Systemic sclerosis is associated with specific alterations in gastrointestinal microbiota in two independent cohorts

Abstract

Objective: To compare faecal microbial composition in patients with systemic sclerosis (SSc) from 2 independent cohorts with controls and to determine whether certain genera are associated with SSc-gastrointestinal tract (GIT) symptoms.

Design: Adult patients with SSc from the University of California, Los Angeles (UCLA) and Oslo University Hospital (OUH) and healthy controls participated in this study (1:1:1). All participants provided stool specimens for 16S rRNA sequencing. Linear discriminant analysis effect size demonstrated genera with differential expression in SSc. Differential expression analysis for sequence count data identified specific genera associated with GIT symptoms as assessed by the GIT 2.0 questionnaire.

Results: The UCLA-SSc and OUH-SSc cohorts were similar in age (52.1 and 60.5 years, respectively), disease duration (median (IQR): 6.6 (2.5-16.4) and 7.0 (1.0-19.2) years, respectively), gender distribution (88% and 71%, respectively), and GIT symptoms (mean (SD) total GIT 2.0 scores of 0.7 (0.6) and 0.6 (0.5), respectively). Principal coordinate analysis illustrated significant microbial community differences between SSc and controls (UCLA: p=0.001; OUH: p=0.002). Patients with SSc had significantly lower levels of commensal genera deemed to protect against inflammation, such as Bacteroides (UCLA and OUH), Faecalibacterium (UCLA), Clostridium (OUH); and significantly higher levels of pathobiont genera, such as Fusobacterium (UCLA), compared with controls. Increased abundance of Clostridium was associated with less severe GIT symptoms in both cohorts.

Conclusions: The present analysis detected specific aberrations in the lower GIT microbiota of patients with SSc from 2 geographically and ethnically distinct cohorts. These findings suggest that GIT dysbiosis may be a pathological feature of the SSc disease state.

Keywords: AUTOIMMUNE DISEASE; INTESTINAL MICROBIOLOGY; SYSTEMIC SCLEROSIS.

Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1

Significant differences in the β diversity of the SSc and healthy samples as demonstrated by principal coordinate analysis plots of the weighted UniFrac distance. Each dot represents a sample from a UCLA-SSc cohort patient (open circle) or a healthy control (closed circle). Each star represents a sample from a OUH-SSc cohort patient. The p values provided were calculated by analysis of variance using distance matrices. OUH, Oslo University Hospital; PCoA, principle coordinate analysis; SSc, systemic sclerosis; UCLA, University of California, Los Angeles.

Figure 2

Microbial composition at the phylum level in UCLA-SSc samples (top left), OUH-SSc samples (top right) and healthy samples (bottom left). Legend provides colour coding specific to each phylum. OUH, Oslo University Hospital; SSc, systemic sclerosis; UCLA, University of California, Los Angeles.

Figure 3

Genus-level taxa associated with UCLA-SSc cohort patients versus healthy particiapnts. LefSe multivariate analysis was used to identify significant associations (q2.5 were included in this figure. LDA, linear discriminant analysis; LefSe, linear discriminant analysis effect size; SSc, systemic sclerosis; UCLA, University of California, Los Angeles.

Figure 4

Genus-level taxa associated with OUH-SSc cohort patients versus healthy participants. LefSe multivariate analysis was used to identify significant associations (q2.5 were included in this figure. LDA, linear discriminant analysis; LefSe, linear discriminant analysis effect size; OUH, Oslo University Hospital; SSc, systemic sclerosis.

Figure 5

Bacterial taxa associated with GIT disease score and domains. Patients were dichotomised into low (none-to-mild) or high (moderate to severe) disease severity groups for the total GIT 2.0 score and its individual domains (constipation, diarrhoea or distension/bloating). DESeq2 multivariate analysis was used to identify microbial taxa significantly associated with low versus high groups (online supplementary table S1), and calculate the fold change between groups. Negative fold change scores (log2) denote organisms decreased in high disease severity groups; whereas, positive fold change scores denote organisms increased in high disease severity groups. Legend provides colour code of bacterial taxa at the phylum level; ‘f” denotes family-level taxa. The size of the coloured dots represents the square root of the absolute mean counts of the OTUs at the genus level. DESeq2, differential expression analysis for sequence count data; GIT, gastrointestinal tract; OUT, operational taxonomic unit.