Identification of a new gene mutated in Fraser syndrome and mouse myelencephalic blebs

Fraser syndrome is a recessive, multisystem disorder presenting with cryptophthalmos, syndactyly and renal defects and associated with loss-of-function mutations of the extracellular matrix protein FRAS1. Fras1 mutant mice have a blebbed phenotype characterized by intrauterine epithelial fragility generating serous and, later, hemorrhagic blisters. The myelencephalic blebs (my) strain has a similar phenotype. We mapped my to Frem2, a gene related to Fras1 and Frem1, and showed that a Frem2 gene-trap mutation was allelic to my. Expression of Frem2 in adult kidneys correlated with cyst formation in my homozygotes, indicating that the gene is required for maintaining the differentiated state of renal epithelia. Two individuals with Fraser syndrome were homozygous with respect to the same missense mutation of FREM2, confirming genetic heterogeneity. This is the only missense mutation reported in any blebbing mutant or individual with Fraser syndrome, suggesting that calcium binding in the CALXbeta-cadherin motif is important for normal functioning of FREM2.     

Population structure, differential bias and genomic control in a large-scale, case-control association study

The main problems in drawing causal inferences from epidemiological case-control studies are confounding by unmeasured extraneous factors, selection bias and differential misclassification of exposure. In genetics the first of these, in the form of population structure, has dominated recent debate. Population structure explained part of the significant +11.2% inflation of test statistics we observed in an analysis of 6,322 nonsynonymous SNPs in 816 cases of type 1 diabetes and 877 population-based controls from Great Britain. The remainder of the inflation resulted from differential bias in genotype scoring between case and control DNA samples, which originated from two laboratories, causing false-positive associations. To avoid excluding SNPs and losing valuable information, we extended the genomic control method by applying a variable downweighting to each SNP.