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Publications

Journal Article Journal Article Epublish

PubMed: 40751201 DOI: 10.1186/s13048-025-01733-z

Exploring causal relationships between brain imaging-derived phenotypes and ovarian cancer risk: a bidirectional Mendelian randomization.

J Ovarian Res 18(1):173

Authors: Ting Liu, Xiaoqian Tuo, Huifang Zhao, Yan Wang, Yu Jiang, Jiaojiao Lu

Affiliations

  • Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, People's Republic of China.
  • Department of Gynecology, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, 710061, People's Republic of China.
  • Department of Gynecology and Obstetrics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, People's Republic of China.
  • Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, 710061, People's Republic of China.

Abstract

BACKGROUND

Ovarian cancer could induce alterations in both structure and function of the brain. This study employs Mendelian randomization (MR) to investigate the causal relationship between brain imaging-derived phenotypes (IDPs) and ovarian cancer, offering new insights into the potential clinical applications of IDPs for ovarian cancer risk assessment.

METHODS

This study identified 587 brain IDPs using structural and diffusion magnetic resonance imaging (MRI) data from the UK Biobank and data were sourced from two independent Genome-Wide Association Studies (GWAS). We selected single nucleotide polymorphisms (SNPs) as instrumental variables based on rigorous criteria. To evaluate the causal effects of IDPs on the risk of ovarian cancer, we employed five MR models: Inverse Variance Weighted (IVW), MR-Egger regression, Weighted median, Weighted mode, and Simple mode. Furthermore, we conducted a meta-analysis to provide additional validation for our results.

RESULTS

Forward MR analysis identified 72 IDPs that were significantly associated with the risk of ovarian cancer, with 65 remaining robust after conducting sensitivity tests. Conversely, reverse MR analysis indicated that 63 IDPs were influenced by ovarian cancer, highlighting a bidirectional causal relationship between these factors. The meta-analysis revealed that an increased cortical surface area of the right precentral gyrus was associated with a heightened risk of ovarian cancer, with an odds ratio (OR) of 1.139 (95% confidence interval [CI]: 1.037-1.250, P = 0.006, common effect model). In contrast, a larger volume of the right medial orbital frontal cortex was linked to a reduced risk of ovarian cancer, with an OR of 0.839 (95% CI: 0.744-0.946, P = 0.004, common effect model). Additionally, in the reverse MR analysis, a higher risk of ovarian cancer was associated with an increased fractional anisotropy (FA) in the right fornix and stria terminalis, while decreased orientation dispersion index (OD) in the left anterior corona radiata.

CONCLUSIONS

This study provides compelling evidence of a causal relationship between IDPs and ovarian cancer risk. It suggests that IDPs might serve as valuable biomarkers for ovarian cancer risk assessment at brain-imaging levels and emphasize the need for further research to explore the biological mechanisms underlying these associations.

MeSH

Risk Assessment, Ovary, Brain, Neoplasms, Phenotype, Ovarian Neoplasms, Random Allocation, Polymorphism, Single Nucleotide