Evidence map›Paper›PMID 32953797›Full record

ArticleAnnals of translational medicine2020

Identification of hub genes in diabetic kidney disease via multiple-microarray analysis.

Yumin Zhang, Wei Li, Yunting Zhou

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 7% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

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  16. Studying Kidney Diseases at the Single-Cell Level.Kidney diseases (Basel, Switzerland) · 2021
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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

3 authors at 3 institutions in 1 country.

Yumin ZhangDepartment of Endocrinology, Zhongda Hospital, Southeast University, Nanjing, China.
Wei LiDepartment of Endocrinology, Zhongda Hospital, Southeast University, Nanjing, China.
Yunting ZhouDepartment of Endocrinology, Zhongda Hospital, Southeast University, Nanjing, China.
Anhui Medical University · CNSoutheast University · CNZhongda Hospital Southeast University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic kidney disease (DKD) is a leading cause of end-stage renal disease; however, the underlying molecular mechanisms remain unclear. Recently, bioinformatics analysis has provided a comprehensive insight toward the molecular mechanisms of DKD. Here, we re-analyzed three mRNA microarray datasets including a single-cell RNA sequencing (scRNA-seq) dataset, with the aim of identifying crucial genes correlated with DKD and contribute to a better understanding of DKD pathogenesis.

methodsThree datasets including GSE131882, GSE30122, and GSE30529 were utilized to find differentially expressed genes (DEGs). The potential functions of DEGs were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A protein-protein interaction (PPI) network was constructed, and hub genes were selected with the top three molecular complex detection (MCODE) score. A correlation analysis between hub genes and clinical indicators was also performed.

resultsIn total, 84 upregulated DEGs and 49 downregulated DEGs were identified. Enriched pathways of the upregulated DEGs included extracellular matrix (ECM) receptor interaction, focal adhesion, human papillomavirus infection, malaria, and cell adhesion molecules. The downregulated DEGs were mainly enriched in ascorbate and aldarate metabolism, arginine and proline metabolism, endocrine- and other factor-regulated calcium reabsorption, mineral absorption and longevity regulating pathway, and multiple species signaling pathway. Seventeen hub genes were identified, and correlation analysis between unexplored hub genes and clinical features of DKD suggested that EGF, KNG1, GADD45B, and CDH2 might have reno-protective roles in DKD. Meanwhile, ATF3, B2M, VCAM1, CLDN4, SPP1, SOX9, JAG1, C3, and CD24 might promote the progression of DKD. Finally, most hub genes were found present in the immune cells of diabetic kidneys, which suggest the important role of inflammation infiltration in DKD pathogenesis.

conclusionsIn this study, we found seventeen hub genes using a scRNA-seq contained multiple-microarray analysis, which enriched the present understanding of molecular mechanisms underlying the pathogenesis of DKD in cells' level and provided candidate targets for diagnosis and treatment of DKD.

Indexed as

diabetic kidney disease (DKD)diagnosisdifferentially expressed genes (DEGs)hub genesSingle-cell RNA sequencing (scRNA-seq)therapeutics

Identifiers

PMID32953797
PMCPMC7475500
OpenAlexW3047417781

What OpenQuestion 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 OpenQuestion graph.