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We investigated whether mutations in the genes that code for the different subunits of the amiloride-sensitive epithelial sodium channel (ENaC) might result in cystic fibrosis (CF)-like disease. In a small fraction of the patients, the disease could be potentially explained by an ENaC mutation by a Mendelian mechanism, such as p.V114I and p.F61L in SCNN1A. More importantly, a more than three-fold significant increase in incidence of several rare ENaC polymorphisms was found in the patient group (30% vs. 9% in controls), indicating an involvement of ENaC in some patients by a polygenetic mechanism. Specifically, a significantly higher number of patients carried c.-55+5G > C or p.W493R in SCNN1A in the heterozygous state, with odds ratios (ORs) of 13.5 and 2.7, respectively. The p.W493R-SCNN1A polymorphism was even found to result in a four-fold more active ENaC channel when heterologously expressed in Xenopus laevis oocytes. About I in 975 individuals in the general population will be heterozygous for the hyperactive p.W493R-SCNN1A mutation and a cystic fibrosis transmembrane conductance regulator (CFTR) gene that results in very low amounts (0-10%) functional CFTR. These ENaC/CFTR genotypes may play a hitherto unrecognized role in lung diseases. Hum Mutat 30:1093-1103, 2009. (C) 2009 Wiley-Liss, Inc.

Genetic matching potentially provides a means to alleviate the effects of incomplete Mendelian randomization in population-based gene-disease association studies. We therefore evaluated the genetic-matched pair study design on the basis of genome-wide SNP data (309 790 markers; Affymetrix GeneChip Human Mapping 500K Array) from 2457 individuals, sampled at 23 different recruitment sites across Europe. Using pair-wise identity-by-state (IBS) as a matching criterion, we tried to derive a subset of markers that would allow identification of the best overall matching (BOM) partner for a given individual, based on the IBS status for the subset alone. However, our results suggest that, by following this approach, the prediction accuracy is only notably improved by the first 20 markers selected, and increases proportionally to the marker number thereafter. Furthermore, in a considerable proportion of cases (76.0%), the BOM of a given individual, based on the complete marker set, came from a different recruitment site than the individual itself. A second marker set, specifically selected for ancestry sensitivity using singular value decomposition, performed even more poorly and was no more capable of predicting the BOM than randomly chosen subsets. This leads us to conclude that, at least in Europe, the utility of the genetic-matched pair study design depends critically on the availability of comprehensive genotype information for both cases and controls. European Journal of Human Genetics (2009) 17, 967-975; doi:10.1038/ejhg.2008.266; published online 21 January 2009

Udgivelsesdato: 2009-Jul, Genetic matching potentially provides a means to alleviate the effects of incomplete Mendelian randomization in population-based gene-disease association studies. We therefore evaluated the genetic-matched pair study design on the basis of genome-wide SNP data (309,790 markers; Affymetrix GeneChip Human Mapping 500K Array) from 2457 individuals, sampled at 23 different recruitment sites across Europe. Using pair-wise identity-by-state (IBS) as a matching criterion, we tried to derive a subset of markers that would allow identification of the best overall matching (BOM) partner for a given individual, based on the IBS status for the subset alone. However, our results suggest that, by following this approach, the prediction accuracy is only notably improved by the first 20 markers selected, and increases proportionally to the marker number thereafter. Furthermore, in a considerable proportion of cases (76.0%), the BOM of a given individual, based on the complete marker set, came from a different recruitment site than the individual itself. A second marker set, specifically selected for ancestry sensitivity using singular value decomposition, performed even more poorly and was no more capable of predicting the BOM than randomly chosen subsets. This leads us to conclude that, at least in Europe, the utility of the genetic-matched pair study design depends critically on the availability of comprehensive genotype information for both cases and controls.

Udgivelsesdato: 2008-Aug-26, Understanding the genetic structure of the European population is important, not only from a historical perspective, but also for the appropriate design and interpretation of genetic epidemiological studies. Previous population genetic analyses with autosomal markers in Europe either had a wide geographic but narrow genomic coverage [1, 2], or vice versa [3-6]. We therefore investigated Affymetrix GeneChip 500K genotype data from 2,514 individuals belonging to 23 different subpopulations, widely spread over Europe. Although we found only a low level of genetic differentiation between subpopulations, the existing differences were characterized by a strong continent-wide correlation between geographic and genetic distance. Furthermore, mean heterozygosity was larger, and mean linkage disequilibrium smaller, in southern as compared to northern Europe. Both parameters clearly showed a clinal distribution that provided evidence for a spatial continuity of genetic diversity in Europe. Our comprehensive genetic data are thus compatible with expectations based upon European population history, including the hypotheses of a south-north expansion and/or a larger effective population size in southern than in northern Europe. By including the widely used CEPH from Utah (CEU) samples into our analysis, we could show that these individuals represent northern and western Europeans reasonably well, thereby confirming their assumed regional ancestry.