Exploratory multi-omics analysis reveals host-microbe interactions associated with disease severity in psoriatic skin

Early human evidence such as case series or small samples is exploring possible benefits.

• Level A · Stronger Clinical Evidence
• Level B · Emerging clinical evidence with positive signals
• Level C · Early human research exploring benefits
• Level D · Scientific groundwork from lab and animal studies
• Emerging · Emerging topic under active research

Abstract (original English)

Background Psoriasis (Pso) is a chronic inflammatory skin disease that poses both physical and psychological challenges. Dysbiosis of the skin microbiome has been implicated in Pso, yet a comprehensive multi-omics analysis of host-microbe interactions is still lacking. To bridge this gap, we conducted an exploratory study by adopting the integrated approach that combines whole metagenomic shotgun sequencing with skin transcriptomics. Methods This was a cross-sectional study, adult patients with plaque-type Psoriasis (Pso) and healthy volunteers were included. Skin microbiota samples and biopsies were collected from both lesional and non-lesional skin areas on the lower back. Weighted Gene Correlation Network Analysis (WGCNA) was employed for co-expression network analysis, and cell deconvolution was conducted to estimate cell fractions. Taxonomic and functional features of the microbiome were identified using whole metagenomic shotgun sequencing. Association between host genes and microbes was analyzed using Spearman correlation. Findings Host anti-viral responses and interferon-related networks were identified and correlated with the severity of psoriasis. The skin microbiome showed a greater prevalence of Corynebacterium simulans in the PASI severe-moderate groups, which correlated with interferon-induced host genes. Two distinct psoriatic clusters with varying disease severi

Evidence level

Early human evidence such as case series or small samples is exploring possible benefits.

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