@article {Tzouvelekis1730, author = {Argyrios Tzouvelekis and Jose D. Herazo-Maya and Xiting Yang and Imre Noth and Shwu-Fan Ma and Brenda M. Juan-Guardela and Heather Lynn and Joseph DeIullis and Guoying Yu and Koji Sakamoto and Melinda Klesen and Michelle Meyers and Kathleen O. Lindell and Kevin F. Gibson and Joe G.N. Garcia and Naftali Kaminski}, title = {Discovery and validation of peripheral blood gene expression profiles predictive of poor outcome and disease progression in idiopathic pulmonary fibrosis}, volume = {44}, number = {Suppl 58}, elocation-id = {1730}, year = {2014}, publisher = {European Respiratory Society}, abstract = {Rationale: Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease associated with increase mortality. In this study we aim to identify and validate peripheral blood mononuclear cell (PBMC) gene expression profiles predictive of poor outcomes and IPF progressionMethods: We collected transplant free survival (TFS) data, extracted RNA from PBMCs and performed Microarrays in IPF patients from a discovery (N=45) and replication cohort (N=75) at the University of Chicago and Pittsburgh, respectively. Significance analysis of Microarrays was used to identify genes associated with TFS. Hierarchical clustering and qRT-PCR were used to validate Microarray findings. Transcript counts were measured by the nCounter system (NanoString) in a larger (N=120), prospectively followed IPF cohort (University of Pittsburgh), at multiple time points per patient (N=425). A linear mixed model was used to identify significant associations between FVC and FVC\% with gene expressions over time after adjusting for differences in age, gender and immunosuppression use.Results: Hierarchical clustering based on 52 outcome predictive genes distinguished two clusters of IPF patients with significant differences in TFS (HR:2.08,CI:1.29-3.32,P=0.017). No differences in age, gender or immunosuppression use were identified between patients in these clusters. 43 and 40 genes of the 52-gene profile were significantly associated with changes over time in FVC and FVC\%, respectively, by the linear mixed model (P\<0.05).Conclusions:A 52-gene profile is predictive of TFS. The majority of these genes are also associated with changes in FVC and FVC\% over time.}, issn = {0903-1936}, URL = {https://erj.ersjournals.com/content/44/Suppl_58/1730}, eprint = {https://erj.ersjournals.com/content}, journal = {European Respiratory Journal} }