Novel Biomarkers for Acute Respiratory Distress Syndrome: Genetics, Epigenetics and Transcriptomics

Zheng, Fei; Pan, Yihang; Yang, Yang; Zeng, Cheng; Fang, Xiangming; Shu, Qiang; Chen, Qixing

doi:10.2217/bmm-2021-0749

Cited by 28 publications

(16 citation statements)

References 115 publications

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“…Briefly, we searched MEDLINE, Embase, bioRxiv, medRxiv, the ARDS Database of Genes 55 , and the NCBI Gene Expression Omnibus from inception to April 1 st , 2023 without language restrictions. We also performed single-level backwards and forwards citation searches using SpiderCite 79 and hand-searched recent review articles 80–83 .…”

Section: Methodsmentioning

confidence: 99%

The genomic landscape of Acute Respiratory Distress Syndrome: a meta-analysis by information content of genome-wide studies of the host response

Millar,

Clohisey-Hendry,

McMannus

et al. 2024

Preprint

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Acute respiratory distress syndrome (ARDS) is a clinically defined syndrome of acute hypoxaemic respiratory failure secondary to non-cardiogenic pulmonary oedema. It arises from a diverse set of triggers and encompasses marked biological heterogeneity, complicating efforts to develop effective therapies. An extensive body of recent work (including transcriptomics, proteomics, and genome-wide association studies) has sought to identify proteins/genes implicated in ARDS pathogenesis. These diverse studies have not been systematically collated and interpreted. To solve this, we performed a systematic review and computational integration of existing omics data implicating host response pathways in ARDS pathogenesis. We identified 40 unbiased studies reporting associations, correlations, and other links with genes and single nucleotide polymorphisms (SNPs), from 6,856 ARDS patients. We used meta-analysis by information content (MAIC) to integrate and evaluate these data, ranking over 7,000 genes and SNPs and weighting cumulative evidence for association. Functional enrichment of strongly-supported genes revealed cholesterol metabolism, endothelial dysfunction, innate immune activation and neutrophil degranulation as key processes. We identify 51 hub genes, most of which are potential therapeutic targets. To explore biological heterogeneity, we conducted a separate analysis of ARDS severity/outcomes, revealing distinct gene associations and tissue specificity. Our large-scale integration of existing omics data in ARDS enhances understanding of the genomic landscape by synthesising decades of data from diverse sources. The findings will help researchers refine hypotheses, select candidate genes for functional validation, and identify potential therapeutic targets and repurposing opportunities. Our study and the publicly available computational framework represent an open, evolving platform for interpretation of ARDS genomic data.

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Section: Methodsmentioning

confidence: 99%

The genomic landscape of Acute Respiratory Distress Syndrome: a meta-analysis by information content of genome-wide studies of the host response

Millar,

Clohisey-Hendry,

McMannus

et al. 2024

Preprint

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“…Improved comprehension of the risk factors of ARDS in patients with sepsis would enable clinicians to detect ARDS at an earlier stage. Additionally, various studies have altered the focus from clinical risk factors to biomarkers in order to predict the development of ARDS [ 25 , 26 ]. This is an approach towards more precise prediction and diagnosis for ARDS.…”

Section: Reviewmentioning

confidence: 99%

A Systematic Review and Meta-Analysis of Independent Predictors for Acute Respiratory Distress Syndrome in Patients Presenting With Sepsis

Mayow¹,

Ahmad²,

Afzal³

et al. 2023

Cureus

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The current meta-analysis was conducted to determine the predictors of acute respiratory distress syndrome (ARDS) in patients with sepsis. The present meta-analysis was conducted in accordance with the MOOSE (Meta-analysis of Observational Studies in Epidemiology) guidelines. We conducted a systematic search using the PubMed, Cochrane Library, and EMBASE databases for studies published between 1 January 2000 and 28 February 2023 that assessed the predictors of ARDS in patients with sepsis. We used key terms such as "predictors," "acute respiratory distress syndrome," and "sepsis" to search for relevant articles. Our search was limited to human studies published in English. A total of six studies were included in this metaanalysis. Of the six studies, four were retrospective and two were prospective. The pooled incidence of ARDS was 11.27%. We identified six factors with a consistent and statistically significant association with ARDS, including sequential organ failure assessment (SOFA) score, Acute Physiology and Chronic Health Evaluation (APACHE) II score, pulmonary sepsis, smoking, pancreatitis, and C-reactive protein. Age, diabetes, and chronic obstructive pulmonary disease (COPD) were not found to be significantly associated with ARDS in this patient population. It is important for healthcare providers to consider these predictors when assessing patients with sepsis and septic shock to identify those at high risk for developing ARDS and implement appropriate preventive measures.

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“…Much of the evidence regarding miRNA identification in ARDS comes from preclinical studies. MiRNAs are involved in several pathophysiologic processes, including regulation of cell proliferation, differentiation, apoptosis, metabolism, and the immune response [ 108 ]. Some transcriptomics analyses of miRNAs in preclinical models revealed that inflammation during ARDS promotes macrophage proliferation and inflammation, also of the lung [ 109 – 112 ].…”

Section: Omics In Ards Researchmentioning

confidence: 99%

Personalized medicine using omics approaches in acute respiratory distress syndrome to identify biological phenotypes

et al. 2022

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In the last decade, research on acute respiratory distress syndrome (ARDS) has made considerable progress. However, ARDS remains a leading cause of mortality in the intensive care unit. ARDS presents distinct subphenotypes with different clinical and biological features. The pathophysiologic mechanisms of ARDS may contribute to the biological variability and partially explain why some pharmacologic therapies for ARDS have failed to improve patient outcomes. Therefore, identifying ARDS variability and heterogeneity might be a key strategy for finding effective treatments. Research involving studies on biomarkers and genomic, metabolomic, and proteomic technologies is increasing. These new approaches, which are dedicated to the identification and quantitative analysis of components from biological matrixes, may help differentiate between different types of damage and predict clinical outcome and risk. Omics technologies offer a new opportunity for the development of diagnostic tools and personalized therapy in ARDS. This narrative review assesses recent evidence regarding genomics, proteomics, and metabolomics in ARDS research.

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Novel Biomarkers for Acute Respiratory Distress Syndrome: Genetics, Epigenetics and Transcriptomics

Cited by 28 publications

References 115 publications

The genomic landscape of Acute Respiratory Distress Syndrome: a meta-analysis by information content of genome-wide studies of the host response

The genomic landscape of Acute Respiratory Distress Syndrome: a meta-analysis by information content of genome-wide studies of the host response

A Systematic Review and Meta-Analysis of Independent Predictors for Acute Respiratory Distress Syndrome in Patients Presenting With Sepsis

Personalized medicine using omics approaches in acute respiratory distress syndrome to identify biological phenotypes

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