Evidence map›Paper›PMID 40951426›Full record

ArticleFrontiers in endocrinology2025

Differential expression and correlation analysis of whole transcriptome for type 2 diabetes mellitus.

Fang Liu, Aihong Peng, Xiaoli Zhu, Guangming Wang

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2025. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Fang LiuSchool of Clinical Medicine, Dali University, Dali, Yunnan, China.
Aihong PengHunan Clinical Laboratory Center, Changsha, Hunan, China.
Xiaoli ZhuEndocrinology Department, The First Affiliated Hospital of Dali University, Dali, Yunnan, China.
Guangming WangSchool of Clinical Medicine, Dali University, Dali, Yunnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that accounts for 90% or more of all diabetes cases and contributes to the global public health burden. The pathogenesis of T2DM is extremely complex, and increasing evidence suggests that non-coding RNA (ncRNA) is an important molecule involved in the regulation of T2DM. However, there are still many unknown lncRNAs and circRNAs that need further exploration. This study aims to explore new lncRNAs and circRNAs and their potential biological functions in T2DM. Methods: This study utilized high-throughput whole-transcriptome RNA sequencing technology to sequence and analyze five whole blood samples from each group, identifying differentially expressed mRNAs, lncRNAs, circRNAs, and miRNAs between the T2DM group and the control group. The biological functions of the differentially expressed RNAs were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Subsequent association analysis was performed based on the screened differentially expressed mRNA, lncRNA, circRNA, and miRNA to construct a competitive endogenous RNA (ceRNA) network. Results: Differential expression results showed that 411 mRNAs were differentially expressed, 500 lncRNAs were differentially expressed, 356 circRNAs were differentially expressed, and 67 miRNAs were differentially expressed in patients with T2DM compared to controls. Functional analysis showed that cytokine-cytokine receptor interaction, graft-versus-host disease, inflammatory bowel disease, Lipid and atherosclerosis, sphingolipid signaling pathway, TNF signaling pathway, and FOXO signaling pathway, etc. play important roles in T2DM. The gene list was enriched with terms such as immune response, 1-phosphatidylinositol-3-kinase activity, oxidoreductase activity, action on the CH-NH2 donor group, interleukin-18 receptor activity, and antimicrobial peptide biosynthesis process, suggesting potential relevance to T2DM. In addition, six circRNAs and six lncRNAs were identified, which can compete with miRNA as ceRNA in the co-expression network. Conclusions: Differentially expressed circRNAs and lncRNAs may play a crucial role in T2DM. The ceRNA regulatory network provides new insights into T2DM.

Indexed as

Diabetes Mellitus, Type 2RNA, Long NoncodingTranscriptomeCase-Control StudiesFemaleGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksHumansMaleMicroRNAsMiddle AgedRNA, CircularRNA, MessengerMicroRNAsRNA, CircularRNA, Long NoncodingRNA, MessengerceRNA networkdifferential expression analysisfunctional analysistype 2 diabetes mellituswhole transcriptome sequencing

Identifiers

PMID40951426
PMCPMC12425763

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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.