Exploring causal relationships between brain imaging-derived phenotypes and ovarian cancer risk: a bidirectional Mendelian randomization
Abstract
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. 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. 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…
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Evidence Hub reads this as a meta-analysis. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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