Biomarker-Based Risk Assessment Strategy for Long COVID: Leveraging Spike Protein and Pro-Inflammatory Mediators to Inform Broader Postinfection Sequelae

Long COVID, characterized by persistent symptoms following acute SARS-CoV-2 infection, has emerged as a significant public health challenge with wide-ranging clinical and socioeconomic implications. Developing an effective risk assessment strategy is essential for early identification and management of individuals susceptible to prolonged symptoms. This study uses a quantitative approach to characterize the dose-response relationships between spike protein concentrations and effects including Long COVID symptom numbers and release of proinflammatory mediators. A mathematical model is also developed to describe the time-dependent change of spike protein concentrations post diagnosis in twelve Long COVID patients with a cluster analysis. Based on the spike protein concentrationLong COVID symptom numbers relationship, we estimated a maximum symptom number (~20) that can be used to reflect a persistent predictor. We found that among the crucial biomarkers associated with Long COVID proinflammatory mediator, CXCL8 has the lowest 50% effective dose (0.01 μg mL-1), followed by IL-6 (0.39), IL-1β (0.46), and TNF-α (0.56). This work provides a comprehensive risk assessment strategy with developed dose-response tools and mathematical modeling to estimate potential spike protein concentration. Our study implicates a persistent Long COVID guideline for personalized care strategies and informs public health policies to support early interventions that reduce long-term disability and healthcare burdens with possibly other postinfection syndromes.