GWAS-by-Subtraction Resolves Coronary Artery Disease-Related and Model-Defined Residual Genetic Components of Ischaemic Stroke

Abstract

Background/Objectives: Genetic overlap between any ischaemic stroke (AIS) and coronary artery disease (CAD) can obscure associations less closely tied to coronary risk. We aimed to separate coronary-shared from residual AIS genetic effects. Methods: We applied GWAS-by-subtraction to GIGASTROKE AIS and UK Biobank/CARDIoGRAMplusC4D CAD summary statistics. A Cholesky model separated a CAD-related shared component (F1) from a model-defined residual AIS component (F2). We tested model order, factor covariance, population prevalence, CAD input, LD reference and sample-size parameter then characterised loci using FUMA, SuSiE-RSS, genetic correlation, MAGMA, SMR/HEIDI and targeted colocalisation. Results: AIS and CAD had a genetic correlation of 0.490. F1 and F2 had SNP heritabilities of 0.0251 and 0.00414, and F2 contained 14 FUMA loci. F2 Z scores remained correlated across covariance (minimum r = 0.994), prevalence (minimum r = 0.998) and alternative-CAD analyses (r = 0.984). Reverse ordering produced reallocation of source-trait signal. At rs974819, the T allele was associated positively with CAD and negatively with marginal AIS, producing a model-derived CAD-AIS-discordant F2 association. Source-trait colocalisation showed that NBEAL1, PHACTR1 and PDGFD signals were present in one or both input-trait analyses, whereas the F11 protein signal aligned with AIS and F2. In a potentially overlapping FinnGen cross-implementation analysis, all 13 F2 lead variants showed concordant directions. Within overlapping stroke-subtype analyses, F2 showed stronger alignment with cardioembolic stroke. Conclusions: GWAS-by-subtraction resolved a model-defined residual AIS component that was stable across covariance, prevalence and CAD-input specifications, supporting a component-based view of AIS genetic effects after modelling shared coronary architecture.