SummaryMany common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.

The number and volume of cells in the blood affect a wide range of disorders including cancer and cardiovascular, metabolic, infectious and immune conditions. We consider here the genetic variation in eight clinically relevant hematological parameters, including hemoglobin levels, red and white blood cell counts and platelet counts and volume. We describe common variants within 22 genetic loci reproducibly associated with these hematological parameters in 13,943 samples from six European population-based studies, including 6 associated with red blood cell parameters, 15 associated with platelet parameters and 1 associated with total white blood cell count. We further identified a long-range haplotype at 12q24 associated with coronary artery disease in 9,479 cases and 10,527 controls. We show that this haplotype demonstrates extensive disease pleiotropy, as it contains known risk loci for type 1 diabetes, hypertension and celiac disease and has been spread by a selective sweep specific to European and geographically nearby populations.

Anaemia is a chief determinant of globalill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P <10−8, which together explain 4–9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

Hematopoiesis is a carefully controlled process that is regulated by complex networks of transcription factors that are, in part, controlled by signals resulting from ligand binding to cell-surface receptors. To further understand hematopoiesis, we have compared gene expression profiles of human erythroblasts, megakaryocytes, B cells, cytotoxic and helper T cells, natural killer cells, granulocytes, and monocytes using whole genome microarrays. A bioinformatics analysis of these data was performed focusing on transcription factors, immunoglobulin superfamily members, and lineage-specific transcripts. We observed that the numbers of lineage-specific genes varies by 2 orders of magnitude, ranging from 5 for cytotoxic T cells to 878 for granulocytes. In addition, we have identified novel coexpression patterns for key transcription factors involved in hematopoiesis (eg, GATA3-GFI1 and GATA2-KLF1). This study represents the most comprehensive analysis of gene expression in hematopoietic cells to date and has identified genes that play key roles in lineage commitment and cell function. The data, which are freely accessible, will be invaluable for future studies on hematopoiesis and the role of specific genes and will also aid the understanding of the recent genome-wide association studies. (Blood. 2009;113:e1-e9) IntroductionThe hematopoietic system represents one of the best-studied cellular differentiation processes in mammals. The differentiation of the hematopoietic stem cell (HSC) into the blood cell lineages, which is depicted as a stepwise process, generates diverse types of cells that perform many different functions. Historical observations of the blood, made in the late 18th century using some of the first microscopes, revealed that blood is composed of a heterogeneous population of cells that are distinct in number, morphology, and function. Since these early studies, the application of both technologic and methodologic advances to the investigation of blood has led to an ever-increasing understanding of the nature and function of the different types of blood cells. For example, the use of monoclonal antibodies (mAbs) and the designation of the cluster of differentiation (CD) markers, of which there are now more than 300, 1 allows hematologists to assign detailed phenotypes to malignant blood cells, which form the basis of decisions on therapeutic intervention.The value of the current understanding of the hematopoietic system to patient care is perhaps best illustrated in the field of malignancy where gene and protein expression profiles permit rapid and routine patient stratification. It is now possible to stratify patients with leukemia and lymphoma with unprecedented accuracy using gene expression profiles. Signature gene expression profiles may be used for diagnosis and predicting disease prognosis. In addition to studies in patients, gene expression profiles are available for a wide range of healthy tissue types. However, many of these resources, although broad in tissue coverage, are limited in the nu...

Glycoprotein (GP) VI is the major receptor responsible for platelet activation by collagen, but the collagen-binding surface of GPVI is unknown. To address this issue we expressed, from insect cells, the immunoglobulin (Ig)-like ectodomains (residues 1-185) of human and murine GPVI, called hD1D2 and mD1D2, respectively. Both proteins bound specifically to collagen-related peptide (CRP), a GPVIspecific ligand, but hD1D2 bound CRP more strongly than did mD1D2. Molecular modeling and sequence comparison identified key differences between hD1D2 and mD1D2. Ten mutant hD1D2s were expressed, of which 4 had human residues replaced by their murine counterpart, and 6 had replacements by alanine. CRP binding studies with these mutants demonstrated that the exchange of lysine at position 59 for the corresponding murine glutamate substantially reduced binding to CRP. The position of lysine59 on the apical surface of GPVI suggests a mode of CRP binding analogous to that used by the related killer cell Ig-like receptors to bind HLA. This surface was confirmed as critical for collagen binding by epitope mapping of an inhibitory phage antibody against GPVI. This anti-GPVI, clone 10B12, gave dose-dependent inhibition of the hD1D2-collagen interaction. Clone 10B12 inhibited activation of platelets by CRP and collagen in aggregometry and thrombus formation by the latter in whole blood perfusion. Antibody 10B12 showed significantly reduced binding to the hD1D2-E59, and, on that basis, the GPVI:10B12 interface was modeled. IntroductionDamage to blood vessels exposes circulating platelets to the extracellular matrix. Here, collagen supports adhesion and stimulates platelet activation by acting as a ligand for a number of platelet receptors. 1 Platelets are first tethered by the interaction of glycoprotein (GP) Ib␣ with the A1 domain of von Willebrand factor (VWF), 2 a plasma protein that binds to exposed collagen. 3 Firm platelet adhesion results from the concerted action of the collagen receptor GPIaIIa (integrin ␣2␤1) and the fibrinogen receptor GPIIbIIIa (␣IIb␤3) which also binds immobilized VWF. 4 Collagen-mediated activation of platelets is dependent on the engagement and clustering of GPVI, 1,5 an immunoglobulin (Ig) superfamily member with homology to killer cell Ig-like receptors (KIRs) and the Fc␣RI. 6 We and others have described the ligandbinding sites of ␣2 integrin 7 and GPIb␣ 2 at the structural level.Recent work has demonstrated the key role played by GPVI in arterial thrombus formation in mice and provides a clear basis for the development of potentially therapeutic GPVI inhibitors. 8 Indeed, blockade of GPVI is attractive for several reasons. First, the expression of GPVI appears to be restricted to platelets and megakaryocytes. 9 Second, collagen is required for prothrombotic "COAT" platelet formation, 10 for which blockade of GPVI may provide a specific control point. Third, patients with congenital or acquired autoantibody-mediated GPVI deficiency have only a mild bleeding disorder, despite having a significantly ...

White blood cell (WBC) count is a common clinical measure from complete blood count assays, and it varies widely among healthy individuals. Total WBC count and its constituent subtypes have been shown to be moderately heritable, with the heritability estimates varying across cell types. We studied 19,509 subjects from seven cohorts in a discovery analysis, and 11,823 subjects from ten cohorts for replication analyses, to determine genetic factors influencing variability within the normal hematological range for total WBC count and five WBC subtype measures. Cohort specific data was supplied by the CHARGE, HeamGen, and INGI consortia, as well as independent collaborative studies. We identified and replicated ten associations with total WBC count and five WBC subtypes at seven different genomic loci (total WBC count—6p21 in the HLA region, 17q21 near ORMDL3, and CSF3; neutrophil count—17q21; basophil count- 3p21 near RPN1 and C3orf27; lymphocyte count—6p21, 19p13 at EPS15L1; monocyte count—2q31 at ITGA4, 3q21, 8q24 an intergenic region, 9q31 near EDG2), including three previously reported associations and seven novel associations. To investigate functional relationships among variants contributing to variability in the six WBC traits, we utilized gene expression- and pathways-based analyses. We implemented gene-clustering algorithms to evaluate functional connectivity among implicated loci and showed functional relationships across cell types. Gene expression data from whole blood was utilized to show that significant biological consequences can be extracted from our genome-wide analyses, with effect estimates for significant loci from the meta-analyses being highly corellated with the proximal gene expression. In addition, collaborative efforts between the groups contributing to this study and related studies conducted by the COGENT and RIKEN groups allowed for the examination of effect homogeneity for genome-wide significant associations across populations of diverse ancestral backgrounds.

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Mean platelet volume (MPV) and platelet count (PLT) are highly heritable and tightly regulated traits. We performed a genomewide association study for MPV and identified one SNP, rs342293, as having highly significant and reproducible association with MPV (per-G allele effect 0.016 ؎ 0.001 log fL; P < 1.08 ؋ 10 ؊24 ) and PLT (per-G effect ؊4.55 ؎ 0.80 10 9 /L; P < 7.19 ؋ 10 ؊8 ) in 8586 healthy subjects. Whole-genome expression analysis in the 1-MB region showed a significant association with platelet transcript levels for PIK3CG (n ‫؍‬ 35; P ‫؍‬ .047). The G allele at rs342293 was also associated with decreased binding of annexin V to platelets activated with collagen-related peptide (n ‫؍‬ 84; P ‫؍‬ .003). The region 7q22.3 identifies the first QTL influencing platelet volume, counts, and function in healthy subjects. Notably, the association signal maps to a chromosome region implicated in myeloid malignancies, indicating this site as an important regulatory site for hematopoiesis. The identification of loci regulating MPV by this and other studies will increase our insight in the processes of megakaryopoiesis and proplatelet formation, and it may aid the identification of genes that are somatically mutated in essential thrombocytosis. (Blood. 2009; 113:3831-3837) IntroductionPlatelets are anucleate blood cell fragments that play a key role in maintaining primary hemostasis and in wound healing. Mean platelet volume (MPV) and platelet count (PLT) are tightly regulated and inversely correlated in the healthy population. Increased MPV represents a strong, independent predictor of postevent outcome in coronary disease and myocardial infarction, 1,2 and changes of either parameter outside the normal ranges are routinely used to ascertain and manage a large number of clinical conditions. Studies in rodents, primates, and twins have confirmed that blood cell quantitative traits, such as MPV and PLT, have high heritability levels. [3][4][5] Genome-wide association studies that used dense genotyping in thousands of subjects have greatly improved the resolution of such complex polygenic traits in humans. 6,7 We therefore reasoned that it should be possible to identify novel quantitative trait loci (QTLs) for MPV and PLT by a similar approach. The identification of such loci will provide new insights in the complex cellular processes of megakaryopoiesis and platelet formation. In addition, it may contribute to our understanding of premalignant conditions such as polycythemia vera and particularly essential thrombocytosis (ET), in which somatically acquired mutations in the JAK2 gene explain only a fraction of cases. 8 Megakaryocytes (MKs), the platelet precursor cells, originate from pluripotent hematopoietic stem cells (HSCs) in a stepwise process of fate determination and proliferation controlled by the cytokine thrombopoietin 9 and several extracellular matrix proteins (ECMPs). [10][11][12] After migration of the MK progenitors from the HSC niche to the bone marrow, platelets are formed via the tightly regulated pro...