Genetic architecture shared between body shape phenotypes and preeclampsia-related diseases: a genome-wide cross-trait analysis.

BACKGROUND

Observational studies have established a strong epidemiological connection between obesity and an increased risk of pre-eclampsia (PE). However, the genetic mechanisms underlying this comorbidity remain largely unexplored. In this study, we conducted a comprehensive cross-trait analysis to elucidate the shared genetic architecture between various adiposity-related traits and PE.

METHODS

Using the genome-wide association study (GWAS) statistics, we first evaluated the overall genetic overlap between adiposity-related traits and PE through multiple approaches, including linkage disequilibrium score regression (LDSC), high-definition likelihood inference (HDL), genetic covariance analysis, and pleiotropy and annotation methods. Causal relationships were then evaluated through bi-directional Generalised Summary-data-based Mendelian Randomisation (GSMR). Candidate pleiotropic loci were identified using a robust suite of analytical tools, including cross-phenotype association analysis, Multi-Trait Analysis of GWAS (MTAG), pleiotropic analysis under a composite null hypothesis, a pleiotropy-informed conditional false discovery rate (pleioFDR) framework, and Functional Mapping and Annotation (FUMA). Bayesian colocalisation (COLOC) was subsequently applied to these loci to pinpoint independent, significant causal single nucleotide polymorphisms (SNPs). To identify and validate shared genes, we performed tissue enrichment analysis, using Multi-marker Analysis of Genomic Annotation, and integrated SPrediXcan with COLOC. Finally, gene functional enrichment was characterised via Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses.

RESULTS

We identified significant positive genetic correlations and robust causal associations between adiposity-related traits and PE-related diseases. Our analyses revealed 35 independent significant causal SNPs, 32 enriched tissues, and 7 shared high-confidence genes supported by COLOC analysis.

CONCLUSIONS

Collectively, our study indicates a genetic correlation and common risk genes, linking adiposity-related traits to PE-related diseases. These findings offer novel insights into the biological mechanisms underlying this comorbidity, highlighting promising targets for future mechanistic studies and stratified preventative strategies.