Mendelian randomization of risk factors for premenstrual disorders

Abstract The causal role of established risk factors for premenstrual disorders (PMDs) remains unclear. We used Mendelian randomization (MR) to assess causality for eight known-risk factors identified through a literature review. Summary statistics for these risk factors were from genome-wide association studies (GWAS) with sample size ranging from 129,017 to 1.2 million, and for PMDs from a GWAS of 72,297 participants. Findings were validated using one-sample MR in LifeGene cohort ( n = 5674–5937). In two-sample MR, genetic liability to smoking initiation (OR = 1.25 (1.10–1.43)), earlier menarche (OR = 0.94 (0.89–0.98) per year), and higher BMI (OR = 1.19 (1.05–1.34) per kg/m 2 ) were associated with PMD risk. No causal association was indicated for anemia, childhood abuse, childhood asthma, diabetes, and endometriosis. In one-sample MR, point estimates for BMI (OR = 1.10 (0.88–1.38) per kg/m²) and earlier menarche (OR = 0.98 (0.83–1.15) per year) were directionally consistent with the two-sample MR findings, but the confidence intervals included null effects. However, a null association was observed for smoking (OR = 0.94 (0.77–1.16)). The two-sample MR supports causal role of earlier menarche, higher BMI, and smoking in risk of PMDs. The lack of replication in one-sample MR highlights the need for triangulating evidence from future well-powered and methodologically comparable studies to strengthen these findings.