Assessing the causal relationships between circulating metabolic biomarkers and breast cancer by using mendelian randomization.

Abstract

Objective: Previous studies have established a causal relationship between metabolites and breast cancer (BC), but the underlying mechanisms remain unclear. Thus, we aimed to investigate the genetic relationship between metabolites and BC, including its subtypes, using Mendelian randomization (MR) analysis.

Methods: Utilizing the latest and most comprehensive summary statistics from genome-wide association studies we conducted an Mendelian randomization study. Data on 233 metabolites, used as exposure variables, were obtained from a study involving 136,016 participants. BC data, used as outcome variables, were sourced from a study comprising 122,977 cases and 105,974 controls. We used the inverse-variance weighted method as the primary approach, along with three supplementary methods, to assess the causal relationship. We also used Cochran's Q test to detect heterogeneity and MR-Egger regression to examine the presence of horizontal pleiotropy.

Results: Upon analyzing 233 metabolites across 11 classes in relation to BC, we found six classes of metabolites (fatty acids glycerides and phospholipids, lipoprotein subclasses, lipids, apolipoproteins, and lipoprotein particle size) associated with overall BC. Five classes of metabolites (fatty acids glycerides and phospholipids, lipoprotein subclasses, lipids, and lipoprotein particle size) were related to estrogen receptor (ER) + BC, and eight classes of metabolites (fatty acids, amino acids, glycerides and phospholipids, lipoprotein subclasses, lipids, apolipoproteins, glycolysis-related metabolites, and lipoprotein particle size) were linked to ER- BC.

Conclusion: Our study demonstrates a genetic causal relationship between most metabolites and BC, confirming the link between these factors. This research provides a significant foundation for the prevention and treatment of BC.