Evidence map›Paper›PMID 40956671›Full record

ArticleEndocrine connections2025

Relationship between Meteorin-like protein and type 2 diabetes mellitus: an update and meta-analysis.

Jing Xie, Yanhua Jiang, Jiayi Yao, Bin Feng, Xin Sun

Abstract read
In one paragraph

Article in Endocrine connections, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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

2 citing papers in PubMed.

  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

5 authors.

Jing XieDepartment of Endocrinology, First Affiliated Hospital of Soochow University, Suzhou, P.R. China.
Yanhua JiangDepartment of Ophthalmology, Fourth People's Hospital of Shenyang, Shenyang, P.R. China.
Jiayi YaoDepartment of Endocrinology, First Affiliated Hospital of Soochow University, Suzhou, P.R. China.
Bin FengDepartment of Endocrinology, First Affiliated Hospital of Soochow University, Suzhou, P.R. China.
Xin SunDepartment of Endocrinology, First Affiliated Hospital of Soochow University, Suzhou, P.R. China.ORCID https://orcid.org/0000-0003-1409-4661

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Meteorin-like protein (Metrnl) is considered a novel adipokine, which plays an important role in the occurrence and development of type 2 diabetes mellitus (T2DM). In a previous meta-analysis, no significant difference in circulating Metrnl levels was found between T2DM patients and normal glucose tolerance individuals. However, these meta-analyses included limited studies, and more studies about Metrnl and T2DM were published recently. Therefore, the association between Metrnl and T2DM remains uncertain. Aim: This study aimed to systematically and comprehensively update the relationship between circulating Metrnl levels and T2DM. Methods: A systematic search was conducted on the Web of Science, Wiley Online Library, PubMed, and Ovid databases using the terms 'type 2 diabetes mellitus' in combination with 'Metrnl'. Meta-analysis results were reported as standardized mean differences (SMDs) with corresponding 95% confidence intervals (CIs). Results: In total, 17 studies, including 649 patients with T2DM and 396 healthy controls, were included in the meta-analysis. We found that circulating Metrnl levels were lower in patients with T2DM than in healthy individuals (SMD: -0.47, 95% CI: (-0.98, 0.05); prediction interval: (-3.66, 2.73)). Moreover, serum Metrnl levels in patients with T2DM were significantly lower than in healthy individuals (SMD: -0.91, 95% CI: (-1.60, -0.22); prediction interval: (-5.03, 3.21)). Conclusions: This study aimed to systematically and comprehensively update the relationship between circulating Metrnl levels and T2DM. A clearer understanding of the role of Metrnl in T2DM could facilitate the development of effective treatments.

Indexed as

Meteorin-likeMetrnlSubfatintype 2 diabetes mellitus

Identifiers

PMID40956671
PMCPMC12478296

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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.