Dataset Information

Serum miR-503 is a Candidate Biomarker for Differentiating Metabolic Healthy Obesity from Metabolic Unhealthy Obesity.

ABSTRACT: Purpose:Overweight and obesity are associated with metabolic diseases. However, a subgroup of the overweight/obese population does not present metabolic abnormalities. Hence, there is an urgent need to identify biomarkers that can distinguish different obesity phenotypes and metabolic status. Patients and Methods:A total of 98 individuals were divided into three groups: metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). Participants were evaluated for anthropometric and biochemical parameters and serum BMPR1A concentration and miR-503 level. Receiver operating characteristic (ROC) curve analysis and logistic regression analysis were performed. Results:The level of miR-503 was significantly higher in the MHO group compared with that in the MUO group, but no difference was observed between the MHNW and MHO groups. Meanwhile, no significant differences in serum BMPR1A concentration were observed between the three groups. ROC curve analysis showed that miR-503 could be used as a marker to distinguish the MUO from the MHO. Logistic regression analysis suggested that miR-503 was an important related factor associated with an unhealthy metabolic state in overweight/obese subjects. Conclusion:miR-503 can be considered as a suitable biomarker to distinguish between the MUO and MHO, which may be a related factor for the incidence of metabolic disorders in overweight/obese subjects.

SUBMITTER: Yue HQ

PROVIDER: S-EPMC7419640 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Serum miR-503 is a Candidate Biomarker for Differentiating Metabolic Healthy Obesity from Metabolic Unhealthy Obesity.

Yue Hai-Qing HQ Zhou Ying-Hui YH Guo Yue Y Tang Chen-Yi CY Wang Fang F Zhou Hou-De HD

Diabetes, metabolic syndrome and obesity : targets and therapy 20200727

<h4>Purpose</h4>Overweight and obesity are associated with metabolic diseases. However, a subgroup of the overweight/obese population does not present metabolic abnormalities. Hence, there is an urgent need to identify biomarkers that can distinguish different obesity phenotypes and metabolic status.<h4>Patients and methods</h4>A total of 98 individuals were divided into three groups: metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), and metabolically unhealthy obese ...[more]

PMID: 32821139

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Project description:Background and aims: Youth populations with overweight/obesity (OW/OB) exhibit heterogeneity in cardiometabolic health phenotypes (e.g. fasting glucose, serum triglycerides, etc.). The underling mechanisms for those differences are still unclear. This study aimed to analyze the whole blood transcriptome profile (RNA-seq) of children with metabolic healthy overweight/obesity (MHO) and metabolic unhealthy overweight/obesity (MUO) phenotypes. Methods: 27 children with OW/OB (10.14 ± 1.3 years, 59% boys) from the ActiveBrains project were included. MHO was defined as having none of the following criteria for metabolic syndrome: elevated fasting glucose, high serum triglycerides, low high-density lipoprotein cholesterol, and high systolic or diastolic blood pressure, while MUO was defined as presenting one or more of these criteria. Inflammatory markers interleukin-1β (IL-1β), IL-6, tumor necrosis factor-α (TNF-α), epidermal growth factor (EGF) and, vascular endothelial growth factor A (VEGF) were additionally determined. Total-blood RNA was analyzed by 5’-end RNA sequencing. Two different bioinformatics approaches were performed: 1) Differential gene expression analyses using Limma R/Bioconductor software package (analyses adjusted by sex and maturational status) and 2) weighted gene coexpression network analyses (WGCNA). Results: Children with MHO had lower values of pro-inflammatory cytokines TNF-α and IL-6 compared to MUO (p < 0.05). 40 genes were differentially expressed (FDR < 0.05) in children with MHO compared to MUO. WGCNA analysis identified 23 gene coexpression modules (i.e. clusters of genes) with low preservation (Zsummary < 2) in children with MHO compared to MUO. Differential and WGCNA gene expression patterns identified 32 genes linked to metabolism, mitochondrial and immune functions. Conclusions: Whole blood transcriptome analysis revealed a distinct pattern of gene expression in children with MHO compared to MUO children. The identified gene expression patterns related to metabolism, mitochondrial and immune functions can promote a better understanding of cardiovascular disease prognosis in individuals with MHO.

Project description:BackgroundAlthough various dietary patterns have been indicated to be associated with the resting metabolic rate [RMR], limited data are available in this field. This study was therefore focused on the association between dietary patterns and resting metabolic rate among participants with overweight and obesity.MethodsThis cross-sectional study was conducted on 304 women with overweight or obesity (BMI ≥ 25 kg/m2), aged 18-50. Anthropometric assessments, physical activity and biochemical measurements were assessed. RMR was also measured by means of indirect calorimetry. Dietary intake of participants was evaluated by 147-item semi-quantitative food frequency questionnaire [FFQ].ResultsThere was a significant association between higher adherence to the healthy dietary pattern [HDP] and RMR (P = 0.05), intakes of protein (P = 0.003), minerals (P = 0.001) as well as fat free mass [FFM] (P = 0.002), bone mineral content (P = 0.001), skeletal muscle mass (P = 0.001), soft lean mass (P = 0.002) and visceral fat area (P = 0.05). Also, there was a considerable association between higher adherence to the unhealthy dietary pattern [UHDP] and fasting blood sugar [FBS] (P = 0.05). Using multinomial logistic regression has been shown that the medium adherence to the HDP was marginally significant with decreased resting metabolic rate [Dec. RMR] group in crude model (OR: 0.54; 95% CI: 0.28-1.05, P = 0.07). After controlling for various confounders such as age, FFM, physical activity, and energy intake, the association between Dec. RMR group and the lowest quartile of the HDP (OR: 0.36; 95% CI: 0.14-0.91, P = 0.03) became significant as well as the association between Dec. RMR group and medium adherence to the HDP (OR: 0.42; 95% CI: 0.18-0.97, P = 0.04). The medium adherence to the UHDP in crude model was also significant with increased resting metabolic rate [Inc. RMR] group (OR: 2.59; 95% CI: 1.01-6.65, P = 0.04).ConclusionsOur study showed that there are significant associations between dietary patterns and RMR status.

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Dataset Information

Serum miR-503 is a Candidate Biomarker for Differentiating Metabolic Healthy Obesity from Metabolic Unhealthy Obesity.

Publications

Serum miR-503 is a Candidate Biomarker for Differentiating Metabolic Healthy Obesity from Metabolic Unhealthy Obesity.

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