Estimating single nucleotide polymorphism associations using pedigree data: applications to breast cancer
D R Barnes1, D Barrowdale, J Beesley
1Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK.
British Journal of Cancer
|June 13, 2013
Summary
A new pedigree-based method effectively identifies breast cancer (BC) genetic associations using family data. This approach offers a valuable complement to traditional population studies for disease risk characterization.
Area of Science:
- Genetics
- Cancer Research
- Statistical Genomics
Background:
- Family pedigree data with multiple genotyped members are underutilized in breast cancer (BC) genetic association studies.
- A novel analytical framework was developed to analyze BC risk associated with single-nucleotide polymorphisms (SNPs) using 736 BC families.
- Each family had an average of eight members genotyped for 24 previously identified BC-associated SNPs.
Purpose of the Study:
- To develop and validate a pedigree-based analytical framework for characterizing SNP associations with breast cancer risk.
- To compare the efficacy of the pedigree-based approach with traditional methods that ignore family structure.
- To investigate parent-of-origin effects (POEs) in BC genetic associations.
Main Methods:
- Modeled breast cancer incidence using SNP effects and residual polygenic effects.
- Estimated relative risks (RRs) by maximizing the retrospective likelihood (RL) of observed family genotypes conditional on disease phenotypes.
- Extended models to assess parent-of-origin effects (POEs).
Main Results:
- Thirteen SNPs showed significant association with BC risk using the pedigree RL approach.
- Results were consistent with large population-based studies, but logistic regression ignoring family structure yielded higher RRs and P-values.
- SNP rs3817198 in LSP1 showed similar maternal and paternal RR estimates to previous reports, but no other SNPs exhibited POEs.
Conclusions:
- Pedigree-based methods are valuable and efficient for characterizing genetic associations with BC risk and other diseases.
- This approach can effectively complement findings from population-based studies.
- The developed framework enhances the utilization of family genetic data in disease association studies.
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