Towards Blood Biomarkers for Detection of Preclinical Atherosclerosis
Early atherosclerosis, meaning the stage at which there are only smaller, still-harmless fatty deposits in artery walls, is present in a sizable fraction of people in their 40s. This can be evaluated with imaging technologies, but suitable imaging approaches are comparatively expensive. Given a reliable, cheaper way to detect this early progression of the condition, adjustments in lifestyle and application of therapies might significantly postpone later mortality. It is always easier to start early in order to slow progression of age-related disease than it is to attempt to fix matters later, once atherosclerotic plaque is more developed and life-threatening.
Established plaque cannot be meaningfully reversed using presently available therapies. In particular, lowering LDL cholesterol in the bloodstream, via statins and the like, has little effect on plaque size. Given approaches under development, it will be possible to reverse plaque and aim for a cure for atherosclerosis in the future, however. Given the development of therapies capable of this goal, only realized in animal studies to date, then a marker of early atherosclerosis could lead to early reversal, periodic clearance of preclinical plaque in order to prevent atherosclerosis from ever developing.
Imaging of subclinical atherosclerosis improves cardiovascular risk prediction on top of traditional risk factors. However, cardiovascular imaging is not universally available. This work aims to identify circulating proteins that could predict subclinical atherosclerosis. Hypothesis-free proteomics was used to analyze plasma from 444 subjects from PESA cohort study (222 with extensive atherosclerosis on imaging, and 222 matched controls) at two timepoints (three years apart) for discovery, and from 350 subjects from AWHS cohort study (175 subjects with extensive atherosclerosis on imaging and 175 matched controls) for external validation. A selected three-protein panel was further validated by immunoturbidimetry in the AWHS population and in 2999 subjects from ILERVAS cohort study.
PIGR, IGHA2, APOA, HPT, and HEP2 were associated with subclinical atherosclerosis independently from traditional risk factors at both timepoints in the discovery and validation cohorts. Multivariate analysis rendered a potential three-protein biomarker panel, including IGHA2, APOA, and HPT. Immunoturbidimetry confirmed the independent associations of these three proteins with subclinical atherosclerosis in AWHS and ILERVAS. A machine-learning model with these three proteins was able to predict subclinical atherosclerosis in ILERVAS, and also in the subpopulation of individuals with low cardiovascular risk.
In conclusion, plasma levels of IGHA2, APOA and HPT are associated with subclinical atherosclerosis independently of traditional risk factors and offers potential to predict this disease. The panel could improve primary prevention strategies in areas where imaging is not available.