Abstract
Physical performance of youth is influenced by various factors, including body composition, biological maturity status, level of habitual physical activity, and muscular strength. Muscular strength has been largely attributed to genetic effects. To exclude possible confounding effects from various acquired factors, this study examined the relationships between polymorphisms of the angiotensin-converting enzyme (ACE), α-actinin-3 (ACTN3), peroxisome proliferator-activated receptor delta (PPARD), and peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PPARGC1A) genes and performance as measured by six fitness tests (handgrip strength of dominant hand, 30- and 60-s sit-ups, standing long jump, 60-m dash, and 800-m run) in 170 sedentary adolescent girls with the adjustment of anthropometric characteristics. We found that subjects with the ACE DD genotype were significantly heavier than those with I allele, while those with the ACTN3 RR genotype had higher fat-free mass percentage (FFM%) than those with the XX genotype. In addition, those with the PPARD TT genotype were significantly taller, heavier, and had a greater FFM than those with the CC genotype. Subjects with the ACE DD, ACTN3 RR and PPARD TC genotype had better performance in handgrip strength, 30- and 60-s sit-up tests, and standing long jump, respectively, when individual gene was analyzed independently after adjusting anthropometric characteristics. In the gene combination analysis, subjects with ACE DD, ACTN3 RR and PPARD TT genotype had significantly greater performance in handgrip strength. Overall, the results indicate that the genes studied have a modest influence on individual performance as assessed by specific fitness and strength tests in female late adolescents.
Electronic supplementary material
The online version of this article (doi:10.1007/s12576-011-0189-0) contains supplementary material, which is available to authorized users.
Keywords: Polygenic trait, Adolescence, Body composition, FFMI, Handgrip strength
Introduction
It has been reported that the physical performance of youth is influenced by a variety of factors, including age, sex, body size, and composition, biological maturity status, level of habitual physical activity and muscular strength [1, 2]. Among them, muscular strength can be attributed to genetic effects varying from 0.27 to 0.58 based on family studies and between 0.14 and 0.83 based on twin studies [3]. Recently, the development of technology for rapid DNA sequencing and genotyping has allowed the identification of some individual genetic variations that contribute to physical performance. Bray et al. [4] has comprehensively reviewed genes and markers that show evidence of association with performance or fitness phenotypes in sedentary or active people, in responses to acute exercise, and in terms of training-induced adaptation. Among the 214 listed autosomal genes, angiotensin-converting enzyme (ACE) and α-actinin-3 (ACTN3) are the genes with the highest number of positive findings. Most studies have linked the ACE I allele to endurance performance [5] and the D allele to muscle strength and power-oriented performance [6–8]. The ACTN3 R allele is prevalent among sprint athletes and the X allele is less common among sprinters, particularly in the homozygous form (XX) [9–13].
In addition to ACE and ACTN3, there is emerging evidence that the peroxisome proliferator-activated receptor delta (PPARD) [14, 15] and peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PPARGC1A) [16] gene may play an important role in physical performance. Recently, Eynon et al. [17] found that the PPARD T294C polymorphism together with peroxisome proliferator-activated receptor γ coactivator-1α (PPARGC1A) play an important role in endurance-type performance.
There are few data available on the combined influence of polymorphisms of ACE, ACTN3 and other genes on physical capability phenotypes, especially in non-athletic populations [18–21]. Furthermore, physical performance is also determined by a range of acquired factors such as age, body composition, and physical training. To exclude possible confounding effects from these factors, the present study was carried out to examine the relationships between the ACE, ACTN3, PPARD, and PPARGC1A genotypes and performance in fitness tests by sedentary female adolescents (16–18 years).
Methods
Subjects
This study was conducted according to the Harriss and Atkinson Statement [22] and approved by the Institutional Review Board of Chang Gung Memorial Hospital. To exclude the possible influences of menstrual and disease status on physical performances, we first surveyed the disease history as well as the menstrual cycle length and the first day of the latest menstrual bleeding for all the 11th grade (16–18 years old) female students. Only those students with a regular menstrual cycle length of 28–30 days and the first day of their latest menstrual bleeding were within just 3 days were asked to participate the present study. Finally, a total of 170 sedentary female students without cardiovascular, metabolic, or musculoskeletal diseases were included for the present analysis. All parents gave written consent and each girl also provided individual written assent. Body mass index (BMI) was calculated as weight (kg) divided by square of the height (m2). The percentage of body fat was estimated by bioelectrical impedance analysis using an OMRON (HBF-355) hand-to-foot body composition monitor (Omron Healthcare, Kyoto, Japan) [23] and was used to calculate the fat-free mass FFM (kg) and the fat-free mass percentage (FFM%). The fat-free mass index (FFMI) was calculated as the FFM (kg) divided by the square of the height (m2).
According to the Taiwan physical fitness test manual [24], six fitness tests were carried out without any prior training. They were (1) handgrip strength of the dominant hand, (2) 30- and 60-s sit-ups, (3) a standing long jump, (4) a 60-m dash, and (5) a 800-m endurance run. All the tests were executed in the morning and all the subjects completed the same test on the same day. In addition, 5 mL of saliva was collected from each participant and centrifuged at 800g for 10 min at room temperature to obtain oral mucosa cells for genotyping.
Genotyping
Genomic DNA was purified from oral mucosa cells by digestion with proteinase K and then extracted using a conventional phenol/chloroform procedure. Genotyping of the ACE I/D (rs1799752) was performed using polymerase chain reaction (PCR) as previously described [25]. The genotypes ACTN3 R577X (rs1815739) and PPARD T294C (rs2016520) were determined by PCR restriction fragment length polymorphism (RFLP) as described by Mills et al. [26] and Ahmetov et al. [14], respectively. The conditions for PCR were as shown in Table 1. Since it has been reported that amplification of the ACE I allele is sometimes suppressed in ID heterozygotes and mistyped as the DD genotype [27], all the samples classified as DD genotype were checked with a second PCR reaction using an I-specific primer pair: 5′-TGGGACCACAGCGCCCGCCACTAC-3′ (forward) and 5′-TCGCCAGCCCTCCCATGCCCATAA-3′ (reverse) [28]. The ACTN3 and PPARD genotypes were determined by enzymatic digestion of their amplicons with Dde I and Bsc4I, respectively. The PPARGC1A Gly482Ser (rs8192678) genotype was determined as described previously [29] using TaqMan-based allelic discrimination assay on a 7500 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA).
Table 1.
Forward/reverse primers and PCR conditions for ACE, ACTN3, and PPARD genotyping
| Gene | Forward primer | Reverse primer | PCR reaction conditions | ||
|---|---|---|---|---|---|
| (5′–3′) | (5′–3′) | Denaturation | Annealing and cycles | Final extension | |
| ACE | CTGGAGACCACTCCCATCCTTTCT | GATGTGGCCATCACATTCGTCAGAT | 95°C for 5 min |
35 cycles of 95°C for 1 min, 58°C for 30 s, 72°C for 40 s |
72°C for 10 min |
| ACTN3 (exon 16) | CTGTTGCCTGTGGTAAGTGGG | TGGTCACAGTATGCAGGAGGG | 95°C for 5 min |
35 cycles of 95°C for 1 min, 58°C for 30 s, 72°C for 40 s |
72°C for 10 min |
| PPARD (exon 4) | CATGGTATAGCACTGCAGGAA | CTTCCTCCTGTGGCTGCTC | 95°C for 5 min |
35 cycles of 95°C for 1 min, 60°C for 30 s, 72°C for 40 s |
72°C for 10 min |
Total genotype score (TGS) determination
The combined influence of the four studied polymorphisms was determined in a similar manner to the previous study by Ruiz et al. [20]. A genotype score (GS) for the ‘optimal’ or preferable endurance genotype in each polymorphism was assigned as 2, whereas a GS of 0 was assigned to the least optimal genotype (Table 2). The sum of the GS from the genes studied (i.e. GSACE + GSACTN3 + GSPPARD) was designated as the TGSACE+ACTN3+PPARD.
Table 2.
Genotype score (GS) and frequency distribution of ACE, ACTN3, PPARD, and PPARGC1A studied in Taiwanese female late adolescents
| Gene | Polymorphism | Genotype score (GS) | Frequency (%) |
|---|---|---|---|
| ACE | 287-bp Ins(I)/Del(D) | 0 = DD, 1 = ID, 2 = II | 7, 44, 49 |
| ACTN3 | Arg(R)577Ter(X) | 0 = RR, 1 = RX, 2 = XX | 27, 53, 20 |
| PPARD | T294C | 0 = TT, 1 = TC, 2 = CC | 38, 45, 17 |
| PPARGC1A | Gly482Ser | 0 = Ser/Ser, 1 = Gly/Ser, 2 = Gly/Gly | 18, 58, 24 |
Genotype score: 0 = “optimal” sprint/power genotype
ACE Angiotensin-converting enzyme gene, ACTN3 α-actinin-3 gene, PPARD peroxisome proliferator-activated receptor delta gene, PPARGC1A peroxisome proliferator-activated receptor gamma coactivator-1 alpha gene
Statistical analysis
All statistical analyses were performed using SPSS v.13.0 (SPSS, Chicago, IL, USA). The distribution of genotypes studied was tested for the fulfilment of Hardy–Weinberg equilibrium status by using a Chi-square test with one degree of freedom. The differences in anthropometric characteristics among the different genotypes were compared by one-way analysis of variance (ANOVA) or the Kruskal–Wallis test depending on the normality of the variables. The differences in physical performance among the different genotypes were compared by analysis of covariance (ANCOVA) adjusted for height, body weight, BMI, FFM%, FFM, and FFMI. The level of significance was set at 0.05. All reported p values are 2-sided.
Results
The distribution of genotype for these four genes studied was not deviated from Hardy–Weinberg equilibrium (all p values >0.05). The association between anthropometric characteristics and ACE, ACTN3, PPARD, and PPARGC1A polymorphisms were shown in Table 3. Subjects with the ACE DD genotype (61.6 kg) were significantly heavier than those with the ID (54.9 kg) and the II (55.4 kg) genotype. Subjects with the ACTN3 RR genotype (71.0%) had higher FFM% values than those with the XX genotype (68.6%). In addition, those with the PPARD TT genotype were significantly taller (161.0 cm), heavier (57.1 kg), and had a greater FFM (39.3 kg) than those with the CC genotype (157.1 cm, 51.8 kg, and 36.2 kg). On the other hand, BMI and FFMI themselves were not significantly associated with the ACE, ACTN3, PPARD, and PPARGC1A polymorphisms.
Table 3.
Association between anthropometric characteristics and ACE, ACTN3, PPARD, and PPARGC1A polymorphisms
| Genotype | Height (cm) | Weight (kg) | BMI (kg m−2) | FFM% | FFM (kg) | FFMI (kg m−2) |
|---|---|---|---|---|---|---|
| ACE | ||||||
| DD (n = 12) | 163.3 ± 2.2 | 61.6 ± 2.2 b,c | 23.1 ± 0.8 | 67.5 ± 1.1 | 41.3 ± 1.0 | 41.3 ± 1.0 |
| ID (n = 74) | 160.5 ± 0.6 | 54.9 ± 1.1 b | 21.2 ± 0.4 | 70.0 ± 0.5 | 38.0 ± 0.5 | 38.0 ± 0.5 |
| II (n = 84) | 159.9 ± 0.6 | 55.4 ± 1.1 c | 21.6 ± 0.4 | 70.1 ± 0.4 | 38.1 ± 0.5 | 38.1 ± 0.5 |
| p value | 0.152 | 0.023 | 0.102 | 0.115 | 0.055 | 0.112 |
| ACTN3 | ||||||
| RR (n = 46) | 160.5 ± 0.8 | 54.3 ± 1.1 | 21.0 ± 0.4 | 71.0 ± 0.6 e | 38.6 ± 0.6 | 41.3 ± 1.0 |
| RX (n = 90) | 161.0 ± 0.7 | 56.0 ± 1.1 | 21.5 ± 0.4 | 69.8 ± 0.5 | 38.2 ± 0.5 | 38.0 ± 0.5 |
| XX (n = 34) | 158.7 ± 0.7 | 56.4 ± 1.7 | 22.3 ± 0.6 | 68.6 ± 0.7 e | 37.8 ± 0.8 | 38.1 ± 0.5 |
| p value | 0.126 | 0.766 | 0.296 | 0.04 | 0.735 | 0.514 |
| PPARD | ||||||
| TT (n = 65) | 161.0 ± 0.7 a | 57.1 ± 1.2 d | 22.0 ± 0.4 | 69.4 ± 0.6 | 39.3 ± 0.6 f | 41.3 ± 1.0 |
| TC (n = 77) | 161.1 ± 0.6 | 55.8 ± 1.2 | 21.4 ± 0.4 | 70.2 ± 0.5 | 38.2 ± 0.5 | 38.0 ± 0.5 |
| CC (n = 28) | 157.1 ± 0.9 a | 51.8 ± 1.3 d | 21.0 ± 0.5 | 70.1 ± 0.7 | 36.2 ± 0.7 f | 38.1 ± 0.5 |
| p value | 0.002 | 0.025 | 0.166 | 0.454 | 0.009 | 0.130 |
| PPARGC1A | ||||||
| Ser/Ser (n = 31) | 159.6 ± 0.9 | 56.5 ± 2.0 | 22.1 ± 0.7 | 69.0 ± 0.7 | 38.0 ± 1.0 | 14.9 ± 0.3 |
| Gly/Ser (n = 98) | 160.3 ± 0.6 | 54.5 ± 0.9 | 21.2 ± 0.3 | 70.2 ± 0.4 | 37.9 ± 0.5 | 14.7 ± 0.1 |
| Gly/Gly (n = 41) | 161.6 ± 0.8 | 57.5 ± 1.6 | 22.0 ± 0.5 | 70.1 ± 0.8 | 39.6 ± 0.6 | 15.1 ± 0.2 |
| p value | 0.259 | 0.197 | 0.234 | 0.361 | 0.149 | 0.269 |
Values expressed as mean ± SE
BMI Body mass index, FFM% far-free mass percentage, FFM fat-free mass, FFMI fat-free mass index
a–fThe bold values indicate that there is a significant difference in the post hoc test using the a,f Scheffe and b–e Mann–Whitney U tests
After adjustment of anthropometric characteristics (height, weight, BMI, FFM%, FFM and FFMI), subjects with the ACE DD genotype had greater handgrip strength (28.3 kg) than those with the ID (25.0 kg) and the II (25.6 kg) genotype (Table 4). Individuals with the ACTN3 RR genotype performed better in the 30- and 60-s sit-up tests (18.7 and 34.1 counts) than those with the RX genotype (17.0 and 30.3 counts). Subjects with the PPARD TC genotype (150.1 cm) performed significantly better in the standing long jump test than those with the CC genotype (136.9 cm). Subjects with the PPARGC1A Gly/Gly genotype (34.4 counts) performed significantly better in the 60-s sit-up test than those with the Gly/Ser genotype (30.5 counts). However, there were no associations between the genotypes and either 60-m dash or 800-m endurance run test.
Table 4.
Association between the fitness test results and ACE, ACTN3, PPARD, and PPARGC1A polymorphisms
| Genotype | Handgrip strength (kg) | Standing long jump (cm) | 30-s sit-up (counts) | 60-s sit-up (counts) | 60-m dash (s) | 800-m run (s) |
|---|---|---|---|---|---|---|
| ACE | ||||||
| DD (n = 12) | 28.3 ± 1.2 | 152.6 ± 6.1 | 18.0 ± 1.2 | 32.3 ± 2.3 | 11.6 ± 0.4 | 290.1 ± 10.0 |
| ID (n = 74) | 25.0 ± 0.5 | 144.5 ± 2.5 | 17.5 ± 0.5 | 31.6 ± 1.0 | 11.9 ± 0.2 | 287.2 ± 4.1 |
| II (n = 84) | 25.7 ± 0.5 | 146.0 ± 2.3 | 18.0 ± 0.4 | 32.0 ± 0.9 | 11.8 ± 0.1 | 281.7 ± 3.8 |
| p value | 0.048 | 0.421 | 0.734 | 0.941 | 0.649 | 0.535 |
| ACTN3 | ||||||
| RR (n = 46) | 26.7 ± 0.6 | 143.8 ± 3.2 | 18.7 ± 0.5 | 34.1 ± 1.2 | 12.1 ± 0.2 | 285.2 ± 5.2 |
| RX (n = 90) | 25.1 ± 0.5 | 145.9 ± 2.2 | 17.0 ± 0.4 | 30.3 ± 0.8 | 11.7 ± 0.1 | 285.1 ± 3.7 |
| XX (n = 34) | 25.3 ± 0.8 | 147.5 ± 3.7 | 18.3 ± 0.7 | 32.8 ± 1.4 | 11.7 ± 0.2 | 282.8 ± 6.1 |
| p value | 0.141 | 0.751 | 0.048 | 0.029 | 0.355 | 0.940 |
| PPARD | ||||||
| TT (n = 65) | 25.6 ± 0.5 | 144.5 ± 2.5 | 17.6 ± 0.5 | 31.7 ± 1.0 | 11.9 ± 0.2 | 281.6 ± 4.3 |
| TC (n = 77) | 25.6 ± 0.5 | 150.1 ± 2.4 | 17.8 ± 0.5 | 31.8 ± 0.9 | 11.6 ± 0.1 | 283.8 ± 4.0 |
| CC (n = 28) | 25.5 ± 0.8 | 136.9 ± 4.0 | 18.0 ± 0.8 | 32.2 ± 1.6 | 12.1 ± 0.2 | 294.4 ± 6.7 |
| p value | 0.996 | 0.018 | 0.930 | 0.969 | 0.158 | 0.274 |
| PPARGC1A | ||||||
| Ser/Ser (n = 31) | 25.8 ± 0.8 | 146.9 ± 3.8 | 18.3 ± 0.7 | 32.9 ± 1.4 | 11.7 ± 0.2 | 288.6 ± 6.2 |
| Gly/Ser (n = 98) | 25.4 ± 0.4 | 146.4 ± 2.1 | 17.3 ± 0.4 | 30.5 ± 0.8 | 11.8 ± 0.1 | 284.9 ± 3.5 |
| Gly/Gly (n = 41) | 26.2 ± 0.7 | 144.1 ± 3.4 | 18.7 ± 0.6 | 34.4 ± 1.3 | 11.9 ± 0.2 | 281.2 ± 5.6 |
| p value | 0.589 | 0.825 | 0.126 | 0.026 | 0.652 | 0.675 |
Values expressed as mean ± SE adjusted for height, body weight, BMI, FFM%, FFM, and FFMI by ANCOVA
The bold values indicate that there is a significant difference in the Bonferroni post hoc test
The combined gene influence on physical performance was further explored. As shown in Table S1 (supplementary) and Table 5, TGSACE+ACTN3+PPARD+PPARGC1A was only marginally associated with handgrip strength, while TGSACE+ACTN3+PPARD was associated with handgrip strength and 60-s sit-up. Additionally, it is worth noting that the maximum handgrip strength (41.4 kg) found among all the subjects was an individual who did not have the “optimal” gene profile for the least endurance group, namely a TGS of 0.
Table 5.
Association between total genotype score (TGSACE+ACTN3+PPARD) and performance in the fitness tests studied
| Physical performance | Total genotype score | |||||||
|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 | 6 | p | |
| n | 3 | 15 | 39 | 38 | 57 | 11 | 7 | |
| Handgrip strength (kg) | 32.7 ± 2.5 (33.1–36.0) | 26.4 ± 1.0 (19.8–35.2) | 25.8 ± 0.7 (15.1–41.4) | 24.3 ± 0.7 (16.6–33.0) | 25.9 ± 0.6 (16.3–37.9) | 25.5 ± 1.3 (18.0–31.4) | 25.1 ± 1.6 (18.6–31.6) | 0.050 |
| Standing long jump (cm) | 168.6 ± 12.2 | 144.6 ± 5.2 | 143.6 ± 3.4 | 144.7 ± 3.4 | 149.5 ± 2.8 | 144.3 ± 6.4 | 133.9 ± 7.9 | 0.235 |
| 30-s sit-up (counts) | 19.80 ± 2.3 | 17.2 ± 1.0 | 18.6 ± 0.6 | 16.6 ± 0.6 | 18.0 ± 0.5 | 17.6 ± 1.2 | 19.2 ± 1.5 | 0.329 |
| 60-s sit-up (counts) | 35.4 ± 4.6 | 30.1 ± 2.0 | 34.4 ± 1.3 | 28.9 ± 1.3 | 32.3 ± 1.1 | 30.1 ± 2.4 | 34.5 ± 3.0 | 0.077 |
| 60-m dash (s) | 11.9 ± 0.7 | 12.4 ± 0.3 | 11.6 ± 0.2 | 12.0 ± 0.2 | 11.6 ± 0.2 | 11.7 ± 0.4 | 12.2 ± 0.5 | 0.335 |
| 800-m run (s) | 281.0 ± 20.0 | 292.8 ± 8.5 | 277.6 ± 5.6 | 292.3 ± 5.6 | 280.8 ± 4.6 | 293.0 ± 10.4 | 281.4 ± 14.0 | 0.457 |
All values indicate the mean ± SE adjusted for height, body weight, BMI, FFM%, FFM and FFMI by ANCOVA (with range, in handgrip strength performance); the bold numbers indicate the lowest and highest handgrip strength
Discussion
In this study, we found that performance in the handgrip strength, 30-/60-s sit-up, standing long jump, and 60-s sit-up test results were significantly associated with ACE, ACTN3, PPARD, and PPARGC1A polymorphisms, respectively, in sedentary female late adolescents after adjusting for anthropometric characteristics (Table 4). The ACE D allele is associated with higher ACE activity and thus an increased angiotensin II level [30]. Therefore, this allele would theoretically favor performance in power-oriented exercise tasks. Previous studies have reported a positive association of the ACE D allele and baseline grip strength in healthy untrained subjects [8], patients with chronic obstructive pulmonary disease [31], advanced cancer patients [32], and elite strength-trained athletes [33]. In contrast, some studies have failed to support such findings [28, 34]. Surprisingly, the Moran et al. [35] study of teenage Greeks reported that the homozygous I-allele individuals exhibited higher performance scores. In the present study, an association between ACE polymorphism and standing long jump was not observed. Similar phenomenon was also noted by Rodriguez-Romo et al. [36] in young non-athletic adults.
It has been reported that ACTN3 XX genotype precluded top-level athletic performance in ‘‘pure’’ power and sprint sports (sprinting, jumping, weightlifting, and throwing events), especially among women [13]. In the present study, we found that those with the ACTN3 RR genotype in combination with the ACE DD genotype performed significantly better in terms of handgrip strength than those with other genotype combinations (Tables S2 and S3). However, no effect on standing long jump was observed. Previous studies have also demonstrated that the ACTN3 R577X polymorphism does not seem to influence explosive leg muscle power (jumping, sprinting) alone or in combination with the ACE I/D polymorphism in a young non-athletic population, irrespective of gender [36]. Clarkson et al. [37] and Walsh et al. [38] reported that women with the ACTN3 XX genotype have lower strength than those with the RX genotype. Chiu et al. [39] reported that pre-adolescents with the ACTN3 RR genotype exhibited the best performance across all phases (before, during, and after training) of 25-m swimming performance. However, in older women (64 years), knee extensor concentric peak power was found to be higher in X allele homozygote individuals compared with RR genotype individuals [40]. These discrepancies may reflect that there is an interaction between age and genotype [41].
There is compelling evidence indicating that a functional T294C polymorphism of PPARD influences human physical performance [15]. In the present study, we found that the subjects with the TC genotype demonstrated a better performance in the lower extremity explosive power standing long jump test than those with CC genotype. This finding supports the hypothesis that the PPARD C allele is associated with a predisposition to endurance performance [17].
The combined effect of the ACE, ACTN3, PPARD, and PPARGC1A polymorphisms on performance across the six fitness tests was further evaluated using the TGS index as described previously [20]. In the present study, since there was no subject with homozygous ACE DD, ACTN3 RR, PPARD TT, and PPARGC1A Ser/Ser genotype, the greatest mean handgrip strength was observed in subjects with TGSACE+ACTN3+PPARD+PPARGC1A = 1 as expected (Table S1). Furthermore, subjects that were homozygous ACE DD, ACTN3 RR, and PPARD TT had the greatest handgrip strength, which suggests that these “strength/power” alleles do indeed confer a performance advantage (Table 5). However, it is also interesting to note that the subject with the best handgrip strength performance did not belong to the “optimal” (TGS = 0) power genotype group. These findings indicate that the relationships between the genetic traits and physical performance are quite complex and not yet completely understood [19, 21, 42].
Handgrip strength has been linked to premature mortality, disability, and other health-related complications in middle-aged and older people [43–45]. In the present study, we demonstrated an association between three genetic polymorphisms (ACE I/D, ACTN3 R577X, and PPARD T294C) and handgrip strength in sedentary female adolescents (16–18 years). These results may provide evidence that helps the development of recommendations such as early specific nutritional and/or functional interventions (e.g., resistance training activity) for those with a high TGS index. In the future, polygenic physical fitness profiling of a larger general population linked to specific nutritional/functional intervention studies will be required to provide valid information on the true role of genetic factors on physical fitness and health.
In conclusion, the results indicate that the studied genes have a moderate influence on performance as measured by specific fitness tests and the effect of the ACE and ACTN3 polymorphisms on the strength type of fitness is greater than the effect of PPARD and PPARGC1A polymorphism among Taiwanese female late adolescents.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgment
This study was supported by Grant NSC-96-2413-H-003-033 from the National Science Council, Taiwan.
Conflict of interest
The authors declare no conflict of interest.
References
- 1.Huang YC, Malina RM. BMI and health-related physical fitness in Taiwanese youth 9–18 years. Med Sci Sports Exerc. 2007;39:701–708. doi: 10.1249/mss.0b013e31802f0512. [DOI] [PubMed] [Google Scholar]
- 2.Moliner-Urdiales D, Ortega FB, Vicente-Rodriguez G, Rey-Lopez JP, Gracia-Marco L, Widhalm K, Sjostrom M, Moreno LA, Castillo MJ, Ruiz JR. Association of physical activity with muscular strength and fat-free mass in adolescents: the HELENA study. Eur J Appl Physiol. 2010;109:1119–1127. doi: 10.1007/s00421-010-1457-z. [DOI] [PubMed] [Google Scholar]
- 3.Peeters MW, Thomis MA, Beunen GP, Malina RM. Genetics and sports: an overview of the pre-molecular biology era. Med Sport Sci. 2009;54:28–42. doi: 10.1159/000235695. [DOI] [PubMed] [Google Scholar]
- 4.Bray MS, Hagberg JM, Perusse L, Rankinen T, Roth SM, Wolfarth B, Bouchard C. The human gene map for performance and health-related fitness phenotypes: the 2006–2007 update. Med Sci Sports Exerc. 2009;41:35–73. doi: 10.1249/mss.0b013e3181844179. [DOI] [PubMed] [Google Scholar]
- 5.Myerson S, Hemingway H, Budget R, Martin J, Humphries S, Montgomery H. Human angiotensin I-converting enzyme gene and endurance performance. J Appl Physiol. 1999;87:1313–1316. doi: 10.1152/jappl.1999.87.4.1313. [DOI] [PubMed] [Google Scholar]
- 6.Jones A, Woods DR. Skeletal muscle RAS and exercise performance. Int J Biochem Cell Biol. 2003;35:855–866. doi: 10.1016/S1357-2725(02)00342-4. [DOI] [PubMed] [Google Scholar]
- 7.Nazarov IB, Woods DR, Montgomery HE, Shneider OV, Kazakov VI, Tomilin NV, Rogozkin VA. The angiotensin converting enzyme I/D polymorphism in Russian athletes. Eur J Hum Genet. 2001;9:797–801. doi: 10.1038/sj.ejhg.5200711. [DOI] [PubMed] [Google Scholar]
- 8.Williams AG, Day SH, Folland JP, Gohlke P, Dhamrait S, Montgomery HE. Circulating angiotensin converting enzyme activity is correlated with muscle strength. Med Sci Sports Exerc. 2005;37:944–948. [PubMed] [Google Scholar]
- 9.Ahmetov II, Druzhevskaya AM, Astratenkova IV, Popov DV, Vinogradova OL, Rogozkin VA. The ACTN3 R577X polymorphism in Russian endurance athletes. Br J Sports Med. 2008;44:649–652. doi: 10.1136/bjsm.2008.051540. [DOI] [PubMed] [Google Scholar]
- 10.Eynon N, Duarte JA, Oliveira J, Sagiv M, Yamin C, Meckel Y, Goldhammer E. ACTN3 R577X polymorphism and Israeli top-level athletes. Int J Sports Med. 2009;30:695–698. doi: 10.1055/s-0029-1220731. [DOI] [PubMed] [Google Scholar]
- 11.Niemi AK, Majamaa K. Mitochondrial DNA and ACTN3 genotypes in Finnish elite endurance and sprint athletes. Eur J Hum Genet. 2005;13:965–969. doi: 10.1038/sj.ejhg.5201438. [DOI] [PubMed] [Google Scholar]
- 12.Papadimitriou ID, Papadopoulos C, Kouvatsi A, Triantaphyllidis C. The ACTN3 gene in elite Greek track and field athletes. Int J Sports Med. 2008;29:352–355. doi: 10.1055/s-2007-965339. [DOI] [PubMed] [Google Scholar]
- 13.Yang N, MacArthur DG, Gulbin JP, Hahn AG, Beggs AH, Easteal S, North K. ACTN3 genotype is associated with human elite athletic performance. Am J Hum Genet. 2003;73:627–631. doi: 10.1086/377590. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Ahmetov II, Williams AG, Popov DV, Lyubaeva EV, Hakimullina AM, Fedotovskaya ON, Mozhayskaya IA, Vinogradova OL, Astratenkova IV, Montgomery HE, Rogozkin VA. The combined impact of metabolic gene polymorphisms on elite endurance athlete status and related phenotypes. Hum Genet. 2009;126:751–761. doi: 10.1007/s00439-009-0728-4. [DOI] [PubMed] [Google Scholar]
- 15.Hautala AJ, Leon AS, Skinner JS, Rao DC, Bouchard C, Rankinen T. Peroxisome proliferator-activated receptor-delta polymorphisms are associated with physical performance and plasma lipids: the HERITAGE Family Study. Am J Physiol Heart Circ Physiol. 2007;292:H2498–H2505. doi: 10.1152/ajpheart.01092.2006. [DOI] [PubMed] [Google Scholar]
- 16.Lucia A, Gomez-Gallego F, Barroso I, Rabadan M, Bandres F, San Juan AF, Chicharro JL, Ekelund U, Brage S, Earnest CP, Wareham NJ, Franks PW. PPARGC1A genotype (Gly482Ser) predicts exceptional endurance capacity in European men. J Appl Physiol. 2005;99:344–348. doi: 10.1152/japplphysiol.00037.2005. [DOI] [PubMed] [Google Scholar]
- 17.Eynon N, Meckel Y, Alves AJ, Yamin C, Sagiv M, Goldhammer E. Is there an interaction between PPARD T294C and PPARGC1A Gly482Ser polymorphisms and human endurance performance? Exp Physiol. 2009;94:1147–1152. doi: 10.1113/expphysiol.2009.049668. [DOI] [PubMed] [Google Scholar]
- 18.Eynon N, Alves AJ, Yamin C, Sagiv M, Duarte JA, Oliveira J, Ayalon M, Goldhammer E, Meckel Y. Is there an ACE ID–ACTN3 R577X polymorphisms interaction that influences sprint performance? Int J Sports Med. 2009;30:888–891. doi: 10.1055/s-0029-1238291. [DOI] [PubMed] [Google Scholar]
- 19.Gomez-Gallego F, Santiago C, Gonzalez-Freire M, Muniesa CA, Fernandez Del Valle M, Perez M, Foster C, Lucia A. Endurance performance: genes or gene combinations? Int J Sports Med. 2009;30:66–72. doi: 10.1055/s-2008-1038677. [DOI] [PubMed] [Google Scholar]
- 20.Ruiz JR, Arteta D, Buxens A, Artieda M, Gomez-Gallego F, Santiago C, Yvert T, Moran M, Lucia A. Can we identify a power-oriented polygenic profile? J Appl Physiol. 2010;108:561–566. doi: 10.1152/japplphysiol.01242.2009. [DOI] [PubMed] [Google Scholar]
- 21.Ruiz JR, Gomez-Gallego F, Santiago C, Gonzalez-Freire M, Verde Z, Foster C, Lucia A. Is there an optimum endurance polygenic profile? J Physiol. 2009;587:1527–1534. doi: 10.1113/jphysiol.2008.166645. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Harriss DJ, Atkinson G. International Journal of Sports Medicine—ethical standards in sport and exercise science research. Int J Sports Med. 2009;30:701–702. doi: 10.1055/s-0029-1237378. [DOI] [PubMed] [Google Scholar]
- 23.Lintsi M, Kaarma H, Kull I. Comparison of hand-to-hand bioimpedance and anthropometry equations versus dual-energy X-ray absorptiometry for the assessment of body fat percentage in 17–18-year-old conscripts. Clin Physiol Funct Imaging. 2004;24:85–90. doi: 10.1111/j.1475-097X.2004.00534.x. [DOI] [PubMed] [Google Scholar]
- 24.Tsai CL. The comparison of the fitness of the students in basketball and volleyball school teams and the students in normal classes in primary school. J Pingtung Teach Coll. 2002;17:499–510. [Google Scholar]
- 25.Alvarez R, Reguero JR, Batalla A, Iglesias-Cubero G, Cortina A, Alvarez V, Coto E. Angiotensin-converting enzyme and angiotensin II receptor 1 polymorphisms: association with early coronary disease. Cardiovasc Res. 1998;40:375–379. doi: 10.1016/S0008-6363(98)00179-5. [DOI] [PubMed] [Google Scholar]
- 26.Mills M, Yang N, Weinberger R, Vander Woude DL, Beggs AH, Easteal S, North K. Differential expression of the actin-binding proteins, alpha-actinin-2 and -3, in different species: implications for the evolution of functional redundancy. Hum Mol Genet. 2001;10:1335–1346. doi: 10.1093/hmg/10.13.1335. [DOI] [PubMed] [Google Scholar]
- 27.Shanmugam V, Sell KW, Saha BK. Mistyping ACE heterozygotes. PCR Methods Appl. 1993;3:120–121. doi: 10.1101/gr.3.2.120. [DOI] [PubMed] [Google Scholar]
- 28.Pescatello LS, Kostek MA, Gordish-Dressman H, Thompson PD, Seip RL, Price TB, Angelopoulos TJ, Clarkson PM, Gordon PM, Moyna NM, Visich PS, Zoeller RF, Devaney JM, Hoffman EP. ACE ID genotype and the muscle strength and size response to unilateral resistance training. Med Sci Sports Exerc. 2006;38:1074–1081. doi: 10.1249/01.mss.0000222835.28273.80. [DOI] [PubMed] [Google Scholar]
- 29.Nikitin AG, Chistiakov DA, Minushkina LO, Zateyshchikov DA, Nosikov VV. Association of the CYBA, PPARGC1A, PPARG3, and PPARD gene variants with coronary artery disease and metabolic risk factors of coronary atherosclerosis in a Russian population. Heart Vessels. 2010;25:229–236. doi: 10.1007/s00380-009-1159-9. [DOI] [PubMed] [Google Scholar]
- 30.Jones A, Montgomery HE, Woods DR. Human performance: a role for the ACE genotype? Exerc Sport Sci Rev. 2002;30:184–190. doi: 10.1097/00003677-200210000-00008. [DOI] [PubMed] [Google Scholar]
- 31.Hopkinson NS, Nickol AH, Payne J, Hawe E, Man WD, Moxham J, Montgomery H, Polkey MI. Angiotensin converting enzyme genotype and strength in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2004;170:395–399. doi: 10.1164/rccm.200304-578OC. [DOI] [PubMed] [Google Scholar]
- 32.Vigano A, Trutschnigg B, Kilgour RD, Hamel N, Hornby L, Lucar E, Foulkes W, Tremblay ML, Morais JA. Relationship between angiotensin-converting enzyme gene polymorphism and body composition, functional performance, and blood biomarkers in advanced cancer patients. Clin Cancer Res. 2009;15:2442–2447. doi: 10.1158/1078-0432.CCR-08-1720. [DOI] [PubMed] [Google Scholar]
- 33.Costa AM, Silva AJ, Garrido ND, Louro H, de Oliveira RJ, Breitenfeld L. Association between ACE D allele and elite short distance swimming. Eur J Appl Physiol. 2009;106:785–790. doi: 10.1007/s00421-009-1080-z. [DOI] [PubMed] [Google Scholar]
- 34.McCauley T, Mastana SS, Hossack J, Macdonald M, Folland JP. Human angiotensin-converting enzyme I/D and alpha-actinin 3 R577X genotypes and muscle functional and contractile properties. Exp Physiol. 2009;94:81–89. doi: 10.1113/expphysiol.2008.043075. [DOI] [PubMed] [Google Scholar]
- 35.Moran CN, Vassilopoulos C, Tsiokanos A, Jamurtas AZ, Bailey ME, Montgomery HE, Wilson RH, Pitsiladis YP. The associations of ACE polymorphisms with physical, physiological and skill parameters in adolescents. Eur J Hum Genet. 2006;14:332–339. doi: 10.1038/sj.ejhg.5201550. [DOI] [PubMed] [Google Scholar]
- 36.Rodriguez-Romo G, Ruiz JR, Santiago C, Fiuza-Luces C, Gonzalez-Freire M, Gomez-Gallego F, Moran M, Lucia A. Does the ACE I/D polymorphism, alone or in combination with the ACTN3 R577X polymorphism, influence muscle power phenotypes in young, non-athletic adults? Eur J Appl Physiol. 2010;110:1099–1106. doi: 10.1007/s00421-010-1608-2. [DOI] [PubMed] [Google Scholar]
- 37.Clarkson PM, Devaney JM, Gordish-Dressman H, Thompson PD, Hubal MJ, Urso M, Price TB, Angelopoulos TJ, Gordon PM, Moyna NM, Pescatello LS, Visich PS, Zoeller RF, Seip RL, Hoffman EP. ACTN3 genotype is associated with increases in muscle strength in response to resistance training in women. J Appl Physiol. 2005;99:154–163. doi: 10.1152/japplphysiol.01139.2004. [DOI] [PubMed] [Google Scholar]
- 38.Walsh S, Liu D, Metter EJ, Ferrucci L, Roth SM. ACTN3 genotype is associated with muscle phenotypes in women across the adult age span. J Appl Physiol. 2008;105:1486–1491. doi: 10.1152/japplphysiol.90856.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Chiu LL, Wu YF, Tang MT, Yu HC, Hsieh LL, Hsieh SS. ACTN3 genotype and swimming performance in Taiwan. Int J Sports Med. 2011;32:476–480. doi: 10.1055/s-0030-1263115. [DOI] [PubMed] [Google Scholar]
- 40.Delmonico MJ, Kostek MC, Doldo NA, Hand BD, Walsh S, Conway JM, Carignan CR, Roth SM, Hurley BF. Alpha-actinin-3 (ACTN3) R577X polymorphism influences knee extensor peak power response to strength training in older men and women. J Gerontol A Biol Sci Med Sci. 2007;62:206–212. doi: 10.1093/gerona/62.2.206. [DOI] [PubMed] [Google Scholar]
- 41.Seto JT, Chan S, Turner N, Macarthur DG, Raftery JM, Berman YD, Quinlan KG, Cooney GJ, Head S, Yang N, North KN. The effect of alpha-actinin-3 deficiency on muscle aging. Exp Gerontol. 2011;46:292–302. doi: 10.1016/j.exger.2010.11.006. [DOI] [PubMed] [Google Scholar]
- 42.Williams AG, Folland JP. Similarity of polygenic profiles limits the potential for elite human physical performance. J Physiol. 2008;586:113–121. doi: 10.1113/jphysiol.2007.141887. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Sasaki H, Kasagi F, Yamada M, Fujita S. Grip strength predicts cause-specific mortality in middle-aged and elderly persons. Am J Med. 2007;120:337–342. doi: 10.1016/j.amjmed.2006.04.018. [DOI] [PubMed] [Google Scholar]
- 44.Ling CH, Taekema D, de Craen AJ, Gussekloo J, Westendorp RG, Maier AB. Handgrip strength and mortality in the oldest old population: the Leiden 85-plus study. CMAJ. 2010;182:429–435. doi: 10.1503/cmaj.091278. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Bohannon RW. Hand-grip dynamometry predicts future outcomes in aging adults. J Geriatr Phys Ther. 2008;31:3–10. doi: 10.1519/00139143-200831010-00002. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.