Evidence map›Paper›PMID 32821139›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2020

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

Hai-Qing Yue, Ying-Hui Zhou, Yue Guo, Chen-Yi Tang, Fang Wang, Hou-De Zhou

Open access · goldAbstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 47% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Hai-Qing YueNational Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, People's Republic of China.
Ying-Hui ZhouNational Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, People's Republic of China.
Yue GuoNational Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, People's Republic of China.
Chen-Yi TangNational Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, People's Republic of China.ORCID 0000-0003-1780-7997
Fang WangNational Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, People's Republic of China.
Hou-De ZhouNational Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, People's Republic of China.
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeOverweight 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

methodsA 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.

resultsThe 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.

conclusionmiR-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.

Indexed as

diagnosismetabolic syndromemicro RNA

Identifiers

PMID32821139
PMCPMC7419640
OpenAlexW3044538223

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.