Intracranial atherosclerotic stenosis (ICAS) is an important cause of ischemic stroke and transient ischemic attack (TIA), which is also associated with increased risks of cognitive impairment and dementia. The prevalence of both asymptomatic and symptomatic ICAS (asICAS and sICAS) is significantly higher in Asian populations than in Western populations. In recent years, substantial new evidence has emerged regarding the epidemiology, diagnosis, assessment, prognosis, and treatment of asICAS and sICAS. The China ICAS Research Group has developed this guideline based on published research and relevant domestic and international guidelines or expert consensus, to further clarify the definition, epidemiology, and prognosis of ICAS and the profiles of high-risk ICAS patients and provide evidence-based recommendations on screening, diagnosis, assessment, and treatment strategies of asICAS and sICAS. For imaging exams, noninvasive and contrast-independent modalities are generally suitable for screening and assessment of ICAS in stroke-free individuals with multiple risk factors as well as for routine exams of stroke patients, while contrast-dependent or invasive imaging methods may be employed for further assessment or guiding treatment decision-making in sICAS patients. In addition, vessel wall imaging is valuable for distinguishing the etiology of intracranial stenosis, particularly in young stroke patients. Multiple imaging modalities or methods are available for the assessment of cerebral perfusion, hemodynamics, and collateral circulation that may meet different needs. Regarding interventions, lifestyle modifications (healthy diet, safe exercise, smoking cessation) are recommended for both asICAS and sICAS patients. For stroke-free individuals with asICAS, controlling vascular risk factor is the primary strategy, while routine aspirin or endovascular treatment for primary stroke prevention is not recommended. For sICAS patients, the cornerstone is intensive medical management, including short-term dual antiplatelet therapy in high-risk patients (such as those with severe luminal stenosis, minor stroke, or high-risk TIA) followed by lifelong monotherapy, aggressive lipid control (targeting low-density lipoprotein cholesterol < 1.8 mmol/L), blood pressure control (<140/90 mmHg), and glycemic control (targeting HbA1c < 7.0%), with structured follow-up to enhance treatment adherence. Endovascular treatment is not recommended for sICAS with mild to moderate luminal stenosis (<70%) but may be considered for carefully selected patients with severe (70-99%), medically refractory sICAS, particularly those with hypoperfusion, with a preference to delay the intervention for more than 21 days after stroke to enhance safety.

Background: Asymptomatic intracranial atherosclerotic stenosis (aICAS) is linked to cognitive impairment, yet the pathogenic pathways remain unresolved. Small-vessel injury and dysfunction of perivascular/glymphatic clearance are leading candidates. We characterized this burden with multiple complementary imaging indicators and integrated plasma biomarkers to evaluate associations with cognition, and examine prognostic value for subsequent decline. Methods: In a multicenter cohort of aICAS patients (n=147) and matched controls (n=68), participants received 3T MRI and a standardized cognitive battery. Imaging markers included diffusion-based glymphatic index (DTI analysis along perivascular space, ALPS), white-matter free water, perivascular-space volume, and white-matter hyperintensity volume, processed with harmonized pipelines. Analyses covered group comparisons, associations with cognitive performance and plasma biomarkers, and structural equation model specified a latent CSVD/Glymphatic Burden to test mediation from an Atherogenic Lipids factor to cognition, Cox models were also used for follow-up decline. Results: Compared with controls, patients showed a lower ALPS index and higher global free water. In subgroup analyses, free water within stenosed perfusion territories was significantly higher in aICAS patients than in normal controls (p<0.05). Within patients, free water was also higher in stenosed compared with non-stenosed territories (p<0.01, Fig 1 ). Across the cohort, a greater glymphatic burden was associated with worse global cognitive performance and deficits in specific domain z-scores, and these associations remained robust after adjustment for demographic covariates ( Fig 2 ). The CSVD/glymphatic burden mediated 58.4% of the adverse effect of atherogenic lipids on MoCA (p=0.010) and correlated with glial fibrillary acidic protein. Furthermore, baseline ALPS index is associated with subsequent cognitive decline (HR<0.01, p=0.025, Fig 3 ). Conclusions: In aICAS, imaging indicators of small-vessel and glymphatic dysfunction were associated with worse cognition. Lipid-related injury exerted an indirect effect through small-vessel/glymphatic pathways, and baseline ALPS predicted near-term cognitive decline. These findings address the unresolved mechanism linking atherosclerosis to cognitive impairment and support a multi-indicator imaging-plus-plasma approach for risk stratification and mechanistic targeting.

Background: Intracranial atherosclerosis (ICAS) encompasses a severity continuum from subclinical plaque to flow-limiting stenosis and stroke. While associated with cognitive impairment and dementia, the stage-specific contribution of the ICAS continuum remains undefined. Methods: This cross-sectional analysis utilized baseline data from a multicenter cohort study. We enrolled patients with radiologically confirmed ICAS and ICAS-free controls. Participants underwent comprehensive assessments, including cognitive evaluation via a comprehensive neuropsychological battery, quantification of plasma Alzheimer’s disease（AD） biomarkers (Aβ42/40 ratio, pTau217, glial fibrillary acidic protein [GFAP], neurofilament light chain [NfL]) using Simoa technology, and evaluation of cerebral small vessel disease (CSVD) burden assessed by a standardized MRI visual rating scale. Results: Among 506 participants (mean age 60±11years; 53.4% male), stratified by ICAS stages: 99 were ICAS-free controls, 84 had asymptomatic ICAS (aICAS) with <50% stenosis, 156 had aICAS with ≥50% stenosis, and 167 had symptomatic ICAS (sICAS) with ≥50% stenosis. The prevalence of cognitive impairment increased progressively across groups: controls (22%), aICAS <50% (35%), aICAS ≥50% (44%), and sICAS (63%). GFAP levels were significantly higher than controls in both aICAS ≥50% (β=11.10; 95% CI, 1.09-21.10) and sICAS (β=14.67; 95% CI, 4.72-24.63). NfL elevation (β=13.51; 95% CI, 10.13-16.90) was observed only in sICAS. Aβ42/40 showed a borderline reduction in sICAS (β=-0.003; 95% CI, -0.005 to 0.00). pTau217 levels were unaltered. CSVD burden increased versus controls in all ICAS groups (aICAS <50%: β=0.53, 95% CI 0.11–0.95; aICAS ≥50%: β=0.56, 95% CI 0.20–0.92; sICAS: β=1.58, 95% CI 1.22–1.94). After adjusting for demographics, vascular risk factors, APOE ε4 carrier status, plasma biomarkers, and CSVD burden, ICAS stage remained independently associated with cognitive impairment (aICAS <50%: OR=2.36, 95% CI 1.13–4.91; aICAS ≥50%: OR=2.78, 95% CI 1.48–5.22; sICAS: OR=4.48, 95% CI 2.31–8.68). Conclusions: The ICAS continuum demonstrates progressive stage-specific associations with cognitive impairment and biomarker profiles, independent of AD pathology and CSVD burden. This supports the use of the ICAS continuum as a framework for defining vascular contributions to cognitive impairment and highlights ICAS severity stages as potential targets for therapeutic intervention.

Background: Hypertension is a primary risk factor for intracranial atherosclerotic stenosis (ICAS), yet the role of circadian blood pressure (BP) patterns, particularly nighttime BP, in ICAS burden and related ischemic events remains unclear. We aimed to investigate the associations of ambulatory BP with ICAS burden and ischemic events. Methods: In this multicenter cross-sectional study, 378 patients with radiologically confirmed ICAS underwent 24-hour ambulatory BP monitoring, magnetic resonance angiography, and high-resolution vessel wall imaging. ICAS burden was categorized as low, moderate, or high based on the number of vessels with ≥50% stenosis or occlusion. Symptomatic ICAS (sICAS) was defined by the presence of ischemic events attributable to ICAS lesions. Logistic regression models were used to evaluate associations between BP parameters and ICAS burden or sICAS. Restricted cubic spline (RCS) analyses assessed potential non-linear dose-response relationships. Results: A total of 301 patients were included in the final analysis. All ambulatory BP parameters were positively associated with ICAS burden after adjusting for cardiovascular risk factors. After mutual adjustment between daytime and nighttime BP, only nighttime SBP and mean arterial pressure (MAP) remained independently associated with ICAS burden. RCS analyses showed significant overall associations for all BP parameters, with non-linear relationships identified for 24-hour MAP and daytime SBP, DBP, and MAP. For sICAS, nighttime DBP and MAP remained independently associated, and all associations were predominantly linear. Conclusions: Nighttime BP exhibits independent dose-response associations with ICAS burden and ischemic events, indicating its potential as a target for risk stratification and management.

INTRODUCTION:The apolipoprotein E ε4 (APOE ε4) allele is a major genetic risk factor for Alzheimer's disease, but its relevance to cognition in intracranial atherosclerosis (ICAS) remains unclear. We investigated the association between APOE ε4 and cognition in ICAS. METHODS:Baseline data from a multicenter cohort were analyzed. Patients with radiologically confirmed ICAS underwent APOE genotyping, plasma biomarker assays, magnetic resonance imaging assessment of cerebral small vessel disease (CSVD) and brain atrophy, and standardized cognitive testing. RESULTS:Among 409 patients (mean age 60 years, 55% male), 16% carried APOE ε4. Carriers showed more frequent cognitive impairment (63% vs 48%), greater stenosis burden, and lower plasma amyloid beta (Aβ)42/40 ratios, whereas other Alzheimer's biomarkers, CSVD burden, and atrophy scores showed no difference. After adjustment, APOE ε4remained associated with cognitive impairment (odds ratio [OR] 1.86). The association was pronounced in women (OR 4.43) but absent in men. DISCUSSION:APOE ε4 is linked to cognitive impairment in ICAS, particularly in women, through mechanisms beyond Alzheimer's pathology. HIGHLIGHTS:In patients with ICAS, cognitive impairment was more prevalent in carriers than in non-carriers. Carriers showed greater stenosis burden and lower plasma Aβ42/40 ratios. After full adjustment (stroke, CSVD, and AD biomarkers), APOE ε4 remained associated with cognitive impairment. Female carriers had substantially higher odds of cognitive impairment.

Background: While the apolipoprotein E ε4 (ApoE4) allele is an established genetic risk factor for Alzheimer’s disease and links to cerebrovascular pathology, its specific impact on cognitive impairment in individuals with intracranial atherosclerosis remains undefined. We sought To investigate whether and how ApoE4 influences cognition in patients with intracranial atherosclerosis. Methods: This cross-sectional analysis utilized baseline data from a prospective multicenter cohort study at nine centers. Four hundred and nine patients with intracranial atherosclerosis (mean age 60 years; 55% male) were enrolled. Cognitive impairment, defined as mild cognitive impairment or dementia, was assessed using a comprehensive neuropsychological battery. ApoE4 carriage, intracranial atherosclerosis severity (via magnetic resonance angiography), plasma Alzheimer’s disease biomarkers (Aβ42/Aβ40, pTau217, GFAP, NfL), and neuroimaging markers (cerebral small vessel disease burden, brain atrophy) were evaluated. Multivariable logistic regression and mediation analyses were performed. Results: ApoE4 carriers had a higher prevalence of cognitive impairment compared to noncarriers (62% vs 48%). After full adjustment (age, sex, education, stroke or transient ischemic attack history, cerebral small vessel disease burden, Alzheimer’s disease biomarkers), ApoE4 carriage was associated with an increased prevalence of cognitive impairment (OR = 2.02; 95% CI, 1.10 to 3.76), This prevalence was stronger in females (OR = 4.90; 95% CI, 1.96 to 13.48). Mediation analysis revealed that the number of vessels with ≥50% stenosis possibly partially mediated the association between ApoE4 carriage and cognitive status (indirect effect: 10%), whereas Alzheimer’s disease biomarkers and cerebral small vessel disease burden did not. Conclusions: ApoE4 carriage is independently associated with increased prevalence of cognitive impairment in ICAS patients, particularly in females. The association was possibly partially mediated by worsening ICAS severity, but not by Alzheimer’s disease or cerebral small vessel disease. ApoE genotyping may help stratify patients with intracranial atherosclerosis for developing targeted interventions.

Background Intracranial atherosclerotic stenosis (ICAS) is a major cause of stroke and cognitive impairment. We evaluated whether nighttime systolic blood pressure (SBP) provides additional information beyond daytime SBP regarding cognition, ICAS burden, and plasma biomarkers in patients with ICAS. Methods In this multicenter cross‐sectional study, patients with ICAS underwent 24‐hour ambulatory BP monitoring, brain magnetic resonance imaging, plasma biomarker assays, and neuropsychological testing. Multivariable models including both daytime and nighttime SBP assessed associations with ICAS burden, cerebral small vessel disease burden, plasma biomarkers, and cognition. Incremental analyses evaluated additional information from nighttime SBP beyond daytime SBP. Structural equation modeling examined patterns of associations among SBP, ICAS burden, NfL (neurofilament light chain), and cognition. Results Among 301 patients, higher nighttime SBP was associated with poorer cognition (per 10 mm Hg, β=−0.139 [95% CI, −0.263 to −0.016]; P=0.028), higher plasma NfL (β=0.162 [95% CI, 0.049–0.275]; P=0.005), and greater ICAS burden (odds ratio [OR], 1.365 [95% CI, 1.090–1.716]; P=0.007) independent of daytime SBP. Among biomarkers, only NfL was consistently associated with nighttime SBP. Incremental analyses supported additional information from nighttime SBP beyond daytime SBP for cognition, ICAS burden, and NfL. In structural equation modeling, the association between nighttime SBP and cognition was more closely aligned with NfL than with ICAS burden. Conclusions In ICAS, nighttime SBP provides additional information beyond daytime SBP for cognition, vascular burden, and neuroaxonal injury. Nighttime SBP and plasma NfL may represent complementary indicators of vascular stress and cognitive vulnerability.

Background:Previous studies have indicated that non-motor symptoms are primary problems in focal dystonia, but limited data are available about cognitive function and their correlation with motor severity in generalized dystonia (GD). Methods:In the present study, we performed a case-control study and enrolled isolated genetic or idiopathic GD patients and age-, sex- and education-matched healthy controls (HC). Clinical characteristics, motor symptoms, psychiatric symptoms, and cognitive performance were assessed in both groups using various standardized rating scales and a comprehensive neuropsychological battery. Group comparisons, multiple linear regression analyses, and correlation analyses were performed, with adjustment for demographic and affective variables and correction for multiple comparisons. Results:Twenty patients with GD and matched healthy controls were enrolled and completed the assessments. Compared with HC, GD patients showed mild impairments, particularly in MoCA, executive function/attention, spatial ability, some tests in memory and similarities while other cognitive function did not differ between patients and HC. After adjustment and multiple comparison correction, MOCA, MOCA, executive function/attention and episodic memory remained the most consistent deficits. Several other cognitive differences were no longer significant after correction. No significant associations were found between cognitive performance and motor severity or disease duration. Cognitive performance did not differ between genetic and idiopathic subgroups or between medication groups. Conclusion:GD is associated with mild and heterogeneous cognitive impairments, with only a subset of deficits remaining robust after adjustment. Cognitive performance appears largely independent of motor severity, disease duration, medication use, and disease etiology.

Intracranial atherosclerotic stenosis is a leading cause of stroke and an increasingly recognized contributor to cognitive impairment and dementia. The mechanisms underlying cognitive dysfunction in intracranial atherosclerotic stenosis remain poorly understood, particularly whether they involve direct vascular brain injury or accelerate neurodegeneration and neuroinflammation. Ultrasensitive plasma biomarkers, including the amyloid-β 42/40 ratio, phosphorylated tau at threonine 217, glial fibrillary acidic protein and neurofilament light chain, offer insights into these processes, but their role in intracranial atherosclerotic stenosis has not been elucidated. We recruited 403 patients with intracranial atherosclerotic stenosis (84 with <50% asymptomatic stenosis, 154 with ≥50% asymptomatic stenosis and 165 with ≥50% symptomatic stenosis) and 98 intracranial atherosclerotic stenosis-free controls across nine centres. Plasma biomarkers were quantified using single-molecule array technology. Cognitive function was assessed with a standardized neuropsychological battery, and multimodal MRI was performed to evaluate infarcts and cerebral small vessel disease burden. Multivariable models examined associations among intracranial atherosclerotic stenosis severity, biomarkers levels, and cognitive impairment. Plasma biomarker levels in patients with asymptomatic stenosis <50% were comparable to those in controls. Glial fibrillary acidic protein was elevated in asymptomatic stenosis ≥50%, while both glial fibrillary acidic protein and neurofilament light chain were increased in symptomatic stenosis. The amyloid-β 42/40 ratio was reduced in symptomatic stenosis ≥50%, whereas phosphorylated tau at threonine 217 was unchanged across groups. In multivariable analyses, none of the plasma biomarkers were significantly associated with cognitive impairment. In contrast, intracranial atherosclerotic stenosis itself was independently associated with cognitive impairment in a graded manner (asymptomatic stenosis <50%: OR = 2.48; asymptomatic stenosis ≥50%: OR = 2.65; symptomatic stenosis: OR = 4.14). These findings indicate that although plasma biomarkers of neurodegeneration and neuroinflammation are altered in advanced intracranial atherosclerotic stenosis, they do not explain the associated cognitive impairment. Instead, cognitive deficits appear to be driven primarily through vascular mechanisms. Our results support reconceptualizing intracranial atherosclerotic stenosis not only as a stroke-prone vascular disorder but also as a covert threat to brain health and cognition. Early identification and aggressive management of intracranial atherosclerotic stenosis, even before conventionally 'significant' stenosis or symptoms, are warranted.

Background: Intracranial atherosclerosis (ICAS) related cognitive impairment has been increasingly recognized, but lacks specific diagnostic tools. We sought to develop and validate a brief cognitive scale for ICAS (BCoS-ICAS). Methods: Patients were enrolled from the Peking Union Medical College Hospital (training cohort, n=609) and 17 tertiary hospitals (validation cohort, n=218) between 2021 and 2025. All underwent comprehensive neuropsychological assessments, 3D-T1 MRI, and plasma biomarker analysis (GFAP, NfL, pTau217). The BCoS-ICAS was derived using a decision-tree machine learning algorithm and partial least squares analysis in the training cohort, then validated in the independent validation cohort. Linear regression models explored associations between the BCoS-ICAS and biomarkers. Results: The BCoS-ICAS includes the Calculation subtest, Auditory Verbal Learning Test (immediate recall and short-delay recall), and Trail Making Test Part A, administered within 15 minutes. It demonstrated superior diagnostic accuracy compared to MoCA and NINDS-CSN in the training cohort (sensitivity, 0.91 [95% CI 0.87 to 0.94]; specificity, 0.82 [95% CI 0.78 to 0.86]; and accuracy, 0.86 [95% CI 0.83 to 0.89]) and external validation cohort (sensitivity, 0.92 [95% CI 0.86 to 0.96]; specificity, 0.85 [95% CI 0.76 to 0.92]; and accuracy, 0.89 [95% CI 0.84 to 0.93]). Scales correlated with total white matter volume (natural algorithm, β 1.282, 95% CI 0.136 to 2.428), plasma GFAP (β -0.003, 95% CI -0.005 to 0.000), and NfL (β -0.004, 95% CI -0.008 to -0.001). Conclusions: The BCoS-ICAS is an efficient 15-minute scale for detecting ICAS-related cognitive impairment, with biological plausibility and potential value for monitoring disease.

Background and purpose: Intracranial arterial stenosis (ICAS) is an important cause of ischemic stroke and is associated with a poor prognosis. Obesity has been reported to be associated with a more favorable prognosis in patients with coronary heart disease, but its impact on ICAS remains largely unexplored. This study aimed to investigate the association between obesity and prognosis in patients with asymptomatic ICAS. Methods: This retrospective cohort study included ICAS patients without stroke history, all of whom had been assessed with transcranial Doppler indicating more than 50% stenosis. Participants were categorized into four groups based on their body mass index (BMI): underweight (BMI<18.5 kg/m 2 ), normal weight (18.5≤BMI<24 kg/m 2 ), overweight (24≤BMI<28 kg/m 2 ) and obese (BMI≥28 kg/m 2 ). The primary outcomes were the occurrence of ischemic stroke and the functional outcomes, which were assessed using the modified Rankin Score (mRS). A poor prognosis is defined as an mRS>2. The association between BMI and prognosis of asymptomatic ICAS was investigated by multivariable analysis. Results: A total of 1248 asymptomatic ICAS patients were included, distributed as follows: 46 underweight, 516 normal weight, 522 overweight, and 164 obese. With a median follow-up of 48 months, the incidence of ischemic stroke was 8.7%, 6.5%, 5% and 1.2% across the underweight, normal weight, overweight, and obese groups, respectively. The poor prognosis rates were 25.6%, 9.5%, 4.7%, and 5.7% in the same respective groups. Multivariable Cox regression analysis revealed that BMI (hazard ratio: 0.87; 95% confidence interval [CI]: 0.79-0.95; p=0.001) was significantly associated with a reduced risk of ischemic stroke, after adjusting for age, sex, cancer status, smoking, alcohol consumption, hypertension, diabetes, hyperlipidemia, cerebral vascular surgery, and the number of ICAS lesions. Logistic regression (odds ratio: 0.85, 95%CI: 0.78 - 0.93, p<0.001) and linear regression (β: -0.03, 95%CI: -0.037 to -0.023, p<0.001) consistently demonstrated a negative correlation between BMI and poor functional outcome after adjustment. Conclusions: The findings suggest the presence of an obesity paradox among patients with ICAS, where obesity is associated with a reduced risk of ischemic stroke and a more favorable prognosis in asymptomatic ICAS patients.

Background: The patterns of neural functional changes induced by chronic hypoperfusion resulting from intracranial arterial stenosis and their relationship to cognitive performance are not yet fully understood, with unilateral asymptomatic middle cerebral artery stenotic-occlusive disease (MCAs/o) serving as an ideal model for investigation. Methods: We established a discovery-validation research pipeline to identify functional abnormalities in the hypoperfused regions of MCAs/o patients and quantify them into a machine learning-based data-driven biomarker, i.e. hypoperfusion-based functional abnormalities (HFA). Pseudocontinuous arterial spin labeling imaging was used to identify hypoperfused regions (HypoR) in the discovery cohort. Functional changes within HypoR, including regional homogeneity (ReHo) and functional connectivity, were analyzed and quantitatively integrated using a logistic regression machine learning model to calculate the HFA after feature extraction. The correlation between HFA and cognitive scores was then assessed, and the findings were validated in the independent cohort (Figure 1). Results: The discovery cohort included 44 MCAs/o patients (LMCAs/o: n=22, age 56±11 years, 13 male; RMCAs/o: n=22, age 49±14 years, 16 male) and 35 matched normal controls (age 52±11 years, 15 male), in which MCAs/o patients showed poorer performance on bilateral hand-grooved pegboard tests (GPT) compared to controls (p<0.05). We identified 45 regions of interest (ROIs) in the stenotic hemisphere with significantly elevated arterial transit time, defining them as hypoperfused areas. We found that MCAs/o patients had increased ReHo(FDR-p<0.05) and reductions in HypoR~non-HypoR connections(FDR-p<0.05), coupled with increased HypoR~HypoR connections(FDR-p<0.05). HFA was then calculated based on functional features, which effectively identified early functional changes in MCAs/o patients(AUC=0.994) and correlated with bilateral GPT(p<0.001) ( Figure 2 ). Validation in an independent cohort(20 MCAs/o, 16 controls) confirmed these findings(AUC=0.948; HFA~bilateral GPT p<0.01, Figure 3 ). Conclusions: Chronic hypoperfusion caused by unilateral MCAs/o can lead to a specific pattern of functional changes characterized by increased local neural activity. The quantified biomarker of this pattern can be used to monitor the decline in cognitive function. Our study provides a foundation for further research into the neural damage caused by chronic hypoperfusion.

BACKGROUND:Asymptomatic intracranial atherosclerotic stenosis (ICAS) is frequently identified in stroke screening programs, particularly in Asian populations. However, the prognosis and management strategies for incidentally detected asymptomatic ICAS in hospital-based, stroke-free populations remain unclear. AIMS:This study aimed to investigate the incidence of symptomatic transition and associated long-term prognostic evolution in this population, providing evidence to inform primary stroke prevention. METHODS:We conducted a prospective cohort study that included 1004 patients with asymptomatic ICAS (⩾50%) screened by transcranial Doppler ultrasound (TCD) between January 2016 and May 2022, with follow-up through August 2023. Using the Fine and Gray competing risk model, we analyzed the incidence of symptomatic transition, defined as a first-ever ischemic stroke or transient ischemic attack occurring within the ICAS territory. Post-transition outcomes, including recurrent stroke, major adverse cardiovascular events (MACE), disability (modified Rankin Scale score > 2), and patient-reported cognitive decline (Everyday Cognition-12 score ⩾ 2), were evaluated by comparative analysis. RESULTS:Over a median follow-up of 3.7 years (IQR 2.4-5.2), 43 (4.3%) patients with asymptomatic ICAS experienced a symptomatic transition under routine clinical surveillance, yielding a 5-year cumulative transition rate of 5.6%. After adjusting for potential confounders, hypertension (hazard ratio (HR) 3.33, 95% CI 1.25-8.87) and hyperlipidemia (HR 2.71, 95% CI 1.28-5.74) were independent predictors of the transition. Through extended follow-up, post-transition risks significantly increased for ischemic stroke (HR 3.37, 95% CI 1.17-9.68), MACE (HR 4.48, 1.83-10.99), disability (odds ratio (OR) 4.80, 2.17-10.64), and patient-reported cognitive decline (OR 3.43, 1.19-9.94). CONCLUSIONS:Asymptomatic ICAS detected by TCD incidentally in hospital-based, stroke-free populations carries a substantial risk of symptomatic transition and subsequent adverse outcomes. These findings underscore the prognostic importance of identifying asymptomatic ICAS clinically and highlight the necessity for intensive vascular risk factor management in this under-recognized group to guide primary stroke prevention strategies.

Unilateral asymptomatic middle cerebral artery stenosis or occlusion (MCAs/o) is an ideal human model for investigating the neural consequences of chronic cerebral hypoperfusion. Using a discovery-validation approach, this study aimed to characterize functional abnormalities in hypoperfused brain regions of unilateral MCAs/o and assess their neurobehavioral implications. In a discovery cohort comprising 41 patients with unilateral MCAs/o and 30 matched controls, patients exhibited significantly impaired performance on bilateral grooved pegboard tests (GPT, P < 0.05). Arterial spin labelling identified hypoperfused regions with prolonged arterial transit time. These regions showed increased intraregional regional homogeneity and functional connectivity (FC), and decreased extraregional FC (FDR-P < 0.05). A machine-learning model integrated these functional imaging features into a hypoperfusion-functional abnormality index (HFAi), which effectively detected early functional abnormalities in MCAs/o patients (AUC = 0.978) and correlated significantly with GPT performance (P < 0.01). Validation in an independent cohort (20 MCAs/o patients and 18 controls) confirmed these findings, demonstrating consistent identification of early functional abnormalities (AUC = 0.861) and correlation between HFAi and GPT scores (P < 0.05). Our results indicate that unilateral MCAs/o increased local neural synchronization coupled with reduced global functional integration, suggesting a shift towards isolated neural processing. These hypoperfusion-related functional abnormalities are closely linked to neurobehavioral alterations and can be objectively quantified.

To assess the diagnostic efficacy of plasma biomarkers in distinguishing Alzheimer's pathologic changes from other forms of dementia, our study focused on examining plasma biomarkers in accordance with the AT(N) system. A total of 156 participants were recruited from the PUMCH dementia cohort. This comprised 55 non-AD (A-) and 101 Alzheimer's pathologic changes (A+) individuals. Among the latter group, there were 40 AD-like(A+T-) and 61 AD(A+T+). Biomarker diagnoses were relied on cerebrospinal fluid (CSF) biomarkers and amyloid PET results. Plasma biomarkers were quantified using single molecule array (SIMOA). Plasma Aβ40, Aβ42, GFAP, NfL, and pTau181 were compared among A-, A+T-, and A+T+ groups. Significant reductions in plasma Aβ42/40, along with elevated levels of plasma pTau181 and GFAP, were observed in both A+T- and A+T+ groups compared to the A- group. However, no significant differences were found between the A+T- and A+T+ groups. Additionally, plasma Aβ42/40, pTau181, and GFAP exhibited significant correlations with multiple CSF biomarkers, especially with CSF Aβ biomarkers, whereas plasma Aβ42, Aβ40, and NfL did not. None of the plasma biomarkers were indicative of disease severity in A+ dementia patients. Finally, a high accuracy diagnostic model in predicting Alzheimer's pathologic changes in dementia patients could be generated using plasma biomarkers. Plasma levels of Aβ42/40, pTau181, and GFAP present valuable indicators in distinguishing Alzheimer's pathologic changes from other forms of dementia. The integration of multiple plasma biomarkers into a diagnostic model can significantly enhance diagnostic accuracy, thereby providing valuable support for clinical practice.

BACKGROUND:We aimed to investigate the effects of evolocumab, a proprotein convertase subtilisin/kexin type-9 inhibitor for intensive lipid-lowering, on intracranial atherosclerotic stenosis. METHODS:From a prospectively established high-resolution magnetic resonance imaging database, consecutive patients with intracranial atherosclerotic stenosis (≥50%) with 2 detections of high-resolution magnetic resonance imaging over 6 months were included in this retrospective analysis. Eligible patients were grouped by treatment: evolocumab add-on (evolocumab+) versus no evolocumab (evolocumab-). The primary outcome was plaque response (plaque regression >5%). Secondary outcomes included the percentage of changes in plaque burden and stenosis degree. Logistic and linear regression analyses were used to estimate the association between evolocumab use and the above outcomes in both the general and subgroup (intensive versus nonintensive statin) analyses. RESULTS:Among 179 statin-treated patients (50 evolocumab+, 129 evolocumab-), evolocumab add-on therapy was associated with higher plaque response (68.0% versus 34.1%), greater plaque burden reduction (median [interquartile range]: -8.2% [-11.4%, -1.8%] versus -1.9% [-6.7%, 4.4%]), and stenosis degree reduction (-15.3% [-33.7%, -1.3%] versus -5.4% [-25.8%, 12.3%]). Adjusted regression analyses showed significant associations between evolocumab use and plaque response (odds ratio [95% CI], 6.67 [2.80, 16.91]), plaque burden reduction (estimate [95% CI], -7.0% [-11.5%, -2.5%]), and stenosis degree reduction (estimate [95% CI], -20.3% [-31.7%, -7.0%]). Subgroup analyses according to background statin intensity showed consistent associations. CONCLUSIONS:Evolocumab add-on therapy over 6 months was associated with intracranial atherosclerotic plaque regression compared with statin therapy alone. However, given the retrospective design and potential between-group differences, these findings require further confirmation in prospective randomized controlled studies.

To the Editor: Diagnosing Alzheimer's disease (AD) remains challenging, as clinical diagnostic accuracy is often inferior to neuropathological confirmation. The AT(N) system, introduced by the National Institute on Aging-Alzheimer's Association (NIA-AA), provides a biomarker framework to increase diagnostic precision in AD research.[1] Recent technological innovations, such as ultrasensitive assays like Simoa, have enabled precise evaluation of blood biomarkers, offering potential for noninvasive diagnostics. Most studies have focused on individuals with normal cognition, subjective cognitive decline, or mild cognitive impairment, examining the predictive role of plasma biomarker levels in AD progression.[2] However, the diagnostic utility of these biomarkers in AD dementia remains underexamined. Therefore, we assessed the accuracy of plasma Aβ40, Aβ42, pTau181, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) levels in diagnosing AD among dementia patients, expanding the use of the AT(N) system for blood-based diagnostics. Ethical approval for this study was obtained from the Ethics Committee of Peking Union Medical College Hospital (No. JS2810). Participants were recruited from the Peking Union Medical College Hospital (PUMCH) Dementia Cohort, with 156 dementia patients clinically diagnosed according to the 2011 NIA-AA criteria. All patients underwent thorough routine examinations, with detailed protocols provided in the Supplementary Materials, https://links.lww.com/CM9/C317. All participants underwent cerebrospinal fluid (CSF) biomarker analysis and/or amyloid positron emission tomography (PET) imaging and then received a biological diagnosis according to the 2018 NIA-AA AT(N) framework. A detailed description of both the sample collection and diagnostic procedures is provided in the Supplementary Materials, https://links.lww.com/CM9/C317. The plasma biomarker detection method is consistent with our previous study and is outlined as follows[3]: Plasma levels of Aβ40, Aβ42, GFAP, NfL, and pTau181 were measured via the ultrasensitive Simoa (Quanterix, MA, USA) Neurology 4-Plex E Assay Kit (Cat No: 103670), and the pTau181 Advantage V2 Assay Kit (Cat No: 103714) on the Simoa HD-X platform (GBIO, Hangzhou, China). Ethylenediaminetetraacetic acid (EDTA) plasma samples were diluted 1:4 for biomarker measurement, and duplicate readings were taken for calibrators, internal quality controls, and all samples. Statistical analysis methods are shown in the Supplementary Materials, https://links.lww.com/CM9/C317. A total of 156 patients were clinically diagnosed with dementia based on the 2011 NIA-AA criteria, regardless of specific disease etiology, and all exhibited significant brain atrophy on anatomical magnetic resonance imaging (MRI), indicating neuronal injury (N+). Patients were further classified into biomarker A–N+, A+T–N+, and A+T+N+ according to the AT (N) framework, where A represents amyloid pathology, T represents tau pathology, and N represents neuronal injury. Each patient underwent blood sample collection, MRI, and cognitive assessments, with 149 providing CSF samples and 52 undergoing amyloid PET imaging. Among the total cohort, 101 patients were positive for Aβ biomarkers (A+N+), and 55 were not (A–N+). Within the A+N+group, 40 patients were classified as AD-like (A+T–N+), and 61 were classified as AD (A+T+N+). Baseline demographics, cognitive scores, and fluid biomarker levels are presented in Supplementary Table 1, https://links.lww.com/CM9/C317. A significant difference in mini-mental state examination (MMSE) scores was noted between the A–N+ and A+T+N+ groups. There was no evidence of a difference among groups in terms of age, sex, years of education, Activities of daily living (ADL) scores, and apolipoprotein E (APOE) ε4 carrier percentages. Supplementary Table 1, https://links.lww.com/CM9/C317 presents the plasma biomarker levels across the different groups. Both the A+T–N+ and A+T+N+ groups showed a significantly decrease in the plasma Aβ42/40 ratio and an increase in plasma pTau181 and GFAP levels compared with the A–N+ group [Figure 1A]. No significant differences were found between the A+T–N+ and A+T+N+ groups in terms of plasma biomarker levels, although a trend toward progressively increasing plasma pTau181 levels was observed across the A–N+, A+T+N+, and A+T+N+ groups. Plasma NfL, Aβ42, and Aβ40 levels were similar across all groups [Supplementary Figure 1A, https://links.lww.com/CM9/C317]. Further comparisons between the A–N+ and A+N+ groups, as well as the PET– and PET+ groups, revealed similar trends, with reduced plasma Aβ42/40 ratios and elevated pTau181 and GFAP levels in the A+N+/PET+ group compared with those in the A–N+/PET– group [Figure 1B, C]. No significant differences in plasma NfL, Aβ42, and Aβ40 levels among groups were observed [Supplementary Figure 1B, C, https://links.lww.com/CM9/C317]. In summary, our findings demonstrate a strong association between plasma biomarker levels—particularly the Aβ42/40 ratio and pTau181 and GFAP levels—and brain Aβ pathology, as confirmed by CSF biomarker analysis and/or AV45 PET.Figure 1: Comparison of plasma AD biomarkers and their correlation with CSF AD biomarkers, along with machine learning model performance in dementia patients. (A) Comparison of plasma Aβ42/40 ratio and plasma pTau181 and GFAP levels among A–N+, A+T–N+, and A+T+N+ groups. (B) Comparison of plasma Aβ42/40 ratio and plasma pTau181 and GFAP levels between A–N+ and A+N+ groups. (C) Comparison of plasma Aβ42/40 ratio and plasma pTau181 and GFAP levels between PET– and PET+ groups. (D) Correlations of biomarkers between CSF and plasma. Correlations were represented by Pearson coefficients, which were calculated and showed by grid color. FDR correction was used in adjusted P-values. Only adjusted P-values reaching significance were labeled. Plasma Aβ42/40 ratio, pTau181, and GFAP exhibited significant correlations with multiple CSF biomarkers. (E) Machine learning models in predicting Aβ positive in dementia patients, ROC curves along with their corresponding AUCs were presented. § P <0.0001, ‡ P <0.001, † P <0.01; * P <0.05. A: Amyloid pathology; T: Tau pathology; N: Neuronal injury; Aβ: Amyloid beta; Aβ42/40: Ratio of Aβ42 to Aβ40; CSF: Cerebrospinal fluid; FDR: False discovery rate; GFAP: Glial fibrillary acidic protein; NfL: Neurofilament light chain; PET: positron emission tomography; pTau181: Phosphorylated Tau 181; ROC: Receiver operating characteristic; SVM: Support vector machine; tTau: Total Tau.To investigate the relationship between biomarker levels across the blood–brain barrier, we assessed the correlations between plasma and CSF biomarker levels [Figure 1D]. Plasma Aβ42/40 ratios and pTau181 and GFAP levels were significantly correlated with various CSF biomarker levels, whereas plasma Aβ42, Aβ40, and NfL levels were not. Notably, plasma Aβ42/40 ratios showed a stronger correlation with CSF biomarker levels than either plasma Aβ42 levels or plasma Aβ40 levels alone did, suggesting that the Aβ42/40 ratio may reduce the influence from blood sample. Interestingly, the plasma GFAP level displayed a stronger correlation with CSF Aβ-related biomarker levels than with CSF pTau181 or tTau levels. Overall, plasma biomarker levels correlated more strongly with CSF Aβ biomarker levels than with CSF pTau levels or neuronal injury marker levels. To assess whether plasma AD biomarkers reflect disease severity in Aβ-positive dementia patients, we analyzed their correlation with MMSE scores in the A+N+ group [Supplementary Figure 2, https://links.lww.com/CM9/C317]. Results showed no significant correlation, suggesting plasma biomarkers may not reliably indicate disease severity in this subgroup. To increase diagnostic accuracy through non-invasive methods, we employed various machine learning models, including random forest, decision tree, logistic regression, and support vector machine (SVM) models. Plasma Aβ42/40 ratios; plasma pTau181, GFAP, and NfL levels; and MMSE and ADL scores were used to predict A+ in dementia patients. Receiver operating characteristic (ROC) curves were generated to evaluate model performance, and the area under the curve (AUC) was calculated for each [Figure 1E]. The random forest model demonstrated the highest AUC (0.83) for predicting patient diagnoses. Additionally, the decrease in the Gini coefficient from the random forest model [Supplementary Figure 3, https://links.lww.com/CM9/C317] indicated that the plasma pTau181 level contributed the most to the predictive accuracy of the model, followed by the plasma Aβ42/40 ratio and GFAP levels, which also played a major role. The plasma NfL level contributed less, underscoring that the plasma Aβ42/40 ratio and pTau181 and GFAP levels are strong indicators of Aβ pathology in the brain. Similar models were developed to predict amyloid PET outcomes, with the random forest model again achieving the highest AUC (0.94) [Supplementary Figure 4, https://links.lww.com/CM9/C317]. Several studies have focused on the associations between blood biomarker levels and AD diagnosis.[4] Machine learning also has played a significant role in improving AD diagnosing accuracy.[5] In this study, We found that the A+T–N+ and A+T+N+ groups had significantly lower plasma Aβ42/40 ratios and higher pTau181 and GFAP levels than did the A–N+ group. Machine learning models further demonstrated the diagnostic value of these biomarkers. However, plasma biomarker levels were not correlated with MMSE scores in A+N+ patients, limiting the utility of these biomarkers in assessing disease severity. In conclusion, the plasma Aβ42/40 ratio and pTau181 and GFAP levels are promising noninvasive biomarkers for detecting brain Aβ pathology in dementia patients and have the potential to increase diagnostic accuracy when these measurements are combined with clinical assessments by machine learning models. Acknowledegements We are grateful to the patients, caregivers, and staffs for providing the clinical information. We are also very grateful to the Clinical Biobank (ISO 20387), Peking Union Medical College Hospital, and Chinese Academy of Medical Sciences for their support in storing clinical specimens for us. Funding This study was supported by grants from the National Key Research and Development Program of China (Nos. 2020YFA0804500 and 2020YFA0804501), CAMS Innovation fund for medical sciences (CIFMS) (Nos. 2021-I2M-1-020 and 2020-I2M-C&T-B-010), National Natural Science Foundation of China (Nos. 81550021 and 30470618), and National High Level Hospital Clinical Research Funding (Nos. 2022-PUMCH-D-007 and 2022-PUMCH-A-254). Conflicts of interest None.

BACKGROUND:Little is known about the dynamic process of the outer-wall boundary during intensive lipid-lowering therapy in patients with intracranial atherosclerotic stenosis and its clinical implications. METHODS:We analyzed patients with first-ever acute ischemic stroke attributed to intracranial atherosclerotic stenosis who received intensive lipid-lowering therapy with high-dose statins or PCSK9i (proprotein convertase subtilisin/kexin type 9 inhibitor). Data were obtained from a multicenter cohort study at 15 hospitals across China and our institutional database in Beijing, China. All patients underwent 3-dimensional T1-weighted high-resolution magnetic resonance vessel wall imaging at baseline and after a >6-month follow-up period. Outer-wall boundary area changes were classified as expansion (>10% increase), shrinkage (>10% decrease), or quiescence (≤10% change). The association between these changes and time to recurrent ipsilateral stroke was assessed. The Kaplan-Meier method and the Cox proportional hazards model were used. RESULTS:Among the 137 patients, 50 (36.5%) exhibited expansion, 40 (29.2%) shrinkage, and 47 (34.3%) quiescence of the outer-wall boundary area. Among these 3 groups, plaque burden decreased significantly between the index imaging and follow-up (all P≤0.02). Lumen area increased significantly in patients with expansion (P<0.001) and quiescence (P=0.01) but not in those with shrinkage of the outer-wall boundary area (P=0.34). Patients with shrinkage of the outer-wall boundary area had a significantly increased risk of recurrent ipsilateral stroke (hazard ratio, 2.95 [95% CI, 1.02-8.55]; P=0.046) compared with patients without such shrinkage. In multivariable Cox regression analysis, shrinkage of the outer-wall boundary area was associated with recurrent ipsilateral stroke compared with non-shrinkage after adjusting for potential confounders (hazard ratio, 4.21 [95% CI, 1.14-15.58]; P=0.031). CONCLUSIONS:Outer-wall boundary area changes vary among patients with intracranial atherosclerotic stenosis under intensive lipid-lowering therapy. Shrinkage of the outer-wall boundary area is significantly associated with a higher risk of stroke recurrence.