4. Discussion
Our data demonstrate differential expression of multiple miRs in skeletal muscle tissue in response to a single submaximal bout of exercise.In comparison to preexisting literature data, we demonstrated significant downregulation of myomiRs miR-1(-3p), miR-133a-3p and -5p, -133b, and miR-499a-5p, as well as of miR-19b-3p, -27a-3p, 199a-3p and -5p, 378a-5p, and 497-5p, both in the microarray (Moreover, KEGG pathway analysis using the DIANA TarBase v7.0 database suggested involvement of several induced (miR-155-5p, miR-1126-5p, and miR-2110) and repressed (miR-10a-5p, miR-15a-5p, miR-27a-3p, miR-29c-3p, miR-30e-5p, miR-199a-3p, miR-199b-3p, miR-363-3p, and miR-660-5p) miRs in fatty acid metabolism and biosynthesis. This might lead to enhanced aerobic capacity and more efficient regeneration [Nevertheless, it is important to be aware of the fact that miRs form a complex network, with each miR targeting a multitude of genes and with each gene product being targeted by multiple miRs [We could demonstrate strong inter-individual variability with regard to skeletal muscle miR acute responses, suggesting that miRs might be suitable biomarkers for individual training adaptation. Indeed, for HIIT, we could detect correlations between miR-199a-3p acute responses and training-associated ΔV̇OIn conclusion, our data suggest that microarray-based prescreening of a small subset of samples, followed by qPCR validation in the entire cohort, might be a valuable instrument for establishing skeletal muscle miR patterns and their modulation by exercise. Firstly, comparison of microarray and qPCR data yielded 73.33% concordance of individual trends (upregulation versus downregulation) in the six subjects initially analyzed. Secondly, when microarray data for miRs with fold changes of 4.5 or more were validated by qPCR in the entire cohort (In addition, in the future, miR-based screening of subjects prior to starting a training regimen might be a means to predict training responses, specifically in clinical settings but also in competitive sports. In particular, such a prediction might be helpful in pre-identifying subjects for which an insufficient response to ‘standard’ training protocols is likely. These individuals might then directly be allocated to alternative, yet-to-be-defined and ‘non-standard’ training regimens, from which they might potentially benefit to a higher degree. 