From GWAS variant to function: A study of ∼148,000 variants for blood cell traits
Quan Sun,
Cheynna A. Crowley,
Le Huang,
Jia Wen,
Jiawen Chen,
Erik L. Bao,
Paul L. Auer,
Guillaume Lettre,
Alexander P. Reiner,
Vijay G. Sankaran,
Laura M. Raffield,
Yun Li
Affiliations
Quan Sun
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Cheynna A. Crowley
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Le Huang
Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Jia Wen
Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Jiawen Chen
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Erik L. Bao
Division of Hematology/Oncology, Boston Children’s Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Broad Institute of Harvard and MIT, Cambridge, MA, USA
Paul L. Auer
Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
Guillaume Lettre
Montreal Heart Institute, Montreal, QC, Canada; Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, QC, Canada
Alexander P. Reiner
Department of Epidemiology, University of Washington, Seattle, WA, USA; Fred Hutchinson Cancer Research Center, University of Washington, Seattle, WA, USA
Vijay G. Sankaran
Division of Hematology/Oncology, Boston Children’s Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Broad Institute of Harvard and MIT, Cambridge, MA, USA
Laura M. Raffield
Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Yun Li
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Corresponding author
Summary: Genome-wide association studies (GWASs) have identified hundreds of thousands of genetic variants associated with complex diseases and traits. However, most variants are noncoding and not clearly linked to genes, making it challenging to interpret these GWAS signals. We present a systematic variant-to-function study, prioritizing the most likely functional elements of the genome for experimental follow-up, for >148,000 variants identified for hematological traits. Specifically, we developed VAMPIRE: Variant Annotation Method Pointing to Interesting Regulatory Effects, an interactive web application implemented in R Shiny. This tool efficiently integrates and displays information from multiple complementary sources, including epigenomic signatures from blood-cell-relevant tissues or cells, functional and conservation summary scores, variant impact on protein and gene expression, chromatin conformation information, as well as publicly available GWAS and phenome-wide association study (PheWAS) results. Leveraging data generated from independently performed functional validation experiments, we demonstrate that our prioritized variants, genes, or variant-gene links are significantly more likely to be experimentally validated. This study not only has important implications for systematic and efficient revelation of functional mechanisms underlying GWAS variants for hematological traits but also provides a prototype that can be adapted to many other complex traits, paving the path for efficient variant-to-function (V2F) analyses.
