Leveraging Genome and Phenome-Wide Association Studies to Investigate Genetic Risk of Acute Lymphoblastic Leukemia.

Abstract

BACKGROUND: Genome-wide association studies (GWAS) of childhood cancers remain limited, highlighting the need for novel analytic strategies. We describe a hybrid GWAS and phenome-wide association study (PheWAS) approach to uncover genotype-phenotype relationships and candidate risk loci, applying it to acute lymphoblastic leukemia (ALL). METHODS: PheWAS was performed for 12 ALL SNPs identified by prior GWAS and two control SNP-sets using UK Biobank data. PheWAS-traits significantly associated with ALL SNPs compared with control SNPs were assessed for association with ALL risk (959 cases, 2,624 controls) using polygenic score and Mendelian randomization analyses. Trait-associated SNPs were tested for association with ALL risk in single-SNP analyses, with replication in an independent case-control dataset (1,618 cases, 9,409 controls). RESULTS: Platelet count was the trait most enriched for association with known ALL risk loci. A polygenic score for platelet count (223 SNPs) was not associated with ALL risk (P = 0.82) and Mendelian randomization did not suggest a causal relationship. However, twelve platelet count-associated SNPs were nominally associated with ALL risk in COG data and three were replicated in UK data (rs10058074, rs210142, rs2836441). CONCLUSIONS: In our hybrid GWAS-PheWAS approach, we identify pleiotropic genetic variation contributing to ALL risk and platelet count. Three SNPs known to influence platelet count were reproducibly associated with ALL risk, implicating genomic regions containing IRF1, proapoptotic protein BAK1, and ERG in platelet production and leukemogenesis. IMPACT: Incorporating PheWAS data into association studies can leverage genetic pleiotropy to identify cancer risk loci, highlighting the utility of our novel approach.