Introduction:
The associations between blood metabolites and breast cancer remain unclear. We conducted a systematic two-sample Mendelian randomization (MR) analysis to identify key human blood metabolites and uncover potential biomarkers for breast cancer development.

Material and methods:
The data were extracted from large-scale genome-wide association study (GWAS) public databases. Instrumental variables were selected from a cohort study of 453 metabolic profiles from 7,824 participants. Breast cancer incidence data were obtained from a large cohort study involving 138,389 cases and 240,341 controls. Causal associations between human blood metabolites and breast cancer incidence were assessed using inverse-variance weighting, and MR-Egger regression.

Results:
Five human blood metabolites were identified as biomarkers for breast cancer: serine (OR, 2.25; 95% CI: 1.18–4.27), 10-undecenoate (11:1n1) (OR, 1.38; 95% CI: 1.00–1.90), X-12696 (OR, 2.15; 95% CI: 1.14–4.08), X-14626 (OR, 1.68; 95% CI: 1.15–2.46), and succinyl carnitine (OR, 1.58; 95% CI: 1.06–2.34). The sensitivity analysis results indicate no pleiotropy between the metabolites and breast cancer risk, confirming the robustness of the findings.

Conclusions:
This study in metabolomics research identified five human blood metabolites — serine, 10-undecenoate (11:1n1), X-12696, X-14626, and succinylcarnitine — as potential biomarkers for assessing breast cancer risk. Among these metabolites, serine and X-12696 showed the strongest associations with the likelihood of developing breast cancer.