Evidence map›Paper›PMID 37480090›Full record

ArticleJournal of translational medicine2023

Identification of pyroptosis-related genes and potential drugs in diabetic nephropathy.

Meng Yan, Wenwen Li, Rui Wei, Shuwen Li, Yan Liu, Yuqian Huang, Yunye Zhang, Zihao Lu, Qian Lu

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
6.5field-weighted citation impact, top 3% 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

32 citing papers in PubMed, 43 citations in OpenAlex.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Meng Yan *Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China. yanmeng0727@xzhmu.edu.cn.ORCID 0000-0002-0540-4720
Wenwen Li *Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.
Rui WeiJiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.
Shuwen LiJiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.
Yan LiuJiangsu Key Laboratory of Brain Disease and Bioinformation, Research Center for Biochemistry and Molecular Biology, Xuzhou Medical University, Xuzhou, China.
Yuqian HuangJiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.
Yunye ZhangJiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.
Zihao LuJiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.
Qian LuJiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China. luqian@xzhmu.edu.cn.
Xuzhou Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic nephropathy (DN) is one of the serious microvascular complications of diabetes mellitus (DM). A growing body of research has demonstrated that the inflammatory state plays a critical role in the incidence and development of DN. Pyroptosis is a new way of programmed cell death, which has the particularity of natural immune inflammation. The inhibition of inflammatory cytokine expression and regulation of pathways related to pyroptosis may be a novel strategy for DN treatment. The aim of this study is to identify pyroptosis-related genes and potential drugs for DN.

methodsDN differentially expressed pyroptosis-related genes were identified via bioinformatic analysis Gene Expression Omnibus (GEO) dataset GSE96804. Dataset GSE30528 and GSE142025 were downloaded to verify pyroptosis-related differentially expressed genes (DEGs). Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a pyroptosis-related gene predictive model. A consensus clustering analysis was performed to identify pyroptosis-related DN subtypes. Subsequently, Gene Set Variation Analysis (GSVA), Gene Ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to explore the differences between DN clusters. A protein-protein interaction (PPI) network was used to select hub genes and DGIdb database was utilized to screen potential therapeutic drugs/compounds targeting hub genes.

resultsA total of 24 differentially expressed pyroptosis-related genes were identified in DN. A 16 gene predictive model was conducted via LASSO regression analysis. According to the expression level of these 16 genes, DN cases were divided into two subtypes, and the subtypes are mainly associated with inflammation, activation of immune response and cell metabolism. In addition, we identified 10 hub genes among these subtypes, and predicted 65 potential DN therapeutics that target key genes.

conclusionWe identified two pyroptosis-related DN clusters and 65 potential therapeutical agents/compounds for DN, which might shed a light on the treatment of DN.

Indexed as

Diabetes MellitusDiabetic NephropathiesApoptosisCluster AnalysisComputational BiologyHumansInflammationPyroptosisDiabetic nephropathyDrug–gene predictionEnrichment analysisLasso regressionPyroptosis

Identifiers

PMID37480090
PMCPMC10360355
OpenAlexW4385064752

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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.