Genes and Athletic Performance: An Update

Abstract

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.

Full text

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
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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*
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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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.
Med Sport Sci. Basel, Karger, 2016, vol 61, pp 41–54 (DOI: 10.1159/000445240)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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=
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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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
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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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.
Med Sport Sci. Basel, Karger, 2016, vol 61, pp 41–54 (DOI: 10.1159/000445240)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

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.
References
1 De Moor MHM, Spector TD, Cherkas LF, Falchi M,
Hottenga JJ, Boomsma DI, De Geus EJC: Genome-
wide linkage scan for athlete status in 700 British fe-
male DZ twin pairs. Twin Res Hum Genet 2007;
10:
812–820.
2 Simoneau J-A, Bouchard C: Genetic determinism of
fiber type proportion in human skeletal muscle.
FASEB J 1995;
9: 1091–1095.
3 Alonso L, Souza E, Oliveira M, do Nascimento L,
Dantas P: Heritability of aerobic power of individu-
als in northeast Brazil. Biol Sport 2014;
31: 267–270.
4 Ahmetov II, Fedotovskaya ON: Current progress in
sports genomics. Adv Clin Chem 2015;
70: 247–314.
5 Eynon N, Nasibulina ES, Banting LK, Cieszczyk P,
Maciejewska-Karlowska A, Sawczuk M, Bondareva
EA, Shagimardanova RR, Raz M, Sharon Y, Williams
AG, Ahmetov II, Lucia A, Birk R: The FTO A/T poly-
morphism and elite athletic performance: a study in-
volving three groups of European athletes. PLoS One
2013;
8:e60570.
6 Wang G, Mikami E, Chiu LL, de Perini A, Deason M,
Fuku N, Miyachi M, Kaneoka K, Murakami H, Tana-
ka M, Hsieh LL, Hsieh SS, Caporossi D, Pigozzi F,
Hilley A, Lee R, Galloway SD, Gulbin J, Rogozkin
VA, Ahmetov II, Yang N, North KN, Ploutarhos S,
Montgomery HE, Bailey ME, Pitsiladis YP: Associa-
tion analysis of ACE and ACTN3 in elite Caucasian
and East Asian swimmers. Med Sci Sports Exerc
2013;
45: 892–900.
7 Ahmetov II, Kulemin NA, Popov DV, Naumov VA,
Akimov EB, Bravy YR, Egorova ES, Galeeva AA,
Generozov EV, Kostryukova ES, Larin AK, Musta-
fina LJ, Ospanova EA, Pavlenko AV, Starnes LM,
Żmijewski P, Alexeev DG, Vinogradova OL, Govo-
run VM: Genome-wide association study identifies
three novel genetic markers associated with elite en-
durance performance. Biol Sport 2015;
32: 3–9.
8 O’Connell K, Posthumus M, Collins M: COL6A1
gene and Ironman triathlon performance. Int J
Sports Med 2011;
32: 896–901.
9 Brown JC, Miller CJ, Posthumus M, Schwellnus MP,
Collins M: The COL5A1 gene, ultra-marathon run-
ning performance, and range of motion. Int J Sports
Physiol Perform 2011;
6: 485–496.
10 Drozdovska SB, Dosenko VE, Ahmetov II, Ilyin VN:
The association of gene polymorphisms with athlete
status in Ukrainians. Biol Sport 2013;
30: 163–167.
11 Ahmetov II, Naumov VA, Donnikov AE,
Maciejewska-Karłowska A, Kostryukova ES, Larin
AK, Maykova EV, Alexeev DG, Fedotovskaya ON,
Generozov EV, Jastrzębski Z, Zmijewski P, Kravtso-
va OA, Kulemin NA, Leonska-Duniec A, Mar-
tykanova DS, Ospanova EA, Pavlenko AV,
Podol’skaya AA, Sawczuk M, Alimova FK, Trofimov
DY, Govorun VM, Cieszczyk P: SOD2 gene poly-
morphism and muscle damage markers in elite ath-
letes. Free Radic Res 2014;
48: 948–955.
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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

Genes and Sports 53
12 Ahmetov II, Hakimullina AM, Popov DV, Lyubaeva
EV, Missina SS, Vinogradova OL, Williams AG,
Rogozkin VA: Association of the VEGFR2 gene
His472Gln polymorphism with endurance-related
phenotypes. Eur J Appl Physiol 2009;
107: 95–103.
13 Mustafina LJ, Naumov VA, Cieszczyk P, Popov DV,
Lyubaeva EV, Kostryukova ES, Fedotovskaya ON,
Druzhevskaya AM, Astratenkova IV, Glotov AS,
Alexeev DG, Mustafina MM, Egorova ES,
Maciejewska-Karłowska A, Larin AK, Generozov
EV, Nurullin RE, Jastrzębski Z, Kulemin NA,
Ospanova EA, Pavlenko AV, Sawczuk M, Akimov
EB, Danilushkina AA, Zmijewski P, Vinogradova
OL, Govorun VM, Ahmetov II: AGTR2 gene poly-
morphism is associated with muscle fibre composi-
tion, athletic status and aerobic performance. Exp
Physiol 2014;
99: 1042–1052.
14 Wang G, Padmanabhan S, Wolfarth B, Fuku N, Lu-
cia A, Ahmetov II, Cieszczyk P, Collins M, Eynon N,
Klissouras V, Williams A, Pitsiladis Y: Genomics of
elite sporting performance: what little we know and
necessary advances. Adv Genet 2013;
84: 123–149.
15 Ahmetov II, Donnikov AE, Trofimov DY: ACTN3
genotype is associated with testosterone levels of ath-
letes. Biol Sport 2014;
31: 105–108.
16 Williams AG, Dhamrait SS, Wootton PT, Day SH,
Hawe E, Payne JR, Myerson SG, World M, Budgett
R, Humphries SE, Montgomery HE: Bradykinin re-
ceptor gene variant and human physical perfor-
mance. J Appl Physiol 2004;
96: 938–942.
17 Saunders CJ, Xenophontos SL, Cariolou MA, Anas-
tassiades LC, Noakes TD, Collins M: The bradykinin
b2 receptor ( BDKRB2 ) and endothelial nitric oxide
synthase 3 ( NOS3 ) genes and endurance perfor-
mance during Ironman triathlons. Hum Mol Genet
2006;
15: 979–987.
18 Akhmetov II, Popov DV, Mozhayskaya IA, Missina
SS, Astratenkova IV, Vinogradova OL, Rogozkin
VA: Association of regulatory genes polymorphisms
with aerobic and anaerobic performance of athletes.
Ross Fiziol Zh Im I M Sechenova 2007;
93: 837–843.
19 Ahmetov II, Popov DV, Astratenkova IV, Druzhevs-
kaia AM, Missina SS, Vinogradova OL, Rogozkin
VA: The use of molecular genetic methods for prog-
nosis of aerobic and anaerobic performance in ath-
letes. Hum Physiol 2008;
34: 338–342.
20 Williams AG, Folland JP: Similarity of polygenic
profiles limits the potential for elite human physical
performance. J Physiol 2008;
586: 113–121.
21 Eynon N, Meckel Y, Alves AJ, Yamin C, Sagiv M,
Goldhammer E, Sagiv M: Is there an interaction be-
tween PPARD T294C and PPARGC1A Gly482Ser
polymorphisms and human endurance perfor-
mance? Exp Physiol 2009;
94: 1147–1152.
22 Gómez-Gallego F, Santiago C, González-Freire M,
Muniesa CA, Fernández del Valle M, Pérez M, Foster
C, Lucia A: Endurance performance: genes or gene
combinations? Int J Sports Med 2009;
30: 66–72.
23 Ruiz JR, Gómez-Gallego F, Santiago C, González-
Freire M, Verde Z, Foster C, Lucia A: Is there an op-
timum endurance polygenic profile? J Physiol 2009;
587: 1527–1534.
24 Ruiz JR, Arteta D, Buxens A, Artieda M, Gómez-Gal-
lego F, Santiago C, Yvert T, Morán M, Lucia A: Can
we identify a power-oriented polygenic profile? J
Appl Physiol 2010;
108: 561–566.
25 Muniesa CA, González-Freire M, Santiago C, Lao JI,
Buxens A, Rubio JC, Martín MA, Arenas J, Gomez-
Gallego F, Lucia A: World-class performance in
lightweight rowing: is it genetically influenced? A
comparison with cyclists, runners and non-athletes.
Br J Sports Med 2010;
44: 898–901.
26 Santiago C, Ruiz JR, Muniesa CA, González-Freire
M, Gómez-Gallego F, Lucia A: Does the polygenic
profile determine the potential for becoming a
world-class athlete? Insights from the sport of row-
ing. Scand J Med Sci Sports 2010;
20: 188–194.
27 Buxens A, Ruiz JR, Arteta D, Artieda M, Santiago C,
González-Freire M, Martínez A, Tejedor D, Lao JI,
Gómez-Gallego F, Lucia A: Can we predict top-level
sports performance in power vs endurance events? A
genetic approach. Scand J Med Sci Sports 2011;
21:
570–579.
28 Eynon N, Ruiz JR, Meckel Y, Morán M, Lucia A: Mi-
tochondrial biogenesis related endurance genotype
score and sports performance in athletes. Mitochon-
drion 2011;
11: 64–69.
29 Hughes DC, Day SH, Ahmetov II, Williams AG: Ge-
netics of muscle strength and power: polygenic pro-
file similarity limits skeletal muscle performance. J
Sports Sci 2011;
29: 1425–1434.
30 Ahmetov II, Gavrilov DN, Astratenkova IV, Dru-
zhevskaya AM, Malinin AV, Romanova EE, Rogoz-
kin VA: The association of ACE , ACTN3 and PPARA
gene variants with strength phenotypes in middle
school-age children. J Physiol Sci 2013;
63: 79–85.
31 Ben-Zaken S, Meckel Y, Lidor R, Nemet D, Eliakim
A: Genetic profiles and prediction of the success of
young athletes’ transition from middle- to long-dis-
tance runs: an exploratory study. Pediatr Exerc Sci
2013;
25: 435–447.
32 Egorova ES, Borisova AV, Mustafina LJ, Arkhipova
AA, Gabbasov RT, Druzhevskaya AM, Astratenkova
IV, Ahmetov II: The polygenic profile of Russian
football players. J Sports Sci 2014;
32: 1286–1293.
33 Gineviciene V, Jakaitiene A, Tubelis L, Kucinskas V:
Variation in the ACE , PPARGC1A and PPARA genes
in Lithuanian football players. Eur J Sport Sci 2014;
14: 289–295.
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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM

54 Ahmetov · Egorova · Gabdrakhmanova · Fedotovskaya
Dr. Ildus I. Ahmetov
Sport Technology Research Center
Volga Region State Academy of Physical Culture, Sport and Tourism
35, Universiade Village, 420138 Kazan (Russia)
E-Mail genoterra@mail.ru
34 Ben-Zaken S, Meckel Y, Nemet D, Eliakim A. Ge-
netic score of power-speed and endurance track and
field athletes. Scand J Med Sci Sports 2015; 25: 166–
174.
35 Kuroyanagi H: Fox-1 family of RNA-binding pro-
teins. Cell Mol Life Sci 2009;
66: 3895–3907.
36 Simonides WS, van Hardeveld C: Thyroid hormone
as a determinant of metabolic and contractile pheno-
type of skeletal muscle. Thyroid 2008;
18: 205–216.
37 Balzan S, Del Carratore R, Nicolini G, Beffy P, Lu-
brano V, Forini F, Iervasi G: Proangiogenic effect of
TSH in human microvascular endothelial cells
through its membrane receptor. J Clin Endocrinol
Metab 2012;
97: 1763–1770.
38 Ahmetov II, Ischenko DS, Kulemin NA, Popov DV,
Galeeva AA, Kostryukova ES, Alexeev DG, Egorova
ES, Gabdrakhmanova LJ, Larin AK, Generozov EV,
Ospanova EA, Pavlenko AV, Akimov EB, Vinogrado-
va OL, Govorun VM: Genome-wide association study
reveals seven genetic markers associated with maxi-
mal oxygen consumption rate in elite Russian endur-
ance athletes. Eur J Hum Genet 2015;
23(suppl 1):470.
39 Galeeva AA, Ischenko DS, Kulemin NA, Popov DV,
Kostryukova ES, Alexeev DG, Egorova ES, Gabdra-
khmanova LJ, Larin AK, Generozov EV, Ospanova
EA, Pavlenko AV, Akimov EB, Vinogradova OL,
Govorun VM, Ahmetov II: A multi-stage genome-
wide association study of elite endurance athlete sta-
tus. Eur J Hum Genet 2015;
23(suppl 1):472.
40 Gabdrakhmanova LJ, Ischenko DS, Kulemin NA,
Popov DV, Galeeva AA, Kostryukova ES, Alexeev
DG, Egorova ES, Larin AK, Generozov EV, Ospano-
va EA, Pavlenko AV, Akimov EB, Vinogradova OL,
Govorun VM, Ahmetov II: The difference in genom-
ic profiles between endurance and power athletes.
Eur J Hum Genet 2015;
23(suppl 1):471.
41 Wang G, Padmanabhan S, Miyamoto-Mikami E,
Fuku N, Tanaka M, Miyachi M, Murakami H, Cheng
YC, Mitchell BD, Austin KG, Pitsiladis YP: GWAS of
elite Jamaican, African American and Japanese
sprint athletes. Med Sci Sports Exerc 2014;
46(suppl):
596–598.
42 De Cesare D, Fimia GM, Sassone-Corsi P: CREM, a
master-switch of the transcriptional cascade in male
germ cells. J Endocrinol Invest 2000;
23: 592–596.
43 Zhang Y, Iwasaki H, Wang H, Kudo T, Kalka TB,
Hennet T, Kubota T, Cheng L, Inaba N, Gotoh M,
Togayachi A, Guo J, Hisatomi H, Nakajima K, Nishi-
hara S, Nakamura M, Marth JD, Narimatsu H: Char-
acterization of a new human UDP-N-acetyl-α-
D -
galactosamine:polypeptide-N-acetyl
galactosaminyl-transferase, designated pp-GalNac-
T13, that is specifically expressed in neurons and
synthesizes GalNac α-serine/threonine antigen. J
Biol Chem 2003;
278: 573–584.
44 Egorova ES, Ischenko DS, Kulemin NA, Galeeva AA,
Kostryukova ES, Alexeev DG, Gabdrakhmanova LJ,
Larin AK, Generozov EV, Ospanova EA, Pavlenko
AV, Govorun VM, Ahmetov II: Genome-wide asso-
ciation study of elite strength athlete status in Rus-
sians. Eur J Hum Genet 2015;
23(suppl 1):468–469.
45 Ischenko DS, Galeeva AA, Kulemin NA, Kostryuko-
va ES, Alexeev DG, Egorova ES, Gabdrakhmanova
LJ, Larin AK, Generozov EV, Ospanova EA, Pavlen-
ko AV, Govorun VM, Ahmetov II: Genome-wide as-
sociation study of elite power athlete status. Eur J
Hum Genet 2015;
23(suppl 1):472.
46 Naumov VA, Ahmetov II, Larin AK, Generozov EV,
Kulemin NA, Ospanova EA, Pavlenko AV, Kostryu-
kova ES, Alexeev DG, Govorun VM: Genome-wide
association analysis identifies a locus on DMD (dys-
trophin) gene for power athlete status in Russians.
Eur J Hum Genet 2014;
22(suppl 1):502.
47 Pokrywka A, Kaliszewski P, Majorczyk E, Zembroń-
Łacny A: Genes in sport and doping. Biol Sport 2013;
30: 155–161.
48 Webborn N, Williams A, McNamee M, Bouchard C,
Pitsiladis Y, Ahmetov I, Ashley E, Byrne N, Campo-
resi S, Collins M, Dijkstra P, Eynon N, Fuku N, Gar-
ton FC, Hoppe N, Holm S, Kaye J, Klissouras V, Lu-
cia A, Maase K, Moran C, North KN, Pigozzi F,
Wang G: Direct-to-consumer genetic testing for pre-
dicting sports performance and talent identification.
Br J Sports Med 2015;
49: 1486–1491.
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)
Downloaded by:
Univ. of California Santa Barbara
128.111.121.42 - 6/12/2016 10:07:06 PM