Late Breaking Abstract - Endobronchial gene-expression clustering in COPD identifies a subgroup with higher level of lymphocytes and accelerated lung function decline

COPD is primarily diagnosed, staged and monitored by phenotypical parameters (e.g. pulmonary function test), even though it is well known that these hardly reflect differences in underlying pathology. Genome-wide gene-expression profiling presents a new depth, which could offer an addition to endotyping (distinct pathobiological mechanism). The aim of this study was to investigate whether whole genome-gene expression profiling in bronchial biopsies can be used to identify different endotypes of COPD. COPD patients were 45-75 years old, had an FEV1/FVC As starting point for cluster-analysis, we used a published 98 genes COPD signature from bronchial brushes. Of these 98 genes, 93 were detected in our RNA-seq dataset and therefore used for unbiased ConcensusClusterPlus clustering. Analysis demonstrated that based on least inter-group consensus, 2 clusters were optimal; COPD Airway Gene Expressed 1 (CAGE1)-cluster (n=39) and CAGE2-cluster (n=17) (Fig. 1A-B). The main differences between the clusters included higher levels of sputum lymphocytes and CD4+ and CD8+ T-cells in biopsies (Fig. 1C). Lung function decline (LFD) between 0.5 to 7.5 years was greater in CAGE2, i.e. 74.3ml vs. 53.2ml, P=0.005 (fig. 1D), which was unable to be predicted by baseline inflammatory cell counts. Smoking status did not affect these outcomes. In conclusion, clustering based on gene-expression profiling identified a COPD phenotype with higher bronchial CD8+ T-cell numbers and accelerated LFD.