Evidence map›Paper›PMID 36967805›Full record

ArticleFrontiers in endocrinology2023

Bulk and single-cell transcriptome analyses of islet tissue unravel gene signatures associated with pyroptosis and immune infiltration in type 2 diabetes.

Yaxian Song, Chen He, Yan Jiang, Mengshi Yang, Zhao Xu, Lingyan Yuan, Wenhua Zhang, Yushan Xu

Open access · goldFull text read
In one paragraph

Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

9 citing papers in PubMed, 12 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Yaxian SongDepartment of Endocrinology, Yunnan Province Clinical Medical Center for Endocrine and Metabolic Disease, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Chen HeDepartment of Geriatric Medicine, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Yan JiangDepartment of Endocrinology, Yunnan Province Clinical Medical Center for Endocrine and Metabolic Disease, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Mengshi YangDepartment of Endocrinology, Yunnan Province Clinical Medical Center for Endocrine and Metabolic Disease, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Zhao XuDepartment of Endocrinology, Yunnan Province Clinical Medical Center for Endocrine and Metabolic Disease, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Lingyan YuanDepartment of Endocrinology, Yunnan Province Clinical Medical Center for Endocrine and Metabolic Disease, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Wenhua ZhangDepartment of Endocrinology, Yunnan Province Clinical Medical Center for Endocrine and Metabolic Disease, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Yushan XuDepartment of Endocrinology, Yunnan Province Clinical Medical Center for Endocrine and Metabolic Disease, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
First Affiliated Hospital of Kunming Medical University · CNKunming Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Type 2 diabetes (T2D) is a common chronic heterogeneous metabolic disorder. However, the roles of pyroptosis and infiltrating immune cells in islet dysfunction of patients with T2D have yet to be explored. In this study, we aimed to explore potential crucial genes and pathways associated with pyroptosis and immune infiltration in T2D. Methods: To achieve this, we performed a conjoint analysis of three bulk RNA-seq datasets of islets to identify T2D-related differentially expressed genes (DEGs). After grouping the islet samples according to their ESTIMATE immune scores, we identified immune- and T2D-related DEGs. A clinical prediction model based on pyroptosis-related genes for T2D was constructed. Weighted gene co-expression network analysis was performed to identify genes positively correlated with pyroptosis-related pathways. A protein-protein interaction network was established to identify pyroptosis-related hub genes. We constructed miRNA and transcriptional networks based on the pyroptosis-related hub genes and performed functional analyses. Single-cell RNA-seq (scRNA-seq) was conducted using the GSE153885 dataset. Dimensionality was reduced using principal component analysis and t-distributed statistical neighbor embedding, and cells were clustered using Seurat. Different cell types were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA). Cell-cell communication and pseudotime trajectory analyses were conducted using the samples from patients with T2D. Results: We identified 17 pyroptosis-related hub genes. We determined the abundance of 13 immune cell types in the merged matrix and found that these cell types were correlated with the 17 pyroptosis-related hub genes. Analysis of the scRNA-seq dataset of 1892 islet samples from patients with T2D and controls revealed 11 clusters. INS and IAPP were determined to be pyroptosis-related and candidate hub genes among the 11 clusters. GSEA of the 11 clusters demonstrated that the myc, G2M checkpoint, and E2F pathways were significantly upregulated in clusters with several differentially enriched pathways. Discussion: This study elucidates the gene signatures associated with pyroptosis and immune infiltration in T2D and provides a critical resource for understanding of islet dysfunction and T2D pathogenesis.

Indexed as

Diabetes Mellitus, Type 2PyroptosisHumansModels, StatisticalPrognosisSingle-Cell Gene Expression Analysisdifferentially expressed geneimmune infiltrationpyroptosissingle-cell RNAtype 2 diabetes

Identifiers

PMID36967805
PMCPMC10034023
OpenAlexW4323666553

What Socratic holds

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Registered trials

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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 Socratic graph.