Multi‐Trait GWAS Analyses of Blood Pressure Traits Provide Limited Gains in Locus Discovery or Polygenic Risk Score Performance Compared to Single‐Trait GWAS

ABSTRACT High blood pressure (BP) represents a major cause of life‐threatening cardiovascular conditions. GWAS have identified >2000 BP‐associated signals. BP‐GWAS usually analyze each BP trait individually. However, multi‐trait GWAS may yield novel loci and improve polygenic risk scores (PRS) prediction. We explored whether multi‐trait BP‐GWAS can: (i) find novel loci undetected by single‐trait GWAS; (ii) increase heritability estimates; (iii) improve PRS prediction of hypertension within the Lifelines Cohort Study. We investigate the utility of multi‐trait GWAS approaches of correlated BP traits (systolic BP, diastolic BP, pulse pressure). We tested two multi‐trait methods inputting results from the latest N > 1 million single‐trait BP‐GWAS: (a) Multi‐Trait Analysis of GWAS (MTAG); (b) genomic structural equation modeling (GenomicSEM); and compared results with single‐trait results. We only identified one novel locus from multi‐trait GWAS: ZNF268 . Neither heritability estimates nor PRS performance improved using multi‐trait GWAS. In this scenario of complete sample overlap across BP‐GWAS, we observed little gain in results from multi‐trait BP‐GWAS over single‐trait BP‐GWAS. Our findings quantify the limited benefit of multi‐trait methods under this specific setting. Future BP genetic discoveries are more likely to come from larger GWAS adding new cohort data. However, conclusions may differ for other traits, depending on trait‐specific genetic architecture.