Trans-ethnic Mendelian randomization study of systemic lupus erythematosus and common female hormone-dependent...

Observational research has reported that systemic lupus erythematosus (SLE) is related to common female hormone-dependent cancers, but the underlying causal effect remains undefined. This study aimed to explore the causal association of these conditions by Mendelian randomization (MR) analysis.

We selected instrumental variables for SLE from genome-wide association studies (GWASs) conducted in European and East Asian populations. The genetic variants for female malignant neoplasms were obtained from corresponding ancestry GWASs. We utilized inverse variance weighted (IVW) as the primary analysis, followed by sensitivity analysis. Furthermore, we conducted multivariable MR (MVMR) to estimate direct effects by adjusting for the body mass index and estradiol. Finally, we implemented reverse direction MR analysis and gave a negative example to test the reliability of MR results.

We found SLE was significantly negatively associated with overall endometrial cancer risk (odds ratio [OR] = 0.961, 95% confidence interval [CI] = 0.935-0.987, P  = 3.57E-03) and moderately inversely related to endometrioid endometrial cancer (ENEC) (OR = 0.965, 95% CI = 0.936-0.995, P  = 0.024) risk in the European population by IVW. We replicated these results using other MR models and detected a direct effect by MVMR (overall endometrial cancer, OR = 0.962, 95% CI = 0.941-0.983, P  = 5.11E-04; ENEC, OR = 0.964, 95% CI = 0.940-0.989, P  = 0.005). Moreover, we revealed that SLE was correlated with decreased breast cancer risk (OR = 0.951, 95% CI = 0.918-0.986, P  = 0.006) in the East Asian population by IVW, and the effect was still significant in MVMR (OR = 0.934, 95% CI = 0.859-0.976, P  = 0.002). The statistical powers of positive MR results were all >0.9.

This finding suggests a possible causal effect of SLE on the risk of overall endometrial cancer and breast cancer in European and East Asian populations, respectively, by MR analysis, which compensates for inherent limitations of observational research.