DNA microarray analysis of chromosomal susceptibility regions to identify candidate genes for allergic disease: A pilot study
Authors: Benson, Mikael; Svensson, Per-Arne; Adner, Mikael; Carén, Helena; Carlsson, Björn; Carlsson, Lena; Martinsson, Tommy; Rudemo, Mats; Cardell, Lars Olaf
Source: Acta Oto-Laryngologica, Volume 124, Number 7, September 2004 , pp. 813-819(7)
Publisher: Informa Healthcare
Abstract:Objective To examine whether DNA microarray analysis of chromosomal susceptibility regions for allergy can help to identify candidate genes. Material and methods Nasal biopsies were obtained from 23 patients with allergic rhinitis and 12 healthy controls. RNA was extracted from the biopsies and pooled into three patient and three control pools. These were then analysed in duplicate with DNA microarrays containing 12 626 genes. Candidate genes were further examined in nasal biopsies (real-time polymerase chain reaction) and blood samples (single nucleotide polymorphisms) from other patients with allergic rhinitis and from controls. Results A total of 37 differentially expressed genes were identified according to criteria involving both the size and consistency of the gene expression levels. The chromosomal location of these genes was compared with the chromosomal susceptibility regions for allergic disease. Using a statistical method, five genes were identified in these regions, including serine protease inhibitor, Kazal type, 5 (SPINK5) and HLA-DRB2. The relevance of these genes was examined in other patients with allergic rhinitis and in controls; none of the genes were differentially expressed in nasal biopsies. Moreover, no association between allergic rhinitis and SPINK5 polymorphisms was found, at either the genotype or haplotype level. Conclusions DNA microarray analysis of chromosomal susceptibility regions did not lead to identification of candidate genes that could be validated in a new material. However, because gene polymorphisms may cause differential gene expression, further studies, including validation data, are needed to examine this approach.
Document Type: Research Article
Affiliations: Department of Mathematical Statistics Chalmers University of Technology Gothenburg Sweden
Publication date: September 2004