This proposal responds to the GO Program """"""""ARRA Medical Sequencing Discovery Projects"""""""" to establish next-generation technologies for medical resequencing in smaller academic laboratories compared to larger facilities like the Genomic Sequencing Centers. In this application, we propose to use next-generation sequencing for medical resequencing of genes that have shown highly significant associations with gout and serum uric acid levels in genome-wide association studies (GWAS) in the """"""""Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)"""""""". Resequencing will characterize the overall """"""""genetic architecture"""""""" by identification of both common functional variants that underlie GWAS statistical associations, as well as rare variants with larger phenotypic effects. Our laboratories have established key elements of next-generation sequencing including a robust and cost-effective process for subgenomic capture to enrich gene targets for resequencing, as well as implementation of the SOLID System v.3 (Applied Biosystems) and associated pipelines for data management and quality control. We have selected 11 genes from CHARGE GWAS results for resequencing of functional regions (promoters, exons, conserved regions) in gout cases and controls (total n=1,199) from the """"""""Atherosclerosis Risk in Communities (ARIC)"""""""" cohort. After resequencing, we will genotype variants in the entire ARIC cohort (n=16,000) to verify resequencing results, and to increase power for statistical analysis. Statistical analyses will include standard association studies for relatively common alleles, as well as analyses of rare variants by tests for differences in numbers of rare variant carriers in cases versus controls, and comparisons of mean uric acid concentrations in carriers versus the overall cohort. For both common and rare variants that show significant associations, we will use bioinformatics to identify possible functional consequences like non-conservative amino acid replacements and premature stop codons, disruption of normal mRNA splicing, or alterations in control elements that regulate gene expression. We propose to replicate our findings by genotyping and statistical analysis in two additional CHARGE cohorts including the """"""""Framingham Health Study (FHS)"""""""" and the """"""""Cardiovascular Health Study (CHS)"""""""".
We propose to use next-generation DNA sequencing technologies to identify genetic variants that influence gout, one of the most common forms of arthritis affecting nearly 3 million adults in the US. Our subjects are from the """"""""Atherosclerosis Risk in Community (ARIC)"""""""" study, a large multi-ethnic epidemiological cohort (16,000 subjects) that has been measured for multiple disease-related risk factors and clinical endpoints. The identification of genetic variants will provide an improved understanding of molecular mechanisms that regulate serum levels of uric acid (the major risk factor for gout), and eventually lead to novel drug targets to improve treatment of gout.
| Köttgen, Anna; Yang, Qiong; Shimmin, Lawrence C et al. (2012) Association of estimated glomerular filtration rate and urinary uromodulin concentrations with rare variants identified by UMOD gene region sequencing. PLoS One 7:e38311 |
