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

Author:

Rowland Bryce1,Venkatesh Sanan23,Tardaguila Manuel4,Wen Jia5,Rosen Jonathan D1,Tapia Amanda L1,Sun Quan1,Graff Mariaelisa6,Vuckovic Dragana7,Lettre Guillaume8,Sankaran Vijay G91011,Voloudakis Georgios3212ORCID,Roussos Panos3212,Huffman Jennifer E13,Reiner Alexander P14,Soranzo Nicole4,Raffield Laura M5,Li Yun1515ORCID

Affiliation:

1. Department of Biostatistics, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599 , USA

2. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai , New York City, NY 10029 , USA

3. Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center , Bronx, NY 10468 , USA

4. Department of Human Genetics, Wellcome Sanger Institute , Hinxton CB10 1SA , UK

5. Department of Genetics, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599 , USA

6. Department of Epidemiology, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599 , USA

7. Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London , London SW7 2AZ , UK

8. Montreal Heart Institute, Université de Montréal , Montreal, Quebec , Canada

9. Division of Hematology/Oncology, Boston Children's Hospital , Boston, MA 02115 , USA

10. Department of Pediatric Oncology, Dana-Farber Cancer Institute , Boston, MA 02115 , USA

11. Broad Institute of MIT and Harvard , Cambridge, MA 02142 , USA

12. Department of Psychiatry, Icahn School of Medicine at Mount Sinai , New York City, NY 10029 , USA

13. Center for Population Genomics, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System , Boston, MA 02130 , USA

14. Department of Epidemiology, University of Washington , Seattle, WA 98195 , USA

15. Department of Computer Science, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599 , USA

Abstract

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.

Funder

National Science Foundation

Brain and Behavior Research Foundation

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Genetics (clinical),Genetics,Molecular Biology,General Medicine

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