Genetic Analyses of Blood Cell Structure for Biological and Pharmacological Inference

Autor: Stephen Kaptoge, Jeffrey M. Verboon, Jennifer G. Sambrook, Emanuele Di Angelantonio, Tao Jiang, William J. Astle, Louisa Mayer, Taco W. Kuijpers, Janine Collins, Vijay G. Sankaran, Michel Georges, Nicholas A. Watkins, Julian C. Knight, Kousik Kundu, Roman Kreuzhuber, Kate Downes, Adam S. Butterworth, Stephen Burgess, David J. Roberts, Luigi Grassi, Stuart Meacham, Dragana Vuckovic, Denis Seyres, Jose A. Guerrero, Parsa Akbari, Mattia Frontini, Nicole Soranzo, Willem H. Ouwehand, Klaudia Walter, Erik L. Bao, John Danesh, Oliver Stegle, James E. Peters
Jazyk: angličtina
Rok vydání: 2020
Předmět:
DOI: 10.1101/2020.01.30.927483
Popis: SUMMARYThousands of genetic associations with phenotypes of blood cells are known, but few are with phenotypes relevant to cell function. We performed GWAS of 63 flow-cytometry phenotypes, including measures of cell granularity, nucleic acid content, and reactivity, in 39,656 participants in the INTERVAL study, identifying 2,172 variant-trait associations. These include associations mediated by functional cellular structures such as secretory granules, implicated in vascular, thrombotic, inflammatory and neoplastic diseases. By integrating our results with epigenetic data and with signals from molecular abundance/disease GWAS, we infer the hematopoietic origins of population phenotypic variation and identify the transcription factor FOG2 as a regulator of plateletα-granularity. We show how flow cytometry genetics can suggest cell types mediating complex disease risk and suggest efficacious drug targets, presenting Daclizumab/Vedolizumab in autoimmune disease as positive controls. Finally, we add to existing evidence supporting IL7/IL7-R as drug targets for multiple sclerosis.
Databáze: OpenAIRE