Genome-wide approaches for identifying interacting susceptibility regions for asthma.
A genome-wide correlation analysis and cluster analysis were utilized to determine chromosomal regions that had similar nonparametric linkage scores across families in order to locate interacting susceptibility loci for asthma. Conditional analysis was performed to detect any increase in lod score over baseline. Eight of the strongest 5% of the correlations in the German and CSGA asthma data sets occurred in both data sets. The strongest positive correlations found in both data sets were between the 200 cM region on chromosome 2 with chromosome 12 at 90-120 cM (r = 0.26) and also with chromosome 6 at 40-70 cM (r = 0.24). While the cluster analysis did not find any regions that clustered across data sets, this method did detect clustering in regions that have been previously linked to asthma.
Colilla
S
S
Department of Human Genetics, University of Chicago, 920 East 58th Street, Chicago, IL 60637, USA.
Tsalenko
A
A
Pluznikov
A
A
Cox
N J
NJ
D000328:Adult; D001249:Asthma / Q000453:epidemiology / Q000235:genetics*; D002648:Child; D002874:Chromosome Mapping / Q000706:statistics & numerical data; D016000:Cluster Analysis; D004843:Epistasis, Genetic; D005260:Female; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease / Q000235:genetics; D005828:Genetics, Population; D005858:Germany; D006801:Humans; D008126:Lod Score; D008297:Male; D013223:Statistics as Topic; D014481:United States