Author

Adam Sang

Date of Award

January 2013

Document Type

Open Access Thesis

Degree Name

Medical Doctor (MD)

Department

Medicine

First Advisor

John A. Elefteriades

Subject Area(s)

Medicine

Abstract

Thoracic aortic aneurysms (TAAs) are clinically-silent diseases that predispose individuals to life-threatening aortic dissection or rupture. If detected early, TAAs can be safely treated with elective surgery. Therefore, there is a great clinical need in screening for TAAs. However, no reliable screening programs exist, and radiographic imaging is too costly and harmful for screening entire at-risk populations. We hypothesize that a novel diagnostic blood test based on the gene-expression profiles of a previously-identified panel of 41 genes (a RNA signature) is greater than 70% sensitive in detecting TAAs. Using RNA extracted from peripheral blood cells of 40 individuals (24 TAA patients and 16 spousal controls), we performed real-time PCR using customized TaqMan Array Cards to analyze the relative expression levels of this panel of genes. A 10-fold cross-validation study based on these expression levels was used to predict whether each sample belonged to a TAA patient or a spousal control. When compared with each sample's true clinical status, this RNA signature-based prediction model was 83% accurate, with a sensitivity of 88% and a specificity of 75%. Furthermore, the expression levels of the individual genes were largely consistent with their expression levels from a previous study of this RNA signature (r2 = 0.75 for TAA patient samples, and r2 = 0.73 for spousal control samples), supporting the reproducibility of this test. Altogether, these findings demonstrate that gene-expression profiling is an accurate, sensitive, and reliable method for detecting TAAs. If utilized as a clinical screening test, this RNA signature has the potential to detect silent TAAs, leading to earlier diagnosis and reduced mortality of this dangerous condition.

Comments

This is an Open Access Thesis.

Open Access

This Article is Open Access

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