Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS

Abstract

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. In this study, 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). The comparison of these 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. 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.

Figure 1:. Molecular signature of COVID-19 ARDS compared to bacterial sepsis-induced ARDS.

a. Differentially abundant molecules (150 metabolites, 70 proteins) between the two ARDS groups. b. Functional annotations of differentially abundant metabolites and proteins at the pathway level. Overall, 33 metabolic and signaling pathways with three or more significant molecules were deregulated between the two ARDS groups. FA=fatty acid.

Figure 2:. Multi-omic network and extracted ECM/CAM/acylcarnitine subnetwork.

a. Gaussian graphical model (GGM) of metabolites and proteins. Shapes and colors of the molecules in the network are based on the two omics types. b. Subnetwork extracted from the full multi-omic GGM, built around tiglyl carnitine and GP6. The observed molecular interactions suggest an interplay of ECM derangement, inflammation, and mitochondrial dysfunction in ARDS pathogenesis.

Figure 3.. Proteomics-based mortality signature.

a. Differentially abundant proteins in COVID-19 survivors and non-survivors, as observed in two bodily fluids, urine and plasma. 60 proteins were significant in urine proteomic profiles, while none of the proteins measured in the plasma of the same patients were associated with mortality. b. Top 14 differential proteins from COVID-19 urine-based mortality signature with log2 fold change larger than or equal to 2 at 5% FDR.