Identification of Predictive Epigenetic Biomarkers of Lung Disease Severity in Cystic Fibrosis

Cystic Fibrosis

Cystic Fibrosis, Lung disease, DNA methylation, Predictive biomarkers

The general aims of this project are (i) to identify predictive epigenetic biomarkers of lung disease severity in Cystic Fibrosis, (ii) to characterize a non-invasive cellular model, spontaneous sputum, for the analysis of these epigenetic biomarkers, (iii) to analyze the variations in DNA methylation for a same patient over time.

Cystic Fibrosis (CF) is an autosomal recessive disease resulting from mutations in the CFTR gene. CFTR encodes a chloride channel, mainly expressed at the apical membrane of epithelial cells. CFTR dysfunction induces mucus thickening, causing multiple disorders in respiratory, digestive and reproductive tracts. In CF patients, lung disease is the main cause of morbidity and mortality, and its severity is variable among CF patients, even among those with the same genotype. This clinical variability depends on two factors: genetic (complex alleles of CFTR gene and modifier genes) and environmental factors. Genetic factors have been largely explored, and several modifier genes have been identified. By contrast, environmental factors are still poorly known. It is well established that environmental factors modify the phenotype by acting on epigenetic marks (i.e. DNA methylation, histone modification) present in the genome. Epigenetic modifications regulate and modulate gene expression. In a previous we profiled DNA methylation genome-wide in nasal epithelial cell samples from 32 CF patients and 24 healthy controls. CF patients homozygous for the p.Phe508del mutation and \>18-years-old were stratified according to the lung disease severity. Through this study, we identified 187 genomic regions (CpG dinucleotides) differentially methylated between CF patients with mild lung disease and CF patients with severe lung disease. The present project aims at identifying predictive epigenetic biomarkers of lung disease severity, among these 187 regions. While the previous study was carried out on genomic DNA extracted from nasal epithelial cells, in the present project we will use a non-invasive model: spontaneous sputum. Hypothesis: some differentially methylated genomic regions between mild and severe CF patients can be used as predictive epigenetic biomarkers of lung disease severity in cystic fibrosis. Objectives: (i) to identify predictive epigenetic biomarkers of lung disease severity among the differentially methylated genomic regions between mild and severe CF patients, (ii) to characterize a non-invasive cellular model, spontaneous sputum, for the analysis of epigenetic biomarkers of lung disease severity in CF, (iii) to analyze the variations in DNA methylation for a same patient over time (at time of inclusion, 6 months, 12 months and 18 months)

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