Skin microbiome and causal relationships in three dermatological diseases: Evidence from Mendelian randomization and Bayesian weighting.

Abstract

Background: Atopic dermatitis (AD), psoriasis (PSO), rosacea, and other related immune skin diseases are affected by multiple complex factors such as genetic and microbial components. This research investigates the causal relationships between specific skin microbiota and these diseases by using Mendelian randomization (MR), and Bayesian weighted Mendelian randomization (BWMR).

Methods: We utilized genome-wide association study (GWAS) data to analyze the associations between various skin bacteria and three dermatological diseases. Single nucleotide polymorphisms (SNPs) served as instrumental variables (IVs) in MR methods, including inverse variance weighted (IVW), and MR Egger. BWMR was employed to validate results and address pleiotropy.

Results: The IVW analysis identified significant associations between specific skin microbiota and dermatological diseases. ASV006_Dry, ASV076_Dry, and Haemophilus_Dry were significantly positively associated with AD, whereas Kocuria_Dry was negatively associated. In PSO, ASV005_Dry was negatively associated, whereas ASV004_Dry, Rothia_Dry, and Streptococcus_Moist showed positive associations. For rosacea, ASV023_Dry was significantly positively associated, while ASV016_Moist, Finegoldia_Dry, and Rhodobacteraceae_Moist were significantly negatively associated. These results were corroborated by BWMR analysis.

Conclusion: Bacterial species such as Finegoldia, Rothia, and Streptococcus play crucial roles in the pathogenesis of AD, PSO, and rosacea. Understanding these microbial interactions can aid in developing targeted treatments and preventive strategies, enhancing patient outcomes and quality of life.