Integration of Genome-Wide Association Studies With Single-Cell and Bulk Expression Quantitative Trait Locus to Identify Stroke Susceptibility Genes

<h4>Background</h4>Previous studies have integrated genome-wide association studies with expression quantitative trait locus (eQTL) data from bulk tissues to identify stroke susceptibility genes. However, eQTL data exhibit high cell-type specificity, and genetic variants may have distinct effects across stroke subtypes.<h4>Methods</h4>We applied the summary-data-based Mendelian randomization (MR) method to integrate eQTL data from 7 brain cell types with genome-wide association studies data for 5 stroke phenotypes (stroke, ischemic stroke, cardioembolic stroke, large artery stroke, and small vessel stroke). Results were compared with summary-data-based MR using eQTL data from 49 tissues in the Genotype-Tissue Expression project. Robustness of significant single-cell summary-data-based MR associations was assessed via MR and colocalization analyses. Further evaluations included single-cell RNA-seq differential expression, protein-protein interaction, druggability, and phenome-wide association studies.<h4>Results</h4>Single-cell summary-data-based MR identified many novel significant genes not detected using bulk tissue eQTL data. Validated associations revealed 2 stroke risk genes (<i>LRCH1</i>, <i>ICA1L</i>), 3 stroke protective genes (<i>AHI1</i>, <i>LYRM9</i>, <i>CENPQ</i>), 2 large artery stroke risk genes (<i>LIPA</i>, <i>ELL</i>), and 1 ischemic stroke protective gene (<i>CENPQ</i>). Single-cell RNA-seq showed significantly increased <i>LIPA</i> expression in mouse stroke samples compared with controls. Protein-protein interaction and druggability analyses, along with phenome-wide association studies, prioritized <i>LIPA</i> and <i>LRCH1</i> as potential therapeutic targets for stroke while indicating possible adverse effects.<h4>Conclusions</h4>Integrating single-cell eQTL with stroke-subtype genome-wide association studies uncovers novel cell-type-specific causal genes and highlights promising therapeutic targets, advancing understanding of stroke pathogenesis.