ArticleVirology journal2024
Integrating clinical data and genetic susceptibility to elucidate the relationship between systemic lupus erythematosus and human cytomegalovirus infection.
Article in Virology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundViral 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.
methodsUsing 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.
resultsIn 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).
conclusionThe 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.