Hematopoiesis generates mature blood cells from hematopoietic stem cells (HSC) in distinct lineages to release of trillions of mature cells each day into the peripheral blood stream to perform essential functions such as oxygen transport, hemostasis and host defense. The formation and turnover of blood cells are tightly controlled and so the properties of blood cells, including their volume and count, have large heritabilities and are easily influenced by genetic variation. Here we describe the most statistically powerful genome wide association study (GWAS) of blood cell indices to date. We tested associations of 29.5 million polymorphic DNA sequence variants derived using the the Affymetrix axiom array with interpolation of 20 million variants using the UK 10000 genome data with 36 different hematological indices of red cells, white cells and platelets, some of which, such as the reticulocyte count, have been explored for the first time. We discovered significant associations at thousands of associated genetic variants, including hundreds of associations for low frequency genetic variants, thus identifying associations with larger effects on indices than those reported for common variants by previous discovery studies. We have described detailed follow-up studies of the novel associations. Using cell type-specific epigenome and gene expression data generated by the BLUEPRINT project and results from chromatin conformation capture in major blood cell types, we can identify the likely causal variants and their functional impact at a large number of the novel loci. Finally, we have evaluated the contribution of genetic variants to common and complex diseases. In conclusion, we have interrogated phenotypes across the whole hematopoietic tree and increased the number of traits associated with blood cell phenotypes by an order of magnitude. Overall, our results demonstrate widespread and powerful genetic influences on the formation and regulation of the major human blood cell types, identifying many novel genes involved and show the value of genome-wide functional annotation from relevant primary cell populations for interpreting genetic association results.

Disclosures

No relevant conflicts of interest to declare.

Author notes

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Asterisk with author names denotes non-ASH members.

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