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Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
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Research Articles

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

Eleanor C. Semmes, Jayaram Vijayakrishnan, Chenan Zhang, Jillian H. Hurst, Richard S. Houlston and Kyle M. Walsh
Eleanor C. Semmes
1Medical Scientist Training Program, Duke University, Durham, North Carolina.
2Children's Health and Discovery Initiative, Department of Pediatrics, Duke University, Durham, North Carolina.
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  • ORCID record for Eleanor C. Semmes
Jayaram Vijayakrishnan
3Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey, United Kingdom.
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Chenan Zhang
4Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California.
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Jillian H. Hurst
2Children's Health and Discovery Initiative, Department of Pediatrics, Duke University, Durham, North Carolina.
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Richard S. Houlston
3Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, Surrey, United Kingdom.
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Kyle M. Walsh
2Children's Health and Discovery Initiative, Department of Pediatrics, Duke University, Durham, North Carolina.
4Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California.
5Department of Neurosurgery, Duke University, Durham, North Carolina.
6Duke Cancer Institute, Duke University, Durham, North Carolina.
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  • ORCID record for Kyle M. Walsh
  • For correspondence: kyle.walsh@duke.edu
DOI: 10.1158/1055-9965.EPI-20-0113 Published August 2020
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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.

This article is featured in Highlights of This Issue, p. 1513

Footnotes

  • Note: Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).

  • Cancer Epidemiol Biomarkers Prev 2020;29:1606–14

  • Received January 21, 2020.
  • Revision received March 23, 2020.
  • Accepted May 6, 2020.
  • Published first May 28, 2020.
  • ©2020 American Association for Cancer Research.
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Cancer Epidemiology Biomarkers & Prevention: 29 (8)
August 2020
Volume 29, Issue 8
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Leveraging Genome and Phenome-Wide Association Studies to Investigate Genetic Risk of Acute Lymphoblastic Leukemia
Eleanor C. Semmes, Jayaram Vijayakrishnan, Chenan Zhang, Jillian H. Hurst, Richard S. Houlston and Kyle M. Walsh
Cancer Epidemiol Biomarkers Prev August 1 2020 (29) (8) 1606-1614; DOI: 10.1158/1055-9965.EPI-20-0113

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Leveraging Genome and Phenome-Wide Association Studies to Investigate Genetic Risk of Acute Lymphoblastic Leukemia
Eleanor C. Semmes, Jayaram Vijayakrishnan, Chenan Zhang, Jillian H. Hurst, Richard S. Houlston and Kyle M. Walsh
Cancer Epidemiol Biomarkers Prev August 1 2020 (29) (8) 1606-1614; DOI: 10.1158/1055-9965.EPI-20-0113
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