Viral Prognosis Using Proteomics

Abstract

So much was learned during the COVID-19 pandemic of 2020-2023. Some of the things that were learned were obvious. Many people in the public learned about social distancing, personal hygiene, and how to conduct a COVID-19 diagnostic test. Pharmaceutical companies and government organizations learned to efficiently work together to produce and distribute vaccines in record time. Although it may have generated controversy, the value in getting vaccinated was revalidated. There were other things that the world learned, although it was not as obvious. The effect of vaccination rate on preventing virus mutation became evident during the pandemic. The original SARS-CoV-2 virus that started the pandemic mutated several times over the course of the pandemic. One thing that became clear during the pandemic was the lack of knowledge on how SARS-CoV-2 infection would affect individuals during the course of the disease. This inability to accurately prognose the disease made it difficult to personalize treatments for specific individuals and the distribution of resources to protect the most vulnerable populations challenging. What is required to increase the accuracy of prognosis is more knowledge about how dynamic changes occur within the host cell during viral infection. Since many proteins become dysregulated during infection, proteomics is a prime technology for gaining this knowledge to increase prognostic capabilities and enable personalized treatments that alleviate the suffering viruses cause on humanity.

Keywords: Biological pathways; Biomarkers of long COVID; Disease severity; Host factors; Patient stratification; Prognostic biomarkers; Prognostic markers of COVID-19COVID-19; Viral factors; Prognosisprognosis.