Disordered intestinal microbes are associated with the activity of Systemic Lupus Erythematosus. (2nd April 2019)

• Record Type: Journal Article
• Authors: Li, Yao; Wang, Hai-Fang; Li, Xin; Li, Hai-Xia; Zhang, Qiong; Zhou, Hong-Wei; He, Yan; Li, Pan; Fu, Chen; Zhang, Xiao-He; Qiu, Yu-Rong; Li, Ji-Liang
• Is Part Of: Clinical science. Volume 133:Number 7(2019)
• Page Start: 821
• Page End: 838
• Publication Date: 2019-04-02
• Subjects: disease activity -- gut microbiota -- PICRUSt -- Random forest -- Systemic lupus erythematosus; Medicine -- Periodicals; Biochemistry -- Periodicals; 616
• DOI: 10.1042/CS20180841
• Languages: English
• ISSNs: 0143-5221

Abstract

Abstract : Intestinal dysbiosis is implicated in Systemic Lupus Erythematosus (SLE). However, the evidence of gut microbiome changes in SLE is limited, and the association of changed gut microbiome with the activity of SLE, as well as its functional relevance with SLE still remains unknown. Here, we sequenced 16S rRNA amplicon on fecal samples from 40 SLE patients (19 active patients, 21 remissive patients), 20 disease controls (Rheumatoid Arthritis (RA) patients), and 22 healthy controls (HCs), and investigated the association of functional categories with taxonomic composition by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). We demonstrated SLE patients, particularly the active patients, had significant dysbiosis in gut microbiota with reduced bacterial diversity and biased community constitutions. Amongst the disordered microbiota, the genera Streptococcus, Campylobacter, Veillonella, the species anginosus and dispar, were positively correlated with lupus activity, while the genus Bifidobacterium was negatively associated with the disease activity. PICRUSt analysis showed metabolic pathways were different between SLE and HCs, and also between active and remissive SLE patients. Moreover, we revealed that a random forest model could distinguish SLE from RA and HCs (area under the curve (AUC) = 0.792), and another random forest model could well predict the activity of SLE patients (AUC = 0.811). In summary, SLE patients, especially the active patients, show an apparent dysbiosis in gut microbiota and its related metabolic pathways. Amongst the disordered microflora, four genera and two species are associated with lupus activity. Furthermore, the random forest models are able to diagnose SLE and predict disease activity.