Transcriptome-wide association study in UK Biobank Europeans identifies associations with blood cell traits

Bryce Rowland, Sanan Venkatesh, Manuel Tardaguila, Jia Wen, Jonathan D. Rosen, Amanda L. Tapia, Quan Sun, Mariaelisa Graff, Dragana Vuckovic, Guillaume Lettre, Vijay G. Sankaran, Georgios Voloudakis, Panos Roussos, Jennifer E. Huffman, Alexander P. Reiner, Nicole Soranzo, Laura M. Raffield, Yun Li

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Previous genome-wide association studies (GWAS) of hematological traits have identified over 10 000 distinct trait-specific risk loci. However, at these loci, the underlying causal mechanisms remain incompletely characterized. To elucidate novel biology and better understand causal mechanisms at known loci, we performed a transcriptome-wide association study (TWAS) of 29 hematological traits in 399 835 UK Biobank (UKB) participants of European ancestry using gene expression prediction models trained from whole blood RNA-seq data in 922 individuals. We discovered 557 gene-trait associations for hematological traits distinct from previously reported GWAS variants in European populations. Among the 557 associations, 301 were available for replication in a cohort of 141 286 participants of European ancestry from the Million Veteran Program. Of these 301 associations, 108 replicated at a strict Bonferroni adjusted threshold ($\alpha$= 0.05/301). Using our TWAS results, we systematically assigned 4261 out of 16 900 previously identified hematological trait GWAS variants to putative target genes. Compared to coloc, our TWAS results show reduced specificity and increased sensitivity in external datasets to assign variants to target genes.

Original languageEnglish
Pages (from-to)2333-2347
Number of pages15
JournalHuman Molecular Genetics
Volume31
Issue number14
DOIs
StatePublished - 15 Jul 2022

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