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Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.
Batra, Richa; Uni, Rie; Akchurin, Oleh M; Alvarez-Mulett, Sergio; Gómez-Escobar, Luis G; Patino, Edwin; Hoffman, Katherine L; Simmons, Will; Whalen, William; Chetnik, Kelsey; Buyukozkan, Mustafa; Benedetti, Elisa; Suhre, Karsten; Schenck, Edward; Cho, Soo Jung; Choi, Augustine M K; Schmidt, Frank; Choi, Mary E; Krumsiek, Jan.
  • Batra R; Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, 10021, USA.
  • Uni R; Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, NY, USA.
  • Akchurin OM; Division of Pediatric Nephrology, Department of Pediatrics, Weill Cornell Medicine, New York, NY, USA.
  • Alvarez-Mulett S; New York-Presbyterian Hospital, New York, NY, USA.
  • Gómez-Escobar LG; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
  • Patino E; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
  • Hoffman KL; Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, NY, USA.
  • Simmons W; Division of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
  • Whalen W; Division of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
  • Chetnik K; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
  • Buyukozkan M; Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, 10021, USA.
  • Benedetti E; Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, 10021, USA.
  • Suhre K; Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, 10021, USA.
  • Schenck E; Bioinformatics Core, Weill Cornell Medicine -Qatar, Qatar Foundation, Doha, Qatar.
  • Cho SJ; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
  • Choi AMK; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
  • Schmidt F; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
  • Choi ME; Proteomics Core, Weill Cornell Medicine -Qatar, Qatar Foundation, Doha, Qatar. frs4001@qatar-med.cornell.edu.
  • Krumsiek J; Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, NY, USA. mec2025@med.cornell.edu.
Mol Med ; 29(1): 13, 2023 01 26.
Article in English | MEDLINE | ID: covidwho-2214525
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Respiratory Distress Syndrome / Sepsis / COVID-19 Type of study: Etiology study / Experimental Studies / Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Humans Language: English Journal: Mol Med Journal subject: Molecular Biology Year: 2023 Document Type: Article Affiliation country: S10020-023-00609-6

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Respiratory Distress Syndrome / Sepsis / COVID-19 Type of study: Etiology study / Experimental Studies / Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Humans Language: English Journal: Mol Med Journal subject: Molecular Biology Year: 2023 Document Type: Article Affiliation country: S10020-023-00609-6