A SYSTEMS BIOLOGY APPROACH TO MODELING IMMUNE DYSREGULATION IN LONG COVID PATIENTS: INTEGRATING SINGLE-CELL TRANSCRIPTOMICS, CYTOKINE NETWORKS, AND CLINICAL TRAJECTORIES

Abstract

COVID is a complex, multisystem condition with persistent symptoms following SARS-CoV-2 infection. This study aimed to characterize its biological, cognitive, and psychosocial dimensions using a mixed-methods experimental design. A cohort of 320 post-COVID-19 individuals was assessed through quantitative biomarker analysis (CRP, IL-6, TNF-α), cognitive testing (MoCA), and symptom inventories. Semi-structured interviews (n = 60) provided qualitative data analyzed via thematic coding. Statistical models including logistic regression and Cox proportional hazards were used to evaluate risk factors. Data triangulation enabled integrative interpretation. Elevated inflammatory markers (mean IL-6 = 6.2 pg/mL; CRP = 4.1 mg/L) were significantly associated with fatigue and dyspnea severity (p < 0.01). Cognitive impairment was observed in 61% of participants, correlating with higher IL-6 and lower MoCA scores. Thematic analysis identified psychosocial stressors including economic loss and stigma. Clustering revealed inflammatory and neurocognitive phenotypes. Vaccinated individuals exhibited reduced biomarker loads and fewer persistent symptoms. Integrated data pointed to systemic immune dysregulation as a core mechanism of Long COVID. Long COVID represents a biologically grounded, multifaceted syndrome requiring precision diagnostics and multidisciplinary care. The study’s findings support the development of biomarker-based criteria and long-term rehabilitation strategies for affected individuals.