Publication:
Plasma proteomics identify potential severity biomarkers from COVID-19 associated network

dc.contributor.departmentDepartment of Molecular Biology and Genetics
dc.contributor.departmentDepartment of Chemical and Biological Engineering
dc.contributor.departmentGraduate School of Health Sciences
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.departmentSchool of Medicine
dc.contributor.departmentKUISCID (Koç University İşbank Center for Infectious Diseases)
dc.contributor.departmentKUTTAM (Koç University Research Center for Translational Medicine)
dc.contributor.kuauthorAkarlar, Büşra
dc.contributor.kuauthorCan, Füsun
dc.contributor.kuauthorDadmand, Sina
dc.contributor.kuauthorKüçük, Nazlı Ezgi Özkan
dc.contributor.kuauthorKuyucu, Gülin Özcan
dc.contributor.kuauthorŞahin, Ayşe Tuğçe
dc.contributor.kuauthorŞentürk, Aydanur
dc.contributor.kuauthorTunçbağ, Nurcan
dc.contributor.kuauthorYurtseven, Ali
dc.contributor.kuauthorErgönül, Önder
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteCollege of Sciences
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF HEALTH SCIENCES
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.contributor.schoolcollegeinstituteSCHOOL OF MEDICINE
dc.contributor.schoolcollegeinstituteResearch Center
dc.date.accessioned2024-11-09T23:58:35Z
dc.description.abstractPurpose: 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.indexedbyWOS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.openaccessYES
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipRoyal Society Newton Advanced Fellowship [NA170389]
dc.description.sponsorshipKoc University Is Bank Center for Infectious Disease (KUISCID) Royal Society Newton Advanced Fellowship, Grant/Award Number: NA170389
dc.description.sponsorshipKoc University Is Bank Center for Infectious Disease (KUISCID)
dc.identifier.doi10.1002/prca.202200070
dc.identifier.eissn1862-8354
dc.identifier.issn1862-8346
dc.identifier.scopus2-s2.0-85140408507
dc.identifier.urihttps://doi.org/10.1002/prca.202200070
dc.identifier.urihttps://hdl.handle.net/20.500.14288/15480
dc.identifier.wos871772100001
dc.keywordsData integration
dc.keywordsEarly severity biomarker
dc.keywordsPlasma proteome
dc.keywordsSARS-Cov-2 infection
dc.keywordsTurkey patient profile
dc.keywordsC-Reactive protein
dc.language.isoeng
dc.publisherWiley-V C H Verlag Gmbh
dc.relation.ispartofProteomics Clinical Applications
dc.subjectBiochemical engineering
dc.subjectBiochemistry
dc.subjectMolecular biology
dc.titlePlasma proteomics identify potential severity biomarkers from COVID-19 associated network
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorŞahin, Ayşe Tuğçe
local.contributor.kuauthorYurtseven, Ali
local.contributor.kuauthorDadmand, Sina
local.contributor.kuauthorKuyucu, Gülin Özcan
local.contributor.kuauthorAkarlar, Büşra
local.contributor.kuauthorKüçük, Nazlı Ezgi Özkan
local.contributor.kuauthorŞentürk, Aydanur
local.contributor.kuauthorErgönül, Mehmet Önder
local.contributor.kuauthorCan, Füsun
local.contributor.kuauthorTunçbağ, Nurcan
local.contributor.kuauthorÖzlü, Nurhan
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