Causal inference study of the effect of serum enzymes on breast cancer risk: Two-sample Mendelian randomization

Breast cancer (BC) has the highest cancer incidence and mortality in women worldwide, and the relationship between serum enzymes and BC has been inconsistent in previous observational studies. In this paper, 2-sample Mendelian randomization (MR) is used to clarify the causal relationship between them. The serum enzymes in 216,026 study subjects from Finnish heritage subjects as the exposure data. The BC included 212,402 study subjects in United Kingdom Biobank as the result data. We performed univariable MR with 5 MR methods inverse variance weighted, MR-Egger regression, weighted median, simple mode, and weighted mode and multivariable MR to estimate the effect of serum enzymes independent of BC. Finally, we performed a series of sensitivity analyses as validation of primary MR results. The single nucleotide polymorphisms screened in this study were mostly strong effect instrumental variables. A total of 5 forest plot model results indicate that abnormal serum enzyme levels have a significant causal relationship with BC. MR analysis of different models of abnormal serum enzyme levels gave consistent direction estimates, and their slopes were relatively consistent. Serum enzyme indicators did not consider heterogeneity in the MR results of BC (Cochran Q P value > .05, I 2 < 50%). MR-Egger's results show that there is no effect of pleiotropy(P ≥ .05, intercepts were close to 0). Sensitivity analysis showed that no significant change in the estimated effect value of abnormal serum enzyme levels was found, indicating the stability of the results. inverse variance weighted model results indicate that BC has no causal effect on abnormal serum enzyme levels (P value > .05). The results of multivariate MR showed that serum enzyme indicators still have a significant direct effect on BC. Our findings suggest that a significant statistical causal association between abnormal serum enzyme levels and the risk of BC. Abnormal serum enzyme levels have important clinical implications and might be used as BC risk.

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Publication Details

Journal
Medicine
Published
2026-06-26
DOI
https://doi.org/10.1097/md.0000000000049516
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

Causal inference study of the effect of serum enzymes on breast cancer risk: Two-sample Mendelian randomization

Bing Xia, Jiani Wang, Cheng Zeng, JIA Xiaohui et al.
Medicine
Genetic Associations and Epidemiology
article

Causal inference study of the effect of serum enzymes on breast cancer risk: Two-sample Mendelian randomization

Bing Xia, Jiani Wang, Cheng Zeng, JIA Xiaohui, L H Zhao, Keliang Cui
article en

Abstract

Breast cancer (BC) has the highest cancer incidence and mortality in women worldwide, and the relationship between serum enzymes and BC has been inconsistent in previous observational studies. In this paper, 2-sample Mendelian randomization (MR) is used to clarify the causal relationship between them. The serum enzymes in 216,026 study subjects from Finnish heritage subjects as the exposure data. The BC included 212,402 study subjects in United Kingdom Biobank as the result data. We performed univariable MR with 5 MR methods inverse variance weighted, MR-Egger regression, weighted median, simple mode, and weighted mode and multivariable MR to estimate the effect of serum enzymes independent of BC. Finally, we performed a series of sensitivity analyses as validation of primary MR results. The single nucleotide polymorphisms screened in this study were mostly strong effect instrumental variables. A total of 5 forest plot model results indicate that abnormal serum enzyme levels have a significant causal relationship with BC. MR analysis of different models of abnormal serum enzyme levels gave consistent direction estimates, and their slopes were relatively consistent. Serum enzyme indicators did not consider heterogeneity in the MR results of BC (Cochran Q P value > .05, I 2 < 50%). MR-Egger's results show that there is no effect of pleiotropy(P ≥ .05, intercepts were close to 0). Sensitivity analysis showed that no significant change in the estimated effect value of abnormal serum enzyme levels was found, indicating the stability of the results. inverse variance weighted model results indicate that BC has no causal effect on abnormal serum enzyme levels (P value > .05). The results of multivariate MR showed that serum enzyme indicators still have a significant direct effect on BC. Our findings suggest that a significant statistical causal association between abnormal serum enzyme levels and the risk of BC. Abnormal serum enzyme levels have important clinical implications and might be used as BC risk.

MedicineVol. 105(26)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Tianjin Medical University Cancer Institute and Hospital (CN), National Cancer Center (US)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 7%
Genetic Associations and Epidemiology
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