Supplementary Material for: Causal association of 91 circulating inflammatory proteins with allergic rhinitis: a Mendelian randomisation study

Abstract
Objective
Allergic rhinitis (AR) is a common chronic allergic inflammatory disease, and circulating inflammatory markers have been found to play an important role in the pathogenesis of allergic rhinitis. The aim of this study was to elucidate the causal relationship between 91 circulating inflammatory markers and AR using Mendelian randomisation (MR) analysis.
Method
The inverse variance weighted (IVW) approach to Mendelian randomisation analysis focuses on exploring causal relationships between exposures and outcomes using publicly available genetic variation from large genome-wide association studies (GWAS). That is, single nucleotide polymorphisms (SNPs) associated with 91 circulating inflammatory markers (14,824 participants of the European ancestry) were used as the exposure, and AR was used as the outcome variable with the aim of exploring the causal relationship between the 91 circulating inflammatory markers and AR. MR-Egger, weighted median (WM) and weighted models were employed as complementary methods to IVW in assessing the reliability of causal relationships.In addition, we utilised the MR robust adjusted profile score (MR-RAPS) method to fully assess Steiger's test was used to confirm whether the causal relationship between exposure and outcome was biased by reverse causality. Sensitivity analyses used Cochran's Q statistic and funnel plots to detect heterogeneity, and the MR-Egger intercept test and leave-one-out to assess horizontal multidimensionality.
Results
This study revealed a causal relationship between 91 circulating inflammatory markers and AR, especially DNER consistently presented as a risk factor for AR and TNF -beta levels consistently as a protective factor for AR. In addition, elevated levels of CCL19, CXCL11, CXCL5, DNER, IL - 18R1 , IL-17C, IL-6, IL-7, IL-4, and FGF19 may increase AR susceptibility. These results not only enhance our understanding of the pathological mechanisms of AR, but also provide potential biomarkers for risk assessment and intervention in clinical practice.
Conclusion
This MR analysis reinforces the importance of 91 circulating inflammatory markers in the diagnosis and prediction of AR. Future studies should further explore the mechanisms of action of these biomarkers and their potential as therapeutic targets for AR.