Hasan Al-Shemari

Modern methods for the study of genetics offer promising new means of exploring complex diseases such as chronic rhinosinusitis (CRS). Powerful new high-throughput tools extend the capabilities of existing technologies. However, for the inexperienced reader, a lack of familiarity with the techniques used may limit comprehension of the articles and hamper the appreciation of the potential of this area of research. To improve understanding, we present an introduction to research methods in common user language, describing the techniques and applications of each while outlining differences between techniques of study of gene expression and genetic association studies. Online tools for experiment design and data analysis are presented. Practical examples from our work in the genetics of CRS are used to help understand applications for these tools. It is expected that this article will allow physicians to acquire an improved understanding of the uses and limitations of these types of studies as these techniques become increasingly commonplace in our specialty.

Chronic rhinosinusitis (CRS) is believed to reflect an inflammatory response of the sinonasal mucosa to bacteria and/or fungi. Staphylococcus aureus, a gram-positive organism, is frequently implicated. Toll-like receptor 2 (TLR2) is involved in innate immunity, recognizing gram-positive organisms via detection of bacterial lipopeptides. As a poor response to sinus surgery has been associated with reduced levels of TLR2 expression, and given the frequent recovery of S. aureus in this condition, we suspected that polymorphisms in TLR2 genes are implicated in this condition. To investigate the association between single nucleotide polymorphisms (SNPs) in the TLR2 gene and CRS. Two hundred six patients with severe CRS and 200 controls were recruited prospectively. A maximally informative set of SNPs in the gene encoding TLR2 were selected from the HapMap data set and genotyped. Eleven of 12 SNPs were successfully genotyped. No significant associations could be detected for the SNPs tested within the limitations of our study, which has the power to detect only those SNPs with a relative risk of 2.0 or greater. Our findings do not support a role for polymorphisms in the TLR2 gene in the pathogenesis of CRS. Nevertheless, other genetic variants within genes regulating innate immunity may be involved and will require further assessment.

Background: Chronic rhinosinusitis (CRS) is increasingly viewed as an inflammatory condition of the sinonasal mucosa interacting with bacteria and/or fungi. However, factors conferring susceptibility to disease remain unknown. Advances in genomics offer powerful tools to explore this disorder. The goal of this study was to evaluate the effect of single nucleotide polymorphisms (SNP) on CRS in a panel of genes related to cysteinyl leukotriene metabolism. Methods: Severe cases of CRS and postal code match controls were recruited prospectively. A total of 206 cases and 200 controls were available for the present study. Using a candidate gene approach, five genes related to cysteinyl leukotriene metabolism were assessed. For each gene, we selected the maximally informative set of common SNPs (tagSNPs) using the European-derived (CEU) HapMap dataset. These SNPs are in arachidonate 5-lipoxygenase (ALOX5), arachidonate 5-lipoxygenase-activating protein (ALOX5AP), leukotriene C4 synthase (LTC4S), cysteinyl leukotriene receptor 1 (CYSLTR1) and cysteinyl leukotriene receptor 2 (CYSLTR2) genes. Results: A total of 59 SNPs were genotyped to capture the common genetic variations within these genes. Three SNPs located within the ALOX5, CYSLTR1 and ALOX5AP genes reached the nominal p-value threshold (p < 0.05) for association with CRS. However, none of these SNPs resist multiple testing adjustment. Conclusion: While these initial results do not support that polymorphsims in genes assessed involved in the leukotriene pathways are contributing to the pathogenesis of CRS, this initial study was not powered to detect polymorphisms with relative risk of 2.0 or less, where we could expect many gene effects for complex diseases to occur. Thus, despite this lack of significant association noted in this study, we believe that validation with external populations and the use of better-powered studies in the future may allow more conclusive findings.