Carotid Arteries in Cerebral Small Vessel Disease and Dementia

Carotid Arteries in Cerebral Small Vessel Disease and Dementia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Carotid Arteries in Cerebral Small Vessel Disease and Dementia Erika Kitajima, Ashley Suwanda, Dan Jobson, Louise Allan, Kian Paydar, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7852432/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Mar, 2026 Read the published version in Acta Neuropathologica Communications → Version 1 posted 9 You are reading this latest preprint version Abstract Carotid artery disease (CAD) is a recognised important cause of stroke. However, the relationship between CAD and cerebral small vessel disease (SVD) and dementia remains unclear. We hypothesized that CAD in older individuals significantly affects cerebral perfusion, and leadsto cerebral SVD. We performed a clinicopathological study in patients from the Cognitive Function After Stroke (CogFAST) study and prospectively recruited patients with various dementia diagnoses and evidence of cerebral SVD. In addition to brain tissues, we collected postmortem samples of the internal carotid arteries (ICA) from these cohorts in the Newcastle Brain Tissue Resource. Standard neuropathological examination was performed for diagnosis and assignment of the cases per current diagnostic criteria for vascular and neurodegenerative dementias, which were assessed for the presence of vascular pathology including the degree of stenosis and sclerosis in vascular tissues. We evaluated a total of 159 ICA samples and brain tissues from all cases with evidence of SVD. Severity of ICA stenosis and sclerotic index correlated strongly with both clinical stroke and brain infarction (F15, df 135, Pfibrocalcific >fibrous cap (thick) >fibrous cap (thin) >thrombus group with a strong inflammatory reaction in fibrocalcific atheromas. Linear regression analysis showed that ICA stenosis was positively correlated to both SVD pathology scores and total number of vascular lesions (r=0.34, 95% CI 0.18-0.49, P<0.034) . We found that severity of stenosis was related to anterior circulation involvement and small infarcts in the subcortical structures including the white matter (WM) rather than the cortex. Total intracranial artery scores were correlated with ICA stenosis and sclerosis (r=0.43, 95% CI 0.26-0.56, P<0.001 ). In the CogFAST group analysis, the smallest lesions in the WM but not in the cortex or basal ganglia and thalamus were associated with severity of ICA stenosis (r=0.42, 95% CI 0.27-0.56, P <0.05). Carotid atherosclerosis promotes cerebral SVD types of change and influences the cerebral arterial system. Our observations also suggest extracranial ICA pathology impacts on the perfusion and integrity of the deep WM. Atherosclerosis Carotid Artery Disease Small Vessel Disease Vascular Dementia White Matter Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Carotid artery disease (CAD) is a well-recognized causes of large vessel stroke. Population based studies reported that the age-standardised incidence rates of ischemic stroke subtypes due to large-artery atherosclerosis is approximately 15 per 100,000 persons [ 28 ]. This accords with the annual rate of first-ever and recurrent stroke attributed to extracranial internal carotid artery (ICA) as 13.4 (11.4–15.4) per 100,000 persons [ 12 ]. Carotid intima-medial thickness and carotid atherosclerotic plaques are also acknowledged as early and measurable risk factors for incident stroke and cerebrovascular events.[ 22 , 50 , 51 ]. ICA stenosis classified as mild to moderate according to ECST or NASCET criteria is generally considered haemodynamically insignificant, and carotid endarterectomy (CEA) offers little to no clinical benefit in these cases. However, severe ICA stenosis is associated with a substantially increased risk of stroke, thereby warranting vascular intervention such as CEA.[ 44 ] to reduce risk of stroke in both symptomatic and asymptomatic patients [ 1 , 5 , 13 , 39 ]. CAD or carotid artery stenosis is also associated with markers of cerebral small vessel disease (SVD) such as white matter (WM) changes and lacunar infarcts [ 4 , 27 ]. Thus, CAD may promote global hypoperfusion [ 30 ], cognitive impairment [ 46 ] and vascular dementia (VaD) [ 11 , 41 ]. However, there are limited studies on the relationship or interaction between CAD and intracranial brain vascular or parenchymal changes. In this study, we assessed the spectrum of CAD in relation to cerebral SVD pathology in prospectively collected carotid arteries from two cohorts namely the Cognitive Function After Stroke (CogFAST) and Newcastle prospective dementia studies where we had clinical, neuroimaging and pathological evidence of cerebral SVD. Materials and Methods Study design and subjects Demographic, clinical and pathological findings in the subjects of the study are given in Table 1 . Study subjects were participants of the Newcastle longitudinal prospective dementia series [ 20 ] and the CogFAST study [ 3 ]. They had a clinical diagnosis of stroke without dementia, vascular dementia, Alzheimer’s disease, mixed dementia (Mixed), Lewy body dementia or Parkinson’s disease with dementia but all had some evidence of cerebral SVD. Age-matched control subjects aged > 70 years were either part of previous prospective studies or based on unrelated brain donations to the Newcastle Brain Tissue Resource (NBTR). They were included as controls if they had not been diagnosed with cognitive impairment or any neurological or psychiatric illness. Ethical approval and permissions for this study using donated human brains was granted by the Newcastle and North Tyneside 1 Research Ethics Committee and facilitated by the NBTR. Permission for use of brains for post-mortem research was also granted by consent from the participants themselves, next-of-kin or family member. Brain tissues were retained in and obtained from the NBTR. Table 1 Demographic details of carotid artery cases in relation to clinical stroke, brain infarcts and dementia Variable Total No. of Cases Clinical Stroke No Stroke Significance* ( P value) Number 159 (100%) 104 (65.4%) 55 (34.6%) - Age (years)† 85.0 ± 0.6 86.6 ± 0.6 82.0 ± 1.1 0.001 Age Range (min-max) 38 (63–101) 31 (68–99) 38 (63–101) - Sex: (Men %) 56% 50% 43% 0.104 Dementia (%) 61.1% 62.6% 59.4% 0.620 Brain Weight (g) 1228 ± 11 1238 ± 14 1210 ± 21 0.442 Brain Infarction (%) 77.4% 96.2% 41.6% <0.001 Neuropathological Findings†† NSP (control %) 11.3% 2.8% 27.3% < 0.001 Cerebrovascular (%) 55.3% 80.0% 9.1% < 0.001 Primary Neurodegenerative (%) 20.8% 4.8% 50.9% 0.05 CAD pathology ICA Stenosis (%) 56.1 ± 1.2 61.3 ± 1.6 48.5 ± 1.1 < 0.001 ICA Sclerosis (SI) 0.346 ± 0.01 0.386 + 0.01 0.290 + 0.01 0.05 Pathological Intimal Thickening (L/R) 48/45 24/28 24/17 > 0.05 Fibrocalcific (L/R)‡‡ 41/47 28/25 13/22 0.018 Fibrous Cap 1 (L/R) 37/37 24/22 13/15 > 0.05 Fibrous Cap 2 (thin) (L/R) 13/9 7/6 6/3 > 0.05 Other Occlusion e.g. thrombus (L/R) 2/1 2/1 0/0 > 0.05 Values are shown as mean ± SEM or % of total lesions otherwise specified. *Statistical significance between variables with and without clinical stroke was evaluated by ANOVA, post-hoc tests, independent t-test or Pearson Chi-square where applicable, variances were determined to be equal unless otherwise stated. †Mean ages (years + SEM) of men and women in the total sample were 83.4 ± 0.8 and 87.0 ± 0.8 (P = 0.001) . ††Neurodegenerative pathologies included Alzheimer’s disease, dementia with Lewy bodies, limbic age-related TDP-43 encephalopathy (LATE), Huntington’s disease, progressive supranuclear palsy, multiple system atrophy, and mitochondrial disorder, any of which could be the cause of clinical dementia. ‡Number of ICA lesions in the left (L) and right (R) segments. Different lesion types were greater in the left ICA than in the right ICA in stroke patients (P = 0.01) . ‡‡Greater number of fibrocalcific lesions in the stroke cases. Abbreviations: CA, carotid artery; CAD, carotid artery disease; ICA, internal carotid artery; L, left; No., number; NSP, no significant pathology; R, right; SI, sclerotic index. Post-mortem Carotid Arteries and Brain Tissues Samples of the right and left ICAs were taken at 4 mm distal to the level of the carotid bifurcation. For quantitative analysis, ten-µm thick serial sections cut from paraffin embedded transverse ICA blocks and CAs blocks were stained with Haematoxylin and Eosin (H&E). Brains were sampled bilaterally and assessed in accordance with the Newcastle brain dissection protocol. Standardised protocols were used for microscopic and macroscopic pathology assessment [ 15 , 23 ]. Briefly, macroscopic infarcts were recorded by visual inspection during dissection, and subsequently their presence was confirmed by microscopy. The size and total number of infarcts (designated as vascular lesions) in both hemispheres in the cortex, basal ganglia, thalamus, white matter, brainstem and cerebellum were recorded as follows: 51 mm. H&E stain was used for neuropathological assessment including vascular pathology scores to confirm SVD pathology. In addition to the total number, vascular lesions in the anterior and posterior circulation territories as well as cortical and subcortical regions were determined for each case. WM scores (0–3) were determined as described previously based on the degree of demyelination and vascular pathology [ 9 , 20 ]. Carotid and Cerebral Artery Pathologies Histopathological evaluation of internal carotid artery was conducted using standard tinctorial stains such as H&E. Carotid artery disease (CAD was categorized using a previously established classification system [ 2 ] with additional adherence to recent observations on calcification of artherosclerotic plaques [ 47 ]. CAD was grouped into five subtypes consisting of intimal thickening, fibrocalcific, fibrous C1 (thick), fibrous C2 (thin) and other which included thrombi. CAD pathology was rated by two investigators (TMP and RNK) with > 90% agreement. Further cellular characterization of the artery vessel walls and atheromatous material was undertaken by immunostaining via standardised methods in 10 post-stroke cases with varied stenosis for α-smooth muscle actin (α-SMA), CD68-positive macrophages and isoAsp-Gly-Arg (isoDGR) degenerative protein modifications (1:200-1:1000 dilutions) [ 19 , 26 ]. ICA including the circle of Willis, basilar, anterior and middle cerebral arteries were examined for the degree of stenosis and assigned scores of 0 to 3 for none, mild, moderate and severe. Total intracerebral artery scores were calculated as an average of all the cerebral artery scores. Carotid artery stenosis was categorized into mild, moderate and severe based on modifications of the ultrasound and angiographic methods used in the European Carotid Surgery Trial (ECST) and the North American Symptomatic Endarterectomy Trial [ 40 , 45 ]. Given our previous histopathological study[ 21 ], we ascertained that moderate stenosis was in range 50–75% matching the ECST low moderate category, while the severe stenosis (> 75%) matched the combined ECST high moderate and severe categories. Following this paradigm we fit all our cases including cerebral arteries into three basic categories of mild ( 75%) stenosis (Supplementary Fig. 1). Measurements of stenosis and sclerosis We scanned H&E stained sections with the highest degree of stenosis using a photo scanner (EPSON Perfection V700, Seiko Epson Corporation, Suwa, Nagano, Japan) [ 21 ]. Total area of the external margin of the adventitia (S1) and luminal area at the interior margin of the intima (S2) were measured using IMAGEJ software (National Institutes of Health, Bethesda, MD, USA). The % diameter stenosis was calculated using the following formula: % diameter stenosis = (S1-S2)/(S1) ×100. The % area stenosis of both right and left ICAs were calculated. To determine the degree of sclerosis, the length from four different points across the artery were taken between the furthest exterior margin (S1) of the adventitia and the luminal area at its inner margin (S2). In preliminary experiments, we attested the use of this modified method by assessing larger vessels with diameters greater than 1mm. The following formula was used to compute the sclerotic index = (S1-S2)/(S1). The measurement result from four points were averaged to have the final sclerotic index. Sclerotic indices were computed from both the left and right ICAs, and a mean value was then calculated. All data analyses were performed by three investigators (EK, AS, YH) blinded to case identities. Neurodegenerative Pathology Assessment Gallyas and Bielschowsky’s silver impregnation and tau immunohistochemistry (AT8 for pTau at 1:1000 dilution) were used to assess neuritic plaques and neurofibrillary tangles for the ‘Consortium to Establish a Registry for Alzheimer’s Disease’ plaque score and ‘Braak and Braak’ neurofibrillary tangle staging. Pathological diagnosis of VaD was assigned, if there was clinical evidence of dementia using the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition and relevant vascular pathology in the general absence of neurodegenerative pathology, that is, Braak staging I-IV. Severity of cerebral amyloid angiopathy (CAA) was assessed using a four-point scale as described previously [ 32 ]. α-synuclein was the pathological alteration in Parkinson's disease and dementia with Lewy bodies dementia [ 20 ]. Total SVD pathology scores were determined out of a total of 20 according to Deramecourt et al [ 9 ]. To assess glial cell responses, immunohistochemical staining was undertaken in sections from the frontal deep WM. Antibodies to GFAP and CD68 were used as respective markers of astrocytes and microglia or macrophages, with the percent area quantified as described previously [ 19 , 20 ]. Statistical analysis Raw data were analysed using GraphPad Prism 10 software (Boston, MA, USA) and IBM SPSS Statistics Version 29.0.1.1 (Armonk, NY, USA). Standard descriptive statistics were used to describe the total and CogFAST samples. Unless otherwise stated, data are presented as mean \(\:\pm\:\) SEM. The Shapiro-Wilk test was used for normality testing. Bivariate relationships of key characteristics e.g. age, brain weight, degrees of stenosis, sclerosis, vascular pathology scores, number of vascular lesions, etc. were examined using correlation analysis (Pearson’s R), Student independent t tests, or analysis of variance (ANOVA) as appropriate. Post-hoc authentication included the Tukey and Bonferroni tests. The percentages of stenosis and sclerotic index were compared between stroke and non-stroke cases. The differences between variables to baseline characteristics were also compared using Pearson’s Chi-squared test. In all analyses, a value of P < 0.05 was considered as statistically significant. Results Clinical stroke, Brain Infarction and Carotid Artery Disease This study was based on clinical and pathological observations in a total of 159 cases for which we had clinical information as well as pathological assessments of the carotid arteries (Table 1 ). Of these, 104 had clinical evidence of stroke with 5% of the cases showing no apparent brain infarction at postmortem (Table 1 ). Unless otherwise specified in the sub-analysis, subsequent analysis involved 140 cases where we had isolated carotid artery samples. We found that clinically defined stroke was associated with older age as was brain infarction on pathological examination ( P = 0.001 ). There were no differences in sex, brain weights or presence of clinical dementia prior to death between the stroke and non-stroke groups ( P > 0.05 ). The numbers of subjects with dementia in the stroke sample was 50% whereas this comprised 43% in the non-stroke sample (Table 1 ). We first noted that neither the mean percent stenosis nor sclerosis was different between the left and right ICAs (Fig. 1 A and B). In subsequent analysis, we therefore averaged the percent values from left and right ICAs and used these as a single measure for each case. We found that the mean percent stenosis and sclerosis were greater in stroke subjects compared to non-stroke subjects (Table 1 ; Fig. 1 C and D). In the total sample incorporating both stroke and non-stroke cases (n = 140), nearly 50% of the subjects exhibited moderate stenosis of the ICA with the rest as mild (32.7%) and severe (21.4%). The degree of stenosis and sclerosis differed significantly between the clinical stroke and non-stroke cases (Fig. 1 C and D). More than 30% of the stroke cases showed severe stenosis compared to 6% in the non-stroke subjects. Similarly, severe sclerosis was also more common in stroke subjects; but remarkably 70% of the non-stroke samples exhibited moderate degrees of sclerosis in the ICA (Fig. 1 D). ICA stenosis and sclerosis measures were strongly related (r = 0.925, P < 0.001) but we also found correlations between clinical stroke and ICA stenosis or sclerosis, in a general linear model controlling for age (F16, df 1, P < 0.001; F 15 df 1, P < 0.001). Thus, stroke patients showed significantly worse ICA stenosis and sclerosis than those without stroke (Fig. 1 ) but moderate degrees of sclerosis were a common finding in the ICA irrespective of stroke pathology. We examined several segments of the common CA, ICA and external CA. We noted atherosclerosis was most frequent in the ICA. Macro- and microscopic examination of both the left and right ICA samples specified five different classic types of changes in the vessel walls (Figs. 2 and 3 ). More than 90% of the subjects had some type of ICA lesion in these age groups (Table 1 ). Light microscopy revealed that in general the atheromatous pathology in the ICA was not qualitatively different from that reported in coronary arteries or aortic arches [ 2 , 6 ]. We found intimal thickening to be a common finding. The frequency in the order of the ICA subtypes in the total sample were intimal thickening > fibrocalcific > fibrous cap (thick) > fibrous cap (thin) > other group (Table 1 ; Fig. 2 J-L). We also found that there was marginally greater ICA pathology in the left than the right ICA. In addition, stroke subjects had more proportions of pathological lesions in both left and right ICAs compared to those without stroke. However, there were substantial proportions of fibrocalcific and fibrous C1 (thick) lesions in both groups (Table 1 ) and across all confirmed brain pathologies including vascular, neurodegenerative and mixed (Supplementary Fig. 2). Ruptured atheromatous lesions were rare with a frequency of < 5% in the total sample suggesting there may be limited contribution by ICAs to thromboembolic strokes in the brain. In order to identify specific changes within the intima and the atheromas in the vessel walls, we immunostained segments of the ICA for cellular inflammatory responses (Fig. 3 ). We found typical frequent disarray of α-SMA positive cells within the vessel wall matrix. Several cells were positive for HSP-27, which we determined as typical foam cells. Numerous CD68 positive macrophages were also evident particularly in the medial layers in all the cases with fibrocalcific or fibrous cap lesions. We noted concentric patterns of cells depicting proliferation within the vasa vasorum. There was occasional evidence of haemorrhage within the atheromas (Fig. 2 D) indicating bleeding from weak vasa vasorum. In addition, as we showed recently [ 25 , 26 ] there was extensive accumulation of isoDGR-modified (deaminated) proteins [ 14 ] in the vessel walls overlapping with CD68-positive macrophages. This indicated an active and sustained inflammatory reaction ongoing within the ICA atheromas, potentially exacerbated by the accumulation of isoDGR-modified proteins [ 34 , 42 ] (Fig. 3 ). Relationship between ICA Pathology and Cerebral SVD Lesions We next determined whether ICA stenosis influenced parenchymal pathology characterised by cerebral SVD (Supplementary Tables 1 and 2). Linear regression analysis showed that ICA stenosis were positively related to both SVD pathology scores and the total number of vascular lesions (Supplementary Table 1). We further noted that subjects with both severe stenosis and sclerosis exhibited greater numbers of vascular lesions (Fig. 4 A and B). We found subcortical rather than cortical vascular lesions to be related to severity of stenosis (Supplementary Table 1). Remarkably, WM scores (of vascular aetiology) were related to both ICA stenosis and sclerosis (Supplementary Table 1). This indicates ICA pathology likely impacts on the integrity of the deep WM. In terms of brain vascular pathology, we observed that cerebral vascular systems within the circle of Willis, basilar and smaller (anterior or middle) cerebral arteries characterised by any atheromatous disease or subtype vessel wall lesions were all related to both ICA stenosis and sclerosis severity (Supplementary Table 1). After averaging scores for all cerebral arterial pathology, we showed that the total intracranial artery scores were positively correlated with ICA stenosis and sclerosis (Supplementary Table 1). There were more vascular lesions in the anterior circulation compared to the posterior circulation ( P < 0.001) (Fig. 4 C; Supplementary Table 1). Our results indicated that CAD in the ICAs increased risk of atheromatous diseases in the cerebral arteries within the anterior circulation. It was also observed that intimal thickening was the most common lesion in cerebral vessels in this age group (Fig. 4 D). Carotid Artery and SVD Pathology in CogFAST In an attempt to elucidate more specific substrates within stroke subjects, we assessed whether the severity of ICA stenosis, as mild, moderate or severe, was associated with a number of clinical and pathological variables specifically in the CogFAST study cases (Table 2 ). Of the 80 subjects we assessed, 23% exhibited mild stenosis, 38% had moderate stenosis and 39% had severe stenosis prior to death. As for the total sample, age, sex and brain weights did not different significantly between the groups (Table 2 ). We found that at least 50% had a diagnosis of dementia in each group. While final Mini-Mental State Examination (MMSE) and Cambridge Cognitive Examination (CAMCOG) cognitive scores tended to be reduced in the severe groups we found that they were only significantly reduced when the moderate-severe stenosis scores were combined and compared to the mild stenosis group ( P < 0.05). CAMCOG scores in the severe group were lower than the mild group ( P = 0.015). Table 2 Demographic details of CogFAST cases in relation to severity of CAD and other pathologies Variable Mild Moderate Severe Significance ( P value) Number of subjects (% of n = 80) 19 (23%) 30 (38%) 31 (39%) - Age (years), mean ± SEM (range) 85.1 ± 1.2 (76–95) 86.2 ± 1.1 (71–98) 88.2 ± 1.1(75–99) 0.156 Sex (male %) 53% 43% 61% 0.373 Brain Weight (g) 1247 ± 40 1204 ± 20 1271 ± 27 0.179 Clinical features Dementia (PSD) (%) 52% 60% 58% 0.876 MMSE 24 ± 1 21 ± 2 20 ± 2 0.250 CAMCOG* 84 ± 4 70 ± 5 68 ± 5 < 0.05 Hypertension 46% 76% 48% 0.233 Type 2 Diabetes 8% 5% 10% 0.771 Hypercholesterolemia 0% 14% 17% 0.290 No of VRFs (range) 1 (0–3) 2 (0–3) 2 (0–3) 0.108 APOE allele Frequencies APOE ε4 (%) 3.3% 5.0% 7.5% > 0.05 APOE ε3 (%) 14.2% 26.7% 35.0% > 0.05 APOE ε2 (%) 2.5% 1.7% 4.2% > 0.05 Pathology markers ICA External Diameter, mean ± SEM cm‖ 0.628 ± 0.060 0.686 ± 0.022 0.728 ± 0.027 > 0.05 % ICA stenosis, mean ± SEM# 40.4 ± 2.1 58.6 ± 1.5 74.3 ± 1.3 < 0.001 % ICA sclerosis, mean ± SEM 0.247 ± 0.013 0.370 ± 0.014 0.482 ± 0.021 0.05 CERAD score, mean (range) 1.0 (0–3) 1.2 (0–3) 1.1 (0–3) > 0.05 α-synuclein, mean (range) 0.0 (0) 0.7 (0–6) 1.7 (0–14) > 0.05 CAA score, mean (range) 1.0 (0–3) 1.1 (0–3) 1.1 (0–3) > 0.05 SVD Pathology Score‡ 12.6 ± 0.8 13.0 ± 0.4 13.3 ± 0.4 0.589 Total cerebral vascular lesions 3.9 ± 0.6 3.8 ± 0.8 4.3 ± 0.5 0.733 Intracranial artery score‡‡ 3.7 ± 0.5 3.6 ± 0.4 4.7 ± 0.4 0.104 WM Scores 2.6 (1–3) 2.9 (2–3) 2.8 (1–3) 0.239 WM GFAP (% area)† 0.82 ± 0.1 0.91 ± 0.1 1.30 ± 0.15 0.043 WM CD68 (% area)† 0.61 + 0.1 0.70 + 0.1 0.82 + 0.1 0.264 Values represent mean + SEM for number of subjects shown. The range of severity scores in the circle of Willis, basilar artery and cerebral arteries was 1.1–1.7. There were no differences between mild, moderate and severe stenosed subjects ( P > 0.250). ‡Post-stroke dementia (PSD) defined by DSM IV, IVR or V criteria was not associated with severity of CA stenosis or sclerosis (cf. Table 1 ). ‖Represents the mean of left ICA and right CA, there were no differences between left and right ICA external diameters ( P > 0.05) . †ANOVA and post-hoc tests showed that GFAP but not CD68 immunoreactivity was increased in the ICA severe stenosis group (n = 35 total in mild, moderate and severe groups, F3.3, df2, P = 0.045). Abbreviations: ANOVA, analysis of variance; CA, carotid arteries; CERAD, Consortium to Establish a Registry for Alzheimer’s Disease; Braak, Braak NFT stage; CAA, cerebral amyloid angiopathy; ICA, internal carotid artery; PSD, post-stroke dementia; CBF, Cerebral blood flow; PSD, post-stroke dementia; VRF, vascular risk factor. There was no evidence for differences in frequencies or number of vascular risk factors between the groups (Table 2 ). However, while there were no cases of hypercholesterolemia in the mild stenosis group, we noted that 14% and 17% of moderate and severe groups exhibited this vascular risk factor. There were also no differences in the frequencies of APOE ε2, ε3 or ε4 alleles between the groups ( P > 0.05). Assessment of relevant pathological indices showed that mean values of both ICA stenosis and sclerosis increased with increasing stenosis severity ( P < 0.001). However, the distribution of vascular pathology or neurodegenerative disease markers was not different between the groups (Table 2 ). The prevalence of moderate-severe CAA pathology (approximately 24%) across all mild, moderate and severe ICA stenosis groups remained almost unchanged (Table 2 ). We also noted that WM pathology scores were almost similar in the mild, moderate and severe groups. However, ANOVA showed that frontal WM GFAP but not CD68 immunoreactivity was significantly increased in severe stenosis subjects relative to the mild stenosis group (P = 0.045). In further analysis, we assessed the location and size of the lesions in the three groups (Fig. 5 ). These lesions were characterised as class II per original Newcastle classification system. Irrespective of the degree of ICA stenosis, we found that the greatest numbers of infarcts (range 42–51%) were in the cortex whereas the basal ganglia and thalamus contained the second highest numbers of infarcts (range 23–30%) (Fig. 5 A). The cerebellum had the least numbers of lesions; although there were significantly more cerebellar infarcts in the mild stenosis compared to the moderate and severe stenosis groups ( P < 0.05). In terms of the size, by far the majority of stroke lesions were small, < 5 mm in ranging from 70 to 80% (Fig. 5 B). There were no overall differences in the distributions of size of infarcts between the mild, moderate and severe stenosis groups (Fig. 5 B). Further scrutiny of the data showed that by far the majority of the smallest infarcts (< 5mm), up to 91% in the WM were evident in the group with severe stenosis. Linear regression analysis indicated that the numbers of smallest lesions in the WM but not in the cortex or basal ganglia and thalamus (BG) were related to the severity of ICA stenosis ( P < 0.05) (Fig. 5 C and legend). Discussion Our clinicopathological analysis of a large sample of ICAs confers several imperative findings and particularly throws light on the consequences of extracranial ICA stenosis on cerebral SVD. We first found that there was increased ICA stenosis and sclerosis in clinically diagnosed stroke cases. This is perhaps not surprising but our findings strongly suggest that the severity of ICA stenosis influences the burden of cerebral SVD pathology; particularly in terms of vascular lesion number, collective SVD pathology scores as well as subcortical structures including the WM, which may be more targeted than other brain regions. It is of particular note that severity of both ICA stenosis and sclerosis was correlated with WM pathology and that mostly SVD type small lacunar lesions were present in the WM. These observations are consistent with clinical studies [ 27 ] and reinforce that not all WM changes evident, such as white matter hyperintensities upon MRI of vascular origin, are solely explained by intracranial SVD. A systematic review followed by meta-analyses suggested that WM ipsilateral and contralateral to CAD site is associated with changes in the apparent diffusion coefficient (ADC), fractional anisotropy (FA), and mean diffusivity (MD) values [ 4 ]. Consistent with our findings, this report indicates that CAD is also associated with quantifiable white matter microstructural damage. Cerebral SVD types of change could be promoted by various mechanisms including altered haemodynamics or perfusion due to ICA occlusion induced by growing yet stable atherosclerotic plaques or a thrombus developing on an atheroma. Thus cerebral SVD events or deep watershed infarcts may not only result from hemodynamic impairment [ 37 ] but also from microemboli alone through plaque inflammation detected by FDG PET and the presence of transcranial Doppler microemboli signals [ 36 ]. It is also plausible that macro-fragments from an atheroma may embolize or a thrombus may break off, leading to artery-to-artery embolism [ 29 , 37 ] or there is cardiogenic microembolism due to atrial fibrillation [ 21 , 33 ]. As we found mostly intact fibrous caps in ICAs in our cases, we would surmise that thromboembolic events of ICA origin are rare to cause strokes in the CogFAST or the total cohort. Irrespective, it needs to be emphasized that effects of antithrombotic agents on embolic signals should still serve as a marker for their efficacy in preventing stroke recurrence [ 17 ]. Secondly, SVD and WM infarction is also associated with the risk of dementia [ 18 , 24 , 31 , 49 ]. Although we did not observe a clear relationship between severity of stenosis and dementia possibly because dementia diagnosis is made as a nominal measure beyond a certain threshold, we did observe that both MMSE and particularly CAMCOG scores worsened with severity of ICA stenosis in the CogFAST cases. However we did not have records of the MMSE and CAMCOG scores for the whole cohort. Furthermore, we did not find any sex or age-related differences in comparison to ICA stenosis or sclerosis in our sample, yet subjects with stroke were still older in age. Previous clinical studies showed that the prevalence of severe CA stenosis was 3.1% (1.7% to 5.3%) in men aged 80 years or older and 0.9 (0.3% to 2.4%) in women [ 7 ]. Thirdly, our findings suggest ICA stenosis and pathology are associated with the lesions in the anterior circulation and that fibrocalcific lesions are more common. It has been suggested that atherosclerotic calcification initially occurs as microcalcifications [ 47 ] and results in larger dense calcification as evident in our cases. There also appears to be a predilection for the left ICA to accumulate distinct types of atheromatous lesions. Our results therefore agree with population based imaging studies showing that the carotid plaques are associated with infarction in the anterior circulation [ 22 ]. Atherosclerosis is a systemic inflammatory disease that associates with several acute cardiovascular complications triggered by atherosclerotic plaque rupture, which primarily manifests as stroke or myocardial infarction. We found that while there were no qualitative differences between subtypes of atheromatous lesions described previously in cardiovascular arterial systems [ 6 ], we found disarray of both αSMA positive cells and other features including foam cells, collagen and lipid clefts. However, we showed that the inflammatory cellular response (demonstrated by CD68-positive macrophages) is concomitant with accumulation of degenerative protein modifications in extracellular matrix proteins such as fibronectin, laminin, and collagens [ 14 , 16 , 38 ]. The isoDGR-motif in the modified proteins is a ligand that specifically binds to integrins receptors, thus promoting immune cells recruitment and sustained inflammation, as detected by isoDGR-specific antibody [ 35 ]. These observations are consistent with the varied transcriptomic and epigenomic characteristics of human carotid atherosclerotic plaques. A previous single-cell RNA and single-cell ATAC sequencing study identified 14 distinct cell populations including endothelial cells, smooth muscle cells, mast cells, B cells, myeloid cells and T cells in multiple cellular activation states and interconversions [ 8 ]. Thereby only further emphasising the inflammatory cellular complexity of localised atherosclerotic plaque sites. Fourthly, we found evidence that severe ICA stenosis influences vessel wall pathology or stenosis in the intracranial arterial system incorporating branches of the circle of Willis, anterior or middle cerebral arteries and the basilar artery. Thus how might ICA stenosis and sclerosis affects cerebral vascular function? It is plausible that carotid arterial walls alter the vascular haemodynamics and endothelial cell function. In turn endothelium dysfunction can reduce vasomotor reactivity to impede normal flow leading to chronic or transient cerebral hypoperfusion particularly in the deeper distal structures including the WM. Relative to this, blood flow in the ICA without stenosis has been estimated to be 418 ml/min but with mild, moderate, and severe stenosis, it was calculated respectively to be 309 ml/min, 229 ml/min, and 117 ml/min [ 48 ]. Similarly, another study showed that with the increase in the severity of ICA stenosis, the ipsilateral blood flow reduced to 197 mL/min when stenosis was 50–69% and to 130 ml/min i.e. to 25% of normal flow with severe (70–99%) stenosis. Furthermore, the blood-brain barrier may also be compromised in the chronic hypoperfusion and hypoxic state [ 10 , 43 , 52 ]. We propose that intimal thickening within the intracranial (and intracerebral) arteries occurring as a function of age in tandem with changes in the haemodynamics and perfusion possibly exert progressive propagation effects along the arterial branching. Our study reports several strengths. The main one is that ICA stenosis severity caused by atherosclerotic disease characterised by fibrocalcific and consolidated fibrous lesions is related to cerebral SVD pathology. However, there are some limitations of for the study. Two of these include: 1) we would need a larger sample size to definitively determine the exact impact of ICA stenosis on cognitive function measures; 2) it remains unclear whether ICA stenosis and hence the resulting hypoperfusion influences the deposition of cerebral neurodegenerative pathologies in earlier stages of dementia. A third limitation is would be the use of medications including antiplatelet agents, anticoagulants, statins, and antihypertensives. These were not fully accounted for in the present analysis because the inromation on hand was not complete. In this respect, a potential future direction would be to investigate, particularly among individuals with severe ICA stenosis, whether these medications influence stroke risk, WM pathology, intimal thickening, fibrocalcific changes, or fibrous cap characteristics In summary, we provide evidence that severity of ICA stenosis influences the accumulation of cerebral SVD pathology and that subcortical structures including the WM may be more targeted than other brain regions. We also show that ICA atheromas are characterised by various subtypes of lesions among which intimal thickening and fibrocalcific lesions are common with significant presence of inflammation. Whilst extracranial stenosis most proximal to the cerebrum likely impact upon vessel wall health in more distal segments of the cerebral microvasculature. Declarations Data Availability The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to case privacy or ethical restrictions. The datasets used and analysed for the current study are available on request from the corresponding author Acknowledgements The authors are grateful to the patients and families for their cooperation in the investigation of this study. We thank the staff of the NBTR, Debbie Lett, Tracy Alder and Philippa Hepplewhite for mobilising the samples and technical assistance. Sources of funding Our work is supported by grants from the UK Medical Research Council (MRC, G0500247), Newcastle Centre for Brain Ageing and Vitality (BBSRC, EPSRC, ESRC and MRC, LLHW), and Alzheimer’s Research (ARUK). Tissue for this study was collected by the Newcastle Brain Tissue Resource, which is funded in part by a grant from the UK MRC (G0400074), by the Newcastle NIHR Biomedical Research Centre in Ageing and Age-Related Diseases award to the Newcastle upon Tyne Hospitals NHS Foundation Trust, and by a grant from the Alzheimer’s Society and ARUK as part of the Brains for Dementia Research Project. LA is supported by the Peninsular NIHR Applied Research Collaboration and the Exeter NIHR Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care." Ethical Approval Ethical approvals were granted by local research ethics committees of the Newcastle upon Tyne Foundation Hospitals Trust. Permission for use of brains for post-mortem research was also granted by consent from next-of-kin or family. All the brain tissues were retained in and obtained from the Newcastle Brain Tissue Resource. Author contributions (per CreDIT) Erika Kitajima: drafting, analysis and acquisition of data Ashley Suwanda: drafting, analysis and acquisition of data Dan Jobson: analysis, acquisition of data and editing manuscript Louise Allan: Clinical data analysis and editing the manuscript Kian Paydar: generating primary data, analysis and interpretation Gan Han: acquisition of data and images Kazuo Washida: analysis and acquisition of data Masafumi Ihara: editing the manuscript, interpretation Pazhanichamy Kalailingam: acquisition of data and images Yoshiki Hase: analysis, interpretation, acquisition of data, editing in manuscript Newman Siu Kwan Sze: editing the manuscript, interpretation and acquisition of data Tuomo Polvikoski: case diagnosis and acquisition of data Raj N Kalaria: drafting, revising the manuscript and interpretation of data, diagnosing the cases and obtaining funding. 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Supplementary Files CAcerebralSVDandDementiaKitajimaetal2025TablesS1andS2.docx SupplementaryFigs1and2CAinSVDKitajimaetal2025.tif Cite Share Download PDF Status: Published Journal Publication published 11 Mar, 2026 Read the published version in Acta Neuropathologica Communications → Version 1 posted Editorial decision: Revision requested 26 Nov, 2025 Reviews received at journal 25 Nov, 2025 Reviews received at journal 22 Nov, 2025 Reviewers agreed at journal 19 Nov, 2025 Reviewers agreed at journal 12 Nov, 2025 Reviewers invited by journal 30 Oct, 2025 Editor assigned by journal 22 Oct, 2025 Submission checks completed at journal 19 Oct, 2025 First submitted to journal 13 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":550249,"visible":true,"origin":"","legend":"\u003cp\u003eCarotid artery stenosis and sclerosis severity in clinical stroke. A and B, Violin plots showing the distribution of % stenosis and sclerosis in left and right CAs and the mean% in both arteries. There were no differences in mean % stenosis or sclerosis between left and right arteries (\u003cem\u003eP\u003c/em\u003e\u0026gt;\u003cem\u003e0.05\u003c/em\u003e). C, Box plots and proportions of subjects with mild, moderate and severe stenosis among those with stroke and those without. D, Box plots and proportions of subjects with mild, moderate and severe sclerosis among those with stroke and those without. *** \u003cem\u003eP=0.001\u003c/em\u003e against clinical stroke group. There were more cases with severe stenosis and sclerosis in subjects with clinical stroke (\u003cem\u003eP=0.001\u003c/em\u003e).\u003c/p\u003e","description":"","filename":"Figure1CAinSVDKitajimaetal2025.png","url":"https://assets-eu.researchsquare.com/files/rs-7852432/v1/834254e9d0e3d4612bb2a7fa.png"},{"id":95797195,"identity":"c36325e4-d33a-44e5-8845-a24c3998daf0","added_by":"auto","created_at":"2025-11-13 08:01:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1393092,"visible":true,"origin":"","legend":"\u003cp\u003eTypes of carotid artery pathology in post-stroke patients. \u0026nbsp;A-I, Representative images show normal and five types of artery wall lesions in internal carotid artery (ICA) causing various degrees of stenosis: intimal thickening (IT) (B-C), thin fibrous cap (D-E), thick fibrous cap (F), fibrocalcific (G-H) and other (I) in post-stroke patients of 75-85 years of age. \u0026nbsp;Thin arrows show the cap lesions where the thick arrow heads (H and I) show ruptured cap (H) and intact intima (I). ICAs in G and H (stars) demonstrate examples of complicated lesions with necrotic core (NC) with calcified plaques and cholesterol clefts (star). I, cholesterol crystals (star) often found in vicinity of foam cells under a thick fibrous cap. \u0026nbsp;ICA sections stained with H\u0026amp;E (A-F, I) and Eosin Van Giessen (G-H). J-L, Proportions of types of lesions in the left and right ICAs in the total sanple (J), the clinical stroke (K) and no stroke (L) samples. Intimal thickening, fibrocalcific and thin fibrous cap lesions were the most common with no differences between left and right ICAs. Abbreviations: COL, collagen; L, lumen; LP, lipid pool; M, media. Scale bar represents 1 mm (A-H) and 200µm (I).\u003c/p\u003e","description":"","filename":"Figure2CAinSVDKitajimaetal2025.png","url":"https://assets-eu.researchsquare.com/files/rs-7852432/v1/a3dc34cad3709126627ed64e.png"},{"id":95665126,"identity":"9c77345b-058e-487c-ab4e-0845d9f2ef74","added_by":"auto","created_at":"2025-11-11 16:43:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3311503,"visible":true,"origin":"","legend":"\u003cp\u003eInternal carotid artery wall changes associated with atheromas and inflammation. A-D, Immunohistochemical and immunofluorescence staining shows distribution of α-SMA, CD68, HSP27, and isoDGR deposits in the wall of carotid arteries. A, Disbanded smooth muscle cells in the intima. CD68 macrophages, HSP27 and isoDGR (degenerative protein modifications, DPMs) in the walls of the vasa vasorum. \u0026nbsp;F-I, Images show high inflammatory activation of CD68 macrophages associated with DPMs in the ICA wall. \u0026nbsp;\u0026nbsp;Abbreviations: \u0026nbsp;isoDGR, isoAsp-Gly-Arg motifs; HSP27, heat shock protein 27. Scale bar represents 100 μm for A-I.\u003c/p\u003e","description":"","filename":"Figure3CAinSVDKitajimaetal2025.png","url":"https://assets-eu.researchsquare.com/files/rs-7852432/v1/928fcdf3a0c75257211b828b.png"},{"id":95797668,"identity":"c579cd1f-2de7-4cea-9fa2-9ced397def96","added_by":"auto","created_at":"2025-11-13 08:09:24","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":327202,"visible":true,"origin":"","legend":"\u003cp\u003eBrain SVD pathology and total number of lesions in relation to carotid artery pathology. A and B, Violin plots showing vascular SVD pathology scores and vascular lesions separated into mild, moderate and severe groups of CA pathology. C, Violin plots showing vascular lesions associated with the anterior and posterior circulations. ***\u003cem\u003eP=0.001\u003c/em\u003eagainst anterior circulation (C). D, Proportions of types of lesions in the whole sample of cerebral arteries. Intimal thickening was the most common type of artery change. *** \u003cem\u003eP=0.001\u003c/em\u003eagainst mild (MildVL) or moderate (ModVL) in CA stenosis and CA sclerosis groups (A-B). Abbreviations: CA, carotid artery; Mod, moderate; Sev, severe; St, stenosis; SVD, small vessel disease; VL, number of vascular lesions; VS, vascular SVD pathology scores.[9]\u003c/p\u003e","description":"","filename":"Figure4CAinSVDKitajimaetal2025.png","url":"https://assets-eu.researchsquare.com/files/rs-7852432/v1/00d239e93d89964ff3be7c95.png"},{"id":95665132,"identity":"bc8164c3-cafd-43a3-9739-6eafc124ba7f","added_by":"auto","created_at":"2025-11-11 16:43:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":884646,"visible":true,"origin":"","legend":"\u003cp\u003ePie charts showing location and size of brain infarcts in subjects with mild, moderate and severe internal carotid artery (ICA) stenosis. \u0026nbsp;A, Distribution of infarcts in five different brain regions: cortex, white matter (WM), basal ganglia and thalamus (BG), brainstem (BS) and cerebellum. The majority of infarcts were observed in the cerebral cortex with decreasing order in BG and WM across moderate or severe ICA stenosis subjects. \u0026nbsp;B, Distribution of brain infarcts size in patients with mild, moderate and severe ICA stenosis. Majority of the infarcts were \u0026lt;5 mm regardless of the degree of ICA stenosis. C, Size distribution of WM infarcts in subjects with mild, moderate and severe ICA stenosis. More than 70% of the infarcts in the WM in all three groups were of \u0026lt;5 mm in size and those in subjects with severe ICA stenosis had proportionally more small lesions e.g. 91%. \u0026nbsp;Linear regression analysis showed severity of ICA stenosis was related to small WM lesions (F3.1, df 50, \u003cem\u003eP\u0026lt;0.048\u003c/em\u003e).\u003c/p\u003e","description":"","filename":"Figure5CAinSVDKitajimaetal2025.png","url":"https://assets-eu.researchsquare.com/files/rs-7852432/v1/788265508213731068ddbeac.png"},{"id":104739562,"identity":"923cd3bc-64f9-4178-b035-0e82638112b6","added_by":"auto","created_at":"2026-03-16 16:09:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6822047,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7852432/v1/4fc87a78-2725-43ec-9357-feb817f88c1f.pdf"},{"id":95665125,"identity":"5e55f8d8-7b67-4534-bdf8-f702c1d1018b","added_by":"auto","created_at":"2025-11-11 16:43:58","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":42041,"visible":true,"origin":"","legend":"","description":"","filename":"CAcerebralSVDandDementiaKitajimaetal2025TablesS1andS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7852432/v1/6f0d69651e33d1e7530d393c.docx"},{"id":95665130,"identity":"26815e12-25ec-4c57-b8a9-253b155adad5","added_by":"auto","created_at":"2025-11-11 16:43:58","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2135432,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigs1and2CAinSVDKitajimaetal2025.tif","url":"https://assets-eu.researchsquare.com/files/rs-7852432/v1/c4a0548c99fb5ba43107495a.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Carotid Arteries in Cerebral Small Vessel Disease and Dementia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCarotid artery disease (CAD) is a well-recognized causes of large vessel stroke. Population based studies reported that the age-standardised incidence rates of ischemic stroke subtypes due to large-artery atherosclerosis is approximately 15 per 100,000 persons [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This accords with the annual rate of first-ever and recurrent stroke attributed to extracranial internal carotid artery (ICA) as 13.4 (11.4\u0026ndash;15.4) per 100,000 persons [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Carotid intima-medial thickness and carotid atherosclerotic plaques are also acknowledged as early and measurable risk factors for incident stroke and cerebrovascular events.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. ICA stenosis classified as mild to moderate according to ECST or NASCET criteria is generally considered haemodynamically insignificant, and carotid endarterectomy (CEA) offers little to no clinical benefit in these cases. However, severe ICA stenosis is associated with a substantially increased risk of stroke, thereby warranting vascular intervention such as CEA.[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] to reduce risk of stroke in both symptomatic and asymptomatic patients [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCAD or carotid artery stenosis is also associated with markers of cerebral small vessel disease (SVD) such as white matter (WM) changes and lacunar infarcts [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Thus, CAD may promote global hypoperfusion [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], cognitive impairment [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] and vascular dementia (VaD) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. However, there are limited studies on the relationship or interaction between CAD and intracranial brain vascular or parenchymal changes. In this study, we assessed the spectrum of CAD in relation to cerebral SVD pathology in prospectively collected carotid arteries from two cohorts namely the Cognitive Function After Stroke (CogFAST) and Newcastle prospective dementia studies where we had clinical, neuroimaging and pathological evidence of cerebral SVD.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and subjects\u003c/h2\u003e\u003cp\u003eDemographic, clinical and pathological findings in the subjects of the study are given in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Study subjects were participants of the Newcastle longitudinal prospective dementia series [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and the CogFAST study [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. They had a clinical diagnosis of stroke without dementia, vascular dementia, Alzheimer\u0026rsquo;s disease, mixed dementia (Mixed), Lewy body dementia or Parkinson\u0026rsquo;s disease with dementia but all had some evidence of cerebral SVD. Age-matched control subjects aged\u0026thinsp;\u0026gt;\u0026thinsp;70 years were either part of previous prospective studies or based on unrelated brain donations to the Newcastle Brain Tissue Resource (NBTR). They were included as controls if they had not been diagnosed with cognitive impairment or any neurological or psychiatric illness. Ethical approval and permissions for this study using donated human brains was granted by the Newcastle and North Tyneside 1 Research Ethics Committee and facilitated by the NBTR. Permission for use of brains for post-mortem research was also granted by consent from the participants themselves, next-of-kin or family member. Brain tissues were retained in and obtained from the NBTR.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic details of carotid artery cases in relation to clinical stroke, brain infarcts and dementia\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal No. of Cases\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eClinical Stroke\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo Stroke\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSignificance*\u003c/p\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e value)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e159 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e104 (65.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55 (34.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85.0\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86.6\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e82.0\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Range (min-max)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38 (63\u0026ndash;101)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (68\u0026ndash;99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38 (63\u0026ndash;101)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex: (Men %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.104\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDementia (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.620\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBrain Weight (g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1228\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1238\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1210\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.442\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBrain Infarction (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e77.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e96.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeuropathological Findings\u0026dagger;\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNSP (control %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCerebrovascular (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary Neurodegenerative (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMixed Pathology (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCAD pathology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICA Stenosis (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56.1\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61.3\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48.5\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICA Sclerosis (SI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.346\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.386\u0026thinsp;+\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.290\u0026thinsp;+\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo. of ICA Lesions\u0026Dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo apparent lesion (L/R)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4/7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11/10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePathological Intimal Thickening (L/R)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48/45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24/28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFibrocalcific (L/R)\u0026Dagger;\u0026Dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41/47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28/25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13/22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFibrous Cap 1 (L/R)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37/37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24/22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13/15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFibrous Cap 2 (thin) (L/R)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13/9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther Occlusion e.g. thrombus (L/R)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2/1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2/1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0/0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eValues are shown as mean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SEM or % of total lesions otherwise specified. *Statistical significance between variables with and without clinical stroke was evaluated by ANOVA, post-hoc tests, independent t-test or Pearson Chi-square where applicable, variances were determined to be equal unless otherwise stated. \u0026dagger;Mean ages (years\u0026thinsp;+\u0026thinsp;SEM) of men and women in the total sample were 83.4\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.8 and 87.0\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.8 \u003cem\u003e(P\u0026thinsp;=\u0026thinsp;0.001)\u003c/em\u003e. \u0026dagger;\u0026dagger;Neurodegenerative pathologies included Alzheimer\u0026rsquo;s disease, dementia with Lewy bodies, limbic age-related TDP-43 encephalopathy (LATE), Huntington\u0026rsquo;s disease, progressive supranuclear palsy, multiple system atrophy, and mitochondrial disorder, any of which could be the cause of clinical dementia. \u0026Dagger;Number of ICA lesions in the left (L) and right (R) segments. Different lesion types were greater in the left ICA than in the right ICA in stroke patients \u003cem\u003e(P\u0026thinsp;=\u0026thinsp;0.01)\u003c/em\u003e. \u0026Dagger;\u0026Dagger;Greater number of fibrocalcific lesions in the stroke cases. Abbreviations: CA, carotid artery; CAD, carotid artery disease; ICA, internal carotid artery; L, left; No., number; NSP, no significant pathology; R, right; SI, sclerotic index.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePost-mortem Carotid Arteries and Brain Tissues\u003c/h3\u003e\n\u003cp\u003eSamples of the right and left ICAs were taken at 4 mm distal to the level of the carotid bifurcation. For quantitative analysis, ten-\u0026micro;m thick serial sections cut from paraffin embedded transverse ICA blocks and CAs blocks were stained with Haematoxylin and Eosin (H\u0026amp;E).\u003c/p\u003e\u003cp\u003eBrains were sampled bilaterally and assessed in accordance with the Newcastle brain dissection protocol. Standardised protocols were used for microscopic and macroscopic pathology assessment [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Briefly, macroscopic infarcts were recorded by visual inspection during dissection, and subsequently their presence was confirmed by microscopy. The size and total number of infarcts (designated as vascular lesions) in both hemispheres in the cortex, basal ganglia, thalamus, white matter, brainstem and cerebellum were recorded as follows: \u0026lt;5 mm, 5\u0026ndash;15 mm, 16\u0026ndash;30 mm, 31\u0026ndash;50 mm and \u0026gt;\u0026thinsp;51 mm. H\u0026amp;E stain was used for neuropathological assessment including vascular pathology scores to confirm SVD pathology. In addition to the total number, vascular lesions in the anterior and posterior circulation territories as well as cortical and subcortical regions were determined for each case. WM scores (0\u0026ndash;3) were determined as described previously based on the degree of demyelination and vascular pathology [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eCarotid and Cerebral Artery Pathologies\u003c/h3\u003e\n\u003cp\u003eHistopathological evaluation of internal carotid artery was conducted using standard tinctorial stains such as H\u0026amp;E. Carotid artery disease (CAD was categorized using a previously established classification system [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] with additional adherence to recent observations on calcification of artherosclerotic plaques [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. CAD was grouped into five subtypes consisting of intimal thickening, fibrocalcific, fibrous C1 (thick), fibrous C2 (thin) and other which included thrombi. CAD pathology was rated by two investigators (TMP and RNK) with \u0026gt;\u0026thinsp;90% agreement. Further cellular characterization of the artery vessel walls and atheromatous material was undertaken by immunostaining via standardised methods in 10 post-stroke cases with varied stenosis for α-smooth muscle actin (α-SMA), CD68-positive macrophages and isoAsp-Gly-Arg (isoDGR) degenerative protein modifications (1:200-1:1000 dilutions) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eICA including the circle of Willis, basilar, anterior and middle cerebral arteries were examined for the degree of stenosis and assigned scores of 0 to 3 for none, mild, moderate and severe. Total intracerebral artery scores were calculated as an average of all the cerebral artery scores.\u003c/p\u003e\u003cp\u003eCarotid artery stenosis was categorized into mild, moderate and severe based on modifications of the ultrasound and angiographic methods used in the European Carotid Surgery Trial (ECST) and the North American Symptomatic Endarterectomy Trial [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Given our previous histopathological study[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], we ascertained that moderate stenosis was in range 50\u0026ndash;75% matching the ECST low moderate category, while the severe stenosis (\u0026gt;\u0026thinsp;75%) matched the combined ECST high moderate and severe categories. Following this paradigm we fit all our cases including cerebral arteries into three basic categories of mild (\u0026lt;\u0026thinsp;50%), moderate (50\u0026ndash;75%) and severe (\u0026gt;\u0026thinsp;75%) stenosis (Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e\n\u003ch3\u003eMeasurements of stenosis and sclerosis\u003c/h3\u003e\n\u003cp\u003eWe scanned H\u0026amp;E stained sections with the highest degree of stenosis using a photo scanner (EPSON Perfection V700, Seiko Epson Corporation, Suwa, Nagano, Japan) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Total area of the external margin of the adventitia (S1) and luminal area at the interior margin of the intima (S2) were measured using IMAGEJ software (National Institutes of Health, Bethesda, MD, USA). The % diameter stenosis was calculated using the following formula: % diameter stenosis = (S1-S2)/(S1) \u0026times;100. The % area stenosis of both right and left ICAs were calculated.\u003c/p\u003e\u003cp\u003eTo determine the degree of sclerosis, the length from four different points across the artery were taken between the furthest exterior margin (S1) of the adventitia and the luminal area at its inner margin (S2). In preliminary experiments, we attested the use of this modified method by assessing larger vessels with diameters greater than 1mm. The following formula was used to compute the sclerotic index = (S1-S2)/(S1). The measurement result from four points were averaged to have the final sclerotic index. Sclerotic indices were computed from both the left and right ICAs, and a mean value was then calculated. All data analyses were performed by three investigators (EK, AS, YH) blinded to case identities.\u003c/p\u003e\n\u003ch3\u003eNeurodegenerative Pathology Assessment\u003c/h3\u003e\n\u003cp\u003eGallyas and Bielschowsky\u0026rsquo;s silver impregnation and tau immunohistochemistry (AT8 for pTau at 1:1000 dilution) were used to assess neuritic plaques and neurofibrillary tangles for the \u0026lsquo;Consortium to Establish a Registry for Alzheimer\u0026rsquo;s Disease\u0026rsquo; plaque score and \u0026lsquo;Braak and Braak\u0026rsquo; neurofibrillary tangle staging. Pathological diagnosis of VaD was assigned, if there was clinical evidence of dementia using the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition and relevant vascular pathology in the general absence of neurodegenerative pathology, that is, Braak staging I-IV. Severity of cerebral amyloid angiopathy (CAA) was assessed using a four-point scale as described previously [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. α-synuclein was the pathological alteration in Parkinson's disease and dementia with Lewy bodies dementia [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Total SVD pathology scores were determined out of a total of 20 according to Deramecourt et al [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. To assess glial cell responses, immunohistochemical staining was undertaken in sections from the frontal deep WM. Antibodies to GFAP and CD68 were used as respective markers of astrocytes and microglia or macrophages, with the percent area quantified as described previously [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eRaw data were analysed using GraphPad Prism 10 software (Boston, MA, USA) and IBM SPSS Statistics Version 29.0.1.1 (Armonk, NY, USA). Standard descriptive statistics were used to describe the total and CogFAST samples. Unless otherwise stated, data are presented as mean\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003eSEM. The Shapiro-Wilk test was used for normality testing. Bivariate relationships of key characteristics e.g. age, brain weight, degrees of stenosis, sclerosis, vascular pathology scores, number of vascular lesions, etc. were examined using correlation analysis (Pearson\u0026rsquo;s R), Student independent t tests, or analysis of variance (ANOVA) as appropriate. Post-hoc authentication included the Tukey and Bonferroni tests. The percentages of stenosis and sclerotic index were compared between stroke and non-stroke cases. The differences between variables to baseline characteristics were also compared using Pearson\u0026rsquo;s Chi-squared test. In all analyses, a value of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered as statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eClinical stroke, Brain Infarction and Carotid Artery Disease\u003c/h2\u003e\u003cp\u003eThis study was based on clinical and pathological observations in a total of 159 cases for which we had clinical information as well as pathological assessments of the carotid arteries (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Of these, 104 had clinical evidence of stroke with 5% of the cases showing no apparent brain infarction at postmortem (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Unless otherwise specified in the sub-analysis, subsequent analysis involved 140 cases where we had isolated carotid artery samples. We found that clinically defined stroke was associated with older age as was brain infarction on pathological examination (\u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.001\u003c/em\u003e). There were no differences in sex, brain weights or presence of clinical dementia prior to death between the stroke and non-stroke groups (\u003cem\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/em\u003e). The numbers of subjects with dementia in the stroke sample was 50% whereas this comprised 43% in the non-stroke sample (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe first noted that neither the mean percent stenosis nor sclerosis was different between the left and right ICAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and B). In subsequent analysis, we therefore averaged the percent values from left and right ICAs and used these as a single measure for each case. We found that the mean percent stenosis and sclerosis were greater in stroke subjects compared to non-stroke subjects (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and D). In the total sample incorporating both stroke and non-stroke cases (n\u0026thinsp;=\u0026thinsp;140), nearly 50% of the subjects exhibited moderate stenosis of the ICA with the rest as mild (32.7%) and severe (21.4%). The degree of stenosis and sclerosis differed significantly between the clinical stroke and non-stroke cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and D). More than 30% of the stroke cases showed severe stenosis compared to 6% in the non-stroke subjects. Similarly, severe sclerosis was also more common in stroke subjects; but remarkably 70% of the non-stroke samples exhibited moderate degrees of sclerosis in the ICA (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). ICA stenosis and sclerosis measures were strongly related (r\u0026thinsp;=\u0026thinsp;0.925, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) but we also found correlations between clinical stroke and ICA stenosis or sclerosis, in a general linear model controlling for age (F16, df 1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; F 15 df 1, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Thus, stroke patients showed significantly worse ICA stenosis and sclerosis than those without stroke (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) but moderate degrees of sclerosis were a common finding in the ICA irrespective of stroke pathology.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe examined several segments of the common CA, ICA and external CA. We noted atherosclerosis was most frequent in the ICA. Macro- and microscopic examination of both the left and right ICA samples specified five different classic types of changes in the vessel walls (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). More than 90% of the subjects had some type of ICA lesion in these age groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Light microscopy revealed that in general the atheromatous pathology in the ICA was not qualitatively different from that reported in coronary arteries or aortic arches [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. We found intimal thickening to be a common finding. The frequency in the order of the ICA subtypes in the total sample were intimal thickening\u0026thinsp;\u0026gt;\u0026thinsp;fibrocalcific\u0026thinsp;\u0026gt;\u0026thinsp;fibrous cap (thick)\u0026thinsp;\u0026gt;\u0026thinsp;fibrous cap (thin)\u0026thinsp;\u0026gt;\u0026thinsp;other group (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ-L). We also found that there was marginally greater ICA pathology in the left than the right ICA. In addition, stroke subjects had more proportions of pathological lesions in both left and right ICAs compared to those without stroke. However, there were substantial proportions of fibrocalcific and fibrous C1 (thick) lesions in both groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and across all confirmed brain pathologies including vascular, neurodegenerative and mixed (Supplementary Fig.\u0026nbsp;2). Ruptured atheromatous lesions were rare with a frequency of \u0026lt;\u0026thinsp;5% in the total sample suggesting there may be limited contribution by ICAs to thromboembolic strokes in the brain.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn order to identify specific changes within the intima and the atheromas in the vessel walls, we immunostained segments of the ICA for cellular inflammatory responses (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). We found typical frequent disarray of α-SMA positive cells within the vessel wall matrix. Several cells were positive for HSP-27, which we determined as typical foam cells. Numerous CD68 positive macrophages were also evident particularly in the medial layers in all the cases with fibrocalcific or fibrous cap lesions. We noted concentric patterns of cells depicting proliferation within the vasa vasorum. There was occasional evidence of haemorrhage within the atheromas (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD) indicating bleeding from weak vasa vasorum. In addition, as we showed recently [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] there was extensive accumulation of isoDGR-modified (deaminated) proteins [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] in the vessel walls overlapping with CD68-positive macrophages. This indicated an active and sustained inflammatory reaction ongoing within the ICA atheromas, potentially exacerbated by the accumulation of isoDGR-modified proteins [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eRelationship between ICA Pathology and Cerebral SVD Lesions\u003c/h2\u003e\u003cp\u003eWe next determined whether ICA stenosis influenced parenchymal pathology characterised by cerebral SVD (Supplementary Tables\u0026nbsp;1 and 2). Linear regression analysis showed that ICA stenosis were positively related to both SVD pathology scores and the total number of vascular lesions (Supplementary Table\u0026nbsp;1). We further noted that subjects with both severe stenosis and sclerosis exhibited greater numbers of vascular lesions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and B). We found subcortical rather than cortical vascular lesions to be related to severity of stenosis (Supplementary Table\u0026nbsp;1). Remarkably, WM scores (of vascular aetiology) were related to both ICA stenosis and sclerosis (Supplementary Table\u0026nbsp;1). This indicates ICA pathology likely impacts on the integrity of the deep WM.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn terms of brain vascular pathology, we observed that cerebral vascular systems within the circle of Willis, basilar and smaller (anterior or middle) cerebral arteries characterised by any atheromatous disease or subtype vessel wall lesions were all related to both ICA stenosis and sclerosis severity (Supplementary Table\u0026nbsp;1). After averaging scores for all cerebral arterial pathology, we showed that the total intracranial artery scores were positively correlated with ICA stenosis and sclerosis (Supplementary Table\u0026nbsp;1). There were more vascular lesions in the anterior circulation compared to the posterior circulation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC; Supplementary Table\u0026nbsp;1). Our results indicated that CAD in the ICAs increased risk of atheromatous diseases in the cerebral arteries within the anterior circulation. It was also observed that intimal thickening was the most common lesion in cerebral vessels in this age group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eCarotid Artery and SVD Pathology in CogFAST\u003c/h2\u003e\u003cp\u003eIn an attempt to elucidate more specific substrates within stroke subjects, we assessed whether the severity of ICA stenosis, as mild, moderate or severe, was associated with a number of clinical and pathological variables specifically in the CogFAST study cases (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Of the 80 subjects we assessed, 23% exhibited mild stenosis, 38% had moderate stenosis and 39% had severe stenosis prior to death. As for the total sample, age, sex and brain weights did not different significantly between the groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). We found that at least 50% had a diagnosis of dementia in each group. While final Mini-Mental State Examination (MMSE) and Cambridge Cognitive Examination (CAMCOG) cognitive scores tended to be reduced in the severe groups we found that they were only significantly reduced when the moderate-severe stenosis scores were combined and compared to the mild stenosis group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). CAMCOG scores in the severe group were lower than the mild group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic details of CogFAST cases in relation to severity of CAD and other pathologies\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSevere\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSignificance\u003c/p\u003e\u003cp\u003e(\u003cem\u003eP\u003c/em\u003e value)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of subjects (% of n\u0026thinsp;=\u0026thinsp;80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31 (39%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years), mean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SEM (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85.1\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.2 (76\u0026ndash;95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86.2\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.1\u003c/p\u003e\u003cp\u003e(71\u0026ndash;98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88.2\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.1(75\u0026ndash;99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.156\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex (male %)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e61%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.373\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBrain Weight (g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1247\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1204\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1271\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.179\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eClinical features\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDementia (PSD) (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.876\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMMSE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.250\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCAMCOG*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.233\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType 2 Diabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.771\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypercholesterolemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.290\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo of VRFs (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (0\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (0\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.108\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAPOE\u003c/b\u003e \u003cem\u003eallele Frequencies\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAPOE ε4 (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAPOE ε3 (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAPOE ε2 (%)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePathology markers\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICA External Diameter, mean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SEM cm‖\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.628\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.686\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.728\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e% ICA stenosis, mean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SEM#\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40.4\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58.6\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e74.3\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e% ICA sclerosis, mean\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;SEM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.247\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.370\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.482\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBraak stage, mean (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.8 (0\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.0 (0\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.8 (0\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCERAD score, mean (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.0 (0\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.2 (0\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.1 (0\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eα-synuclein, mean (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.7 (0\u0026ndash;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.7 (0\u0026ndash;14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCAA score, mean (range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.0 (0\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.1 (0\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.1 (0\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSVD Pathology Score\u0026Dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.6\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.0\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.3\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.589\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal cerebral vascular lesions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.9\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.8\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.3\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.733\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntracranial artery score\u0026Dagger;\u0026Dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.7\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.6\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.7\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.104\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWM Scores\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.6 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.9 (2\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.8 (1\u0026ndash;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.239\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWM GFAP (% area)\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.82\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.91\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.30\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026plusmn;\u003c/span\u003e\u0026thinsp;0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWM CD68 (% area)\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.61\u0026thinsp;+\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.70\u0026thinsp;+\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.82\u0026thinsp;+\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.264\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eValues represent mean\u0026thinsp;+\u0026thinsp;SEM for number of subjects shown. The range of severity scores in the circle of Willis, basilar artery and cerebral arteries was 1.1\u0026ndash;1.7. There were no differences between mild, moderate and severe stenosed subjects (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.250). \u0026Dagger;Post-stroke dementia (PSD) defined by DSM IV, IVR or V criteria was not associated with severity of CA stenosis or sclerosis (cf. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). ‖Represents the mean of left ICA and right CA, there were no differences between left and right ICA external diameters (\u003cem\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05)\u003c/em\u003e. \u0026dagger;ANOVA and post-hoc tests showed that GFAP but not CD68 immunoreactivity was increased in the ICA severe stenosis group (n\u0026thinsp;=\u0026thinsp;35 total in mild, moderate and severe groups, F3.3, df2, P\u0026thinsp;=\u0026thinsp;0.045). Abbreviations: ANOVA, analysis of variance; CA, carotid arteries; CERAD, Consortium to Establish a Registry for Alzheimer\u0026rsquo;s Disease; Braak, Braak NFT stage; CAA, cerebral amyloid angiopathy; ICA, internal carotid artery; PSD, post-stroke dementia; CBF, Cerebral blood flow; PSD, post-stroke dementia; VRF, vascular risk factor.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThere was no evidence for differences in frequencies or number of vascular risk factors between the groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, while there were no cases of hypercholesterolemia in the mild stenosis group, we noted that 14% and 17% of moderate and severe groups exhibited this vascular risk factor. There were also no differences in the frequencies of \u003cem\u003eAPOE ε2, ε3\u003c/em\u003e or \u003cem\u003eε4\u003c/em\u003e alleles between the groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eAssessment of relevant pathological indices showed that mean values of both ICA stenosis and sclerosis increased with increasing stenosis severity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, the distribution of vascular pathology or neurodegenerative disease markers was not different between the groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The prevalence of moderate-severe CAA pathology (approximately 24%) across all mild, moderate and severe ICA stenosis groups remained almost unchanged (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). We also noted that WM pathology scores were almost similar in the mild, moderate and severe groups. However, ANOVA showed that frontal WM GFAP but not CD68 immunoreactivity was significantly increased in severe stenosis subjects relative to the mild stenosis group (P\u0026thinsp;=\u0026thinsp;0.045).\u003c/p\u003e\u003cp\u003eIn further analysis, we assessed the location and size of the lesions in the three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These lesions were characterised as class II per original Newcastle classification system. Irrespective of the degree of ICA stenosis, we found that the greatest numbers of infarcts (range 42\u0026ndash;51%) were in the cortex whereas the basal ganglia and thalamus contained the second highest numbers of infarcts (range 23\u0026ndash;30%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The cerebellum had the least numbers of lesions; although there were significantly more cerebellar infarcts in the mild stenosis compared to the moderate and severe stenosis groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In terms of the size, by far the majority of stroke lesions were small, \u0026lt;\u0026thinsp;5 mm in ranging from 70 to 80% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). There were no overall differences in the distributions of size of infarcts between the mild, moderate and severe stenosis groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Further scrutiny of the data showed that by far the majority of the smallest infarcts (\u0026lt;\u0026thinsp;5mm), up to 91% in the WM were evident in the group with severe stenosis. Linear regression analysis indicated that the numbers of smallest lesions in the WM but not in the cortex or basal ganglia and thalamus (BG) were related to the severity of ICA stenosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC and legend).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur clinicopathological analysis of a large sample of ICAs confers several imperative findings and particularly throws light on the consequences of extracranial ICA stenosis on cerebral SVD. We first found that there was increased ICA stenosis and sclerosis in clinically diagnosed stroke cases. This is perhaps not surprising but our findings strongly suggest that the severity of ICA stenosis influences the burden of cerebral SVD pathology; particularly in terms of vascular lesion number, collective SVD pathology scores as well as subcortical structures including the WM, which may be more targeted than other brain regions. It is of particular note that severity of both ICA stenosis and sclerosis was correlated with WM pathology and that mostly SVD type small lacunar lesions were present in the WM. These observations are consistent with clinical studies [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and reinforce that not all WM changes evident, such as white matter hyperintensities upon MRI of vascular origin, are solely explained by intracranial SVD. A systematic review followed by meta-analyses suggested that WM ipsilateral and contralateral to CAD site is associated with changes in the apparent diffusion coefficient (ADC), fractional anisotropy (FA), and mean diffusivity (MD) values [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Consistent with our findings, this report indicates that CAD is also associated with quantifiable white matter microstructural damage.\u003c/p\u003e\u003cp\u003eCerebral SVD types of change could be promoted by various mechanisms including altered haemodynamics or perfusion due to ICA occlusion induced by growing yet stable atherosclerotic plaques or a thrombus developing on an atheroma. Thus cerebral SVD events or deep watershed infarcts may not only result from hemodynamic impairment [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] but also from microemboli alone through plaque inflammation detected by FDG PET and the presence of transcranial Doppler microemboli signals [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. It is also plausible that macro-fragments from an atheroma may embolize or a thrombus may break off, leading to artery-to-artery embolism [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] or there is cardiogenic microembolism due to atrial fibrillation [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. As we found mostly intact fibrous caps in ICAs in our cases, we would surmise that thromboembolic events of ICA origin are rare to cause strokes in the CogFAST or the total cohort. Irrespective, it needs to be emphasized that effects of antithrombotic agents on embolic signals should still serve as a marker for their efficacy in preventing stroke recurrence [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSecondly, SVD and WM infarction is also associated with the risk of dementia [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Although we did not observe a clear relationship between severity of stenosis and dementia possibly because dementia diagnosis is made as a nominal measure beyond a certain threshold, we did observe that both MMSE and particularly CAMCOG scores worsened with severity of ICA stenosis in the CogFAST cases. However we did not have records of the MMSE and CAMCOG scores for the whole cohort. Furthermore, we did not find any sex or age-related differences in comparison to ICA stenosis or sclerosis in our sample, yet subjects with stroke were still older in age. Previous clinical studies showed that the prevalence of severe CA stenosis was 3.1% (1.7% to 5.3%) in men aged 80 years or older and 0.9 (0.3% to 2.4%) in women [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThirdly, our findings suggest ICA stenosis and pathology are associated with the lesions in the anterior circulation and that fibrocalcific lesions are more common. It has been suggested that atherosclerotic calcification initially occurs as microcalcifications [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] and results in larger dense calcification as evident in our cases. There also appears to be a predilection for the left ICA to accumulate distinct types of atheromatous lesions. Our results therefore agree with population based imaging studies showing that the carotid plaques are associated with infarction in the anterior circulation [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAtherosclerosis is a systemic inflammatory disease that associates with several acute cardiovascular complications triggered by atherosclerotic plaque rupture, which primarily manifests as stroke or myocardial infarction. We found that while there were no qualitative differences between subtypes of atheromatous lesions described previously in cardiovascular arterial systems [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], we found disarray of both αSMA positive cells and other features including foam cells, collagen and lipid clefts. However, we showed that the inflammatory cellular response (demonstrated by CD68-positive macrophages) is concomitant with accumulation of degenerative protein modifications in extracellular matrix proteins such as fibronectin, laminin, and collagens [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The isoDGR-motif in the modified proteins is a ligand that specifically binds to integrins receptors, thus promoting immune cells recruitment and sustained inflammation, as detected by isoDGR-specific antibody [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. These observations are consistent with the varied transcriptomic and epigenomic characteristics of human carotid atherosclerotic plaques. A previous single-cell RNA and single-cell ATAC sequencing study identified 14 distinct cell populations including endothelial cells, smooth muscle cells, mast cells, B cells, myeloid cells and T cells in multiple cellular activation states and interconversions [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Thereby only further emphasising the inflammatory cellular complexity of localised atherosclerotic plaque sites.\u003c/p\u003e\u003cp\u003eFourthly, we found evidence that severe ICA stenosis influences vessel wall pathology or stenosis in the intracranial arterial system incorporating branches of the circle of Willis, anterior or middle cerebral arteries and the basilar artery. Thus how might ICA stenosis and sclerosis affects cerebral vascular function? It is plausible that carotid arterial walls alter the vascular haemodynamics and endothelial cell function. In turn endothelium dysfunction can reduce vasomotor reactivity to impede normal flow leading to chronic or transient cerebral hypoperfusion particularly in the deeper distal structures including the WM. Relative to this, blood flow in the ICA without stenosis has been estimated to be 418 ml/min but with mild, moderate, and severe stenosis, it was calculated respectively to be 309 ml/min, 229 ml/min, and 117 ml/min [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Similarly, another study showed that with the increase in the severity of ICA stenosis, the ipsilateral blood flow reduced to 197 mL/min when stenosis was 50\u0026ndash;69% and to 130 ml/min i.e. to 25% of normal flow with severe (70\u0026ndash;99%) stenosis. Furthermore, the blood-brain barrier may also be compromised in the chronic hypoperfusion and hypoxic state [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. We propose that intimal thickening within the intracranial (and intracerebral) arteries occurring as a function of age in tandem with changes in the haemodynamics and perfusion possibly exert progressive propagation effects along the arterial branching.\u003c/p\u003e\u003cp\u003eOur study reports several strengths. The main one is that ICA stenosis severity caused by atherosclerotic disease characterised by fibrocalcific and consolidated fibrous lesions is related to cerebral SVD pathology. However, there are some limitations of for the study. Two of these include: 1) we would need a larger sample size to definitively determine the exact impact of ICA stenosis on cognitive function measures; 2) it remains unclear whether ICA stenosis and hence the resulting hypoperfusion influences the deposition of cerebral neurodegenerative pathologies in earlier stages of dementia. A third limitation is would be the use of medications including antiplatelet agents, anticoagulants, statins, and antihypertensives. These were not fully accounted for in the present analysis because the inromation on hand was not complete. In this respect, a potential future direction would be to investigate, particularly among individuals with severe ICA stenosis, whether these medications influence stroke risk, WM pathology, intimal thickening, fibrocalcific changes, or fibrous cap characteristics\u003c/p\u003e\u003cp\u003eIn summary, we provide evidence that severity of ICA stenosis influences the accumulation of cerebral SVD pathology and that subcortical structures including the WM may be more targeted than other brain regions. We also show that ICA atheromas are characterised by various subtypes of lesions among which intimal thickening and fibrocalcific lesions are common with significant presence of inflammation. Whilst extracranial stenosis most proximal to the cerebrum likely impact upon vessel wall health in more distal segments of the cerebral microvasculature.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available on request from the corresponding author. \u0026nbsp;The data are not publicly available due to case privacy or ethical restrictions. The datasets used and analysed for the current study are available on request from the corresponding author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the patients and families for their cooperation in the investigation of this study. \u0026nbsp;We thank the staff of the NBTR, Debbie Lett, Tracy Alder and Philippa Hepplewhite for mobilising the samples and technical assistance.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSources\u0026nbsp;of funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur work is supported by grants from the UK Medical Research Council (MRC, G0500247), Newcastle Centre for Brain Ageing and Vitality (BBSRC, EPSRC, ESRC and MRC, LLHW), and Alzheimer\u0026rsquo;s Research (ARUK). Tissue for this study was collected by the Newcastle Brain Tissue Resource, which is funded in part by a grant from the UK MRC (G0400074), by the Newcastle NIHR Biomedical Research Centre in Ageing and Age-Related Diseases award to the Newcastle upon Tyne Hospitals NHS Foundation Trust, and by a grant from the Alzheimer\u0026rsquo;s Society and ARUK as part of the Brains for Dementia Research Project. \u0026nbsp; LA is supported by the Peninsular NIHR Applied Research Collaboration and the Exeter NIHR Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.\u0026quot;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical\u003c/strong\u003e\u003cstrong\u003eApproval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approvals were granted by local research ethics committees of the Newcastle upon Tyne\u0026nbsp;Foundation\u0026nbsp;Hospitals\u0026nbsp;Trust.\u0026nbsp;Permission\u0026nbsp;for\u0026nbsp;use\u0026nbsp;of\u0026nbsp;brains\u0026nbsp;for\u0026nbsp;post-mortem\u0026nbsp;research\u0026nbsp;was also\u0026nbsp;granted\u0026nbsp;by\u0026nbsp;consent\u0026nbsp;from\u0026nbsp;next-of-kin\u0026nbsp;or\u0026nbsp;family.\u0026nbsp;All\u0026nbsp;the\u0026nbsp;brain\u0026nbsp;tissues\u0026nbsp;were\u0026nbsp;retained\u0026nbsp;in\u0026nbsp;and obtained from the Newcastle Brain Tissue Resource.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions (per CreDIT)\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eErika Kitajima: drafting, analysis and acquisition of data\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAshley Suwanda: drafting, analysis and acquisition of data\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDan\u0026nbsp;Jobson: analysis, acquisition\u0026nbsp;of\u0026nbsp;data\u0026nbsp;and\u0026nbsp;editing manuscript\u003c/li\u003e\n \u003cli\u003eLouise Allan:\u0026nbsp;Clinical data\u0026nbsp;analysis and editing the manuscript\u003c/li\u003e\n \u003cli\u003eKian Paydar: \u0026nbsp;generating primary data, analysis and interpretation\u003c/li\u003e\n \u003cli\u003eGan Han: acquisition\u0026nbsp;of\u0026nbsp;data and images\u003c/li\u003e\n \u003cli\u003eKazuo Washida: analysis and\u0026nbsp;acquisition\u0026nbsp;of\u0026nbsp;data\u003c/li\u003e\n \u003cli\u003eMasafumi Ihara: editing the manuscript,\u0026nbsp;interpretation\u003c/li\u003e\n \u003cli\u003ePazhanichamy Kalailingam: acquisition of data and images\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eYoshiki\u0026nbsp;Hase:\u0026nbsp;analysis,\u0026nbsp;interpretation,\u0026nbsp;acquisition\u0026nbsp;of\u0026nbsp;data, editing in manuscript\u003c/li\u003e\n \u003cli\u003eNewman Siu Kwan Sze: editing the manuscript, interpretation and acquisition of data\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTuomo\u0026nbsp;Polvikoski:\u0026nbsp;case\u0026nbsp;diagnosis\u0026nbsp;and\u0026nbsp;acquisition\u0026nbsp;of\u0026nbsp;data\u003c/li\u003e\n \u003cli\u003eRaj\u0026nbsp;N\u0026nbsp;Kalaria:\u0026nbsp;drafting,\u0026nbsp;revising\u0026nbsp;the\u0026nbsp;manuscript\u0026nbsp;and\u0026nbsp;interpretation\u0026nbsp;of\u0026nbsp;data,\u0026nbsp;diagnosing the cases and obtaining funding.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eConflict\u0026nbsp;of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;authors\u0026nbsp;have\u0026nbsp;no\u0026nbsp;disclosures\u0026nbsp;or\u0026nbsp;conflicts\u0026nbsp;of\u0026nbsp;interest\u0026nbsp;in\u0026nbsp;relation\u0026nbsp;to\u0026nbsp;this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read and agreed to the published version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e(1991)MRC European Carotid Surgery Trial: interim results for symptomatic patients with severe (70-99%) or with mild (0-29%) carotid stenosis. 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Stroke 29: 2125-2128 Doi 10.1161/01.str.29.10.2125\u003c/li\u003e\n \u003cli\u003eWardlaw JM, Smith C, Dichgans M (2013) Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging. Lancet Neurol 12: 483-497 Doi 10.1016/S1474-4422(13)70060-7\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"acta-neuropathologica-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anec","sideBox":"Learn more about [Acta Neuropathologica Communications](https://actaneurocomms.biomedcentral.com/)","snPcode":"40478","submissionUrl":"https://submission.springernature.com/new-submission/40478/3","title":"Acta Neuropathologica Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Atherosclerosis, Carotid Artery Disease, Small Vessel Disease, Vascular Dementia, White Matter","lastPublishedDoi":"10.21203/rs.3.rs-7852432/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7852432/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCarotid artery disease (CAD) is a recognised important cause of stroke. However, the relationship between CAD and cerebral small vessel disease (SVD) and dementia remains unclear. \u0026nbsp;We hypothesized that CAD in older individuals significantly affects cerebral perfusion, and leadsto cerebral SVD. \u0026nbsp;We performed a clinicopathological study in patients from the Cognitive Function After Stroke (CogFAST) study and prospectively recruited patients with various dementia diagnoses and evidence of cerebral SVD. In addition to brain tissues, we collected postmortem samples of the internal carotid arteries (ICA) from these cohorts in the Newcastle Brain Tissue Resource. Standard neuropathological examination was performed for diagnosis and assignment of the cases per current diagnostic criteria for vascular and neurodegenerative dementias, which were assessed for the presence of vascular pathology including the degree of stenosis and sclerosis in vascular tissues. \u0026nbsp;We evaluated a total of 159 ICA samples and brain tissues from all cases with evidence of SVD. Severity of ICA stenosis and sclerotic index correlated strongly with both clinical stroke and brain infarction (F15, df 135, \u003cem\u003eP\u0026lt;0.001\u003c/em\u003e). More than 90% of the subjects had one subtype of ICA lesion in the order: intimal thickening \u0026gt;fibrocalcific \u0026gt;fibrous cap (thick) \u0026gt;fibrous cap (thin) \u0026gt;thrombus group with a strong inflammatory reaction in fibrocalcific atheromas. Linear regression analysis showed that ICA stenosis was positively correlated to both SVD pathology scores and total number of vascular lesions (r=0.34, 95% CI 0.18-0.49, \u0026nbsp;\u003cem\u003eP\u0026lt;0.034)\u003c/em\u003e. We found that severity of stenosis was related to anterior circulation involvement and small infarcts in the subcortical structures including the white matter (WM) rather than the cortex. Total intracranial artery scores were correlated with ICA stenosis and sclerosis (r=0.43, 95% CI 0.26-0.56, \u003cem\u003eP\u0026lt;0.001\u003c/em\u003e). In the CogFAST group analysis, the smallest lesions in the WM but not in the cortex or basal ganglia and thalamus were associated with severity of ICA stenosis (r=0.42, 95% CI 0.27-0.56, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). Carotid atherosclerosis promotes cerebral SVD types of change and influences the cerebral arterial system. Our observations also suggest extracranial ICA pathology impacts on the perfusion and integrity of the deep WM.\u003c/p\u003e","manuscriptTitle":"Carotid Arteries in Cerebral Small Vessel Disease and Dementia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-11 16:43:53","doi":"10.21203/rs.3.rs-7852432/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-27T04:47:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-25T22:51:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-22T15:17:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"154939189874638645158906936646047906744","date":"2025-11-19T22:44:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8072760927341679255206007811966706052","date":"2025-11-12T15:52:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-31T03:11:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-22T15:00:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-19T22:40:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Acta Neuropathologica Communications","date":"2025-10-13T21:40:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"acta-neuropathologica-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anec","sideBox":"Learn more about [Acta Neuropathologica Communications](https://actaneurocomms.biomedcentral.com/)","snPcode":"40478","submissionUrl":"https://submission.springernature.com/new-submission/40478/3","title":"Acta Neuropathologica Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d41eabb7-966a-467b-83dc-60e876ba31c0","owner":[],"postedDate":"November 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T16:04:51+00:00","versionOfRecord":{"articleIdentity":"rs-7852432","link":"https://doi.org/10.1186/s40478-026-02250-w","journal":{"identity":"acta-neuropathologica-communications","isVorOnly":false,"title":"Acta Neuropathologica Communications"},"publishedOn":"2026-03-11 16:00:31","publishedOnDateReadable":"March 11th, 2026"},"versionCreatedAt":"2025-11-11 16:43:53","video":"","vorDoi":"10.1186/s40478-026-02250-w","vorDoiUrl":"https://doi.org/10.1186/s40478-026-02250-w","workflowStages":[]},"version":"v1","identity":"rs-7852432","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7852432","identity":"rs-7852432","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}