Genetic Analyses of Blood Cell Structure for Biological and Pharmacological Inference
By
Parsa Akbari,
Dragana Vuckovic,
Tao Jiang,
Kousik Kundu,
Roman Kreuzhuber,
Erik L. Bao,
Louisa Mayer,
Janine H Collins,
Kate Downes,
Michel Georges,
Luigi Grassi,
Jose A. Guerrero,
Stephen Kaptoge,
Julian Knight,
Stuart Meacham,
Jennifer Sambrook,
Denis Seyres,
Oliver Stegle,
Jeffrey M. Verboon,
Klaudia Walter,
Nicholas A Watkins,
John Danesh,
David J. Roberts,
Emanuele Di Angelantonio,
Vijay G. Sankaran,
Mattia Frontini,
Stephen Burgess,
Taco W Kuijpers,
James E. Peters,
Adam S. Butterworth,
Willem H Ouwehand,
Nicole Soranzo,
William J. Astle
Posted 31 Jan 2020
bioRxiv DOI: 10.1101/2020.01.30.927483
Thousands 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 platelet α-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.
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