Related Experiment Video
Updated: Jan 7, 2026

Measurement of Pulse Propagation Velocity, Distensibility and Strain in an Abdominal Aortic Aneurysm Mouse Model
Published on: February 23, 2020
A sparse proteomic risk score incorporating plasma MMP12 level improves prediction of abdominal aortic aneurysm
Michael G Clark1, Shuai Yuan1,2, Susanna C Larsson3,4
1Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Background:
Screening criteria for abdominal aortic aneurysm (AAA) are based on clinical factors, such as age and smoking history, but do not include biological factors that may better reflect disease pathogenesis.
Objectives:
We sought to determine whether a proteomic risk score (ProRS) incorporating plasma protein abundance could improve prediction of AAA.
Methods:
We performed a cross-sectional analysis of nearly 37,000 participants in the UK Biobank Pharma Proteomics Project with plasma protein abundance data for 274 cardiometabolic proteins. ProRS models were developed using regularized regression.
Results:
The generated sparse ProRS contained well-established clinical risk factors as well as a single protein - matrix metalloproteinase 12 (MMP12). Overall performance and discriminatory utility of this model was higher than an identical model without MMP12 (difference in Brier score 2.1 × 10-4, 95% CrI 2.0-2.3 × 10-4; difference in AUROC 0.021, 95% CrI 0.020 - 0.022). Within the cohort, current AAA screening recommendations applied to 4.6% of the population and captured 30% of cases, whereas screening 4.6% of the population at highest risk by ProRS captured 52% of cases. Among individuals with incident AAA, MMP12 abundance was independently associated with time to rupture or repair (HR 1.86, 95% CI 1.39-2.50, p < 0.001). Additionally, MMP12 level improved discrimination of AAA in an external cohort (SIMPLER; difference in AUROC 0.084, 95% CrI 0.081 - 0.087).
Conclusions:
A biologically-plausible ProRS incorporating a single matrix metalloproteinase improved prediction of AAA over clinical factors alone. These results may be used to enhance screening strategies for AAA.

