Genomic Correlations, Shared Loci, and Drug Targets Between Polycystic Ovary Syndrome and Asthma: Insights From Genome-wide Association Analysis

Abstract

Background: Observational studies have shown an association between polycystic ovary syndrome (PCOS) and asthma-related traits. However, whether this association is genetically driven or arises from observational biases remains unclear.

Methods: This study integrated data from 10 074 PCOS cases and asthma-related traits obtained from the UK Biobank and FinnGen cohorts. Global and local genetic architectures were examined using pleiotropic analysis under the composite null hypothesis, functional mapping and annotation of genetic associations, and fine-mapping credible set analysis. Drug database mining was employed to identify pleiotropic genes as potential therapeutic targets. Tissue and cell enrichment analyses were conducted to uncover shared biological mechanisms.

Results: We identified 3 novel significant genetic loci for asthma subtypes (2 for allergic asthma and 1 for childhood asthma). A positive overall genetic correlation between PCOS and asthma-related traits was observed. We discovered 5 pleiotropic causal regions encompassing 13 genes, with ERBB3 emerging as a potential central gene contributing to the shared pathophysiology of PCOS and asthma-related traits. Additionally, drug repositioning analysis suggested anakinra and artenimol as potential therapeutic candidates for PCOS and asthma comorbidity. The linkage disequilibrium score for the specific expression of genes analysis, along with transcriptome-wide association studies, further identified gene expression patterns at the tissue/cell level in the hypothalamo-pituitary, exocrine/endocrine, respiratory, and urogenital systems.

Conclusion: Our findings provide novel insights into the genetic basis and biological processes underlying the association between PCOS and asthma-related traits, warranting evaluation of whether PCOS-specific asthma risk assessment could improve clinical outcomes.

Keywords: asthma; genetic architecture; genome-wide association studies; polycystic ovary syndrome.

Figure 1.

Overview of the study design. (A) Gwas data sources; (B) Genome-wide association analysis. Abbreviations: HESS, heritability estimation from summary statistics; LDSC-SEG, linkage disequilibrium score regression for the specific expression of genes analysis; PCOS, polycystic ovary syndrome.

Figure 2.

Multilevel enrichment analysis of pleiotropic genes associated with PCOS and asthma. (A) Enrichment of differentially expressed 13 pleiotropic genes across 54 GTEx tissues. The y-axis represents significance as −log10(P-value). Red bars represent significant enrichment after Bonferroni correction for multiple testing. (B) Disease associations of 11 pleiotropic genes reported in the GWAS Catalog. Left panel shows the proportion of overlapping genes in gene sets for each disease/trait. Middle panel displays enrichment significance as −log10(adjusted P-value). Right panel indicates specific overlapping genes. (C) Colocalization analysis of ERBB3 eQTLs across multiple tissues. The x-axis shows −log10(P-value) of colocalization, with higher values indicating stronger evidence of shared causal variants between PCOS/asthma and ERBB3 expression in the respective tissues. Abbreviations: DEG, differentially expressed genes; eQTL, expression quantitative trait loci; GTEx, genotype-tissue expression; GWAS, genome-wide association studies; PCOS, polycystic ovary syndrome.