Systems Analysis of the Human Pulmonary Arterial Hypertension Lung Transcriptome

Stearman RS, Bui QM, Speyer G, Handen A, Cornelius AR, Graham B, Kim S, Mickler EA, Tuder RM, Chan SY, Geraci MW 2019. American Journal of Respiratory Cell and Molecular Biology


Rationale: Pulmonary arterial hypertension (PAH) is characterized by increased pulmonary artery pressure and vascular resistance, typically leading to right heart failure and death. Current therapies improve quality of life of the patients but have a modest effect on long-term survival. A detailed transcriptomics and systems biology view of the PAH lung is expected to provide new testable hypotheses for exploring novel treatments. Objectives: Complete transcriptomics analysis of PAH and control lung tissue to develop disease-specific and clinical data/tissue pathology gene expression classifiers from expression datasets. Gene expression data were integrated into pathway analyses. Methods: Gene expression microarray data was collected from 58 PAH and 25 control lung tissues. The strength of the dataset and its derived disease classifier was validated using multiple approaches. Pathways and upstream regulators analyses was completed with standard and novel graphical approaches. Measurements and Main Results: The PAH lung dataset identified expression patterns specific to PAH subtypes, clinical parameters, and lung pathology variables. Pathway analyses indicate the important global role tumor necrosis factor and transforming growth factor signaling pathways. In addition, novel upstream regulators and insight into the cellular and innate immune responses driving PAH were identified. Finally, WNT-signaling pathways may be a major determinant underlying the observed sex differences in PAH. Conclusion: This study provides a transcriptional framework for the PAH-diseased lung, supported by previously reported findings, and will be a valuable resource to PAH research community. Our investigation revealed novel potential targets and pathways amenable to further study in a variety of experimental systems.