Pleiotropy and pathway analyses of genetic variants associated with both type 2 diabetes and prostate cancer

L. A. Raynor, Jim Pankow, Laura J. Rasmussen-Torvik, Weihong Tang, Anna E Prizment, David J. Couper

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Aims: Epidemiological evidence shows that diabetes is associated with a reduced risk of prostate cancer. The objective of this study was to identify genes that may contribute to both type 2 diabetes and prostate cancer outcomes and the biological pathways these diseases may share. Methods: The Atherosclerosis Risk in Communities (ARIC) Study is a population-based prospective cohort study in four U.S. communities that included a baseline examination in 1987-89 and three follow-up exams at three year intervals. Participants were 45-64 years old at baseline. We conducted a genomewide association (GWA) study of incident type 2 diabetes in males, summarized variation across genetic loci into a polygenic risk score, and determined if that diabetes risk score was also associated with incident prostate cancer in the same study population. Secondarily we conducted a separate GWA study of prostate cancer, performed a pathway analysis of both type 2 diabetes and prostate cancer, and qualitatively determined if any of the biochemical pathways identified were shared between the two outcomes. Results: We found that the polygenic risk score for type 2 diabetes was not statistically significantly associated with prostate cancer. The pathway analysis also found no overlap between pathways associated with type 2 diabetes and prostate cancer. However, it did find that the growth hormone signaling pathway was statistically significantly associated with type 2 diabetes (p=0.0001). Conclusion: The inability of this study to find an association between type 2 diabetes polygenic risk scores with prostate cancer or biological pathways in common suggests that shared genetic variants may not contribute significantly to explaining shared etiology.

Original languageEnglish (US)
Pages (from-to)49-60
Number of pages12
JournalInternational Journal of Molecular Epidemiology and Genetics
Volume4
Issue number1
StatePublished - 2013

Keywords

  • Pathway analysis
  • Polygenic risk score
  • Prostate cancer
  • Type 2 diabetes

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