Transcriptional Analysis identifies long non-coding RNAs as potential biomarkers in pneumonia and COPD exacerbation

Acute infections of the lower respiratory tract like community-acquired pneumonia (CAP) and acute exacerbations of chronic obstructive pulmonary disease (AECOPD) constitute the third most frequent cause of death worldwide. Urgent medical needs are early diagnosis and differential diagnosis as well as profound pathophysiological insights. Chronic obstructive pulmonary disease (COPD) is a poorly reversible condition characterized by airflow limitation and decrease of lung function. Community acquired pneumonia (CAP) is clinically defined by a sudden onset of severe illness that is accompanied by signs of lower respiratory tract infection, fever, cough and dyspnoea. We investigated the PBMC RNA profile of 5 healthy donors, 6 pneumonia patients and 6 COPD patients with acute exacerbations. Long non-coding RNAs (lncRNAs) and long non-coding intergenic RNAs (lincRNAs) are a newly emerging class of regulatory RNAs in the cell that can be involved in a multitude of processes e.g. epigenetic regulation and transcriptional regulation. In this regard, they are potential regulators of gene expression. From a total of 540 differentially expressed lnc and lincRNAs between CAP, AECOPD and healthy donors, we investigated which coding transcript expression patterns correlate with the expression of a given lnc- or lincRNA across all three conditions. We found RNAs that were down-regulated with disease, such as LOC100996286. The pool of transcript that correlated strongly with LOC100996286 included e.g. LRRC14 and TRAF5, and showed a strong pathway enrichment with GO terms T cell activation (p = 3.03*10^-12), T cell differentiation (p = 2.46*10^-11) and lymphocyte differentiation (p = 4.92*10^-12). Up-regulated non-coding RNAs included ENSG00000237326, which strongly correlated with genes such as ANKRD33 and CEP104. The GO term that was most strongly enriched among the genes correlating with ENSG00000237326 was myeloid cell homeostasis (p = 1.31*10^-6). Correlation of coding and non-coding RNAs might indicate co-regulation, which might yield to the establishment of interdependent biomarker networks.