Evidence map›Paper›PMID 32869917›Full record

ArticleJournal of clinical laboratory analysis2020

Urinary miR-3137 and miR-4270 as potential biomarkers for diabetic kidney disease.

Xiaoyu Li, Rong Xu, Xiangyang Liu, Linxin Xu, Mei Xue, Ying Cheng, Ting Li, Xiaochen Yu, Yue Wang, Chunjun Li and 2 more

Abstract read
In one paragraph

Article in Journal of clinical laboratory analysis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Research progress on the regulation of miRNAs in diabetic kidney disease and osteoporosis.International journal of clinical and experimental pathology · 2026
    Review
  4. Article
  5. Review
  6. Review
  7. Article
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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

12 authors.

Xiaoyu LiNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.ORCID https://orcid.org/0000-0003-3890-8332
Rong XuNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Xiangyang LiuNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Linxin XuNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Mei XueNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Ying ChengNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Ting LiNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Xiaochen YuNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Yue WangNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Chunjun LiNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Bei SunNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
Liming ChenNHC Key Laboratory of Hormones and Development (Tianjin Medical University), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.

Funding

Bethune-Merck fundNational Key Research and Development Program of China 2018YFC1314001National Nature Science Foundation of China 81970697Postgraduate Innovation Fund of '13th Five-Year comprehensive investment', Tianjin Medical University YJSCX201815Scientific Research Funding of Tianjin Medial University Chu Hsien-I Memorial Hospital 2018ZDKF08
6 · The paper itself

Abstract

backgroundAs one of the most prevalent diagnostic indicators of diabetic kidney disease (DKD), albumin-to-creatinine ratio (ACR) shows considerably limited predictive power in clinical application. We analyzed microarray expression profiling of urine to seek for differentially expressed miRNAs for potential biomarkers of DKD.

methodsUrine samples from type 2 diabetes mellitus (T2DM) patients with (30 mg/g < ACR < 300 mg/g, DKD group) or without DKD (ACR < 30 mg/g, DM group) were collected for miRNA microarray analysis. The differentially expressed miRNAs were screened by bioinformatics analysis and validated by quantitative real-time PCR. Target genes of differentially expressed miRNAs were predicted in miRDB, Targetscan, and microRNA.org databases. We also conducted the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways analysis to explore for potential mechanisms in DKD.

resultsNine miRNAs were down-regulated and seventeen miRNAs were up-regulated in DKD group, compared to DM group. The levels of miR-3137 and miR-4270 in DKD group were 0.670 ± 0.505 and 2.116 ± 1.762 times than those in DM group, respectively, showing great significance. A total of 1076 target genes were simultaneously predicted by miRDB, Targetscan, and microRNA.org databases. According to the GO analysis results, disorders of endomembrane system may be one of the major pathological changes in DKD. In addition, Rap 1 signaling pathway is also altered obviously in DKD, discovered by the KEGG analysis.

conclusionMiR-3137 and miR-4270 show the potential for urinary biomarkers of DKD. The pathological changes of DKD may be related to disorders of endomembrane system and alternation of Rap1 signaling pathway.

Indexed as

Diabetic NephropathiesAgedBiomarkersComputational BiologyFemaleHumansMaleMicroRNAsMiddle AgedBiomarkersMicroRNAsMIRN3137 microRNA, humanbioinformatics analysisbiomarkersdiabetic kidney diseasemiRNAsurine

Identifiers

PMID32869917
PMCPMC7755759

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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.