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55 Causal association between 637 human metabolites and ovarian cancer: a mendelian randomization study
  1. Yedong Huang1,2,
  2. Wenyu Lin1,3 and
  3. Xiangqin Zheng1,2
  1. 1College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China
  2. 2Department of Gynecology, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, China
  3. 3Laboratory of Gynecologic Oncology, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, China


Introduction/Background Current evidence suggests a significant association between metabolites and ovarian cancer (OC); however, the causal relationship between the two remains unclear. This study employs Mendelian randomization (MR) to investigate the causal effects between different metabolites and OC.

Methodology In this study, a total of 637 metabolites were selected as the exposure variables from the Genome-wide Association Study (GWAS) database ( The OC related GWAS dataset (ieu-b-4963) was chosen as the outcome variable. R software and the Two-Sample Mendelian Randomization (TSMR) package were utilized for the analysis in this study. MR analysis employed the inverse variance-weighted method (IVW), MR-Egger and weighted median (WM) for regression fitting, taking into consideration potential biases caused by linkage disequilibrium and weak instrument variables. Metabolites that did not pass the tests for heterogeneity and horizontal pleiotropy were considered to have no significant causal effect on the outcome. Steiger’s upstream test was used to determine the causal direction between the exposure and outcome variables.

Results The results from IVW analysis revealed that a total of 31 human metabolites showed a significant causal effect on OC (P<0.05). Among them, 9 metabolites exhibited consistent and stable causal effects, which were confirmed by Steiger’s upstream test (P<0.05). Among these 9 metabolites, Androsterone sulfate, Propionylcarnitine, 5alpha-androstan-3beta,17beta-diol disulfate, Total lipids in medium VLDL and Concentration of medium VLDL particles demonstrated a significant positive causal effect on OC, indicating that these metabolites promote the occurrence of OC. On the other hand, X-12093, Octanoylcarnitine, N2,N2-dimethylguanosine, and Cis-4-decenoyl carnitine showed a significant negative causal association with OC, suggesting that these metabolites can inhibit the occurrence of OC.

Conclusion The study revealed the complex effect of metabolites on OC through Mendelian randomization. As promising biomarkers, these metabolites are worthy of further clinical validation.

Disclosures Ethics Approval and Consent to Participate

This analysis of publicly available data does not require ethical approval.

Consent for publication

All authors have given consent to the publication of this study.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Competing interests

The authors declare no conflict of interest.

Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author Contributions

Y.H. and W.L. contributed to the acquisition, analysis, and interpretation of data; and to drafting the article. X.Z. contributed to the critically revised the article for important intellectual content, and supervised the study. All authors have given their final approval of the version to be submitted.

Acknowledgements The authors acknowledge the efforts of the Genome-Wide Association Study (GWAS) database in providing high quality open resources for researchers.

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