Evidence map›Paper›PMID 35957725›Full record

ArticleAnnals of translational medicine2022

Transcriptomic analysis and laboratory experiments reveal potential critical genes and regulatory mechanisms in sepsis-associated acute kidney injury.

Boyang Liu, Shengxiang Ao, Fang Tan, Wei Ma, Haoru Liu, Huaping Liang, Xia Yang, Xinjin Chi

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
5.5field-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

33 citing papers in PubMed, 50 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 4 institutions in 1 country.

Boyang Liu *Department of Anesthesiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Shengxiang Ao *Department of Wound Infection and Drug, State Key Laboratory of Trauma, Burn and Combined Injury, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Fang Tan *Department of Anesthesiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Wei MaDepartment of Wound Infection and Drug, State Key Laboratory of Trauma, Burn and Combined Injury, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Haoru LiuDepartment of Wound Infection and Drug, State Key Laboratory of Trauma, Burn and Combined Injury, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Huaping LiangDepartment of Wound Infection and Drug, State Key Laboratory of Trauma, Burn and Combined Injury, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Xia YangDepartment of Wound Infection and Drug, State Key Laboratory of Trauma, Burn and Combined Injury, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
Xinjin ChiDepartment of Anesthesiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Daping Hospital · CNThe Seventh Affiliated Hospital of Sun Yat-sen University · CNArmy Medical University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sepsis-associated acute kidney injury (SA-AKI) is one of the most frequent and serious complications of sepsis. However, the transcriptional regulatory network of the pathophysiological mechanism of the kidney has not been revealed. This study identified new mechanisms in SA-AKI using bioinformatics analyses and laboratory-based experiments. Methods: We performed transcriptomic profiling of mouse kidneys after cecal ligation and puncture (CLP) to mimic clinical sepsis. RNA from kidney samples from the CLP and control groups was isolated and analyzed using bulk messenger RNA (mRNA)-seq. Differentially expressed genes (DEGs) between the two groups were identified, and GO, KEGG and GSEA pathway enrichment analyses were performed. The protein-protein interaction (PPI) network of DEGs and hub genes was analyzed. The hub genes were verified using quantitative real-time polymerase chain reaction (qPCR) or Western blotting. The interaction network, targeted microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) of hub genes were predicted, and the critical miRNA-hub gene regulatory axis was verified using qPCR, Western blotting, malondialdehyde (MDA) determination and flow cytometry. Correlation analyses of N6-adenosine methylation (m6A) RNA methylation regulators and hub genes and m6A modification analysis were performed. Results: A total of 4,754 DEGs were identified between the two groups using high-throughput sequencing. The pathways in which DEGs were enriched included ferroptosis (the highest enrichment score), apoptosis, and the PI3K-Akt, NF-kappa B and IL-17 signaling pathways. Seven ( Conclusions: The findings of this study provide new insights into the mechanism regulating the occurrence and progression of SA-AKI. The mmu-miR-7212-5p-Hmox1 axis in ferroptosis and m6A RNA methylation regulators may have potential clinical significance for the future treatment of SA-AKI. The datasets generated for this study can be found in the repository of the GEO database (Series number: GSE186822).

Indexed as

acute kidney injury (AKI)bioinformatics analysisferroptosisN6-adenosine methylation RNA methylation (m6A RNA methylation)Sepsis

Identifiers

PMID35957725
PMCPMC9358506
OpenAlexW4285541747

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

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.