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

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. 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.

Univ Med Ctr Maribor
Tyrolpath Obrist Brunhuber GmbH
Laborteam
NIDDK
St Vincent Hosp Zams
Medizinische Universität Innsbruck
Medizinische Universität Graz
Karl Landsteiner Privatuniversität für Gesundheitswissenschaften GmbH
Veterinärmedizinische Universität Wien
University of Maribor
National Institutes of Health (NIH) - USA
IMC Fachhochschule Krems