Background
Increasing number of observational studies have associated mood instability to common female diseases, but the underlying causal relationship remains unclear. In this work, Mendelian randomization (MR) analysis was applied to explore the genetically predicted causal relationship of mood swings and several prevalent gynecological disorders.
Methods
Instrumental variables (IVs) of mood swings were selected from UK Biobank (UKB), with 204,412 cases and 247,207 controls being incorporated. The genetic variants for female disorders were obtained from genome-wide association studies (GWASs) and FinnGen consortium. To avoid biases caused by racial difference, only European population was included here. Five strong analytical methodologies were used to increase the validity of the results, the most substantial of which was the inverse variance weighting (IVW) method. Pleiotropy, sensitivity, and heterogeneity were assessed to strengthen the findings.
Results
We found mood swings was significantly positively associated with risk of endometrial cancer (OR = 2.60 [95%CI = 1.36, 4.95], P = 0.0037), cervical cancer (OR = 1.01[95%CI = 1.00,1.02], P = 0.0213) and endometriosis (OR = 2.58 [95%CI = 1.18, 5.60], P = 0.0170) by IVW method. However, there was no causal relationship between mood swing and ovarian cancer. No pleiotropy and heterogeneity existed and sensitivity tests were passed.
Conclusion
This study reveals genetically predicted causal relationships between mood swing and the risk of endometrial cancer, cervical cancer and endometriosis in European populations through MR analysis, which makes up for observational research's inherent limitations.