A novel lung disease phenotype adjusted for mortality attrition for cystic fibrosis genetic modifier studies

Abstract

Genetic studies of lung disease in cystic fibrosis (CF) are hampered by the lack of a severity measure that accounts for chronic disease progression and mortality attrition. Further, combining analyses across studies requires common phenotypes that are robust to study design and patient ascertainment. Using data from the North American Cystic Fibrosis Modifier Consortium (Canadian Consortium for CF Genetic Studies, Johns Hopkins University CF Twin and Sibling Study, and University of North Carolina/Case Western Reserve University Gene Modifier Study), the authors calculated age-specific CF percentile values of FEV1 which were adjusted for CF age-specific mortality data. The phenotype was computed for 2,061 patients representing the Canadian CF population, 1,137 extreme phenotype patients in the UNC/Case Western study, and 1,323 patients from multiple CF sib families in the CF Twin and Sibling Study. Despite differences in ascertainment and median age, our phenotype score was distributed in all three samples in a manner consistent with ascertainment differences, reflecting the lung disease severity of each individual in the underlying population. The new phenotype score was highly correlated with the previously recommended complex phenotype, but the new phenotype is more robust for shorter follow-up and for extreme ages. A disease progression and mortality-adjusted phenotype reduces the need for stratification or additional covariates, increasing statistical power, and avoiding possible distortions. This approach will facilitate large-scale genetic and environmental epidemiological studies which will provide targeted therapeutic pathways for the clinical benefit of patients with CF.

Figure 1

Cross-sectional plot of mean FEV1pp by mean age for 2061 CGS patients. Non-linear smoothed regression is plotted with 2 standard errors of the mean. Mean is based on the mean value of three years of data preceding study enrollment.

Figure 2

Cross-sectional plot of NoRMA score by mean age for 2061 CGS patients.

Figure 3

Frequency distributions of KNoRMA in the three study samples: 1137 GMS patients, 1323 TSS patients, and 2061 CGS patients.