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  5. Mavlyanov I.R., Ashirmetov A.Кh., Yulchiev S.Т., Rakhimova N.M. Does the preferred distance of elite stayers depend on genetic polymorphism?

Mavlyanov I.R., Ashirmetov A.Кh., Yulchiev S.Т., Rakhimova N.M. Does the preferred distance of elite stayers depend on genetic polymorphism?

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Publication date: 01.07.2022
DOI: 10.51871/2782-6570_2022_01_02_7                               
UDC 575.174.015.3; 796.422.1

DOES THE PREFERRED DISTANCE OF ELITE STAYERS DEPEND ON GENETIC POLYMORPHISM?

I.R. Mavlyanov, A.Кh. Ashirmetov, S.Т. Yulchiev, N.M. Rakhimova

Republican Scientific and Practical Center of Sports Medicine, Tashkent, Uzbekistan

Annotation. The study was performed to assess the dependence of the distance preference of elite stayers on the combination of genetic markers associated with endurance, power or strength. Shares of the corresponding alleles and the “Total Genotype Score” of following genes were analyzed: ACE I/D, ACTN3 C/T, AMPD1 S/T, PPARA G/C, PPARG2 C/G, MTHFR A/C, HIF1A C/T, ADRB2 C>G, ADRB2 G>A, NOS3 C/T in the athletes preferring short (0.8 and 1.5 km), average (1.5-21.1 km) and long (21.1 and 41.1 km) distances, and the individuals, not engaged in sports. It was revealed that the proportions of the corresponding alleles and the mean Total Genotype Score values of the studied genes were higher in power and strength, but lower in endurance in stayers, who prefer short distances, compared to marathon runners and the control group, while in the last two groups they did not differ.

Keywords: sports genetics, genetic polymorphism, endurance, power, strength, running distance, elite athletes, marathon.

Introduction. Lately, the genetic aspect of achievements of elite athletes becomes more relevant for understanding, whether the athlete is able to perform under various conditions in addition to their potential trainability. However, the “one gene as the magic bullet” concept, which was earlier gaining its popularity in sports, was not proven, since such gene was never discovered [1-2]. We have found instead that elite athletes have a number of favorable alleles, but none of them has the ideal genetic profile [1, 3]. 

At the present moment, it is known that genetic coding of athletic activity and its determinants are polygenic. The genetic basis usually includes a complex phenotype architecture, caused by a different number of genetic variants that affect a certain attribute, their allele frequency, dimensions of their effect and multiple gene-gene and gene-environment interactions [4-6].

It was found that the so-called “genetic profile” for success in sports can be phenotypically subdivided into a number of opposite types (e.g. endurance, power, strength, speed, coordination etc.). Thus, according to the research of the I.I. Akhmedov’s team [7], a total number of DNA polymorphisms, related to the athletic status, was 220 in 2021, only 97 markers of which appeared to be significant at least in two studies (related to endurance – 35, power – 24 and strength – 38).

Normally, the genetic markers, related to endurance, power or strength, are identified through the comparison of allele frequencies in groups of athletes, engaged in corresponding sports, e.g. marathon runners, sprinters or weightlifters, regarding the non-athletic control [1, 2, 4, 5]. In terms of running in track-and-field, the athletes are specialized by choosing appropriate distances.   

However, during competitions, taking into account their capabilities, they can perform in other distances. For this purpose, they prepare with different training modes, since the duration and intensity of training sessions must depend on the cleared distance. For example, if the marathon distance is cleared for not less than 2.5 hours continuously, focusing mainly on saving energy and endurance, then for short-distance run, the attention should be given to developing high speed, for average-distance run, besides speed – power and endurance
[8-9]. Speaking otherwise, the training mode must be constructed, according to the need in the appropriate energy supply and oxygen consumption [10-11]. At the same time, these processes, often possessing opposite characteristics, must occur simultaneously in various ratios in the stayer’s body when running certain distances. Nonetheless, the appropriate genetic profile of the athlete that creates a basis for successful (in terms of sports) distance clearing has not been identified.

Considering this fact, we have conducted this study to evaluate connection between the distance, preferred by elite stayers, with the combination of genetic markers, related to endurance, power and strength.

Methods and organization. The study involved 22 elite Uzbekistan athletes, engaged in track-and-field (running in particular), as well as 125 individuals, not engaged in sports. The test subjects were not divided by gender or nationality.

According to the indicators of athletic achievements at major international competitions in 2017-2020, we have divided the elite track-and-field athletes, regardless their gender, into 3 groups, depending on the distance preference, so the basis was the only the minimality of the time required to clear the appropriate distance.

Since there are no athletes in Uzbekistan, who won at international competitions on sprinter distances (100 m or 200 m), we carried out the study, involving only stayers, divided into 3 groups. Those were the winners at competitions, who cleared following distances in the shortest time:

1) short distances (800 and 1500 m);

2) short (1500 m) and average (5 and 190 km) distances, even a semi marathon (21.1 km);

3) marathon distances (21.1 and 42.1 km).

Indicators of time and average speed of clearing distance at international competitions, presented in table 1, allow to get a view on the level of test subjects.

Table 1

Time and average speed of clearing distances at international competitions by elite track-and-field athletes

Distance

Men

Women

Clearance time

Average speed

Clearance time

Average speed

800 m

<115 s

>6.9 m/s

<135 s

>5.9 m/s

1500 m

<4 min

>6.2 m/s

<4,5 min

>5.55 m/s

5000 m

<16 min

>5.2 m/s

<17 min

>4.9 m/s

10000 m

<32 min

>5.2 m/s

<35 min

>4.76 m/s

Semi marathon

<70 min

>5.0 m/s

<75 min

>4.69 m/s

Marathon

<148 min

>4.74 m/s

<155 min

>4.53 m/s

The genotyping was conducted with the polymerase chain reaction (PCR) amplification. Samples of venous blood were collected in the ethylenediaminetetraacetic acid (EDTA) solution and stored at the temperature of
-20̊С before the analysis. The DNA isolation was made with the Ribo-prep reagent set (Interlabservis, Russia).

We detected polymorphism of studied genes with the Real-Time PCR method (OOO NPF “Litekh”, Russia). In order to conduct the PCR amplification in real time, we used the GeneAmp® PCR – ABI 7500 Fast Real-Time with the 96-cell block. The real-time amplification program included 100 s of preliminary denaturation at 95 °С once, at 95 °С for 15 s and at 64°С for 40 s (included 45 repeats).

We examined genetic polymorphisms, for which connection with features of endurance, power and strength was earlier demonstrated in publications and which were recommended according to the meta-analysis results [7].

To comprehensively examine genotypes with prevailing endurance or power-strength type, we selected 10 genes (ACE, ACTN3, AMPD1, PPARA, PPARG2, MTHFR, HIF1A, ADRB2 C>G, ADRB2 G>A, NOS3), six of which had polymorphism that demonstrated favorable allele variants for the endurance type (ACE (rs4646994)_I/D_(I), ACTN3_(rs1815739)_C/T_(Т), AMPD1_(rs17602729)_C/Т_(C), PPARA (rs4253778)_G/C_(G), HIF1A (rs11549465)_C/T_(С), ADRB2 (rs1042713) _G>A _(А)).

In order to identify the power type, we defined polymorphisms of 10 genes with the favorable allele: ACE (rs4646994)_I/D_(D), ACTN3 (rs1815739)_C/T_(С), AMPD1_(rs17602729)_C/Т_(C), PPARA (rs4253778)_G/C _(С), PPARG2 (rs1801282)_C/G_(G), MTHFR (rs1801131)_ A/C_(C), HIF1A (rs11549465)_C/T_(Т), ADRB2 (rs1042714)_C>G_(G), ADRB2 (rs1042713)_ G>A_(G), NOS3_C/T_(T). We analyzed 5 genes for identifying the strength type: ACTN3 (rs1815739)_C/T_(С), PPARA (rs4253778)_G/C_(С), PPARG2 (rs1801282)_C/G_(G), MTHFR (rs1801131)_A/C_(C), HIF1A (rs11549465)_ C/T_(Т).

The so-called Total Genotype Score (TGS) (in the range from 0 to 100) was calculated with the Williams and Folland model [12]. When looking for the searched allele that shows the corresponding athletic type, we assessed the homozygote variant as “2”, heterozygote variant – as “1” and absence of the allele – as “0”.

Then, the total genotype score, obtained as a result of accumulated combination of polymorphism candidates that explains individual variations in endurance indicators, was calculated according to the following formula:

ТGS endurance = (100/6х2) х (GS ACE(I) + GS ACTN3(Т) + GS AMPD1(C) + GS PPARA(G) + GS HIF1A(С) + GS ADRB2G>A(А)).

The same was done for power and strength indicators:

ТGS power = (100/10х2) х (GS ACE(D) + GS ACTN3(С) + GS AMPD1(C) + GS MTHFR (C) + GS PPARG2 (G) + GS PPARA(С) + GS HIF1A(Т) + GS ADRB2C>G(G) + GS ADRB2G>A(G) + GS NOS3(Т));

ТG strength = (100/5х2) х (GS ACTN3(С) + GS MTHFR (C) + GS PPARG2 (G) + GS PPARA(С) + GS HIF1A (Т)).

Results and discussion. In this study, we evaluated the connection between the distance, preferred by elite athletes, and variants of 10 genes, early connected with the state of endurance, power or strength of a person.

According to a number of authors, endurance indicators are based on the features of cell metabolism and functioning of the cardiovascular system, closely connected with the prevalence of slow-twitch fibers in skeletal muscles, hemoglobin mass, maximal oxygen consumption speed (VO2max) and cardiac output [13-14]. Moreover, 44-68% of the phenotype variability, connected with endurance, consist of genetic factors [15].

A great share of fast-twitch muscle fibers and muscle mass, accelerated reaction time and a number of anthropometric signs are typical for power indicators [9, 16, 17], with varying heredity from 49 to 86% in different phenotypes [18].

Signs of strength abilities in athletes are mainly based on the high glycolytic ability, hypertrophy of the skeletal system and skeletal muscles with the prevalence of fast-twitch fibers, which is different from features of endurance, but is more similar to power indicators [13, 19]. Meanwhile, genetic factors had value in 30-84% of phenotype variations [18].

We have examined polymorphisms of 10 genes, one of the alleles of which was associated to power (strength) indicators, other alleles of 5 of these genes – to endurance. The studied genes have different targets and ways to influence homeostasis. In particular, the ACE, NOS3 and ADRB2 genes code ferments, participating in the regulation of cardiovascular functions, such as blood pressure and vasodilation [10, 20, 21, 22, 23]. The ACTN3 gene codes structural sarcomeric protein α-actin-3, discovered exclusively in the type II fast-twitch muscle fibers, the function of which correlates with physical strength, speed and power of muscle contraction [1, 4, 11]. The effect of HIF1A stimulates erythropoiesis and increases the efficiency of oxygen delivery to working muscles [21]. The PPARA and PPARG genes code a receptor family (alpha and gamma), activated by the peroxisome proliferation, which contribute to consumption, utilization and catabolism of fatty acids in mitochondria instead of glucose under conditions of energy deficit [22].

For the MTHFR C677T polymorphism, we have found the connection with such efficiency indicators, as the aerobic and anaerobic threshold values [24]. The AMPD plays a key role in production of adenosine triphosphate (ATP) by converting adenosine monophosphate (AMP) into inosine monophosphate. The T allele prevalence, which decreases the AMPD activity in skeletal muscles, is lower among elite athletes for both the endurance and the power type, compared to the control group [20, 23].

The conducted studies led to following results. Figure 1 shows indicators of the gene alleles, relevant to endurance. It is obvious that the control data of some genes differ from info from international sources (more than 10%). In particular, they were higher for PPARA and ACTN3, but lower for AMPD1 (almost by 20%) and ADRB2 A>G.

Fig. 1. Distribution of frequency of gene alleles, associated with the endurance indicator, in elite track-and-field athletes, depending on the preferred distance

Note: international – frequency of gene alleles, associated with the endurance indicator, in the total population (n=2504), according to the data from the 1000 Genomes project [7]

When analyzing the data from track-and-field athletes, depending on the preferred distance, it was revealed that the quantitative level of almost all endurance alleles has a tendency to grow with the increasing distance. Moreover, such pattern for the HIF1A and ADRB2 A>G is seen in a form of a rise from average to long distance, for AMPD1 и ACE – from short to average, for PPARA и ACTN3 – an evenly growth.

It is important to note, that shares of endurance alleles of the HIF1A and ADRB2 A>G genes in athletes, who clear short and average distances perfectly, did not differ from indicators of the control group, while the same situation with the PPARA gene was discovered only in long distances. In other cases, the tendency of similarity with the indicators of the control group was typical for athletes, preferring marathon (ACTN3) or average distances (AMPD1 and ACE).  

As it was shown in figure 2, shares of gene alleles, associated with power, have some differences with the international data in the control group. For example, this indicator was almost 2 times higher for the ADRB2 C>G и PPARG2 genes, for the PPARA – almost 2 times lower. An upward tendency was also found, regarding the ADRB2 A>G and MTHFR genes (differences more than 10%).


Fig. 2. Distribution of frequency of gene alleles, associated with the power and strength indicators, in elite track-and-field athletes, depending on the preferred distance

The typical feature of the changing allele share for athletes appeared to be a decrease in their number in the course of the increasing distance (except PPARG2). It was shown in both an uneven nature (for NOS3 and ACE – change from short to average distances, for ADRB2 A>G, ADRB2 C>G and HIF1A – from average to long distances) and in the form of a gradual decrease (ACTN3, PPARA and MTHFR).

The tendency of similarity with indicators of the control group in the shares of power alleles was identified mostly in athletes, who prefer marathon distances (NOS3, PPARA, PPARG2, ACE и ACTN3). However, it was typical for other genes, regarding both average distances alone (MTHFR and ADRB2 C>G) and in combination with short distances (ADRB2 A>G and HIF1A).

Since the described alleles that show power-related processes, associated to strength in athletes for 5 genes (ACTN3, MTHFR, PPARA, PPARG2 and HIF1A) are related to the manifestation of strength in athletes, the pattern, presented in figure 2, will also describe this parameter. In particular, the tendency of similarity with the indicators of the control group is demonstrated mainly in relation to marathon distances, control values have twofold differences from international ones for the PPARA and PPARG2 genes.

Although the level of endurance alleles of other genes increases in groups of athletes with the increase of cleared distance, they only reach (PPARA) or do not reach (ACE and ACTN3) the control level.

In terms of power alleles, the highest values in the group of short-distance runners with their gradual decrease in the course of increasing distances and, in some degree, exceeding the control level of value in all marathon runners, were found for the NOS3, ACE and ACTN3 genes. In other cases (except AMPD1, dynamics of which are described above), they either did not exceed the control level in any group (ADRB2 A>G, ADRB2 C>G, HIF1A and PPARG2), or they were higher than this level for stayers, competing at short distances. However, in the course of increasing distance, they decreased and turned out to be lower than the control values for marathon runners (MTHFR and PPARA).

It became obvious, that the genetic profile of a marathon runner is characterized by an absolute prevalence of endurance alleles in the HIF1A and AMPD1 genes, as well as the high level of such allele in the ADRB2 A>G gene, which exceed the control levels. The data obtained correspond perfectly with the information from scientific literature, in which a significant connection between the beta-2 adrenergic receptor (ADRB2) rs1042713 and adenosine monophosphate deaminase 1 (AMPD1) rs17602729 and the fastest registered time of completing marathon among male athletes was discovered [23], as well as between the HIF1A activation and high value of VO2max, which is an important factor, determining performance of the marathon run [21].

Among studied genes, according to the opinion of Akhmetov et al. [7], the most prospective genetic markers, regarding endurance, are PPARA rs4253778, strength – PPARG rs1801282, power – ACTN3 rs1815739, AMPD1 rs17602729 and NOS3 rs2070744.

The results of our study have made clear that the term of genetic markers’ perspectivity must be approached differentially. They can differ, depending on the athlete’s specialization and preferred distances. In our opinion, prospective genetic markers of stayers can be following gene alleles that significantly exceed the control level:            

- for marathon runners, endurance-related – HIF1A and AMPD1, power-related – AMPD1, NOS3 and ACTN3;

- for all-round runners (average distances) – AMPD1, power-related – NOS3, ACTN3, PPARA;

- for short-distance runners, power-related – NOS3, ACTN3, PPARA, MTHFR and ACE.

It needs to be noted, that the prospective genetic markers, common to all stayers, are power alleles of the NOS3 and ACTN3 genes, for marathon and all-round runners – the AMPD1 gene additionally.

The results of our studies correspond with the data from literature, where a connection of ACTN3 and ACE with specific sprinter phenotypes was revealed. The ACTN3 rs1815739 variant influences the 200 m run greatly (sprinter speed), while the ACE ID polymorphism more involved in running longer distances – 400 m (sprinter performance) [11]. At the same time, we have revealed that the Olympic standard runners, short (100 m) to ultramarathon distances, have the excess of the

I ACE allele (typical for endurance) [25], while the ACTN3 is the only gene that demonstrated a connection between the genotype and performance in some groups of elite strength-based athletes [4].

Since the genetic support of athletic indicators is complicated, the revealed differences between groups in the allele frequency of each polymorphism point out a need to use new approaches for identifying genetic contribution to athletic improvement. This is the reason why we have calculated the gathered combination of 10 genes’ polymorphisms, related to endurance, power and strength, using the simple model of the Total Genotype Score (TGS). It shows the additive influence of genotypes on predicting complex signs, such as athletic results. Points, given to the genotypes in TGS, must show the degree of the genotype predisposition to a certain sign [23, 26].

Average TGS levels of endurance, power and strength of athletes, depending on the preferred distance, are shown in table 2.

Table 2

Indicators of the Total Genotype Score of endurance, power and strength among elite athletes, depending on the preferred distance

№

Indicators

Control

Preferred distances

Short

Average

Long

1

Endurance (E)

65.9±3.1±

53.3±3.5*

63.4±3.4+

69.4 ± 3.6+

2

Power (P)

42.3±2.0

48.0±2.2*

46.43±2.3

41.7±2.4+

3

Strength (S)

24.7±1.5

34.0±2.3*

27.1±2.0+

23.3±2.4+

4

E/P ratio

1.56±0.11

1.11±0.1*

1.37±0.1+

1.66±0.14+

5

E/S ratio

2.67±0.23

1.57±0.18*

2.34±0.23+

2.98±0.25+

Note: * – difference are statistically significant regarding the control group; (+) – statistically significant differences between groups of athletes, regarding short distances (p<0.05)

It demonstrated an uneven increase of endurance indicators and their gradual decrease, regarding power and strength and depending on the increasing distance. Moreover, control indicators have statistically significant differences only for athletes, preferring short distances, and show a tendency of similarity with indicators of marathon runners, but they are not at the same level.

The analysis of correlation between the endurance TGS and the TGS of power and strength has revealed that only differences in athletes, who prefer short distances, were statistically significant, regarding the control level. The endurance/power TGS ratio increases in stayers with an increase in the preferred distance (p<0.05). The same can be noted for the endurance/strength TGS ratio. In both cases, marathon runners reach the control indicators and slightly exceed them.

As we can see, endurance plays an important role in winning a marathon, since in the course of increasing distance, the expression of the depending allele spectrum increases as well, while the share of alleles, related to power and strength, decreases. It is shown in a gradual decrease of average speed of athletes, while the distance increases, as it was shown in table 1.

It is known that slow-twitch muscle fibers react better to low-intensity training with weights or aerobic training, while high-intensity (strength) training is more suitable for fast-twitch muscle fibers [13-14]. Based on the data obtained, we can identify the recommended markers in beginner athletes, as well as use the revealed genotype spectrum for selection of training, appropriate for a certain person.

The examination of people, not engaged in sports, has demonstrated prevalence of endurance genotypes, regarding the power and strength type, which is possibly connected to the natural selection of such genotypes in order to adapt to the arid climate, where oxygen content of air is lower, than in north latitude with colder and more humid climate [27]. The control genotype is almost similar to the genotype of marathon and all-round runners (who prefer average distances). By the way, the all-round runners make a half of examined elite runners.

Such phenomenon is not surprising, since a similar pattern has been established with respect to multiple Olympic marathon-running champions of Kenyan-Ethiopian origin, where, according to results of international studies, the researchers could not find any distinctive feature in genotypes from the local population that does not engage in sports [28-29]. It follows that any native person of these countries possesses the needed favorable genotype to, under the condition of appropriate training, become an Olympic champion. On the other hand, it can explain an absence of elite sprinters in Uzbekistan, but at the same time show the polygenic nature of complex signs of endurance.

However, this assumption needs to be confirmed by further research, primarily by providing sufficient statistical power, identifying ethnic/geographical differences and expanding the range of genetic markers. The first issue is a specific one in terms of elite level indicators, since elite athletes are by default limited with a small number of older individuals. In order to make a population description, according to existing rules, we need to examine not less than 1000 test subjects from several regions of the republic, taking into account their ethnic characteristics. Moreover, it is still unknown, which genes are directly connected to participation in elite marathons due to a small dimension of the effect. It is possible that genes, related with the electrolyte balance, hidropoiesis, body temperature and other systems’ regulation, might play an important role [27].

Conclusion. We have revealed that shares of corresponding alleles and average values of the TGS of examined genes were higher in power and strength, but lower in endurance among elite stayers, preferring short distances, compared to marathon runners and the control group, while there was no difference in the last two groups. Since the combination of complex multifactor interactions between various genes and environmental factors has a significant influence on the result, the selection of genetic marker perspective for stayers must be approached differentially, depending on the preferred distance.

It was found that prospective genetic markers for all stayers are power alleles of the NOS3 and ACTN3 genes, marathon athletes also have AMPD1 and the endurance allele – HIF1A. In addition, according to the power indicator, the number of prospective markers also includes PPARA for average-distance runners, for short-distance runners – PPARA, MTHFR and ACE.

Using these markers in sports practice would allow us to select differentially effective and targeted physical training programs for every stayer.

The examination of people, not engaged in sports, has demonstrated the prevalence of endurance genotypes, regarding the power and strength type. It is possibly related to the natural selection due to living in arid climate of Uzbekistan. In order to clarify this circumstance, it is necessary to conduct further studies with an increase in both the sample size of elite groups and the population, and an expansion of the genetic markers spectrum.

REFERENCES

  1. Akhmetov I.I. Molecular genetics in sports. Moscow: Sovetskij Sport, 268 p. (in Russ.)
  2. Mavlyanov I.R., Ashirmetov A.К Prospects of molecular genetics in sports medicine. Journal of Diseases, 2016, vol. 3(1), pp. 8-15.
  3. Gineviciene V., Utkus, Pranckeviciene E., Semenova E.A., Hall E.C.R., Ahmetov I.I. Perspectives in Sports Genomics. Biomedicines, 2022, vol. 10(2), pp. 298. Epub 2022 Jan 27. DOI: 10.3390/biomedicines10020298.
  4. John R., Dhillon M.S., Dhillon S. Genetics and the Elite Athlete: Our Understanding in 2020. Indian J Orthop, 2020, vol. 54(3), pp. 256-263.
  5. Ghosh A., Mahajan P.B. Can genotype determine the sports phenotype? A paradigm shift in sports medicine. Basic Clin. Physiol. Pharmacol, 2016, vol. 27, pp. 333-339.
  6. Sellami M., Elrayess M.A., Puce L., Bragazzi N.L. Molecular Big Data in Sports Sciences: State-of-Art and Future Prospects of OMICS-Based Sports Sciences. Front Mol Biosci, 2021, vol. 8, p. 815410. Epub 2022 Jan 11. DOI: 10.3389/fmolb.2021.815410.
  7. Ahmetov I.I., Hall E.C.R., Semenova E.A., Pranckeviciene E., Gineviciene V. Advances in sports genomics. Advances in Clinical Chemistry, 2021, vol. 107, 215-263. DOI: https://doi.org/10.1016/bs.acc.2021.07.004
  8. Mavlyanov I.R., Ashirmetov A.Kh., Mavlyanov Z.I. Problems and prospects of development of sports medicine. Asian Journal of Research, 2017, vol. 3(3), pp. 61-89.
  9. Haugen T., Seiler S., Sandbakk Ø., Tønnessen E. The training and development of elite Sprint performance: an integration of scientific and best practice literature. Sports Med. Open, 2019, vol. 5, pp. 44.
  10. DawsonA., Sheikhsaraf B., Boidin M.,  Erskine R.M., Thijssen D.H.J. Intra‐individual differences in the effect of endurance versus resistance training on vascular function: A cross‐over study. Scand J Med Sci Sports, 2021, vol. 31(8), pp. 1683-1692.
  11. Silva H-H.,  Silva M-R.G., Cerqueira F., Tavares V., Medeiros R. Genomic profile in association with sport-type, sex, ethnicity, psychological traits and sport injuries of elite athletes. J Sports Med Phys Fitness, 2022, vol. 62(3), pp. 418-434. Epub 2021 Mar 5. DOI: 10.23736/S0022-4707.21.12020-1.
  12. Williams A.G., Folland J.P. Similarity of polygenic profiles limits the potential for elite human physical performance. J Physiol, 2008, vol. 586, pp.113-121.
  13. Fuku N., Kumagai H., Ahmetov I.I. Genetics of muscle fiber composition. Sports, Exercise, and Nutritional Genomics: Current Status and Future Directions, Academic Press, USA, 2019. pp. 295-314.
  14. Hall E., Semenova E.A., Borisov O.V., Andryushchenko O.N.,  Andryushchenko L.B., Zmijewski P., Generozov E.V., Ahmetov I.I. Association analysis of multiple traits and muscle fiber composition in athletes and untrained subjects. Sport, 2021, vol. 38, pp. 3-10.
  15. Miyamoto-Mikami E., Zempo H., Fuku N., Kikuchi N., Miyachi M., Murakami H. Heritability estimates of endurance-related phenotypes: a systematic review and meta-analysis. J. Med. Sci. Sports, 2018, vol. 28, pp. 834–845.
  16. Suga T., Terada M., Tanaka T., Miyake Y., Ueno H., Otsuka M., Nagano A., Isaka T. Calcaneus height is a key morphological factor of sprint performance in sprinters. Rep, 2020, vol. 10, p. 15425.
  17. Hall E., Lysenko E.A., Semenova E.A., Borisov O.V., Andryushchenko O.N.,  Andryushchenko L.B., Vepkhvadze T.F., Lednev E.M., Zmijewski P., Popov D.V., Generozov E.V., Ahmetov I.I. Prediction of muscle fiber composition using multiple repetition testing. Sport, 2021, vol. 38, pp. 277-283.
  18. Zempo H., Miyamoto-Mikami E., Kikuchi N., Fuku N., Miyachi M., Murakami H. Heritability estimates of muscle strength-related N. phenotypes: a systematic review and meta-analysis. J. Med. Sci. Sports, 2017, vol. 27, pp. 1537-1546.
  19. Stepto N.K., Coffey V.G., Carey A.L., Ponnampalam A.P., Canny B.J., Powell D., Hawley J.A. Global gene expression in skeletal muscle from well-trained strength and endurance athletes. Sci. Sports Exerc, 2009, vol. 41, pp. 546-565.
  20. Gronek P., Gronek J., Lulińska-Kuklik E., Spieszny M., Niewczas M., Kaczmarczyk M., Petr M., Fischerova P., Ahmetov I.I., Żmijewski P. Polygenic Study of Endurance‐Associated Genetic Markers NOS3 (Glu298Asp), BDKRB2 (9/+9),UCP2 (Ala55Val), AMPD1 (Gln45Ter) and ACE (I/D) in Polish Male Half Marathoners. J Hum Kinet, 2018, vol. 64, pp. 87-98. 
  21. Moir J., Kemp R., Folkerts D., Spendiff O., Pavlidis C., Opara E.   Genes and Elite Marathon Running Performance: A Systematic Review. J Sports Sci Med, 2019, vol. 18(3), pp. 559-568.
  22. Ipekoglu G.,  Bulbul A.,  Cakir H.I. A meta-analysis on the association of ACE and PPARA gene variants and endurance athletic status. J Sports Med Phys Fitness, 2021. Epub 2021 May 24. DOI: 10.23736/S0022-4707.21.12417-X. 
  23. Delgado V., Orriols J.J.T., Martín D.M., Coso J.D. Genotype scores in energy and iron-metabolising genes are higher in elite endurance athletes than in nonathlete controls. Appl Physiol Nutr Metab, 2020, vol. 45(11), pp.1225-1231. 
  24. Dinç N.,  Yücel S.B.,  Taneli F., Sayın M.V. The effect of the MTHFR C677T mutation on athletic performance and the homocysteine level of soccer players and sedentary individuals. J Hum Kinet, 2016, vol. 51, pp. 61-69.
  25. Tsianos G.I., Evangelou E., Boot A., Zillikens M.C., van Meurs J.B., Uitterlinden A.G., Ioannidis J.P. Associations of polymorphisms of eight muscle-or metabolism-related genes with performance in Mount Olympus marathon runners. Journal of Applied Physiology, 2010, vol. 108(3), pp. 567-574.
  26. Pranckeviciene E., Gineviciene V., Jakaitiene A., Januska L., Utkus A. Total Genotype Score Modelling of Polygenic Endurance-Power Profiles in Lithuanian Elite Athletes. Genes (Basel), 2021, vol. 12(7), pp. 1067. Epub 2021 Jul 13. DOI: 10.3390/genes12071067.
  27. Gibson O.R., James C.A., Mee J.A., Willmott A.G.B., Turner G., Hayes M., Maxwell N.S. Heat alleviation strategies for athletic performance: A review and practitioner guidelines. Temperature (Austin), 2020, vol. 7(1), pp. 3-36.
  28. Wilber R.L, Pitsiladis Y.P. Kenyan and Ethiopian distance runners: what makes them so good? The International Journal of Sports Physiology and Performance, 2012, vol. 2, pp. 92-102.
  29. Ash G.I., Scott R.A., Deason M., Dawson T.A., Wolde B., Bekele Z., Teka S., Pitsiladis Y.P. No association between ACE gene variation and endurance athlete status in Ethiopians. Medicine and Science in Sports and Exercise, 2011, vol. 43(4), pp. 590-597.

INFORMATION ABOUT THE AUTHORS:
Iskandar Rakhimovich Mavlyanov – Doctor of Medical Sciences, Professor, Deputy Director for Scientific Work, Republican Scientific and Practical Center of Sports Medicine at the National Olympic Committee of Uzbekistan, Tashkent.
Abdurashid Hamidovich Ashirmetov – Doctor of Medical Sciences, Ministry of Health of Uzbekistan, Tashkent.
Sunnatilla Tuichibaevich Yulchiev – Candidate of Medical Sciences, Head of the Sports Department, Republican Scientific and Practical Center of Sports Medicine, Tashkent.
Noiba Mirzaathamovna Rakhimova – Candidate of Biological Sciences, Senior Researcher, Head of the Laboratory Diagnostics Department, Republican Scientific and Practical Center of Sports Medicine, Tashkent.

For citation: Mavlyanov I.R., Ashirmetov A.Кh., Yulchiev S.Т., Rakhimova N.M. Does the preferred distance of elite stayers depend on genetic polymorphism? Russian Journal of Sports Science: Medicine, Physiology, Training, 2022, vol. 1, no. 2. DOI: 10.51871/2782-6570_2022_01_02_7                              

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