Introducing Markers which are Involved in COVID-19 Disease: Severe Condition Versus Mild State, a Network Analysis

AuthorVahid Mansourien
AuthorMostafa Rezaei-Taviranien
Authorfarshad okhovatianen
AuthorHojjat Allah Abbaszadehen
OrcidVahid Mansouri [0000-0002-3044-3342]en
OrcidMostafa Rezaei-Tavirani [0000-0003-1767-7475]en
Orcidfarshad okhovatian [0000-0003-3891-5647]en
OrcidHojjat Allah Abbaszadeh [0000-0002-7157-1834]en
Issued Date2021-12-31en
AbstractBackground: Coronavirus disease 2019 (COVID-19) had a pandemic spread worldwide. Most infected patients had a good prognosis, but some developed severe illnesses, which led to fatalities. It is urgent to define markers that reveal the severity of the disease. This study aimed to introduce the main plasma protein biomarkers involved in severe conditions versus mild infection states. Materials and Methods: A total of 91 significant differentially expressed proteins (DEPs) in the sera of the patients with the severe condition versus mild states were extracted from an original article. The protein interaction is included in a network designed via STRING database and Cytoscape software to find the critical proteins which differentiate severe conditions versus mild states. Results: A total of 6 hub nodes identified as critical target proteins were APOB, SERPINA1, CP, ORM1, HASPA8, and VW, according to the Degree value of nodes. Conclusion: The expression of different biomarkers in the sera of COVID-19 patients can be considered differential markers that separate severe conditions from mild states; however, a more thorough investigation is required. Keywords: COVID-19, Protein, Plasma, Biomarker, Network analysis ?en
DOIhttps://doi.org/10.22037/jcma.v6i4.35656en
URIhttps://brieflands.com/journals/jcma/articles/149740en
KeywordKey words: COVID-19en
KeywordProteinen
KeywordPlasmaen
KeywordBiomarkeren
KeywordNetwork analysisen
PublisherBrieflandsen
TitleIntroducing Markers which are Involved in COVID-19 Disease: Severe Condition Versus Mild State, a Network Analysisen
TypeOriginal Articlesen

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