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Background: To date, microRNAs (miRs) carried in extracellular vesicles (EVs) in response to exercise have been studied in blood but not in non-invasively collectable body fluids. In the present study, we examined whether six exercise-responsive miRs, miRs-21,-26,-126,-146,-221, and-222, respond to acute endurance exercise stimuli of different intensities in sweat. Methods: We investigated the response of miRs isolated from sweat and serum EVs to three endurance exercise protocols: (1) maximal aerobic capacity (VO 2max), (2) anaerobic threshold (AnaT), and (3) aerobic threshold (AerT) tests. Sauna bathing was used as a control test to induce sweating through increased body temperature in the absence of exercise. All protocols were performed by the same subjects (n = 8, three males and five females). The occurrence of different miR carriers in sweat and serum was investigated via EV markers (CD9, CD63, and TSG101), an miR-carrier protein (AGO2), and an HDL-particle marker (APOA1) with Western blot. Correlations between miRs in sweat and serum (post-sample) were examined. Results: Of the studied miR carrier markers, sweat EV fractions expressed CD63 and, very weakly, APOA1, while the serum EV fraction expressed all the studied markers. In sweat EVs, miR-21 level increased after AerT and miR-26 after all the endurance exercise tests compared with the Sauna (p < 0.050). miR-146 after AnaT correlated to sweat and serum EV samples (r = 0.881, p = 0.004). Conclusion: Our preliminary study is the first to show that, in addition to serum, sweat EVs carry miRs. Interestingly, we observed that miRs-21 and-26 in sweat EVs respond to endurance exercise of different intensities. Our data further confirmed that miR responses to endurance exercise in sweat and serum were triggered by exercise and not by increased body temperature. Our results highlight that sweat possesses a unique miR carrier content that should be taken into account when planning analyses from sweat as a substitute for serum.

IMPORTANCEModerate-to-vigorous physical activity (MVPA) in old age is an important indicator of good health and functional capacity enabling independent living.OBJECTIVETo investigate whether physical activity and other health habits at ages 31-48 years predict objectively measured MVPA decades later.DESIGN, SETTING, AND PARTICIPANTSThis prospective twin cohort study in Finland comprised 616 individuals (197 complete twin pairs, including 91 monozygotic pairs, born 1940-1944), who responded to baseline questionnaires in 1975, 1981, and 1990, and participated in accelerometer monitoring at follow-up (mean age, 73 years).EXPOSURESPrimary exposure was long-term leisure-time physical activity, 1975-1990 (LT-mMET index). Covariates were body mass index (BMI), work-related physical activity, smoking, heavy alcohol use and health status in 1990, and socioeconomic status.MAIN OUTCOMES AND MEASURESPhysical activity was measured with a waist-worn triaxial accelerometer (at least 10 hours per day for at least 4 days) to obtain daily mean MVPA values.RESULTSHigh baseline LT-mMET index predicted higher amounts of MVPA (increase in R2 of 6.9% after age and sex adjustment, P<.001) at follow-up. After addition of BMI to the regression model, the R2 value of the whole multivariate model was 17.2%, and with further addition of baseline smoking, socioeconomic status, and health status, the R2 increased to 20.3%. In pairwise analyses, differences in MVPA amount were seen only among twin pairs who were discordant at baseline for smoking (n=40 pairs, median follow-up MVPA 25 vs. 35 min, P=.037) or for health status (n=69 pairs, 30 vs. 44 min, P=.014). For smoking, the difference in MVPA also was seen for monozygotic pairs, but for health status, it was seen only for dizygotic pairs. Mediation analysis showed that shared genetic factors explained 82% of the correlation between LT-mMET and MVPA.CONCLUSIONS AND RELEVANCELow leisure-time physical activity at younger age, overweight, smoking, low socioeconomic status, and health problems predicted low MVPA in old age in individual-based analyses. However, based on the pairwise analyses and quantitative trait modeling, genetic factors and smoking seem to be important determinants of later-life MVPA.

Introduction. High physical activity (PA) at old age indicates good functional capacity enabling independent living. We investigated how different disease conditions are associated with measured PA indicators in old women and men, and whether they recognize this association. Materials and methods. This cross-sectional twin cohort study in Finland comprised 779 individuals (276 complete twin pairs, including 117 monozygotic pairs), who participated in hip-worn accelerometer monitoring of PA and responded to questions on diseases and mobility limitations at mean age of 73 (range 71 to 75). Results. Of the participants, 23.2% reported having a disease restricting mobility. With sex and age in the regression model, the reported disease restricting mobility explained 11.8% of the variation in moderate-to-vigorous PA and 10.4% of the variation in daily steps. Adding stepwise other self-reported diseases and body-mass index to the model increased the explanatory power for moderate-to-vigorous PA up to 18.5% and 25.5%, and for daily steps up to 16.0% and 20.7%, respectively. In the co-twin control analysis the PA differences were smaller in disease-discordant monozygotic than dizygotic pairs. Conclusions. Chronic disease conditions are associated with low PA, which individuals may not always recognize. Shared genetic factors may explain part of the associations.

Moderate-to-vigorous physical activity (MVPA) in old age is an important indicator of good health and functional capacity enabling independent living. In our prospective twin cohort study with 616 individuals we investigated whether long-term physical activity assessed three times, in 1975, 1982 and 1990 (mean age 48 years in 1990), and other self-reported health habits predict objectively measured MVPA measured with a hip-worn triaxial accelerometer (at least 10 hours per day for at least 4 days) 25 years later (mean age of 73 years). Low leisure-time physical activity at younger age, higher relative weight, smoking, low socioeconomic status, and health problems predicted low MVPA in old age in individual-based analyses (altogether explaining 20.3% of the variation in MVPA). However, quantitative trait modeling indicated that shared genetic factors explained 82% of the correlation between baseline and follow-up physical activity. Pairwise analyses within monozygotic twin pairs showed that only baseline smoking was a statistically significant predictor of later-life MVPA. The results imply that younger-age physical activity is associated with later-life MVPA, but shared genetic factors underlies this association. Of the other predictors mid-life smoking predicted less physical activity at older age independent of genetic factors.