Clinical Trial Finder

Inclusion Criteria:

• - Diagnosed with CF.

Exclusion criteria:

- Only those subjects who are not able to consent to this protocol

BACKGROUND: Cystic Fibrosis is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene resulting in impaired chloride transport across epithelial cells. While many organs are involved, infection, inflammation and destruction of the lungs ultimately result in morbidity and mortality. There is an association between residual CFTR function and severity of disease, however there is great variability within specific mutations suggesting gene modifiers. Even though there are over 900 mutations in CFTR that are related to CF lung disease, F508 the most common one is represented in 70 percent of the American CF population. Thus, establishing a phenotype/genotype correlation using homozygote F508 patients is likely to identify genes that are responsible for a mild form of disease. Why is this important? Whereas since the identification of the gene CFTR a significant amount of knowledge has been accumulated on CFTR function and CF pathogenesis, the cure for CF (treated as a monogenic disease) has been elusive. Identification of genetic modifiers (that may explain why 10 percent of CF patients died before the age of 10, 1/3 before the age of 20 while 50 percent live over 32 years of age) should expand the therapeutic targets that may lead to shifting of the severe phenotypes to milder ones. Moreover, the approach outlined in this study may also result in a better understanding of CFTR and delta F508 biogenesis and function, as it may identify genes directly related to CFTR. The study is in response to a Request for Applications titled "Genetic Modifiers of Single Gene Defect Diseases" released in August, 2000 and co-sponsored by the National Institute of Diabetes, Digestive, and Kidney Diseases. DESIGN NARRATIVE: Patients with cystic fibrosis (CF) display a wide range of disease severity, particularly in pulmonary phenotype. Although some of this variability can be attributed to specific mutations within the CFTR gene (allelic heterogeneity), much of this variability has not been adequately explained. The central hypothesis of the study is that much of the "severity" (or "mildness") of CF lung disease reflects the influence of non-CFTR "modifier" alleles (genes). The study is designed to identify associations between non-CFTR genes and the pulmonary phenotype. To accomplish this goal, studies will be conducted on 600 CF patients who have the same CFTR genetic background, i.e., homozygous deltaF508, and who are at the extremes of pulmonary phenotype, i.e., the most severe and mildest lung disease. Pulmonary disease severity (or mildness) will be quantitated by longitudinal lung function analysis with informative censoring. The overall strategy will be to test for the association of candidate modifier alleles (genes) with the severity (or mildness) of pulmonary disease. Key clinical features (gender; age-at-diagnosis; sweat chloride; nutrition; and respiratory microbiology) will be important variables in the overall analysis. Initially, the study will test candidate genes (n=200) that have been implicated in the pathophysiology of CF lung disease. A pooling strategy will be used to expedite the first rounds of testing. After pooling DNA from the "severe" patients, and pooling DNA from the mild patients, those genes (alleles) can be identified with the greatest association with phenotype. Follow-up genotyping in individual subjects will allow subgroup analyses (gender; age-at-diagnosis; nutrition; respiratory microbiology) for each gene, as well as more complex analyses to search for interaction among different alleles. Subsequent studies will involve genome-wide testing with single nucleotide polymorphisms (SNPs) to identify loci (and genes) that are not present in the initial list of candidate genes. Identification of genes that modulate the severity of the pulmonary phenotype will improve understanding of the pathophysiology of CF lung disease, and identify new targets for therapeutic intervention.