医学
内科学
Wnt信号通路
微阵列
基因表达
队列
病理
心脏病学
基因
生物
遗传学
作者
Anna R. Hemnes,Aaron W. Trammell,Stephen L. Archer,Stuart Rich,Chang Yu,Hui Nian,Niki Penner,Mitchell Funke,Lisa Wheeler,Ivan M. Robbins,Eric D. Austin,John H. Newman,James West
出处
期刊:Circulation
[Ovid Technologies (Wolters Kluwer)]
日期:2014-11-01
卷期号:131 (4): 401-409
被引量:84
标识
DOI:10.1161/circulationaha.114.013317
摘要
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.
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