frequencies
between athletes with the best and the worst competition results
[8, 9] .
Since endurance and power are located at opposite extremes of the muscle perfor-
mance continuum, the comparison of allelic or genotype frequencies between endur-
ance and power athletes (or power/strength athletes vs. athletes involved in low-in-
tensity sports, etc.) is also a way to identify endurance/power markers
[10, 11] . Cross-
sectional association studies are another type of study design in sports genomics and
examine whether athletes with one genotype (or allele) of a particular DNA sequence
have different measures of a trait (e.g. VO
2max , running time, percentage of fast-
twitch muscle fibres, cardiac size, lactate, etc.) compared to the rest of the sample
[12,
13] .
A genome-wide association study (GWAS) is a new approach that involves rap-
idly scanning several hundred thousand (up to 5 million) markers across the complete
sets of DNA by microchips of many people to find DNA polymorphisms associated
with a particular trait. One of the advantages of the GWAS approach is that it is un-
biased with respect to genomic structure and previous knowledge of the trait (hypoth-
esis-free), in contrast to candidate gene studies, where knowledge of the trait is used
to identify candidate loci contributing to the trait of interest
[14] . Thus, GWASs fa-
cilitated by high-throughput genotyping technologies have been enormously success-
ful in identifying single-nucleotide polymorphisms (SNPs) that are associated with
complex traits.
DNA polymorphisms (with the frequency in the population of 1% or greater) and
rare DNA mutations (less than 1% frequency) can generally be classified as genetic
markers associated with endurance, power and strength (or combined power/
strength) athlete status. It should be noted that other possible athlete statuses involv-
ing coordination and flexibility have still not been studied. The significance of a par-
ticular sport-related genetic marker is based on several criteria, such as type of the
Posthumus M, Collins M (eds): Genetics and Sports, ed 2, revised, extended.
Med Sport Sci. Basel, Karger, 2016, vol 61, pp 41–54 (DOI: 10.1159/000445240)
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Genes and Sports 43
polymorphism (stop loss/gain, frameshift, missense, synonymous, 3 /5 -UTR, intron-
ic, non-coding RNA, 5 /3 -near gene, intergenic, etc.), its frequency in a given popu-
lation, number of case-control and cross-sectional studies with positive or negative
(controversial) results, total number of studied athletes, and supporting evidence
from the functional studies (overexpression or knockout models, analysis of the lucif-
erase activity with specific allele, etc.)
[15] .
Despite the obvious role of genetics in human athletic performance, there is little
unequivocal evidence in support of a specific genetic variant with a major gene effect
on a relevant performance phenotype, at least across the normal range of human trait
distributions. This may be because complex traits are fundamentally polygenic (nu-
merous genes with small effects), or because researchers failed to take into consider-
ation the full range of environmental effects, or both. It is very important to note that
each DNA locus can probably explain a very small proportion of the phenotypic vari-
ance (e.g. 0.1 to 1%) [4] . Therefore, very large sample sizes are needed to detect
associations, and various combinatorial approaches should be used.
To date, several studies have sought to define or quantify the impact of multiple
genotype combinations that influence human physical performance
[16–34] . Figure
1 presents the cumulative number of sports-related DNA polymorphisms discovered
from 1998 to 2015. By the end of June 2015, the total number of DNA polymor-
phisms with regard to sports genomics was 155. As the figure shows, most of these
polymorphisms (77%) were discovered in the last 6 years (2010–2015), indicating a
growing interest in the field of sports genomics and progress in DNA technologies.
2012200920051998 2015
79
36
8
1
155
160
140
120
100
80
60
40
20
180
0
Cumulative number of DNA polymorphisms
Fig. 1. Growth in the number
of sports-related DNA poly-
morphisms discovered from
1998 to 2015.
Posthumus M, Collins M (eds): Genetics and Sports, ed 2, revised, extended.
Med Sport Sci. Basel, Karger, 2016, vol 61, pp 41–54 (DOI: 10.1159/000445240)
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44 Ahmetov · Egorova · Gabdrakhmanova · Fedotovskaya
The search for relevant publications was primarily based on the journals indexed in
PubMed, SPORTDiscus and Google Scholar using a combination of key words (e.g.
athletes, sport, exercise, physical performance, endurance, power, strength, training,
gene, genetics, genotype, polymorphism, mutation). However, not all data from the
articles were included in the current review due to language limitations, i.e. there
were many more papers published in Chinese, German, Lithuanian, Russian, Spanish,
Ukrainian, and other languages. Furthermore, data from the articles describing per-
formance-associated polymorphisms investigated in the non-athletic cohorts or ar-
ticles with very small cohorts of athletes (less than 25) and controls, as well as papers
with mixed groups of athletes without stratification (e.g. when endurance athletes
and sprinters were analysed as a combined group) were excluded from the current
review.
A literature search revealed that at least 155 genetic markers (located within 82
autosomal genes, mitochondrial DNA, X and Y chromosomes) are linked to elite
athlete status. These include 93 endurance-related genetic markers and 62 power/
strength-related genetic markers ( tables 1 , 2 ). Importantly, 41 markers were identi-
fied within the last 2 years after performing GWASs of African-American, Jamai-
can, Japanese and Russian athletes, indicating that GWASs represent a promising
and productive way to study sports-related phenotypes. Of note, 31 genetic markers
[endurance markers: ACE I, ACTN3 577X, ADRB2 16Arg, AQP1 rs1049305 C,
AMPD1 Gln12, BDKRB2 –9, COL5A1 rs12722 T, GABPB1 rs12594956 A and
rs7181866 G, HFE 63Asp, KCNJ11 Glu23, mtDNA H haplogroup, mtDNA K hap-
logroup (unfavourable), PPARA rs4253778 G, PPARD rs2016520 C, PPARGC1A
Gly482, UCP3 rs1800849 T; power/strength markers: ACE D, ACTN3 Arg577, AGT
235Thr, AMPD1 Gln12, CKM rs1803285 G, CREM rs1531550 A, GALNT13
rs10196189 G, HIF1A 582Ser, IL6 rs1800795 G, MTHFR rs1801131 C, NOS3
rs2070744 T, PPARA rs4253778 C, PPARG 12Ala, SOD2 Ala16] have shown posi-
tiveassociations with athlete status in at least 2 studies and 12 of them (endurance
markers: ACE I, ACTN3 577X, HFE 63Asp, PPARA rs4253778 G, PPARGC1A
Gly482; power/strength markers: ACE D, ACTN3 Arg577, AMPD1 Gln12, HIF1A
582Ser, MTHFR rs1801131 C, NOS3 rs2070744 T, PPARG 12Ala) in 3 or more stud-
ies. Conversely, the significance of 29 markers was not replicated in at least 1 study
[for details, see
4 ], raising the possibility that several findings might be false-positive
and require additional studies. Interestingly, almost all chromosomes (except for
chromosome 20) include sport-related genetic markers.
According to existing data, endurance athlete status remains the most studied
trait. Due to space limitations, there was no possibility to describe all 155 DNA poly-
morphisms in the current paper, but it should be noted that 120 of these genetic
markers (mainly identified by candidate gene approach) were comprehensively
characterized in a very recent review
[4] . Given that, in this review we focus on the
description of novel DNA polymorphisms recently identified by the GWAS ap-
proach.
Posthumus M, Collins M (eds): Genetics and Sports, ed 2, revised, extended.
Med Sport Sci. Basel, Karger, 2016, vol 61, pp 41–54 (DOI: 10.1159/000445240)
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Genes and Sports 45
Table 1. Gene variants (genetic markers) for endurance athlete status
Gene Location Polymorphism Endurance-related marker
ACE 17q23.3 Alu I/D (rs4646994) I
ACOXL 2q13 rs13027870 A/G rs13027870 G
ACTN3 11q13.1 R577X (rs1815739 C/T) 577X
ADRA2A 10q24–q26 6.7/6.3 kb 6.7 kb
ADRB1 10q25.3 Ser49Gly (rs1801252 A/G) 49Gly
ADRB2 5q31–q32 Gly16Arg (rs1042713 G/A) 16Arg
ADRB3 8p12–8p11.1 Trp64Arg (rs4994 T/C) 64Arg
AGTR2 Xq22–q23 rs11091046 A/C rs11091046 C
AQP1 7p14 rs1049305 C/G rs1049305 C
AMPD1 1p13 Gln12X (rs17602729 C/T) Gln12
BDKRB2 14q32.1–q32.2 +9/–9 (exon 1) –9
rs1799722 C/T rs1799722 T
CAMK1D 10p13 rs11257754 A/G rs11257754 A
CKM 19q13.32 rs8111989 A/G (NcoI) rs8111989 A
CLSTN2 3q23 rs2194938 A/C rs2194938 A
COL5A1 9q34.2–q34.3 rs12722 C/T (BstUI) rs12722 T
rs71746744 (AGGG/–) rs71746744 AGGG
COL6A1 21q22.3 rs35796750 T/C rs35796750 T
CPQ 8q22.2 rs6468527 A/G rs6468527 A
EPAS1 (HIF2A) 2p21–p16 rs1867785 A/G rs1867785 G
rs11689011 C/T rs11689011 T
GABPB1 (NRF2) 15q21.2 rs12594956 A/C rs12594956 A
rs8031031 C/T rs8031031 T
rs7181866 A/G rs7181866 G
GALM 2p22.1 rs3821023 A/G rs3821023 A
GNB3 2p13 rs5443 C/T (C825T) rs5443 T
GRM3 7q21.1–q21.2 rs724225 A/G rs724225 G
HFE 6p21.3 His63Asp (rs1799945 C/G) 63Asp
HIF1A 14q23.2 Pro582Ser (rs11549465 C/T) Pro582
IGF1R 15q26.3 rs1464430 A/C rs1464430 A
IL15RA 10p15.1 Asn146Thr (rs2228059 A/C) 146Thr
ITPR1 3p26.1 rs1038639 G/T rs1038639 T
rs2131458 C/T rs2131458 T
FMNL2 2q23.3 rs12693407 A/G rs12693407 G
KCNJ11 11p15.1 Glu23Lys (rs5219 C/T) Glu23
L3MBTL4 18p11.31 rs17483463 C/T rs17483463 T
MCT1 (SLC16A1) 1p12 Glu490Asp or A1470T (rs1049434 A/T) Glu490
mtDNA loci mtDNA Haplogroups constructed from several mtDNA
polymorphisms or single polymorphisms
G1
H
HV
L0
M*
m.11215T, m.152C, m.15518T, m.15874G, m.4343G,
m.514(CA)≤4, poly(C ≥7) stretch at m.568–573
m.16080G
m.5178C
N9
V
Unfavourable: B
Unfavourable: K
Unfavourable: J2
Unfavourable: T
Unfavourable: L3*
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Med Sport Sci. Basel, Karger, 2016, vol 61, pp 41–54 (DOI: 10.1159/000445240)
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46 Ahmetov · Egorova · Gabdrakhmanova · Fedotovskaya
Gene Variants and Endurance Athlete Status
A literature search revealed at least 93 markers are associated with endurance athlete
status, and 19 of them were discovered by the use of microchip technology ( table1 ).
Initially, Ahmetov et al.
[7] examined the association between 1,140,419 SNPs and the
relative maximal oxygen consumption rate (V
O
2max ) in 80 international-level Russian
endurance athletes (46 males and 34 females), and identified 6 suggestive ‘endurance
alleles’ (with p< 10
–5 to 10
–8 ) which were replicated both in female and male sub-
groups. To validate the obtained results, the authors further performed case-control
studies by comparing the frequencies of 6 SNPs between 218 endurance athletes (or
100 elite endurance athletes) and opposite cohorts (192 Russian controls, 1,367
European controls, and 230 Russian power athletes). It was assumed that the
Gene Location Polymorphism Endurance-related marker
NALCN-AS1 13q33.1 rs4772341 A/G rs4772341 A
NATD1 17p11.2 rs732928 A/G rs732928 G
NFATC4 14q11.2 Gly160Ala (rs2229309 G/C) Gly160
NFIA-AS2 1p31.3 rs1572312 C/A rs1572312 C
NOS3 7q36 Glu298Asp (rs1799983 G/T) Glu298
(CA)n repeats 164 bp
27-bp repeats (4B/4A) 4B
rs2070744 T/C (–786 T/C) rs2070744 T
PPARA 22q13.31 rs4253778 G/C rs4253778 G
PPARD 6p21.2–p21.1 rs2016520 T/C rs2016520 C
rs1053049 T/C rs1053049 T
PPARGC1A 4p15.1 Gly482Ser (rs8192678 G/A) Gly482
rs4697425 A/G rs4697425 A
PPARGC1B 5q32 Ala203Pro (rs7732671 G/C) 203Pro
Arg292Ser (rs11959820 C/A) 292Ser
PPP3CA 4q24 rs3804358 C/G rs3804358 C
PPP3CB 10q22.2 rs3763679 C/T rs3763679 C
PPP3R1 2p15 Promoter 5I/5D 5I
RBFOX1 16p13.3 rs7191721 G/A rs7191721 G
SGMS1 10q11.2 rs884880 A/C rs884880 A
SLC2A4 17p13 rs5418 G/A rs5418 A
SOD2 6q25.3 Ala16Val (rs4880 C/T) C (Ala)
SPOCK1 5q31.2 rs1051854 G/T rs1051854 T
TFAM 10q21 Ser12Thr (rs1937 G/C) 12Thr
TPK1 7q34–q35 rs10275875 C/T rs10275875 T
TSHR 14q31 rs7144481 T/C rs7144481 C
UCP2 11q13 Ala55Val (rs660339 C/T) 55Val
UCP3 11q13 rs1800849 C/T rs1800849 T
VEGFA 6p12 rs2010963 G/C rs2010963 C
VEGFR2 4q11–q12 His472Gln (rs1870377 T/A) 472Gln
Y chromosome
haplogroups
Y
chromosome
Haplogroups constructed from several Y
chromosome polymorphisms
E*, E3* and K*(xP)
Unfavourable: E3b1
ZNF429 19p12 rs1984771 A/G rs1984771 G
Table 1. Continued
Posthumus M, Collins M (eds): Genetics and Sports, ed 2, revised, extended.
Med Sport Sci. Basel, Karger, 2016, vol 61, pp 41–54 (DOI: 10.1159/000445240)
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Genes and Sports 47
Table 2. Gene variants (genetic markers) for power/strength athlete status
Gene Location Polymorphism Power/strength-related marker
ACE 17q23.3 AluI/D (rs4646994) D
ACTN3 11q13.1 R577X (rs1815739 C/T) Arg577
ADRB2 5q31–q32 Gly16Arg (rs1042713 G/A) Gly16
Gln27Glu (rs1042714 C/G) 27Glu
AGT 1q42.2 Met235Thr (rs699 T/C) 235Thr
AGTR2 Xq22–q23 rs11091046 A/C rs11091046 A
AMPD1 1p13 Gln12X (rs17602729 C/T) Gln12
ARHGEF28 5q13.2 rs17664695 A/G rs17664695 G
CACNG1 17q24 Gly196Ser (rs1799938 G/A) 196Ser
CALCR 7q21.3 rs17734766 A/G rs17734766 G
CKM 19q13.32 rs8111989 A/G (NcoI) rs8111989 G
CLSTN2 3q23 rs2194938 A/C rs2194938 C
COTL1 16q24.1 rs7458 C/T rs7458 T
CREM 10p11.21 rs1531550 G/A rs1531550 A
DMD Xp21.2 rs939787 C/T rs939787 T
EPAS1 (HIF2A) 2p21–p16 rs1867785 A/G rs1867785 G
rs11689011 C/T rs11689011 C
FOCAD 9p21 rs17759424 A/C rs17759424 C
GABRR1 6q15 rs282114 A/G rs282114 A
GALNT13 2q24.1 rs10196189 A/G rs10196189 G
GPC5 13q32 rs852918 G/T rs852918 T
HIF1A 14q21–q24 Pro582Ser (rs11549465 C/T) 582Ser
HSD17B14 19q13.33 rs7247312 A/G rs7247312 G
IGF1 12q23.2 C–1245T (rs35767 C/T) rs35767 T
IGF1R 15q26.3 rs1464430 A/C rs1464430 C
IL1RN 2q14.2 VNTR 86-bp (intron 2) IL1RN*2
IL6 7p21 –174 C/G (rs1800795 C/G) rs1800795 G
IP6K3 6p21.31 rs6942022 C/T rs6942022 C
MCT1 (SLC16A1) 1p12 Glu490Asp or A1470T (rs1049434 A/T) 490Asp
MED4 13q14.2 rs7337521 G/T rs7337521 T
MPRIP 17p11.2 rs6502557 A/G rs6502557 A
mtDNA loci mtDNA Haplogroups constructed from several
mtDNA polymorphisms or single
polymorphisms
F
m.204C
m.151T
m.15314A
Non-L/U6
Unfavourable: m.16278T, m.5601T, m.4833G, m.5108C,
m.7600A, m.9377G, m.13563G, m.14200C, m.14569A
MTHFR 1p36.3 A1298C (rs1801131 A/C) rs1801131 C
MTR 1q43 A2756G (rs1805087 A/G) rs1805087 G
MTRR 5p15.31 A66G (rs1801394 A/G) rs1801394 G
NOS3 7q36 rs2070744 T/C (–786 T/C) rs2070744 T
Glu298Asp (rs1799983 G/T) Glu298
NRG1 8p12 rs17721043 A/G rs17721043 A
PPARA 22q13.31 rs4253778 G/C rs4253778 C
PPARG 3p25 Pro12Ala (rs1801282 C/G) 12Ala
PPARGC1B 5q32 rs10060424 C/T rs10060424 C
RC3H1 1q25.1 rs767053 A/G rs767053 G
SOD2 6q25.3 Ala16Val (rs4880 C/T) C (Ala)
SUCLA2 13q14.2 rs10397 A/C rs10397 A
Posthumus M, Collins M (eds): Genetics and Sports, ed 2, revised, extended.
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48 Ahmetov · Egorova · Gabdrakhmanova · Fedotovskaya
endurance allele’ should be underrepresented in at least 1 opposite cohort (Russian
controls or Russian power athletes) when compared to endurance athletes. This ap-
proach resulted in the remaining 3 SNPs ( NFIA-AS2 rs1572312 C, TSHR rs7144481
C, RBFOX1 rs7191721 G) to be associated with endurance athlete status.
The NFIA-AS2 gene encodes long non-coding RNA with undescribed function.
Genes of antisense long non-coding RNAs are transcribed from either the same ge-
nomic site or a site distant from the gene locus where the sense transcript counterpart
is produced. Antisense long non-coding RNAs repress – and in some cases can also
activate – transcription of the targeted protein coding genes via mechanisms such as
DNA methylation and chromatin modification at the genomic loci of the targeted
genes. It was hypothesized that NFIA-AS2 is involved in the regulation of expression
of the nuclear factor IA ( NFIA ) gene or erythroid/myeloid-specific RNAs. NFIA, as a
transcription factor, induces erythropoiesis, whereas its silencing drives granulopoie-
sis. Consistent with the hypothesis, the authors also reported that the C allele was as-
sociated with activation of erythropoiesis (high level of haemoglobin, high number of
reticulocytes and erythrocytes), while the A allele was associated with activated granu-
lopoiesis (high number of neutrophils and greater leucocyte/erythrocyte ratio)
[7] .
As to the other 2 gene polymorphisms, it was established that RNA binding protein,
fox-1 homolog (Caenorhabditis elegans) 1 (encoded by the RBFOX1 gene) is an impor-
tant splicing factor regulating developmental and tissue-specific alternative splicing in
heart, muscle, and neuronal tissues
[35] . Therefore, RBFOX1 is implicated in multiple
medical conditions, including muscular dystrophies, cancers, neurodevelopmental and
neuropsychiatric disorders. The thyroid-stimulating hormone receptor encoded by the
TSHR gene is a membrane receptor for thyrotropin (produces thyroid hormones) and
thyrostimulin (activates TSHR protein), and therefore a major controller of thyroid cell
metabolism. Thyroid hormones are known as determinants of the metabolic and con-
tractile phenotype of skeletal muscle
[36] . TSHR also mediates the effect of thyrotropin
on angiogenesis via cAMP-mammalian target of rapamycin signalling
[37] . The
rs7144481 polymorphism is located in the regulatory region (3 -UTR) of the TSHR gene.
With respect to the same groups of athletes and GWAS data using different criteria,
such as (i) the SNP should be independently associated with V
O
2max in male and fe-
male athletes separately (with p< 10
–3 adjusted for sex), (ii) the frequency of the en-
durance-related allele should be overrepresented in endurance athletes in comparison
Gene Location Polymorphism Power/strength-related marker
TPK1 7q34–q35 rs10275875 C/T rs10275875 С
UCP2 11q13 Ala55Val (rs660339 C/T) Ala55
VDR 12q13.11 FokI f/F (rs10735810 T/C) rs10735810 T
WAPAL 10q23.2 rs4934207 C/T rs4934207 C
ZNF423 16q12 rs11865138 C/T rs11865138 C
Table 2. Continued
Posthumus M, Collins M (eds): Genetics and Sports, ed 2, revised, extended.
Med Sport Sci. Basel, Karger, 2016, vol 61, pp 41–54 (DOI: 10.1159/000445240)
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Genes and Sports 49
with controls and (iii) power athletes, the same group of authors identified an addi-
tional 6 alleles ( ZNF429 rs1984771 G, FMNL2 rs12693407 G, ACOXL rs13027870 G,
ITPR1 rs2131458 A, GALM rs3821023 A, NATD1 rs732928 G) with a suggested sig-
nificance for the determination of endurance performance
[38] . These SNPs are lo-
cated in the genes involved in the regulation of lipid (ACOXL) and carbohydrate
(GALM) metabolism, morphogenesis and cytokinesis (FMNL2) , intracellular Ca
2+
signalling (ITPR1) and other processes (ZNF429, NATD1) .
In the third study of the same group, Galeeva et al.
[39] performed a GWAS in 4
subgroups of Russian endurance athletes (n= 223; all and elite long-distance athletes,
all and elite middle-distance athletes) and controls (n= 173), and found 93 SNPs as-
sociated with endurance athlete status with replications in all subgroups (p< 10
–4 ),
but none of them reached a genome-wide significance level. Adding 3 criteria – (i) an
increase in the frequency of the effect allele with an increase in the level of achieve-
ment of endurance athletes, (ii) significant differences in allelic frequencies between
56 elite endurance athletes and 67 elite power athletes (second case-control study),
and (iii) a positive correlation of the effect allele with high values of V
O
2max – result-
ed in the remaining 5 SNPs (effect alleles: CAMK1D rs11257754 A, CPQ rs6468527
A, GRM3 rs724225 G, SGMS1 rs884880 A, L3MBTL4 rs17483463 T) to be associated
with elite endurance athlete status. These SNPs are located in the genes involved in
the regulation of carbohydrate metabolism (CAMK1D) , synthesis of thyroxine (CPQ) ,
glutamatergic neurotransmission (GRM3) , sphingomyelin and diacylglycerol metab-
olism ( SGMS1 ) and chromatin modification (L3MBTL4) .
Finally, Gabdrakhmanova et al. [40] studied the differences in genomic profiles be-
tween Russian endurance and power athletes using the GWAS approach. At the first
stage, by comparing genetic profiles of 2 groups of elite athletes (171 elite power and 56
elite endurance athletes), the authors identified 13 SNPs with suggestive significance (p
values from 10
–5 to 10 –6 ). At the second stage, they compared allelic frequencies of the
discovered SNPs between 223 endurance athletes and 173 controls. As a final point, the
regression analysis was performed to reveal the association with VO
2max of endurance
athletes (n= 71). These analyses resulted in the remaining 5 SNPs ( CLSTN2 rs2194938
A, TPK1 rs10275875 T, ITPR1 rs1038639 T, NALCN-AS1 rs4772341 A, SPOCK1
rs1051854 T) to be associated with endurance athlete status (based on case-control
study and correlation with VO
2max ). These SNPs are located in the genes involved in
the regulation of neuronal excitability (CLSTN2, NALCN-AS1) , vitamin B
1 metabolism
(TPK1) , muscle contraction (ITPR1) , and protein metabolism (SPOCK1) .
Gene Variants and Power/Strength Athlete Status
A literature search revealed at least 62 markers are associated with power/strength
athlete status, and 22 of them were discovered by the use of microchip technology
( table2 ). By performing 3 GWASs of elite Jamaican (n= 95), African-American (n=
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50 Ahmetov · Egorova · Gabdrakhmanova · Fedotovskaya
108), and Japanese (n= 54) sprint athletes and their matched controls (total number
of controls: 617) and a subsequent meta-analysis, Wang et al.
[41] found that the
CREM A allele of the rs1531550 (G/A) polymorphism and the GALNT13 G allele of
the rs10196189 (A/G) polymorphism were significantly (p< 2 × 10
–6 ) overrepresent-
ed in elite sprinters compared with controls. These results were also replicated (p<
0.001) in the Russian cohorts of sprinters and power/strength athletes [unpubl. data].
The CREM gene encodes a cAMP-responsive element modulator which is a bZIP
transcription factor that binds to the cAMP-responsive element found in many viral
and cellular promoters. It is an important component of cAMP-mediated signal
transduction during the spermatogenetic cycle, as well as other complex processes
[42] . CREM is highly expressed in the testis, heart, brain, pancreas, and retina. The
UDP-N-acetyl-α-
D -galactosamine:polypeptide N-acetylgalactosaminyltransferase 13
protein (encoded by GALNT13 ) is a member of the GALNT family, which initiates
O-linked glycosylation of mucins by the initial transfer of N-acetylgalactosamine with
an α-linkage to a serine or threonine residue and thus catalyses the initial reaction in
O-linked oligosaccharide biosynthesis. GALNT13 is highly expressed in the brain, B
cells, kidney and liver and may be involved in metabolism and energy pathways
[43] .
In the GWAS of 483 Russian athletes (49 strength athletes, 103 endurance athletes
and 331 athletes from other sports with a strength component: 89 sprinters, 38
strength/speed athletes, 64 wrestlers, 42 rugby players, 98 rowers/kayakers/canoers)
and 173 controls, Egorova et al.
[44] first identified 43 SNPs associated (p< 10
–5 ) with
elite strength athlete status (when compared with controls), but none of them reached
a genome-wide significance level. Adding 3 criteria – (i) an increase in the frequency
of the effect allele with an increase in the level of achievement of strength athletes, (ii)
significant differences in allelic frequencies between strength and endurance athletes,
and (iii) at least 1 replication of association between effect alleles and predisposition
to other sports with strength component – resulted in the remaining 8 SNPs [ SUCLA2
rs10397 A, MED4 rs7337521 T, GPC5 rs852918 T, GABRR1 rs282114 A, CACNG1
rs1799938 A (196Ser), ARHGEF28 rs17664695 G, WAPAL rs4934207 C, MPRIP
rs6502557 A alleles] with p values from 9.1 × 10
–5 to 3.1 × 10
–6 . These SNPs are lo-
cated in the genes involved in the regulation of ATP production ( SUCLA2 ), transcrip-
tion of DNA ( MED4 ), cell division and growth (GPC5, ARHGEF28) , neurotransmis-
sion (GABRR1) , muscle contraction (CACNG1, MPRIP) , and DNA repair (WAPAL) .
In another study, Ischenko et al. [45] performed a GWAS in 176 Russian power (89
sprinters, 38 speed/strength athletes and 49 strength athletes) athletes, a group of ath-
letes with a speed/strength component (n= 204; 64 wrestlers, 42 rugby players, 98 row-
ers/kayakers/canoers), 223 endurance athletes and 173 controls. Initially, they per-
formed 7 analyses using the GWAS data (elite power athletes vs. controls, all sprinters
vs. controls, elite sprinters vs. controls, all speed/strength athletes vs. controls, elite
speed/strength athletes vs. controls, all strength athletes vs. controls, elite strength ath-
letes vs. controls) and found 68 SNPs which were associated with power athlete status
(with p values from 0.001 to 1.34 × 10
–5 ) and replicated in all 3 subgroups of power
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Genes and Sports 51
athletes (regardless of their level of achievement). The comparison of allelic frequen-
cies of these SNPs between the large cohort of power athletes (n= 380; i.e. power ath-
letes plus group of athletes with speed/strength component) and endurance athletes
(as a second control group) resulted in the remaining 8 SNPs ( PPARGC1B rs10060424
C, NRG1 rs17721043 A, ZNF423 rs11865138 C, RC3H1 rs767053 G, IP6K3 rs6942022
C, HSD17B14 rs7247312 G, CALCR rs17734766 G, COTL1 rs7458 T) associated with
power athlete status. These SNPs are located in the genes involved in the regulation of
muscle fibre composition and carbohydrate/lipid metabolism (PPARGC1B) , growth
and development (NRG1, ZNF423) , mRNA deadenylation and degradation (RC3H1) ,
metabolism of inositol hexakisphosphate (IP6K3) , metabolism of steroids (HSD17B14) ,
calcium homeostasis (CALCR) and actin cytoskeleton (COTL1) .
The comparison of genetic profiles of 492 elite Russian power/strength and 227
endurance athletes and controls revealed that the rare DMD rs939787 T allele was
overrepresented in power/strength athletes (25.0%) compared to endurance athletes
(8.8%; p= 3.9 × 10
–9 ) and controls (16.3%; p= 0.0354). These results indicate that the
DMD rs939787 T allele is favourable for power/strength performance
[46] . The dys-
trophin ( DMD ) gene is the largest gene found in nature (2.4 Mb). Dystrophin is a
large, rod-like cytoskeletal protein which is found at the inner surface of muscle fibres.
Dystrophin is part of the dystrophin-glycoprotein complex, which bridges the inner
cytoskeleton (F actin) and the extracellular matrix. In the subsequent study, by com-
paring genetic profiles of 2 groups of elite Russian athletes (171 elite power and 56
elite endurance athletes), and then between power athletes and controls, Gabdra-
khmanova et al.
[40] identified 3 SNPs (effect alleles: CLSTN2 rs2194938 C, FOCAD
rs17759424 C, TPK1 rs10275875 С) associated with power athlete status. These SNPs
are located in the genes involved in the regulation of neuronal excitability (CLSTN2) ,
cell growth (FOCAD) , and vitamin B
1 metabolism (TPK1) .
Conclusion
The current review provides evidence that at least 155 genetic markers are linked to
elite athlete status. However, it should be emphasized that most (80%) of the case-
control and association studies have not yet been replicated in independent samples.
Based on that, we strongly believe that much more research is needed before these
findings can be extended to practice in sport. On the other hand, since sport-related
DNA polymorphisms do not fully explain the heritability of athlete status, other forms
of variation, such as rare mutations and epigenetic markers (i.e. stable and heritable
changes in gene expression), must be considered. The issues with respect to appropri-
ate study designs, sample size, population stratification, and quality of the genotype/
phenotype measurement are also of great importance. Future research should also be
focused on identifying genetic markers associated with other sport-related pheno-
types, such as flexibility, coordination and temperament of elite athletes.
Posthumus M, Collins M (eds): Genetics and Sports, ed 2, revised, extended.
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52 Ahmetov · Egorova · Gabdrakhmanova · Fedotovskaya
The impact of genetics in sports and exercise appears to have multiple influences.
Its positive effect on exercise performance must be combined with effective training
programmes and favourable lifestyle habits for success in sports and health benefits
[47] . Accordingly, one of the applications of sports genetics could be the development
of predictive genetic performance tests, although it is still too premature currently in
sports genomics to be able to definitively test for predictive genetic markers
[48] . Fur-
thermore, the application of genetic testing in sports could provide new opportunities
for sports clubs to understand the athletes’ susceptibility to certain pathological states
(injuries, cardiomyopathies, sudden death, etc.), to map genetic suitability for spe-
cific team positions and roles, and to gain insights into the athletes’ development in
various sports or physical activities. Future research including multicentre GWASs
and whole-genome sequencing in large cohorts of athletes with further validation and
replication will substantially contribute to the discovery of large numbers of the caus-
al genetic variants (mutations and DNA polymorphisms) that would partly explain
the heritability of athlete status and related phenotypes.
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... Athletic performances are influenced by environmental factors (training, lifestyle, physiological and psychological factors) and genetics [1]. On average, 66% (depending on sports discipline) of the variance in the athlete status is explained by genetic factors [2]. The combination of phenotype with genotype could be the key to excellence [3]. ...
... Sports genetics relates to the genotypic basis of sport phenotype. Angiotensinconverting enzyme (ACE) and alfa-actinin 3 (ACTN3) are two of the most studied genes influencing endurance, strength/power and other phenotypic traits concerning athletic performance [2,4,5], while monocarboxylate transporter 1 (MCT1) gene analysis, instead, showed correlations with skeletal muscles capacity to take up lactate from the circulation [6] which is linked with elite sprint/power athletic status [7]. ...
... It is considered by Woods [8] not a "gene for human performance, but a marker of modulation". Among others, ACE is associated with endurance polygenic [2,4,5,8]. Generally, the I allele is more frequent in elite endurance athletes, while the D allele among those engaged in more power-oriented sports, given the enzyme highest fasttwitch muscle fibers [2,4,5,8]. ACTN3 is known as the "speed gene" [9] and more recently it has been investigated with its association with physical performance. ...
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Athletic performance is influenced by many factors such as the environment, diet, training and endurance or speed in physical effort and by genetic predisposition. Just a few studies have analyzed the impact of genotypes on physical performance in rugby. The aim of this study was to verify the modulation of genetic influence on rugby-specific physical performance. Twenty-seven elite rugby union players were involved in the study during the in-season phase. Molecular genotyping was performed for: angiotensin-converting enzyme (ACE rs4646994), alfa-actinin-3 (ACTN3 rs1815739) and monocarboxylate transporter 1 (MCT1 rs1049434) and their variants. Lean mass index (from skinfolds), lower-limb explosive power (countermovement jump), agility (505), speed (20 m), maximal aerobic power (Yo-yo intermittent recovery test level 1) and repeated sprint ability (12 × 20 m) were evaluated. In our rugby union players ACE and ACTN3 variants did not show any influence on athletic performance. MCT1 analysis showed that TT-variant players had the highest peak vertical power (p = 0.037) while the ones with the AA genotype were the fastest in both agility and sprint tests (p = 0.006 and p = 0.012, respectively). Considering the T-dominant model, the AA genotype remains the fastest in both tests (agility: p = 0.013, speed: p = 0.017). Only the MCT1 rs1049434 A allele seems to be advantageous for elite rugby union players, particularly when power and speed are required.
... Elite athletes are thought to have an exceptional genetic potential [1] with incredible interindividual variability of physical performance traits (i.e., power, strength, endurance, muscle fiber composition and size, neuromuscular coordination and flexibility), personality profile [2], VO2 max (maximum oxygen consumption) and injury susceptibility [3]. ...
... The physical performance of athletes has been linked to more than 200 genetic variants, among which 155 correlate with elite athlete status [2]. In opposition, genetic foundations of competition-facilitating behavior and low stress response that influence elite performances are still scarce [4][5][6][7]. ...
... Previous studies have shown that genetic determinants among Angiotensin-I-Converting Enzyme (ACE), Actinin Alpha 3 (ACTN3), Angiotensinogen (AGT), NFE2-like BZIP Transcription Factor 2 (NRF-2), PPARG Coactivator 1 Alpha (PGC1A), Peroxisome Proliferator-Activated Receptor Gamma (PPARG) and Transcription Factor A, Mitochondrial (TFAM) genes are associated with sport-type (for instance endurance versus power) [2,5]. However, results are conflicted, and few genetic variants are linked to psychological traits and sport injuries [4] in relation to elite sport performance. ...
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Genetic factors are among the major contributors to athletic performance. Although more than 150 genetic variants have been correlated with elite athlete status, genetic foundations of competition-facilitating behavior influencing elite performances are still scarce. This is the first study designed to examine the distribution of genetic determinants in the athletic performance of elite rink-hockey players. A total of 116 of the world’s top best rink-hockey players (28.2 ± 8.7 years old; more than 50% are cumulatively from the best four world teams and the best five Portuguese teams), who participated at the elite level in the National Rink-Hockey Championship in Portugal, were evaluated in anthropometric indicators/measurements, training conditions, sport experience and sport injuries history. Seven genetic polymorphisms were analyzed. Polymorphism genotyping was performed using the TaqMan® Allelic Discrimination Methodology. Rink-hockey players demonstrated significantly different characteristics according to sex, namely anthropometrics, training habits, sports injuries and genetic variants, such as Vitamin D Receptor (VDR) rs731236 (p < 0.05). The Fatty Acid Amide Hydrolase (FAAH) rs324420 A allele was significantly associated with improved athletic performance (AA/AC vs. CC, OR = 2.80; 95% Cl, 1.23–6.35; p = 0.014; p = 0.008 after Bootstrap) and confirmed as an independent predictor among elite rink-hockey players (adjusted OR = 2.88; 95% Cl, 1.06–7.80; p = 0.038). Our results open an interesting link from FAAH-related biology to athletic performance.
... A large and growing body of literature has investigated the impact of many polymorphic variants on changes in athletic performance and conflicting results have been obtained [12,13]. The literature search uncovered approximately 300 genetic markers associated with athletic performance. ...
... These include 93 endurance-and 62 power/strengthrelated genetic markers. Most of the data were recognized with the use of the candidate gene approach [12] and were well-described in [11,14]. Much of the current literature pays particular attention to MCT1, NRF2, MYBPC3 and HFE genes. ...
... MYBPC3 codes for the thick-filament-associated protein cardiac myosin-binding protein C, and thus is linked with muscle sarcomeric structure and its contraction and relaxation [21]. MCT1, NRF2 and HFE were listed in [12]. All four were also published elsewhere (MCT1 in [22][23][24][25], NRF2 in [26,27], MYBPC3 in [28], and HFE in [18]). ...
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Background: To date, nearly 300 genetic markers were linked to endurance and power/strength traits. The current study aimed to compare genotype distributions and allele frequencies of the common polymorphisms: MCT1 rs1049434, NRF2 rs12594956, MYBPC3 rs1052373 and HFE rs1799945 in Polish elite athletes versus nonathletes. Methods: The study involved 101 male elite Polish athletes and 41 healthy individuals from the Polish population as a control group. SNP data were extracted from whole-genome sequencing (WGS) performed using the following parameters: paired reads of 150 bps, at least 90 Gb of data per sample with 300 M reads and 30× mean coverage. Results: All the analyzed polymorphisms conformed to Hardy-Weinberg equilibrium (HWE) in athletes and the control group, except the MCT1 rs1049434, where allele T was over-represented in the elite trainers' group. No significant between-group differences were found for analyzed polymorphisms. Conclusions: The MCT1 rs1049434 transmission distortion might be characteristic of Polish athletes and the effect of strict inclusion criteria. This result and the lack of statistically significant changes in the frequency of other polymorphisms between the groups might result from the small group size.
... Following the introduction of human DNA sequences with the Genome Project in 2000, the number of studies that reveal the relationship between athletic performance and genes has started to increase [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. There are more than a hundred genes related to athletic capacity [16]. The top well-known gene related to the physical capacity is the Angiotensin-Converting Enzyme (ACE) gene. ...
... Due to expanded vasoconstriction in individuals with high ACE activity there's not sufficient blood stream to the muscle tissue [18]. People with low ACE activity have a high level of endurance performance and long duration of exercise efficiency due to the wealthy blood circulation [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. In people with high ACE enzyme activity, long-term endurance performance (exertion levels that can be sustained for more than 30 min) is low because of the increased vasoconstriction due to insufficient blood flow to the muscle tissue; on the other hand, short-term endurance (exertion levels that can be sustained for 2-8 min) [20], strength and power development are observed at medium and high levels. ...
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Background The aim of this study is to determine the effect of ACE gene polymorphism on the parameters studied (push-up & sit-up) in a long-term study, which has been carried out for many years and to find out whether the differences in ACE gene's metabolism due to the influence of parameters such as outside impacts and lifestyle (active or sedentary life) have a role in the development of strength endurance or not. Main text 59 male army officers made up the research team. A follow-up study of strength endurance (push-up and sit-up) test was conducted in the gym. The exam took two minutes to complete, and each application was tested separately. In both 2004 and 2019, persons with genotype ID had the best mean sit-up and push-up outcomes, followed by participants with genotype DD, and finally participants with genotype II ( P 0.05). Compared to the original rates in 2004, all genotype groups showed a significant reduction in push-up and sit-up scores in the test. Conclusion The findings of this study may reveal if strength and lifestyle choices affect the metabolic implications of the genetic polymorphism in the body. Particular varieties actuated by genes, on either hand, don’t result in significant improvements without any changes in individuals’ practices or ways of living, as per the conclusions.
... 9 Later on, a comprehensive review identified 155 genetic markers linked to athletic status. 10 The angiotensin I converting enzyme insertion/ deletion variant (ACE I/D) is one of the most frequently studied variation in sport genetics, and the insertion allele has been linked to endurance performance, while the deletion allele has been linked to muscular power. 11,12 Traditionally, polymorphism investigations in sport science have focused on the two opposite sides of the neuromuscular spectrum, that is, power vs. endurance sports. ...
... (i) Most publications in the field of sport genetics make use of a candidate gene approach in which replication of results is often lacking. 10,121 We also found 29 genetic variants that were not replicated, at least not within (inter) national competing runners and cyclists. To date, only a handful of genome wide association studies have been conducted. ...
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Abstract The aim of this systematic review and meta‐analysis was to identify the genetic variants of (inter)national competing long‐distance runners and road cyclists compared to controls. The Medline and Embase databases were searched until 15 November 2021. Eligible articles included genetic epidemiological studies published in English. A homogenous group of endurance athletes competing at (inter)national level and sedentary controls were included. Pooled odds ratios based on genotype frequency with corresponding 95% confidence intervals (95%CI) were calculated using random effects models. Heterogeneity was addressed by Q‐statistics and I2. Sources of heterogeneity were examined by meta‐regression and risk of bias was assessed with the Clark Baudouin scale. This systematic review comprised of 43 studies including a total of 3938 athletes and 10752 controls in the pooled analysis. Of the 42 identified genetic variants, 13 were investigated in independent studies. Significant associations were found for five polymorphisms. Pooled odds ratio [95%CI] favoring athletes compared to controls was 1.42 [1.12‐1.81] for ACE II (I/D), 1.66 [1.26‐2.19] for ACTN3 TT (rs1815739), 1.75 [1.34‐2.29] for PPARGC1A GG (rs8192678), 2.23 [1.42‐3.51] for AMPD1 CC (rs17602729), and 2.85 [1.27‐6.39] for HFE GG+CG (rs1799945). Risk of bias was low in 25 (58%) and unclear in 18 (42%) articles. Heterogeneity of the results was low (0‐20%) except for HFE (71%), GNB3 (80%), and NOS3 (76%). (Inter)national competing runners and cyclists have a higher probability to carry specific genetic variants compared to controls. This study confirms that (inter)national competing endurance athletes constitute a unique genetic make‐up, which likely contributes to their performance level.
... Among them, physical factors are more discussed in TID. Genetic factors are considered to play a critical role in athletic performance and related phenotypes (Miah and Rich, 2006;Ahmetov et al., 2016;David et al., 2017). There is a consensus in the scientific and sporting communities that genetic factors contribute to athletic performance. ...
... According to research, at least 155 genetic markers were found to be related to elite athlete performance (93 genetic markers related to endurance and 62 genetic markers related to power/strength). Meanwhile, genomewide association studies (GWASs) are the most commonly used method to identify athletic performance in athletes (Ahmetov et al., 2016). Components like height, body fat percentage, size of palm, dynamic balance, static balance, and hand strength were the key elements in TID of badminton (Mojtaba et al., 2012). ...
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Talent is one of the most significant factors to promote the development of sports undertakings. The present study aimed to explore the factors affecting the identification of sports talents in China's physical education curriculum. Based on the literature review, this study puts forward a model to examine the influencing factors of sports talent identification in China's physical education curriculum using structural equation modeling and uses the structural equation modeling and factor analysis method to verify the hypothesis combined with the results of 310 effective questionnaires. The article summarizes influencing factors from four aspects, namely, physical, psychological, coach, and environmental factors. On the basis of relevant literature, the hypothesis model was established by structural equation modeling. The results show that the main factors affecting the identification of sports talents in the physical education curriculum are personal physical quality performance, psychological quality, coach's knowledge, and the identification policies of schools to sports talents. The conclusion of this study can provide guidance for the reform of the physical education curriculum, the growth of sports talents, and the development of sports talents in China.
... Exploration of the GWAS summary statistics in the total and male population with the SNP2GENE and GENE2FUNC implemented in the FUMA platform revealed a genomic risk locus on chromosome 4 with a cluster of candidate SNPs located in PPP3CA, a gene previously found to be associated with endurance capacity in humans (31). This gene encodes CnAα, the Copyright © 2022 by the American College of Sports Medicine. ...
Article
Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Central Norway Regional Health Authority Norwegian Health Association Introduction Cardiovascular disease (CVD) is the leading cause of death worldwide. Several studies have shown that low cardiorespiratory fitness (CRF) is a major risk factor for CVD and is suggested to be a stronger predictor of CVD morbidity and mortality than established cardiovascular risk factors. CRF quantified as maximal oxygen uptake (VO2max) has a strong genetic component, estimated to be ~50%. Unfortunately, current studies on genetic markers for CRF are limited by small sample sizes. In addition, there are few studies on directly measured VO2max, as most of the previous studies are based on estimated CRF. To overcome these limitations, we performed a large-scale systematic screening for genetic variants associated with VO2max aiming to provide awaited insight to this complex trait and discover possible links between VO2max and CVD. Purpose To identify and validate genetic factors associated with VO2max. Methods The genotypes of 70,000 participants from the Trøndelag Health study (HUNT) were imputed providing information on 25 million single-nucleotide polymorphisms (SNPs). We conducted a genome-wide association study (GWAS) including 4,525 participants with directly measured VO2max from the HUNT3 Fitness study. The GWAS was performed using BOLT-LMM, adjusted for age, gender, physical activity, principal components, and genotyping batch. In addition, we ran a GWAS with the same covariates except physical activity. Further, gender specific analyses were conducted. For validation, similar analyses were performed in the United Kingdom Biobank (UKBB). In the UKBB, CRF was assessed through a submaximal bicycle test. The analyses of UKBB included ~60,000 participants and over 90 million SNPs. Functional analyses of the GWAS results were examined by functional mapping and annotation (FUMA). Results Two GWAS-significant (p < 5×10-8) SNPs associated with VO2max were identified in the total population, two in the male population, and 24 in the female population in HUNT. Two of the 24 SNPs found in the female population were nominally significant in the UKBB. One of the validated SNPs in the female population is located inside PIK3R5, that is shown to be of importance in cardiac function and CVD. In addition, the functional analyses in the total- and male population revealed candidate SNPs in a gene previously found to be associated with endurance, PPP3CA. Conclusions We have identified 28 novel SNPs associated with VO2max in the HUNT cohort. Two of these SNPs were nominally validated in females in UKBB. One of the validated SNPs resides within a gene previously reported to be related to heart function and CVD. In addition, the functional analyses in the total- and male population revealed candidate SNPs in a gene previously found to be associated with endurance. Further functional analyses using bioinformatic approaches may provide more information on the physiological importance of these findings and their relation to CVD.
... The correlation between genetics and sport susceptibility may provide information to improve athletic performance, including injury risk reduction [8]. Genetic component may explain approximately 66% of the variance in athlete status depending on sport discipline [9]. In fact, genotype-phenotype correlation could provide decisive information to guide the athlete toward better sports performance [10]. ...
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Several genes are involved in sport performance, especially in injuries incidence. The aim of this study was to investigate the association of ACE, ACTN3, COL1A1, and MCT1 genotypes and injuries in rugby players in order to find a genotype/phenotype correlation and provide useful information improving athletic performance. One-hundred male professional and semiprofessional rugby players were selected. Analysis was performed genotyping the genes ACE, ACTN3, COL1A1, and MCT1 as candidate gene of interest involved in athletic performance. A control group of nonathletic Italian male participants was analyzed to compare the results. We found statistical significance of MCT1 rs1049434 AA for total injuries (X2 = 0.115; p = 0.003) and bone injuries (X2 = 0.603; p = 0.007) in the rugby athlete population. No statistical significance was found between injury incidence and ACE, ACTN3, COL1A1 genotypes. The MCT1 AA genotype is associated with the incidence of total and bone injuries in the rugby player population. Although environmental factors such as lifestyle, diet, training, and stress can influence athletic performance, our data demonstrated the importance of genetic study in sport aimed at developing personalized training and achieving the best possible athletic excellence.
... Exploration of the GWAS summary statistics in the total and male population with the SNP2GENE and GENE2FUNC implemented in the FUMA platform revealed a genomic risk locus on chromosome 4 with a cluster of candidate SNPs located in PPP3CA, a gene previously found to be associated with endurance capacity in humans (31). This gene encodes CnAα, the Copyright © 2022 by the American College of Sports Medicine. ...
Article
Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Central Norway Regional Health AuthorityNorwegian Health Association Introduction Cardiovascular disease (CVD) is the leading cause of death worldwide. Several studies have shown that low cardiorespiratory fitness (CRF) is a major risk factor for CVD. Low CRF is suggested to be a stronger predictor of CVD morbidity and mortality than established cardiovascular risk factors like obesity, diabetes, and cholesterol. Several studies suggest that CRF quantified as maximal oxygen uptake (VO2max) has a strong genetic component, estimated to be ~50%. Unfortunately, current studies on genetic markers for CRF are limited by small sample sizes. In addition, there are few studies on directly measured VO2max, as most of the previous studies are based on estimated CRF. Directly measured VO2max is considered as the gold standard for measuring CRF. Thus, a large-scale systematic screening for genetic variants associated with VO2max may provide awaited insight to this complex trait and discover possible links between VO2max and CVD. Purpose To identify and validate genetic factors associated with VO2max. Methods The genotypes of 70.000 participants from the Trøndelag Health study (HUNT) were imputed providing information on 25 million SNPs. We conducted a genome-wide association study (GWAS) including 4525 participants with directly measured VO2max from the HUNT3 Fitness study. The GWAS was performed using BOLT-LMM, adjusted for age, gender, physical activity, principal components, and genotyping batch. In addition, we ran a GWAS with the same covariates except physical activity. Further, gender specific analyses were conducted. For validation, similar analyses were performed in the United Kingdom Biobank (UKBB). In the UKBB, CRF was assessed through a submaximal bicycle test. The analyses of UKBB included ~60.000 participants and over 90 million SNPs. Results Two GWAS-significant (p < 5x10-8) SNPs associated with VO2max were identified in the total population in HUNT. Further, 24 GWAS-significant SNPs associated with VO2max in females, and two GWAS-significant SNPs associated with VO2max in males were discovered. Two of the 24 SNPs found in the female population were nominally significant in the UKBB. The validated SNPs are rs376927175, an intergenic SNP downstream of APBA1, and rs551942830 (proxy for rs190675254 with LD = 1.0), a 3 Prime UTR variant inside PIK3R5. PIK3R5 encodes the regulatory subunit of one class of PI3Ks, that is shown to be of importance in cardiac function and CVD. None of the SNPs found in the total population nor the male population were validated in UKBB. Conclusions We have identified 28 novel SNPs associated with VO2max in the HUNT cohort. Two of these SNPs were nominally validated in females in UKBB. One of the validated SNPs resides within a gene previously reported to be related to heart function and CVD. Further functional analyses using bioinformatic approaches may provide more information on the physiological importance of these findings and their relation to CVD.
Article
Molecular genetic methods are an integral part of recent medicine. Polymerase chain reaction, Sanger sequencing, next-generation sequencing are widely used in many areas: diagnostics of infectious, inherited, oncological diseases, prenatal screening, study of polymorphisms that increase the risk of developing multifactorial diseases or promoting development physical qualities necessary to achieve success in sports and competitive activity. The growing demand for genotyping raises a number of ethical and social issues affecting the degree of usefulness of genotyping a healthy person and the scientific reliability of the data obtained using direct-to-consumer genetic testing. The review presents and systematizes the laboratory diagnostic methods used today to study nucleic acids that carry important information about human health and physical qualities.
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The general consensus among sport and exercise genetics researchers is that genetic tests have no role to play in talent identification or the individualised prescription of training to maximise performance. Despite the lack of evidence, recent years have witnessed the rise of an emerging market of direct-to-consumer marketing (DTC) tests that claim to be able to identify children's athletic talents. Targeted consumers include mainly coaches and parents. There is concern among the scientific community that the current level of knowledge is being misrepresented for commercial purposes. There remains a lack of universally accepted guidelines and legislation for DTC testing in relation to all forms of genetic testing and not just for talent identification. There is concern over the lack of clarity of information over which specific genes or variants are being tested and the almost universal lack of appropriate genetic counselling for the interpretation of the genetic data to consumers. Furthermore independent studies have identified issues relating to quality control by DTC laboratories with different results being reported from samples from the same individual. Consequently, in the current state of knowledge, no child or young athlete should be exposed to DTC genetic testing to define or alter training or for talent identification aimed at selecting gifted children or adolescents. Large scale collaborative projects, may help to develop a stronger scientific foundation on these issues in the future.
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Understanding the genetic architecture of athletic performance is an important step in the development of methods for talent identification in sport. Research concerned with molecular predictors has highlighted a number of potentially important DNA polymorphisms contributing to predisposition to success in certain types of sport. This review summarizes the evidence and mechanistic insights on the associations between DNA polymorphisms and athletic performance. A literature search (period: 1997-2014) revealed that at least 120 genetic markers are linked to elite athlete status (77 endurance-related genetic markers and 43 power/strength-related genetic markers). Notably, 11 (9%) of these genetic markers (endurance markers: ACE I, ACTN3 577X, PPARA rs4253778 G, PPARGC1A Gly482; power/strength markers: ACE D, ACTN3 Arg577, AMPD1 Gln12, HIF1A 582Ser, MTHFR rs1801131 C, NOS3 rs2070744 T, PPARG 12Ala) have shown positive associations with athlete status in three or more studies and six markers (CREM rs1531550 A, DMD rs939787 T, GALNT13 rs10196189 G, NFIA-AS1 rs1572312 C, RBFOX1 rs7191721 G, TSHR rs7144481 C) were identified after performing genome-wide association studies (GWAS) of African-American, Jamaican, Japanese and Russian athletes. On the other hand, the significance of 29 (24%) markers was not replicated in at least one study. Future research including multicenter GWAS, whole-genome sequencing, epigenetic, transcriptomic, proteomic and metabolomic profiling and performing meta-analyses in large cohorts of athletes is needed before these findings can be extended to practice in sport.
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The objective of this study was to evaluate the genetic and environmental contribution to variation in aerobic power in monozygotic (MZ) and dizygotic (DZ) twins. The sample consisted of 20 MZ individuals (12 females and 8 males) and 16 DZ individuals (12 females and 4 males), aged from 8 to 26 years, residents in Natal, Rio Grande do Norte. The twins were assessed by a multistage fitness test. The rate of heritability found for aerobic power was 77%. Based on the results, the estimated heritability was largely responsible for the differences in aerobic power. This implies that such measures are under strong genetic influence.
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To investigate the association between multiple single-nucleotide polymorphisms (SNPs), aerobic performance and elite endurance athlete status in Russians. By using GWAS approach, we examined the association between 1,140,419 SNPs and relative maximal oxygen consumption rate (VO2max) in 80 international-level Russian endurance athletes (46 males and 34 females). To validate obtained results, we further performed case-control studies by comparing the frequencies of the most significant SNPs (with P<10(-5)-10(-8)) between 218 endurance athletes and opposite cohorts (192 Russian controls, 1367 European controls, and 230 Russian power athletes). Initially, six ‘endurance alleles’ were identified showing discrete associations with VO2max both in males and females. Next, case-control studies resulted in remaining three SNPs (NFIA-AS2 rs1572312, TSHR rs7144481, RBFOX1 rs7191721) associated with endurance athlete status. The C allele of the most significant SNP, rs1572312, was associated with high values of VO2max (males: P=0.0051; females: P=0.0005). Furthermore, the frequency of the rs1572312 C allele was significantly higher in elite endurance athletes (95.5%) in comparison with non-elite endurance athletes (89.8%, P=0.0257), Russian (88.8%, P=0.007) and European (90.6%, P=0.0197) controls and power athletes (86.2%, P=0.0005). The rs1572312 SNP is located on the nuclear factor I A antisense RNA 2 (NFIA-AS2) gene which is supposed to regulate the expression of the NFIA gene (encodes transcription factor involved in activation of erythropoiesis and repression of the granulopoiesis). Our data show that the NFIA-AS2 rs1572312, TSHR rs7144481 and RBFOX1 rs7191721 polymorphisms are associated with aerobic performance and elite endurance athlete status.
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Exercise-induced oxidative stress is a state that primarily occurs in athletes involved in high-intensity sports when pro-oxidants overwhelm the antioxidant defense system to oxidize proteins, lipids, and nucleic acids. During exercise, oxidative stress is linked to muscle metabolism and muscle damage, because exercise increases free radical production. The T allele of the Ala16Val (rs4880 C/T) polymorphism in the mitochondrial superoxide dismutase 2 (SOD2) gene has been reported to reduce SOD2 efficiency against oxidative stress. In the present study we tested the hypothesis that the SOD2 TT genotype would be underrepresented in elite athletes involved in high-intensity sports and associated with increased values of muscle and liver damage biomarkers. The study involved 2664 Caucasian (2262 Russian and 402 Polish) athletes. SOD2 genotype and allele frequencies were compared to 917 controls. Muscle and liver damage markers [creatine kinase (CK), creatinine, alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP)] were examined in serum from 1444 Russian athletes. The frequency of the SOD2 TT genotype (18.6%) was significantly lower in power/strength athletes (n = 524) compared to controls (25.0%, p = 0.0076) or athletes involved in low-intensity sports (n = 180; 33.9%, p < 0.0001). Furthermore, the SOD2 T allele was significantly associated with increased activity of CK (females: p = 0.0144) and creatinine level (females: p = 0.0276; males: p = 0.0135) in athletes. Our data show that the SOD2 TT genotype might be unfavorable for high-intensity athletic events.
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What is the central question of this study? Variations in genes are considered to be molecular determinants maintaining the expression of the slow or fast myosin heavy chains of adult skeletal muscle. The role of polymorphisms of candidate genes involved in skeletal muscle development, energy homeostasis and thyroid and calcium metabolism in the determination of muscle fibre type has not previously been reported.What is the main finding and its importance? We show that the AGTR2 rs11091046 C allele is associated with an increased proportion of slow-twitch muscle fibres, endurance athlete status and aerobic performance. Such findings have important implications for our understanding of muscle function in both health and disease.
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Abstract Research concerned with predictors of talent in football has highlighted a number of potentially important and partially inherited measures such as body size, anaerobic power, aerobic capacity, agility, psychological profile, game intelligence and susceptibility to injuries. Genotyping for performance-associated DNA polymorphisms at an early age could be useful in predicting later success in football. The aim of the study was to investigate individually and in combination the association of common gene polymorphisms with football player's status. A total of 246 Russian football players and 872 controls were genotyped for 8 gene polymorphisms, which were previously reported to be associated with athlete status. Four alleles (ACE D, ACTN3 Arg577, PPARA rs4253778 C and UCP2 55Val) were first identified, showing discrete associations with football player's status. Next, we determined the total genotype score (TGS, from the accumulated combination of the 4 polymorphisms, with a maximum value of 100 for the theoretically optimal polygenic score) in athletes and controls. The mean TGS was significantly higher in football players (52.0 (17.6) vs. 41.3 (15.5); P < 0.0001) than in controls. These data suggest that the likelihood of becoming a football player depends on the carriage of a high number of "favourable" gene variants.
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Athletic performance is a polygenic trait influenced by both environmental and genetic factors. To investigate individually and in combination the association of common gene polymorphisms with athlete status in Ukrainians. A total of 210 elite Ukrainian athletes (100 endurance-oriented and 110 power-orientated athletes) and 326 controls were genotyped for ACE I/D, HIF1A Pro582Ser, NOS3 -786 T/C, PPARA intron 7 G/C, PPARG Pro12Ala and PPARGC1B Ala203Pro gene polymorphisms, most of which were previously reported to be associated with athlete status or related intermediate phenotypes in different populations. Power-oriented athletes exhibited an increased frequency of the HIF1A Ser (16.1 vs. 9.4%, P = 0.034) and NOS3 T alleles (78.3 vs. 66.2%, P = 0.0019) in comparison with controls. Additionally, we found that the frequency of the PPARG Ala allele was significantly higher in power-oriented athletes compared with the endurance-oriented athletes (24.7 vs. 13.5%; P = 0.0076). Next, we determined the total genotype score (TGS, from the accumulated combination of the three polymorphisms, with a maximum value of 100 for the theoretically optimal polygenic score) in athletes and controls. The mean TGS was significantly higher in power-oriented athletes (39.1 ± 2.3 vs. 32.6 ± 1.5; P = 0.0142) than in controls. We found that the HIF1A Ser, NOS3 T and PPARG Ala alleles were associated with power athlete status in Ukrainians.
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Genes control biological processes such as muscle production of energy, mitochondria biogenesis, bone formation, erythropoiesis, angiogenesis, vasodilation, neurogenesis, etc. DNA profiling for athletes reveals genetic variations that may be associated with endurance ability, muscle performance and power exercise, tendon susceptibility to injuries and psychological aptitude. Already, over 200 genes relating to physical performance have been identified by several research groups. Athletes' genotyping is developing as a tool for the formulation of personalized training and nutritional programmes to optimize sport training as well as for the prediction of exercise-related injuries. On the other hand, development of molecular technology and gene therapy creates a risk of non-therapeutic use of cells, genes and genetic elements to improve athletic performance. Therefore, the World Anti-Doping Agency decided to include prohibition of gene doping within their World Anti-Doping Code in 2003. In this review article, we will provide a current overview of genes for use in athletes' genotyping and gene doping possibilities, including their development and detection techniques.