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Exploring the Role of Skin Microbiota in Autoimmune Skin Diseases from a Bidirectional Mendelian Randomization
Junlin Wang1, Xuejun Wang1, Xuanjie Tao2
1Department of Dermatology, Heilongjiang Academy of Traditional Chinese Medicine, Harbin, Heilongjiang, People's Republic of China.
Background:
The etiologies of psoriasis, localized scleroderma (LoS), and systemic lupus erythematosus (SLE) remain incompletely understood. Although skin microbiota are implicated in cutaneous immune homeostasis, their causal relationships with autoimmune skin diseases are unclear.
Objective:
To investigate bidirectional causal associations between skin microbiota and psoriasis, LoS, and SLE.
Methods:
Summary-level genome-wide association study (GWAS) data for 1656 skin microbiome traits were obtained from public resources, and GWAS data for psoriasis, LoS, and SLE were obtained from FinnGen version 9. Two-sample Mendelian randomization (MR) was performed using inverse-variance weighting as the primary method, supplemented by MR-Egger regression, weighted median, simple mode, weighted mode, heterogeneity tests, pleiotropy assessment, MR-PRESSO, and leave-one-out analysis.
Results:
Forward MR identified skin microbiota traits associated with the risk of psoriasis, LoS, and SLE. Specifically, 4, 5, and 5 microbiota traits were positively associated with these diseases, respectively, whereas 4, 3, and 8 traits were inversely associated. Reverse MR suggested that psoriasis, LoS, and SLE may also influence skin microbiota composition: psoriasis and LoS were associated with increased abundance of 4 and 1 microbiota traits, respectively, and psoriasis, LoS, and SLE were associated with reduced abundance of 8, 6, and 2 traits, respectively. Most significant associations showed no strong evidence of heterogeneity or horizontal pleiotropy.
Conclusion:
This bidirectional MR study provides genetic evidence supporting reciprocal relationships between skin microbiota and autoimmune skin diseases. The findings are exploratory and require replication in larger multi-ancestry cohorts and functional validation before clinical translation.
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