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.