Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk

Abstract

Prostate cancer (PCa) is the most common cancer and the second leading cause of cancer death among men in the United States. Considering that PCa development requires the coordination of many genes, it is expected that simultaneous evaluation of multiple genetic variants can improve the statistical power to detect additional PCa risk variants. Recent improvements in analytical methods and computation make it feasible to search for gene-gene interaction of SNPs in the genome. We hypothesized that multiple sequence variants in the genome may interact to increase PCa risk. These variants may or may not have known main effect on PCa risk and can be better detected by systematically evaluating gene-gene interactions for SNPs in the genome. We utilized data from an existing GWAS of a large NCI Cancer Genetic Markers of Susceptibility (CGEMS) study to systematically discover gene-gene interactions in the genome. We identified pairs of SNPs that interact with each of the thirty-two known risk SNPs on PCa risk using logistic regression. And we confirmed the interaction for approx. 300 pairs of SNPs in another case-control study population in Sweden (CAPS) (P<0.05).

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2011
Accession Number
ADA549774

Entities

People

  • Jielin Sun

Organizations

  • Wake Forest University

Tags

DTIC Thesaurus Topics

  • Biomedical Research
  • Computer Programs
  • Data Analysis
  • Department Of Defense
  • Genes
  • Genetic Markers
  • Genome
  • Health Services
  • Information Science
  • Neoplasms
  • Prostate
  • Prostate Cancer
  • Regression Analysis
  • Statistical Analysis
  • Stem Cells
  • Transcription Factors
  • United States

Fields of Study

  • Biology

Readers

  • Molecular Genetics
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.

Technology Areas

  • Biotechnology