PLoS ONE (Oct 2007)

Gene expression signature in peripheral blood detects thoracic aortic aneurysm.

  • Yulei Wang,
  • Catalin C Barbacioru,
  • Dov Shiffman,
  • Sriram Balasubramanian,
  • Olga Iakoubova,
  • Maryann Tranquilli,
  • Gonzalo Albornoz,
  • Julie Blake,
  • Necip N Mehmet,
  • Dewi Ngadimo,
  • Karen Poulter,
  • Frances Chan,
  • Raymond R Samaha,
  • John A Elefteriades

DOI
https://doi.org/10.1371/journal.pone.0001050
Journal volume & issue
Vol. 2, no. 10
p. e1050

Abstract

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BackgroundThoracic aortic aneurysm (TAA) is usually asymptomatic and associated with high mortality. Adverse clinical outcome of TAA is preventable by elective surgical repair; however, identifying at-risk individuals is difficult. We hypothesized that gene expression patterns in peripheral blood cells may correlate with TAA disease status. Our goal was to identify a distinct gene expression signature in peripheral blood that may identify individuals at risk for TAA.Methods and findingsWhole genome gene expression profiles from 94 peripheral blood samples (collected from 58 individuals with TAA and 36 controls) were analyzed. Significance Analysis of Microarray (SAM) identified potential signature genes characterizing TAA vs. normal, ascending vs. descending TAA, and sporadic vs. familial TAA. Using a training set containing 36 TAA patients and 25 controls, a 41-gene classification model was constructed for detecting TAA status and an overall accuracy of 78+/-6% was achieved. Testing this classifier on an independent validation set containing 22 TAA samples and 11 controls yielded an overall classification accuracy of 78%. These 41 classifier genes were further validated by TaqMan real-time PCR assays. Classification based on the TaqMan data replicated the microarray results and achieved 80% classification accuracy on the testing set.ConclusionsThis study identified informative gene expression signatures in peripheral blood cells that can characterize TAA status and subtypes of TAA. Moreover, a 41-gene classifier based on expression signature can identify TAA patients with high accuracy. The transcriptional programs in peripheral blood leading to the identification of these markers also provide insights into the mechanism of development of aortic aneurysms and highlight potential targets for therapeutic intervention. The classifier genes identified in this study, and validated by TaqMan real-time PCR, define a set of promising potential diagnostic markers, setting the stage for a blood-based gene expression test to facilitate early detection of TAA.