Dermatomyositis (DM) is a subtype of idiopathic inflammatory myopathies (IIM) and characterized by immune mediated proximal limb muscle injury and rash. The pathogenesis of DM has not been fully elucidated. Microbiome and metabolism disorders showed important roles in immune and inflammatory diseases, yet few studies dedicated in these changes of DM. In this study, we investigated DM patients’ fecal microbiome and metabolites, in seek of potential biomarkers of the disease. 

Stool samples were collected from 16 patients diagnosed DM according to 2017 EULAR/ACR classification criteria and 16 healthy controls. 16S rRNA gene sequencing and untargeted metabolomics were performed and compared between the DM group and the healthy group.

The Chao1 index of the DM group was significantly lower than that of the healthy group (Figure 1A, p=0.0017), suggesting that the estimated number of operational taxonomic units (OTUs) was reduced in patients with myopathies. The Shannon diversity of DM patients decreased significantly (Figure 1A, p=0.00016), indicating that the gut microbiota of healthy individuals was more diverse and evenly distributed. Principal Coordinates Analysis (PCoA) revealed that the gut microbiota of DM patients clustered together and were clearly distinguished from those of healthy controls (Figure 1A; adonis analysis, P=0.001, R²=0.16).

The gut microbiota composition of DM patients and healthy controls was compared at different taxonomic levels. The 16 DM patients had higher abundance of Bacteroidetes and lower abundance of Firmicutes, resulting in a significantly lower Firmicutes/Bacteroidetes (F/B) ratio in DM patients (Figure 1B, p=0.0015). In total, 25 differentially abundant microbiota were identified at the family level and 69 at the genus level (Figure 1C, p<0.05 in Wilcoxon rank sum test), indicating a large number of taxonomic changes.

We use linear discriminant analysis effect size (LEfSe) to look for the different microbiota that not only different in abundance, but also can discriminate disease group from health group. Microbes met the criteria both linear discriminant analysis (LDA) value > 4.0 and p value <0.05 were selected preliminary. Then we merge the same classification of microbes and removed genus abundance that was less than 1%. In conclusion, 5 microbes were identified as the most differentially changed microbes in DM, Blautia decreased and Bacteroides, Porphyromonadaceae, Lactobacillus, and Proteobacteria increased (Figure 1D). The area under the curve (AUC) of Blautia was 0.9688 (95% CI: 0.9057,1.0000), which is the biggest and close to 1.

Metabolic profiling was conducted by liquid chromatography-mass spectrometry (LC-MS). The Principal Component Analysis (PCA) showed that the metabolic profiles of the DM group and control group clustered separately (Figure 1E). Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) was further conducted in positive ion mode (R²Y=0.996, Q²=0.779) and negative ion mode (R²Y=0.979, Q²=0.787) (Figure 1E), confirming that the metabolic profiles of DM patients were significantly different from those of healthy controls.

A total of 74 significant differential metabolites were selected based on the criteria of p value ≤ 0.05 and Variable Importance in Projection (VIP) ≥ 1, among which 64 metabolites were decreased and 10 were increased in DM patients (Figure 1E). Three important metabolic pathways were screened out (FDR < 0.05 and Impact ≥ 0.1, MetaboAnalyst) that were related to fecal metabolic disturbances in DM patients: Aminoacyl-tRNA biosynthesis, Phenylalanine, tyrosine and tryptophan biosynthesis, and Phenylalanine metabolism (Figure 1F). Phenylacetylglycine was significantly decreased in DM patients (p<0.001) and had the largest AUC (0.957). This metabolite also showed the biggest association between Blautia (r=0.718) and hit the Phenylalanine metabolism pathway (Figure 1F).

Our study showed that, the microbe Blautia and the metabolic phenylacetylglycine in gut could be the biomarker of DM and might play a potential role to be explored of the disease in the future.