Machine Learning to Identify Critical Biomarker Profiles in New SARS-CoV-2 Variants

Christoph Schatz; Ludwig Knabl; Hye Kyung Lee; Rita Seeboeck; Dorothee von Laer; Eliott Lafon; Wegene Borena; Harald Mangge; Florian Prüller; Adelina Qerimi; Doris Wilflingseder; Wilfried Posch; Johannes Haybaeck

doi:10.3390/microorganisms12040798

Machine Learning to Identify Critical Biomarker Profiles in New SARS-CoV-2 Variants

Christoph Schatz, Ludwig Knabl, Hye Kyung Lee, Rita Seeboeck, Dorothee von Laer, Eliott Lafon, Wegene Borena, Harald Mangge, Florian Prüller, Adelina Qerimi, Doris Wilflingseder, Wilfried Posch, Johannes Haybaeck

Institute of Clinical Pathology and Molecular Pathology of the Lower Austria Central Region (University Hospital St. Pölten)

Research output: Journal article (peer-reviewed) › Journal article

Abstract

The global dissemination of SARS-CoV-2 resulted in the emergence of several variants, including Alpha, Alpha + E484K, Beta, and Omicron. Our research integrated the study of eukaryotic translation factors and fundamental components in general protein synthesis with the analysis of SARS-CoV-2 variants and vaccination status. Utilizing statistical methods, we successfully differentiated between variants in infected individuals and, to a lesser extent, between vaccinated and non-vaccinated infected individuals, relying on the expression profiles of translation factors. Additionally, our investigation identified common causal relationships among the translation factors, shedding light on the interplay between SARS-CoV-2 variants and the host's translation machinery.

Original language	English
Article number	798
Journal	Microorganisms
Volume	12
Issue number	4
DOIs	https://doi.org/10.3390/microorganisms12040798
Publication status	Published - 15 Apr 2024

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10.3390/microorganisms12040798

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title = "Machine Learning to Identify Critical Biomarker Profiles in New SARS-CoV-2 Variants",

abstract = "The global dissemination of SARS-CoV-2 resulted in the emergence of several variants, including Alpha, Alpha + E484K, Beta, and Omicron. Our research integrated the study of eukaryotic translation factors and fundamental components in general protein synthesis with the analysis of SARS-CoV-2 variants and vaccination status. Utilizing statistical methods, we successfully differentiated between variants in infected individuals and, to a lesser extent, between vaccinated and non-vaccinated infected individuals, relying on the expression profiles of translation factors. Additionally, our investigation identified common causal relationships among the translation factors, shedding light on the interplay between SARS-CoV-2 variants and the host's translation machinery.",

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AU - Schatz, Christoph

AU - Knabl, Ludwig

AU - Lee, Hye Kyung

AU - Seeboeck, Rita

AU - von Laer, Dorothee

AU - Lafon, Eliott

AU - Borena, Wegene

AU - Mangge, Harald

AU - Prüller, Florian

AU - Qerimi, Adelina

AU - Wilflingseder, Doris

AU - Posch, Wilfried

AU - Haybaeck, Johannes

PY - 2024/4/15

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AB - The global dissemination of SARS-CoV-2 resulted in the emergence of several variants, including Alpha, Alpha + E484K, Beta, and Omicron. Our research integrated the study of eukaryotic translation factors and fundamental components in general protein synthesis with the analysis of SARS-CoV-2 variants and vaccination status. Utilizing statistical methods, we successfully differentiated between variants in infected individuals and, to a lesser extent, between vaccinated and non-vaccinated infected individuals, relying on the expression profiles of translation factors. Additionally, our investigation identified common causal relationships among the translation factors, shedding light on the interplay between SARS-CoV-2 variants and the host's translation machinery.

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U2 - 10.3390/microorganisms12040798

DO - 10.3390/microorganisms12040798

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JO - Microorganisms

JF - Microorganisms

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ER -

Machine Learning to Identify Critical Biomarker Profiles in New SARS-CoV-2 Variants

Abstract

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