Integrating clinical data and genetic susceptibility to elucidate the relationship between systemic lupus erythematosus and human cytomegalovirus infection

Abstract

Abstract Background Viral infections are known to induce the occurrence and pathogenesis of systemic lupus erythematosus (SLE). Previous studies have indicated a possible relationship between SLE and human cytomegalovirus (HCMV) infection and have attributed HCMV to be associated with various autoantibodies; however, these studies were constrained by variations in sample size and potential selection bias. Therefore, in the present study, we aimed to elucidate the relationship between HCMV and autoantibodies in patients with SLE by integrating clinical data and genetic susceptibility. Methods Using various statistical methods, we conducted a retrospective analysis of the spectrum of SLE autoantibodies and HCMV infections among patients hospitalized at our center over the past 10 years. Machine learning modeling was used to predict active HCMV infections based on the antinuclear (ANA) spectrum. Moreover, Mendelian randomization (MR) was used to investigate the causal relationship between SLE and HCMV infection. Results In the HCMV group, the levels of ANA, anti-dsDNA, anti-histone antibody (AHA), and anti-nucleosome antibody (ANuA) were significantly increased (P 0.05). Conclusion The ANA spectrum in patients with SLE can be used to predict HCMV infection status. Due to the inherent susceptibility of patients with SLE to HCMV infection, we propose for the first time that if a patient with SLE exhibits high serum titers of ANA, anti-dsDNA, ANuA, and AHA, caution should be exercised for HCMV infection, which can contribute to the clinical assessment of SLE and improve patient prognosis.

Keywords

• Systemic lupus erythematosus
• Human cytomegalovirus
• Autoantibody
• Genetic causality
• Retrospective analysis
• Prediction model