Ankylosing spondylitis status and risk of secondary systemic amyloidosis: A two-sample mendelian randomization study.

OBJECTIVES

There is still controversy regarding the causal relationship between ankylosing spondylitis (AS) and secondary systemic amyloidosis (SSA). This study utilized aggregated data from genome-wide association studies (GWAS) on population cohorts to investigate whether a causal relationship exists between AS and SSA.

METHODS

The genetic causal relationship between AS status and SSA was analyzed utilizing a two-sample Mendelian randomization (TSMR). The analyses were conducted using the weighted mode method (WM2), inverse variance weighted method (IVW), simple mode (SM), weighted median method (WM1), and Mendelian randomization Egger regression (MR-Egger). Among these methods, the primary results were based on the IVW approach. The association was evaluated using the odds ratio (OR) along with a 95% confidence interval (95% CI).

RESULTS

The IVW analysis revealed a positive causal relationship between AS status and SSA (OR = 1.411, 95 % CI = 1.069, 1.862, P = 0.015). Meanwhile, the WM1 (OR = 1.394, 95 % CI = 1.115, 1.742, P = 0.004) and WM2 (OR = 1.393, 95 % CI = 1.112, 1.743, P = 0.045) methods also identified a positive causal relationship between AS status and SSA. The MR-Egger method did not identify a causal relationship between AS and SSA (OR = 1.175, 95 % CI = 0.888, 1.555, P = 0.342). The SM results demonstrated that the observed genotypes did not exhibit statistically significant differences between AS and SSA (OR = 1.184, 95 % CI = 0.416, 3.366, P = 0.767). The results of the MR-Egger regression suggested that the results were unaffected by bias caused by genetic pleiotropy (Intercept = 0.283, SE = 0.134, P = 0.126). Cochran's Q test did not reveal any significant heterogeneity (Q = 1.759, P = 0.624). The "leave-one-out" analysis further confirmed that the absence of any single SNP did not impact the robustness of our results.

CONCLUSION

This study revealed a positive causal relationship between AS status and the occurrence of SSA, providing new insights into the genetic analysis of SSA.