Application of a New Method for GWAS in a Related Case/Control Sample with Known Pedigree Structure: Identification of New Loci for Nephrolithiasis

In contrast to large GWA studies based on thousands of individuals and large meta-analyses combining GWAS results, we analyzed a small case/control sample for uric acid nephrolithiasis. Our cohort of closely related individuals is derived from a small, genetically isolated village in Sardinia, with well-characterized genealogical data linking the extant population up to the 16th century. It is expected that the number of risk alleles involved in complex disorders is smaller in isolated founder populations than in more diverse populations, and the power to detect association with complex traits may be increased when related, homogeneous affected individuals are selected, as they are more likely to be enriched with and share specific risk variants than are unrelated, affected individuals from the general population. When related individuals are included in an association study, correlations among relatives must be accurately taken into account to ensure validity of the results. A recently proposed association method uses an empirical genotypic covariance matrix estimated from genome-screen data to allow for additional population structure and cryptic relatedness that may not be captured by the genealogical data. We apply the method to our data, and we also investigate the properties of the method, as well as other association methods, in our highly inbred population, as previous applications were to outbred samples. The more promising regions identified in our initial study in the genetic isolate were then further investigated in an independent sample collected from the Italian population. Among the loci that showed association in this study, we observed evidence of a possible involvement of the region encompassing the gene LRRC16A, already associated to serum uric acid levels in a large meta-analysis of 14 GWAS, suggesting that this locus might lead a pathway for uric acid metabolism that may be involved in gout as well as in nephrolithiasis.Author Summary: There are a number of factors that contribute to renal stone formation, including diet and obesity, specific drugs, other diseases, climate changes, metabolic disorders, and genetic predisposition. In this article, we focus on identifying genomic regions that may be involved with nephrolithiasis associated with a uric acid component. We analyze data from a genetic isolate in Sardinia to take advantage of the potential improvement in power to detect association with complex traits when related, homogeneous affected individuals are selected. To take into account the correlations among our related sample of cases and controls, we applied a recently proposed method that corrects for both known and unknown population and pedigree structure using genome-wide data. In simulation studies for outbred populations with related individuals and population structure, the method has been demonstrated to provide a substantial improvement over a number of existing methods in terms of power and type 1 error. We investigate the properties of this new method, as well as other association methods, in our inbred sample. To our knowledge, this is the first application of this recently proposed method to a founder population. This study is also the first genome-wide association study carried out for uric acid nephrolithiasis.