Association of endopeptidases, involved in SARS‐CoV‐2 infection, with microbial aggravation in sputum of severe asthma

Abdel‐Aziz, Mahmoud I.; Kermani, Nazanin Zounemat; Neerincx, Anne H.; Vijverberg, Susanne; Guo, Yike; Howarth, Peter H.; Dahlén, Sven‐Erik; Djukanović, Ratko; Sterk, Peter J.; Kraneveld, Aletta D.; Zee, Anke H. Maitland‐van der; Chung, Kian Fan; Adcock, Ian M.

doi:10.1111/all.14731

Cited by 3 publications

(3 citation statements)

References 9 publications

(11 reference statements)

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“…Many peptidases such as endopeptidases and L-amino acid peptides have immunological functions. For example, endopeptidases can be protective against COVID-19 or influenza infection (Tan et al 2017 ; Abdel-Aziz et al 2021 ). Meanwhile, the top GO term for the molecular function was secretory granule (12 genes).…”

Section: Discussionmentioning

confidence: 99%

Using system biology and bioinformatics to identify the influences of COVID-19 co-infection with influenza virus on COPD

Liang

Zheng

Wang

et al. 2023

Funct Integr Genomics

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Coronavirus disease 2019 (COVID-19) has speedily increased mortality globally. Although they are risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), less is known about the common molecular mechanisms behind COVID-19, influenza virus A (IAV), and chronic obstructive pulmonary disease (COPD). This research used bioinformatics and systems biology to find possible medications for treating COVID-19, IAV, and COPD via identifying differentially expressed genes (DEGs) from gene expression datasets (GSE171110, GSE76925, GSE106986, and GSE185576). A total of 78 DEGs were subjected to functional enrichment, pathway analysis, protein-protein interaction (PPI) network construct, hub gene extraction, and other potentially relevant disorders. Then, DEGs were discovered in networks including transcription factor (TF)-gene connections, protein-drug interactions, and DEG-microRNA (miRNA) coregulatory networks by using NetworkAnalyst. The top 12 hub genes were MPO, MMP9, CD8A, HP, ELANE, CD5, CR2, PLA2G7, PIK3R1, SLAMF1, PEX3, and TNFRSF17. We found that 44 TFs-genes, as well as 118 miRNAs, are directly linked to hub genes. Additionally, we searched the Drug Signatures Database (DSigDB) and identified 10 drugs that could potentially treat COVID-19, IAV, and COPD. Therefore, we evaluated the top 12 hub genes that could be promising DEGs for targeted therapy for SARS-CoV-2 and identified several prospective medications that may benefit COPD patients with COVID-19 and IAV co-infection. Supplementary Information The online version contains supplementary material available at 10.1007/s10142-023-01091-3.

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Section: Discussionmentioning

confidence: 99%

Using system biology and bioinformatics to identify the influences of COVID-19 co-infection with influenza virus on COPD

Liang

Zheng

Wang

et al. 2023

Funct Integr Genomics

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“… 60 Several additional studies have also performed multi-omics analysis by finding feature-by-feature correlations. 104 , 105 …”

Section: Correlation-based Methodsmentioning

confidence: 99%

Multi-omic approaches for host-microbiome data integration

Chetty,

Blekhman

2024

Gut Microbes

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The gut microbiome interacts with the host through complex networks that affect physiology and health outcomes. It is becoming clear that these interactions can be measured across many different omics layers, including the genome, transcriptome, epigenome, metabolome, and proteome, among others. Multi-omic studies of the microbiome can provide insight into the mechanisms underlying host-microbe interactions. As more omics layers are considered, increasingly sophisticated statistical methods are required to integrate them. In this review, we provide an overview of approaches currently used to characterize multi-omic interactions between host and microbiome data. While a large number of studies have generated a deeper understanding of host-microbiome interactions, there is still a need for standardization across approaches. Furthermore, microbiome studies would also benefit from the collection and curation of large, publicly available multi-omics datasets.

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“…A representative example of a deeper, more comprehensive dive inside the complex multifactorial mechanisms of asthma characteristics in the context of such an extensive initiative was recently presented [178]. Analysis of 120 sputum samples from severe smoking and non-smoking asthmatics, mild-to-moderate asthmatics and healthy controls from the U-BIOPRED adult cohort was conducted to access potential links between endopeptidase expression, microbial composition and inflammatory features, aiming towards a stratification of asthmatics according to risk of SARS-CoV-2 infection.…”

Section: Large Consortia Integrative Multi-omics Studiesmentioning

confidence: 99%

Microbiome Research and Multi-Omics Integration for Personalized Medicine in Asthma

Logotheti

Agioutantis

Κatsaounou

et al. 2021

JPM

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Asthma is a multifactorial inflammatory disorder of the respiratory system characterized by high diversity in clinical manifestations, underlying pathological mechanisms and response to treatment. It is generally established that human microbiota plays an essential role in shaping a healthy immune response, while its perturbation can cause chronic inflammation related to a wide range of diseases, including asthma. Systems biology approaches encompassing microbiome analysis can offer valuable platforms towards a global understanding of asthma complexity and improving patients’ classification, status monitoring and therapeutic choices. In the present review, we summarize recent studies exploring the contribution of microbiota dysbiosis to asthma pathogenesis and heterogeneity in the context of asthma phenotypes–endotypes and administered medication. We subsequently focus on emerging efforts to gain deeper insights into microbiota–host interactions driving asthma complexity by integrating microbiome and host multi-omics data. One of the most prominent achievements of these research efforts is the association of refractory neutrophilic asthma with certain microbial signatures, including predominant pathogenic bacterial taxa (such as Proteobacteria phyla, Gammaproteobacteria class, especially species from Haemophilus and Moraxella genera). Overall, despite existing challenges, large-scale multi-omics endeavors may provide promising biomarkers and therapeutic targets for future development of novel microbe-based personalized strategies for diagnosis, prevention and/or treatment of uncontrollable asthma.

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Association of endopeptidases, involved in SARS‐CoV‐2 infection, with microbial aggravation in sputum of severe asthma

Cited by 3 publications

References 9 publications

Using system biology and bioinformatics to identify the influences of COVID-19 co-infection with influenza virus on COPD

Using system biology and bioinformatics to identify the influences of COVID-19 co-infection with influenza virus on COPD

Multi-omic approaches for host-microbiome data integration

Microbiome Research and Multi-Omics Integration for Personalized Medicine in Asthma

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