What question did this study set out to answer?

This research aims to explore the genetic interactions between breast cancer and schizophrenia.

December 9, 2025

Dissecting the genetic interaction between breast cancer risk and schizophrenia: evidence from crosstrait genome-wide analysis

Key Points

This research aims to explore the genetic interactions between breast cancer and schizophrenia.
Utilized genome-wide association study data for both conditions.
Applied linkage disequilibrium score regression to evaluate genetic correlations.
Conducted localized variant association analysis to detect regional genetic signals.
Implemented conditional/conjunctional false discovery rate methodologies to examine shared genetic architecture.
Combined conjFDR with multitrait analysis of GWAS strategies to validate overlapping genetic loci.
Identified significant positive genome-wide genetic correlations between schizophrenia and breast cancer.
Revealed numerous chromosomal loci with shared genetic signals through regional structure analysis.
Confirmed genetic overlap between conditions using conditional/conjunctional false discovery rate models.
Highlighted specific shared genetic loci, including GATAD2A, with biological relevance.

Abstract

Background Epidemiological evidence suggests a link between schizophrenia (SCZ) and increased breast cancer (BC) risk, but the genetic mechanisms remain unclear. Exploring their shared genetic susceptibility may help reveal the basis of this comorbidity. Methods This study was conducted utilizing genome-wide association study (GWAS) data for SCZ and BC, employing a multitiered genetic analytical framework to systematically assess the genetic association patterns between these two conditions. Initially, linkage disequilibrium score regression and high-dimensional likelihood modeling were applied to quantitatively evaluate genome-wide genetic correlations, while localized variant association analysis was performed to detect regional genetic association signals within specific genomic loci. Subsequently, conditional/conjunctional false discovery rate (condFDR/conjFDR) methodologies were implemented to uncover the shared genetic architecture underlying both traits. Ultimately, conjFDR was integrated with multitrait analysis of GWAS (MTAG) strategies to further identify and validate potentially overlapping genetic variant loci. Results The analysis revealed significantly positive genome-wide genetic correlations between SCZ and BC, as well as among various BC subtypes. Regional genetic structure analysis identified numerous chromosomal loci exhibiting shared genetic signals. The condFDR/conjFDR models provided additional confirmation of the genetic overlap between the two traits. Through the combined application of conjFDR and MTAG, a collection of shared genetic loci with plausible biological relevance was identified and substantiated, including BATXN7 , FOXP1 , EMB , LINC00536 , ZNF365 , MAPT , STXBP4 , and GATAD2A . Conclusion The findings elucidated genetic associations between SCZ and BC and identified critical shared genetic contributors, thereby offering molecular evidence for the investigation of comorbidity mechanisms and potential intervention strategies.

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Cite This Study

Zhang et al. (Tue,) studied this question.

synapsesocial.com/papers/69401efa2d562116f28f99b0 https://doi.org/https://doi.org/10.1097/ypg.0000000000000410

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