Genetic Polymorphisms Associated with Elite Athlete Status



Fig. 10.1
Mitochondrial haplogroup distribution in endurance athletes sprint/power athletes, and controls. *P = 0.032 vs Control, *P = 0.007 vs Control (Modified from Mikami 2011)



Interestingly, Okura et al. (2003) reported that m.15497G>A polymorphism characterizing haplogroup G1 was associated with obesity-related phenotypes in middle-aged individuals. Therefore, we hypothesized that haplogroup G1 is “a thrifty genotype” because of tightly coupled OXPHOS (Fuku et al. 2013; Mikami et al. 2011). Tightly coupled OXPHOS would be expected to decrease heat production and result in a higher efficiency of ATP production. The improved efficiency in ATP production could explain, at least in part, the association between haplogroup G1 and endurance performance. On the other hand, this improved efficiency in ATP production may predispose individuals to obesity if they become sedentary later on in life. Further extensive studies are necessary to investigate this hypothesis.

Sprint/power performance relies more on anaerobic glycolysis than mitochondrial OXPHOS. However, we found that mitochondrial haplogroup F was significantly associated with elite sprint/power athletic status. Mitochondrial haplogroup F is one of the major components of macrohaplogroup N (Tanaka et al. 2004). We also found that macrohaplogroup N was significantly associated with stronger leg extension power and higher vertical jump performance (Fuku et al. 2012). It is possible that certain mtDNA polymorphisms may influence the regulation of ATP production not only by the OXPHOS system in the mitochondria but also by the glycolytic pathway in the cytosol. Indeed, Hwang et al. (2011) reported that hybrid cells harboring haplogroups F and N9a exhibited significant differences in their nuclear gene expression pattern; mitochondrial haplogroup F showed a decreased gene expression of mitochondrial OXPHOS pathway and an increased gene expression of the cytosolic glycolysis pathway compared with mitochondrial haplogroup N9a. This observation can be regarded as a compensatory response for decreased ATP production caused by a defective mitochondrial haplogroup, resulting in an increased expression of the nuclear genes involved in glycolysis. This phenomenon might explain, at least partly, the association between mitochondrial haplogroup F and elite SPA status.

In the Asian population, Kim et al. (2012) also investigated the association between elite Korean athletic status and mitochondrial haplogroups. In that study, they found that EMA had an excess of haplogroups M* and N9, but a dearth of haplogroup B as compared with CON. On the other hand, the haplogroup distribution in SPA did not differ from CON. Although the dearth of haplogroup B in EMA is consistent between elite Japanese (Mikami et al. 2011) and Korean (Kim et al. 2012) athlete studies, other associations were not replicated in these studies. Therefore, further replication studies and more detailed analysis (e.g. entire mtDNA sequencing) are needed.



10.4.4 Comprehensive Analysis of mtDNA Variants in Elite Japanese Athletes


As mentioned above, associations of different mitochondrial haplogroups with elite athletic status has been reported in Europeans, Africans, and Asians, respectively. However, the functional polymorphisms which are responsible for the previously reported associations between haplogroups and elite athletic status have not been identified. Each mitochondrial haplogroup is divided into several subhaplogroups which are younger branches than the haplogroups in the mtDNA phylogenetic tree. Young branches (subhaplogroups) in the mtDNA phylogenetic tree contain a higher proportion of nonsynonymous substitutions in the protein-coding genes and substitutions in the rRNA and tRNA genes than old branches (haplogroups) (Elson et al. 2004; Ruiz-Pesini and Wallace 2006), since influential variants have been eliminated from the older branches of the tree by ‘purifying selection’ (in evolutionary terms). Thus, subhaplogroup-specific substitutions are more likely to be associated with various health- and performance-related phenotypes. Then, in order to identify the precise mtDNA polymorphisms which associate with elite Japanese athletic status, we analyzed entire mtDNA sequences of 185 elite Japanese athletes from various sports (Mikami et al. 2013). All athletes had represented Japan at international competitions, and they were divided into 100 EMA and 85 SPA. The control group (CON) consisted of 672 Japanese individuals, whose entire mtDNA sequences were registered in our Human Mitochondrial Genome Single Nucleotide Polymorphism Database (http://​mtsnp.​tmig.​or.​jp/​mtsnp/​index.​shtml) (Tanaka et al. 2004). From the analysis of the entire mtDNA of 185 elite Japanese athletes and 672 control subjects, we detected a total of 1,488 mtDNA variants. Among these variants, a total of 311 variants were polymorphisms (minor allele frequency > 1 % in CON), and the frequencies of these polymorphisms were compared among the three groups. Consequently, we found that the EMA displayed an excess of seven polymorphisms, including subhaplogroup D4e2- and D4g-specific polymorphisms, as compared with CON (P < 0.05, Table 10.1), whereas SPA displayed an excess of three polymorphisms and a dearth of nine polymorphisms, including haplogroup G- and subhaplogroup G2a-specific polymorphisms, as compared with CON (P < 0.05, Table 10.1). However, none of these polymorphisms differed significantly between groups after correcting for multiple comparison (false discovery rate q-value > 0.05); a reflection most likely due to a lack of sufficient statistical power. Therefore, replication studies are required to confirm these associations between mtDNA variants and elite athletic performance.


Table 10.1
Polymorphisms in the entire mtDNA with differences between groups (Modified from Mikami 2013)


























































































































































































































































































































































Polymorphism

Amino acid change

Minor allele

Gene region

Haplogroup/subhaplogroup specificity

CON (n = 672)

EMA (n = 100)

SPA (n = 85)

EMA vs. CON

SPA vs CON

EMA vs. SPA

% (n)

% (n)

% (n)

P value

OR (95 % CI)

P value

OR (95 % CI)

P value

OR (95 % CI)

Control region

m.16140 T>C
 
C

Control region

B5, B4c1b, M7a2

5.7 (38)

1.0 (1)

9.4 (8)

0.047

0.17 (0.02–1.24)

0.172

1.73 (0.78–3.85)

0.008

0.10 (0.10–0.79)

m.16278C>T
 
T

Control region

B4d, D4g1, G2

8.3 (56)

10.0 (10)

0.0 (0)

0.578

1.22 (0.60–2.48)

0.006

0.00

0.003

INF



m.151C>T
 
T

Control region

D4a2a, D5c, B4d3, F1b1a1a1, M7b2b, Z1

1.2 (8)

1.0 (1)

4.7 (4)

0.869

0.84 (0.10–6.78)

0.014

4.10 (1.21–13.91)

0.121

0.20 (0.02–1.87)

m.152 T>C
 
C

Control region

A, A1a, A1b, A2a, A3, A5c, B4b1b, B5b3, D4a, D4b1a1,D4f, D4l1a, D5b1a, D5c, F1, F1b1, F1c, F4a, G2a1, G3a, G4a, N1b, N9b, M7a1a6, M7a1b, M8a2, M12, Y1b, Z

18.5 (124)

28.0 (28)

24.7 (21)

0.025

1.72 (1.07–2.77)

0.167

1.45 (0.85–2.46)

0.613

1.19 (0.61–2.29)

m.204 T>C
 
C

Control region

B4d3, B5, D4d1a, M7a1a, M7a1b, N9a2, Z4

4.9 (33)

2.0 (2)

10.7 (9)

0.192

0.40 (0.09–1.67)

0.029

2.32 (1.07–5.02)

0.013

0.17 (0.04–0.81)

m.514(CA)n
 
(CA) ≥ 5

Control region

A, B4a, B4c1b1, B4e, B5, C1, D4b, D4c, D5a2, F1, M7a1a, M7c, M10a, N1b, Z5, Z3

40.6 (273)

27.0 (27)

40.0 (34)

0.009

1.85 (1.16–2.95)

0.912

1.03 (0.65–1.63)

0.061

0.55 (0.30–1.03)

Poly–C stretch at m.568–573
 
C ≥ 7

Control region

C5, D4g1, F4b, G4a, M10

4.0 (27)

11.0 (11)

1.2 (1)

0.003

2.95 (1.42–6.16)

0.191

0.28 (0.04–2.12)

0.007

10.38 (1.31–82.17)

RNA-coding region

m.4343A>G
 
G

tRNA Gln

D4g

2.4 (16)

6.0 (6)

0.0 (0)

0.042

2.62 (1.00–6.85)

0.150

0.00

0.022

INF



m.5601C>T
 
T

tRNA Ala

G2a

4.8 (32)

3.0 (3)

0.0 (0)

0.429

0.62 (0.19–2.06)

0.040

0.00

0.107

INF



Protein-coding region

m.4833A>G

Thr122Ala

G

ND2

G

8.6 (58)

11.0 (11)

2.4 (2)

0.438

1.31 (0.66–2.59)

0.044

0.26 (0.06–1.06)

0.022

5.13 (1.10–23.83)

m.5108 T>C


C

ND2

G, B4c2, M7a1b

9.4 (63)

12.0 (12)

2.4 (2)

0.408

1.32 (0.68–2.54)

0.029

0.23 (0.06–0.97)

0.013

5.66 (1.23–26.05)

m.7600G>A


A

COII

G2a

4.8 (32)

3.0 (3)

0.0 (0)

0.429

0.62 (0.19–2.06)

0.040

0.00

0.107

INF



m.9377A>G


G

COIII

G2a, D5b2

5.0 (34)

3.0 (3)

0.0 (0)

0.368

0.58 (0.17–1.93)

0.034

0.00

0.107

INF



m.11215C>T


T

ND4

D4e

4.8 (32)

10.0 (10)

3.5 (3)

0.031

2.22 (1.06–4.67)

0.610

0.73 (0.22–2.44)

0.086

3.04 (0.81–11.42)

m.13104A>G


G

ND5

D4g, D4k3

3.0 (20)

6.0 (6)

0.0 (0)

0.118

2.08 (0.81–5.31)

0.107

0.00

0.022

INF



m.13563A>G


G

ND5

G2

4.8 (32)

3.0 (3)

0.0 (0)

0.429

0.62 (0.19–2.06)

0.040

0.00

0.107

INF



m.14200 T>C


C

ND6

G2a

4.5 (30)

3.0 (3)

0.0 (0)

0.499

0.966 (0.20–2.21)

0.047

0.00

0.107

INF



m.14569G>A


A

ND6

G, B4b1b, N9a2c

9.5 (64)

13.0 (13)

2.4 (2)

0.279

1.42 (0.75–2.68)

0.027

0.23 (0.06–0.95)

0.008

6.20 (1.36–28.32)

m.15314G>A

Ala190Thr

A

Cytb

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Oct 16, 2016 | Posted by in SPORT MEDICINE | Comments Off on Genetic Polymorphisms Associated with Elite Athlete Status

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