Integration of complex data sources to provide biologic insight into pulmonary vascular disease (2015 Grover Conference Series)

Abstract

The application of complex data sources to pulmonary vascular diseases is an emerging and promising area of investigation. The use of -omics platforms, in silico modeling of gene networks, and linkage of large human cohorts with DNA biobanks are beginning to bear biologic insight into pulmonary hypertension. These approaches to high-throughput molecular phenotyping offer the possibility of discovering new therapeutic targets and identifying variability in response to therapy that can be leveraged to improve clinical care. Optimizing the methods for analyzing complex data sources and accruing large, well-phenotyped human cohorts linked to biologic data remain significant challenges. Here, we discuss two specific types of complex data sources-gene regulatory networks and DNA-linked electronic medical record cohorts-that illustrate the promise, challenges, and current limitations of these approaches to understanding and managing pulmonary vascular disease.

Keywords: biorepository; computational network modeling; electronic medical record; genomics; pulmonary vascular disease; systems biology.

Figure 1

Prediction of microRNA (miR-)130/301-PPARγ (peroxisome proliferator–activated receptor γ; also PPARG) signaling axis in pulmonary hypertension (PH) via in silico network modeling. A, As we previously reported, we constructed a comprehensive network of pulmonary hypertension (PH)–relevant genes and analyzed its pathway enrichment (color coding denotes functional pathway) and architectural structure (circles denote architectural clusters). B, We ranked microRNAs (miRNAs/miRs) on the basis of the size and intercluster spread of their target pools and identified miR-130/301 as a highly influential regulatory factor. We ranked genes in the miR-130/301 target pool in silico by “hubness” and other centrality metrics and found top-ranking genes to form the outline of two known proliferative pathways in the lung. C, D, We verified these findings in vivo and in vitro, demonstrating that miR-130/301 was upregulated in the pulmonary vasculature of PH patients (multiple etiologies; C) and that it modulated vascular proliferation in PAECs (data not shown) and PASMCs by the STAT3-miR-204-SRC axis (D). E, As predicted by our network-based algorithms, a model was confirmed of the global influence of miR-130/301 on vascular proliferation in response to a variety of PH triggers. α-SMA: α smooth muscle actin; APLN: apelin; BMPR2: bone morphogenetic protein receptor 2; CAV1: caveolin 1; FGF2: fibroblast growth factor 2; HIF-2α: hypoxia-inducible factor 2α; IL: interleukin; OCT4: octamer-binding transcription factor 4; PAEC: pulmonary arterial endothelial cell; PAH: pulmonary arterial hypertension; PASMC: pulmonary arterial smooth muscle cell; STAT3: signal transducer and activator of transcription 3. Images adapted from Bertero et al. and reprinted with permission.

Figure 2

Illustration of hemodynamic data extraction from Vanderbilt’s Synthetic Derivative. This represents a typical deidentified right heart catheterization report in Vanderbilt’s Synthetic Derivative demonstrating resting baseline values and repeat values after nitric oxide inhalation. A code is programmed for each individual hemodynamic data point and exported to a text file.

Figure 3

Diagnostic flow diagram of Vanderbilt cohort according to hemodynamic profiles. After extraction of all first-time unique right heart catheterizations (RHCs), a number of exclusions were applied, including subjects with minimal data or extreme physiology, subjects with prior heart or lung transplant, and subjects with chronic thromboembolic pulmonary hypertension (PH) or complex congenital heart disease. Subjects were subsequently stratified by hemodynamic profile into absence of PH (noPH), precapillary PH (PCPH), and pulmonary venous hypertension (PVH). PCPH was further subdivided into pulmonary arterial hypertension (PAH) on the basis of elevated pulmonary vascular resistance (PVR) and absence of parenchymal lung disease. COPD: chronic obstructive pulmonary disease; ICD-9: International Classification of Diseases, Ninth Revision; ILD: interstitial lung disease; mPAP: mean pulmonary artery pressure; PWP: pulmonary wedge pressure;