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Comparison of COVID-Induced ARDS and Sepsis-Induced ARDS

In a recently published study medRxiv* Preprint server, researchers compared the pathophysiology of coronavirus disease 2019 (COVID-19) and bacterial sepsis-induced acute respiratory distress syndrome (ARDS).

There are several similarities between COVID-19 induced ARDS and non-COVID-19 ARDS in terms of clinical presentations and pathologies. However, COVID-19 ARDS is characterized by a greater inflammatory response than traditional ARDS.

Study: Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.  Credit: Chinnapong/Shutterstock​​​​​​Study: Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS. ​​​​​​​Image credit: Chinnapong / Shutterstock

About the study

In the present study, researchers performed a multi-omic analysis to identify and compare signatures found in COVID-19 ARDS and non-COVID-19 ARDS based on the subnetworks.

The team assessed the molecular differences between bacterial sepsis-induced and COVID-19-induced ARDS by analyzing three molecular layers including metabolic, lipidomic and proteomic. The biological processes responsible for the variations between COVID-19 and bacterial sepsis-induced ARDS were identified by annotating the differentiated molecules. This molecular annotation was performed using metabolon subpathways, with the lipids being annotated using lipid classes, while the proteins were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways.

In addition, the team used previous studies that compared COVID-19 ARDS and non-COVID-19 ARDS to either less severe COVID-19 infections or healthy controls. In addition, the team selected processes related to ARDS to study at the molecular level.

The variations in omics correlations with clinical manifestations were also assessed in the two ARDS cohorts. These assessments included assessment of Acute Kidney Injury (AKI), PaO2/FiO2 Ratio, thrombocytosis and mortality. A systemic view of the multi-omic molecules in the two ARDS groups was developed via a Gaussian graphical model that identified the interactions occurring between the molecules.

study overview.  This study was based on 67 ARDS patients, 43 with COVID-19 and 24 with bacterial sepsis.  Profiling of plasma samples revealed 1,906 molecules measured, including 663 metabolites, 1,051 lipids and 266 proteins.  For the inter-ARDS comparison, we identified molecules and signaling pathways that are differentially regulated between the two ARDS groups.  In addition, we have focused on several selected pathways with therapeutic relevance and constructed a cascade of biological processes originating from sphingosine metabolism.  For the intra-ARDS comparison, we identified molecules associated with clinical manifestations, including acute kidney injury (AKI), thrombocytosis (platelet count), PaO2/FiO2 ratio, and mortality, within each ARDS group.  Furthermore, we constructed a data-driven multi-omic network based on the Gaussian graphical model (GGM).  This network was used to generate sub-networks associated with clinical manifestations.

study overview. This study was based on 67 ARDS patients, 43 with COVID-19 and 24 with bacterial sepsis. Profiling of plasma samples revealed 1,906 molecules measured, including 663 metabolites, 1,051 lipids and 266 proteins. For the inter-ARDS comparison, we identified molecules and signaling pathways that are differentially regulated between the two ARDS groups. In addition, we have focused on several selected pathways with therapeutic relevance and constructed a cascade of biological processes originating from sphingosine metabolism. For the intra-ARDS comparison, we identified molecules associated with clinical manifestations, including acute kidney injury (AKI), thrombocytosis (platelet count), PaO2/FiO2 ratio, and mortality, within each ARDS group. Furthermore, we constructed a data-driven multi-omic network based on the Gaussian graphical model (GGM). This network was used to generate sub-networks associated with clinical manifestations.

Results

The team analyzed a total of 67 patients admitted to the intensive care unit (ICU), including 24 patients diagnosed with bacterial sepsis and 43 with COVID-19. Among these patients, 25.4% were women with a mean age of 60 years. Approximately 11 of the COVID-19 ARDS and nine bacterial sepsis-induced ARDS patients died. In addition, nearly 46.3% of patients reported acute kidney injury (AKI), including 16 in the COVID-19 ARDS and 15 in the bacterial sepsis-induced ARDS cohorts.

Multi-omic comparison between COVID-19 ARDS and bacterial sepsis-induced ARDS.  a.  Metabolomic, lipidomic and proteomic analyzes between the two ARDS groups.  706 molecules were present at different frequencies in the two ARDS groups.  b.  Functional Notes on Important Molecules.  Pathways and classes with at least 4 significant molecules were included in these diagrams.  FDR – False Detection Rate.  Abbreviations of lipid classes: TAG – triacylglycerol, PC – phosphatidylcholine, DAG – diacylglycerol, CE – cholesteryl ester, HCER – hexosylceramide, Total – total lipids, SM – sphingomyelin, LPC – lysophosphatidylcholine, LCER – lactosylceramide, DCER – dihydroceramide, CER – ceramide, PE – Phosphatidylethanolamine, MAG - Monoacylglycerol, LPE - Lysophosphatidylethanolamine, PI - Phosphatidylinositol.

Multi-omic comparison between COVID-19 ARDS and bacterial sepsis-induced ARDS.​​​​​​​a. Metabolomic, lipidomic and proteomic analyzes between the two ARDS groups. 706 molecules were present at different frequencies in the two ARDS groups. b. Functional Notes on Important Molecules. Pathways and classes with at least 4 significant molecules were included in these diagrams. FDR – False Detection Rate. Abbreviations of lipid classes: TAG – triacylglycerol, PC – phosphatidylcholine, DAG – diacylglycerol, CE – cholesteryl ester, HCER – hexosylceramide, Total – total lipids, SM – sphingomyelin, LPC – lysophosphatidylcholine, LCER – lactosylceramide, DCER – dihydroceramide, CER – ceramide, PE – Phosphatidylethanolamine, MAG – Monoacylglycerol, LPE – Lysophosphatidylethanolamine, PI – Phosphatidylinositol.

Analysis of the plasma molecular profile showed that 175 of the 663 metabolites, 437 of the 1051 lipids and 94 of the 266 proteins examined were present with different abundances in the plasma groups. The team also observed that 10 metabolites belonging to the branched-chain amino acids (BCAAs) pathway were found in abundance between the two ARDS groups. Among these, eight showed higher and two lower levels of COVID-19-induced ARDS compared to those in bacterial sepsis-induced ARDS.

Seven metabolites from the glutamate pathway were unequally abundant between the two ARDS groups, including four metabolites with higher and three with lower concentrations in the COVID-19-induced ARDS samples than in the bacterial sepsis-induced ARDS samples. The team also found significant changes in lipidomic profiles between the ARDS groups, with the largest differences observed in the triacylglycerols (TAGs) and diacylglycerols (DAGs) lipid classes. This underscored the role of lipid metabolism in disease prognosis. Researchers found that levels of TAGs and DAGs were higher in COVID-19 ARDS than in bacterial sepsis-induced ARDS.

A total of 12 proteins from the phosphoinositide-3-kinase-AKT pathway were abundant between the two ARDS, including eight with higher and four with lower levels in COVID-19 ARDS compared to bacterial sepsis-induced ARDS. On the other hand, 11 proteins belonging to the mitogen-activated protein kinase (MAPK) signaling pathway were abundant between the two ARDS groups, including eight with higher and three with lower levels in COVID-19 ARDS compared to bacterial sepsis. induced ARDS.

Significant associations with regard to PaO were found in the omics analysis2/FiO2 Ratio in the COVID-19 ARDS cohort, while neither molecule correlated with mortality. In addition, 249 and 111 molecules were found to be associated with AKI and platelet count, respectively. These included 76 molecules that overlap between the COVID-19 ARDS and bacterial sepsis-induced ARDS.

Regarding the AKI signature in COVID-19 ARDS patients, a total of 233 molecules were correlated with AKI, including 135 metabolites and two proteins positively associated with AKI, 96 metabolites negatively associated while none of the lipids a had bandage. In bacterial sepsis-induced ARDS, 46 metabolites were positively and 19 metabolites negatively associated with AKI, while no lipids or proteins showed any correlation with AKI.

Overall, the study results showed that multi-omic analysis could efficiently identify novel therapeutic approaches and detect distinct pathophysiological features within ARDS.

*Important NOTE

medRxiv publishes preliminary scientific reports that are not peer-reviewed and therefore should not be relied upon as conclusive, guide clinical practice/health behavior, or be treated as established information.

Magazine reference:

  • Multi-Omic Comparative Analysis of COVID-19 and Bacterial Sepsis-Induced ARDS, Richa Batra, William Wahlen, Sergio Alvarez-Mulett, Katherine Hoffman, Will Simmons, John Harrington, Kelsey Chetnik, Mustafa Buyukozkan, Elisa Benedetti, Mary E. Choi, Karsten Suhre, Frank Schmidt, Edward Schenck, Augustine MK Choi, Soo Jung Cho, Jan Krumsiek, medRxiv 2022.05.16.22274587, DOI: https://doi.org/10.1101/2022.05.16.22274587, https://www.medrxiv.org /content/10.1101/2022.05.16.22274587v1

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