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Arthritis Res Ther. 2019 Feb 6;21(1):49. doi: 10.1186/s13075-019-1816-z.

Microbiome dysbiosis is associated with disease duration and increased inflammatory gene expression in systemic sclerosis skin.

Author information

1
Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
2
Program in Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
3
Department of Environmental Health Science, University of South Carolina Arnold School of Public Health, Columbia, SC, USA.
4
Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
5
Division of Rheumatology, Arthritis Center, Boston University Medical Center, Boston, MA, USA.
6
Division of Rheumatology, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.
7
Division of Dermatology, University of California, San Francisco, USA.
8
Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA. Michael.L.Whitfield@Dartmouth.edu.
9
Program in Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Hanover, NH, USA. Michael.L.Whitfield@Dartmouth.edu.
10
Department of Biomedical Data Science, Program in Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Hanover, NH, USA. Michael.L.Whitfield@Dartmouth.edu.

Abstract

BACKGROUND:

Infectious agents have long been postulated to be disease triggers for systemic sclerosis (SSc), but a definitive link has not been found. Metagenomic analyses of high-throughput data allows for the unbiased identification of potential microbiome pathogens in skin biopsies of SSc patients and allows insight into the relationship with host gene expression.

METHODS:

We examined skin biopsies from a diverse cohort of 23 SSc patients (including lesional forearm and non-lesional back samples) by RNA-seq. Metagenomic filtering and annotation was performed using the Integrated Metagenomic Sequencing Analysis (IMSA). Associations between microbiome composition and gene expression were analyzed using single-sample gene set enrichment analysis (ssGSEA).

RESULTS:

We find the skin of SSc patients exhibits substantial changes in microbial composition relative to controls, characterized by sharp decreases in lipophilic taxa, such as Propionibacterium, combined with increases in a wide range of gram-negative taxa, including Burkholderia, Citrobacter, and Vibrio.

CONCLUSIONS:

Microbiome dysbiosis is associated with disease duration and increased inflammatory gene expression. These data provide a comprehensive portrait of the SSc skin microbiome and its association with local gene expression, which mirrors the molecular changes in lesional skin.

KEYWORDS:

Metagenomics; Microbiome; RNA-sequencing; Scleroderma; Systemic sclerosis

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