• Marco Mura, Masaki Anraku, Zhihong Yun, Karen McRae, Mingyao Liu, Thomas K Waddell, Lianne G Singer, John T Granton, Shaf Keshavjee, and Marc de Perrot.
• Toronto General Hospital, Toronto, ON, Canada.
• Chest. 2012 Mar 1;141(3):661-73.

BackgroundPulmonary hypertension (PH) associated with pulmonary fibrosis (PF) is a severe condition with poor outcome. It is unknown whether patients with PF with associated PH (APH) represent a distinct phenotype of the disease. We hypothesized that the lung tissue gene expression pattern of patients with APH has a characteristic profile when compared with patients with PF without APH. We sought to determine if different gene expression signatures in PF could be determined based on pulmonary arterial pressures (PAPs) and to provide new insights into the pathobiology of APH.MethodsMicroarray analysis (Affymetrix) was performed after RNA was extracted from explanted lungs in 116 consecutive patients with PF (development set, n = 84; validation set, n = 32) and seven subjects with idiopathic pulmonary arterial hypertension undergoing lung transplant (LTx). PAP were recorded intraoperatively immediately before starting LTx. The development set was divided into three groups according to mean PAP (mPAP): severe PH group (mPAP ≥ 40 mm Hg, n = 17); intermediate PH group (mPAP 21-39 mm Hg, n = 45); NoPH group (mPAP ≤ 20 mm Hg, n = 22).ResultsDistinct gene signatures were observed. Patients in the severe PH group showed increased expression of genes, gene sets, and networks related to myofibroblast proliferation and vascular remodeling, whereas patients in the NoPH group strongly expressed proinflammatory genes. Two-dimensional hierarchic clustering based on 222 differentially expressed genes (severe PH vs no PH) dichotomized subjects into two phenotypes in the intermediate PH group and in the validation set. Real-time polymerase chain reaction confirmed the differential expression of selected genes.ConclusionsGene expression profiles distinguish PF phenotypes with and without APH. This observation can have important implications for future trials.

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