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.