Evidence map›Paper›PMID 30755828›Full record

ArticlePeerJ2019

The identification of gene signature and critical pathway associated with childhood-onset type 2 diabetes.

Keren Jia, Yingcheng Wu, Jingyi Ju, Liyang Wang, Lili Shi, Huiqun Wu, Kui Jiang, Jiancheng Dong

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 26% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Identification of Hub Genes in Type 2 Diabetes Mellitus Using Bioinformatics Analysis.Diabetes, metabolic syndrome and obesity : targets and therapy · 2020
    Article
  5. 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 1 institution in 1 country.

Keren JiaMedical School of Nantong University, Nantong, Jiangsu, China.
Yingcheng WuMedical School of Nantong University, Nantong, Jiangsu, China.
Jingyi JuMedical School of Nantong University, Nantong, Jiangsu, China.
Liyang WangMedical School of Nantong University, Nantong, Jiangsu, China.
Lili ShiDepartment of Medical Informatics, Medical School of Nantong University, Nantong, Jiangsu, China.
Huiqun WuDepartment of Medical Informatics, Medical School of Nantong University, Nantong, Jiangsu, China.
Kui JiangDepartment of Medical Informatics, Medical School of Nantong University, Nantong, Jiangsu, China.
Jiancheng DongMedical School of Nantong University, Nantong, Jiangsu, China.
Nantong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In general, type 2 diabetes (T2D) usually occurs in middle-aged and elderly people. However, the incidence of childhood-onset T2D has increased all across the globe. Therefore, it is very important to determine the molecular and genetic mechanisms of childhood-onset T2D. In this study, the dataset GSE9006 was downloaded from the GEO (Gene Expression Omnibus database); it includes 24 healthy children, 43 children with newly diagnosed Type 1 diabetes (T1D), and 12 children with newly diagnosed T2D. These data were used for differentially expressed genes (DGEs) analysis and weighted co-expression network analysis (WGCNA). We identified 192 up-regulated genes and 329 down-regulated genes by performing DEGs analysis. By performing WGGNA, we found that blue module (539 genes) was highly correlated to cyan module (97 genes). Gene ontology (GO) and pathway enrichment analyses were performed to figure out the functions and related pathways of genes, which were identified in the results of DEGs and WGCNA. Genes with conspicuous logFC and in the high correlated modules were input into GeneMANIA, which is a plugin of Cytoscape application. Thus, we constructed the protein-protein interaction (PPI) network (92 nodes and 254 pairs). Eventually, we analyzed the transcription factors and references related to genes with conspicuous logFC or high-degree genes, which were present in both the modules of WGCNA and PPI network. Current research shows that EGR1 and NAMPT can be used as marker genes for childhood-onset T2D. Gestational diabetes and chronic inflammation are risk factors that lead to the development of childhood-onset T2D.

Indexed as

Chronic diseaseEGR1ImmunoreactionNAMPTToll-like receptorType 2 diabetes

Identifiers

PMID30755828
PMCPMC6368838
OpenAlexW2914265902

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.