Evidence map›Paper›PMID 37443002›Full record

ArticleBMC medical genomics2023

Network analysis identifies a gene biomarker panel for sepsis-induced acute respiratory distress syndrome.

Duan Zhu, Mi Zhou, Houli Zhang, Liang Gong, Jianlin Hu, Hu Luo, Xiangdong Zhou

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

Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

5 citing papers in PubMed, 5 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

7 authors at 2 institutions in 1 country.

Duan ZhuDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Army Medical University (Southwest Hospital), No.30 Gaotanyan Main Street, Chongqing, 400038, China.
Mi ZhouDepartment of Biochemistry and Molecular Biology, Army Medical University, Chongqing, China.
Houli ZhangDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Army Medical University (Southwest Hospital), No.30 Gaotanyan Main Street, Chongqing, 400038, China.
Liang GongDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Army Medical University (Southwest Hospital), No.30 Gaotanyan Main Street, Chongqing, 400038, China.
Jianlin HuDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Army Medical University (Southwest Hospital), No.30 Gaotanyan Main Street, Chongqing, 400038, China.
Hu LuoDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Army Medical University (Southwest Hospital), No.30 Gaotanyan Main Street, Chongqing, 400038, China. luohucy@163.com.
Xiangdong ZhouDepartment of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Army Medical University (Southwest Hospital), No.30 Gaotanyan Main Street, Chongqing, 400038, China. xiangdongzhou@126.com.
Army Medical University · CNSouthwest Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute respiratory distress syndrome (ARDS) is characterized by non-cardiogenic pulmonary edema caused by inflammation, which can lead to serious respiratory complications. Due to the high mortality of ARDS caused by sepsis, biological markers that enable early diagnosis are urgently needed for clinical treatment.

methodsIn the present study, we used the public microarray data of whole blood from patients with sepsis-induced ARDS, patients with sepsis-alone and healthy controls to perform an integrated analysis based on differential expressed genes (DEGs) and co-expression network to identify the key genes and pathways related to the development of sepsis into ARDS that may be key targets for diagnosis and treatment.

resultsCompared with controls, we identified 180 DEGs in the sepsis-alone group and 152 DEGs in the sepsis-induced ARDS group. About 70% of these genes were unique to the two groups. Functional analysis of DEGs showed that neutrophil-mediated inflammation and mitochondrial dysfunction are the main features of ARDS induced by sepsis. Gene network analysis identified key modules and screened out key regulatory genes related to ARDS. The key genes and their upstream regulators comprised a gene panel, including EOMES, LTF, CSF1R, HLA-DRA, IRF8 and MPEG1. Compared with the healthy controls, the panel had an area under the curve (AUC) of 0.900 and 0.914 for sepsis-alone group and sepsis-induced ARDS group, respectively. The AUC was 0.746 between the sepsis-alone group and sepsis-induced ARDS group. Moreover, the panel of another independent blood transcriptional expression profile dataset showed the AUC was 0.769 in diagnosing sepsis-alone group and sepsis-induced ARDS group.

conclusionsTaken together, our method contributes to the diagnosis of sepsis and sepsis-induced ARDS. The biological pathway involved in this gene biomarker panel may also be a critical target in combating ARDS caused by sepsis.

Indexed as

Respiratory Distress SyndromeSepsisGene Regulatory NetworksGenetic MarkersHumansInflammationGenetic MarkersAcute respiratory distress syndromeAUCGene biomarker panelNetwork analysisSepsis

Identifiers

PMID37443002
PMCPMC10339646
OpenAlexW4384201419

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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.