Plaque characteristics and biomarkers predicting regression and progression of carotid atherosclerosis

Type 2 diabetes exacerbates changes in blood pressure-independent arterial stiffness: cross-sectional and longitudinal evidence from the SUMMIT study

Greater central artery stiffness is observed in people with type 2 diabetes (T2DM). Elevated blood pressure (BP) and altered arterial wall structure/composition in T2DM are generally considered as main drivers for this alteration. However, because conventional arterial stiffness measures are BP-dependent and as such an influence of BP remains in a measure, it is unclear if greater central artery stiffness is a function of greater BP, or due to changes in the structure and composition of the arterial wall. We aimed to measure BP-independent arterial stiffness (β0) cross-sectionally and longitudinally in T2DM. We studied 753 adults with T2DM (DM+) and 436 adults without (DM-) at baseline (Phase 1), and 310 DM+ and 210 DM- adults at 3-yr follow-up (Phase 2). We measured carotid-femoral pulse wave velocity and used it to calculate β0. In Phase 1, β0 was significantly greater in DM+ than DM- after adjusting for age and sex [27.5 (26.6-28.3) vs. 23.6 (22.4-24.8) au, P < 0.001]. Partial correlation analyses after controlling for age and sex showed that β0 was significantly associated with hemoglobin A1c (r = 0.15 P < 0.001) and heart rate [(HR): r = 0.23 P < 0.001)] in DM+. In Phase 2, percentage-change in β0 was significantly greater in DM+ than DM- [19.5 (14.9-24.0) vs. 5.0 (-0.6 to 10.6) %, P < 0.001] after adjusting for age, sex, and baseline β0. β0 was greater in DM+ than DM- and increased much more in DM+ than in DM- over 3 yr. This suggests that T2DM exacerbates BP-independent arterial stiffness and may have a complemental utility to existing arterial stiffness indices.NEW & NOTEWORTHY We demonstrate in this study a greater BP-independent arterial stiffness β0 in people with type 2 diabetes (T2DM) compared to those without, and also a greater change in β0 over 3 yr in people with T2DM than those without. These findings suggest that the intrinsic properties of the arterial wall may change in a different and more detrimental way in people with T2DM and likely represents accumulation of cardiovascular risk.

Serum proteomic profiling of carotid arteriopathy: A population outcome study

BACKGROUND AND AIMS

Circulating proteins reflecting subclinical vascular disease may improve prediction of atherosclerotic cardiovascular disease (ASCVD). We applied feature selection and unsupervised clustering on proteomic data to identify proteins associated with carotid arteriopathy and construct a protein-based classifier for ASCVD event prediction.

METHODS

491 community-dwelling participants (mean age, 58 ± 11 years; 51 % women) underwent carotid ultrasonography and proteomic profiling (CVD II panel, Olink Proteomics). ASCVD outcome was collected (median follow-up time: 10.2 years). We applied partial least squares (PLS) to identify proteins linked to carotid intima-media thickness (cIMT). Next, we assessed the association between future ASCVD events and protein-based phenogroups derived by unsupervised clustering (Gaussian Mixture modelling) based on proteins selected in PLS.

RESULTS

PLS identified 19 proteins as important, which were all associated with cIMT in multivariable-adjusted linear regression. 8 of the 19 proteins were excluded from the clustering analysis because of high collinearity. Based on the 11 remaining proteins, the clustering algorithm subdivided the cohort into two phenogroups. Compared to the first phenogroup (n = 177), participants in the second phenogroup (n = 314) presented: i) a more unfavorable lipid profile with higher total cholesterol and triglycerides and lower HDL cholesterol (p ≤ 0.014); ii) higher cIMT (p = 0.0020); and iii) a significantly higher risk for future ASCVD events (multivariable-adjusted hazard ratio (95 % CI) versus phenogroup 1: 2.05 (1.26-3.52); p = 0.0093). The protein-based phenogrouping supplemented ACC/AHA 10-year ASCVD risk scoring for prediction of a first ASCVD event.

CONCLUSIONS

Focused protein-based phenogrouping identified individuals at high risk for future ASCVD and may complement current risk stratification strategies.

Characteristics and evaluation of atherosclerotic plaques: an overview of state-of-the-art techniques

Atherosclerosis is an important cause of cerebrovascular and cardiovascular disease (CVD). Lipid infiltration, inflammation, and altered vascular stress are the critical mechanisms that cause atherosclerotic plaque formation. The hallmarks of the progression of atherosclerosis include plaque ulceration, rupture, neovascularization, and intraplaque hemorrhage, all of which are closely associated with the occurrence of CVD. Assessing the severity of atherosclerosis and plaque vulnerability is crucial for the prevention and treatment of CVD. Integrating imaging techniques for evaluating the characteristics of atherosclerotic plaques with computer simulations yields insights into plaque inflammation levels, spatial morphology, and intravascular stress distribution, resulting in a more realistic and accurate estimation of plaque state. Here, we review the characteristics and advancing techniques used to analyze intracranial and extracranial atherosclerotic plaques to provide a comprehensive understanding of atheroma.

Serum LDL-C/HDL-C ratio and the risk of carotid plaques: a longitudinal study

BACKGROUND

Dyslipidemia contributes to an increased risk of carotid atherosclerosis. However, the association between the ratio of low-density lipoprotein cholesterol (LDL-C) to high-density lipoprotein cholesterol (HDL-C) and carotid plaque formation has not been well documented. This study aims to assess the role of LDL-C/HDL-C in the risk of carotid plaque formation in a Chinese population.

METHODS

We followed 2,191 participants who attended the annual routine health examination. Cox proportional hazards regression, restricted cubic spline (RCS), and subgroup analysis were applied to evaluate the association between the LDL-C/HDL-C ratio and carotid plaques. The hazard ratio (HR) and 95% confidence interval (CI) were used to estimate the strength of the association.

RESULTS

Among 2,191 participants, 388 had incident carotid plaques detected, with a median follow-up time of 1.05 years. Compared with subjects younger than 45 years, those aged 45 to 59 years (HR: 2.00, 95% CI: 1.55-2.58) and over 60 years (HR: 3.36, 95% CI: 2.47-4.58) had an increased risk of carotid plaque formation. Males (HR: 1.26, 95% CI: 1.01-1.56), diabetes (HR: 1.46, 95% CI: 1.06-2.01) and a high LDL-C/HDL-C ratio (HR: 1.22, 95% CI: 1.07-1.38) were significantly linked with the occurrence of carotid plaques. After adjusting for potential confounding factors, we observed that a high LDL-C/HDL-C ratio promoted carotid plaque events (HR: 1.30, 95% CI: 1.12-1.50). The RCS analysis revealed a significant nonlinear association. The association was stronger among females (P-interaction < 0.05).

CONCLUSION

A high LDL-C/HDL-C ratio could accelerate the occurrence of carotid plaques. Older men with diabetes and dyslipidemia are the critical target population. Women may be more likely to benefit from lipid-lowering interventions and thus avoid carotid plaque formation.