Exploring the mechanisms of long COVID: Insights from computational analysis of SARS-CoV-2 gene expression and symptom associations.

Abstract

Long coronavirus disease(COVID) has emerged as a global health issue, affecting a substantial number of people worldwide. However, the underlying mechanisms that contribute to the persistence of symptoms in long COVID remain obscure, impeding the development of effective diagnostic and therapeutic interventions. In this study, we utilized computational methods to examine the gene expression profiles of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) infection and their associations with the wide range of symptoms observed in long COVID patients. Using a comprehensive data set comprising over 255 symptoms affecting multiple organ systems, we identified differentially expressed genesand investigated their functional similarity, leading to the identification of key genes with the potential to serve as biomarkers for long COVID. We identified the participation of hub genes associated with G-protein-coupled receptors (GPCRs), which are essential regulators of T-cell immunity and viral infection responses. Among the identified common genes were CTLA4, PTPN22, KIT, KRAS, NF1, RET, and CTNNB1, which play a crucial role in modulating T-cell immunity via GPCR and contribute to a variety of symptoms, including autoimmunity, cardiovascular disorders, dermatological manifestations, gastrointestinal complications, pulmonary impairments, reproductive and genitourinary dysfunctions, and endocrine abnormalities. GPCRs and associated genes are pivotal in immune regulation and cellular functions, and their dysregulation may contribute to the persistent immune responses, chronic inflammation, and tissue abnormalities observed in long COVID. Targeting GPCRs and their associated pathways could offer promising therapeutic strategies to manage symptoms and improve outcomes for those experiencing long COVID. However, the complex mechanisms underlying the condition require continued study to develop effective treatments. Our study has significant implications for understanding the molecular mechanisms underlying long COVID and for identifying potential therapeutic targets. In addition, we have developed a comprehensive website (https://longcovid.omicstutorials.com/) that provides a curated list of biomarker-identified genes and treatment recommendations for each specific disease, thereby facilitating informed clinical decision-making and improved patient management. Our study contributes to the understanding of this debilitating disease, paving the way for improved diagnostic precision, and individualized therapeutic interventions.