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. 2015 Jan 27;131(4):401-9; discussion 409.
doi: 10.1161/CIRCULATIONAHA.114.013317. Epub 2014 Oct 31.

Peripheral blood signature of vasodilator-responsive pulmonary arterial hypertension

Anna R Hemnes  1 , Aaron W Trammell  2 , Stephen L Archer  2 , Stuart Rich  2 , Chang Yu  2 , Hui Nian  2 , Niki Penner  2 , Mitchell Funke  2 , Lisa Wheeler  2 , Ivan M Robbins  2 , Eric D Austin  2 , John H Newman  2 , James West  2
Affiliations

Peripheral blood signature of vasodilator-responsive pulmonary arterial hypertension

Anna R Hemnes et al. Circulation. .

Abstract

Background: Heterogeneity in response to treatment of pulmonary arterial hypertension (PAH) is a major challenge to improving outcome in this disease. Although vasodilator-responsive PAH (VR-PAH) accounts for a minority of cases, VR-PAH has a pronounced response to calcium channel blockers and better survival than vasodilator-nonresponsive PAH (VN-PAH). We hypothesized that VR-PAH has a different molecular cause from VN-PAH that can be detected in the peripheral blood.

Methods and results: Microarrays of cultured lymphocytes from VR-PAH and VN-PAH patients followed at Vanderbilt University were performed with quantitative polymerase chain reaction performed on peripheral blood for the 25 most different genes. We developed a decision tree to identify VR-PAH patients on the basis of the results with validation in a second VR-PAH cohort from the University of Chicago. We found broad differences in gene expression patterns on microarray analysis including cell-cell adhesion factors and cytoskeletal and rho-GTPase genes. Thirteen of 25 genes tested in whole blood were significantly different: EPDR1, DSG2, SCD5, P2RY5, MGAT5, RHOQ, UCHL1, ZNF652, RALGPS2, TPD52, MKNL1, RAPGEF2, and PIAS1. Seven decision trees were built with the use of expression levels of 2 genes as the primary genes: DSG2, a desmosomal cadherin involved in Wnt/β-catenin signaling, and RHOQ, which encodes a cytoskeletal protein involved in insulin-mediated signaling. These trees correctly identified 5 of 5 VR-PAH patients in the validation cohort.

Conclusions: VR-PAH and VN-PAH can be differentiated with the use of RNA expression patterns in peripheral blood. These differences may reflect different molecular causes of the 2 PAH phenotypes. This biomarker methodology may identify PAH patients who have a favorable treatment response.

Keywords: biomarkers; pulmonary hypertension; treatment.

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Conflict of interest statement

Disclosures: ARH, AWT, SLA, SR, CY, HN, NP, MF, LW, IMR, EDA, JHN and JW report no conflicts of interest.

Figures

Figure 1
Figure 1
Principle Components Analysis (PCA) in VR-PAH. (A) Plot of the 3 strongest principal components, representing 14%, 11%, and 7% respectively of the total variability among the 64 arrays, shows strong separation of the calcium channel responders (red triangles) compared to non-responsive PAH (black circles) or healthy controls (green circles). (B) Each of the first three principal components separates calcium channel responders (red triangles) from both non-responsive PAH patients (black circles) and from healthy controls (p<.01 by ANOVA with post-hoc t-test). (C) Heat map of expression of 75 genes differentially expressed in calcium channel responders (top group) compared to non-responders (bottom group). Each column corresponds to a gene, while each row corresponds to a patient; green corresponds to high expression, and red to low expression. Normalization has been performed on each gene such that the range and the average are the same across genes.
Figure 2
Figure 2
Heatmap of microarray data in 19 VN-PAH patients with medication histories followed at Vanderbilt. 9/19 had prior exposure to calcium channel blockers prior to enrollment. Differences between VR-PAH and VN-PAH persisted after segregation of VN-PAH by ever- or never-exposure to calcium channel blocker medication.
Figure 3
Figure 3
Whole blood qPCR of genes differentially expressed in microarray analysis. qPCR of whole blood was performed in controls, VN-PAH and VR-PAH. VR-PAH 1 and VN-PAH 1 represent the Vanderbilt cohort, VR-PAH 2 and VN-PAH 2 represent the University of Chicago cohort. *p<0.05 by Kruskall-Wallis with Dunn’s multiple comparisons test.
Figure 4
Figure 4
Example of a decision tree to differentiate VR-PAH from VN-PAH. The figure shows an example of a decision tree based on the primary gene RHOQ and TPD52 as the secondary gene. Numbers shown within the tree are for the performance of the tree in the Vanderbilt cohort. In the upper right is the performance of the decision tree in the University of Chicago validation cohort. Below the tree is a demonstration of how the tree would be performed in one patient from VR-PAH.
See this image and copyright information in PMC

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