An additional confounding factor is the controversy in miRNA nomenclature among studies. This situation is evident, for example, in light of the study of Uhlemann et al. (21), who used the nomenclature miR-133, without specifying whether they refer to miR-133a or miR-133b and with their respective -3p and -5p chains. The same situation occurs for cel-miR-39, which is commonly used for normalization purposes and for which no information about the -3p or -5p chains often is provided by most authors (Table 5).
Summarizing, together with the diverse approaches used by the different authors, it also is evident the heterogeneity of the results obtained. This situation raises doubts not only about the lack of coincidence in the response of certain miRNAs but also about the coincidences themselves. Therefore, the notion that the diverse methodological approaches are not responsible for the heterogeneous observed results cannot be excluded.
DIFFERENT METHODOLOGICAL APPROACHES AND EXPERIMENTAL DESIGNS: BEHIND THE SCENES
The results obtained in the different studies are hardly complementary or comparable, mainly due to huge differences in the methodologies used (detection technique, normalization strategy, and treatment of missing values), in the experimental design (timing of sampling and type and number of c-miRNAs analyzed), and in the characteristics of the participants (age, exercise background, dietary intake, and pathologic condition). Next, we analyze in detail potential confounding influences of these factors.
Methods of c-miRNA Analysis
Real-time quantitative polymerase chain reaction (RT-qPCR) has been the technique of choice by most authors who have analyzed c-miRNAs in response to exercise. However, this does not rule the technique out as a potential source of confusion between studies mainly because of the lack of information on the different approaches used for qPCR raw data processing, particularly cycle threshold, handling of missing data, and normalization strategy. Information on the first two is practically nonexistent in the literature as is the influence of dissociation and melting curve analysis on the final inclusion of amplified miRNAs (12–14,17,19,24,25). As expected, a variety of normalization strategies has been used by different authors, as summarized in Table 5, because no stable constitutive or exogenous miRNA or group of miRNAs have been established or validated for the normalization of miRNA expression in this context (11). Most authors have used cel-miR-39 for normalization; cel-miR-39 is a Caenorhabditis elegans miRNA that is added in equal quantities to all samples (11,15,17,18,20–22,24,26,27). Other authors have used specific software tools to detect which gene or group of genes are expressed more stably in their specific samples and use these genes for normalization (10,19). The amount of RNA extracted from serum or plasma samples is small and difficult to accurately quantify. Therefore, the amount of RNA that is initially added for miRNA detection will hardly be the same for all samples. Consequently, normalizing by an exogenous miRNA that is added in equal amounts in all samples or by an endogenous miRNA for which the raw expression is stable seem to be questionable options. A solid and common standardization strategy would be desirable, as proposed by Lee et al. (32). However, considering the limited and heterogeneous information about c-miRNAs in the context of exercise, this is not realistic nowadays. Carrying out a pilot study using different methods for data normalization, including synthetic miRNAs, endogenous miRNAs, and the mean expression of all analyzed miRNAs to identify the combination of normalizers that best suit the specific characteristics of each study would be desirable (33), and seems to be the best option at present. Unfortunately, this is not easy to achieve, and the confounding influence of data processing would persist.
Another important point is how miRNA levels are estimated from qPCR formulas. Although several models can be used, the literature describes two that are widely applied: the efficiency calibrated model (34) and the ΔΔCT model (35). How miRNA levels are analyzed using these formulas also might be relevant. Whereas absolute quantification uses an internal or external calibration curve to derive the input template copy number, relative quantification relies on the comparisons between expressions of target genes versus a reference gene (ΔCT) (36). Most studies of circulating miRNAs in response to exercise use relative quantification. However, the use of miRNAs as biomarkers will probably require the use of a quantitative value (i.e., copy number) to be used routinely in the clinical practice. Regarding the data quality control, most studies of miRNA expression in the field do not report the estimation of the amplification efficiency. Thus, the lack of proper quality control also could have a significant impact on the final data analysis (36).
Most authors have analyzed the circulating levels of a selection of one or a few miRNAs (typically between three and eight; Tables 1–4). In most cases, the selected miRNAs are among those that are enriched in skeletal muscle, i.e., the so-called myomiRs: miR-1, miR-133a, miR-133b, miR-206a, miR-208b, miR-486, and miR-499. Notably, very few authors have analyzed all myomiRs (7,12,14,19), and the selections considered in the remaining studies are not always the same. In addition, several authors have accompanied the analysis of myomiRs with a few other miRNAs that have previously been described as circulating markers of processes that are directly related to the response to exercise, such as inflammation or angiogenesis (8,18) (see Table, Supplemental Digital Content 1, http://links.lww.com/ESSR/A47). Furthermore, in studies with diseased people, miRNAs that are altered in a particular pathological situation or are related to metabolic pathways that are relevant to that condition also are frequently included (24,26). Limiting the analysis to a selection of miRNAs might provide an incomplete perspective of their holistic regulatory role, i.e., the systemic nature of the response to acute exercise and training. Surprisingly, few authors have addressed wider screenings of more than 100 miRNAs in this situation (12,14,15,17,19,20,28), and again, they have done so with a variety of approaches (Tables 1–4): whereas some authors have used microarray or commercial qPCR panels, others have opted for customized panels of a group of miRNAs that are related to some biological processes, such as inflammation or metabolism. Apart from the complex handling of data, one limitation of this type of approach is that all variables are considered equally (un)related to each other when performing the statistical analysis, although they are not really unrelated. In fact, most human miRNAs are located in clusters, so those miRNAs in the same cluster are coordinately regulated and expressed (37). Still, this constitutes an interesting approach because, as proposed by Nielsen et al. (19), the origin and fate of circulating miRNAs seem to be diverse and not restricted to skeletal or cardiac muscle.
In this sense, the tissue or cell type from which c-miRNAs originate and whether they are actively or passively released into the circulation have barely been studied. Most authors agree that plasma myomiR appearance in response to exercise is not a consequence of passive leakage from damaged skeletal or cardiac muscle because neither their plasma levels nor their kinetics correlate with those of classic markers of muscle damage, such as plasma creatine kinase concentration (7,9,16,18,21). However, it is unknown how miRNAs are secreted in response to exercise or if they can be incorporated into some tissues. The only study to date that has attempted to elucidate this issue in the context of exercise was published by Wahl et al. in 2016 (22) and focused on vascular miRNAs, such as miR-16, miR-21, and miR-126, not on myomiRs. Although the authors do not provide in vivo evidence of endothelial damage after exercise, they suggest in light of their in vitro results that these miRNAs can be passively released into circulation packed in microparticles because of the exercise-induced apoptosis of endothelial cells and that they act as intercellular communicators.
The active secretion of exosomes and other extracellular vesicles, such as microparticles and apoptotic bodies, has been recognized because of their possible role in intercellular communication (38). Exosomes are nanovesicles originated by inward budding inside an intracellular endosome, leading to the formation of a multivesicular body, which could then fuse with the plasma membrane releasing the internal vesicles (39). The presence of miRNAs in the exosomes exported by cells was first described in 2007 (40). Since then, very few studies have focused on the influence of exercise on the secretion of miRNAs transported by exosomes or other extracellular vesicles (41). Most studies have analyzed total plasma miRNA levels. Whether exosomal miRNAs contribute to the biological effects of exercise is completely unknown. It has been proposed that plasma miRNA and plasma-derived exosomal miRNA levels may not differ when evaluating healthy people (42). However, some studies suggest that they can be differentially regulated in disease conditions (43). Whether it also is the case for exercise activity — that is to say whether exercise condition regulates the exosomal miRNA profile — is poorly characterized. In this context, initial evidence suggests that acute aerobic exercise could influence the level of certain miRNAs in extracellular vesicles (41). Moreover, miRNAs encapsulated in extracellular vesicles seem to be more protected from degradation than those not encapsulated (44). Furthermore, whether the abundance of the miRNAs in body fluids reflects their abundance in cells or tissues is matter of debate. There are a number of publications that have suggested the existence of a selection mechanism for miRNA release and propose that the extracellular and cellular miRNA signatures differ (45). Indeed, the incorporation of miRNAs into exosomes is regulated by the presence of specific sequence motif overrepresented in miRNAs (46). Because the exposition to physiological and pathological stress may alter the miRNA content of the secreted vesicles (45), it seems that extracellular miRNAs could be biomarkers of the exercise response of the different tissues, more than surrogate biomarkers of miRNA tissue content.
Considering all of the aforementioned, the lack of coincidence in the results between studies could be partially due to the differences in the selected miRNAs, in the criteria used for this selection, and in the technical approaches used. Furthermore, deepening the study of the relation between circulating miRNA abundance and tissue content, as well as whether exercise-induced circulating miRNAs are encapsulated or not in extracellular vesicles, also could help in determining the search and use of circulating miRNAs as biomarkers or mediators of the systemic adaptations to exercise.
Exercise Models and Dietary Control
Another element of methodological divergence is the model of exercise performed by the volunteers. Most studies about acute exercise and training in health and disease consist of endurance aerobic exercise interventions (Tables 1–4), although the type, duration, and intensity of exercise varied between studies. Even in those studies in which the exercise model was the same, such as in those that have analyzed the acute response to a marathon, both the characteristics of the subjects (which we will analyze later) and the sampling points or dietary control differed between studies, which could influence the observed responses. Thus, in some cases, the baseline sample was drawn just before the start of the marathon (15,21), whereas in others, it was taken one (9), two (18), or even between 2 and 5 d before (11). In these cases, the observed differences in the expression of c-miRNAs between the baseline and the postexercise levels did not allow for the isolation of the effect of exercise because of many uncontrolled factors, particularly food and nutrient intake.
There is increasing evidence about the influence of dietary components in the expression of miRNAs and in the levels of c-miRNAs (47) as well as a new, intriguing, and controversial relation between the ingestion of miRNAs from food sources and their absorption, appearance in biological fluids, and intracellular regulatory role (48). Despite this, very few authors have considered monitoring food or nutrient intake (7,15,17,19,22), and only de Gonzalo-Calvo et al. (15) and Wahl et al. (22) have used strict control and recording of food intake before, during, and after exercise. Surprisingly, no study of diseased people has provided this information despite the fact that studies of metabolic disorders have been performed.
Characteristics of the Subjects
As previously mentioned, huge differences in the characteristics of the subjects included in the different studies are evident, particularly in relation to age and exercise background (Tables 1–4). For example, whereas in the study by Baggish et al. (8), the participants were young male university rowers aged 19.1 yr on average, Uhlemann et al. (21) recruited adult male runners aged 56.8 yr, and Gomes et al. (16) analyzed the acute c-miRNA response to a half marathon in obese and overweight amateur runners, some of whom had only 6 mo of regular exercise background. Thus, both factors could introduce one more element of variability that explains the heterogeneity in the results.
Almost all of the studies have been performed with men or with men and women considered together. Information about the specific response of c-miRNAs to exercise in women is lacking, and studies would be desired because sex-related differences in the circulating levels of certain miRNAs, such as miR-125a or miR-34a, have been described (49). Therefore, it is unclear if sex influences c-miRNA response to exercise.
There is not much information about the effect of age on the c-miRNA profiles of humans. Noren Hooten et al. (50) observed that the expressions of miR-151a-5p, miR-181a-5p, and miR-1248 are significantly suppressed in older (64 yr old) versus younger (30 yr old) men and women. Furthermore, Zhang et al. (51) suggested that the circulating profiles of miR-29b and miR-92a should gradually change with the aging process based on observations of the differences between subjects aged 22, 40, 59, and 70 yr. Regarding the response to exercise, in a pioneering study, Margolis et al. (17) observed that the acute response of c-miRNAs to resistance exercise differs between young (22 ± 1 yr) and old (74 ± 2 yr) male volunteers (Table 1). Therefore, differences in the ages of subjects could determine differences not only in the response to exercise but also in the baseline levels of some c-miRNAs, which introduces another confounding factor.
For their part, Baggish et al. (9) suggested that systematic training may be associated with elevated basal levels of c-miRNAs per se, particularly some myomiRs, as observed by Nielsen et al. (52) in skeletal muscle cells. This elevation could mask the effect of acute exercise on these c-miRNAs and explain why, in some studies with trained individuals, no changes in the circulating levels of myomiRs are reported.
CIRCULATING miRNAs AS BIOMARKERS OF EXERCISE RESPONSE?
Numerous studies have proposed the use of c-miRNAs as diagnostic, prognostic, and therapeutic biomarkers of numerous and diverse pathological processes (6). However, c-miRNAs also seem to be able to regulate various developmental and physiological processes (6). The potential of c-miRNAs as biomarkers lies in the fact that, on the one hand, they can be released into extracellular media, including blood, in response to cellular stress and damage, which would define specific profiles, and, on the other hand, they exhibit optimal biochemical and physiological properties to constitute excellent biomarkers (39).
Therefore, it is not surprising that, considering the aforementioned and the fact that c-miRNAs respond to exercise, they also have been proposed as biomarkers in the context of exercise (30,31). However, several questions should be addressed in this regard.
First, the commonly used concept of c-microRNAs as exercise biomarkers seems unclear. Alternative and more accurate expressions have been proposed by several authors, such as “biomarkers for exercise-related biological responses” (29) or simply “biomarkers of exercise response” (30), when referring to c-miRNAs as biomarkers of physical performance, physical fitness/capacity, training load, or exercise/training adaptations, response, and injury (29–31).
Furthermore, the National Institutes of Health working group (53) defined a biomarker as a biological marker that is objectively measured and evaluated as an indicator of normal biological processes, pathological processes, or pharmacological responses to therapeutic interventions. From a clinical point of view, it is widely accepted that a biomarker should be implicated in the pathophysiology of a given disease. This situation is recommended; nonetheless, biomarkers do not necessary need to be mediators in the causal pathway of the outcome of interest to be useful. Biomarkers could merely be bystanders passively associated with the outcome, although they should strongly correlate with the endpoints of interest and be accurately and reproducibly measured (54).
In this sense, some articles have demonstrated that both the baseline c-miRNA profile and the response of c-miRNAs to acute endurance exercise are related to aerobic fitness in healthy but not in diseased volunteers, which suggests a specific value as a biomarker in this context. Bye et al. (55) observed a differentiated baseline c-miRNA profile in middle-aged (40–45 yr) healthy male and female volunteers depending on their V[Combining Dot Above]O2max and demonstrated higher levels of miR-21 (only in men), miR-210, and miR-222 in those with low aerobic fitness. Similarly, Mooren et al. (18) found that the changes in the plasma concentrations of miR-1, miR-133a, and miR-206 in response to acute aerobic exercise (marathon) exhibited a strong correlation with classical aerobic performance parameters, such as V[Combining Dot Above]O2max and running speed at the individual lactate threshold. In addition, Clauss et al. (11) reported that the responses to acute exercise (marathon) of plasma miR-1, miR-26a, miR-29b, miR-30, and miR-133a are different in elite compared with amateur runners. In contrast, regarding patients of chronic obstructive pulmonary disease (COPD), heart failure, and chronic kidney disease (CKD), although differentiated basal miRNA profiles compared with healthy controls were observed, no correlation was found in performance in a 6-min walk distance (56), parameters of cardiopulmonary exercise testing (57), or peak oxygen consumption (V[Combining Dot Above]O2peak) (58). Finally, Wardle et al. (59) demonstrated that the type of exercise background modified the baseline levels of certain c-miRNAs because miR-21, miR-146a, miR-221, and miR-222 expression differed between strength and endurance athletes.
Other authors have described c-miRNAs as promising biomarkers of acute exercise load as considered in terms of type, dose, and intensity of exercise. Thus, using a randomized crossover design, Banzet et al. (10) described different profiles of several c-miRNAs in response to concentric versus eccentric exercise. Using a repeated-measures design, de Gonzalo-Calvo et al. (15) and Wahl et al. (22) observed that the number, type, and kinetics of the c-miRNAs analyzed significantly differed according to the dose (10-km running vs marathon) and the intensity (high-volume, high-intensity, and sprint-interval exercise protocols) of exercise, respectively. In contrast, Cui et al. (14) compared two classical and opposite protocols for improving endurance capacity, i.e., interval high-intensity and moderate continuous exercise, and these produced similar changes in the c-miRNA profile. Several other authors have separately found exercise load-related c-miRNA profiles in response to acute exercise in healthy volunteers (Table 1), also suggesting an effect of exercise load. However, we have only highlighted these articles because of their solid experimental designs: crossover or repeated measures. Establishing such comparisons between separate studies is problematic because of the previously mentioned huge differences in the experimental designs, the methodological approaches, and the subjects’ characteristics between studies or even between groups in the same study (21). A more complete overview of the methodology used and a stricter control of confusing factors may help comparisons between future studies (32).
Thus currently, the measurement of microRNAs is efficient, but it has not been demonstrated to be reproducible because of the plethora of uncontrolled and confusing elements, which weakens their current potential as biomarkers in the field of exercise. Therefore, observations of changes in the expression of c-miRNAs in response to exercise are not sufficient to define them as biomarkers.
An alternative that has barely been explored might be to analyze the response to exercise of extensive panels of miRNAs that have previously been described or validated as circulating biomarkers of physiological (coagulation, neurogenesis, inflammation, angiogenesis) or pathological (cardiac damage, endothelial dysfunction) processes related to exercise in crossover or repeated-measures designs.
Related and more important than their potential utility as biomarkers is the role of miRNAs as regulators of the molecular response to exercise (60). Most studies included in this review have a clear descriptive and associative character. Therefore, the origin, the form of transport, the quantitative amount released, and the tissue and gene targets of the c-miRNAs that respond to exercise remain to be known and validated. Additional studies using exercise animal models and in vitro approaches will provide insights to understand the extent and importance of their functional role in the molecular response to exercise and to determine their potential value as biomarkers in this context in health and performance applications, which for today is still unclear (Figure).
The studies available to date agree that both acute exercise and training modify the c-miRNA profiles of healthy and diseased volunteers. However, the low reproducibility of the results powerfully limited their usefulness as biomarkers in this context. The huge differences in methodology, in the experimental design, and in the characteristics of the participants, have strongly influenced the results obtained.
Instead of deepening the study of microRNAs as biomarkers, it seems to be a priority to study their regulatory role in the molecular response to acute exercise, as well as in recovery and adaptation in detail; such study will help to validate the use of c-miRNAs as biomarkers of exercise response.
The eventual validation of c-miRNAs as biomarkers in health and disease may allow for the development of more specific recommendations for the use of training as a therapeutic and preventive tool and for exploring the maximal limits of safe and healthy exercise. Understanding the role of exercise as a c-miRNA profile modulator also could set exercise as a valuable alternative or adjuvant to upcoming pharmacological and nutritional interventions based on miRNAs. However, we are still miles away from c-miRNAs being considered as validated biomarkers of exercise response in health and disease.
This study was supported in part by the Ministerio de Economía y Competitividad, Spain (DEP2012-39262 to EI-G and DEP2015-69980-P to BF-G).
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