Article

Assessing the reproducibility of asthma candidate gene associations, using genome-wide data.

Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA.
American Journal of Respiratory and Critical Care Medicine (Impact Factor: 11.99). 04/2009; 179(12):1084-90. DOI: 10.1164/rccm.200812-1860OC
Source: PubMed

ABSTRACT Association studies have implicated many genes in asthma pathogenesis, with replicated associations between single-nucleotide polymorphisms (SNPs) and asthma reported for more than 30 genes. Genome-wide genotyping enables simultaneous evaluation of most of this variation, and facilitates more comprehensive analysis of other common genetic variation around these candidate genes for association with asthma.
To use available genome-wide genotypic data to assess the reproducibility of previously reported associations with asthma and to evaluate the contribution of additional common genetic variation surrounding these loci to asthma susceptibility.
Illumina Human Hap 550Kv3 BeadChip (Illumina, San Diego, CA) SNP arrays were genotyped in 422 nuclear families participating in the Childhood Asthma Management Program. Genes with at least one SNP demonstrating prior association with asthma in two or more populations were tested for evidence of association with asthma, using family-based association testing.
We identified 39 candidate genes from the literature, using prespecified criteria. Of the 160 SNPs previously genotyped in these 39 genes, 10 SNPs in 6 genes were significantly associated with asthma (including the first independent replication for asthma-associated integrin beta(3) [ITGB3]). Evaluation of 619 additional common variants included in the Illumina 550K array revealed additional evidence of asthma association for 15 genes, although none were significant after adjustment for multiple comparisons.
We replicated asthma associations for a minority of candidate genes. Pooling genome-wide association study results from multiple studies will increase the power to appreciate marginal effects of genes and further clarify which candidates are true "asthma genes."

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Available from: Scott Weiss, Apr 23, 2015
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