Mapping Phenotypes in Abdominal Aortic Aneurysms

/Abstract Abdominal aortic aneurysms (AAA) are prevalent in the US Veteran population and associate with high morbidity and mortality when dilation occurs to the point of rupture. Monitoring by imaging is the current gold standard for measuring current vessel dimensions for risk stratification and deciding on need for surgical repair. Surgical repair is associated with a high morbidity and mortality, making it unsuitable for routine standard care, and imaging provides information on dilation progression that has already occurred. Understanding mechanisms of growth in humans with AAA, therefore, will allow us to predict which individuals will experience growth before they do, which would greatly improve our management of Veterans with AAA. The goal of this project is to develop and validate a plasma protein interactome map that can inform present and future AAA status clinically and provide mechanistic insight into how aneurysms progressively dilate. We will use the clinical dataset obtained from the Non-invasive Treatment of Abdominal Aortic Aneurysm Clinical Trial (N-TA3CT). N-TA3CT was a randomized, placebo-controlled, double-blind clinical trial that assessed effect of doxycycline (100 mg orally twice a day) on growth of small AAA. Added to this dataset, we have quantified >1,000 proteins from plasma samples for deep proteomic assessment. We hypothesize that constructing a comprehensive AAA interaction network map will reveal plasma protein patterns that signify current and predict future aortic aneurysm growth regulated by neutrophil activation. Aim 1 will map plasma proteins that denote current and predict future aneurysm growth, Aim 2 will determine plasma proteins that reflect neutrophil activation as an indicator of aneurysm status, and Aim 3 will establish and extensively validate an AAA interaction network map that informs aneurysm status. This project will address knowledge gaps regarding how to assess aneurysmal remodeling and how to predict future progression in dilation. The Veteran population is particularly afflicted by AAA, and understanding how to most effectively track our patients will not only improve their care but also refine the need for timely and expensive surveillance monitoring by imaging. Project Number: 1I01CX002780-01A1 | Fiscal Year: 2026 | NIH Institute/Center: Veterans Affairs (VA) | Principal Investigator: JOHN CURCI | Institution: VETERANS HEALTH ADMINISTRATION, NASHVILLE, TN | Activity Code: I01 | Study Section: Special Emphasis Panel[ZRD1 SURG-P (01)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11170239