Publication: Plasma proteomics identify potential severity biomarkers from COVID-19 associated network
dc.contributor.department | Department of Molecular Biology and Genetics | |
dc.contributor.department | Department of Chemical and Biological Engineering | |
dc.contributor.department | Graduate School of Health Sciences | |
dc.contributor.department | Graduate School of Sciences and Engineering | |
dc.contributor.department | School of Medicine | |
dc.contributor.department | KUISCID (Koç University İşbank Center for Infectious Diseases) | |
dc.contributor.department | KUTTAM (Koç University Research Center for Translational Medicine) | |
dc.contributor.kuauthor | Akarlar, Büşra | |
dc.contributor.kuauthor | Can, Füsun | |
dc.contributor.kuauthor | Dadmand, Sina | |
dc.contributor.kuauthor | Küçük, Nazlı Ezgi Özkan | |
dc.contributor.kuauthor | Kuyucu, Gülin Özcan | |
dc.contributor.kuauthor | Şahin, Ayşe Tuğçe | |
dc.contributor.kuauthor | Şentürk, Aydanur | |
dc.contributor.kuauthor | Tunçbağ, Nurcan | |
dc.contributor.kuauthor | Yurtseven, Ali | |
dc.contributor.kuauthor | Ergönül, Önder | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.schoolcollegeinstitute | College of Sciences | |
dc.contributor.schoolcollegeinstitute | GRADUATE SCHOOL OF HEALTH SCIENCES | |
dc.contributor.schoolcollegeinstitute | GRADUATE SCHOOL OF SCIENCES AND ENGINEERING | |
dc.contributor.schoolcollegeinstitute | SCHOOL OF MEDICINE | |
dc.contributor.schoolcollegeinstitute | Research Center | |
dc.date.accessioned | 2024-11-09T23:58:35Z | |
dc.description.abstract | Purpose: Coronavirus disease 2019 (COVID-19) continues to threaten public health globally. Severe acute respiratory coronavirus type 2 (SARS-CoV-2) infection-dependent alterations in the host cell signaling network may unveil potential target proteins and pathways for therapeutic strategies. In this study, we aim to define early severity biomarkers and monitor altered pathways in the course of SARS-CoV-2 infection. Experimental Design: We systematically analyzed plasma proteomes of COVID-19 patients from Turkey by using mass spectrometry. Different severity grades (moderate, severe, and critical) and periods of disease (early, inflammatory, and recovery) are monitored. Significant alterations in protein expressions are used to reconstruct the COVID-19 associated network that was further extended to connect viral and host proteins. Results: Across all COVID-19 patients, 111 differentially expressed proteins were found, of which 28 proteins were unique to our study mainly enriching in immunoglobulin production. By monitoring different severity grades and periods of disease, CLEC3B, MST1, and ITIH2 were identified as potential early predictors of COVID-19 severity. Most importantly, we extended the COVID-19 associated network with viral proteins and showed the connectedness of viral proteins with human proteins. The most connected viral protein ORF8, which has a role in immune evasion, targets many host proteins tightly connected to the deregulated human plasma proteins. Conclusions and Clinical Relevance: Plasma proteomes from critical patients are intrinsically clustered in a distinct group than severe and moderate patients. Importantly, we did not recover any grouping based on the infection period, suggesting their distinct proteome even in the recovery phase. The new potential early severity markers can be further studied for their value in the clinics to monitor COVID-19 prognosis. Beyond the list of plasma proteins, our disease-associated network unravels altered pathways, and the possible therapeutic targets in SARS-CoV-2 infection by connecting human and viral proteins. Follow-up studies on the disease associated network that we propose here will be useful to determine molecular details of viral perturbation and to address how the infection affects human physiology. | |
dc.description.indexedby | WOS | |
dc.description.indexedby | Scopus | |
dc.description.indexedby | PubMed | |
dc.description.openaccess | YES | |
dc.description.sponsoredbyTubitakEu | N/A | |
dc.description.sponsorship | Royal Society Newton Advanced Fellowship [NA170389] | |
dc.description.sponsorship | Koc University Is Bank Center for Infectious Disease (KUISCID) Royal Society Newton Advanced Fellowship, Grant/Award Number: NA170389 | |
dc.description.sponsorship | Koc University Is Bank Center for Infectious Disease (KUISCID) | |
dc.identifier.doi | 10.1002/prca.202200070 | |
dc.identifier.eissn | 1862-8354 | |
dc.identifier.issn | 1862-8346 | |
dc.identifier.scopus | 2-s2.0-85140408507 | |
dc.identifier.uri | https://doi.org/10.1002/prca.202200070 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/15480 | |
dc.identifier.wos | 871772100001 | |
dc.keywords | Data integration | |
dc.keywords | Early severity biomarker | |
dc.keywords | Plasma proteome | |
dc.keywords | SARS-Cov-2 infection | |
dc.keywords | Turkey patient profile | |
dc.keywords | C-Reactive protein | |
dc.language.iso | eng | |
dc.publisher | Wiley-V C H Verlag Gmbh | |
dc.relation.ispartof | Proteomics Clinical Applications | |
dc.subject | Biochemical engineering | |
dc.subject | Biochemistry | |
dc.subject | Molecular biology | |
dc.title | Plasma proteomics identify potential severity biomarkers from COVID-19 associated network | |
dc.type | Journal Article | |
dspace.entity.type | Publication | |
local.contributor.kuauthor | Şahin, Ayşe Tuğçe | |
local.contributor.kuauthor | Yurtseven, Ali | |
local.contributor.kuauthor | Dadmand, Sina | |
local.contributor.kuauthor | Kuyucu, Gülin Özcan | |
local.contributor.kuauthor | Akarlar, Büşra | |
local.contributor.kuauthor | Küçük, Nazlı Ezgi Özkan | |
local.contributor.kuauthor | Şentürk, Aydanur | |
local.contributor.kuauthor | Ergönül, Mehmet Önder | |
local.contributor.kuauthor | Can, Füsun | |
local.contributor.kuauthor | Tunçbağ, Nurcan | |
local.contributor.kuauthor | Özlü, Nurhan | |
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