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

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.

Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS (preprint)

Background: Acute respiratory distress syndrome (ARDS), a life-threatening condition characterized by hypoxemia and poor lung compliance, is associated with high mortality. ARDS induced by COVID-19 has similar clinical presentations and pathological manifestations as non-COVID-19 ARDS. However, COVID-19 ARDS is associated with a more protracted inflammatory respiratory failure compared to traditional ARDS. Therefore, a comprehensive molecular comparison of ARDS of different etiologies groups may pave the way for more specific clinical interventions. Methods and Findings: In this study, we compared COVID-19 ARDS (n=43) and bacterial sepsis-induced (non-COVID-19) ARDS (n=24) using multi-omic plasma profiles covering 663 metabolites, 1,051 lipids, and 266 proteins. To address both between- and within- ARDS group variabilities we followed two approaches. First, we identified 706 molecules differently abundant between the two ARDS etiologies, revealing more than 40 biological processes differently regulated between the two groups. From these processes, we assembled a cascade of therapeutically relevant pathways downstream of sphingosine metabolism. The analysis suggests a possible overactivation of arginine metabolism involved in long-term sequelae of ARDS and highlights the potential of JAK inhibitors to improve outcomes in bacterial sepsis-induced ARDS. The second part of our study involved the comparison of the two ARDS groups with respect to clinical manifestations. Using a data-driven multi-omic network, we identified signatures of acute kidney injury (AKI) and thrombocytosis within each ARDS group. The AKI-associated network implicated mitochondrial dysregulation which might lead to post-ARDS renal-sequalae. The thrombocytosis-associated network hinted at a synergy between prothrombotic processes, namely IL-17, MAPK, TNF signaling pathways, and cell adhesion molecules. Thus, we speculate that combination therapy targeting two or more of these processes may ameliorate thrombocytosis-mediated hypercoagulation. Conclusion: We present a first comprehensive molecular characterization of differences between two ARDS etiologies: COVID-19 and bacterial sepsis. Further investigation into the identified pathways will lead to a better understanding of the pathophysiological processes, potentially enabling novel therapeutic interventions.

Auto-Immunoproteomics Analysis of COVID-19 ICU Patients Revealed Increased Levels of Autoantibodies Related to Male Reproductive System (preprint)

The role of autoantibodies in coronavirus disease (COVID-19) complications is not yet fully understood. The current investigation screened two independent cohorts of 97 COVID-19 patients (Discovery (Disc) cohort from Qatar (n = 49) and Replication (Rep) cohort from New York (n = 48)) utilizing high-throughput KoRectly Expressed (KREX) immunome protein-array technology. Autoantibody responses to 57 proteins were significantly altered in the COVID-19 Disc cohort compared to healthy controls (P [≤] 0.05). The Rep cohort had altered autoantibody responses against 26 proteins compared to non-COVID-19 ICU patients that served as controls. Both cohorts showed substantial similarities (r2 = 0.73) and exhibited higher autoantibodies responses to numerous transcription factors, immunomodulatory proteins, and human disease markers. Analysis of the combined cohorts revealed elevated autoantibody responses against SPANXN4, STK25, ATF4, PRKD2, and CHMP3 proteins in COVID-19 patients. KREX analysis of the specific IgG autoantibody responses indicates that the targeted host proteins are supposedly increased in COVID-19 patients. The autoantigen-autoantibody response was cross-validated for SPANXN4 and STK25 proteins using Uniprot BLASTP and sequence alignment tools. SPANXN4 is essential for spermiogenesis and male fertility, which may predict a potential role for this protein in COVID-19 associated male reproductive tract complications and warrants further research.

Integrative Metabolomic and Proteomic Signatures Define Clinical Outcomes in Severe COVID-19 (preprint)

The novel coronavirus disease-19 (COVID-19) pandemic caused by SARS-CoV-2 has ravaged global healthcare with previously unseen levels of morbidity and mortality. To date, methods to predict the clinical course, which ranges from the asymptomatic carrier to the critically ill patient in devastating multi-system organ failure, have yet to be identified. In this study, we performed large-scale integrative multi-omics analyses of serum obtained from COVID-19 patients with the goal of uncovering novel pathogenic complexities of this disease and identifying molecular signatures that predict clinical outcomes. We assembled a novel network of protein-metabolite interactions in COVID-19 patients through targeted metabolomic and proteomic profiling of serum samples in 330 COVID-19 patients compared to 97 non-COVID, hospitalized controls. Our network identified distinct protein-metabolite cross talk related to immune modulation, energy and nucleotide metabolism, vascular homeostasis, and collagen catabolism. Additionally, our data linked multiple proteins and metabolites to clinical indices associated with long-term mortality and morbidity, such as acute kidney injury. Finally, we developed a novel composite outcome measure for COVID-19 disease severity and created a clinical prediction model based on the metabolomics data. The model predicts severe disease with a concordance index of around 0.69, and furthermore shows high predictive power of 0.83-0.93 in two previously published, independent datasets.

The maladaptive vascular response in COVID-19 acute respiratory distress syndrome and recovery (preprint)

ABSTRACT Vascular injury is a menacing element of acute respiratory distress syndrome (ARDS) pathogenesis. To better understand the role of vascular injury in COVID-19 ARDS, we used lung autopsy immunohistochemistry and blood proteomics from COVID-19 subjects at distinct timepoints in disease pathogenesis, including a hospitalized cohort at risk of ARDS development (“ at risk” , N=59), an intensive care unit cohort with ARDS ( “ARDS ”, N=31), and a cohort recovering from ARDS (“ recovery ”, N=12). COVID-19 ARDS lung autopsy tissue revealed an association between vascular injury and platelet-rich microthrombi. This link guided the derivation of a protein signature in the at risk cohort characterized by lower expression of vascular proteins in subjects who died, an early signal of vascular limitation termed the maladaptive vascular response . These findings were replicated in COVID-19 ARDS subjects, as well as when bacterial and influenza ARDS patients (N=29) were considered, hinting at a common final pathway of vascular injury that is more disease (ARDS) then cause (COVID-19) specific, and may be related to vascular cell death. Among recovery subjects, our vascular signature identified patients with good functional recovery one year later. This vascular injury signature could be used to identify ARDS patients most likely to benefit from vascular targeted therapies.

Identifying organ dysfunction trajectory-based subphenotypes in critically ill patients with COVID-19 (preprint)

Rationale. COVID-19-associated respiratory failure offers the unprecedented opportunity to evaluate the differential host response to a uniform pathogenic insult. Prior studies of Acute Respiratory Distress Syndrome (ARDS) have identified subphenotypes with differential outcomes. Understanding whether there are distinct subphenotypes of severe COVID-19 may offer insight into its pathophysiology. Objectives. To identify and characterize distinct subphenotypes of COVID-19 critical illness defined by the post-intubation trajectory of Sequential Organ Failure Assessment (SOFA) score. Methods. Intubated COVID-19 patients at two hospitals in New York city were leveraged as development and validation cohorts. Patients were grouped into mild, intermediate, and severe strata by their baseline post-intubation SOFA. Hierarchical agglomerative clustering was performed within each stratum to detect subphenotypes based on similarities amongst SOFA score trajectories evaluated by Dynamic Time Warping. Statistical tests defined trajectory subphenotype predictive markers. Measurements and Main Results. Distinct worsening and recovering subphenotypes were identified within each stratum, which had distinct 7-day post-intubation SOFA progression trends. Patients in the worsening suphenotypes had a higher mortality than those in the recovering subphenotypes within each stratum (mild stratum, 29.7% vs. 10.3%, p=0.033; intermediate stratum, 29.3% vs. 8.0%, p=0.002; severe stratum, 53.7% vs. 22.2%, p<0.001). Worsening and recovering subphenotypes were replicated in the validation cohort. Routine laboratory tests, vital signs, and respiratory variables rather than demographics and comorbidities were predictive of the worsening and recovering subphenotypes. Conclusions. There are clear worsening and recovering subphenotypes of COVID-19 respiratory failure after intubation, which are more predictive of outcomes than baseline severity of illness. Organ dysfunction trajectory may be well suited as a surrogate for research in COVID-19 respiratory failure.