Novel Causal Evidence for the Role of Circulating Lipid Metabolites in Breast Cancer Risk: A Bidirectional Mendelian Randomization Analysis

<b>Background:</b> Dysregulated lipid metabolism has been implicated in breast cancer pathogenesis; however, the causal nature of these associations remains unclear. This study aimed to investigate the causal relationships between circulating lipid metabolites and the risk of estrogen receptor-positive (ER+) and ER-negative (ER-) breast cancer using a bidirectional Mendelian randomization (MR) approach. <b>Methods:</b> We evaluated 386 circulating lipid metabolites as exposures in two-sample MR analyses, with ER+ and ER- breast cancer as outcomes. Genetic instruments were selected based on genome-wide significance (<i>p</i> < 1 × 10^-5) and linkage disequilibrium clumping (<i>R</i> ² < 0.01 within a 1000 kb window). The inverse variance weighted method was used as the primary analytical approach. Sensitivity analyses-including MR-Egger regression, Cochran's <i>Q</i> test, and leave-one-out analyses-were conducted to assess pleiotropy and heterogeneity. Validation analyses were performed using an independent genome-wide association study (GWAS) dataset for ER+ breast cancer. Reverse MR analysis was also conducted to evaluate potential reverse causality. <b>Results:</b> Among the 386 lipid metabolites analyzed, 24 and 23 exhibited nominal associations (<i>p</i> < 0.05) with ER+ and ER- breast cancer, respectively. After applying false discovery rate (FDR) correction (FDR < 0.05), three metabolites-myristoleate (14:1n5), tricosanoyl sphingomyelin (d18:1/23:0), and 5α-androstan-3β, 17β-diol monosulfate (2)-remained significantly associated with an increased risk of ER+ breast cancer. In contrast, none of the associations with ER- breast cancer remained significant after FDR correction. Sensitivity analyses indicated no evidence of horizontal pleiotropy or heterogeneity, and the associations remained robust in leave-one-out analyses. These findings were further validated in an independent GWAS dataset. Moreover, reverse MR analysis found no evidence supporting a causal effect of ER+ breast cancer on the levels of the three identified lipid metabolites. <b>Conclusions:</b> This study provides robust genetic evidence supporting a causal role for specific lipid metabolites in the development of ER+ breast cancer. These metabolites may serve as potential biomarkers for early detection and targets for preventive interventions.