Evidence mapPaperPMID 41214769Full record

ArticleEuropean journal of medical research2025

Lactylation modulates immune infiltration in sepsis-induced acute respiratory distress syndrome: a multi-omics and machine learning study with experimental confirmation.

Tao Suo, Mengmeng Xu, Jin Fang

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Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Tao SuoDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China.
Mengmeng XuDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, Anhui, China.
Jin FangDepartment of Pathophysiology, School of Basic Medical College, Anhui Medical University, Hefei, 230001, Anhui, China. fangjin1123@126.com.

Funding

key medical and health specialty construction project of Anhui Province 2021szdzk05research initiation fund for doctors of the first affiliated hospital of USTC RC2022010
6 · The paper itself

Abstract

objectivesTo investigate lactylation-driven mechanisms in the pathogenesis of sepsis-induced acute respiratory distress syndrome (ARDS).

methodsMulti-cohort transcriptomic data sets (GSE10474, GSE32707, and GSE66890) were integrated with machine learning algorithms (LASSO, support vector machine, random forest) to identify differentially expressed lactylation-related genes (LRGs). Five hub genes (ALDH1A1, CALM1, CCNA2, HIST1H2BN, SH3GL1) were prioritized. Orthogonal experimental validation was performed using qRT-PCR and Western blotting. Subsequent analyses explored immune cell correlations (focusing on ALDH1A1), regulatory networks (transcription factors and miRNAs), and potential therapeutic drug candidates.

resultsIntegration of bioinformatics analyses identified 25 differentially expressed LRGs and prioritized 5 hub genes. Experimental validation (qRT-PCR/Western blot) consistently demonstrated downregulation of all five hub gene proteins. Notably, this contradicted the bioinformatically predicted upregulation of CCNA2, HIST1H2BN, and SH3GL1, revealing a significant transcriptional-translational discordance. Further analysis revealed ALDH1A1-associated myeloid-derived suppressor cell and neutrophil correlations, a regulatory network comprising 68 transcription factors and 79 miRNAs, and 26 prioritized drug candidates.

conclusionsThis study establishes a protein-verified lactylation-related gene signature with diagnostic relevance for sepsis-induced ARDS. Crucially, it highlights post-transcriptional regulation, evidenced by the discordance between mRNA levels and protein expression of key hub genes, as a key mechanistic feature in the pathogenesis of this condition. The identified regulatory networks and drug candidates provide potential avenues for further research and therapeutic development.

Indexed as

Machine LearningRespiratory Distress SyndromeSepsisComputational BiologyGene Expression ProfilingGene Regulatory NetworksHumansMicroRNAsMultiomicsTranscriptomeMicroRNAsAcute respiratory distress syndromeImmune cell infiltrationMachine learningSepsis

Identifiers

PMID41214769
PMCPMC12604238

What Socratic holds

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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 Socratic graph.