Why do I need a CK test? You may need a CK test if you have symptoms of a muscular disorder. What happens during a CK test?
Will I need to do anything to prepare for the test? You don't need any special preparations for a CK test.
Are there any risks to the test? What do the results mean? To get more information, your provider may order tests to check the levels of specific CK enzymes: If you have higher than normal CK-MM enzymes, it may mean you have a muscle injury or disease, such as muscular dystrophy or rhabdomyolis.
If you have higher than normal CK-MB enzymes, it may mean you have an inflammation of the heart muscle or are having or recently had a heart attack.
If you have higher than normal CK-BB enzymes, it may mean you have had a stroke or brain injury. Other conditions that can cause higher than normal CK levels include: Blood clots Infections Hormonal disorders, including disorders of the thyroid and adrenal glands Lengthy surgery Certain medicines Strenuous exercise If you have questions about your results, talk to your health care provider.
Is there anything else I need to know about a CK test? References Cedars-Sinai [Internet]. Los Angeles: Cedars-Sinai; c Neuromuscular Disorders; [cited June 12]; [about 2 screens]. The Nemours Foundation; c Your Muscles; [cited Jun 19]; [about 3 screens]. Washington D. Tests for Musculoskeletal Disorders; [updated Dec; cited Jun 12]; [about 2 screens].
Values for molecular parameters reported in the literature are usually given as mean and standard error. However, in the sloppy modeling framework, it is preferable to choose a normal distribution in log space [20] , [22] , [54].
A Gaussian distribution of logarithmic parameters has been proposed to be biologically plausible [55]. This forms a convenient way to deal with dimensionless positive quantities as parameter values [56]. If the standard error is small relative to the mean of the parameter, the shapes of the prior distributions become approximately normal see Figure 3.
Since standard errors for only nine of all 22 system parameters could be found, we chose the default value for the remaining parameters to be at the maximum of all values for parameters with known error. This maximum was the error of the parameter for the binary dissociation constant for creatine from Mi-CK K ib,Mi , and see Table 1.
In order to investigate the effect of altered default prior standard deviation on posterior parameter distributions and ensemble predictions, we performed several additional ensemble simulations with lower and higher default values.
Results of these simulations can be found in Text S1. The parameter describing MOM conductance for adenine nucleotides, PS mom,AdN , could not be reliably determined by experiments on the organellar level and was therefore not constrained by a prior. A first estimate of parameter values was determined by a least-squares fit to the data, using the cost function of equation 4. This initial best parameter estimate resulting from the optimization is used as the starting point for a walk through the parameter space using the Metropolis-Hastings algorithm.
Starting the random walk from the optimized set of parameters made the algorithm converge more quickly to the posterior distribution. We use the algorithm's implementation in SloppyCell to sample parameter sets with probability density proportional to. All scripts to reproduce the presented calculations can be found in Dataset S2. The correlation time of a parameter is defined as the time constant of its autocorrelation function. For our model, taking steps in the random walk is sufficient to obtain more than independent parameter sets.
The independent parameter sets in the ensemble provide the final estimate of the parameters, not only characterized by a mean but also by a standard deviation which reflects the spread of the estimation. For computational performance reasons, we calculated model simulations for parameter estimation and ensemble sampling with an ATP hydrolysis rate averaged over the cardiac cycle rather than the pulsatile pattern shown in Figure 8.
This reduced the time needed for calculations tremendously, making it feasible to do the ensemble calculations in several hours. However, to investigate the damping characteristics of the system, we use a pulsatile forcing function of ATP hydrolysis see Figure 8A [18]. To assess the differences in metabolite levels and fluxes caused by replacing the pulsatile function with a time-averaged continuous function, parameter sets were randomly drawn from all parameter sets tried in the Monte-Carlo random walk, to compare the values of model results between pulsatile and nonpulsatile simulations.
The variables most affected by the pulsatile approximation are R diff,PCr and t mito. The difference between pulsatile vs.
The difference between pulsatile and non-pulsatile model results for other variables is below 4. Patched SloppyCell Python library. This additional dataset consists of a patched version of the SloppyCell Python library, version 0.
The package is provided as a zip file. Detailed installation instructions can be found in the zip file. Model files and Python code. This zip file contains the model in SBML format and all Python scripts necessary to reproduce the results in this study. Ensemble predictions with different default prior standard deviations. This supplemental text reports the results of our analysis procedure when smaller or larger default prior standard deviations for parameters with unknown standard error are assumed.
Model analysis with additional microcompartment which couples CK to the adenine nucleotide translocator. In this supplemental text we present the results of the analysis of a computational model which implements substrate channeling between Mi-CK and ANT in a microcompartment, integrated with the data on mitochondrial response times used in this study.
We are very grateful to Ryan Gutenkunst for excellent advice on using the SloppyCell modeling environment and to Bernd Brandt for scientific advice and help with the computer cluster. We also thank Jaap Heringa for suggestions and comments on the manuscript. Performed the experiments: HH. Author Summary Creatine kinase CK has several functions in cellular energy metabolism. Introduction It is well established that creatine kinase CK catalyzes the reversible transfer of phosphate from ATP to creatine Cr : 1 However, how this biochemical function plays a role in cell functioning has been the subject of intense controversy [1].
Download: PPT. Figure 1. Scheme of model of the compartmentalized creatine kinase system. Results We employed experimental data from three scales: molecular kinetic parameters, organellar capacity parameters and whole organ dynamic response data. Figure 2. Fit by the model of measured response times to heart rate steps.
Parameter estimation Model parameters were estimated simultaneously to fit the t mito values for all conditions using a least-squares optimization procedure. Monte Carlo sampling of parameter sets Starting from the optimized parameter set see Table 1 , we sampled the parameter space to generate an ensemble of independent parameter sets using the Metropolis-Hastings algorithm.
Figure 3. Distributions of individual parameters in the ensemble generated by the Metropolis-Hastings algorithm. Figure 4. Prediction of energy transport from mitochondria to cytosol by PCr. Figure 5. Dependence of PCr diffusion flux on heart rate and mitochondrial membrane permeability to adenine nucleotides. Prediction of temporal energy buffering The results described above indicate that direct ATP transport is predominant in working heart muscle.
Figure 6. Fluctuations of metabolite concentrations and fluxes during the cardiac cycle at three levels of CK activity. The specific role of the mitochondrial CK isoform Transport of HEP by PCr from mitochondria to cytosol partially takes place via the circuit formed by both CK isoforms, but was predicted to be quantitatively not very important.
Figure 7. Ensemble predictions of metabolite concentration and flux oscillations during the cardiac cycle for selective CK isoform inhibition.
Discussion The relative importance of the different roles of the CK system in myocytes is still hotly debated [4]. Methods Computational model For our analysis, we employed a previously published computational model [18].
Figure 8. Pulsatile nature of energy production and consumption in the beating heart and the response to a step in heart rate. Sloppy ensemble modeling Almost all models in systems biology contain parameters that cannot be determined precisely. Experimental data Measured values of molecular model parameters and their provenance, extracted from the scientific literature, are listed in Table 1. Cost function Model parameters are fitted to experimental data using a modified Levenberg-Marquardt least-squares procedure in logarithmic parameter space, which is part of the SloppyCell modeling environment.
Determining prediction uncertainty: Ensemble simulations A first estimate of parameter values was determined by a least-squares fit to the data, using the cost function of equation 4. Supporting Information. Dataset S1. Dataset S2. Text S1. Text S2. Acknowledgments We are very grateful to Ryan Gutenkunst for excellent advice on using the SloppyCell modeling environment and to Bernd Brandt for scientific advice and help with the computer cluster.
References 1. PLoS Comput Biol. Am J Physiol C—C View Article Google Scholar 4. Greenhaff PL The creatine-phosphocreatine system: there's more than one song in its repertoire. J Physiol. Beard DA Modeling of oxygen transport and cellular energetics explains observations on in vivo cardiac energy metabolism. Vendelin M, Kongas O, Saks V Regulation of mitochondrial respiration in heart cells analyzed by reaction-diffusion model of energy transfer.
Am J Physiol Cell Physiol. Biochim Biophys Acta 81— View Article Google Scholar 8. Am J Physiol H—H View Article Google Scholar 9. Available: Gustafson LA, Van Beek JH Activation time of myocardial oxidative phosphorylation in creatine kinase and adenylate kinase knockout mice.
Aliev MK, Saks VA Compartmentalized energy transfer in cardiomyocytes: use of mathematical modeling for analysis of in vivo regulation of respiration. Biophys J. Acta Physiol Scand — View Article Google Scholar Mol Cell Biochem. Beard DA A biophysical model of the mitochondrial respiratory system and oxidative phosphorylation. Wu F, Beard DA Roles of the creatine kinase system and myoglobin in maintaining energetic state in the working heart.
BMC Syst Biol. Nature Precedings. Beek JHGM van Adenine nucleotide-creatine-phosphate module in myocardial metabolic system explains fast phase of dynamic regulation of oxidative phosphorylation.
Phys Biol. Stoner CD, Sirak HD Steady-state kinetics of the overall oxidative phosphorylation reaction in heart mitochondria. J Bioenerg Biomembr — Heineman FW, Balaban RS Phosphorus nuclear magnetic resonance analysis of transient changes of canine myocardial metabolism in vivo. J Clin Invest. J Biol Chem. Jacobus WE, Saks VA Creatine kinase of heart mitochondria: changes in its kinetic properties induced by coupling to oxidative phosphorylation. Arch Biochem Biophys — Circ Res.
Direct demonstration of compartmentation with the use of labeled precursors. Mol Cell Biochem 43— Vendelin M, Birkedal R Anisotropic diffusion of fluorescently labeled ATP in rat cardiomyocytes determined by raster image correlation spectroscopy.
Cardiac and skeletal muscles exhibit tissue-specific adaptation of the mitochondrial function. Lipskaya TY, Savchenko MS Once again about the functional coupling between mitochondrial creatine kinase and adenine nucleotide translocase. Biochemistry Moskow. Chance B The energy-linked reaction of calcium with mitochondria. FEBS Lett. Free Radic Res. Nat Med. Brewer GJ, Wallimann TW Protective effect of the energy precursor creatine against toxicity of glutamate and beta-amyloid in rat hippocampal neurons.
J Neurochem. J Neurosci. Amino acids. IET Syst Biol. Nucleic Acids Res. Beek JH van, Westerhof N Response time of mitochondrial oxygen consumption following stepwise changes in cardiac energy demand.
Adv Exp Med Biol — ATP levels never deplete to critical levels; this is because the sensitivity of ATP is set very high to guarantee that they never deplete, so a slight reduction in high ATP level triggers an early protective reaction.
This might be a component function in the overall action of fatigue to limit muscle activity or it could be a system that evolved prior to or in parallel with fatigue mechanisms. The AMPK mechanism of control involves phosphorylation of CK, and it may be that phosphorylation provides a signal to facilitate removal of CK from the cytosol see Figure 4.
Such a mechanism would explain the appearance of serum CK following physical exercise as opposed to structural damage arising from muscle trauma. Following muscle damaging exercise, CK levels continue to rise in the blood for hours or days see Figures 3 a — 3 c despite significant metabolic disruptions having ceased. The capacity for compromised muscle tissue to generate force is impaired [ 27 , 31 , 62 ]; therefore, measures are required to protect and facilitate the repair of muscle tissue.
In addition, other processes which disrupt the cell membrane, for example, inflammation, continue [ 63 ], allowing CK to exit the cell over time. This extended loss of CK may be associated with protective mechanisms, and a prolonged involvement of AMPK, allowing repair and restoration of muscle function.
Exercise-induced muscle disruption is known to produce insulin-like growth factor II IGF II in response to cell damage and is thought to stimulate satellite cells and hypertrophy. An association has been found between a polymorphism in the sarcomeric protein myosin light chain kinase and changes in blood CK, Mb, and isometric strength, in individuals with specific genetic variations in alleles of IGF II who experienced increased muscle disruption as a result of maximal isotonic eccentric contractions [ 64 ].
This suggests that these genome variations may lead to alterations in calcium handling and force effects during exercise, thereby influencing muscle disruption. This could explain the susceptibility of some individuals, who are otherwise healthy, to muscle disruption and exertional rhabdomyolysis [ 64 ] and the large intersubject variation in levels of serum CK found in many studies. Heled et al. A genetic association was found between a specific CK-MM genotype of the Ncol polymorphism with an augmented response to exercise.
Yamin et al. ACE genotypes may be involved in the excitation coupling process and influence the risk for developing rhabdomyolysis and, conversely, protection against exercise-induced muscle injury.
However, this effect may be more noticeable in previously sedentary individuals performing intense exercise [ 65 ]. Other studies featuring physically active subjects did not find a comparable association [ 7 ].
Intensive exercise initiates an immune response resulting in acute and delayed leukocytosis, featuring neutrophils predominantly. This delayed proinflammatory response may in part be related to the serum CK response observed after exercise-induced muscle damage, due to leucocytes infiltrating and destabilising the cell membrane during the process of repair.
This biphasic response has been noted in other studies [ 23 , 35 ] and may be related to the time line of inflammation. Exercise modality can affect the appearance of CK in blood serum. Training status may affect this time response.
Stepping exercise resulted in a CK serum increase in women at day 3, whereas, there was no significant increase in CK serum levels in men performing the same protocol see Figure 3 c. Pantoja et al. The duration of the ten-rep max for elbow flexion for each subject was recorded with a chronometer in order to standardise exercise in both land and water environments and induce the same energy-generating metabolic pathways.
Subjects executed as many maximal effort contractions as possible for each set performing three sets in both environments with two-minute rest between sets; each environment session land or water was separated by four weeks. A significant increase in serum CK was observed at 48 hours after exercise on land, and no significant change in baseline serum CK levels occurred in water. No further samples were taken after this time. The main mechanism hypothesised to have attenuated muscle damage in water was reduced eccentric contractions [ 70 ].
There are difficulties in comparing exercise intensity and work volume in land and water [ 71 , 72 ]. Standardisation of exercise between water and land is challenging due to the differing conditions in water compared to air resistance, temperature, and hydrostatic pressure. The significance of exercise modality on CK serum response appears to be related to the magnitude of eccentric contractions involved in the activity and the subsequent extent of muscle disruption. Greater muscle cell disturbance delays the appearance of a CK serum peak compared to less disruption.
This may be linked to the time course of inflammation; however, evidence in the literature supporting this theory remains unclear. The molecular mechanisms that result in CK release from muscle after mild exercise are unclear. More clarification could provide important information for athletes concerned about muscle hypertrophy, performance, and the importance of rest periods between periods of exercise.
Future studies should include an exploration of ethnic variations in CK response to exercise. In the absence of any mechanical muscle damage, it remains a question as to whether raised CK after exercise does represent a degree of actual muscle damage or some form of disruption in energy control processes or some other molecular reaction mechanism. Since muscle tissue cannot ignore brain centred nerve stimulations causing increase in both the number of motor units recruited and the frequency of motor unit stimulation, as well as creation of longer tetanic contractions, it would seem logical that muscle would have some mechanism of moderation to delay the final sanction of fatigue for as long as possible.
Although PCr resynthesis is greatly diminished during high-intensity exercise, AMPK may still be required to maintain the ratio. It is speculated here that the control involves expulsion of CK from the cytosol see Figure 3. If this is the case, then increased serum CK levels arising from normal physical exercise may be a consequence of normal metabolic activity rather than representative of physical damage to muscle. Such a system would not act in isolation but as part of a sophisticated process involving other regulatory functions in the muscle, and only when the full integrated system is understood will it be possible to explain the many anomalies associated with muscle action.
Unfortunately, it has not been possible from the available literature to extract more definitive evidence for this suggestion. The considerable variability across many studies makes interpretation more difficult, and it is clear that the lack of agreed guideline procedures and defined parameters for the conduct and evaluation of exercise-based experimental work in this area is a major barrier to the greater understanding of the influence of exercise on muscle and human health in general.
The establishment of an international committee on exercise-based experimental and laboratory protocols may be beneficial. Such a committee could provide leadership, clarity, and standardisation that would enable researchers to effectively answer related experimental questions.
The authors have no conflicts of interests that are directly relevant to the content of this paper. Baird et al. This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Special Issues. Baird , 1 Scott M. Graham, 1 Julien S. Baker, 1 and Gordon F. Academic Editor: H. Received 21 Jun Revised 06 Sep Accepted 28 Sep Published 11 Jan Abstract The appearance of creatine kinase CK in blood has been generally considered to be an indirect marker of muscle damage, particularly for diagnosis of medical conditions such as myocardial infarction, muscular dystrophy, and cerebral diseases.
Figure 1. Phosphocreatine PCr circuit showing the rephosphorylation of creatine Cr in mitochondria using ATP derived from oxidative phosphorylation oxid phos and subsequent use of mitochondrial PCr by cytosolic creatine kinase CK to resupply ATP for muscle activity, adapted from Saks [ 5 ]. Figure 2. Theoretical model of muscle damage and repair cycle reproduced from Kendall and Eston [ 11 ].
Figure 3. PRE refers to the baseline period before exercise. Days 1—4 represent the 4-day immobilization and days 5—9 are the recovery period. Reprinted from Sayers and Clarkson [ 4 ].
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