Background and Aims

To determine the sex-specific added value of carotid plaque components – beyond traditional cardiovascular risk factors – for predicting new-onset atherosclerotic cardiovascular disease (ASCVD).

Methods

Between 2007 and 2012, participants from the population-based Rotterdam Study with asymptomatic carotid wall thickening >2.5 mm on ultrasonography, were invited for carotid MRI. Among 1349 participants (mean age: 72 years, 49.5% women) without cardiovascular disease, we assessed plaque thickness, carotid stenosis (>30%), presence of intraplaque hemorrhage, lipid-rich necrotic core, and calcification. Follow-up for ASCVD was complete until January 1, 2015. Using Cox regression we fitted sex-specific prediction models including traditional cardiovascular risk factors (‘base’ models), and calculated 5-year predicted risks of ASCVD. We extended the ‘base’ models by single and simultaneous additions of plaque characteristics, and calculated the c-statistics.

Results

The median predicted 5-year ASCVD risk based on cardiovascular risk factors was 5.3% in women and 9.5% in men. Intraplaque hemorrhage was a strong predictor of ASCVD in women (adjusted HR: 3.31, 95%CI=1.77-6.17). The c-statistic (95%CI) improved from 0.72 (0.65-0.78) to 0.76 (0.70-0.83) after single addition of intraplaque hemorrhage to the ‘base’ model. Simultaneous addition of plaque components, plaque thickness, and stenosis did not change these results. In men, carotid stenosis was associated with incident ASCVD (adjusted HR: 1.75, 95%CI=1.00-3.08), yet the association diminished after additionally adding other plaque characteristics, and no improvements were observed in c-statistics.

Conclusions

Presence of intraplaque hemorrhage is a strong predictor of ASCVD in women, independent of traditional cardiovascular risk factors, other plaque components, plaque size, and stenosis.

Background and Aims

Common cardiovascular risk equations are imprecise for heterozygous Familial Hypercholesterolemia (HeFH). Coronary Artery Calcium (CAC) score could help to better stratify the risk of major cardiovascular events (MACE). We investigated the additional contribution of CAC Score to SAFEHEART risk equation (SAFEHEART-RE) for MACE prediction in HeFH.

Methods

We analyzed data from primary prevention HeFH patients undergoing CAC quantification from two ongoing national registries , REFERCHOL and SAFEHEART. CAC score was expressed as log(CAC + 1).We used probability-weighted Cox proportional hazard models to estimate hazard ratios (HR). Area under the receiver operator characteristic curve (AUC) and net reclassification improvement (NRI) were used to compare incremental contribution of CAC score to SAFEHEART-RE for MACE prediction. MACE were defined as coronary heart disease, stroke or transient ischemic attack, peripheral artery disease, resuscitated sudden death and cardiovascular death.

Results

We included 1424 patients (age 48.9±12.8, men 45.9%).

After a 2.4-years follow-up, MACE occurred in 70 subjects. The addition of log(CAC+1) to SAFEHEART-RE was associated with an improved prediction of MACE in intermediate-risk (from HR 3.2 [95%CI 1.77-5.59] to HR 8.18 [95%CI 3.26-20.37]) and in high-risk subjects (from HR 3.5 [95%CI 1.93-6.30] to HR 20.21 [95%CI 8.58-47.6]) (log-rank p <0.0001). The c-statistics confirmed a significant improvement in MACE prediction by the addition of log(CAC+1) to SAFEHEART-RE (AUC 0.896 [0.889-0.903]) versus SAFEHEART-RE alone (AUC 0.859 [0.852-0.866]) (p= 0.004). The addition of CAC score was associated with an overall NRI of 46.8%.

Conclusions

Identification of very-high risk HeFH patients is possible by combining information from SAFEHEART-RE and CAC score.

Background and Aims

We recently reported on the cellular landscape of advanced carotid atherosclerotic plaques, providing detailed insight on plaque pathology while creating a vast resource for further studies. Large-scale GWAS have identified hundreds of common variants for atherosclerotic disease and cardiovascular risk factors. One of the major challenges in the post-GWAS era remains decoding of susceptibility loci to targets that have the ability to translate into clinical care.

Methods

We developed a framework where we intersected scRNA-seq and GWAS summary statistics to offer a data driven guide towards disease relevant target identification. We performed gene-based association studies using GWAS summary statistics of atherosclerotic disease, cardiometabolic traits and other traits. We calculated a per cell population score to test for enrichment based on expression in individual cells of plaques of associated genes.

Results

We show that loci associated with coronary artery disease have a prominent substrate in plaque SMCs (APOE, KANK2, SORT1), ECs (SLC44A1, ATP2B1) and MCs (APOE, HNRNPUL1), and coronary calcification loci risk loci are present in SMCs and ECs (COL5A1, YWHAE and MORF4L1). Considering plaque SMC-subtypes, risk loci for coronary calcification were enriched in synthetic SMCs. To assess the generalizability of our workflow, we applied our method to scRNAseq-data of liver and show that hepatocyte cell populations are enriched for circulating lipid-associated loci.

Conclusions

We present a data-driven guide to identify putative target genes in known susceptibility loci of cardiovascular traits that can be validated through functional testing in relevant cell types.

Background and Aims

Atherosclerosis is a chronic inflammatory process involving multiple different cells including monocytes and smooth muscle cells. There is accumulating evidence suggesting that colchicine might be beneficial in these patients with atherosclerosis however, its specific mechanism of action on plaque cells remains unclear.

Methods

Apolipoprotein E knockout mice (ApoE^-/-) on a high fat diet were treated with daily intraperitoneal injections of Colchicine or PBS for 16 weeks. The aorta was harvested for en face staining, immunostaining, and qPCR analysis. Human Peripheral Blood Monocytes (HPBM) and Human Coronary Artery Smooth Muscle Cells (HCASMC) from healthy donors were treated with Colchicine In Vitro. HPBM were also isolated from Acute Coronary Syndrome (ACS) patients and treated with Colchicine In Vitro.

Results

Colchicine treated ApoE^-/- mice had decreased atherosclerotic plaque burden and lipid content on en face staining of the aorta. There was also a decrease in CD68⁺ cells within atherosclerotic plaques. Colchicine treated mice also had lower pro-inflammatory transcript levels of IL-1β, TNF-α, IL-6 and MCP-1. LPS stimulated HPBM that were treated with Colchicine demonstrated a decrease in TNF-α and MCP-1 gene and protein expression. In Vitro treatment of HCASMC with Colchicine demonstrated decreased cholesterol and oxidised LDL (ox-LDL) uptake as well as decreased IL-6 and MCP-1 transcript levels. There was also a reduction in HCASMC proliferation, migration and lipid uptake when cultured in Colchicine treated LPS-stimulated Monocyte secreted media from healthy controls and ACS patients.

Conclusions

Colchicine treatment decreases atherogenesis in a murine model of atherosclerosis and demonstrated anti-inflammatory effects on monocytes and smooth muscle cells.