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1.
Cells ; 11(5)2022 03 01.
Article in English | MEDLINE | ID: covidwho-1715131

ABSTRACT

Severe COVID-19 patients present a clinical and laboratory overlap with other hyperinflammatory conditions such as hemophagocytic lymphohistiocytosis (HLH). However, the underlying mechanisms of these conditions remain to be explored. Here, we investigated the transcriptome of 1596 individuals, including patients with COVID-19 in comparison to healthy controls, other acute inflammatory states (HLH, multisystem inflammatory syndrome in children [MIS-C], Kawasaki disease [KD]), and different respiratory infections (seasonal coronavirus, influenza, bacterial pneumonia). We observed that COVID-19 and HLH share immunological pathways (cytokine/chemokine signaling and neutrophil-mediated immune responses), including gene signatures that stratify COVID-19 patients admitted to the intensive care unit (ICU) and COVID-19_nonICU patients. Of note, among the common differentially expressed genes (DEG), there is a cluster of neutrophil-associated genes that reflects a generalized hyperinflammatory state since it is also dysregulated in patients with KD and bacterial pneumonia. These genes are dysregulated at the protein level across several COVID-19 studies and form an interconnected network with differentially expressed plasma proteins that point to neutrophil hyperactivation in COVID-19 patients admitted to the intensive care unit. scRNAseq analysis indicated that these genes are specifically upregulated across different leukocyte populations, including lymphocyte subsets and immature neutrophils. Artificial intelligence modeling confirmed the strong association of these genes with COVID-19 severity. Thus, our work indicates putative therapeutic pathways for intervention.


Subject(s)
COVID-19 , Lymphohistiocytosis, Hemophagocytic , Artificial Intelligence , COVID-19/complications , COVID-19/genetics , Child , Humans , Lymphohistiocytosis, Hemophagocytic/complications , Neutrophil Activation , SARS-CoV-2 , Systemic Inflammatory Response Syndrome
2.
Am J Physiol Regul Integr Comp Physiol ; 320(3): R250-R257, 2021 03 01.
Article in English | MEDLINE | ID: covidwho-1024272

ABSTRACT

The COVID19 pandemic has caused more than a million of deaths worldwide, primarily due to complications from COVID19-associated acute respiratory distress syndrome (ARDS). Controversy surrounds the circulating cytokine/chemokine profile of COVID19-associated ARDS, with some groups suggesting that it is similar to patients without COVID19 ARDS and others observing substantial differences. Moreover, although a hyperinflammatory phenotype associates with higher mortality in non-COVID19 ARDS, there is little information on the inflammatory landscape's association with mortality in patients with COVID19 ARDS. Even though the circulating leukocytes' transcriptomic signature has been associated with distinct phenotypes and outcomes in critical illness including ARDS, it is unclear whether the mortality-associated inflammatory mediators from patients with COVID19 are transcriptionally regulated in the leukocyte compartment. Here, we conducted a prospective cohort study of 41 mechanically ventilated patients with COVID19 infection using highly calibrated methods to define the levels of plasma cytokines/chemokines and their gene expressions in circulating leukocytes. Plasma IL1RA and IL8 were found positively associated with mortality, whereas RANTES and EGF negatively associated with that outcome. However, the leukocyte gene expression of these proteins had no statistically significant correlation with mortality. These data suggest a unique inflammatory signature associated with severe COVID19.


Subject(s)
COVID-19/metabolism , COVID-19/pathology , Inflammation/metabolism , Respiratory Distress Syndrome/mortality , SARS-CoV-2 , Aged , COVID-19/mortality , Cohort Studies , Cytokines/genetics , Cytokines/metabolism , Female , Gene Expression Regulation , Humans , Male , Middle Aged
3.
Cell Syst ; 12(1): 23-40.e7, 2021 01 20.
Article in English | MEDLINE | ID: covidwho-837999

ABSTRACT

We performed RNA-seq and high-resolution mass spectrometry on 128 blood samples from COVID-19-positive and COVID-19-negative patients with diverse disease severities and outcomes. Quantified transcripts, proteins, metabolites, and lipids were associated with clinical outcomes in a curated relational database, uniquely enabling systems analysis and cross-ome correlations to molecules and patient prognoses. We mapped 219 molecular features with high significance to COVID-19 status and severity, many of which were involved in complement activation, dysregulated lipid transport, and neutrophil activation. We identified sets of covarying molecules, e.g., protein gelsolin and metabolite citrate or plasmalogens and apolipoproteins, offering pathophysiological insights and therapeutic suggestions. The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype. We present a web-based tool (covid-omics.app) enabling interactive exploration of our compendium and illustrate its utility through a machine learning approach for prediction of COVID-19 severity.


Subject(s)
COVID-19/blood , COVID-19/genetics , Machine Learning , Sequence Analysis, RNA/methods , Severity of Illness Index , Aged , Aged, 80 and over , COVID-19/therapy , Cohort Studies , Female , Gelsolin/blood , Gelsolin/genetics , Humans , Inflammation Mediators/blood , Male , Middle Aged , Neutrophils/metabolism , Principal Component Analysis/methods
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