Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets’ important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors.
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We thank all participants and study coordinating centers. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute, the NIH, or the U.S. Department of Health and Human Services. The Framingham Heart Study (FHS) authors acknowledge that the computational work reported on in this paper was performed on the Shared Computing Cluster, which is administered by Boston University’s Research Computing Services. The MHI Biobank acknowledges the technical support of the Beaulieu-Saucier MHI Pharmacogenomic Center. We would like to thank Liling Warren for contributions to the genetic analysis of the SOLID-TIMI-52 and STABILITY datasets. The University Medicine Greifswald is a member of the Caché Campus program of the InterSystems GmbH. The SHIP and SHIP-TREND samples were genotyped at the Helmholtz Zentrum München. Estonian Genome Center, University of Tartu (EGCUT) would like to acknowledge Mr. V. Soo, Mr. S. Smith, and Dr. L. Milani. The Airwave Health Monitoring Study thanks Louisa Cavaliero who assisted in data collection and management as well as Peter McFarlane and the Glasgow CARE, Patricia Munroe at Queen Mary University of London, and Joanna Sarnecka and Ania Zawodniak at Northwick Park. FINCAVAS thanks the staff of the Department of Clinical Physiology for collecting the exercise test data. Young Finns Study (YFS) acknowledges the expert technical assistance in statistical analyses by Irina Lisinen.