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Cystic fibrosis (CF) is a recessive disorder caused by mutations in the CFTR gene; the main organs affected are the lungs and digestive system. The severity of lung disease in CF varies and cannot be explained by CFTR mutations; this study wanted to identify additional genetic factors that may influence disease severity.

Individuals with CF enrolled in three different studies were genotyped. Two of these cohorts, Genetic Modifier Consortium (GMC) and Canadian Consortium for Genetic Studies (CCGS) consisted of unrelated individuals and the cystic fibrosis Twin and Sibling Study (TSS) consisted of related individuals. In order to identify candidate loci, a genome-wide association (GWA) study was carried out on genotype data of the unrelated individuals as a whole and then only those with one particular CFTR mutation – a  homozygous deletion. Family based linkage analysis as well as GWA was carried out on the genotype data of the related individuals.

The GWA study on all unrelated individuals identified seven genetic regions with possible association. A significant association between lung disease severity and a single nucleotide polymorphism (SNP) on chromosome 11 was detected when the analysis was restricted to those individuals with the homozygous deletion. This association was also confirmed in the cohort of related individuals with the same deletion. Analysis on data from the TSS cohort identified a locus at chromosome 20 associated with lung disease severity.  Both these regions contain genes that modify lung function.

The use of two different approaches provided complementary findings and a method that can be applied to identify other modifying genes related to CF. Further studies are needed to investigate the candidate genes at the regions identified and their role in influencing the severity of lung disease, as well as to investigate other genetic regions identified in this study

Along with the identification of two genetic regions related to lung disease severity in CF, this research also provides a methodology that could potentially be used to study modifier genes involved in other monogenic disorders. The rarity of many monogenic disorders often means that sample sizes are too small for their use in GWA studies, but the collaborative approach used here overcomes this problem to a certain degree. This study also highlights the fact that although monogenic disorders are generally attributed to a single gene, the reality is in fact more complex.