Characteristics of gut microbiota and serum metabolism in patients with atopic dermatitis

Abstract

Background: Atopic dermatitis (AD) is a chronic inflammatory skin disease that affects 15%-30% of children and 10% of adults globally, with its incidence being influenced by genetic, environmental, and various other factors. While the immune plays a crucial role in the development, the composition of gut microbiota and serum metabolites also contribute to its pathogenesis.

Subject: Study the characteristics of gut microbiota and serum metabolites in patients with atopic dermatitis METHOD: In this study, we collected stool and serum samples from 28 AD patients and 23 healthy individuals (NC) for metagenomic sequencing of gut microbiota and non-targeted metabolomic sequencing of serum.

Result: Our results revealed a lower diversity of gut microbiota in the AD group compared to the NC group. The predominant Phylum in AD patients were Bacteroidetes, Pseudomonas, and Verrucomicrobia, with the most dominant bacterial genus being Faecalibacterium. At the species level, Prevotella copri and Faecalibacterium prausnitzii were found to be the most abundant bacteria. Significant differences in serum metabolite profiles were observed between NC and AD patients, with noticeable variations in metabolite expression levels. The majority of metabolites in the serum of AD patients exhibited low expression, while a few showed high expression levels. Notably, metabolites such as Cholesterol glucuronide, Styrene, Lutein, Betaine, Phosphorylcholine, Taurine, and Creatinine displayed the most pronounced alterations.

Conclusion: These findings contribute to a further understanding of the complexities underlying this disease.

Keywords: atopic dermatitis; gut microbiota; metagenomics.

FIGURE 1

A schematic of the design and the experimental flow diagram.

FIGURE 2

The gut microbiome community is divided into two groups. (A) Rarefaction curves between the number of samples and the number of genes. In all samples, the number of genes approached saturation. (B) chao1 index, (C) Shannon index, (D)Simpson index, (E–G) The top 10 representative phyla, genera, and species as well as their proportions in each of the two groups, (H) A Venn diagram displaying group overlaps revealed that 325685 of the total richness of 2123609 genes were unique to AD. The blue circle represents AD, and the green circle represents NC.

FIGURE 3

Key species selection by LEfSe. Differential microbial score chart: the higher absolute value of the score, the greater the contribution of the microbe to the difference.

FIGURE 4

Cladogram generated from the LEfSe analysis indicating the phylogenetic distribution of the microbiota of AD and control groups from phylum to species.

FIGURE 5

Overview of altered serum metabolism in AD (n = 28) and NC (n = 23). (A) PLS‐DA shows the differences between the groups’ metabolites. (B) The two rightmost points in the figure are the actual R2Y and Q2 values of the model, and the remaining points are the R2Y and Q2 values obtained by randomly arranging the samples used. (C) Volcano plot, metabolites that differ between AD and NC.

FIGURE 6

The horizontal axis in the figure represents different experimental groups, and the vertical axis represents the differential metabolites compared within each group. The colored blocks at different positions represent the relative expression levels of corresponding metabolites at those positions, with red indicating high expression levels of the substance in the group and blue indicating low expression levels of the substance in the group.

FIGURE 7

The horizontal axis represents the Rich Factor corresponding to each pathway, and the vertical axis represents the name of the KEGG metabolic pathway. The size of the circles represents the number of differential metabolites enriched in that pathway.

FIGURE 8

The correlation analysis between Enterocloster bolteae and Ruminococcus_gnavus and significantly different metabolites.