Proteomics

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Identification of serum prognostic biomarkers of severe COVID-19 using a quantitative proteomic approach

ABSTRACT: The COVID-19 pandemic is an unprecedented threat to humanity that has provoked global health concerns. Since the etiopathogenesis of this illness is not fully characterized, the prognostic factors enabling treatment decisions have not been well documented. Accurately predicting the progression of the disease would aid in appropriate patient categorization and thus help determine the best treatment option. Here, we have introduced a proteomic approach utilizing data-independent acquisition mass spectrometry (DIA-MS) to identify the serum proteins that are closely associated with COVID-19 prognosis. Twenty-seven proteins were differentially expressed between severely ill COVID-19 patients with an adverse or favorable prognosis.

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Yayoi Kimura 

PROVIDER: PXD021702 | JPOST Repository | Tue Nov 02 00:00:00 GMT 2021

REPOSITORIES: jPOST

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Action DRS
20200612QE_COVID_11_S_s_1.raw Raw
20200612QE_COVID_1_S_s_1.raw Raw
20200612QE_COVID_21_S_s_1.raw Raw
20200612QE_COVID_25_S_s_1.raw Raw
20200612QE_COVID_2_S_s_1.raw Raw
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The COVID-19 pandemic is an unprecedented threat to humanity that has provoked global health concerns. Since the etiopathogenesis of this illness is not fully characterized, the prognostic factors enabling treatment decisions have not been well documented. Accurately predicting the progression of the disease would aid in appropriate patient categorization and thus help determine the best treatment option. Here, we have introduced a proteomic approach utilizing data-independent acquisition mass s  ...[more]

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