Abstract
B-cell malignancies (BCM) originate from the same cell of origin, but at different maturation stages and have distinct clinical phenotypes. Although genetic risk variants for individual BCMs have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. We explored genome-wide association studies of chronic lymphocytic leukaemia (CLL, N = 1,842), Hodgkin lymphoma (HL, N = 1,465) and multiple myeloma (MM, N = 3,790). We identified a novel pleiotropic risk locus at 3q22.2 (NCK1, rs11715604, P = 1.60 × 10−9) with opposing effects between CLL (P = 1.97 × 10−8) and HL (P = 3.31 × 10−3). Eight established non-HLA risk loci showed pleiotropic associations. Within the HLA region, Ser37 + Phe37 in HLA-DRB1 (P = 1.84 × 10−12) was associated with increased CLL and HL risk (P = 4.68 × 10−12), and reduced MM risk (P = 1.12 × 10−2), and Gly70 in HLA-DQB1 (P = 3.15 × 10−10) showed opposing effects between CLL (P = 3.52 × 10−3) and HL (P = 3.41 × 10−9). By integrating eQTL, Hi-C and ChIP-seq data, we show that the pleiotropic risk loci are enriched for B-cell regulatory elements, as well as an over-representation of binding of key B-cell transcription factors. These data identify shared biological pathways influencing the development of CLL, HL and MM. The identification of these risk loci furthers our understanding of the aetiological basis of BCMs.
Highlights
analysis based on subsets (ASSET) is able to identify variants that are positively and negatively associated with different diseases. Applying this statistical procedure to six B-cell malignancies (BCM) genome-wide association studies (GWAS) we report the identification of a novel pleiotropic region influencing BCM risk, as well as eight non-HLA linked pleiotropic loci that have only previously been described in single GWAS
In order for candidate SNPs to be considered, they were required to meet the following criteria: (1) variant associations at P ≤ 5.0 × 10−8 for the ASSET test; (2) at least one other variant in the same region with the same pleiotropic association at P ≤ 1.0 × 10−6; (3) the individual one-sided ASSET subset tests were significant at P < 0.01; (4) the variant is not driven by a single study; (5) the variant cannot be both positively and negatively associated in different datasets of the same BCM; and (6) if a variant is positively and negatively associated with different BCM, the 2-sided P-value must be lower than both individual 1-sided P-values
Motivated by the stratified Q-Q plots, which suggested the existence of pleiotropy, we utilised genotype data from six datasets in British and German populations, to conduct an agnostic cross-cancer genome-wide analysis to identify specific pleiotropic associations for chronic lymphocytic leukaemia (CLL), Hodgkin lymphoma (HL) and MM for both HLA and non-HLA regions
Summary
While conventional meta-analysis provides a powerful tool for combining distinct GWAS, this approach is suboptimal in the presence of disease heterogeneity, such as when SNP associations are only manifest in a specific subset of the diseases, or have opposing effects for different diseases To address such shortcomings in searching for pleiotropic risk SNPs for BCM, we adopted the previously validated association analysis based on subsets (ASSET) meta-analytic approach[35,36]. ASSET is able to identify variants that are positively and negatively associated with different diseases Applying this statistical procedure to six BCM GWAS (two each of CLL, HL and MM) we report the identification of a novel pleiotropic region influencing BCM risk, as well as eight non-HLA linked pleiotropic loci that have only previously been described in single GWAS. Within the HLA region, we report two novel coding variants in class II HLA proteins which have pleiotropic effects on BCM risk
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