THU628 Causal Relationship Between The Menstrual Cycle Length And Basal Metabolic Rate: A Two-sample Mendelian Randomization Study

Disclosure: M. Kazemi: None. S.A. Parry: None. Long or irregular menstrual cycles, as a hallmark reproductive trait in polycystic ovary syndrome (PCOS), have been associated with aberrant energy expenditure, obesity, and cardiometabolic comorbidities. However, current observational studies addressing the contributions of energy expenditure to menstrual cyclicity have generated conflicting results and have not utilized the full extent of known single nucleotide polymorphisms associated with basal energy expenditure. Whether the relationship is causal is uncertain. We conducted a two-sample Mendelian Randomization study to interrogate the causal relationships between basal metabolic rate and length of menstrual cycles. The (MR) analyses were performed using publicly released genome-wide association studies (GWAS) statistics from 2 separate European cohorts using the UK Biobank database. The inverse-variance weighted (IVW) method was used as the primary analysis. We applied four complementary methods, including weighted median, weighted mode, MR-Egger regression, and MR pleiotropy residual sum and outlier (MR-PRESSO), to detect and correct the effect of horizontal pleiotropy. The result of the IVM method revealed that genetically determined basal metabolic rate has an inverse causal effect on the length of the menstrual cycle (β, -0.13, SE, 0.03; P=2.17 E-05). The results of MR-Egger regression, weighted median, and weighted mode methods were consistent with those of the IVW method. Sensitivity analyses revealed that horizontal pleiotropy was unlikely to distort the causal estimates. Collectively, our MR analysis revealed that basal metabolic rate appears to be causally affecting the length of menstrual cycles. Our findings reflect novel insights into the role of energy metabolism on menstrual disturbances. However, the molecular mechanisms should be investigated. Future MR analysis is warranted to confirm our findings by controlling for potentially relevant confounders, including obesity and age. Nevertheless, our findings have perturbations to elucidate causal pathways explaining obesity in relevant conditions, including PCOS. Presentation: Thursday, June 15, 2023