Carotid stiffness is associated with retinal microvascular dysfunction-The Maastricht study

Instrumenting Carotid Sonography Biomarkers and Polygenic Risk Score As a Novel Screening Approach for Retinal Detachment

Purpose

Retinal detachment (RD) is a vision-threatening condition that manifests silently before abrupt disease onset; thus, most of the RD at-risk individuals are left unchecked until the first RD attack.

Methods

To establish an RD risk-informing system for a broader population, we utilized carotid ultrasonography (CUS) biometrics, RD polygenic risk score (PRSRD), and clinical covariates (COVs) to assess RD risk predisposition factors. First, a backpropagation logistic regression model identified RD-associated CUS biomarkers and further incorporated them as a multivariable RD-risk nomogram. Next, a PRSRD model was established with the selected single-nucleotide polymorphisms (SNPs) curated as high functional expression candidates in the retina single-cell RNA datasets. Finally, a three-component RD prediction model (CUS, PRSRD, and COVs) was assembled by logistic cumulative analysis.

Results

Demographic analysis reported hypertension (HTN) status was associated with RD (odds ratio [OR] = 1.601). The CUS regression model revealed that the minimum flow of the right internal carotid artery (ICA-Qmin; OR = 1.04) and the time-averaged maximum velocity of the right common carotid artery (CCA-TAMAX; OR = 1.03) were associated with increased RD risk. Notably, genome-wide association studies (GWAS) identified three significant SNPs (IGFBPL1 rs117248428, OR = 1.63; CELF2 rs56168975, OR = 1.72; and PAX6 rs11825821, OR = 1.61; P < 5.00 × 10-6) that are highly expressed at the RD border of the retinal pigment epithelium and choroid. Finally, the three-component model demonstrated state-of-the-art RD prediction (AUCHTN+ = 0.95, AUCHTN- = 0.93).

Conclusions

Based on instrumenting CUS images and genetic PRSRD, we are proposing a screening method for RD at-risk patients.

Translational Relevance

Results from this study demonstrated the combination of CUS and GWAS as a cost-effective, population-wide screening framework for identifying RD at-risk individuals.

Retinal Microvascular Changes in Association with Endothelial Glycocalyx Damage and Arterial Stiffness in Patients with Diabetes Mellitus Type 2: A Cross-Sectional Study in a Greek Population

PURPOSE

To evaluate the potential association between endothelial glycocalyx damage, as well as arterial stiffness, and the retinal changes on optical coherence tomography (OCT) and OCT-angiography (OCT-A) in patients with type 2 diabetes mellitus (DM).

METHODS

Participants in this cross-sectional study were 65 patients with DM type 2 and 42 age- and gender-matched controls without DM. The demographic and clinical characteristics of the participants were recorded. All patients underwent a thorough ophthalmological examination and multimodal imaging, including fundus photography, OCT, and OCT-A. In addition, evaluation of the endothelial glycocalyx thickness by measuring the perfused boundary region (PBR5-25) of the sublingual microvessel, as well as of the arterial stiffness, by measuring the carotid-femoral pulse wave velocity (PWV), the central aortic pressures and the augmentation index (Aix) was performed. Univariate and multivariate logistic regression analysis was performed for the examination of the potential association between the eye imaging variables and the cardiovascular-related variables. The odds ratios (OR) with the respective 95% confidence intervals (CI) were calculated. A p-value < 0.05 was considered statistically significant.

RESULTS

Patients with DM presented significantly higher PBR5-25 compared to controls without DM (p = 0.023). At the univariate analysis, increased PBR5-25 (≥2.19 μm vs. <2.19 μm) was associated with decreased peripapillary VD at the superior quadrant (univariate OR (95% CI) = 0.34 (0.12-0.93), p = 0.037). Multivariate logistic regression analysis showed that increased PWV (≥13.7 m/s vs. <13.7 m/s) was associated with an increased foveal avascular zone (FAZ) area on OCT-A (p = 0.044) and increased FAZ perimeter (p = 0.048). Moreover, increased Aix (≥14.745% vs. <14.745%) was associated with diabetic macular edema (DME) presence (p = 0.050) and increased perifoveal and parafoveal superior and temporal thickness on OCT (p < 0.05 for all associations).

CONCLUSIONS

Markers of endothelial damage and arterial stiffness were associated with structural and microvascular retinal alterations in patients with DM, pointing out that OCT-A could be a useful biomarker for detecting potential cardiovascular risk in such patients.

Associations of between- and within-day patterns of physical activity accumulation with arterial stiffness and indices of microvascular health-Evidence from The Maastricht study

While physical activity (PA) is understood to promote vascular health, little is known about whether the daily and weekly patterns of PA accumulation associate with vascular health. Accelerometer-derived (activPAL3) 6- or 7-day stepping was analyzed for 6430 participants in The Maastricht Study (50.4% women; 22.4% Type 2 diabetes mellitus (T2DM)). Multivariable regression models examined associations between stepping metrics (average step count, and time spent slower and faster paced stepping) with arterial stiffness (measured as carotid-femoral pulse wave velocity (cfPWV)), and several indices of microvascular health (heat-induced skin hyperemia, retinal vessel reactivity and diameter), adjusting for confounders and moderators. PA pattern metrics were added to the regression models to identify associations with vascular health beyond that of stepping metrics. Analyses were stratified by T2DM status if an interaction effect was present. Average step count and time spent faster paced stepping was associated with better vascular health, and the association was stronger in those with compared to those without T2DM. In fully adjusted models a higher step count inter-daily stability was associated with a higher (worse) cfPWV in those without T2DM (std β = 0.04, p = 0.007) and retinal venular diameter in the whole cohort (std β = 0.07, p = 0.002). A higher within-day variability in faster paced stepping was associated with a lower (worse) heat-induced skin hyperemia in those with T2DM (std β = -0.31, p = 0.008). Above and beyond PA volume, the daily and weekly patterns in which PA was accumulated were additionally associated with improved macro- and microvascular health, which may have implications for the prevention of vascular disease.

Assessment of the relationship of systemic vascular dysfunction and cardiac autonomic neuropathy (CAN) with diabetic retinopathy

Context

Diabetic retinopathy, a form of microvasculopathy, is the leading cause of the visual abnormality. However, there is no conclusive evidence of the relationship of systemic vascular dysfunction with retinal microvasculopathy. In addition, diabetes-associated cardiac autonomic neuropathy may also compromise vascular function.

Aims

The present study intends to correlate arterial stiffness, endothelial function, and heart rate variability (HRV) as a standardized measure of cardiac autonomic neuropathy with diabetic retinopathy.

Settings and Design

The present cross-sectional, observational study was conducted in the Department of Physiology.

Materials and Methods

Twenty subjects were recruited in group 1 (T2DM, type 2 diabetes mellitus patients, without retinopathy) and group 2 (T2DM with retinopathy). The vascular parameters such as heart rate, peripheral and central blood pressure, augmentation index [AIx (%)], brachial -ankle pulse wave velocity (baPWV), and reactive hyperaemia index (RHI) were recorded.

Statistical Analysis Used

Independent sample t-test (for parametric data) and Mann-Whitney U test (for non-parametric data) were employed to compare the variables of two groups. Spearman correlation was used to examine the relationship among the parameters. Linear regression analysis was performed to examine the important vascular predictor for diabetic retinopathy.

Results

baPWV was significantly higher in group 2 than in group 1 and positively associated with group 2. RHI was significantly less in group 2 than group 1 and negatively associated with group 2. Among HRV metrics, standard deviation of successive differences (SDSD), root mean square of successive differences between normal heartbeats (RMSSD), and high frequency (HF) power were significantly decreased in group 2 than in group 1. SDSD, RMSSD, and HF power were negatively associated with group 2. RHI emerged as a significant predictor of diabetic retinopathy following linear regression.

Conclusions

Overall, the result of the present study indicates that metabolic dysregulation of glucose may affect the normal functioning of the autonomic nervous system and vascular function. Therefore, screening of vascular function and cardiac autonomic tone may be advocated in diabetic patients in routine clinics to examine the existence of any comorbid condition, such as diabetic retinopathy, as systemic vascular changes may also affect ophthalmic vasculature.

Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review

Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework.