Skin microbiome and its association with host cofactors in determining atopic dermatitis severity

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Abstract

Background

Atopic dermatitis (AD) is a heterogeneous, chronic inflammatory skin disease linked to skin microbiome dysbiosis with reduced bacterial diversity and elevated relative abundance of Staphylococcus aureus ( S. aureus).

Objectives

We aimed to characterize the yet incompletely understood association between the skin microbiome and patients' demographic and clinical cofactors in relation to AD severity.

Methods

The skin microbiome in 48 adult moderate‐to‐severe AD patients was investigated using next‐generation deep sequencing (16S rRNA gene, V1–V3 region) followed by denoising (DADA2) to obtain amplicon sequence variant (ASV) composition.

Results

In lesional skin, AD severity was associated with S. aureus relative abundance ( r _S = 0.53, p < 0.001) and slightly better with the microbiome diversity measure Evenness ( r _S = −0.58, p < 0.001), but not with Richness. Multiple regression confirmed the association of AD severity with microbiome diversity, including Shannon (in lesional skin, p < 0.001), Evenness (in non‐lesional skin, p = 0.015) or S. aureus relative abundance ( p < 0.012), and with patient's IgE levels ( p < 0.001), race ( p < 0.032), age ( p < 0.034) and sex ( p = 0.012). The lesional model explained 62% of the variation in AD severity, and the non‐lesional model 50% of the variation.

Conclusions

Our results specify the frequently reported “reduced diversity” of the AD‐related skin microbiome to reduced Evenness, which was in turn mainly driven by S. aureus relative abundance, rather than to a reduced microbiome Richness. Finding associations between AD severity, the skin microbiome and patient's cofactors is a key aspect in developing new personalized AD treatments, particularly those targeting the AD microbiome.

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Most cited references 59

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DADA2: High resolution sample inference from Illumina amplicon data

Benjamin J. Callahan, Paul McMurdie, Michael Rosen … (2016)

We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

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Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

Evan Bolyen, Jai Rideout, Matthew Dillon … (2019)

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Is Open Access

Structure, Function and Diversity of the Healthy Human Microbiome

Tatiana Vishnivetskaya, Jeroen Raes (2014)

Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin, and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics, and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analyzed the largest cohort and set of distinct, clinically relevant body habitats to date. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families, and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology, and translational applications of the human microbiome.