The Association between Intracranial Atherosclerotic Stenosis and Post- stroke Mild Behavioral Impairment

doi:10.21203/rs.3.rs-3896391/v1

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The Association between Intracranial Atherosclerotic Stenosis and Post- stroke Mild Behavioral Impairment

https://doi.org/10.21203/rs.3.rs-3896391/v1

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Purpose

The aim of this study was to analyze the association between Intracranial atherosclerotic stenosis (ICAS) and post-stroke mild behavioral impairment (MBI) in patients with minor stroke.

Methods

A total of 121 patients underwent high-resolution 3T magnetic resonance angiography and MBI checklist (MBI-C) assessment. We adjusted for demographic and vascular risk factors in logistic regression analysis, to determine the association of ICAS with MBI.

Results

Of the 121 patients with minor stroke in this study, 52 (42.98%) were diagnosed with ICAS. After adjusting for potential confounders, we found that patients with ICAS were more likely to develop MBI after an acute, non-disabling ischemic stroke compared to patients without ICAS (Odds Ratio:5.28; 95% Confidence Interval: 2.27-13.0)

Conclusions

Our study demonstrated a positive association between ICAS and post-stroke MBI in patients with minor stroke. Furthermore, the inverse correlation between precuneus cortical thickness and MBI scores provides a new insight into further diagnosing MBI through imaging. Our findings suggest that early detection and treatment of ICAS may help prevent the development of MBI in patients with minor stroke.

Intracranial atherosclerotic stenosis

mild behavioral impairment

minor stroke

gray matter volume

cortical thickness

Intracranial atherosclerotic disease is a highly prevalent cause of stroke that is associated with substantial morbidity and mortality. It is more prevalent among blacks, Hispanics, and Asians compared with whites[1]. The relation between cognitive impairment and intracranial atherosclerosis is increasingly recognized[2–5]. Growing evidence shows that intracranial atherosclerosis is associated with clinical and pathologic manifestations of Alzheimer disease[6–12]. Few biomarkers have been found to identify the vulnerable plaques [13]. Intracranial atherosclerotic stenosis (ICAS) may be associated with cognitive impairment and AD by causing cerebral hypoperfusion [14, 15]. Early recognition of cognitive impairment in ICAS patients has raised concerns. Neuropsychiatric symptoms (NPS) are common in dementia and in predementia syndromes, such as mild cognitive impairment (MCI). NPS in MCI confers a greater risk for conversion to dementia in comparison to MCI patients without NPS. NPS in older adults with normal cognition also confers a greater risk of cognitive decline compared to older adults without NPS. Mild behavioral impairment (MBI) has been proposed as a diagnostic construct aimed at identifying patients with an increased risk of developing dementia but who may or may not have cognitive symptoms[16]. There is an increasing realization of the need for improved markers of early identification of people with preclinical AD and their translation into practical stratification tools and a broader range of treatment targets [17]. Identifying a marker that is quickly and inexpensively detected in the general population and whose cognitive correlates could be measured over the short term would represent a significant step toward reaching this goal. There is an increasing evidence base that later life emergent and persistent neuropsychiatric symptoms (NPS), known as mild behavioral impairment (MBI),[17]may be one such maker. MBI is a neurobehavioral syndrome characterized by new and sustained NPS onset in later life[18]. For some individuals, MBI may be an early manifestation of neurodegenerative disease in advance of significant cognitive impairment. MBI consists of five domains: impaired drive and motivation (apathy)[19] emotional dysregulation (mood and anxiety symptoms); impulse dyscontrol/agitation/abnormal reward salience (changes in response inhibition and self-regulation); social inappropriateness (impaired social cognition); and abnormal thoughts/perception (psychosis), assessed individually and collectively for their impact on cognition. Notably, MBI explicitly excludes psychiatric illness a priori and mandates that NPS be emergent in later life and sustained for six months. Early recognition of cognitive impairment in ICAS patients has raised concerns, as These individuals may greatly benefit from early intervention of vascular risk factors unknown.[20]. Considering that MBI is a precursor to multiple dementias and that ICAS is associated with dementia, it is necessary to explore whether MBI exists as a clinical precursor to ICAS. In addition, studies that explored structural neuroimaging correlates of MBI in older adults at risk for AD dementia are scarce.

2.1Study population

In this cross-sectional study, we recruited patients hospitalized in our stroke center from June 2021 toto February 2023. The inclusion criteria are as follows: (I) patients aged between 50 and 85 years; (II) patients with ICAS {defined as intracranial artery stenosis (> 50% or occlusion) at Willis circle branch [intracranial internal carotid artery (ICA), middle cerebral artery (MCA), anterior cerebral artery (ACA), posterior cerebral artery (PCA), basilar artery (BA) or intracranial segment of the vertebral artery (VA)]} confirmed by magnetic resonance angiography (MRA); (III) patients with a National Institutes of Health Stroke Scale (NIHSS) score of < 4.

The exclusion criteria are as follows: (I) patients with > 50% extracranial artery stenosis; (II) patients with relative or absolute contraindications to MRI (e.g., metals in the body, claustrophobia, etc.); (III) those with intracranial stenosis due to non-atherosclerotic etiologies, such as vasculitis, dissection, moyamoya disease, embolus, immune system diseases, or other causes; (IV) patients with other known etiological types of stroke, such as cerebral hemorrhage or subarachnoid hemorrhage, and cardiac cerebral embolism; (V) patients diagnosed with neurodegenerative diseases such as AD, Lewy body dementia, frontotemporal dementia or Parkinson’s disease; (VI) patients with a history of traumatic brain injury, multiple sclerosis, encephalitis, tumors, poisoning, syphilis, and severe heart, lung, liver, kidney, or endocrine system diseases; and (VII) patients who refuse to sign the informed consent;(VII) inability for cognitive assessment due to severe aphasia, deafness, or difficulty in completing the procedures of the study. Finally, a total of 121 participants were included in this study. The study was approved by the Ethics Committee of Shanghai HuaDong Hospital (Shanghai, China) and was conducted by the principles of the Declaration of Helsinki. A signed informed consent form was obtained from all participants directly or from their legal guardians (spouse or child). All patients were assessed using the MOCA Scale, Fatigue Scale-14(FS-14), Frail Scale and Mild Behavioral Impairment Checklist (MBI-C). MBI-C was developed by members of the International Society to Advance Alzheimer’s Research and Treatment (ISTAART) which is more accurate than the Neuropsychiatric Inventory Questionnaire or other non-specificin struments. It includes five domains and 34 questions to be answered by family members or persons who were close to the patient in the event of symptoms lasting more than six months.

2.2. Neuroimaging Evaluations

All MR images were acquired on 3.0 Tesla MRI (MAGNETOM Trio, Siemens, Erlangen, Germany) in the Department of Radiology of Huadong Hospital, Shanghai. T1-weighted images, T2-weighed images, and T2 fluid-attenuated inversion recovery (FLAIR) sequences were included in this study. The T2 FLAIR sequence was used to measure WMH with the following scan parameters: TR/TE = 8500/81 ms; inversion time = 2000 ms; flip angle = 150°; slice thickness = 5 mm.

All participants underwent an MRI assessment to establish the diagnosis of acute ischemic stroke. Vessel segments analyzed included the middle cerebral artery (M1–M4 segments), anterior cerebral artery (A1–A3 segments), intracranial segments of the vertebral artery, basilar artery, and posterior cerebral artery (P1–P3segments). For each territory, the ordinal degree of narrowing was recorded for the most stenotic plaque measured on time-of-flight MRA images with criteria established in the Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) trial [21]. Because our objective was to study the association of ICAS with MBI, vessel segments noted to have plaque but without any measurable stenosis were not included. We analyzed the most stenotic segment of each vessel territory and used the severity of the most stenotic lesion in each participant to determine the association of ICAS with MBI. We tried to accurately classify stenosis in clinically significant and commonly used ordinal categories (no detectable stenosis, < 50%, 51–70%, 71–99%, and occlusion) [22]. We grouped ≥ 50% stenosis into 1 category for this analysis to achieve meaningful statistical power.

The Warfarin–Aspirin Symptomatic Intracranial Disease Study (WASID) Group established a reliable method for the measurement of stenosis grades in the intracranial major cerebral arteries[21]. They defined percent stenosis of an intracranial artery as follows: percent stenosis = [(1 - (D-stenosis/D-normal))] x 100, where D-stenosis = the diameter of the artery at the site of the most severe stenosis and D-normal = the diameter of the proximal normal artery.

2.3Analysis of brain structure

For the present study, FLAIR images were registered to T1-weighted images by applying SPM12 (Welcome Institute of Neurology, University College London, UK, http://www.fil.ion.ucl.ac.uk/spm/doc/) for Matlab (The MathWorks, Inc., Natick, Massachusetts, United States). Often, the whole brain is parcellated into several disjoint regions, which are represented as network nodes. Based on the DK40 Automatic Brain Region Division (Aparc), we divided the cerebral cortex into 40 regions[23]. The gray matter of the brain was divided into 48 regions by Hammersmith atlas with VBM probabilistic maps in SPM format[24]. White matter hyperintensities (WMHs) were focal or confluent hyperintensities in the deep and periventricular white matter on FLAIR images, and we used the modified Fazekas scale to rate the degree of WMH severity [14] visually. Automated WMH segmentation was performed on the registered 2D FLAIR images by the lesion prediction algorithm[25] as implemented in the LST toolbox version 3.0.0 (www.statistical-modelling.de/lst.html) for SPM. WMH volume was quantified using the spatial dimensions of the voxels in each MRI slice. Due to missing data and MRI image quality issues, we were only able to perform WMH correlation analysis in some patients. These patients were divided into two groups according to the Fazekas grading scale: (1) Lower WMH (LWMH) group: WMH score 1–2 points, and (2) Higher WMH (HWMH) group: WMH score 3–6 points.

2.4. Evaluation of Cognitive Function

ISTAART further operationalized the measurement of MBI with the development of the Mild Behavioral Impairment-Checklist (MBI-C, available at http://www.MBItest.org)[26]. Mallo et al. showed that the cutoff point 6.5 significantly classified people with MBI diagnoses with a sensitivity of 100% and a specificity of 78.20%. The cut-point of 6.5 on the MBI-C best differentiated patients with MBI from those without[27]. All participants were evaluated with MBI-C. The MoCA is a simple, stand-alone cognitive screening tool with superior sensitivity. It covers essential cognitive domains, can be administered in 10 minutes, and fits on one page. Moreover, the data indicate that it has excellent test-retest reliability and positive and negative predictive values for MCI and AD[28]. Accordingly, the diagnosis of post-stroke cognitive impairment in our study was defined as a MoCA score of less than 26.

2.5. Demographic and Clinical Risk Factors

The following demographic and clinical data were collected at the beginning of the study: age, sex, education level, current smoking status, tobacco use and intravenous thrombolytic treatment with recombinant tissue-type plasminogen activator. The personal medical history for each patient concerning prior stroke or Transient Ischemic Attack (TIA), hypertension, diabetes, dyslipidemia, and atrial fibrillation, as well as the use of medication, was obtained via a self-report. Alcohol use was defined as the daily intake of at least 100 ml of liquor three times per week or more. Current smoking status was recorded in case the patient had been smoking for at least three months before their enrollment in the study. A stroke neurologist recorded the NIHSS score on the day of admission.

2.6. Statistical Analysis

The data are presented as mean ± standard deviation for continuous quantitative variables, and as frequencies and rate (%) for categorical variables. Initially, the Kolmogorov-Smirnov test was applied to detect normal distributions among the quantitative variables. Subsequently, we used either the Student’s t-test or one-way analysis of variance (ANOVA) to compare the normally distributed quantitative variables and the Chi-square test for the customarily distributed qualitative variables. Mann-Whitney U test was applied to compare variables with a nonnormal distribution. Univariate logistic regression analysis was performed to explore the association between ICAS and MBI. The following factors were considered during adjustment for confounders: age, sex, education level, history of hypertension, diabetes, and laboratory test results of hypercholesterolemia. We used binary logistic regression analysis to assess the degree of association between variables, and used the Odds Ratio (OR) and the corresponding 95% confidence interval (CI) to describe the strength of the association. By using the stepAIC method, we selected the best prediction model more scientifically and accurately, and improved the accuracy and reliability of prediction. In addition, we studied the relationship between ICAS and MOCA score, frailty and fatigue in the same way. Logistic regression was performed on each of the 40 cerebral cortex regions to screen out meaningful variables. Voxel-based logistic regression models were used to evaluate the associations between the MBI-C Score and meaningful regional GM volume and cortical thickness. Age, sex, and years of education were used as covariates in all voxel-based regression analyses. The same approach was taken for the analysis of the relationship between WMH and MBI. All statistical analyses were performed using the R Statistical Software Package. P values less than 0.05 were considered statistically significant.www.r-project.org/). P values less than 0.05 were considered statistically significant.

3.1. Characteristics of the Subjects

Baseline demographics are summarized in Table 1. There were no significant differences in gender, education, HTN, DM, CAD, hypercholesterolemia, Smoke, alcholo and education level between the 69 patients with ICAS and the 52 patients without ICAS. Importantly, patients with MBI had a significantly higher percentage of ICAS than those without MBI (15.9% vs. 51.9%, respectively; p < 0.05). While there were statistical differences in age, MOCA score and The Frail Scale score between the two groups (p < 0.05) (Table 1).

Abbreviations: MBI-C: Mild Behavioral Impairment Checklist; MoCA: Montreal Cognitive Assessment; ICAS: intracranial atherosclerotic stenosis; HTN: hypertension; DM: diabetes mellitus; CAD: coronary artery disease; HC： hypercholesterolemia; FBI: Fasting blood insulin； CRP: C-reactive protein； WBC: White blood cell count; N: Neutrophil count; L: Lymphocyte count; PLT: Platelet count; ESR: Erythrocyte sedimentation rate. *p<0.05.

3.2. The distribution of ICAS.

Table 2 presents the percentage and distribution of ICAS in patients with a minor stroke. We observed that the majority of stenotic sites were located in the Middle Cerebral Artery (MCA), followed by the Posterior Cerebral Artery (PCA).

Table 2 The percentage and distribution of ICAS in patients with a minor stroke.

Abbreviations: ICA: Internal carotid artery (intracranial segments), MCA: middle cerebral artery (M1-M3 segments), ACA: anterior cerebral artery (A1 segments), VA: vertebral artery (intracranial segment), BA: basilar artery, PCA: posterior cerebral artery (P1-P3 segments).

3.3. the association between ICAS and MBI

Binary logistic regression was used to assess the association between ICAS and MBI, as shown in Table 3. ICAS was positively associated with MBI following an acute, non-disabling ischemic stroke after adjustment for age and sex in model 2 (OR: 5.62; 95% CI: 2.41-14.0). This association still existed after adjustment for the following factors in model 3 (OR: 5.28; 95% CI: 2.27-13.0): education level, history of hypertension, diabetes, and HDL(Table 3).[23] This illustrates that our results are robust. Additionally, Supplementary Table 1 reveals the associations between ICAS and MoCA, frailty, and fatigue. Although the results did not exhibit robust and significant relationships, there may be some underlying connections.

Abbreviations: Model 1: unadjusted; Model 2: adjusted for age and sex; Model 3: adjusted for age, sex, education level, history of hypertension, diabetes, atrial fibrillation, stroke, smoking, drinking, and laboratory tests of FBI, CRP, WBC, N, L, PLT, ESR. OR indicates odds ratio; CI, confidence interval; ICAS, intracranial atherosclerotic stenosis. *p<0.05.

3.4 Analysis based on brain structure.

Voxel-based logistic regression analysis between WMH volume and MBI did not show a correlation between WMH and MBI scores, Moca scores, The Frail Scale, and The Fatigue Scale (Table 4). Binary logistic regression was performed on cortical thickness and gray matter volume and MBI in different brain regions, and the results were shown in Supplementary Table 2 and Supplementary Table 3, respectively. The gray matter volume and MBI-C score did not show a correlation in any brain region (Supplementary Table 3). The thickness of the right precuneus cortex was screened for possible association with the MBI-C score(Supplementary Table 2). Subsequently, multivariable logistic regression analysis showed that after adjusting for confounders, the MBI-C score was negatively correlated with right precuneus thickness (p<0.05, CI: 0.00-0.24).

Abbreviations: MBI-C: Mild Behavioral Impairment Checklist; MoCA: Montreal Cognitive Assessment; ICAS: intracranial atherosclerotic stenosis; HWMH: Higher white matter hyperintensities

We found that participants with ICAS≥50%, compared to those without ICAS, had five times higher odds of MBI, even after adjustment for demographic and vascular risk factors. ICAD is also associated with Moca and fatigue but not with the volume of WMH and gray matter volume. NPS are common features of all types of dementia, irrespective of disease etiology and disease stage[29]. MBI may be an earlier marker of neurodegenerative disease than MCI, captured at the stage of subjective cognitive decline or before, raising the possibility that MBI represents a novel target for dementia clinical trials or prevention strategies[30]. A growing body of research suggesting that atherosclerosis is an essential contributor to late-life cognitive impairment[2, 31]. It is not clear from our studies what the mechanisms are by which vessel disease could cause neuronal dysfunction or whether this is only an association. It could simply be driven by the exact mechanisms that drive arteriolosclerosis embolization or spontaneous cerebral micro-emboli both of which have also been linked to late-life cognitive impairment[32]. Current theories of dementia pathogenesis suggest there is a continuum between vascular disease and dementia such as AD[31]. Although there are suggestions that there are associations between atherosclerosis and excess β-amyloidosis, definitive evidence for a synergistic interaction between cerebrovascular disease and AD pathophysiology has been elusive. As this study is cross-sectional, it is only hypothesis-generating regarding this point. There is increasing recognition that microvascular disease and β-amyloid and tau deposition often coexist. The findings suggest that cerebrovascular disease may play an essential role in determining the presence and severity of the clinical symptoms of AD. Many believe that identifying and treating vascular risk factors is equally vital to preventing cognitive decline[33]. A small number of studies have examined the link between ICAD and dementia. Intracranial arterial stenosis increased the risk of developing AD dementia after MCI[11, 34, 35] Our results support cadaveric studies that have shown that the number of atherosclerotic plaques and degree of stenosis is associated with AD[6, 8, 10, 36, 37]. Furthermore, some studies have examined a link between MBI and early AD-related pathological changes[38-41]. MBI has demonstrated an association with AD risk genes[42]. Thus, it seems that MBI identifies a potential at-risk group for incident cognitive decline and AD dementia.

Our study found that ICAS was significantly associated with cognition 25.3(OR: 25.3; 95% CI: 6.92-164), which is consistent with previous findings. Studies have found that neuropsychiatric symptoms occur in the pre-dementia period, even before the onset of cognitive symptoms[43-45], not only in frontotemporal dementia (FTD)[46, 47], but also in AD[43, 46, 48]. A follow-up study of more than five years found that NPS preceded a cognitive diagnosis for most people who developed cognitive decline (MCI and dementia)[44]. The study longitudinally analyzed NPS in 1,998 subjects who progressed from cognitively normal (CN) to MCI or dementia [as assessed using the Neuropsychiatric Inventory (NPI)] and found that among those who eventually developed AD, 30% developed NPS before MCI, whereas 42% developed NPS after MCI but before dementia. In addition, the prevalence of NPS in the year prior to the MCI or dementia diagnosis was 45–60%. Despite the fact that the volunteers in this study had a high family history of dementia, it is clear that the presence of new-onset NPS in cognitively normal older adults is likely to mean that they are at an increased risk of developing cognitive impairment.

Our study also found that precuneus cortical thickness was significantly inversely correlated with MBI scores, even after adjusting for age, sex, educational attainment, and ICAS.The precuneus is an intriguing cortical area, not only due to its buried location in the posteromedial cortex of the parietal lobe but also because of its possible role in fundamental cognitive functioning, especially in the human brain[49]. Considerable prior neuroimaging has implicated the precuneus as a central node in the human brain, essential for supporting complex cognition and behavior. The widespread connectivity of the precuneus, involving higher association regions, suggests an essential role in integrating both internally and externally driven information[50]. Previous studies have also shown that the precuneus might have a smaller volume[51, 52]or be functionally impaired [53, 54] in younger patients with AD.Activations in the precuneus were consistently found in studies of episodic memory, visuospatial imagery and self-processing. The most parsimonious account for these kinds of activations is that they reflect cognitive processes that are tapped by the tasks in the different domains[55]. Our study provides a new way to further diagnose MBI through imaging.

There are several limitations in this study. Firstly, this is an observational cohort study, so there may be some residual confounding bias even after multivariable adjustment. Secondly, we did not discuss the five domains of MBI separately. Thirdly, the ε4 allele of the apolipoprotein E gene (APOE4) is a potent genetic risk factor for sporadic and late-onset familial AD[56]. However, we did not study the relationship between APOE4 and MBI.

In conclusion, this study has been designed to provide insights into the impact of ICAS on MBI in patients with mild stroke. It is anticipated that a precise diagnostic and treatment strategy for the ICAS population will eventually be established.

ICAS: Intracranial atherosclerotic stenosis MBI: mild behavioral impairment MBI-C : MBI checklist NPS: Neuropsychiatric symptoms MCI: mild cognitive impairment ICA: internal carotid artery, MCA : middle cerebral artery ACA: anterior cerebral artery PCA: posterior cerebral artery BA: basilar artery VA: vertebral artery MRA: magnetic resonance angiography NIHSS: National Institutes of Health Stroke Scale FS-14: Fatigue Scale-14 ISTAART: International Society to Advance Alzheimer’s Research and Treatment FLAIR: fluid-attenuated inversion recovery WASID: Warfarin-Aspirin Symptomatic Intracranial Disease WMHs: White matter hyperintensities TIA: Transient Ischemic Attack CI: confidence interval HTN: hypertension DM: diabetes mellitus CAD: coronary artery disease HC： hypercholesterolemia FBI: Fasting blood insulin CRP: C-reactive protein WBC: White blood cell count N: Neutrophil count L: Lymphocyte count PLT: Platelet count ESR: Erythrocyte sedimentation rate. FTD : frontotemporal dementia CN : cognitively normal

Human rights and animal rights

No animals were used in this study. All humans research procedures followed were in accordance with the guidelines of the Declaration of Helsinki of 1975, as revised in 2013 (http://ethics.iit.edu/ecodes/node/3931).

Consent for publication

Informed consent was obtained from the patients or legally authorized representatives before the therapies.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Funding

1. The projects of the National Natural Science Foundation of China (82201565).

2. Shanghai Sailing Program (Grant Numbers:21YF1411600).

3. Investigator Initiated Research Projects of Huadong Hospital [Grant Number: HDLC2022003].

4. Shanghai Hospital Development Center Foundation (SHDC22022304).

Medical writing and editorial assistance

The authors did not use medical writing or editorial support for this paper.

Author contributions

Zhengxin Liu analyzed and interpreted the data and wrote the manuscript; Wenshi Wei reviewed the manuscript.

Ethics approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Conflict of interest

The authors declare no conflict of interest, financial or otherwise.

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The Association between Intracranial Atherosclerotic Stenosis and Post- stroke Mild Behavioral Impairment

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Abstract

Purpose

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Conclusions

1. Background

2. Methods

2.1Study population

2.2. Neuroimaging Evaluations

2.3Analysis of brain structure

2.4. Evaluation of Cognitive Function

2.5. Demographic and Clinical Risk Factors

2.6. Statistical Analysis

3. Results

3.1. Characteristics of the Subjects

Discussion

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