POSITIONAL CANDIDATE GENE APPROACHES IN ASTHMA GENE DISC

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DESCRIPTION (Adapted from the applicant's abstract) The proposed project takes advantage of the rapid progression of the Human Genome Project (HGP) in identifying positional candidate genes and is built on our ongoing asthma gene-mapping study and existent DNA samples in 2,756 nuclear families with at least two siblings with physician-diagnosed asthma and available parents. Our preliminary analysis based on a genome-wide scan on 435 families with both siblings experiencing a positive methacholine challenge test has identified two regions that are significantly linked to asthma related phenotypes. The region near D22S926 on chromosome 22 is significantly linked to FEV1. We have initially identified 6-7 candidate genes in each of the two linkage regions. With the completion of the HGP and availability of more detailed gene annotation in the near future, the list of positional candidate genes will grow. We hypothesize that one or more of the positional candidate genes on our list is associated with asthma intermediate phenotypes with significant linkages to the candidate regions. We have identified 675 families with at least one sibling with a positive methacholine challenge test (PD20 less than or equal to? 16 mg) and high peripheral blood eosinophil count (Panel I Families), and 909 families with at least two siblings with FEV1 measurements available (Panel II Families) to test our hypothesis using the family based association test (FBAT). The DHPLC method, a state-of-the-art mutation detection technology, will be used to rapidly discover a sufficient number of novel single nucleotide polymorphism markers (SNPs) in the selected positional candidate genes. The common polymorphisms of selected candidate genes will be genotyped using oligonucleotide ligation assay (OLA). To incorporate information from two or more SNP loci from multiple related genes and from environmental risk factors in our analyses, we will also assess the contribution of haplotypes and test gene-gene and gene- environment interactions in addition to single locus analysis. There are two unique features to this proposal: (1) the linkages in the two proposed regions are significant; and (2) our large sample size assures adequate power to detect the association. With our expertise in epidemiology, clinical medicine, molecular genetics, biostatistics, and the population resources, we are confident that we can advance the understanding of the genetic determinants of asthma. The findings from the proposed study may lead to improved strategies for prevention, diagnosis, and treatment of this disease. (End of Abstract.)