Predicting the risk of progression in patients with thoracic aortic aneurysm

Change log
Hill, Priya 

This body of work has examined a range of easily quantifiable circulating biomarkers in a cohort of 50 patients with aneurysms of the arch and descending thoracic aorta. I have described within this thesis various obstacles (logistical and biological) to identifying biomarkers of aneurysm progression. Despite these challenges, I have created a unique dataset quantifying plasma proteins and PBMC-RNAs in a cohort of 50 AD patients with measurements of growth or clinical progression over 2 years. Analysis of my dataset indicates that: a) aortic size alone is not a good predictor of growth b) prediction of future growth can be improved by combining plasma protein measurements with aortic size:

dAoD/dT = 0.43(baseline indexed AoD) -1.5(logTGFB1) -0.86(logIL2) dAoV/dT = 1.57(baseline indexed AoD) +0.01(logTGFB1) -22.5(logIL2)

c) wall stress estimations appear to provide even more robust predictions of future growth d) PBMC-RNA profiling could be useful as a diagnostic tool to detect patients with AD aneurysms.

Sinha, Sanjay
Progression, Aorta, Aneurysm, Biomarkers, Wall stress
Doctor of Philosophy (PhD)
Awarding Institution
University of Cambridge