Evidence map›Paper›PMID 28260062›Full record

ArticleMolecular medicine reports2017

Serum microRNA profiling and bioinformatics analysis of patients with type 2 diabetes mellitus in a Chinese population.

Ze-Min Yang, Long-Hui Chen, Min Hong, Ying-Yu Chen, Xiao-Rong Yang, Si-Meng Tang, Qian-Fa Yuan, Wei-Wen Chen

Open access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 22% 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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Genomic and Transcriptomic Variations ofJournal of nutrition and metabolism · 2026
    Article
  4. Article
  5. Characterizing Circulating microRNA Signatures of Type 2 Diabetes Subtypes.International journal of molecular sciences · 2025
    Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Article
  12. Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes.International journal of molecular sciences · 2021
    Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. [MiR-665 Promotes the Biological Behavior of Small Cell Lung Cancer by Targeting LLGL1].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2020
    Article
  19. Article
  20. Article
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

8 authors at 3 institutions in 1 country.

Ze-Min YangDepartment of Biochemistry and Molecular Biology, School of Basic Courses, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, P.R. China.
Long-Hui ChenPi‑Wei Institute, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510405, P.R. China.
Min HongDepartment of Traditional Chinese Medicine, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, Guangdong 510080, P.R. China.
Ying-Yu ChenDepartment of Traditional Chinese Medicine, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, Guangdong 510080, P.R. China.
Xiao-Rong YangClinical Laboratory, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, Guangdong 510080, P.R. China.
Si-Meng TangDepartment of Biochemistry and Molecular Biology, School of Basic Courses, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, P.R. China.
Qian-Fa YuanDepartment of Biochemistry and Molecular Biology, School of Basic Courses, Guangdong Pharmaceutical University, Guangzhou, Guangdong 510006, P.R. China.
Wei-Wen ChenPi‑Wei Institute, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510405, P.R. China.
First Affiliated Hospital of Guangdong Pharmaceutical University · CNGuangdong Pharmaceutical University · CNGuangzhou University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 2 diabetes mellitus (T2DM) is characterized by islet β-cell dysfunction and insulin resistance, which leads to an inability to maintain blood glucose homeostasis. Circulating microRNAs (miRNAs) have been suggested as novel biomarkers for T2DM prediction or disease progression. However, miRNAs and their roles in the pathogenesis of T2DM remain to be fully elucidated. In the present study, the serum miRNA expression profiles of T2DM patients in Chinese cohorts were examined. Total RNA was extracted from serum samples of 10 patients with T2DM and five healthy controls, and these was used in reverse-transcription‑quantitative polymerase chain reaction analysis with the Exiqon PCR system of 384 serum/plasma miRNAs. A total of seven miRNAs were differentially expressed between the two groups (fold change >3 or <0.33; P<0.05). The serum expression levels of miR‑455‑5p, miR‑454‑3p, miR‑144‑3p and miR‑96‑5p were higher in patients with T2DM, compared with those of healthy subjects, however, the levels of miR‑409‑3p, miR‑665 and miR‑766‑3p were lower. Hierarchical cluster analysis indicated that it was possible to separate patients with T2DM and control individuals into their own similar categories by these differential miRNAs. Target prediction showed that 97 T2DM candidate genes were potentially modulated by these seven miRNAs. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that 24 pathways were enriched for these genes, and the majority of these pathways were enriched for the targets of induced and repressed miRNAs, among which insulin, adipocytokine and T2DM pathways, and several cancer‑associated pathways have been previously associated with T2DM. In conclusion, the present study demonstrated that serum miRNAs may be novel biomarkers for T2DM and provided novel insights into the pathogenesis of T2DM.

Indexed as

Gene Expression ProfilingAgedChinaCluster AnalysisCohort StudiesDiabetes Mellitus, Type 2FemaleGene Expression RegulationGenomicsHumansMaleMicroRNAsMiddle AgedMicroRNAs

Identifiers

PMID28260062
PMCPMC5364922
OpenAlexW2589647915

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.