Evidence map›Paper›PMID 34735495›Full record

ArticlePloS one2021

Bioinformatics analysis of genes related to iron death in diabetic nephropathy through network and pathway levels based approaches.

Yaling Hu, Shuang Liu, Wenyuan Liu, Ziyuan Zhang, Yuxiang Liu, Dalin Sun, Mingyu Zhang, Jingai Fang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

20 citing papers in PubMed, 39 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 1 institution in 1 country.

Yaling HuShanxi Medical University, Taiyuan, Shanxi, China.
Shuang LiuDepartment of Urology, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Wenyuan LiuDepartment of Nephrology, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Ziyuan ZhangDepartment of Nephrology, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Yuxiang LiuShanxi Medical University, Taiyuan, Shanxi, China.
Dalin SunDepartment of Nephrology, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Mingyu ZhangShanxi Medical University, Taiyuan, Shanxi, China.
Jingai FangDepartment of Nephrology, The First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.ORCID 0000-0002-2659-6477
Shanxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic nephropathy is one of the common microvascular complications of diabetes. Iron death is a recently reported way of cell death. To explore the effects of iron death on diabetic nephropathy, iron death score of diabetic nephropathy was analyzed based on the network and pathway levels. Furthermore, markers related to iron death were screened. Using RNA-seq data of diabetic nephropathy, samples were clustered uniformly and the disease was classified. Differentially expressed gene analysis was conducted on the typed disease samples, and the WGCNA algorithm was used to obtain key modules. String database was used to perform protein interaction analysis on key module genes for the selection of Hub genes. Moreover, principal component analysis method was applied to get transcription factors and non-coding genes, which interact with the Hub gene. All samples can be divided into two categories and principal component analysis shows that the two categories are significantly different. Hub genes (FPR3, C3AR1, CD14, ITGB2, RAC2 and ITGAM) related to iron death in diabetic nephropathy were obtained through gene expression differential analysis between different subtypes. Non-coding genes that interact with Hub genes, including hsa-miR-572, hsa-miR-29a-3p, hsa-miR-29b-3p, hsa-miR-208a-3p, hsa-miR-153-3p and hsa-miR-29c-3p, may be related to diabetic nephropathy. Transcription factors HIF1α, KLF4, KLF5, RUNX1, SP1, VDR and WT1 may be related to diabetic nephropathy. The above factors and Hub genes are collectively involved in the occurrence and development of diabetic nephropathy, which can be further studied in the future. Moreover, these factors and genes may be potential target for therapeutic drugs.

Indexed as

Gene Regulatory NetworksCase-Control StudiesComputational BiologyDatabases, GeneticDiabetic NephropathiesFerroptosisGene Expression ProfilingHumansMicroRNAsPrincipal Component AnalysisSequence Analysis, RNAMicroRNAs

Identifiers

PMID34735495
PMCPMC8568295
OpenAlexW3209164696

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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.