Evidence map›Paper›PMID 36650594›Full record

ArticleBMC medical genomics2023

Identification of key regulatory genes and their working mechanisms in type 1 diabetes.

Hui Li, Xiao Hu, Jieqiong Li, Wen Jiang, Li Wang, Xin Tan

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

6 authors at 1 institution in 1 country.

Hui LiPediatric Department, The First Hospital of Changsha, No. 311, Yingpan Road, Kaifu District, Changsha, 410000, Hunan, People's Republic of China.
Xiao HuPediatric Department, The First Hospital of Changsha, No. 311, Yingpan Road, Kaifu District, Changsha, 410000, Hunan, People's Republic of China.
Jieqiong LiPediatric Department, The First Hospital of Changsha, No. 311, Yingpan Road, Kaifu District, Changsha, 410000, Hunan, People's Republic of China.
Wen JiangPediatric Department, The First Hospital of Changsha, No. 311, Yingpan Road, Kaifu District, Changsha, 410000, Hunan, People's Republic of China.
Li WangPediatric Department, The First Hospital of Changsha, No. 311, Yingpan Road, Kaifu District, Changsha, 410000, Hunan, People's Republic of China.
Xin TanPediatric Department, The First Hospital of Changsha, No. 311, Yingpan Road, Kaifu District, Changsha, 410000, Hunan, People's Republic of China. tanxin35713067@163.com.
The First Hospital of Changsha · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundType 1 diabetes (T1D) is an autoimmune disease characterized by the destruction of beta cells in pancreatic islets. Identification of the key genes involved in T1D progression and their mechanisms of action may contribute to a better understanding of T1D.

methodsThe microarray profile of T1D-related gene expression was searched using the Gene Expression Omnibus (GEO) database. Then, the expression data of two messenger RNAs (mRNAs) were integrated for Weighted Gene Co-Expression Network Analysis (WGCNA) to generate candidate genes related to T1D. In parallel, T1D microRNA (miRNA) data were analyzed to screen for possible regulatory miRNAs and their target genes. An miRNA-mRNA regulatory network was then established to predict the key regulatory genes and their mechanisms.

resultsA total of 24 modules (i.e., clusters/communities) were selected using WGCNA analysis, in which three modules were significantly associated with T1D. Further correlation analysis of the gene module revealed 926 differentially expressed genes (DEGs), of which 327 genes were correlated with T1D. Analysis of the miRNA microarray showed that 13 miRNAs had significant expression differences in T1D. An miRNA-mRNA network was established based on the prediction of miRNA target genes and the combined analysis of mRNA, in which the target genes of two miRNAs were found in T1D correlated genes.

conclusionAn miRNA-mRNA network for T1D was established, based on which 2 miRNAs and 12 mRNAs were screened, suggesting that they may play key regulatory roles in the initiation and development of T1D.

Indexed as

Diabetes Mellitus, Type 1MicroRNAsGene Expression ProfilingGene Regulatory NetworksGenes, RegulatorHumansRNA, MessengerMicroRNAsRNA, MessengerDifferentially expressed genesGEOType 1 diabetesWGCNA

Identifiers

PMID36650594
PMCPMC9843847
OpenAlexW4316812963

What Socratic holds

Textmetadata
LicenceCC BY
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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.