Abstract
BackgroundGenotyping technologies enable us to genotype multiple Single Nucleotide Polymorphisms (SNPs) within selected genes/regions, providing data for haplotype association analysis. While haplotype-based association analysis is powerful for detecting untyped causal alleles in linkage-disequilibrium (LD) with neighboring SNPs/haplotypes, the inclusion of extraneous SNPs could reduce its power by increasing the number of haplotypes with each additional SNP.MethodsHere, we propose a haplotype-based stepwise procedure (HBSP) to eliminate extraneous SNPs. To evaluate its properties, we applied HBSP to both simulated and real data, generated from a study of genetic associations of the bactericidal/permeability-increasing (BPI) gene with pulmonary function in a cohort of patients following bone marrow transplantation.ResultsUnder the null hypothesis, use of the HBSP gave results that retained the desired false positive error rates when multiple comparisons were considered. Under various alternative hypotheses, HBSP had adequate power to detect modest genetic associations in case-control studies with 500, 1,000 or 2,000 subjects. In the current application, HBSP led to the identification of two specific SNPs with a positive validation.ConclusionThese results demonstrate that HBSP retains the essence of haplotype-based association analysis while improving analytic power by excluding extraneous SNPs. Minimizing the number of SNPs also enables simpler interpretation and more cost-effective applications.
Highlights
Genotyping technologies enable us to genotype multiple Single Nucleotide Polymorphisms (SNPs) within selected genes/regions, providing data for haplotype association analysis
BPI and Pulmonary Function among Transplant Patients Given the importance of innate immunity in protection from diseases of the airway, we conducted a genetic association study using a candidate gene approach to determine if polymorphisms in genes of the innate immune pathway are associated with the development of hematopoietic stem cell transplant- (HCT-) related airflow obstruction (AFO), the details of which have been published elsewhere [14]
The haplotype-based stepwise procedure (HBSP) described above is effective in selecting a subset of SNPs whose haplotypes are significantly associated with a disease phenotype by eliminating SNPs with random polymorphisms
Summary
Genotyping technologies enable us to genotype multiple Single Nucleotide Polymorphisms (SNPs) within selected genes/regions, providing data for haplotype association analysis. Genotyping technology enables population researchers to genotype dozens to thousands of SNPs within any selected candidate gene or within any genomic region Such SNP data are increasingly collected in disease association studies, using a case-control study design [1, 2], with the analytic objective of assessing association between SNP genotypes and a disease phenotype of interest. Recent population genetic studies of the human genome have suggested that recombination processes, together with other population genetic forces, have created long-range haplotype blocks [10, 11] These block structures are useful for reducing the number of statistical comparisons, as well as for interpretation of disease associations with common extended haplotypes. A haplotype of multiple SNPs may be thought of as an allele at a multi-allelic marker locus, and increasing polymorphism with multiple haplotypes improves the power to detect disease associations
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