Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS
Abstract Background Acute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial...
| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-01-01
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| Series: | Molecular Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s10020-023-00609-6 |
| _version_ | 1811175818866458624 |
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| author | Richa Batra Rie Uni Oleh M. Akchurin Sergio Alvarez-Mulett Luis G. Gómez-Escobar Edwin Patino Katherine L. Hoffman Will Simmons William Whalen Kelsey Chetnik Mustafa Buyukozkan Elisa Benedetti Karsten Suhre Edward Schenck Soo Jung Cho Augustine M. K. Choi Frank Schmidt Mary E. Choi Jan Krumsiek |
| author_facet | Richa Batra Rie Uni Oleh M. Akchurin Sergio Alvarez-Mulett Luis G. Gómez-Escobar Edwin Patino Katherine L. Hoffman Will Simmons William Whalen Kelsey Chetnik Mustafa Buyukozkan Elisa Benedetti Karsten Suhre Edward Schenck Soo Jung Cho Augustine M. K. Choi Frank Schmidt Mary E. Choi Jan Krumsiek |
| author_sort | Richa Batra |
| collection | DOAJ |
| description | Abstract Background Acute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial clinical challenges due to a lack of etiology-specific therapies, multisystem involvement, and heterogeneous, poor patient outcomes. A molecular comparison of ARDS groups holds the potential to reveal common and distinct mechanisms underlying ARDS pathogenesis. Methods We performed a comparative analysis of urine-based metabolomics and proteomics profiles from COVID-19 ARDS patients (n = 42) and bacterial sepsis-induced ARDS patients (n = 17). To this end, we used two different approaches, first we compared the molecular omics profiles between ARDS groups, and second, we correlated clinical manifestations within each group with the omics profiles. Results The comparison of the two ARDS etiologies identified 150 metabolites and 70 proteins that were differentially abundant between the two groups. Based on these findings, we interrogated the interplay of cell adhesion/extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis through a multi-omic network approach. Moreover, we identified a proteomic signature associated with mortality in COVID-19 ARDS patients, which contained several proteins that had previously been implicated in clinical manifestations frequently linked with ARDS pathogenesis. Conclusion In summary, our results provide evidence for significant molecular differences in ARDS patients from different etiologies and a potential synergy of extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis. The proteomic mortality signature should be further investigated in future studies to develop prediction models for COVID-19 patient outcomes. |
| first_indexed | 2024-04-10T19:42:03Z |
| format | Article |
| id | doaj.art-73b7e4f3cafd424db0c9cb48062b9e13 |
| institution | Directory Open Access Journal |
| issn | 1528-3658 |
| language | English |
| last_indexed | 2024-04-10T19:42:03Z |
| publishDate | 2023-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Molecular Medicine |
| spelling | doaj.art-73b7e4f3cafd424db0c9cb48062b9e132023-01-29T12:15:04ZengBMCMolecular Medicine1528-36582023-01-0129111010.1186/s10020-023-00609-6Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDSRicha Batra0Rie Uni1Oleh M. Akchurin2Sergio Alvarez-Mulett3Luis G. Gómez-Escobar4Edwin Patino5Katherine L. Hoffman6Will Simmons7William Whalen8Kelsey Chetnik9Mustafa Buyukozkan10Elisa Benedetti11Karsten Suhre12Edward Schenck13Soo Jung Cho14Augustine M. K. Choi15Frank Schmidt16Mary E. Choi17Jan Krumsiek18Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell MedicineDivision of Nephrology and Hypertension, Joan and Sanford I. Weill Department of MedicineDivision of Pediatric Nephrology, Department of Pediatrics, Weill Cornell MedicineDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell MedicineDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell MedicineDivision of Nephrology and Hypertension, Joan and Sanford I. Weill Department of MedicineDivision of Biostatistics, Department of Population Health Sciences, Weill Cornell MedicineDivision of Biostatistics, Department of Population Health Sciences, Weill Cornell MedicineDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell MedicineDepartment of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell MedicineDepartment of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell MedicineDepartment of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell MedicineBioinformatics Core, Weill Cornell Medicine –Qatar, Qatar FoundationDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell MedicineDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell MedicineDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell MedicineProteomics Core, Weill Cornell Medicine –Qatar, Qatar FoundationDivision of Nephrology and Hypertension, Joan and Sanford I. Weill Department of MedicineDepartment of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell MedicineAbstract Background Acute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial clinical challenges due to a lack of etiology-specific therapies, multisystem involvement, and heterogeneous, poor patient outcomes. A molecular comparison of ARDS groups holds the potential to reveal common and distinct mechanisms underlying ARDS pathogenesis. Methods We performed a comparative analysis of urine-based metabolomics and proteomics profiles from COVID-19 ARDS patients (n = 42) and bacterial sepsis-induced ARDS patients (n = 17). To this end, we used two different approaches, first we compared the molecular omics profiles between ARDS groups, and second, we correlated clinical manifestations within each group with the omics profiles. Results The comparison of the two ARDS etiologies identified 150 metabolites and 70 proteins that were differentially abundant between the two groups. Based on these findings, we interrogated the interplay of cell adhesion/extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis through a multi-omic network approach. Moreover, we identified a proteomic signature associated with mortality in COVID-19 ARDS patients, which contained several proteins that had previously been implicated in clinical manifestations frequently linked with ARDS pathogenesis. Conclusion In summary, our results provide evidence for significant molecular differences in ARDS patients from different etiologies and a potential synergy of extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis. The proteomic mortality signature should be further investigated in future studies to develop prediction models for COVID-19 patient outcomes.https://doi.org/10.1186/s10020-023-00609-6COVID-19Acute respiratory distress syndrome (ARDS)Multi-omicMortality signatureNetwork-basedComputational analysis |
| spellingShingle | Richa Batra Rie Uni Oleh M. Akchurin Sergio Alvarez-Mulett Luis G. Gómez-Escobar Edwin Patino Katherine L. Hoffman Will Simmons William Whalen Kelsey Chetnik Mustafa Buyukozkan Elisa Benedetti Karsten Suhre Edward Schenck Soo Jung Cho Augustine M. K. Choi Frank Schmidt Mary E. Choi Jan Krumsiek Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS Molecular Medicine COVID-19 Acute respiratory distress syndrome (ARDS) Multi-omic Mortality signature Network-based Computational analysis |
| title | Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS |
| title_full | Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS |
| title_fullStr | Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS |
| title_full_unstemmed | Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS |
| title_short | Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS |
| title_sort | urine based multi omic comparative analysis of covid 19 and bacterial sepsis induced ards |
| topic | COVID-19 Acute respiratory distress syndrome (ARDS) Multi-omic Mortality signature Network-based Computational analysis |
| url | https://doi.org/10.1186/s10020-023-00609-6 |
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