Open Access
01-12-2024 | Human Cytomegalovirus | Research
Integrating clinical data and genetic susceptibility to elucidate the relationship between systemic lupus erythematosus and human cytomegalovirus infection
Authors:
Xin Luo, Liuliu Quan, Qingting Lin, Huiteng Rong, Yue Liu, Jiaqi Meng, Xin You
Published in:
Virology Journal
|
Issue 1/2024
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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 < 0.001) and were linked to the presence of CMV-pp65-antigen-positive polymorphonuclear leukocytes (P < 0.001). A weak correlation was observed between the titers of anti-CMV IgM and ANA (P < 0.001). The ANA spectrum demonstrated a strong predictive performance for active HCMV infection based on principal component analysis (Adonis and ANOSIM P < 0.001) as well as support vector machine and extreme gradient boosting modeling. MR analyses of inverse-variance weighted, weighted mean, MR-Egger, and weighted mode revealed that patients with SLE were at a higher risk of developing HCMV infection (P < 0.05). However, HCMV infection did not have a causal effect on SLE (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.