Acute response of biomarkers in plasma from capillary blood after a strenuous endurance exercise bout

Thirty-seven active young female and male adults were enrolled in this study (Table 1). All participants were at least 18 years of age and had no health impairments after medical examination. The study protocol complied with the Declaration of Helsinki, was approved by the local ethical committee (009/2021—Ethics Commission, German Sport University, Cologne), and fulfilled the international ethical standards (Harriss and Atkinson 2015). All participants signed an informed consent after receiving all relevant study information.

Using a pre-post design, subjects completed an incremental ramp test on a treadmill. At the beginning of the test procedure, a standardized 2-min warm-up was completed at low intensity (blood lactate < 2 mmol/L). VO_2max was determined via a ramp test to exhaustion on a treadmill (PPS Med treadmill, Woodway, Waukesha USA): start at 2.4 m/s followed by an increment from 0.2 m/s per 30 s to 4 m/s; thereafter 0.5% incline increment per 30 s. The VO_2max as well as the objective exhaustion of the athletes was verified according to the guidelines established by Midgley et al. (2007) for all participants. Fifteen minutes before and immediately after the VO_2max test, blood was taken. This sampling procedure is described in the following section. The first blood sample was taken after a 10-min rest period. Subsequently, each subject received an individualized fixed amount of carbohydrates (0.5 g maltodextrin/kg body mass) to ensure standardized conditions. This was to minimize interindividual variability in food intake in terms of time and content prior to the ramp test. In addition, all subjects were familiarized with the testing procedure before the start of the study and motivated in the same way at the end of the testing procedures. Participants were instructed to avoid any strenuous physical exertion two days prior to the diagnostic appointment and attended without having their regular breakfast.

3–5 ml venous blood samples were taken from a vein in the bend of the arm using S-serum monovettes. In addition, approximately 200 μL of capillary blood were taken from the earlobe by plasma microvettes. To achieve better blood supply, the earlobes were rubbed with a skin-warming gel (Finalgon—active ingredients nonivamide and nicoboxil). Venous samples were initially stored in an upright position for 15 min after sampling. This was followed by centrifugation at 2000 times gravity and 4 °C for 15 min to separate the blood into serum and cellular fractions. After the respective aliquoting of plasma and serum using a pipette, samples were quickly frozen at – 80 °C.

Plasma and serum levels of IL-1β (Analytical sensitivity (AS): 0.8 pg/mL; Coefficient of variation (CV): 2.3%), IL-1ra (AS: 18.0 pg/mL; CV: 2.1%), IL-6 (AS: 1.7 pg/mL; CV: 2.6%), IL-8 (AS: 1.8 pg/mL; CV: 1.8%), IL-17A (AS: 1.8 pg/mL; CV: 2.5%), IFN-y (AS: 0.4 pg/mL; CV: 2.8%), CCL-2 (AS: 9.9 pg/mL; CV: 1.4%), MMP-9 (AS: 13.6 pg/mL), SPARC (AS: 97.9 pg/mL), CD163 (AS: 530 pg/mL), S100A8 (AS: 15.3 pg/mL), S100A9 (AS: 6.39 pg/mL), S100B (AS: 4.34 pg/mL), BDNF (AS: 0.32 pg/mL), and MPO (AS: 26.2 pg/mL) were determined using a human Magnetic Luminex Assay (Bio-Techne, Abingdon, Oxon, UK) using a Magpix Luminex instrument with valid xMax technology (Luminex Corp, Austin, Texas, US) (Satterly et al. 2016). The Magnetic Luminex assays were pre-coated with analyte-specific antibodies on magnetic microparticles embedded with fluorophores in specific ratios for each individual microparticle region. 50 µL Microparticles, 50 µL standards and 50 µL samples were pipetted into the wells and the immobilized antibodies bound the analytes of interest. After incubation on a shaker for two hours and washing off all unbound substances, a biotinylated antibody cocktail of 50 µL was added to the analytes in each well. After another one-hour incubation and another wash to remove unbound biotinylated antibody, a streptavidin–phycoerythrin conjugate (streptavidin-PE) of 50 µL was added to each well to bind to the biotinylated antibody. Final washing after a 30-min incubation removed unbound streptavidin-PE, the microparticles were resuspended in 100 µL buffer and analyzed with the Magpix Luminex instrument.

All data are presented as group means ± standard deviation or with 95% confidence intervals. First, the data that fell out of the analytical range due to insufficient measurement sensitivity were omitted. After that the data were cleaned for outliers using z-transformation (z-score > 3 standard deviations) (Stocker and Steinke 2016). Accordingly, differentiated N-values were formed. Data were visually inspected for normal distribution and variance homogeneity. Further, the data were analyzed using the pairwise T test for normal distributed data and Wilcoxon-Test for non-normal distributed data. A p value of ≤ 0.05 was accepted as statistically significant. As the study corresponds to an exploratory approach, there was no multiple test adjustment of the α-error. Standardized mean differences (SMD; trivial: SMD <|0.2|; small: |0.2|≤ SMD <|0.5|; moderate: |0.5|≤ SMD <|0.8|; large SMD ≥|0.8|), effect size, and rank-biserial correlation (r; small: |0.1|≤ r <|0.3|; moderate: |0.3|≤ r <|0.5|; large r ≥|0.5|) as a measure of the pairwise effect size estimation were also calculated (Cohen 1988). The agreement between both blood withdrawal locations (venous vs. capillary) were analyzed by calculating the systematic bias (mean difference between devices) and the limits of agreement (LoA: 1.96*standard deviation of the difference between both devices), considering a 95% random error component (Atkinson and Nevill 1998) and plotting several Bland–Altman plots (Bland and Altman 1986). Intraclass correlation coefficients (ICC) were additionally calculated (Atkinson and Nevill 1998). ICC were rated as excellent (0.9–1), good (0.75–0.9), moderate (0.5–0.75) and poor (0–0.5) (Koo and Li 2016). A linear regression analyses was calculated to analyze associations based on the dependent venous blood values on the independent capillary blood values. Thereby, regression coefficient (B), standard error of regression coefficient (SEB), intercept, coefficient of determination (R), adjusted multiple coefficient of determination (R²), and significance level (p) are given (Cohen 1988). The statistical analyses were conducted using SPSS version 26 (IBM SPSS Statistics 26, IBM GmbH, Munich, Germany). The Bland–Altman plots were created using the logarithmised values for better comparability of the biomarkers (Prism 9, GraphPad Software, San Diego, CA, USA).

Significant increases during exercise in plasma concentrations were found for IL-1β (p = 0.022; d =  – 0.57; r = – 0.63), IL-6 (p < 0.001; d =  – 0.89; r =  – 0.89), IL-8 (p < 0.001; d =  – 0.98; SMD = 1.38), IL-17A (p = 0.006; d =  – 0.66; SMD = 0.63), IFN-y (p = 0.002; d =  – 0.61; r =  – 0.60), CCL-2 (p = 0.003; d =  – 0.55; SMD = 0.53), MMP-9 (p = 0.005; d =  – 0.50; SMD = 0.51), SPARC (p < 0.001; d =  – 0.93; SMD = 1.12), CD163 (p < 0.001; d =  – 0.80; SMD = 0.90), S100A9 (p < 0.001; d =  – 0.97; SMD = 1.54), S100B (p = 0.017; d =  – 0.67; SMD = 0.62), BDNF (p = 0.038; d =  – 1.35; SMD = 1.04), while no changes were detected in plasma levels of IL-1ra, MPO, and S100A8 (p > 0.05) (Fig. 1). The effects of exercise on markers in serum from venous blood can be found in Table 2.

Table 3 presents the intraclass correlations (ICCs) and 95% confidence intervals (CIs) depicting the agreement between the marker concentration in capillary plasma and venous serum. While IFN-y (post) showed a good ICC-value (ICC = 0.87), the ICCs of IL-1β, IL-8, IL-17A, CCL-2, MMP-9 (post), SPARC, and BDNF (post) can be classified as moderate (0.5–0.75; Table 3). For all other time points and parameters, ICCs were classified as poor (< 0.5; Table 3). Table 3 shows higher venous concentrations compared to capillary blood for negative bias, and higher capillary blood concentrations compared to venous blood for positive values. In general, IL-1ß, IL-8, IL-17A, CCL-2, MMP-9 (post), SPARC, and BNDF (post) show a good to moderate agreement for both compartments and results as valid markers. The regression data support these results, since for IFN-y, IL-1ß, IL-8, IL-17a, CCL-2, MMP-9 (post), and SPARC (Table 4) significant associations with results of maximum low adjusted coefficient of determination (R²) > 0.3 were shown. This indicates that the variance of the previously mentioned biomarker concentrations in capillary plasma can be predicted to 30–82% by the concentration of the markers in venous serum. BA plots showed acceptable LoA’s between the two compartments for IFN-y (post), IL-8, and IL-17A (Fig. 2). However, this doesn’t exclude the markers IL-1ß, CCL-2, MMP-9 (post) and SPARC in their validation, but in their practicability (Fig. 2). All other markers with a low agreement and a higher scattered distribution are not shown in Fig. 2.

These data confirm the assumption that, especially in the case of cytokines without clear reference values, an individual range must first be established for each athlete, also considering the blood collection site. At the same time, the collection procedure must be strongly standardized. Future studies should investigate the extent to which these ranges in capillary blood can then be used to monitor the stress-recovery cycles of athletes. This type of blood sampling is a much more user-friendly, especially for athletes. Future studies should further validate the marker concentrations in capillary plasma and perform time series analyses to account for the individuality of the exercise response of each marker. A clinical application of the analyses in capillary blood is also conceivable, for example when it comes to vulnerable patient groups in whom cytokines are to be measured as non-invasively as possible.