Multiple loci are associated with white blood cell phenotypes

Abstract

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.

Figure 1. Results of discovery phase meta-analyses for white blood cell phenotypes.

Red regions denote loci containing SNPs reaching genome-wide significance at p-values<5.00E-08. Blue regions denote suggestive loci containing SNPs with p-values between 5.00E-08 and 1.00E-07.

Figure 2. GRAIL gene clusters represented graphically for all clusters reaching a FDR adjusted p-value <0.05.

The relative thickness of each line connecting nodes is indicative of a p-value closer to zero. Gene symbols are designated on each node, with the cytogenetic position following the colon. Individual gene clusters are color-coded.

Figure 3. The directionality and magnitude of effects for SNPs significant in both the meta-analysis and eQTL analysis are highly correlated (r² = 0.795).

Effect estimates in both the eQTL analysis and meta-analysis were standardized to effects based on dosages of the minor allele for each SNP. Meta-analysis effects are based on beta coefficients from regression, while eQTL effects are based on standardized betas. This figure only includes significant SNPs to improve clarity.