Dysbiosis in Peripheral Blood Mononuclear Cell Virome Associated With Systemic Lupus Erythematosus - Guo, Gangqiang; Ye, Lele; Shi, Xinyu; Yan, Kejing; Huang, Jingjing; Lin, Kangming; Xing, Dong; Ye, Sisi; Wu, Yuqing; Li, Baoqing; Chen, Chaosheng; Xue, Xiangyang; et al. (Frontiers in Cellular and Infection Microbiology, 2020)
Objective. Pathogen infection plays a role in the development and progression of systemic lupus erythematosus (SLE). Previous studies showed that peripheral blood mononuclear cells (PBMCs) harbor many viral communities. However, little is known about the viral components and the expression profiles of SLE-associated virome. We aimed to identify viral taxonomic markers of SLE that might be used in the detection of disease or in predicting its outcome. Methods. Non-human sequence data from high-throughput transcriptome sequencing of PBMC samples from 10 SLE patients and 10 healthy individuals were used for taxonomic alignment against an integrated virome reference genome database. Based on abundance profiles of SLE-associated virome species, genera, or host, Random Forests model was used to identify the viruses associated with SLE diagnostic markers. Spearman’s correlation and functional clustering was used to analyze the interaction of candidate virome dysbiosis and SLE-associated differentially expressed genes. Results. A total of 419 viruses (38 human associated viruses, 350 phage, and 31 other viruses) was detected and the diversity of the PBMC virome was significantly increased in patients with SLE compared to the healthy controls (HCs). Viral taxa discriminated the cases from the controls, with an area under the receiver operating characteristic curve of 0.883, 0.695, and 0.540 for species, genus, and host, respectively. Clinical subgroup analysis showed that candidate PBMC viral markers were associated with stable- and active-stage SLE. Functional analyses showed that virome dysbiosis was mainly relevant to cellular and metabolic processes. Conclusion. We identified virome signatures associated with SLE, which might help develop tools to identify SLE patients or predict the disease stage.