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

Microorganisms. 2024 Apr 15;12(4):798. doi: 10.3390/microorganisms12040798.

Authors

Christoph Schatz^{1

2}, Ludwig Knabl¹, Hye Kyung Lee³, Rita Seeboeck^{4

5}, Dorothee von Laer⁶, Eliott Lafon⁷, Wegene Borena⁶, Harald Mangge⁸, Florian Prüller⁸, Adelina Qerimi², Doris Wilflingseder^{7

9}, Wilfried Posch⁷, Johannes Haybaeck^{10

11

12

13}

Affiliations

¹ Tyrolpath Obrist Brunhuber GmbH, 6311 Zams, Austria.
² Institute of Pathology, Neuropathology and Molecular Pathology, Medical University of Innsbruck, Muellerstrasse 44, 6020 Innsbruck, Austria.
³ Laboratory of Genetics and Physiology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
⁴ Department Life Sciences, IMC University of Applied Sciences Krems, 3500 Krems, Austria.
⁵ Clinical Institute of Pathology, University Hospital St. Poelten, Karl Landsteiner University of Health Science, 3100 St. Poelten, Austria.
⁶ Institute of Virology, Medical University of Innsbruck, Peter-Mayr-Strasse 4b, 6020 Innsbruck, Austria.
⁷ Institute of Hygiene and Medical Microbiology, Medical University of Innsbruck, Schöpfstrasse 41, 6020 Innsbruck, Austria.
⁸ Clinical Institute for Medical and Chemical Laboratory Diagnosis (CIMCL), Medical University of Graz, Auenbruggerplatz 15, 8036 Graz, Austria.
⁹ Department of Pathobiology, Infectiology, Veterinary University of Vienna, Veterinärplatz 1, 1210 Vienna, Austria.
¹⁰ Department of Pathology, Saint Vincent Hospital Zams, 6511 Zams, Austria.
¹¹ Diagnostic and Research Center for Molecular BioMedicine, Institute of Pathology, Medical University of Graz, 8010 Graz, Austria.
¹² Department of Pathology, Laborteam, 9403 Goldach, Switzerland.
¹³ Department of Pathology, University Medical Centre Maribor, 2000 Maribor, Slovenia.

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.

Keywords: Alpha; Alpha + E484K; Beta; F1 score; Omicron; PC algorithm; Restricted Boltzmann Machine neural network; SARS-CoV-2; machine learning; precision; recall; vaccination state; variants; z-scores.

Grants and funding

This work was supported in part (H.K.L. and L.K.) by the Intramural Research Programs (IRPs) of the National Institute of Diabetes and Digestive and Kidney Diseases, USA.