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Journal of neuroinflammation · 2026

Genetically predicted susceptibility to dust-induced lung diseases and risk of autoimmune diseases: a two sample Mendelian randomization study.

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Kim Youjin, Sumikawa Maiko Hajime, Lee Wanhyung, Lee Seunghyun

Аннотация

BACKGROUND: Observational studies have linked occupational and environmental dust exposure to increased risk of autoimmune diseases (AIDs). However, it remains unclear whether genetic susceptibility to dust-induced lung pathology has a causal effect on AID risk. This study aimed to determine whether genetic susceptibility to dust-induced lung diseases causally influences AIDs risk using Mendelian randomization (MR). METHODS: We conducted a two-sample MR analysis using genetic variants associated with lung diseases due to external agents (ICD-10 J60-J70; FinnGen, n = 500,348), and AIDs (UK Biobank, n = 53,831). Analyses included inverse variance weighting (IVW), MR-Egger, and weighted median methods, complemented by sensitivity analyses for heterogeneity and pleiotropy. Bonferroni and false discovery rate (FDR) corrections were applied to account for multiple testing. RESULTS: Genetically predicted susceptibility to dust-induced lung diseases showed largely null effects for most AIDs. A suggestive association was observed for ankylosing spondylitis (AS) in the primary analysis (IVW OR 1.39, 95% CI 1.05–1.84), but became non-significant after Bonferroni and FDR corrections. Sensitivity analyses did not reveal strong evidence of horizontal pleiotropy. Thus, while a potential signal exists for AS, no robust causal effects were identified for other AIDs. CONCLUSIONS: In our study, susceptibility to dust-induced lung diseases was not robustly associated with most AIDs, but showed a suggestive disease-specific signal for AS, plausibly mediated by lung inflammation and remodeling. Other AIDs may rely on alternative systemic pathways independent of overt lung damage. Our findings highlight the mechanistic heterogeneity in dust-related autoimmunity and should be interpreted as hypothesis-generating, warranting validation in independent, larger cohorts.

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