GWAS Summary Statistics for "Improving polygenic risk prediction performance through integrating electronic health records by phenotype embedding"

These genome-wide association summary statistics were generated as part of the study “Improving polygenic risk prediction performance through integrating electronic health records by phenotype embedding.” The analyses leverage electronic health record (EHR)-derived phenotype embeddings to enhance polygenic risk prediction using only GWAS summary data. Five embedding approaches were evaluated: Word2Vec, Word2Vec_PCA, Word2Vec_ICA, GPT_PCA, and GPT_ICA, to capture latent clinical structures within EHR data. Genome-wide association analyses were conducted in the UK Biobank European training population (N = 207,734), focusing on HapMap3 SNPs to ensure well-imputed, high-quality variants suitable for cross-cohort analyses. The resulting summary statistics (SNP, CHR, POS, A1, A2, N, MAF, BETA, SE, Z, P) enable replication and further meta-analyses of embedding-based GWAS results. This dataset supports the development of the EEPRS and MTAG_EEPRS frameworks described in the accompanying manuscript and preprint (doi:https://doi.org/10.1101/2025.08.05.668705).