Large-scale Multi-omic Analysis of COVID-19 Severity

Overmyer, Katherine A.; Miller, Ian; Balnis, Joseph; Bernstein, Matthew N.; Peters-Clarke, Trenton M.; Meyer, Jesse G.; Quan, Qiuwen; Muehlbauer, Laura K.; Trujillo, Edna A.; He, Yuchen; Chopra, Amit; Chieng, Hau; Tiwari, Anupama; Judson, Marc A.; Paulson, Brett R.; Brademan, Dain R.; Zhu, Yunyun; Serrano, Lia R.; Linke, Vanessa; Drake, Lisa A.; Adam, Alejandro P.; Schwartz, Bruce A.; Singer, Harold A.; Swanson, Scott; Mosher, Deane F.; Stewart, Ron; Coon, Joshua J.; Jaitovich, Ariel

doi:10.1101/2020.07.17.20156513

Cited by 69 publications

(108 citation statements)

References 103 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previously, we and others investigated the association of plasma and serum biomarkers with COVID-19 severity [7][8][9][10][11]14 . In other studies, the potential prognostic value of several established and newly discovered blood markers for predicting the future course of disease was investigated, e.g.…”

Section: Discussionmentioning

confidence: 99%

“…Several recent investigations have identified protein biomarkers and clinical parameters that classify COVID-19 patients according to disease severity [7][8][9][10][11][12][13][14][15] . To identify i) which of these markers and parameters correlate with each other by being attributed to a common biological or physiological response, and ii) which markers predict outcome, we longitudinally phenotyped 139 individuals admitted at Charité University Hospital, Berlin, Germany, between March 01, 2020 and June 30, 2020 due to PCR confirmed SARS-CoV-2 infection (Supp.…”

Section: Covariation Of Clinical Diagnostic Parameters and The Plasmamentioning

confidence: 99%

“…A number of biomarkers that classify COVID-19 severity have recently been described, based on clinical chemistry, enzyme activities, immunoprofiling, single cell sequencing, proteomics, and metabolomics [7][8][9][10][11][12][13][14][15] . These severity classifiers characterize COVID-19 pathology and host responses mainly in blood, serum, plasma or immune cells.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome

Demichev¹,

Tober‐Lau²,

Nazarenko³

et al. 2020

Preprint

View full text Add to dashboard Cite

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. There is an urgent need for predictive markers that can guide clinical decision-making, inform about the effect of experimental therapies, and point to novel therapeutic targets. Here, we characterize the time-dependent progression of COVID-19 through different stages of the disease, by measuring 86 accredited diagnostic parameters and plasma proteomes at 687 sampling points, in a cohort of 139 patients during hospitalization. We report that the time-resolved patient molecular phenotypes reflect an initial spike in the systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution and immunomodulation. Further, we show that the early host response is predictive for the disease trajectory and gives rise to proteomic and diagnostic marker signatures that classify the need for supplemental oxygen therapy and mechanical ventilation, and that predict the time to recovery of mildly ill patients. In severely ill patients, the molecular phenotype of the early host response predicts survival, in two independent cohorts and weeks before outcome. We also identify age-specific molecular response to COVID-19, which involves increased inflammation and lipoprotein dysregulation in older patients. Our study provides a deep and time resolved molecular characterization of COVID-19 disease progression, and reports biomarkers for risk-adapted treatment strategies and molecular disease monitoring. Our study demonstrates accurate prognosis of COVID-19 outcome from proteomic signatures recorded weeks earlier.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Covariation Of Clinical Diagnostic Parameters and The Plasmamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome

Demichev¹,

Tober‐Lau²,

Nazarenko³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…In addition, two recent studies that conducted an integrated immune analysis of COVID-19 patients found impaired IFN responses in severe and critically ill patients (Arunachalam et al, 2020;Hadjadj et al, 2020). Further support for the role of CoV-2 infection (Blanco-Melo et al, 2020;Emanuel et al, 2020;Overmyer et al, 2020;Sun et al, 2020).…”

Section: Introductionmentioning

confidence: 98%

Functional Landscape of SARS-CoV-2 Cellular Restriction

Martin-Sancho

Lewinski

Pache

et al. 2020

Preprint

View full text Add to dashboard Cite

A deficient interferon response to SARS-CoV-2 infection has been implicated as a determinant of severe COVID-19. To identify the molecular effectors that govern interferon control of SARS-CoV-2 infection, we conducted a large-scale gain-of-function analysis that evaluated the impact of human interferon stimulated genes (ISGs) on viral replication. A limited subset of ISGs were found to control viral infection, including endosomal factors that inhibited viral entry, nucleic acid binding proteins that suppressed viral RNA synthesis, and a highly enriched cluster of ER and Golgi-resident ISGs that inhibited viral translation and egress. These included the type II integral membrane protein BST2/tetherin, which was found to impede viral release, and is targeted for immune evasion by SARS-CoV-2 Orf7a protein. Overall, these data define the molecular basis of early innate immune control of viral infection, which will facilitate the understanding of host determinants that impact disease severity and offer potential therapeutic strategies for COVID-19.

show abstract

“…Gene expression data of SARS-CoV-2 infected individuals were analyzed using discovery (11 subjects with mild or severe SARS-CoV-2, single cell gene expression, GEO: GSE149689), validation (100 subjects, bulk cell RNA-seq gene expression, GEO Accession: GSE157103 6 ) and cellular source (7 subjects, single cell gene expression, GEO accession: GSE150728 7 ) cohorts. All analyses were performed in R software (version 4.0.2) 12 .…”

Section: Methodsmentioning

confidence: 99%

A repurposed, blood gene signature is associated with poor outcomes in SARS-CoV-2

Juan-Guardela

Sun

Zhang

et al. 2020

Preprint

View full text Add to dashboard Cite

Poor outcomes after SARS-CoV-2 infection are difficult to predict. Survivors may develop pulmonary fibrosis. We previously identified a 52-gene signature in peripheral blood, predictive of mortality in Idiopathic Pulmonary Fibrosis. In this study, we analyzed this signature in SARS-CoV-2 infected individuals and identified genomic risk profiles with significant differences in outcomes. Analysis of single cell expression data shows that monocytes, red blood cells, neutrophils and dendritic cells are the cellular source of the high risk gene signature.

show abstract

Large-scale Multi-omic Analysis of COVID-19 Severity

Cited by 69 publications

References 103 publications

A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome

A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcome

Functional Landscape of SARS-CoV-2 Cellular Restriction

A repurposed, blood gene signature is associated with poor outcomes in SARS-CoV-2

Contact Info

Product

Resources

About