Biomedical subjects

Kelly M Burkett

Publications and source records attributed to Kelly M Burkett.

3 recordsLinked to original sources

PubMed2006

Contribution of alpha- and beta-defensins to lung function decline and infection in smokers: an association study.

BACKGROUND: Alpha-defensins, which are major constituents of neutrophil azurophilic granules, and beta-defensins, which are expressed in airway epithelial cells, could contribute to the pathogenesis of chronic obstructive pulmonary disease by amplifying cigarette smoke-induced and infection-induced inflammatory reactions leading to lung injury. In Japanese and Chinese populations, two different beta-defensin-1 polymorphisms have been associated with chronic obstructive pulmonary disease phenotypes. We conducted population-based association studies to test whether alpha-defensin and beta-defensin polymorphisms influenced smokers' susceptibility to lung function decline and susceptibility to lower respiratory infection in two groups of white participants in the Lung Health Study (275 = fast decline in lung function and 304 = no decline in lung function). METHODS: Subjects were genotyped for the alpha-defensin-1/alpha-defensin-3 copy number polymorphism and four beta-defensin-1 polymorphisms (G-20A, C-44G, G-52A and Val38Ile). RESULTS: There were no associations between individual polymorphisms or imputed haplotypes and rate of decline in lung function or susceptibility to infection. CONCLUSION: These findings suggest that, in a white population, the defensin polymorphisms tested may not be of importance in determining who develops abnormally rapid lung function decline or is susceptible to developing lower respiratory infections.

Adult↗

PubMed2005

A comparison of five methods for selecting tagging single-nucleotide polymorphisms.

Our goal was to compare methods for tagging single-nucleotide polymorphisms (tagSNPs) with respect to the power to detect disease association under differing haplotype-disease association models. We were also interested in the effect that SNP selection samples, consisting of either cases, controls, or a mixture, would have on power. We investigated five previously described algorithms for choosing tagSNPS: two that picked SNPs based on haplotype structure (Chapman-haplotypic and Stram), two that picked SNPs based on pair-wise allelic association (Chapman-allelic and Cousin), and one control method that chose equally spaced SNPs (Zhai). In two disease-associated regions from the Genetic Analysis Workshop 14 simulated data, we tested the association between tagSNP genotype and disease over the tagSNP sets chosen by each method for each sampling scheme. This was repeated for 100 replicates to estimate power. The two allelic methods chose essentially all SNPs in the region and had nearly optimal power. The two haplotypic methods chose about half as many SNPs. The haplotypic methods had poor performance compared to the allelic methods in both regions. We expected an improvement in power when the selection sample contained cases; however, there was only moderate variation in power between the sampling approaches for each method. Finally, when compared to the haplotypic methods, the reference method performed as well or worse in the region with ancestral disease haplotype structure.

Genetic Techniques↗

PubMed2004

Microarray genotyping resource to determine population stratification in genetic association studies of complex disease.

We have developed a robust microarray genotyping chip that will help advance studies in genetic epidemiology. In population-based genetic association studies of complex disease, there could be hidden genetic substructure in the study populations, resulting in false-positive associations. Such population stratification may confound efforts to identify true associations between genotype/haplotype and phenotype. Methods relying on genotyping additional null single nucleotide polymorphism (SNP) markers have been proposed, such as genomic control (GC) and structured association (SA), to correct association tests for population stratification. If there is an association of a disease with null SNPs, this suggests that there is a population subset with different genetic background plus different disease susceptibility. Genotyping over 100 null SNPs in the large numbers of patient and control DNA samples that are required in genetic association studies can be prohibitively expensive. We have therefore developed and tested a resequencing chip based on arrayed primer extension (APEX) from over 2000 DNA probe features that facilitate multiple interrogations of each SNP, providing a powerful, accurate, and economical means to simultaneously determine the genotypes at 110 null SNP loci in any individual. Based on 1141 known genotypes from other research groups, our GC SNP chip has an accuracy of 98.5%, including non-calls.

Animals↗