Causal associations of specific immunoglobulin G N-glycosylation subtypes with osteoporosis: A two-sample Mendelian randomization.

OBJECTIVES: This study aims to examine whether genetically predicted immunoglobulin G (IgG) N-glycosylation patterns (IGPs) affect osteoporosis risk using a two-sample Mendelian randomization (MR) method. MATERIALS AND METHODS: In a collaborative effort involving the Medical Research Council (MRC) Human Genetics Unit and the FinnGen consortium, we conducted genome-wide association studies (GWAS) to explore the relationship between 77 IGPs (8,090 samples) and osteoporosis (438,872 samples). Utilizing the inverse-variance weighted (IVW) method as our primary analytical tool, we delved into these complex genetic associations. To further substantiate our findings, we employed additional complementary methods such as MR-Egger, weighted median, and weighted mode. Sensitivity analyses, including MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), MR-Egger, Cochran's Q, and leave-one-out methods, were used to test the core MR assumptions and validate the robustness of the results. This multi-faceted approach allowed us to detect underlying causal relationships with greater confidence. RESULTS: The IGP4 exhibited a protective effect against osteoporosis with an odds ratio (OR) of 0.77 (95% confidence interval [CI]: 0.63-0.95, p=0.012). In contrast, IGP45 demonstrated a modest risk increase with an OR of 1.10 (95% CI: 1.01-1.19, p=0.021). Similarly, the results of the present MR study suggest that IGP56 also showed a protective trend, with an OR of 0.86 (95% CI: 0.78-0.96, p=0.006). To confirm our findings, we conducted rigorous sensitivity analyses utilizing MR-PRESSO, MR-Egger, Cochran's Q, and leave-one-out methods. These analyses revealed no evidence of heterogeneity or horizontal pleiotropy, thereby reinforcing the robustness and reliability of our findings. CONCLUSION: Our study results indicate that IgG45 contributes positively to osteoporosis, whereas IgG4 and IgG56 exhibit a negative correlation. Nonetheless, additional research is crucial to understand their mechanisms and devise broader preventive strategies for osteoporosis.