Exploration of SNP-set Interactions in Genome-Wide Association Studies

  • Author / Creator
    Alam, Shomoita
  • Advance in biotechnologies has enabled genome-wide association studies (GWAS) that scan the entire human genome for understanding genetic contributions to the risk of a certain disease as well as to variation in treatment efficacy and side effects. In GWAS, the association between each single-nucleotide polymorphism (SNP) and a phenotype is assessed statistically, typically analyzing one single SNP at a time, ignoring potential SNP-SNP interactions. Such individual-SNP analysis approaches have extracted small fractions of expected genetic contributions to disease risks: this has been recognized as “the missing heritability problem” of GWAS. Biologically, it is highly unlikely that a single SNP alone would determine disease risk, especially for complex chronic diseases. We therefore tested whether biological interactions among multiple SNPs determine disease risks and whether it can explain the missing heritability problem. The methodologies proposed in this work take into account the interaction between selected SNP-sets using two methods: (1) method based on logic regression that incorporates two specific forms of interaction; and (2) method based on SNP-pair analysis which is an exploration of genotypes that are only observed in cases with a sufficient frequency and with no control having the same specific genotypes. Both methods could identify many previously-found and novel susceptibility genes for the datasets we tested on, although validation studies are required to avoid spurious findings. While our results do not provide a satisfactory solution to the ``missing heritability” problem, they show the importance of considering SNP interactions and their exploration in considering genetic contributions of disease etiology, prevention and treatment.

  • Subjects / Keywords
  • Graduation date
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
  • Institution
    University of Alberta
  • Degree level
  • Department
    • Department of Public Health Sciences
  • Specialization
    • Epidemiology
  • Supervisor / co-supervisor and their department(s)
    • Yasui, Yutaka (School of Public Health)
  • Examining committee members and their departments
    • Yuan, Yan (School of Public Health)
    • Yasui, Yutaka (School of Public Health)
    • Dinu, Irina (School of Public Health)