STROBE statement—Checklist of items that should be included in reports of observational studies.

STROBE statement—Checklist of items that should be included in reports of observational studies.</p

RT miRNA primers.

Discrepancies between the measurement of body mass index (BMI) and metabolic health status have been described for the onset of metabolic diseases. Studying novel biomarkers, some of which are associated with metabolic syndrome, can help us to understand the differences between metabolic health (MetH) and BMI. A group of 1469 young adults with pre-specified anthropometric and blood biochemical parameters were selected. Of these, 80 subjects were included in the downstream analysis that considered their BMI and MetH parameters for selection as follows: norm weight metabolically healthy (MHNW) or metabolically unhealthy (MUNW); overweight/obese metabolically healthy (MHOW) or metabolically unhealthy (MUOW). Our results showed for the first time the differences when the MetH status and the BMI are considered as global MetH statures. First, all the evaluated miRNAs presented a higher expression in the metabolically unhealthy group than the metabolically healthy group. The higher levels of leptin, IL-1b, IL-8, IL-17A, miR-221, miR-21, and miR-29 are directly associated with metabolic unhealthy and OW/OB phenotypes (MUOW group). In contrast, high levels of miR34 were detected only in the MUNW group. We found differences in the SIRT1-PGC1α pathway with increased levels of SIRT1+ cells and diminished mRNA levels of PGCa in the metabolically unhealthy compared to metabolically healthy subjects. Our results demonstrate that even when metabolic diseases are not apparent in young adult populations, MetH and BMI have a distinguishable phenotype print that signals the potential to develop major metabolic diseases.</div

Metabolic and anthropometric parameters.

Discrepancies between the measurement of body mass index (BMI) and metabolic health status have been described for the onset of metabolic diseases. Studying novel biomarkers, some of which are associated with metabolic syndrome, can help us to understand the differences between metabolic health (MetH) and BMI. A group of 1469 young adults with pre-specified anthropometric and blood biochemical parameters were selected. Of these, 80 subjects were included in the downstream analysis that considered their BMI and MetH parameters for selection as follows: norm weight metabolically healthy (MHNW) or metabolically unhealthy (MUNW); overweight/obese metabolically healthy (MHOW) or metabolically unhealthy (MUOW). Our results showed for the first time the differences when the MetH status and the BMI are considered as global MetH statures. First, all the evaluated miRNAs presented a higher expression in the metabolically unhealthy group than the metabolically healthy group. The higher levels of leptin, IL-1b, IL-8, IL-17A, miR-221, miR-21, and miR-29 are directly associated with metabolic unhealthy and OW/OB phenotypes (MUOW group). In contrast, high levels of miR34 were detected only in the MUNW group. We found differences in the SIRT1-PGC1α pathway with increased levels of SIRT1+ cells and diminished mRNA levels of PGCa in the metabolically unhealthy compared to metabolically healthy subjects. Our results demonstrate that even when metabolic diseases are not apparent in young adult populations, MetH and BMI have a distinguishable phenotype print that signals the potential to develop major metabolic diseases.</div

Circulating relative miRNA expression according to body mass index and metabolic health status.

Fold change of A) miR-221, B) miR-29a, C) mR-21 and D) miR-34a. The boxes represent medians and interquartile ranges. Data were analyzed using the Kruskal–Wallis and Dunn’s post hoc tests when significant values were obtained (*p < 0.05).</p

Regulation of gene expression of SIRT1 and PGC1-α.

Relative expression of SIRT1 in the globular blood fraction by ddPCR and flow cytometry. SIRT1 expression was analyzed based on BMI (A) and MetH (B). Boxes represent medians and interquartile ranges. Mann–Whitney U test; a significant value *p < 0.05 was observed. SIRT1 protein expression in blood samples and metabolic health (C) or BMI (E). D) Expression of SIRT1 and BMI of metabolically healthy and metabolically unhealthy subjects *p < 0.05. Relative expression of PGC1-α in the globular blood fraction by ddPCR. PGC1-α expression was analyzed based on BMI (F), and G) MetH. Boxes represent medians and interquartile ranges. Mann–Whitney U test; a significant value ***p<0.001 was observed. ChiP-qPCR analysis of PPAR-α with ADIPOQ (H) and PGC1-α (I) promoter regions. Bars represent medians and interquartile ranges, and data were analyzed using the Kruskal–Wallis test and Dunn’s post hoc test when significant values were obtained (*p < 0.05).</p

Statistical analysis for binary logistic regression related to BMI.

Statistical analysis for binary logistic regression related to BMI.</p

Circulating expression levels of miR-21 and miR-29a by sex.

A) Relative miR‐21 and B) miR-29a expression levels by sex and grouped by metabolic health status and BMI. Data were analyzed by the Kruskal–Wallis test and Mann–Whitney U test; a significant value (p (TIF)</p

miRNAs qPCR primers and probes.

Discrepancies between the measurement of body mass index (BMI) and metabolic health status have been described for the onset of metabolic diseases. Studying novel biomarkers, some of which are associated with metabolic syndrome, can help us to understand the differences between metabolic health (MetH) and BMI. A group of 1469 young adults with pre-specified anthropometric and blood biochemical parameters were selected. Of these, 80 subjects were included in the downstream analysis that considered their BMI and MetH parameters for selection as follows: norm weight metabolically healthy (MHNW) or metabolically unhealthy (MUNW); overweight/obese metabolically healthy (MHOW) or metabolically unhealthy (MUOW). Our results showed for the first time the differences when the MetH status and the BMI are considered as global MetH statures. First, all the evaluated miRNAs presented a higher expression in the metabolically unhealthy group than the metabolically healthy group. The higher levels of leptin, IL-1b, IL-8, IL-17A, miR-221, miR-21, and miR-29 are directly associated with metabolic unhealthy and OW/OB phenotypes (MUOW group). In contrast, high levels of miR34 were detected only in the MUNW group. We found differences in the SIRT1-PGC1α pathway with increased levels of SIRT1+ cells and diminished mRNA levels of PGCa in the metabolically unhealthy compared to metabolically healthy subjects. Our results demonstrate that even when metabolic diseases are not apparent in young adult populations, MetH and BMI have a distinguishable phenotype print that signals the potential to develop major metabolic diseases.</div

Circulating expression levels of miR-34a and miR-221 by sex.

A) Relative miR‐34a and B) miR-221 expression levels by sex and grouped by metabolic health status and BMI. Data were analyzed by the Kruskal–Wallis test and Mann–Whitney U test; a significant value (p (TIF)</p

Statistical analysis for binary logistic regression related to metabolic health.

Statistical analysis for binary logistic regression related to metabolic health.</p