No abstract

Several genome-wide screens for asthma and related phenotypes have been published to date but data on fine-mapping are scarce. For higher resolution we performed a fine-mapping study with 2 cM average spacing in often discussed asthma candidate regions (2p, 5q, 6p, 7p, 9q, 11p, and 12q) to narrow down the regions of interest. All participants of a Caucasian family study (97 families with at least two affected sib pairs) were genotyped for 49 supplementary polymorphic dinucleotide markers. Our results indicate increased evidence for linkage on chromosome 6p, 9q, and 12q. These candidate regions were further analyzed with SNP polymorphisms in the endothelin 1 (EDN1), lymphotoxin alpha (LTA), and neuronal nitric oxide synthase (NOS1) genes. In addition, IL4 -590C>T and IL10 -592C>A, localized on chromosomes 5q and 1q, respectively, have been analyzed for SNP association. Of the six SNPs tested, four revealed weak association with the examined phenotypes. These are the IL10 -592C>A SNP in the interleukin 10 gene (p=0.036 for eosinophil cell counts), the 4124T>C SNP in EDN1 (p=0.044 for asthma), the 3391C>T SNP in NOS1 with eosinophil cell counts (p=0.0086), and the 5266C>T polymorphism, also in the NOS1 gene, for high IgE levels (p=0.022). In summary, fine mapping data enable us to confine asthma candidate regions, while variants of EDN1 and NOS1, or nearby genes, may play an important role in this context. Hum Mutat 18:327 336, 2001.

Background: Asthma is a complex genetic disease with more than 20 genome-wide scans conducted so far. Regions on almost every chromosome have been linked to asthma and several genes have been associated. However, most of these associations are weak and are still awaiting replication.

These findings indicate that neither the human ITGB7 nor the VDR gene seem to be associated with the pathogenesis of asthma or the expression of related allergic phenotypes such as eosinophilia and changes in total IgE level.

To identify susceptibility gene regions for complex diseases a combined linkage analysis of several genome scans might give additional insights to individual studies. In this article we consider different weighting schemes to combine the score statistics of individual studies to an overall statistic within multipoint nonparametric linkage analysis by GENEHUNTER/ALLEGRO. With the Genetic Analysis Workshop (GAW) 12 asthma data sets the weights are dominated by the large differences in the relevant sample sizes.