Multidimensional clinical phenotyping of an adult cystic fibrosis patient population.

Douglas J Conrad,Barbara A Bailey,Amit Gaggar

doi:10.1371/journal.pone.0122705

Abstract

BackgroundCystic Fibrosis (CF) is a multi-systemic disease resulting from mutations in the Cystic Fibrosis Transmembrane Regulator (CFTR) gene and has major manifestations in the sino-pulmonary, and gastro-intestinal tracts. Clinical phenotypes were generated using 26 common clinical variables to generate classes that overlapped quantiles of lung function and were based on multiple aspects of CF systemic disease.MethodsThe variables included age, gender, CFTR mutations, FEV1% predicted, FVC% predicted, height, weight, Brasfield chest xray score, pancreatic sufficiency status and clinical microbiology results. Complete datasets were compiled on 211 subjects. Phenotypes were identified using a proximity matrix generated by the unsupervised Random Forests algorithm and subsequent clustering by the Partitioning around Medoids (PAM) algorithm. The final phenotypic classes were then characterized and compared to a similar dataset obtained three years earlier.FindingsClinical phenotypes were identified using a clustering strategy that generated four and five phenotypes. Each strategy identified 1) a low lung health scores phenotype, 2) a younger, well-nourished, male-dominated class, 3) various high lung health score phenotypes that varied in terms of age, gender and nutritional status. This multidimensional clinical phenotyping strategy identified classes with expected microbiology results and low risk clinical phenotypes with pancreatic sufficiency.InterpretationThis study demonstrated regional adult CF clinical phenotypes using non-parametric, continuous, ordinal and categorical data with a minimal amount of subjective data to identify clinically relevant phenotypes. These studies identified the relative stability of the phenotypes, demonstrated specific phenotypes consistent with published findings and identified others needing further study.

Highlights

Cystic fibrosis is a multi-system disease with clinical manifestations in sweat glands, sinuses, lungs, pancreas, hepato-biliary tree, and the lower gastrointestinal tract
An earlier report using a similar approach in a homozygous ΔF508 Cystic Fibrosis Transmembrane Regulator (CFTR) Cystic Fibrosis (CF) patient population identified the borders dividing severe, moderate and mild patient populations at ageÃFEV1% products of approximately 1000 and 1600 [10]
The distribution of the ageÃFEV1% predicted product in this current less-restricted patient population demonstrated a rightward shift of the distribution compared to the earlier data as a result of including all genotypes (Figs. 1 and S2)

Summary

Introduction

Cystic fibrosis is a multi-system disease with clinical manifestations in sweat glands, sinuses, lungs, pancreas, hepato-biliary tree, and the lower gastrointestinal tract. These manifestations result from mutations in the Cystic Fibrosis Transmembrane Regulator (CFTR) gene which cause mucus dysfunction above epithelial surfaces [1]. (PA), Staphylococcus aureus, and other fungal species which are inherently resistant to anti-microbial therapy [2] These chronic airway infections incite innate and adaptive immune responses which cause most of the morbidity and mortality associated with CF. Cystic Fibrosis (CF) is a multi-systemic disease resulting from mutations in the Cystic Fibrosis Transmembrane Regulator (CFTR) gene and has major manifestations in the sino-pulmonary, and gastro-intestinal tracts. Clinical phenotypes were generated using 26 common clinical variables to generate classes that overlapped quantiles of lung function and were based on multiple aspects of CF systemic disease.

Methods

Results

Conclusion