%0 Journal Article %A Pierre-Joseph Royer %A Daniel Baron %A Damien Reboulleau %A Adrien Tissot %A Karine Botturi-Cavailles %A Antoine Roux %A Martine Reynaud-Gaubert %A Romain Kessler %A Sacha Mussot %A Claire Dromer %A Olivier Brugière %A Jean-Francois Mornex %A Romain Guillemain %A Marcel Dahan %A Christiane Knoop %A Christophe Pison %A Angela Koutsokera %A Laurent Nicod %A Sophie Brouard %A Antoine Magnan %T Blood mRNA and miRNA transcriptome to predict chronic lung allograft dysfunction %D 2015 %R 10.1183/13993003.congress-2015.PA1792 %J European Respiratory Journal %P PA1792 %V 46 %N suppl 59 %X Chronic Lung Allograft Dysfunction (CLAD) manifests as Bronchiolitis Obliterans Syndrome (BOS) and the recently described Restrictive Allograft Syndrome (RAS). CLAD is unpredictable and irreversible. Thus predictive biomarkers of CLAD are needed to provide an early and personalized intervention.Our objective is to establish a predictive blood transcriptomic signature of CLAD. We hypothesized that gene and miRNA expression profiling of peripheral blood could uncover the early alterations of CLAD before the degradation of lung function. We selected 88 lung transplant recipients from the COLT (Cohort in Lung Transplantation) cohort. Patients were unequivocally phenotyped by an adjudication committee at 3 years post transplantation as stable (n=49), BOS (n=29) or RAS (n=10). Blood transcriptome (mRNA and microRNA) was investigated longitudinally at 6 months and 1 year post-transplantation, i.e. before the onset of CLAD. Integrated analysis of miRNA and mRNA expression was performed.Preliminary results show more than 500 differentially expressed genes (DEG) between Stable and BOS groups. Hierarchical clustering of DEG discriminates between stable and BOS patients with an accuracy approaching 80%. Gene ontology was conducted to categorize the function of the DEG. Analysis of KEGG pathways revealed several enrichment-related pathways including haematopoietic cell lineage or B cell receptor signaling pathway.As a conclusion, our work supports blood transcriptome analysis to predict and to explore the physiopathology of CLAD. Several biomarkers and pathways were identified. Investigations are ongoing to define the final gene-set predictor.Systems prediction of CLAD: http://www.sysclad.eu/ %U