bioRxivGeneticsPreprint
Genetic Analyses of Blood Cell Structure for Biological and Pharmacological Inference
Parsa AkbariiD, Dragana VuckoviciD, Tao JiangiD, Kousik KunduiD, Roman KreuzhuberiD, Erik L. BaoiD, Louisa MayeriD, Janine CollinsiD, Kate DownesiD, Michel GeorgesiD, Luigi GrassiiD, José A. GuerreroiD, Stephen K. KaptogeiD, Julian Charles KnightiD, Stuart MeachamiD, Jennifer Sambrook, Denis SeyresiD, Oliver StegleiD, Jeffrey M. VerbooniD, Klaudia WalteriD, Nicholas A. Watkins, John DaneshiD, David J. RobertsiD, Emanuele Di AngelantonioiD, Vijay G. SankaraniD, , William John AstleiD
Abstract
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 -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.
- organism: human
- assay: bulk RNA-seq
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 7
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