Evidence map›Paper›PMID 42410766›Full record

ArticleMedicine2026

Bioinformatic identification of genes and mechanisms related to acute respiratory distress syndrome and sepsis: A bioinformatic study.

Rui Zhang, Yinghua Fu, Fang Long, Qiong Cheng

Abstract read
In one paragraph

Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Rui ZhangDepartment of Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0009-0009-9263-1179
Yinghua FuDepartment of Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Fang LongZhuzhou Lukou District People's Hospital, Zhuzhou, Hunan, China.
Qiong ChengDepartment of Critical Care Medicine, Dazhou Central Hospital, Dazhou, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We hypothesized that acute respiratory distress syndrome (ARDS) and sepsis share hypoxia-related transcriptional signatures that reflect overlapping immunopathogenic mechanisms. This study aimed to identify shared hypoxia-related genes and associated regulatory features using bioinformatic analyses. Gene expression datasets GSE28750 and GSE76293 were analyzed separately after within-dataset normalization. Differentially expressed genes (DEGs) were defined using |logFC| > 1 and adjusted P < .05. Hypoxia-related genes were compiled from GeneCards, PubMed-curated studies, and molecular signatures database, harmonized by official gene symbols, and intersected with common DEGs from both datasets to identify hypoxia-related DEGs (HRDEGs). Gene ontology enrichment, gene set enrichment analysis, interaction network analysis, immune infiltration analysis, and protein-protein interaction analysis using STRING with a minimum interaction score of 0.400 were subsequently performed. Eleven HRDEGs were identified: capping actin protein, gelsolin-like, CKS2, CLU, FLVCR1, FUNDC1, HPSE, LCN2, MAPK14, PFKFB3, PLAC8, and TDRD9. Gene ontology enrichment suggested involvement in cellular iron ion homeostasis- and iron ion transport-related processes. Gene set enrichment analysisindicated enrichment of hypoxia- and inflammation-related pathways. Under the stricter STRING threshold (score ≥ 0.400), the protein-protein interaction network showed a limited but biologically plausible interaction pattern among the HRDEGs. Predicted miRNA, ribonucleic acid-binding protein, transcription factor, drug, and immune infiltration analyses further suggested that these genes may participate in inflammatory and immune regulatory processes relevant to ARDS and sepsis. This bioinformatic study identified shared hypoxia-associated genes in ARDS and sepsis and generated testable hypotheses regarding their possible regulatory and immunologic relevance. These findings should be interpreted as exploratory and warrant experimental validation in future studies.

Indexed as

Computational BiologyRespiratory Distress SyndromeSepsisDatabases, GeneticGene Expression ProfilingGene OntologyGene Regulatory NetworksHumansHypoxiaProtein Interaction Mapsacute respiratory distress syndromebioinformatic analysishypoxiaimmune infiltrationsepsis

Identifiers

PMID42410766
PMCPMC13336989

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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.