Potential Plasma Proteins (LGALS9, LAMP3, PRSS8 and AGRN) as Predictors of Hospitalisation Risk in COVID-19 Patients

Potential Plasma Proteins (LGALS9, LAMP3, PRSS8 and AGRN) as Predictors of Hospitalisation Risk in COVID-19 Patients

<i>Background:</i> The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has posed unprecedented challenges to healthcare systems worldwide. Here, we have identified proteomic and genetic signatures for improved prognosis which is vital for COVID-19 research. <i>Method...

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Main Authors: Thomas McLarnon, Darren McDaid, Seodhna M. Lynch, Eamonn Cooper, Joseph McLaughlin, Victoria E. McGilligan, Steven Watterson, Priyank Shukla, Shu-Dong Zhang, Magda Bucholc, Andrew English, Aaron Peace, Maurice O’Kane, Martin Kelly, Manav Bhavsar, Elaine K. Murray, David S. Gibson, Colum P. Walsh, Anthony J. Bjourson, Taranjit Singh Rai
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Biomolecules
Subjects:
SARS-CoV-2
COVID-19
biomarker
LGALS9
LAMP3
PRSS8
Online Access:https://www.mdpi.com/2218-273X/14/9/1163
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Summary:<i>Background:</i> The COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, has posed unprecedented challenges to healthcare systems worldwide. Here, we have identified proteomic and genetic signatures for improved prognosis which is vital for COVID-19 research. <i>Methods:</i> We investigated the proteomic and genomic profile of COVID-19-positive patients (n = 400 for proteomics, n = 483 for genomics), focusing on differential regulation between hospitalised and non-hospitalised COVID-19 patients. Signatures had their predictive capabilities tested using independent machine learning models such as Support Vector Machine (SVM), Random Forest (RF) and Logistic Regression (LR). <i>Results:</i> This study has identified 224 differentially expressed proteins involved in various inflammatory and immunological pathways in hospitalised COVID-19 patients compared to non-hospitalised COVID-19 patients. LGALS9 (<i>p</i>-value < 0.001), LAMP3 (<i>p</i>-value < 0.001), PRSS8 (<i>p</i>-value < 0.001) and AGRN (<i>p</i>-value < 0.001) were identified as the most statistically significant proteins. Several hundred rsIDs were queried across the top 10 significant signatures, identifying three significant SNPs on the <i>FSTL3</i> gene showing a correlation with hospitalisation status. <i>Conclusions:</i> Our study has not only identified key signatures of COVID-19 patients with worsened health but has also demonstrated their predictive capabilities as potential biomarkers, which suggests a staple role in the worsened health effects caused by COVID-19.
ISSN:2218-273X

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