Long COVID syndrome (LCS) is characterized by persistent multi-system manifestations with an unclear underlying pathophysiology. Identifying the genetic and immunological factors associated with LCS is essential for improved risk stratification and clinical management. This study investigated whether incorporating HLA-DRB1 and HLA-DQB1 genotyping data could enhance the predictive value of laboratory parameters for identifying individuals at higher risk of developing LCS. Demographic characteristics and relevant clinical history data were extracted from the medical records of 88 individuals diagnosed with LCS (LCS+) and 96 individuals without LCS (LCS-). Serum levels of anti-receptor binding domain IgG (anti-RBD IgG), anti-β2-glycoprotein I IgG (anti-β2GPI IgG), and C-reactive protein (CRP) were measured. Low-resolution genotyping was performed to identify HLA-DRB1 and HLA-DQB1 alleles. Logistic regression analysis was employed to examine the associations between HLA alleles and LCS status. Subsequently, mediation analysis was conducted to explore the potential mechanistic roles of anti-RBD IgG, CRP, and anti-β2GPI IgG in these observed relationships. The LCS+ group exhibited a significantly higher frequency of the HLA-DRB101 allele and a lower frequency of the HLA-DRB111 than the LCS- cohort. Serum levels of both CRP and anti-β2GPI IgG were substantially higher in the LCS+ cohort, whereas anti-RBD IgG levels were significantly lower. After adjusting for key variables, HLA-DRB101 and HLA-DRB111 remained significantly associated with LCS. Mediation analysis suggested that these HLA associations might be partially mediated by CRP, anti-RBD IgG, and anti-β2GPI IgG levels. Our findings indicate that the combination of HLA-DRB101 and HLA-DRB111 allele screening with serological profiling (anti-RBD IgG, CRP, and anti-β2GPI IgG) may contribute to refining predictive models of LCS susceptibility, though clinical utility requires validation in larger, independent cohorts.
Long Covid