2023 Volume 30 Issue 12 Pages 1828-1837
Aims: Intracranial plaque may cause stroke in the absence of luminal stenosis. Although urine albumin-to-creatinine ratio (ACR) has been proved an established risk factor for cardiovascular disease, stroke and carotid atherosclerosis, little is known on the relationship between urine ACR and intracranial plaque.
Methods: Subjects with history of stroke or coronary heart disease (CHD) were excluded in the PRECISE study. The intracranial plaque was assessed by vessel wall magnetic resonance imaging (MRI). Subjects were stratified according to ACR tertiles. Logistic regression and ordinal regression were performed to analyze the association between ACR and the presence of intracranial plaque or sum of the stenosis score for each artery.
Results: 2962 individuals were included with the mean age of 61.0±6.6 years. The median ACR was 11.7mg/g (interquartile range 7.0-22.0 mg/g), and the mean estimated glomerular filtration rate (eGFR) based on combination of creatinine and cystatin C was 88.5±14.8 ml/min·1.73m2. 495 (16.7%) participants had intracranial plaque. The highest ACR tertile with ACR ＞16.00mg/g was independently associated with the presence of intracranial plaque (OR 1.38, 95% CI: 1.05-1.82, p=0.02) and the odds of higher intracranial plaque burden (common OR 1.39, 95% CI: 1.05-1.83, p=0.02) after adjustment of confounding factors. No significant association was observed between eGFR and intracranial plaque presence or intracranial plaque burden.
Conclusions: Among a low-risk community-dwelling population without prior stroke or CHD in China, ACR was independently associated with intracranial plaque presence and plaque burden measured by vessel wall MRI.
Trial Registration Number: NCT03178448
Intracranial atherosclerosis is a major cause of ischemic stroke worldwide and carries a high risk of stroke recurrence1). Compared to extracranial atherosclerosis, intracranial atherosclerosis is more common in China, accounting for about 33–50% of stroke and ＞50% of transient ischemic attack (TIA)1). Although intracranial artery stenosis has been the leading indicator for patient selection in clinical trials, mounting evidence suggested that intracranial plaque originating from the vessel wall may cause ischemic stroke in absence of luminal stenosis2, 3). The early identification of asymptomatic intracranial plaque and its risk factors therefore become essential for stroke prevention especially in the general population.
Increased urine albumin-to-creatinine ratio (ACR) is a surrogate marker for early kidney damage. Albuminuria, defined as an ACR ≥ 30mg/g, is an established risk factor for cardiovascular morbidity and mortality for the general population and for individuals with hypertension or diabetes mellitus4). In addition, ACR can predict stroke and stroke prognosis in non-diabetic and non-hypertensive population5-7). In recent years, extensive studies have suggested that even low-grade albuminuria within the normal range is associated with an increased risk of cardiovascular disease (CVD) and carotid atherosclerosis8-12). As intracranial arteries exhibit some unique histological features that are quite different from extracranial arteries13, 14), it is not clear whether the relationship between albuminuria and extracranial atherosclerosis can be generalized to intracranial arteries. To our knowledge, only the ARIC study has focused on the role of albuminuria in intracranial plaque in a community-based population15).
In this study, we aim to conduct a cross-sectional analysis in China to explore the association between albuminuria and intracranial plaque in a relatively low-risk community population free of stroke and CHD from the baseline survey of the PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study, in which the advanced vessel wall magnetic resonance imaging (MRI) utilization enabled precise evaluation of intracranial plaque.
The PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study is a population-based prospective cohort study with comprehensive evaluation of intracranial artery stenosis and plaque using advanced vascular imaging techniques. The PRECISE study enrolled community-dwelling adults aged 50 to 75 years based on cluster sampling from 6 villages and 4 living communities of Lishui in southeast China. Data were collected from May 2017 to September 2019 and analyzed from September to November 2021. Details of the rationale, design, and methodology of the PRECISE study have been previously described16). Subjects with no previous history of stroke or CHD were included in this study for baseline cross-sectional analysis. This study was approved by the ethics committee. Written informed consents were obtained from all participants in the study.
Data CollectionAll the data collection was performed at Lishui Hospital through face-to-face interviews and examinations by centralized trained personnel following a standard data collection protocol developed by the steering committee. All interviewers were trained before the kick-off meeting. An electronic data capture system (EDC) was developed and used for data collection. All data elements from each participant were automatically checked for completeness, correct coding, value range and logical error through EDC. Independent data monitoring was also performed through EDC by an independent contract research organization. All data were de-identified before data analysis.
Baseline information was collected, including baseline demographic characteristics, current smoking and drinking status and medical history of diabetes, hypertension or dyslipidemia. Other clinical variables used in this analysis include body mass index (BMI), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG) and hemoglobin A1c (HbA1c). BMI was calculated as the weight divided by the height squared (kg/m2). Current smokers were defined as those who smoked at least 1 cigarette per day on average during the last month17). Hypertension was defined as systolic blood pressure of 140mmHg or greater, diastolic blood pressure of 90mmHg or greater, self-reported hypertension previously diagnosed by a physician, or current use of antihypertensive agents18, 19). Diabetes was defined as fasting plasma glucose of 126.1mg/dL or greater (to convert to millimoles per liter, multiply by 0.0555), 2-hour postload glucose of 200mg/dL or greater, hemoglobin A1c of 6.5% or greater (to convert to proportion of total hemoglobin, multiply by 0.01), self-reported diabetes previously diagnosed by a physician, or current use of antidiabetic agents20, 21). Dyslipidemia was defined as total cholesterol 240mg/dL or greater, low-density lipoprotein cholesterol of 160mg/dL or greater, high-density lipoprotein cholesterol of less than 40mg/dL (to convert cholesterol to millimoles per liter, multiply by 0.0259), or self-reported dyslipidemia previously diagnosed by a physician22, 23).
A midstream morning urine sample was collected. Albumin-to-creatinine ratio (ACR) was determined by dividing urinary albumin by urinary creatinine as a measure of albuminuria. Serum creatinine and serum cystatin C levels were measured. Using the Chronic Kidney Disease Epidemiology Collaboration equations, eGFR was calculated not only on the basis of cystatin C (eGFRSCys), but also on both creatinine and cystatin C (eGFRSCr-SCys)24). As compared with creatinine-based eGFR, eGFR based on cystatin C in combination with creatinine showed improved risk stratification in mortality and cardiovascular events15).
Intracranial Plaque EvaluationIntracranial arteries were evaluated by MRI at baseline using a 3.0T scanner (Ingenia 3.0T [Philips]) by trained investigators based on a standardized protocol. MRI sequences included 3-dimensional time-of-flight magnetic resonance angiography (3-D–TOF MRA), 3-D isotropic high-resolution black-blood T1w vessel wall MRI, and simultaneous non-contrast angiography and intraplaque hemorrhage imaging.
MRI data were collected in DICOM format on discs and then analyzed by 2 raters who were masked to the participants’ information. Inconsistencies were settled by another senior neurologist. The presence of intracranial plaque was defined as eccentric wall thickening with or without luminal stenosis as seen on 3-D-TOF MRA or black-blood MR images.
The intracranial arterial segments evaluated included the bilateral distal internal carotid, middle cerebral (M1, M2), anterior cerebral (A1, A2), posterior cerebral (P1, P2), basal and vertebral (V4) arteries. The extent of atherosclerosis was visually graded by the degree of the luminal narrowing for the most stenotic plaque according to the following criteria: 0 for no atherosclerotic plaque; 1 for atherosclerotic plaque without significant lumen stenosis or stenosis ＜50%; 2 for 50%–69% stenosis; 3 for 70%–99% stenosis; 4 for occlusion25). We adopted the intracranial plaque burden score to evaluate the severity of intracranial plaque. The intracranial plaque burden score was defined as the sum of the stenosis score for each artery, which was then categorized into four grades with 0, 1, 2-3, and ≥ 4. This intracranial plaque burden score system has been proved to be associated with stroke recurrence at 12 month26).
Statistical AnalysisContinuous variables are expressed as mean with standard deviation (SD) or medians with interquartile ranges (IQR), as appropriate. Categorical data were presented as proportions. Subjects were stratified according to ACR tertiles. We compared baseline characteristics, prevalence of intracranial plaque and intracranial plaque burden score among participants with different ACR categories using t test, Wilcoxon rank sum test, 1-way analysis of variance, or Kruskal-Wallis test for continuous variables as appropriate and χ2 test for categorical variables.
Adjusted odds ratios (OR) and their 95% confidence intervals (CI) were estimated using multivariable logistic regression models to examine the association between ACR and the prevalence of intracranial plaque. Adjusted common odds ratios (cOR) and their 95% confidence intervals (CI) were estimated with multivariable ordinal regression models to evaluate the association between ACR and intracranial plaque burden. The lowest tertile of ACR was used as reference group. Serial models were performed as detailed below: 1) adjusted for age and sex; 2) additionally adjusted for history of hypertension, diabetes, current smoker, current drinker, BMI, HDL, LDL, and HbA1c; 3) additionally adjusted for eGFRSCr-SCys or eGFRSCys. All analyses were conducted with SAS Version 9.4 software (SAS Institute Inc). Two tailed p values ＜0.05 were considered to be statistically significant.
A total of 3067 subjects participated in the PRECISE study. After excluding 100 individuals with a history of stroke or CHD, three with missing ACR, and two individuals with noninterpretable MRI images of the intracranial arteries, 2962 subjects were included in the final analysis (Fig.1). There were 153 participants with distal internal carotid plaque (5.2%), 223 with middle cerebral artery plaque (7.5%), 57 with anterior cerebral artery plaque (1.9%), 101 with posterior cerebral artery plaque (3.4%), 37 with vertebral artery plaque (1.3%), and 87 with basal artery plaque (2.9%).
PRECISE, The PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events study; CHD, coronary heart disease; ACR, albumin-to-creatinine ratio; MRI, magnetic resonance imaging.
The mean age of the study participants was 61.0±6.6 years, and 1366 (46.1%) were male. The median ACR (IQR) was 11.0 (7.0-22.0) mg/g. The mean eGFRSCr-SCys and eGFRSCys for the cohort were 88.5±14.8 ml/min·1.73m2 and 82.5±17.5ml/min·1.73m2. The prevalence of eGFRSCr-SCys and eGFRSCys ＜60 ml/min·1.73m2 was 3.4% (101 cases) and 10.6% (315 cases), respectively. A total of 495 (16.7%) participants had intracranial plaques: 287(9.7%) had an intracranial plaque burden score of 1, 177(6.0%) had a score of 2-3, and 31(1.0%) had a score of ≥ 4. Intracranial plaque was similarly prevalent in men and in women.
Participants were divided into 3 groups according to ACR tertiles, 877 (29.6%) with ACR ＜7.00mg/g, 1037 (35.0%) with ACR 7.00-16.00mg/g, and 1048 (35.4%) with ACR ＞16.00mg/g, respectively. Those with higher ACR were more likely to be elderly, female, have higher prevalence of hypertension, diabetes, hyperlipidemia, displayed higher BMI, HbA1c, TC, TG, and lower eGFR (Table 1), and have lower prevalence of current smokers or drinkers.
| All subjects (N= 2962) | ACR 1st tertile (N= 877) | ACR 2nd tertile (N= 1037) | ACR 3rd tertile (N= 1048) | p value | |
|---|---|---|---|---|---|
| ＜7.00mg/g | 7.00-16.00mg/g | ＞16.00mg/g | |||
| Age, year | 61.0±6.6 | 59.9±6.2 | 60.7±6.5 | 62.3±6.8 | ＜0.001 |
| Male, n (%) | 1366 (46.1) | 546 (62.3) | 449 (43.3) | 371 (35.4) | ＜0.001 |
| Medical hisroty | |||||
| Diabetes, n (%) | 624 (21.1) | 115 (13.1) | 183 (17.6) | 326 (31.1) | ＜0.001 |
| Hypertension, n (%) | 1243 (42.0) | 230 (26.2) | 378 (36.5) | 635 (60.6) | ＜0.001 |
| Dyslipidemia, n (%) | 588 (19.9) | 141 (16.1) | 215 (20.7) | 232 (22.1) | 0.003 |
| Current smoker, n (%) | 613 (20.7) | 259 (29.5) | 208 (20.1) | 146 (13.9) | ＜0.001 |
| Current drinker, n (%) | 561 (18.9) | 203 (23.1) | 184 (17.7) | 174 (16.6) | ＜0.001 |
| BMI, kg/m2 | 23.8±3.0 | 23.3±2.8 | 23.6±2.9 | 24.3±3.3 | ＜0.001 |
| TC, mmol/L | 5.3±1.0 | 5.2±0.9 | 5.3±1.0 | 5.4±1.0 | ＜0.001 |
| HDL, mmol/L | 1.4±0.3 | 1.4±0.3 | 1.4±0.3 | 1.4±0.3 | 0.45 |
| LDL, mmol/L | 2.8±0.8 | 2.7±0.7 | 2.8±0.8 | 2.8±0.8 | 0.05 |
| TG, mmol/L | 1.8±1.3 | 1.6±1.1 | 1.8±1.3 | 2.0±1.3 | ＜0.001 |
| HbA1c, % | 5.9±0.9 | 5.8±0.6 | 5.8±0.7 | 6.2±1.2 | ＜0.001 |
| eGFRSCr-SCys, ml/min | 88.5±14.8 | 88.7±13.1 | 89.9±14.2 | 87.0±16.6 | ＜0.001 |
| eGFRSCys, ml/min | 82.5±17.5 | 83.1±16.4 | 84.1±16.9 | 80.3±18.8 | ＜0.001 |
| ACR, mg/g | |||||
| Median (IQR) | 11.0 (7.0-22.0) | 5.00 (4.00-6.00) | 10.00 (9.00-12.00) | 31.00 (20.5-58.5) | ＜0.001 |
ACR, albumin-to-creatinine ratio; BMI, body mass index; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride; HbA1c, hemoglobin A1c; eGFR, estimated glomerular filtration rate; IQR, interquartile range.
The prevalence of intracranial plaque was almost 2-fold as high in participants with ACR ＞16.00mg/g (22.0% vs. 11.9%), compared with those with ACR ＜7.00mg/g. The proportions of participants with higher intracranial plaque burden also increased with higher ACR tertile (Fig.2).
ACR, albumin-to-creatinine ratio. The extent of atherosclerosis was visually graded by the degree of the luminal narrowing for the most stenotic plaque according to the following criteria: 0 for no atherosclerotic plaque; 1 for atherosclerotic plaque without significant lumen stenosis or stenosis ＜50%; 2 for 50%–69% stenosis; 3 for 70%–99% stenosis; 4 for occlusion[2]. Our assessment included nine intracranial arteries (the bilateral distal internal carotid, middle cerebral, anterior cerebral, posterior cerebral, basal, and vertebral arteries). The intracranial plaque burden score was defined as the sum of the stenosis score for each artery, which was then categorized into four grades with 0, 1, 2-3, and ≥ 4. P value was obtained by Chi-square test to assess the association between ACR and intracranial plaque burden.
With multivariable adjustment for age, sex, current smoker, current alcohol, hypertension, diabetes, BMI, HbA1c, HDL, LDL and eGFRSCr-SCys, the highest ACR tertile with ACR ＞16.00mg/g remained an independent risk factor for the prevalence of intracranial atherosclerotic plaque (OR 1.38, 95% CI: 1.05-1.82, p=0.02) compared with those with ACR ＜7.00mg/g. With 1- SD increase in ACR levels, the risk of intracranial plaque increased by 12%. In fully-adjusted analysis, those with ACR ＞16.00mg/g also exhibited odds of higher intracranial plaque burden compared to the reference group (cOR 1.39, 95% CI: 1.05-1.83, p=0.02) (Table 2, Fig.3).
| Groups | Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|---|
| OR/cOR (95% CI) | p value | OR/cOR (95% CI) | p value | OR/cOR (95% CI) | p value | ||
| Prevalence of intracranial plaque | ACR 1st tertile | Ref. | Ref. | Ref. | |||
| ACR 2nd tertile | 1.35 (1.03-1.77) | 0.03 | 1.20 (0.91-1.58) | 0.20 | 1.20 (0.91-1.58) | 0.19 | |
| ACR 3rd tertile | 1.98 (1.52-2.58) | ＜0.001 | 1.38 (1.05-1.82) | 0.02 | 1.38 (1.05-1.82) | 0.02 | |
| Per 1-SD | 1.21 (1.11-1.32) | ＜0.001 | 1.12 (1.03-1.21) | 0.007 | 1.12 (1.03-1.22) | 0.008 | |
| P for trend | ＜0.001 | 0.03 | 0.03 | ||||
| Intracranial plaque burden | ACR 1st tertile | Ref. | Ref. | Ref. | |||
| ACR 2nd tertile | 1.35 (1.03-1.77) | 0.03 | 1.21 (0.92-1.59) | 0.18 | 1.21 (0.92-1.59) | 0.17 | |
| ACR 3rd tertile | 1.99 (1.53-2.58) | ＜0.001 | 1.39 (1.05-1.83) | 0.02 | 1.39 (1.05-1.83) | 0.02 | |
| Per 1-SD | 1.19 (1.11-1.28) | ＜0.001 | 1.11 (1.04-1.20) | 0.004 | 1.11 (1.03-1.20) | 0.005 | |
| P for trend | ＜0.001 | 0.03 | 0.03 | ||||
ACR, albumin-to-creatinine ratio; OR, odds ratio; cOR, common odds ratio; CI, confidence interval; SD, standard deviation.
Model 1: adjusted for age and sex;
Model 2: Model 1＋history of smoking, alcohol, hypertension, diabetes, BMI, HbA1c, HDL, LDL; Model 3: Model 2＋eGFRSCr-SCys.
The solid line indicates adjusted odds ratio and the dashed line the 95% confidence interval bands.
The solid line indicates adjusted common odds ratio and the dashed line the 95% confidence interval bands.
No significant association was observed between eGFRSCr-SCys and intracranial plaque presence or intracranial plaque burden (data not shown). Similar findings were seen for eGFRSCys, therefore only the results based on eGFRSCr-SCys were reported.
There were 374 participants with anterior circulation arterial plaque (12.6%), 203 participants with posterior circulation arterial plaque (6.9%). Interestingly, the highest ACR tertile with ACR ＞16.00mg/g was independently associated with the prevalence of posterior circulation arterial plaque (OR=1.71, 95% CI: 1.05-1.82, p=0.01) compared with those with ACR ＜7.00mg/g after multivariable adjustment, but not with the prevalence of plaque in anterior circulation arteries.
In this community-based cohort of Chinese middle-aged and elderly individuals free of previous stroke and CHD, a baseline ACR level (higher than 16 mg/g) well below the current albuminuria threshold was independently associated with the presence of intracranial plaque and intracranial plaque burden, even after adjustment for established cardiovascular risk factors and eGFR.
A growing body of evidence has shown that ACR is associated with extracranial atherosclerosis4, 8-12). However, few studies have focused on the relationship between ACR and intracranial atherosclerosis. To our knowledge, only three studies investigated the role of ACR beyond 30mg/g in intracranial atherosclerotic stenosis15, 27, 28). Among them, the ARIC study was the only one investigating the association between albuminuria and intracranial plaque in the community population, which showed a negative result15). Our observations add important insights to the limited amount of current knowledge of the association between ACR and intracranial plaque and plaque burden as measured by vessel wall MRI in a large community-dwelling adults free of prior stroke and CHD.
Intracranial atherosclerosis is a major contributor in stroke incidence and mortality in China1). Traditionally, severe (70-99%) and moderate (50-69%) intracranial stenosis have been demonstrated as considerable risk factors for ischemic stroke and stroke recurrence. However, in more recent studies, the role of percent stenosis in predicting stroke risk has been superseded by collateral flow, characterization of the atherosclerotic lesion, and hemodynamics3). Many authors have suggested that atherosclerotic plaque originates in the vessel wall, and may cause ischemic stroke in absence of luminal stenosis29-31). Therefore, using intracranial stenosis as an assessment and risk stratification of intracranial atherosclerosis is inadequate and may even be misleading3, 26, 32). Meanwhile, current understanding of intracranial atherosclerosis has been advanced by high-resolution three-dimensional vessel wall MRI, a novel emerging imaging technique that allows direct visualization of the vessel wall pathology and helps to precisely evaluate atherosclerosis even when luminal angiography reveals no abnormalities14, 33). A systematic review demonstrated that about half of the patients with acute/subacute ischemic stroke symptoms and nevertheless no significant stenosis on MRA had intracranial active plaques revealed by high resolution vessel wall MRI. These plaques may be culprit lesions in many ischemic strokes2). Therefore, the evaluation of intracranial plaque well before the stage of stenosis by vessel wall MRI enabled the identification of high-risk individuals missed by artificially graded degree of luminal stenosis. The PRECISE is the second study, after the ARIC study, to assess intracranial plaque using vessel wall MRI in a Chinese community-based population. In this study, we excluded the individuals with a history of stroke or CHD to explore the status of intracranial plaque and plaque burden. Our result showed that 16.7% of the 2,962 individuals had intracranial plaque, which was only half of that in the ARIC study (36.3%). This result may be explained by the younger age (61.0±6.6 vs 76.3±5.3 years), lower proportion of diabetes (21.1% vs. 29.3%), hypertension (42.0% vs. 73.6%), eGFRSCys ＜60ml/min (10.6% vs. 45.6%), and no history of atherosclerotic cardiovascular disease in our cohort.
Albuminuria, is not only a marker of early kidney damage but also a novel risk factor for CVD and mortality. Recently the association between CVD and ACR below the albuminuria range has also received more attention8). Although there is substantial evidence supporting the association of ACR and extracranial arteries, including the coronary artery and carotid artery4, 8-12), fewer studies have focused on the relationship between ACR and intracranial atherosclerosis. Dewei An et al. performed computerized tomography angiography (CTA) in 889 hypertensive patients and found that ACR ≥ 30mg/g was independently associated with prevalence and severity of intracranial stenosis27). According to G.N.Tomas et al who reported similar results, 24-hour urinary albumin excretion rate ＞20ug/min was associated with middle cerebral artery (MCA) stenosis as measured by transcranial Doppler ultrasound in type 2 diabetic patients28). In our study, an ACR level above 16mg/g showed a strong positive correlation with intracranial plaque after adjusting for conventional risk factors and eGFR, suggesting that low grade albuminuria may predict early intracranial plaque formation. In addition, the intracranial plaque burden score, which combined the number of atherosclerosis lesions and the degree of stenosis, was also assessed. The result indicated that ACR ＞16.00mg/g was independently related to intracranial plaque burden in the fully-adjusted model, which suggested that albuminuria was not only associated with intracranial plaque presence, but also with the severity of intracranial atherosclerosis.
No association was observed between eGFR and intracranial plaque presence or intracranial plaque burden in this study. This result differed from the ARIC study, in which ACR was not associated with intracranial plaque, but eGFRSCys ＜60 mL/min/1.73 m2 was independently associated with the presence of plaque, any detectable stenosis, and severe stenosis or occlusion7). It was not clear whether this difference was due to a higher proportion of eGFR ＜60mL/min/1.73 m2 in the ARIC study (45.6% vs 10.6%). Both eGFR and albuminuria have been identified as independent risk factors for stroke, cardiovascular events and all-cause mortality4, 34), however, some evidence suggested that albuminuria was a better predictor of vascular events and mortality than eGFR35, 36). The longitudinal study of the PRECISE cohort will allow us to further examine how changes in albuminuria and renal function over the 4-year planned follow-up time influence vascular events risk.
Although we acknowledge that we cannot speculate on a causal relationship between ACR and intracranial plaque in this cross-sectional study, some potential mechanisms might explain a relationship between them. The hemodynamics of the vascular beds of the brain and the kidney are similar. It is thought that assessment of kidney structure damage by ACR could be a window to the systemic vasculature, reflecting the permeability of the vasculature in general and an individual’s susceptibility to target organ damage. Albuminuria may share a common pathophysiologic process or risk factors with intracranial atherosclerosis, including endothelial dysfunction, microinflammation, and oxidative stress factors37). For individuals without a history of stroke, whether increased ACR and presence of intracranial plaque on vessel wall MRI are associated with future risk of ischemic stroke is being investigated in the PRECISE cohort. Several large trials have demonstrated that a reduction in albuminuria is associated with decreased incidence of cardiovascular events and stroke38). There is also a need for further investigation as to whether albuminuria would be a target for the early intervention of intracranial atherosclerosis.
Interestingly, we also found that ACR was independently associated with the prevalence of posterior circulation arterial plaque, but not with the prevalence of plaque in anterior circulation arteries. The mechanisms of posterior circulation atherosclerosis may differ from that of the anterior circulation arteries. Our data were in line with previous results showing that the prevalence of atherosclerosis in anterior circulation was higher than that in posterior circulation, and hypertension and diabetes were significantly more common in participants with posterior circulation atherosclerosis than that in the anterior circulation, which may explain the closer relationship between posterior circulation atherosclerosis and ACR39, 40). However, the prevalence of anterior or posterior circulation artery plaque was relatively low in our cohort, thus the result should be interpreted with caution.
This study has important strengths, including the large sample size, thorough evaluation of intracranial plaque with advanced vessel wall MRI and the central laboratory assay of urine ACR and serological indexes. However, our study somehow has several limitations. Firstly, the present study is a cross-sectional analysis of the cohort at baseline, and therefore cannot assess the causal relationship between ACR and intracranial plaque; the current findings will be complemented by long-term monitoring of atherosclerosis progression. Secondly, only 3.4% of the subjects in this study had an eGFRSCr-SCys of less than 60mL/min.1.73m2, so the relationship between ACR and intracranial plaque in participants with moderate to severe kidney impairment need further investigation. Thirdly, we only used a single urine specimen to assess the ACR, which has day-to-day variability. However, large sample size and central laboratory assay of ACR are the strengths of our study, thus the variance may be attenuated. Lastly, plaque morphology data on vessel wall MRI such as plaque concentricity, calcification, or positive remodeling, were not included in the present study and will be analyzed in future research.
In summary, our study revealed that ACR level is independently associated with the presence of intracranial plaque and plaque burden measured by vessel wall MRI and that ACR may be an important factor in risk stratification for intracranial atherosclerosis in low-risk population.
Drs Yongjun Wang had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Zhou, Pan, YongjunWang.
Acquisition, analysis, or interpretation of data: Yin Zhang, Pan, Cai, Jing, Yan, S.Wang, Meng, Mei, Yanli Zhang, S. Li, Wei.
Drafting of the manuscript: Yin Zhang, Zhou, Yongjun Wang.
Critical revision of the manuscript for important intellectual content: Pan, Jing, Cai, S. Wang, Meng, Mei, S. Li, Wei.
Statistical analysis: Pan, Yanli Zhang.
Obtained funding: Yongjun Wang.
Administrative, technical, or material support: Pan, Cai, Jing, S. Wang, Meng, Mei, Yanli Zhang, S. Li, Wei.
Supervision: Zhou, Yongjun Wang.
The study was supported by grants from the National Natural Science Foundation of China (81870905, U20A20358), Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences(2019-I2M-5-029), Key Science and Technologies Research and Development Program of Lishui City (2019ZDYF18), Zhejiang provincial program for the Cultivation of High-level Innovative Health Talents, and AstraZeneca Investment (China).
The data analyzed during the current study available from the corresponding author on reasonable request.
Dr Yongjun Wang reported receiving grants from AstraZeneca during the conduct of the study. No other disclosures were reported.
