Top-level performances in endurance sports require several years of hard training loads. A major objective of this endurance training is to reach the most elevated metabolic adaptations the athlete will be able to support. As a consequence, overtraining is a recurrent problem that highly-trained athletes may experience during their career. Many studies have revealed that overtraining could be highlighted by various biochemical markers but a principal discrepancy in the diagnosis of overtraining stems from the fact that none of these markers may be considered as universal. In endurance sports, the metabolic aspects of training fatigue appear to be the most relevant parameters that may characterise overtraining when recovery is not sufficient, or when dietary habits do not allow an optimal replenishment of substrate stores. From the skeletal muscle functions to the overall energetic substrate availability during exercise, six metabolic schemes have been studied in relation to overtraining, each one related to a central parameter, i.e. carbohydrates, branched-chain amino acids, glutamine, polyunsaturated fatty acids, leptin, and proteins. We summarise the current knowledge on these metabolic hypotheses regarding the occurrence of overtraining in endurance sports.
Recent studies have shown that endurance overtraining could result from successive and cumulative alterations in metabolism, which become chronic during training. The onset of this process is a biochemical alteration in carbohydrate (saccharide) metabolism. During endurance exercises, the amount of saccharide chains from two blood glycoproteins (alpha(2)-macroglobulin and alpha(1)-acid glycoprotein) was found to have decreased, i.e. concentrations of these proteins remained unchanged but their quality changed. These saccharide chains were probably used for burning liver glycogen stores during exercise. This step was followed by alterations in lipid metabolism. The most relevant aspect of this step was that the mean chain length of blood fatty acids decreased, i.e. the same amount of fatty acids were found within the blood, but overtrained individuals presented shorter fatty acids than well-trained individuals. This suggests that alterations appeared in the liver synthesis of long-chain fatty acids or that higher peroxidation of blood lipoparticles occurred. For the final step of this overtraining process, it was found that these dysfunctions in carbohydrate/lipid metabolism led to the higher use of amino acids, which probably resulted from protein catabolism. The evolution of three protein concentrations (alpha(1)-acid glycoprotein, alpha(2)-macroglobulin and IgG(3)) correlated with this amino acid concentration increase, suggesting a specific catabolism of these proteins. At this time only, overtraining was clinically diagnosed through conventional symptoms. Therefore, this process described successive alterations in exercise metabolism that shifted from the main energetic stores of exercise (carbohydrates and lipids) towards molecular pools (proteins) normally not substantially used for the energetic supply of skeletal muscles. Now, a general biochemical model of the overtraining process may be proposed which includes most of the previously identified metabolic hypotheses.
Seventeen type I male diabetic adolescents and 17 control subjects matched for age, height, and weight were submitted to maximal exercise on a bicycle ergometer. The diabetic subjects were divided into two groups according to their degree of metabolic control using total glycosylated hemoglobin (HbA1): group 1, diabetics with HbA1 less than 8.5% (n = 9) and group 2, diabetics with HbA1 greater than 8.5% (n = 8). Oxygen uptake, pulmonary ventilation, and heart rate were recorded at rest and at maximal load. Glucose, lactate, and free fatty acids were determined in blood before and after exercise. Maximal work load and oxygen uptake were significantly lower in the two diabetic groups than in the healthy controls. An inverse relationship was observed between HbA1 concentration and the maximal work load (r = -0.63; P less than 0.01). It can be concluded that diabetic adolescents should obtain the best possible degree of metabolic control to improve their performances.
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