Predicting the risk of progression in patients with thoracic aortic aneurysm

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.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2020

Author dc:creator

• Hill, Priya

Advisor dc:contributor.advisor

• Sinha, Sanjay

• Progression
• Aorta
• Aneurysm
• Biomarkers
• Wall stress

Licence

• https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/3d6163ba-5b6f-4866-b00d-e0b5c1ab152c/download
• https://www.rioxx.net/licenses/all-rights-reserved/

Language dc:language

en

DOI dc:identifier.doi

https://doi.org/10.17863/CAM.47001

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/299932