CM-MM and ACE genotypes and physiological prediction of the creatine kinase response to exercise
Abstract
Exertional rhabdomyolysis (ERB) is a syndrome of severe skeletal muscle breakdown. Blood levels of creatine kinase (CK) are widely used as a marker to reflect muscle breakdown. Some individuals exhibit extreme increases in blood CK after exercise and have been characterized as high responders (HR), but no clinical definition of HR exists and reasons for the HR phenomenon are not understood. This study investigated possible associations between the magnitude of the CK response to exercise and polymorphisms of two genes: muscle-specific creatine kinase (CK-MM) NcoI and angiotensin-converting enzyme (ACE) I/D. An exercise test for defining HR was also investigated. Participants (n = 88) underwent an exercise test that included stepping up and down two stairs for 5 min followed by 15 squats while wearing a backpack weighted at 30% of their body weight. CK levels were measured before, immediately after, and 48 and 72 h after the test. Nine participants (10.2%) were defined as HR. Participants with the CK-MM NcoI AA genotype had a sixfold higher risk of being HR compared with GG and AG genotypes (P = 0.031). No significant differences were found for the ACE I/D polymorphism. Percent body fat was an independent predictor of being a HR. We conclude that the CK-MM AA genotype and percent body fat may be part of the constellation of mechanisms that explain susceptibility to ERB. A physiological test that may assist in predicting ERB is also presented.
exertional rhabdomyolysis (ERB) is a clinical syndrome of skeletal muscle destruction in response to exercise. In severe cases this syndrome may lead to kidney failure and even death (13, 34). This exertion-induced muscle injury results in the release of intracellular substances from affected myocytes [e.g., creatine kinase (CK), myoglobin, calcium, potassium] into the blood. The most widely used marker reflective of muscle breakdown is the enzyme CK (31). Some individuals exhibit extreme increases in CK in response to exercise and have been defined as high responders (HR) (22, 31, 34). A clinical or case definition for a HR compared with normal or low responder does not exist, and reasons for the HR phenomenon are unknown.
It has been suggested that genetics may be part of this phenomenon, but the important genes remain unclear (4, 34). One possibility is the gene encoding the enzyme CK. This enzyme, which is abundant in skeletal muscle, serves a key role in energy metabolism (7). One isozyme of CK, the muscle-specific CK (CK-MM), is localized at the M line and the sarcoplasmic reticulum of myofibrils (27, 32). CK-MM attempts to maintain energy homeostasis by providing a steady supply of creatine phosphate, which is critical for sustaining the Ca2+-ATPase of the sarcoplasmic reticulum and other energy-dependent enzymes (7). The CK-MM-encoding gene has been mapped to chromosome 19q13.2–13.3, and its structure has been extensively described (23).
Several lines of evidence suggest that the CK-MM-NcoI single-nucleotide polymorphism (SNP) in the 3′-untranslated region might contribute to individual differences in physical performance (2, 36, 38), but the mechanisms are unclear. Additionally, the CK-MM NcoI polymorphism might be associated with differential CK-MM activities in myocytes (25). Others have postulated that CK-MM genotype may be associated with the expression and stability of its mRNA (35, 38). Interestingly, the CK-MM gene is located in the same region on chromosome 19 as two other genes related to muscle function and specific myopathies: the myotonic dystrophy protein kinase (DMPK) (3) and the ryanodine receptor 1 (RYR1) (26). On the basis of these observations and the specific functions of the CK-MM enzyme (7), we hypothesized that different genotypes of the CK-MM NcoI polymorphism might be associated with differential CK responses to exercise.
Another polymorphism linked to physical performance is the gene encoding the angiotensin-converting enzyme (ACE) (8, 21). This gene has an insertion/deletion polymorphism that consists of a 287-base pair Alu repeat sequence in intron 16: the three genotypes are insertion (II), insertion/deletion (ID), and deletion (DD). Most studies have suggested that genotypes with the I allele are associated with better aerobic performance than the DD genotype (8, 20, 21); however, some have found no such association (24). The DD genotype has also been associated with lower physiological tolerance to exercise heat stress compared with the ID and II genotypes (10). Finally, it has been suggested that ACE genotypes might affect the metabolic efficiency of muscle during repeated contractions (38). Therefore, we also hypothesized that ACE I/D genotypes would reflect differential CK responses to standardized exercise.
To address our hypotheses, we implemented a short-duration, moderate-intensity exercise test to elicit changes in blood levels of CK. The overall objectives of the study were to 1) establish specific and statistically based criteria for normal and high CK responses to a standardized exercise test; 2) examine potential associations between the CK response to exercise and genotypes of the CK-MM NcoI polymorphism; and 3) examine the association between the CK response to exercise and genotypes of the ACE I/D polymorphism.
MATERIALS AND METHODS
Healthy, physically active volunteers (n = 88) participated in the study (60 men, and 28 women; 76 Caucasians and 12 non-Caucasians). The anthropometric and demographic characterizations of the participants are presented in Table 1. All participants gave informed consent before participation and went through a medical examination. The study was approved by the Institutional Review Board of the Uniformed Services University of the Health Sciences (USUHS).
Measure | Value |
---|---|
Age, yr | 29±6.7 |
Height, cm | 172±10.6 |
Weight, kg | 75.2±13.7 |
BMI, kg/m2 | 25.2±2.9 |
Body fat, % | 17.2±4.4 |
Experimental protocol.
Participants visited the Human Performance Laboratory on three occasions at ∼0900 in the morning. They were instructed to arrive having 1) had at least 6 h sleep; 2) not participated in any exercise for at least 72 h before they arrived; 3) had no coffee or nicotine since arising; and 4) consumed no alcohol for at least 24 h before their arrival. Participants were also instructed not to participate in any exercise over the 3 days following the exercise test. The first visit included an exercise test with blood draws before and after the exercise test, and the second and third visits (48 and 72 h later) only included blood draws.
On the first visit, participants underwent a medical examination and anthropometric measurements to include weight, height, and percent body fat. Percent body fat was calculated according to the mean of three skinfold-thickness measurements made with calipers at each of two sites (triceps and subscapular) (19). All measurements were performed by the same experienced researcher. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m2). Blood (20 ml) was drawn into EDTA-containing tubes from each subject for genetic and biochemical analyses. After being cleared by an on-site physician, participants underwent an exercise test that included stepping up and down two stairs (30-cm height each) for 5 min at a pace of 54 steps/min (using a metronome) followed by 15 knee bends completed within 1 min (3-s count down and 2-s count up were done to increase the eccentric contraction time). A backpack weighted at 30% of their body weight was worn during both tests. Immediately after the participant completed the exercise, another blood sample (20 ml) was obtained, and blood lactate level was measured. Heart rate was measured before and immediately after the step exercise to evaluate the participant's physiological effort. Heart rate was assessed using a wristwatch monitor linked to a coded chest transmitter (Polar). Two additional blood samples (20 ml each) were obtained at 48 and 72 h subsequent to the first visit.
Biochemical measurements.
Serum CK level was measured using a Vitros 250 Chemistry System (Ortho-Clinical Diagnostics, Johnson and Johnson, Rochester, NY). Blood lactate was measured using a hand-held lactate meter (Accutrend Lactate; Roche Diagnosis).
Blood samples, collected in EDTA-containing tubes, were separated by low-speed centrifugation, and plasma, buffy coat, and red blood cells were isolated. DNA was extracted from the buffy coat using a DNA extraction kit (QIAamp DNA mini kit 250; catalog no. 51306; Qiagen Sciences). The DNA concentration was calculated from absorbance measured at 260 nm, and purity was estimated by the ratio of absorbance at 260:280 nm using a spectrophotometer (model UV-2401PC; Shimadzu Scientific). The identification of specific polymorphisms in the CK and ACE genes were conducted using standard PCR techniques with specific primers to these genes.
To distinguish between the polymorphism within the CK-MM gene [National Center for Biotechnology Information (NCBI) accession no. NM_001824], we followed the protocol previously established to distinguish between two alleles, A and G (25). Briefly, PCR amplification was conducted to amplify 1,170-base pair (bp) DNA fragment localized in the gene followed by restriction digestion using the NcoI restriction endonuclease (New England Biolabs) to distinguish between the A and G alleles (NCBI rs no. 1803285). This DNA fragment was amplified using the specific primer pairs: 5′-GTGCGGTGGACACAGCTGCCG-3′ (forward) and 5′-CAGCTTGGTCAAAGACATTGAGG-3′ (reverse).
Each PCR reaction was contained in 50-μl reaction consisting of 300 ng genomic DNA, 1× buffer (includes 1.5 Mm MgCl2 and standard amounts of dNTPs), 300 ng sense primer, 300 nM antisense primer, and 3.75 U Expand Long Taq (Roche Diagnostics). The PCR conditions were as follows: initial denaturing at 95°C, 5 min; 30 cycles at 95°C for 30 s, at 62°C for 30 s, at 72°C for 45 s, and final extension at 72°C for 5 min. The PCR products were initially sequenced (Biomedical Instrumentation Center, USUHS) to confirm the specificity of the amplification product. Subsequently, 10 μl of the PCR reaction was digested using 5 U of the restriction enzyme NcoI in the appropriate buffer for 1 h at 37°C. Positive and negative controls were included in each restriction enzyme digestion with equal amounts of DNA in each parallel reaction to include 1) no DNA; 2) CK-MM amplicons not having the NcoI restriction site (G/G) (negative control); 3) CK-MM amplicons known to have the NcoI restriction site (A/A) (positive control); 4) CK-MM amplicons having the NcoI restriction site (A/A), but without including the enzyme NcoI in the reaction; and 5) unknown samples. The allele without the NcoI restriction site was designated as the G allele (1,170 bp), whereas the allele with the polymorphic NcoI site was designated as the A allele (985 bp + 185 bp). The resulting fragments of both the PCR products and the digestion process were resolved by electrophoresis in a 1.5% agarose gel stained with GelStar (Cambrex) and visualized under ultraviolet light.
To distinguish between the ACE I/D genotypes, PCR protocols previously established were used (17, 18). PCR was conducted in a manner similar to that described above using the specific primer pairs previously shown to amplify and distinguish the ACE I/D polymorphisms: 5′-TGGGACCACAGCGCCCGCCACTAC-3′ and 5′-CTGGAGACCACTCCCATCCTTTCT-3′.
Each PCR reaction was carried out in 50 μl consisting of 300 ng genomic DNA, 1× buffer (includes 1.5 mM MgCl2 and standard amounts of dNTPs), 300 nM sense primer, 300 nM antisense primer, and 3.75 U Expand Long Taq (Roche Diagnostics). The PCR conditions were as follows: initial denaturing at 95°C for 5 min; 36 cycles at 95°C for 1 min, at 58°C for 1 min, at 72°C for 1 min, and final extension at 72°C for 7 min. The resulting 190-bp fragment for the D allele and 490-bp fragment for the I allele were resolved by electrophoresis on a 2% agarose gel stained with GelStar (Cambrex) and visualized under ultraviolet light. The PCR products were initially sequenced (Biomedical Instrumentation Center, USUHS) to confirm the specificity of the amplification products.
Statistical analysis.
Data analyses were conducted using SAS version 9.01 (SAS Institute, Cary, NC). According to our preliminary results, and to maximize power to detect differences, a collapsing strategy was adopted in which the AA polymorphism in the CK-MM gene was compared with the G+ genotype (GG and GA), and the II polymorphism in the ACE gene was compared with the D+ (DD and ID) polymorphism. Distributions were considered for each of the variables with normality of continuous variables assessed using the Shapiro-Wilk test. Continuous variables were log transformed to base e before analysis where this improved approximation to a normal distribution. The difference between baseline CK and peak CK (at 48 or 72 h), or CKΔ, was considered the response following exposure. A HR was further defined as a CKΔ ≥ 90th percentile (i.e., no/yes) or 230 U/l, according to the definition for a “rare event” (37), and compared with normal responders (NR). Analysis of variance, Fisher's exact test, or Pearson correlations or Spearman's rank correlation coefficients were employed, where appropriate, to examine bivariate associations among genotypes, anthropometric, demographic, and physiological variables. Statistical significance was defined as P < 0.05 for a two-tailed test.
Significant bivariate associations between genetic polymorphisms and HR were further assessed using logistic regression models, ln {Pr(Y = 1)/[1 − Pr(Y = 1)]} = β0 + , where Y is a dichotomous random variable HR with 0 = no and 1 = yes; β0 represents the population average baseline odds for Y = 1; and βj{j = 1, … , k} represents a parameter describing the association between k random variables X (i.e., genotype and %body fat) and the logit (log transformed odds) of Y. The probability of being a HR, as a function of predictors included in the logistic model, is defined as Pr(Y = 1) = 1/{ 1 + exp[−(β0 + )]}. Furthermore, the conditional odds ratio for HR, an unbiased estimator of the relative risk under the aforementioned rare disease assumption, is defined as eβj.
Potential confounding variables, including baseline CK, age, BMI, percent body fat, ethnicity (i.e., Caucasian yes/no), and sex (i.e., female yes/no), were fit to simple logistic regression models, including genotype (i.e, AA/G+ or II/D+) as the only predictor of HR contingent on P < 0.05 for a bivariate association with either genotype or HR. These variables were retained in the logistic regression model only if inclusion elicited a ≥10% change in the magnitude of the genotype coefficient (12) and “stability” of the model was maintained. Results are presented as means ± SE unless marked otherwise.
The program PS Power and Sample Size Calculations version 2.1 were used to calculate power (5a). For the CK-MM gene, there was 67.0% power available to detect an odds ratio for HR equal to 6.0 (i.e., that observed in this study for AA vs. G+) at α = 0.05 for the GG vs. A+. An odds ratio of at least 8.0 would have been required for 80% power. For the ACE gene, there was 72.0% power available to detect an odds ratio of HR equal to 6.0 at α = 0.05 between DD and I+. An odds ratio of 7.3 would be detectable with 80% power. No II genotypes were found among the HR, and thus we were unable to estimate power for an analysis of II vs. D+ for HR vs. NR.
RESULTS
Of the 88 participants, nine (10.2%) were defined as HR according to our statistical criteria for increases in serum CK. The dynamics of serum CK in the HR and NR are presented in Fig. 1. The average increase in the serum CK (CKΔ) for the HR group was significantly higher compared with the NR group (1,048 ± 421 U/l compared with 12 ± 8 U/l, respectively; P < 0.0001). No significant differences between the two groups were found for baseline serum CK (HR, 161 ± 33 U/l; NR, 147 ± 13 U/l; P = 0.54); they were within the normal expected ranges.
Logistic regression analyses indicated that none of the anthropometric or demographic measurements (age, BMI, ethnicity, and sex) influenced the CK response. Mean values for the HR and NR groups are presented in Table 2. Body fat percentage was the only phenotypic measure that differed as a function of HR and NR: body fat was significantly higher in the HR (HR: 20.5 ± 1.6% vs. NR: 16.9 ± 0.6%, respectively; P = 0.03). No associations between the magnitude of the CK response and measures reflecting the participant's physical fitness (heart rate and lactate levels postexercise) were noted (Table 3).
Measure | HR (n = 9) | NR (n = 79) | P |
---|---|---|---|
Age, yr | 32.6±3.4 | 28.8±0.6 | NS |
BMI, kg/m2 | 26.1±3 | 25.4±0.4 | NS |
Body fat, % | 20.5±1.6 | 16.9±0.6 | P = 0.03 |
Caucasians, % | 77.8±15 | 87.3±3 | NS |
Females, % | 14.5±17 | 30.4±5 | NS |
Preexercise | Postexercise | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
HR (n = 9) | NR (n = 79) | P | HR (n = 9) | NR (n = 79) | P | |||||
Lactate, mmol/l | 1.8±0.8 | 1.5±0.7 | NS | 7.7±3.0 | 7.5±2.3 | NS | ||||
Heart rate, beats/min | 72±17 | 70±11 | NS | 170±11 | 170 ±14 | NS |
The allele frequencies of the CK-MM and the ACE gene polymorphisms were both distributed according to the Hardy-Weinberg equilibrium (CK-MM: AA 40%, AG 48%, GG 12% and ACE: DD 30%, ID 54%, II 16%). No differences in genotypes distributions were noted as a function of demographic measures (age, ethnicity, and sex) or physiological measures (heart rate or blood lactate) for either gene. Only 12 participants (14%) were not Caucasians, and these 12 were of diverse ethnicities.
The probability of being a HR was analyzed for both the CK-MM and ACE genes to examine possible associations between the CK response to exercise and genotype. For the CK-MM gene, the HR group had a significantly higher percentage of the AA genotype, and the NR group had a significantly higher percentage of the G+ genotype (HR vs. NR: AA 78% vs. 36%, and G+ 22% vs. 64%, respectively) (P < 0.05) (Fig. 2). Also, 19.4% of the participants with AA genotype were defined as HR compared with only 3.8% of the participants with G+ genotype (P = 0.028). The logistic regression model of HR on AA/G+ genotype (Table 4) yielded an odds ratio (eβj) indicating an approximately sixfold higher risk of being HR among participants with the AA genotype compared with participants with the G+ genotype. Although percent body fat was higher in the HR than NR, inclusion of body fat into the logistic regression model did not change the magnitude of the genetic influence.
Genotype | Β | SE (β) | χ2 | P | eβj | 95% CI |
---|---|---|---|---|---|---|
AA | 1.80 | 0.84 | 4.63 | 0.031 | 6.03 | 1.17–31.01 |
As for the ACE gene, no association between the CK response and the three genotypes was noted. However, none of the HR had the II genotype. Similarly, peak changes in serum CK levels were lower in the II (26 ± 21 U/l) compared with the D+ group (146 ± 66.8 U/l), but these results were not statistically significant.
DISCUSSION
ERB often occurs unexpectedly among military and athletic populations, with some individuals being more susceptible than others (14, 28). In most cases, ERB is caused by repetitive eccentric exercise that may impose both mechanical and metabolic stress on the muscle cells (6). The primary marker for muscle breakdown, serum CK, varies among individuals in response to exercise: a portion of the population has exaggerated increases in CK (4, 22, 28, 31). Nevertheless, no clinical or physiological criteria have been established to define HR. Reasons for an exaggerated response are not fully understood but may reflect genetics (4), fiber type, an underlying myopathy, and/or some other environmental/behavioral factors, including fitness level (6). Whether a high CK response to exercise implies greater susceptibility to ERB is unknown, but regardless, criteria to identify susceptible individuals are needed. We used the candidate gene approach to search for potential associations between the CK response to exercise and polymorphisms of two candidate genes; CK-MM NcoI and ACE I/D. To that end, we also used an exercise protocol that may be important in establishing criteria for defining normal and abnormal exercise-induced CK levels in physically active populations.
Importantly, our findings showed that the risk of having a high CK response to our exercise test is related to a specific CK-MM genotype of the NcoI polymorphism: participants with the AA genotype had a sixfold higher risk compared with those with the G+ polymorphism (GG and AG) for exhibiting an exaggerated CK response to exercise. Logistic regression modeling showed that the CK-MM polymorphism is independently associated with the CK response after adjusting for all of the measured phenotypic and demographic variables. Ethnicity and sex did not appear to influence the results; however, it should be emphasized that we did not have sufficient power to analyze by ethnicity. Despite clear differences in CK responses, HR and NR groups did not differ in their postexercise heart rate or blood lactate levels, which are known to be related to fitness level (11). These results imply that fitness level is not a confounder of our results, even though fitness may be associated with different degrees of muscle breakdown after exercise (5). A recent study of athletes who participated in a continuous 246-km running race did not find any association between the elevation in CK levels and performance (29). Thus fitness level may be a significant confounder with respect to CK increases, but only when comparing very active to sedentary individuals. Overall fitness may not be important when studying highly active individuals. Active individuals may, therefore, be the best group to study when phenotypic and physiological measurements are used as independent variables.
Previous studies found associations among humans between the CK-MM NcoI polymorphism and endurance performance (2, 3, 36, 38). However, to our knowledge, no one has shown an association between the CK-MM polymorphism and the CK response to exercise. Because the G allele is the rare allele for the CK-MM NcoI polymorphism, it is reasonable to speculate that this allele might be associated with a protective mechanism against exertional muscle breakdown, if one assumes that the CK response to exercise reflects the magnitude of muscle breakdown. Although our results may help explain the issue of HR in the normal population, the explanation is likely part of a more complex picture.
The mechanism by which the CK-MM polymorphism may influence the CK response to exercise is unknown. However, a few possible mechanisms can be offered. First, the CK-MM polymorphism examined in this study lies in the 3′-untranslated region, which influences the intracellular localization of its mRNA (38). This may affect the stability of the gene and its rate of transcription (35), which, in turn, could lead to differential expression of CK-MM and, possibly, alter muscle cell function (35). Such an event could therefore influence muscle integrity. The CK-MM NcoI polymorphism may also be associated with differential enzyme activities and be influenced by muscle fiber types (25). Enzyme activity and fiber typing measures were not obtained in the present study but may contribute to our findings. Another potential mechanism may be gene linkage. The location of the CK-MM gene (chromosome 19q13.2–13.3) is in the same region where the gene encoding for the myotonic dystrophy disease gene (DMPK) is located (19q13.3) (3). Indeed, although the results are not consistent (1), it has been suggested that the CK-MM gene may be a useful marker for myotonic dystrophy (3). The implications of this evidence and their possible association with our findings are unclear but strengthen the importance of this gene with regard to both normal and abnormal muscle function. Another potential genetic linkage is the RYR1 gene, which is also located in the same chromosome region (19q13.3) (26). Mutations in the RYR1 gene have been associated with susceptibility to malignant hyperthermia (MH), a hypermetabolic/hyperpyrexic skeletal muscle syndrome elicited by certain drugs used for anesthesia (15),(26). Moreover, the RyR1 gene has been associated with susceptibility to ERB (33). To our knowledge, susceptibility to increased muscle breakdown and associations between mutations in the RYR1 gene and the CK-MM polymorphism have not been studied. Nevertheless, the similar locations of the two genes, the possible association of the RYR1 gene with ERB, and our findings suggest a possible functional linkage that may influence muscle function during both mechanical work and metabolic stress.
Our interest in the ACE I/D polymorphism was based on reports in the literature (20, 21). The existence of the I allele (ID and II genotypes) has been associated with superior endurance performance (21), as well as with exercise heat tolerance compared with the DD genotype (10). The D allele has also been associated with clinical severity among individuals with McArdle's myopathy (myophosphorylase deficiency) (17). One suggested mechanism for these results is metabolic efficiency of the muscle during repeated contractions: different genotypes of the ACE polymorphism could directly influence metabolic efficiency (21): an increased metabolic efficiency during exercise might protect the muscle from prolonged mechanical tension and metabolic stress. Nevertheless, some have reported that the ACE I/D polymorphism has no influence on physical performance (24). In the present study, the ACE polymorphism was not significantly associated with the CK response to exercise. Nevertheless, despite a lack of statistical significance, it is important to note that no one in the HR group had the II genotype, and across the population, the II genotype was associated with lower levels of serum CK after our standardized exercise test compared with the DD and DI groups. These results are similar to previous studies showing a physiological advantage of the I allele (21). Additional participants would increase the power and perhaps the significance of these results in the future. Recent studies have shown that the degree of influence the ACE polymorphism may exert depends on the type of exercise and participant's fitness levels (16). Our findings, however, showed no association among the ACE genotypes and postexercise lactate level and/or heart rate, which suggests that fitness levels does not explain these findings.
Importantly, of all the demographic and anthropometric measures, only percent body fat differed between HR and NR groups. The exact explanation for this finding is unclear, but body fat may be part of a complex phenotypic and genotypic picture that predisposes certain individuals to high CK responses to exercise. For example, specific muscle fiber type profiles have been associated with obesity (30), and since the distribution of fiber types may also reflect skeletal muscle efficiency and performance (9), a circumstantial or indirect influence would be possible. Further studies will be required to address this issue.
The phenomenon of differential CK responses to exercise has been reported by a number of investigators (4, 14, 29, 31), but different exercise protocols have been used, to include long duration exercise (28) and isolated muscle group resistance workouts (4). Moreover, in some studies, CK levels after exercise were very high (22, 28). One of our purposes was to develop a simple, short-duration, and standardized test with minimum risk that would assist in defining normal and exaggerated CK responses. Importantly, we have described a standardized, scientific, and statistical approach for classifying persons as HR. We examined the distribution of responses for the population studied and used a statistical definition of a rare event (37) to classify individuals as HR for our specific exercise protocol. This approach resulted in assigning the label HR to an individual if his/her increase in serum CK over baseline at 48 or 72 h after exercise was greater than 230 U/l. Using this criterion, 9 of 88 subjects (10.2%) met the criteria for HR. Although this percentage within an active and healthy population may seem high, similar and even higher percentages have been found in previous laboratory controlled studies (22, 28, 31), as well as after selected athletic events (14, 29).
A few limitations of our study must be noted. First, our sample size was relatively small and homogeneous, at least in terms of age and fitness level. Second, our definition of HR was specific to our study population and exercise challenge test. Indeed, the clinical implications of the definition and the clinical specificity and sensitivity of the test still need to be ascertained within a larger sample. Third, most of our participants (86%) were Caucasians, and the distribution of CK-MM (38) and ACE (18) polymorphisms may differ by ethnicity. As such, these results may not apply to other ethnic groups. Finally, it should also be emphasized that the exercise protocol used in the present study was developed for active populations, such as athletes and soldiers, which may explain the relatively small increases in CK levels after exercise compared with other findings (22, 28). Along those same lines, our results may also be specific to the exercise protocol that we used, which was short in duration, moderately intense, and primarily anaerobic in nature (as noted by the postexercise lactate levels). Although our definition of HR has strong statistical support, we realize that more data will be required to define the true thresholds for low, normal, and high responders in larger populations.
In summary, we developed a simple exercise test and suggested possible criteria that may assist in defining high vs. normal CK responses to exercise. We also found that one genotype of the CK-MM NcoI polymorphism was associated with the risk of having an exaggerated CK response to exercise. Whether these data will allow us to identify individuals who are susceptible to muscle breakdown during exercise remains to be determined. Likewise, persons with exaggerated CK responses had a higher percent body fat than those with low CK responses. However, we cannot conclude that this makes them more susceptible to muscle breakdown during exercise, but body composition may be one of multiple phenotypic variables that make some individual susceptible to ERB. Despite the fact that we did not find any significant difference or associations with the ACE gene, the role of the I/D polymorphism in the ACE gene has not yet been ruled out: a larger sample size will be required to verify these results.
GRANTS
This study was funded by Uniformed Services University of the Health Sciences Grant RO91CE. The statistical analysis was funded by the Division of Epidemiology, Statistics, and Prevention Research, National Institute of Child Health and Human Development, Bethesda, Maryland.
FOOTNOTES
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
The opinions and assertions expressed herein are those of the authors and should not be construed as reflecting those of the Uniformed Services University of the Health Sciences or the U.S. Department of Defense.
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