Whole blood RNA-seq demonstrates an increased host immune response in individuals with cystic fibrosis who develop nontuberculous mycobacterial pulmonary disease

Background
Individuals with cystic fibrosis have an elevated lifetime risk of colonization, infection, and disease caused by nontuberculous mycobacteria. A prior study involving non-cystic fibrosis individuals reported a gene expression signature associated with susceptibility to nontuberculous mycobacteria pulmonary disease (NTM-PD). In this study, we determined whether people living with cystic fibrosis who progress to NTM-PD have a gene expression pattern similar to the one seen in the non-cystic fibrosis population.
Methods
We evaluated whole blood transcriptomics using bulk RNA-seq in a cohort of cystic fibrosis patients with samples collected closest in timing to the first isolation of nontuberculous mycobacteria. The study population included patients who did (n = 12) and did not (n = 30) develop NTM-PD following the first mycobacterial growth. Progression to NTM-PD was defined by a consensus of two expert clinicians based on reviewing clinical, microbiological, and radiologic..., Study population and clinical data
This study is a secondary data analysis using blood samples and data from the “CF Biomarker” cohort approved by the University of British Columbia-Providence Health Care ethics review board (H12-00835). The local ethics board also reviewed and approved the secondary analysis (H20-00117). Patients in the parent cohort were recruited following informed consent at the St. Paul’s Hospital Adult CF Clinic (Vancouver, Canada) between January 2012 and December 2019. In the current analysis, we included participants who consented to the future use of their samples and data, had at least one positive respiratory culture for NTM, and had a whole blood RNA sample available (PAXgene® stored at -70°C). Lung transplant recipients and subjects without a definite diagnosis of CF were excluded. We preferentially selected blood samples taken during clinically stable periods and closest to the first positive growth of NTM. We did not limit blood sampling to within a spec..., The data sets are provided as comma-separated values and can be opened with standard statistical software or explored with a spreadsheet program. In our analyses, we employed R and the GUI R studio (v 4.1.1) for analysis. Raw sequencing processing and transcript counting was done in a CentOS high performance cluster, dependencies and commands ran are described inside markdown scripts.Â