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.

Keywords:

• micro RNA
• metabolic syndrome
• diagnosis

Data Sharing Statement

We commit to responsible sharing of data from this clinical trial. This includes summary data and anonymized individual participant data as well as other information, such as study protocol. Requests from any qualified researchers who engage in rigorous, independent scientific research will be considered. Data will be provided following review and approval of a research proposal and statistical analysis plan and execution of a data sharing agreement. For more information, please email Hou-De Zhou, [email protected].

Ethics and Consent Statement

This study has been approved by the ethics committee of National Clinical Research Center for Metabolic Disease, the Second Xiangya Hospital of Central South University and has been performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

Disclosure

The authors report no conflicts of interest in this work.

Additional information

Funding

This work was supported by the National Natural Scientific Foundation of China [grant numbers: 81770880, 81800788, 81970762], the Science & Technology Department of Hunan Province [grant numbers: 2015JC3012, 2018SK52511] and Hunan Research Innovation Project for Postgraduate Students [grant number: CX2018B069].