Abstract
aims to improve aerobic capacity. During physical exertion, fluid shifts from intravascular to interstitial spaces, affecting potential
Pomeranian Medical University in Szczecin, 72 Powsta ´nców Wlkp. Al., 70-111 Szczecin, Poland; bartosz.wojciuk@pum.edu.pl 8 Department of Clinical Oncology, Pomeranian Medical University, 4 Arko ´nska St., 71-455 Szczecin, Poland; violetta.sulzyc.bielicka@pum.edu.pl *Correspondence: robert.nowak@usz.edu.pl † These authors share equal first authorship. Abstract Background: Endurance effort aims to improve aerobic capacity. During physical exertion, fluid shifts from intravascular to interstitial spaces, affecting potential conclusions from laboratory test results. The study aimed to assess the effects of endurance exercise on clinical interpretations of routine laboratory hematological and biochemical diagnostic tests.Methods: Participants were young, healthy, and physically active men aged 16–36 and women aged 16–29, who performed progressive treadmill tests to exhaustion. Blood samples were collected before the test, immediately after the test, and after 17 h of recovery. Results: The results showed that endurance exercise led to transient increases in the number of peripheral blood leukocytes and their subpopulations. A direct biological effect of endurance effort was an increase in the activity of amylase, AST, ALT, CK, GGT, LDH, and ALP, as well as in the concentration of creatinine, urea, uric acid, glucose, albumin, total protein, total cholesterol, HDL, triglycerides, sodium, chloride, phosphorus, and iron. Decreases in potassium and calcium (total and ionized) concentrations were also observed.Conclusions: The analyses clearly showed that laboratory tests performed in highly trained individuals may provide interpretation difficulties, and the reference ranges generally accepted in the healthy population might not apply to athletes. Keywords:physical effort; laboratory medicine; blood morphology; clinical biochemistry; exercise biochemistry J. Clin. Med.2025,14, 5703 https://doi.org/10.3390/jcm14165703
J. Clin. Med.2025,14, 5703 2 of 25 1. Introduction According to the Centers for Disease Control and Prevention (USA) and in the context of sports training, physical effort is a form of physical activity that is planned (usually by a professional) and repeated, the purpose of which is to improve and/or maintain physical fitness at a high level [1]. The World Health Organization has defined physical activity as a movement of the body produced by skeletal muscles. Therefore, this refers to any type of movement, not only including physical effort but also to everyday activities [2]. A physical exercise is a specific task performed to achieve physical activity or exertion. As a result of a physical exercise, a number of functional changes occur in the body whose size and nature depend on, for example, the level of training, the type of exercise, its intensity, or its duration [3–6]. Repeated endurance training leads to a number of adaptive changes at the cellular level. These mainly concern an increase in the number of mitochondria, resulting in an increased ability to produce ATP through increased oxidative phosphorylation. At rest, the reserves of ATP in muscles are small [7–9], but an increase and subsequent continuous supply of ATP is needed during exercise [9,10], regardless of whether this is to last for seconds or hours (h). Within 17 h after a physical exercise, there is an increase in the synthesis of alpha- aminolevulinic acid, considered to be the first symptom of enzymatic adaptation in response to physical exercise. With training, skeletal muscle hexokinase activity increases; the skeletal-muscle-specific isozyme of lactate dehydrogenase decreases, and the heart-muscle- specific isozyme increases in activity [11,12]. Muscle contractile activity during training increases muscle fiber plasticity and remodeling, allowing functional adaptation [10,13,14]. After endurance training, a general increase in mRNA expression in response to exercise facilitates the synthesis of some proteins, influencing muscle remodeling and adapting their structure to subsequent training loads [5]. For example, in human and rodent studies, moderate training causes a ~2×increase in HK II mRNA [12]. During molecular adaptive changes, there is a gradual increase in protein
[10,13,14]. After endurance training, a general increase in mRNA expression in response to exercise facilitates the synthesis of some proteins, influencing muscle remodeling and adapting their structure to subsequent training loads [5]. For example, in human and rodent studies, moderate training causes a ~2×increase in HK II mRNA [12]. During molecular adaptive changes, there is a gradual increase in protein and enzymatic activity. This is caused by the activation or repression of specific signaling pathways regulating transcription and translation and the expression of exercise-responsive genes, such as the regulatory genes of carbohydrate and lipid metabolism and their transport and oxidation, mitochondrial metabolism, and oxidative phosphorylation [15–17]. The result of these adaptive changes is to optimize the body’s performance in terms of fatigue resistance while maintaining homeostasis in the face of metabolic disturbances [11,18,19]. One of the many adaptive processes to repeated endurance exercise is an increase in plasma volume, perhaps to hypervolemia, at rest (which will partially counter the loss in volume during exercise). This is related to the balance between hydrostatic and osmotic forces, i.e., passive water movement and active transport of osmotically active substances. The movement of water between the interstitial and intravascular spaces depends on this balance between hydrostatic and oncotic pressure, with the latter mostly dependent on the plasma albumin concentration. Repeated endurance exercise increases plasma volume, often by 8–12%, mainly through plasma, with delayed red-cell mass gains. Due to the ability of this protein to affect osmotic pressure, changes in the albumin distribution between body compartments play a key role in changing plasma volume in training individuals [20–22]. Water and salt retention after exercise is also affected by increases in the activities of plasma renin and vasopressin [23]. Exercise increases capillary hydrostatic pressure and intramuscular osmolality (from metabolites like lactate, K + , and phosphate), leading to net filtration of plasma into the interstitial space. Elevated cardiac output also increases capillary permeability to proteins, promoting outward fluid shifts and resulting in hemoconcentration (~1 g hemoglobin per 100 mL). During physical exercise, the intramuscular metabolite content and extravascular
osmolality (from metabolites like lactate, K + , and phosphate), leading to net filtration of plasma into the interstitial space. Elevated cardiac output also increases capillary permeability to proteins, promoting outward fluid shifts and resulting in hemoconcentration (~1 g hemoglobin per 100 mL). During physical exercise, the intramuscular metabolite content and extravascular
J. Clin. Med.2025,14, 5703 3 of 25 osmolality increase, which, together with an increase in blood pressure and activation of the sympathetic nervous system, cause a fluid shift from the vascular space to the interstitial space, in proportion to protein and electrolyte concentrations [23–26]. This causes a decrease in plasma volume and the phenomenon of hemoconcentration [27,28]. During prolonged exercise of increasing intensity, both the metabolic rate and heat production increase, which also reduces the plasma volume during physical exercise [26,29]. Increasing the intensity of an exercise results in an increased loss of plasma volume [28,30]. Changes in blood biomarker concentrations caused by physical exercise can result from tissue stresses in response to physical activity and/or from hemoconcentration. Loss of plasma volume causes an increase in the concentration of circulating biomarkers regardless of their response to tissue stresses [30,31]. Therefore, it is essential to define the post- exercise loss of plasma volume to determine an adjusted effect of exercise on changes in the concentrations or activities of circulating biomarkers [32]. Response to physical exercise provides one component of biological variability, i.e., the physical changes can depend on the individual subjects. This biological variability depends on parameters such as sex, age, diet, stress, body characteristics, circadian rhythm, and lifestyle [33]. For this reason, laboratory test results in physically active people should be interpreted with great caution, and extrapolation to the general population might not be possible because results may deviate from accepted reference ranges as a result of these subjects’ adaptation to regular physical exercise or as a direct consequence of exercise. Similarly, changes might not apply to pathology, injury, or disease [32]. The body’s response to physical effort is related to the level of training. The same series of exercises will cause a different scale of changes in biochemical or hematological parameters in a fit athlete than in a person who leads a sedentary lifestyle [34]. Thus, in an untrained person, after a specific training load, an apparent change in the results of biomarker analysis might be visible. In contrast, in a person who regularly exercises, this might only be
will cause a different scale of changes in biochemical or hematological parameters in a fit athlete than in a person who leads a sedentary lifestyle [34]. Thus, in an untrained person, after a specific training load, an apparent change in the results of biomarker analysis might be visible. In contrast, in a person who regularly exercises, this might only be visible as a result of more intensive physical effort [35]. The present study has analyzed parameters from a group of young, healthy, trained people. These individuals, although not athletes, had been trained to a level at which the exercises they could perform could be dangerous to apply to people with a normally sedentary lifestyle. From the above, the reference ranges from a healthy population leading a sedentary lifestyle are difficult to translate to highly trained individuals or recreational athletes, and their application to competitive athletes may even be misleading [36]. However, knowledge about the dynamics of changes in biomarkers in the blood of highly trained people might allow for generalization to other highly trained individuals or athletes, preventing unnecessary additional tests and limiting the requirement for study tests during training and sports competitions. Additionally, this knowledge might be of use for clinicians who encounter such subjects. Information from the patient about the time that has passed since the last training before blood sampling and the frequency of training is necessary when interpreting laboratory test results to avoid misdiagnosis. Hence, this study aimed to assess the effects of endurance exercise on the clinical interpretation of routine laboratory hematological and biochemical diagnostic tests and especially (i) to try to distinguish the effects of hemoconcentration from tissue effects, especially in young men, and (ii) to provide further data to clinicians, including some data from women. The parameters included the following: metabolite concentrations: glucose, urea, creatinine, uric acid, and bilirubin (total and direct); albumin, total protein, and C-reactive protein; the lipid profile: triglycerides and cholesterol: total, high-density, and low-density lipoprotein concentrations; enzyme activities: aspartate and alanine aminotransferases, gamma-glutamyltransferase, alkaline phosphatase, creatine kinase, lactate dehydrogenase, and amylase; and selected ions.
from women. The parameters included the following: metabolite concentrations: glucose, urea, creatinine, uric acid, and bilirubin (total and direct); albumin, total protein, and C-reactive protein; the lipid profile: triglycerides and cholesterol: total, high-density, and low-density lipoprotein concentrations; enzyme activities: aspartate and alanine aminotransferases, gamma-glutamyltransferase, alkaline phosphatase, creatine kinase, lactate dehydrogenase, and amylase; and selected ions.
J. Clin. Med.2025,14, 5703 4 of 25 2. Materials and Methods 2.1. Participants In this study, 296 participants (234 men and 62 women) were recruited from team sports, from football and handball sports clubs. The participants included trained, young, healthy subjects of European descent. The exclusion criteria were metabolic syndrome, cardiovascular diseases, immunodeficiencies, and endocrinological-related diseases. Ad- ditionally, all participants were non-smokers and refrained from taking any medications or supplements known to affect metabolism. Physical fitness level was designated based on a participant’s declaration of weekly training volumes and training experience. The participants were familiar with the protocols of the exercises to be performed, and they took part in the experiment after two days of recovery from the effort. They (and their parents if appropriate) were fully informed of any risks and discomfort associated with the experimental procedures before giving their written consent to participate. The study was approved by the local Ethics Committee at the Regional Medical Chamber in Szczecin (approval no. 05/KB/VII2019) and followed the latest Declaration of Helsinki (2024). 2.2. Exercise Tests and Blood Sampling All participants performed the same progressive efficiency test on a mechanical tread- mill until exhaustion. The test was performed in the morning under laboratory conditions, two hours after a light breakfast and after two days of recovery, at a temperature of20–23 ◦ C . The proper test was preceded by a five-minute (min) warm-up run. During the proper test, the speed started at 5 km/h and was increased by 2 km/h every 3 min (min) of the test until exhaustion, meaning that the subject was unable to continue the run and had achieved that individual’s maximum fatigue. Further details have been previously described [37,38]. Blood samples were obtained three times from an elbow vein: 5 min before the exercise test (pre), no longer than 5 min after the exercise test (post), and about 17 h after the test, at the end of the recovery period (rec). It should be noted that, for safety reasons, the test protocol required the participant to have a light breakfast. Therefore, blood samples collected before (pre) and
elbow vein: 5 min before the exercise test (pre), no longer than 5 min after the exercise test (post), and about 17 h after the test, at the end of the recovery period (rec). It should be noted that, for safety reasons, the test protocol required the participant to have a light breakfast. Therefore, blood samples collected before (pre) and after (post) the test were not fasting blood, whereas the third (fasting) blood sample (rec) was drawn in the morning before breakfast. Each time, blood samples were drawn into two tubes: for serum preparation, a 7.5 mL S- Monovette tube with a clot activator (SARSTEDT AG & Co., Nümbrecht, Germany) was used, and for complete blood count and plasma preparation, a 9 mL S-Monovette tube with ethylenediaminetetraacetic acid (EDTA K3, 1.6 mg EDTA/mL blood; SARSTEDT) was used. Blood samples to obtain serum or plasma were centrifuged at 2000×gfor 10 min at room temperature. Biochemical and hematological analyses were performed immediately after blood collection. 2.3. Medical Laboratory Methods 2.3.1. Hematological Analyses Complete blood counts, including assessments of amounts of white blood cells (WBC), red blood cells (RBC), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentra- tion (MCHC), and total platelet levels (PLT), were obtained using a hematology analyzer ABX Micros 60 (Horiba ABX, Warsaw, Poland). 2.3.2. Biochemical Analyses Biochemical analyses were conducted for clinical chemistry variables (using an Auto Chemistry Analyser BM-100; BioMaxima, Lublin, Poland) or for ions (using an Ion Selec- tive Analyser BM ISE; BioMaxima). From blood plasma, the following parameters were
J. Clin. Med.2025,14, 5703 5 of 25 determined: metabolite concentrations of creatinine, uric acid, and bilirubin (total and direct); albumin, total protein, and C-reactive protein (CRP); the lipid profile: triglycerides (TG), cholesterol: total (TC), high-density (HDL-C or Ch-HDL), and low-density lipopro- tein (LDL-C or Ch-LDL) concentrations; enzyme activities: aspartate (AST) and alanine (ALT) aminotransferases, gamma-glutamyltransferase (GGTP), alkaline phosphatase (ALP), creatine kinase (CK), lactate dehydrogenase (LDH), and amylase. The serum was used for determining the concentrations of glucose, urea, and ions. All the studied variables were determined using diagnostic methods according to the appropriate manufacturer’s protocols (BioMaxima). All analyses were compared with a multiparametric panel of control sera, including control sera with normal levels (BioNorm) and with high levels (BioPath) (both from BioMaxima). 2.4. Calculations and Statistical Analyses Sera osmolalities were calculated using the mmol/L concentrations of Na + , glucose, and urea according to the following formula [39,40]: Total osmolality(mOsm/L)=2× fi Na + fl +[glucose]+[urea] Moreover, to compensate for changes in analyzed variables due to hemoconcentration, plasma volume loss (∆PV) was calculated according to the equation from Dill and Costill, provided by Alis et al. [27], as follows: ∆PV(%)=100× ȷ Hbpre Hbpost × 100−Htcpost 100−Htcpre −1 ff where Hbpre= hemoglobin pre-test (g/dL); Hbpost= hemoglobin post-test (or in recov- ery) (g/dL); Htcpre= hematocrit pre-test (%); and Htcpost= hematocrit post-test (or in recovery) (%). The formula for the correction of blood parameters was as follows [27]: [Corrected parameter concentration]=[Uncorrected parameter concentration]× ȷ 1+ ∆PV(%) 100 ff Statistical analyses were performed using Statistica (version 13, 2017; TIBCO, Palo Alto, CA, USA). The normality of the data distribution was assessed using the Shapiro–Wilk test. Since the data did not follow a normal distribution, non-parametric tests were used, and all data are presented as medians (interquartile range) except for age, which is presented as the median (minimum–maximum range). Changes between analyzed time points (baseline vs. post-effort vs. recovery) were assessed using Friedman’s analysis of variance for repeated measures, followed by post-hoc Dunn’s tests with Bonferroni correction. 3. Results To solve the scientific problem, young, trained, and healthy volunteers were recruited and performed the endurance effort
(interquartile range) except for age, which is presented as the median (minimum–maximum range). Changes between analyzed time points (baseline vs. post-effort vs. recovery) were assessed using Friedman’s analysis of variance for repeated measures, followed by post-hoc Dunn’s tests with Bonferroni correction. 3. Results To solve the scientific problem, young, trained, and healthy volunteers were recruited and performed the endurance effort on a mechanical treadmill until exhaustion. The blood samples for all analyzes were collected at three time points according to the study protocol presented in Figure. The general characteristics by sex of the participants are presented in Table. The most essential data are those for men (due to the larger number of participants). The data for women are provided mainly for comparison. There were no unexpected differences between the sexes.
Description
This study analyzes the impact of endurance exercise on laboratory parameters in young trained individuals.