Early predictors of carotid atherosclerosis in patients with type 2 diabetes mellitus

Abstract

Type 2 diabetes mellitus (T2DM) promotes a risk of the development of atherosclerosis and potentiates atherosclerotic cardiovascular events. Among these patients, chronic hyperglycemia, dyslipidemia, oxidative stress and systemic inflammation has been found as triggers for accelerating plaque formation. Additionally, conventionally used risk factors, such as age, overweight/obesity, hypertension, poor glycemic control, renal dysfunction, and metabolic disturbances frequently underestimate the patients at the risk of asymptomatic carotid atherosclerosis. Further interventions may be required to prevent vascular complications. To note, asymptomatic carotid plaque in T2DM is associated with older age, increased body mass index, biomarkers of poor glycemic control (glycated hemoglobin, fasting glucose), kidney dysfunction [urinary albumin-to-creatinine ratio (UACR)], and metabolic abnormalities [high-density lipoprotein cholesterol, serum uric acid (SUA)]. However, renal (UACR) and metabolic (SUA) biomarkers are likely to be investigated as promising biomarkers for early stage of asymptomatic coronary atherosclerosis, which as expecting could improve diagnostic value of intima-media thickness.

Key Words: Type 2 diabetes mellitus; Carotid plaque; Intima-media thickness; Serum uric acid; Urinary albumin-to-creatinine ratio; Risk factors

Core Tip: The integration of routinely used biomarkers of kidney dysfunction (urinary albumin-to-creatinine ratio) and metabolic abnormality (serum uric acid, high-density lipoprotein cholesterol) to predictive model may be practically useful to pre-screen the patients with type 2 diabetes mellitus at higher risk of carotid atherosclerotic plaque.

INTRODUCTION

Atherosclerosis is a common complication in patients with type 2 diabetes mellitus (T2DM), which is closely associated with huge economic burdens on patients’ families and resource of health systems[1,2]. Over the last two decades, the number of people living with both atherosclerosis and T2DM has significantly increased depending on global growth of T2DM prevalence[3]. In 2020, the estimated global prevalence rate of carotid atherosclerosis in people aged 30–79 years was 21.1%, equivalent to 815.8 million people worldwide[4]. To the best of our knowledge, asymptomatic carotid plaques tended to be more prevalent (72% vs 60%, P = 0.06) in new-onset T2DM compared to controls[5]. Patients with a new diagnosis of T2DM had more advanced preclinical carotid atherosclerosis than non-diabetic subjects even after controlling for traditional risk factors including age, sex, hypertension, dyslipidemia, and smoking[5]. Moreover, the prevalence of cardiovascular disease (CVD) including stroke, myocardial infarction, angina pectoris, heart failure (HF), ischemic heart disease, CVD, coronary heart disease, atherosclerosis, and cardiovascular (CV) death, among T2DM patients was 32.2% and 29.1% had atherosclerosis[6]. Although carotid plaques can predict future major adverse CV events (MACEs) in asymptomatic individuals with T2DM, their interactions with conventional and non-conventional CV risk factors remain inadequately defined.

DEFINITION AND RISK FACTORS FOR CAROTID ATHEROSCLEROSIS

In most population-based observational and clinical studies on the prevalence of carotid atherosclerosis, which used ultrasonography of the bilateral carotid arteries, the following criteria for atherosclerotic lesions were employed: (1) Increased carotid intima-media thickness (IMT) of 1.0 mm or more; (2) Focal IMT of 1.5 mm or more encroaching into the lumen; and (3) Local thickening of the carotid IMT of > 50% compared to the surrounding vessel wall[7]. However, criterion a may be preserved as increased carotid IMT of 1 mm or more since values of carotid IMT > 0.9 mm was considered abnormal according to by the European Society of Cardiology guideline[8]. According to these criteria, in general population carotid atherosclerosis is highly prevalent in men than in female and closely associated with conventional CV risk factors, i.e. elevated systolic blood pressure, fasting glucose levels, and several inflammatory biomarkers, such as monocyte count to high-density lipoprotein cholesterol (HDL-C) ratio, and triglyceride glucose body mass index (BMI)[9]. Among T2DM individuals[10-14], the predictors for carotid atherosclerosis were older age, hypertension, duration of T2DM, serum uric acid (SUA) and its ratio to serum albumin, fasting and post-prandial plasma glucose, inflammatory biomarkers [high-sensitive C-reactive protein (CRP), tumor necrosis factor-alpha, receptor for advanced end-glycation products, interferon gamma], low levels of bilirubin, N-terminal osteocalcin, as well as peri-renal fat thickness, but not visceral fat area, subcutaneous fat area or traditional metabolic risk factors[15-18].

Thus, three main groups of risk factors have been identified as being involved in the formation and progression of carotid atherosclerosis in patients with T2DM (Figure 1). The first of these can be conditionally defined as T2DM-dependent factors, which include classic factors of tissue damages associated with glucose and lipid toxicity, mitochondrial dysfunction, insulin resistance (IR) and inflammation[19].

Figure 1 Pathogenetic factors of accelerating atherosclerosis in type 2 diabetes mellitus. AGE: Advanced end-glycation products; CKD: Chronic kidney disease; CV: Cardiovascular; HF: Heart failure; MetS: Metabolic syndrome; T2DM: Type 2 diabetes mellitus; VSMCs: Vascular smooth muscle cells.

They contribute to the development of systemic inflammation, metabolic maladaptation known as metabolic memory, impaired tissue regeneration, hormonal and metabolic disturbances, vasculopathy and consequently accelerating atherosclerosis[20]. The second group of factors consists of classic CV risk factors, whose role in the formation and progression of systemic atherosclerosis has been well studied and is often incorporated into various prognostic scales [i.e., Cardiovascular Risk Score-2, Atherosclerotic Cardiovascular Disease Risk (ASCVD) Estimator and Reynolds Risk Score][21]. Moreover, these scores for ASCVD risk estimation are utilized as reliable tools to categorize plaque quality and to choose an intervention approach[22]. Additionally, a number of non-classical risk factors (the third group), such as genetic predisposition, altered epigenetic regulation of glucose and lipid homeostasis through an expression of nuclear factor-kappa B (NF-kB)-dependent proteins, pro-inflammatory genes, genes coding expression of adhesive molecules, glucose transporters, and adipose tissue dysfunction, the presence of concomitant diseases (metabolic syndrome, HF, chronic kidney disease) are markedly implicated in T2DM-associated vascular injury and ectopic vascular calcification[23-25]. Although carotid atherosclerosis is a risk factor for MACE among T2DM patients and its predictive and incremental value for MACE combined with traditional CV risk factors exhibits a high variability among studied populations[26-28]. Thus, plaque information when added to traditional risk factors can improve ASCVD risk prediction, but this discriminative value is sufficiently variable and requires to be clearly reported, for instance with reliable metabolic, renal, and vascular biomarkers. Without a doubt, these biomarkers should describe the key pathogenetic mechanisms of carotid atherosclerosis formation independently of traditional risk factors.

PATHOGENETIC MECHANISMS OF ATHEROSCLEROSIS ACCELERATION IN T2DM

Regardless of the risk factors profile and a quality of glucose control, oxidative stress, lipid toxicity, inflammation and metabolic memory phenomenon are considered as the key triggers for initiating vascular damage and accelerating atherosclerosis in T2DM[29]. Further the local processes of plaque composition involved in the alteration of endothelial, calcium accumulation, proliferation and differentiation of vascular smooth muscle cells, polarizing macrophages with forming foam cells and consequently shaping plaque. These pathophysiological pathways are under regulation of a number of coexisting factors, including estrogens through bone-related protein and Lp(a), systemic inflammation, adipose tissue dysfunction, microRNAs and bioactive lipids[30]. They mainly act as modulators of phosphoinositide 3-kinase/protein kinase B/NF-kB, mammalian target of rapamycin/activator protein-1/vascular endothelial growth factor receptor pathway and regulate cell proliferation and differentiation, apoptosis/ferroptosis, expression of adhesion molecules and angiogenesis[31-34]. These pathogenetic mechanisms ultimately result in a metabolic sequence that affects the function of antigen-presenting cells, endothelial progenitor cells, and other cellular elements involved in plaque formation.

BIOMARKERS OF CAROTID ATHEROSCLEROSIS IN T2DM

Although previous studies have widely assessed the risk factors associated with atherosclerosis, it remains unclear whether the integrated biomarkers of kidney diseases and metabolic condition are predictively applicable to T2DM patients with carotid atherosclerosis. The study by Shi and Li[35], published in this issue of the World Journal of Diabetes, was to evaluate the possible associations of the conventional biomarkers of renal dysfunction [urinary albumin-to-creatinine ratio (UACR)] and metabolic indicator (SUA) with subclinical carotid plaque formation that was detected as IMT ≥ 1.5 mm in patients with known T2DM. The authors established that age, fasting plasma glucose, glycated hemoglobin (HbA1c), systolic blood pressure, serum creatinine, UACR, SUA, and HDL-C were independent predictors of carotid atherosclerosis. In a retrospective single-center study, Shi and Li[35] provided important clinical evidence of an association between asymptomatic carotid atherosclerosis and routine, easy-to-use biomarkers, i.e. UACR and SUA, which can be utilized for the early identification of individuals at risk. Since monitoring renal function and uric acid levels is routinely used to assess the condition of patients with diabetes mellitus, one of the main advantages of this study is undoubtedly the simplicity and cost-effectiveness of prescreening based on the above biomarkers. This approach does not require additional economic costs or staff training, and can also be used to analyze previously obtained data. The extent to which the new discriminatory model for the preliminary detection of carotid atherosclerosis is applicable in populations of patients with varying ASCVD risk remains to be established. Although in previous clinical studies SUA and UACR demonstrated positive correlations with target organ damage and MACEs in diabetes mellitus, they are not specific biomarkers of metabolic disorders[36,37]. In this context, it is undoubtedly necessary to validate the study results and compare the findings with those from other studies that have investigated alternative inflammatory markers, novel lipid-related indices and imaging-based predictors. Indeed, the linear associations between various insulin-based (Homeostasis Model Assessment of Insulin Resistance) and non-insulin-based IR (i.e., MeTabolic Score for Insulin Resistance) indices, lipid abnormalities defined as Castelli's risk indices-I, II and subclinical atherosclerosis were found in the CHIEF Atherosclerosis Study[38]. In contrast with the findings reported by Shi and Li[35], the indices of IR correlated with carotid IMT in patients without hyperuricemia, whereas in those with elevated SUA did not. In several studies and meta-analysis, triglyceride-glucose (TyG) index and TyG-BMI, novel surrogate indicators of IR, were found to be positively associated with extension of multifocal atherosclerosis and the risk of ASCVD in people without ASCVDs at baseline[38,39]. Interestingly, SUA has revealed moderate interaction with IR and arterial stiffness in a large cohort of newly diagnosed, never-treated hypertensive patients[40]. Moreover, SUA to HDL ratio has been suggested as a promising predictive factor for metabolic syndrome and ASCVD outcomes in T2DM[41,42], but its discriminative potency for carotid IMT in asymptomatic patients at higher risk of ASCVD remains uncertain. Because this parameter can be a valuable indicator in facilitating the early identification of individuals at elevated ASCVD risk, the incorporation of routine SUA to HDL ratio monitoring into clinical practice could support the early identification of high-risk individuals, facilitate timely interventions, and reduce the burden of CV and metabolic diseases[43]. The relationship between carotid atherosclerosis and novel inflammatory markers was investigated, including the platelet-to-lymphocyte ratio, the neutrophil-to-lymphocyte ratio, the lymphocyte-to-monocyte ratio, the platelet-to-neutrophil ratio, neutrophil-to-lymphocyte-platelet ratio, systemic immune-inflammation index, systemic inflammation response index and aggregate index of systemic inflammation, has been investigated in numerous clinical studies[43]. These new inflammatory markers were not only significantly correlated with carotid IMT, but were also affordable and simple to detect. To note, conventionally used in routine clinical practice high-sensitivity CRP along with certain inflammatory cytokines, such as interleukins (IL-2, IL-6, IL-8), tumor necrosis factor-alpha, interferon-gamma, monocyte chemoattractant protein-1, have revealed the association with carotid IMT, degree of carotid stenosis and recently symptomatic carotid atherosclerosis[44-46]. Last, but not least, computed tomography angiography, magnetic resonance angiography and 18F-fluorodeoxyglucose positron emission tomography scans are proven valuable tools for evaluating patients with carotid atherosclerosis and perhaps with plaque vulnerability, while they have demonstrated weaker predictive ability for ASCVD events in asymptomatic individuals in comparison with symptomatic patients[47]. All these findings mentioned above suggest the discovery of alternative characterization of atherosclerosis risk beyond classical CV risk factors, inflammatory indices and neuroimaging features in asymptomatic individuals.

Another issue that remains unresolved in the study is the lack of information regarding the discriminatory potential of the new model for patients with target lipid levels who are receiving adequate statin therapy or combined lipid-lowering therapy, antihypertensive treatment, or management of HF. These treatments could significantly influence vascular outcomes and biomarker levels. Indeed, recent clinical studies have shown that statins, ezetimibe and the protein convertase subtilisin/kexin type 9 significantly improve blood pressure control and a signature of circulating biomarkers reflecting inflammation, oxidative stress and kidney function, as well as decreasing the risk of carotid atherosclerosis progression among asymptomatic individuals and patients with known ASCVD[48-51]. Future treatment modalities targeting carotid plaque modification may prevent related vascular complications and carotid plaque assessment may be used a surrogate risk marker for management of CVDs.

Not only was this aspect of implementing a biomarker model for predicting carotid atherosclerosis in patients with T2DM left out of the discussion, it is also likely to be a significant limitation due to the retrospective nature of the study. Nevertheless, the results obtained by the authors are undoubtedly highly attractive due to their practical value, offering prospects for future research in this area.

CONCLUSION

Asymptomatic carotid plaque in T2DM is associated with older age, increased BMI, biomarkers of poor glycemic control (HbA1c, fasting glucose), kidney dysfunction (UACR), and metabolic abnormalities (HDL-C, SUA). However, conventionally used risk factors, such as age, overweight/obesity, hypertension, poor glycemic control, renal dysfunction, and metabolic disturbances frequently underestimate the patients at the risk of asymptomatic carotid atherosclerosis, while it may be a target for further interventions to prevent vascular complications. Routine measurements of these parameters, especially SUA and UACR, could be practically useful to pre-screen the patients with T2DM at higher risk of carotid plaque formation.