ArticleVirology journal2026
Viral metagenomic analysis of the blood virome in patients with multiple autoimmune diseases.
Article in Virology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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12 authors.
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Abstract
Autoimmune diseases are chronic and heterogeneous disorders resulting from the breakdown of immune tolerance and subsequent tissue damage. Beyond genetic predisposition, viral infections are increasingly recognized as pivotal environmental contributors to disease onset. In this study, we performed comprehensive viral metagenomic profiling of blood samples from 205 patients with systemic lupus erythematosus (SLE), Sjögren's syndrome (SS), ankylosing spondylitis (AS), and undifferentiated connective tissue disease (UCTD). A total of approximately 103.98 million sequencing reads were analyzed, revealing 44 viral families, including 30 DNA and 14 RNA families. RNA viruses dominated the virome composition, accounting for 71% of total reads, with Picobirnaviridae being consistently prevalent and abundant across all disease groups. Alpha and beta diversity analyses revealed significant heterogeneity in viral community structures among different disease groups, with a marked diversity skew observed in the SS group. Disease-specific viral composition patterns were prominent, and the number of core viral species shared across the four groups was limited. Of particular note, Anelloviridae was significantly enriched in the AS and UCTD groups, suggesting its potential as a biomarker for immunosuppressive states. Furthermore, bacteriophages such as Microviridae exhibited differential abundance across groups, reflecting the potential role of virus-microbe-host immune interactions in disease pathogenesis. In conclusion, this study provides a comprehensive profile of the blood virome in four autoimmune diseases, highlighting the potential role of viral communities in immune regulation and offering new perspectives for the development of related biomarkers.
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