Metabolic Fingerprint; The metabolic syndrome (MetS), a condition that involves cardiometabolic risk factors, such as visceral obesity, hyperglycemia, dyslipidemia, and hypertension, shows alarmingly increasing rates. MetS increases the risk of type 2 diabetes, cardiovascular disease, and all-cause mortality. Although the patho physiological mechanisms behind the manifestation of MetS are far from clear, insulin resistance appears as the most widely accept and unifying cause, as it affects many major metabolic pathways.
Exercise plays an important role in the prevention and treatment of MetS, as it exerts a beneficial effect on the associated risks. It takes a single bout of exercise to acutely improve the lipidemic profile, blood pressure, insulin sensitivity, glucose homeostasis, as well as immunological, vascular, and hemostatic functions. This means that the cardiometabolic benefits of exercise training could be greatly attributed to recent exercise.
Serum metabolic fingerprint
The majority of relevant studies have implemented continuous moderate intensity exercise (CME). Studies that have implemented different exercise modes, i.e., high-intensity interval exercise (HIIE); also resistance exercise (RE), have also reported improvements in insulin sensitivity and MetS risk factors.
Thus, this study focuses on investigating whether the serum metabolic fingerprint; which responds differently depending on the presence of MetS or the mode of exercise. More specifically, they compare the effects of a resting trial (REST) along with three fundamentally different exercise modes (HIIE, CME, and RE) on the serum metabolic fingerprints of sedentary, middle-aged men with or without MetS. Moreover, we compared the results in serum with previously published results from the same
study in urine.
This study investigated the alterations in the human serum metabolic fingerprint, due to the effect of three independent factors, that is, exercise mode, time after exercise, and the presence or not of MetS. A targeted UPLC-MS/MS analytical method, which identifies polar compounds, was use. As far as we know, this was the first time that the serum metabolic fingerprints of three fundamentally different exercise modes were compare.
The statistical analysis
Following both univariate (ANOVA) and multivariate (PLS-DA) statistical analysis; so they showe that time had the strongest differentiating effect on the metabolic fingerprints; so with exercise mode coming second. The largest changes were in the immediate post-exercise samples. Of the three exercise modes; so the greatest responses were due to RE; so while CME had minimal effect.
They have monitored the changes of 46 serum metabolites; so after acute bouts of three exercise modes in men with and without MetS, using a UPLC-MS/MS-based metabolomics approach. The differences found between exercise modes reflect differences in the predominant energy systems. The strongest response was seen after RE, followed by HIIE, while CME’s effect was weak.
Unlike in urine, where we have previously reported a diminish response to exercise in individuals with MetS; so no valid model could separate the two groups in serum. However, exercise exerted a beneficial effect on prominent serum biomarkers; so of metabolic risks, such as BCAA, alanine, acetylcarnitine, choline, and betaine. These results add to the ongoing research efforts to map the molecular responses to exercise and to optimize exercise guidelines for individuals at cardiometabolic risk.