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Genes to diseases (G2D) computational method to identify asthma candidate genes.

ABSTRACT: Asthma is a complex trait for which different strategies have been used to identify its environmental and genetic predisposing factors. Here, we describe a novel methodological approach to select candidate genes for asthma genetic association studies. In this regard, the Genes to Diseases (G2D) computational tool has been used in combination with a genome-wide scan performed in a sub-sample of the Saguenay-Lac-St-Jean (SLSJ) asthmatic familial collection (n = 609) to identify candidate genes located in two suggestive loci shown to be linked with asthma (6q26) and atopy (10q26.3), and presenting differential parent-of-origin effects. This approach combined gene selection based on the G2D data mining analysis of the bibliographic and protein public databases, or according to the genes already known to be associated with the same or a similar phenotype. Ten genes (LPA, NOX3, SNX9, VIL2, VIP, ADAM8, DOCK1, FANK1, GPR123 and PTPRE) were selected for a subsequent association study performed in a large SLSJ sample (n = 1167) of individuals tested for asthma and atopy related phenotypes. Single nucleotide polymorphisms (n = 91) within the candidate genes were genotyped and analysed using a family-based association test. The results suggest a protective association to allergic asthma for PTPRE rs7081735 in the SLSJ sample (p = 0.000463; corrected p = 0.0478). This association has not been replicated in the Childhood Asthma Management Program (CAMP) cohort. Sequencing of the regions around rs7081735 revealed additional polymorphisms, but additional genotyping did not yield new associations. These results demonstrate that the G2D tool can be useful in the selection of candidate genes located in chromosomal regions linked to a complex trait.

SUBMITTER: Tremblay K

PROVIDER: S-EPMC2488373 | biostudies-literature | 2008 Aug

REPOSITORIES: biostudies-literature

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Genes to diseases (G2D) computational method to identify asthma candidate genes.

Tremblay Karine K Lemire Mathieu M Potvin Camille C Tremblay Alexandre A Hunninghake Gary M GM Raby Benjamin A BA Hudson Thomas J TJ Perez-Iratxeta Carolina C Andrade-Navarro Miguel A MA Laprise Catherine C

PloS one 20080806 8

Asthma is a complex trait for which different strategies have been used to identify its environmental and genetic predisposing factors. Here, we describe a novel methodological approach to select candidate genes for asthma genetic association studies. In this regard, the Genes to Diseases (G2D) computational tool has been used in combination with a genome-wide scan performed in a sub-sample of the Saguenay-Lac-St-Jean (SLSJ) asthmatic familial collection (n = 609) to identify candidate genes loc ...[more]

PMID: 18682798

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Project description:BACKGROUND: Asthma genetics has been extensively studied and many genes have been associated with the development or severity of this disease. In contrast, the genetic basis of allergic rhinitis (AR) has not been evaluated as extensively. It is well known that asthma is closely related with AR since a large proportion of individuals with asthma also present symptoms of AR, and patients with AR have a 5-6 fold increased risk of developing asthma. Thus, the relevance of asthma candidate genes as predisposing factors for AR is worth investigating. The present study was designed to investigate if SNPs in highly replicated asthma genes are associated with the occurrence of AR. METHODS: A total of 192 SNPs from 21 asthma candidate genes reported to be associated with asthma in 6 or more unrelated studies were genotyped in a Swedish population with 246 AR patients and 431 controls. Genotypes for 429 SNPs from the same set of genes were also extracted from a Singapore Chinese genome-wide dataset which consisted of 456 AR cases and 486 controls. All SNPs were subsequently analyzed for association with AR and their influence on allergic sensitization to common allergens. RESULTS: A limited number of potential associations were observed and the overall pattern of P-values corresponds well to the expectations in the absence of an effect. However, in the tests of allele effects in the Chinese population the number of significant P-values exceeds the expectations. The strongest signals were found for SNPs in NPSR1 and CTLA4. In these genes, a total of nine SNPs showed P-values <0.001 with corresponding Q-values <0.05. In the NPSR1 gene some P-values were lower than the Bonferroni correction level. Reanalysis after elimination of all patients with asthmatic symptoms excluded asthma as a confounding factor in our results. Weaker indications were found for IL13 and GSTP1 with respect to sensitization to birch pollen in the Swedish population. CONCLUSIONS: Genetic variation in the majority of the highly replicated asthma genes were not associated to AR in our populations which suggest that asthma and AR could have less in common than previously anticipated. However, NPSR1 and CTLA4 can be genetic links between AR and asthma and associations of polymorphisms in NPSR1 with AR have not been reported previously.

Dataset Information

Genes to diseases (G2D) computational method to identify asthma candidate genes.

Publications

Genes to diseases (G2D) computational method to identify asthma candidate genes.

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