Introduction: Many patients with moyamoya disease (MMD) exhibit cognitive decline; however, the link between cognitive reserve (CR) and cognitive function in those who have not undergone revascularization remains unexplored. We aimed to evaluate preoperative cognitive impairment in such patients and to explore the relationship between CR, measured using the Cognitive Reserve Index questionnaire (CRIq), and cognitive abilities across different domains, determined using neuropsychological tests. Methods: Demographic, clinical, CRIq, and neuropsychological assessment data were gathered from patients with MMD who underwent preoperative cognitive functional assessments at our center during 2021–2023. These patients were categorized according to their Montreal Cognitive Assessment score. Multivariable linear regression was performed to analyze the association between CRIq score and cognitive performance, both globally and in specific domains. Results: In the MMD cohort of 53 patients, 49% (n = 26) of the patients exhibited a decrease in overall cognitive performance. Individuals with cognitive dysfunction had significantly lower composite CRIq scores than those with intact cognition. Although no association between overall cognitive ability and CR was observed, independent associations emerged between CR and specific cognitive functions – language (β = 0.56, p = 0.002), verbal memory (β = 0.45, p = 0.001), and executive function (β = 0.35, p = 0.03). Conclusion: This preliminary study revealed that expressive language, verbal memory, and executive function are linked to CR in presurgical patients with MMD, highlighting the role of CR in predicting cognitive outcomes. Further research is warranted to elucidate the combined effects of CR and other risk factors on the cognitive function of patients with MMD.

Moyamoya disease (MMD) is a cerebrovascular disorder characterized by the progressive stenosis of large intracranial arteries, such as the terminal portion of the internal carotid artery, accompanied by the development of collaterals at the base of the brain that have a “puff of smoke” appearance upon angiography [1]. One-third to two-thirds of patients with MMD have cognitive impairment [2]. Such cognitive impairment may result not only from cerebrovascular events but can also occur in asymptomatic patients without a history of stroke, owing to chronic hypoperfusion and hypoxia [3]. For example, previous research of patients with MMD revealed no significant differences in the frequency or likelihood of cognitive impairment between those with and those without a history of stroke [4‒6]. As a result, cognitive decline is observed both in patients with an earlier onset of the disease and in those with a prolonged disease duration [7]. Furthermore, individuals with normal intelligence may exhibit selective impairments in certain cognitive domains [2].

The concept of cognitive reserve (CR) has evolved from its original definition as a mechanism for the optimization of brain performance through diverse strategies in 2002 [8], as a gap is discernible between the expected decline in cognitive function due to aging or pathological conditions in the brain and the deficits that are actually observed [9]. This reserve is built up through a variety of life experiences, such as the level of education achieved, engagement in intellectual activities, career history, and exposure to various environmental factors [10, 11]. CR is recognized for its ability to improve the efficiency, capacity for processing, and adaptability of brain networks, thereby protecting the individual against the impacts of aging, disease progression, and brain damage, including conditions such as neurodegenerative disease, cerebral stroke, and traumatic brain injury [12‒14]. Given the challenges in directly quantifying CR, researchers often rely on sociobehavioral proxy indicators, such as educational background, professional experience, leisure pursuits, and the ability to speak multiple languages [15].

The Cognitive Reserve Index questionnaire (CRIq) is completed either by the patients themselves or by their relatives. It yields three sub-scores corresponding to different dimensions: education, working activities, and leisure time [16]. Research on its utility has been conducted not only in the general population but also among patients with multiple sclerosis, frontotemporal dementia, traumatic brain injury, and other conditions that affect the brain [17‒19].

The concept of CR has been thoroughly validated in patients who have had a stroke, and a cumulative number of studies are being conducted to explore the impact of potential CR proxies to predict cognitive impairment post stroke [14]. However, to date, no research has been published on the relationship between CR and cognitive function in patients with MMD who have not undergone revascularization, although the condition is similar to stroke. Furthermore, the utility of the CRIq for the measurement of CR in patients with MMD has not been documented. Therefore, the aim of this study was to assess the extent of cognitive impairment based on preoperative cognitive evaluations and to investigate the association between CR and cognitive function, both overall and in specific cognitive domains in patients with MMD.

Participants

This study had a retrospective, cross-sectional design, focusing on patients who underwent preoperative cognitive assessments at our institution from October 2021 to October 2023, prior to revascularization surgery. The inclusion criteria were as follows: patients who (1) were aged 18 years or older, (2) underwent digital subtraction angiography according to the guidelines established in 2012, (3) completed the CRIq and neuropsychological assessments before revascularization surgery, (4) were right-handed patients, and (5) had not had a stroke in the past year. Patients who had the following conditions were excluded: (1) severe dyskinesia or paralysis; (2) language disorders, such as aphasia; and (3) psychiatric disorders. The study protocol was approved by the Institutional Review Board (IRB) of our hospital (IRB number: OC24RISI0021). The IRB waived the requirement for informed consent owing to the retrospective nature of the study. All procedures were performed in compliance with relevant laws and institutional guidelines. The study was reported in accordance with the STROBE guidelines [20].

Korean Version of the CRIq

The Korean version of the CRIq, developed by Choi et al. [21], was administered to patients by physicians and clinical psychologists prior to the preoperative neuropsychological assessment. The CRIq consists of 20 items with numerical scales and dichotomous answers. In the education domain, scores are computed by combining the regular and irregular educational periods. Within the occupational activities domain, scores are derived by multiplying the level of occupation by the years of employment. In the leisure activities domain, frequencies and durations of various kinds of leisure activities are evaluated, and the cumulative durations of activities performed above a certain frequency threshold are converted into scores. Linear models with age as the independent variable and scores for the three domains as the dependent variables are employed to calculate detailed, domain-specific scores (CRI-education, CRI-occupational activities, and CRI-leisure time). Subsequently, the average of these detailed scores is recalibrated to a mean of 100 and a standard deviation of 15 to obtain the composite CRIq score.

Neuropsychological Evaluation

Trained neuropsychologists performed all of the neuropsychological assessments. The Korean version of the Montreal Cognitive Assessment (MoCA) was used to evaluate global cognitive function. Patients who had no more than 6 years of education were assigned an additional point to their total MoCA score. The MoCA score ranges from 0 to 30, with higher scores indicating better cognitive function. A composite score of 26 or above indicates normal cognitive function, and a score below 26 points indicates cognitive impairment. The Seoul Neuropsychological Screening Battery, a comprehensive neuropsychological test battery that incorporates standardized and validated measures across a spectrum of cognitive abilities, was administered to all participants [22]. For the purposes of our research, we selected the following assessments that yield numerical outcomes: the digit span tests (DSTs, both forward and backward) for attention; the Korean version of the Boston Naming Test (BNT) for language function; the Seoul Verbal Learning Test (SVLT) with its 20-min delayed recall (DR) components for verbal memory; the Rey-Osterrieth Complex Figure Test (RCFT), encompassing both copying and 20-min DR tasks, for visuospatial function and visual memory, respectively; the Controlled Oral Word Association Test for phonemic fluency; the Stroop Color and Word Test for cognitive processing and flexibility; the Digit Symbol Coding (DSC) task for processing speed and working memory; and the Trail Making Test (TMT) for frontal/executive function, with parts A and B (time) specifically for visual attention and task switching, respectively.

Covariates

Clinical data, including age, sex, clinical presentation of MMD, history of stroke, current smoking status, and alcohol consumption habits, were collected via chart review. Furthermore, the presence of vascular risk factors, such as hypertension, diabetes mellitus, and dyslipidemia, was recorded. For radiological examination, MMD in the right and left cerebral hemispheres of the patients was evaluated by highly experienced neurosurgeons using digital subtraction angiography, according to the Suzuki staging system. In terms of white matter lesions, patients were separately assessed for deep white matter hyperintensities and periventricular hyperintensities based on the Fazekas scale by using fluid-attenuated inversion recovery brain magnetic resonance imaging.

Statistical Analysis

Continuous data are presented as means (standard deviations) and medians (interquartile ranges), and categorical data are presented as frequencies (percentages), to describe the demographic and clinical characteristics of the patients. The normality of each data set was assessed using the Kolmogorov-Smirnov test. Continuous variables were compared using the Mann-Whitney U test for skewed distributions and the independent samples t test for normal distributions. Categorical variables were compared using the χ2 test or Fisher’s exact test, as appropriate. When comparing the raw scores for each specific cognitive domain between the normal cognition and cognitive impairment groups, p values were calculated after adjusting for age, sex, and education. We explored the relationship between CR and cognitive function by using multivariable linear regression models to investigate the associations between the composite CRIq score and the global/individual domains of cognitive function, using the results of neuropsychological tests. The models controlled for potential confounding factors, including age, sex, education level, diabetes mellitus, dyslipidemia, hypertension, Suzuki stage, white matter hyperintensities, and history of stroke. We ensured the validity of our regression models by calculating the variance inflation factor for all variables, using a threshold of variance inflation factor >10 to identify variables with severe collinearity. We performed all statistical analyses using R version 4.2.2 and established statistical significance at a p value of less than 0.05.

Demographics, Clinical Information, and Neuropsychological Assessment according to MoCA Group

Among a total of 53 patients, 26 (49%) had cognitive impairment (MoCA score <26) and 27 (51%) patients were cognitively normal. The median MoCA score for the cognitively impaired group was 24.0 (21.0–25.0), whereas in the cognitively normal group, the median MoCA score was 27.0 (27.0–28.5). Although no significant difference in the sex ratio was observed, the cognitively impaired group was older, with a median age of 60.5 (52.0–63.0) years, and had lower educational attainment, with a median of 9 (6.0–12.0) years of education. Regarding comorbidities, no differences in the prevalence of hypertension, diabetes mellitus, dyslipidemia, or history of drinking or smoking were observed between the two groups. Furthermore, no significant differences occurred between the two groups in terms of clinical features of MMD, history of stroke, or brain imaging findings, including white matter lesions and Suzuki staging (Table 1). The groups significantly differed in their median composite CRIq scores (cognitively impaired: 100.0 [92.0–105.0] vs. cognitively normal: 107.0 [99.5–113.5], p = 0.016) (Fig. 1).

Table 1.

Demographic and clinical information of 53 patients with MMD

Cognitive VariablesMoCA score <26 (n = 26)MoCA score ≥26 (n = 27)Total (N = 53)p value
Age 60.5 (52.0–63.0) 50.0 (45.5–55.5) 55.0 (46.0–61.0) 0.018 
Sex, n (%)    0.309 
 Male 9 (35) 5 (19) 14 (26)  
 Female 17 (65) 22 (81) 39 (74)  
Education years 9.0 (6.0–12.0) 12.0 (12.0–13.0) 12.0 (9.0–12.0) <0.001 
Clinical presentation, n (%)    0.394 
 Asymptomatic 12 (46) 18 (67) 30 (57)  
 Transient ischemic attack 1 (4) 1 (4) 2 (4)  
 Ischemic 12 (46) 8 (30) 20 (38)  
 Hemorrhagic 1 (4) 0 (0) 1 (2)  
Stroke history, n (%)    0.131 
 No 12 (46) 19 (70) 31 (58)  
 Yes 14 (54) 8 (30) 22 (42)  
Current smoking, n (%)    0.659 
 No 21 (81) 24 (89) 45 (85)  
 Yes 5 (19) 3 (11) 8 (15)  
Alcohol drinking, n (%)    0.745 
 No 23 (88) 22 (81) 45 (85)  
 Yes 3 (12) 5 (19) 8 (15)  
Hypertension, n (%)    >0.999 
 No 16 (62) 17 (63) 33 (62)  
 Yes 10 (38) 10 (37) 20 (38)  
Diabetes mellitus, n (%)    0.676 
 No 20 (77) 23 (85) 43 (81)  
 Yes 6 (23) 4 (15) 10 (19)  
Dyslipidemia, n (%)    0.835 
 No 19 (73) 18 (67) 37 (70)  
 Yes 7 (27) 9 (33) 16 (30)  
Fazekas scale for white matter lesions 
 Periventricular white matter, n (%)    0.402 
  0 20 (77) 17 (63) 37 (70)  
  1 6 (23) 9 (33) 15 (28)  
  2 0 (0) 1 (4) 1 (2)  
 Deep white matter, n (%)    0.070 
  0 21 (81) 18 (67) 39 (74)  
  1 5 (19) 4 (15) 9 (17)  
  2 0 (0) 5 (19) 5 (9)  
 Suzuki stage, right side, n (%)    0.315 
  0 2 (8) 4 (15) 6 (11)  
  1 4 (15) 7 (26) 11 (21)  
  2 7 (27) 3 (11) 10 (19)  
  3 6 (23) 6 (22) 12 (23)  
  4 3 (12) 0 (0) 3 (6)  
  5 3 (12) 6 (22) 9 (17)  
  6 1 (4) 1 (4) 2 (4)  
 Suzuki stage, left side, n (%)    0.259 
  0 5 (19) 0 (0) 5 (9)  
  1 2 (8) 4 (15) 6 (11)  
  2 5 (19) 5 (19) 10 (19)  
  3 7 (27) 6 (22) 13 (25)  
  4 5 (19) 7 (26) 12 (23)  
  5 2 (8) 4 (15) 6 (11)  
  6 0 (0) 1 (4) 1 (2)  
Cognitive VariablesMoCA score <26 (n = 26)MoCA score ≥26 (n = 27)Total (N = 53)p value
Age 60.5 (52.0–63.0) 50.0 (45.5–55.5) 55.0 (46.0–61.0) 0.018 
Sex, n (%)    0.309 
 Male 9 (35) 5 (19) 14 (26)  
 Female 17 (65) 22 (81) 39 (74)  
Education years 9.0 (6.0–12.0) 12.0 (12.0–13.0) 12.0 (9.0–12.0) <0.001 
Clinical presentation, n (%)    0.394 
 Asymptomatic 12 (46) 18 (67) 30 (57)  
 Transient ischemic attack 1 (4) 1 (4) 2 (4)  
 Ischemic 12 (46) 8 (30) 20 (38)  
 Hemorrhagic 1 (4) 0 (0) 1 (2)  
Stroke history, n (%)    0.131 
 No 12 (46) 19 (70) 31 (58)  
 Yes 14 (54) 8 (30) 22 (42)  
Current smoking, n (%)    0.659 
 No 21 (81) 24 (89) 45 (85)  
 Yes 5 (19) 3 (11) 8 (15)  
Alcohol drinking, n (%)    0.745 
 No 23 (88) 22 (81) 45 (85)  
 Yes 3 (12) 5 (19) 8 (15)  
Hypertension, n (%)    >0.999 
 No 16 (62) 17 (63) 33 (62)  
 Yes 10 (38) 10 (37) 20 (38)  
Diabetes mellitus, n (%)    0.676 
 No 20 (77) 23 (85) 43 (81)  
 Yes 6 (23) 4 (15) 10 (19)  
Dyslipidemia, n (%)    0.835 
 No 19 (73) 18 (67) 37 (70)  
 Yes 7 (27) 9 (33) 16 (30)  
Fazekas scale for white matter lesions 
 Periventricular white matter, n (%)    0.402 
  0 20 (77) 17 (63) 37 (70)  
  1 6 (23) 9 (33) 15 (28)  
  2 0 (0) 1 (4) 1 (2)  
 Deep white matter, n (%)    0.070 
  0 21 (81) 18 (67) 39 (74)  
  1 5 (19) 4 (15) 9 (17)  
  2 0 (0) 5 (19) 5 (9)  
 Suzuki stage, right side, n (%)    0.315 
  0 2 (8) 4 (15) 6 (11)  
  1 4 (15) 7 (26) 11 (21)  
  2 7 (27) 3 (11) 10 (19)  
  3 6 (23) 6 (22) 12 (23)  
  4 3 (12) 0 (0) 3 (6)  
  5 3 (12) 6 (22) 9 (17)  
  6 1 (4) 1 (4) 2 (4)  
 Suzuki stage, left side, n (%)    0.259 
  0 5 (19) 0 (0) 5 (9)  
  1 2 (8) 4 (15) 6 (11)  
  2 5 (19) 5 (19) 10 (19)  
  3 7 (27) 6 (22) 13 (25)  
  4 5 (19) 7 (26) 12 (23)  
  5 2 (8) 4 (15) 6 (11)  
  6 0 (0) 1 (4) 1 (2)  

All data are shown as n (%) or median (interquartile range). p values for continuous variables were calculated using the Mann-Whitney U test or Student’s t test, whereas, for categorical variables, the χ2 test or Fisher’s exact test was employed, as appropriate. Total percentages may not equal 100% because of rounding.

MoCA, Montreal Cognitive Assessment.

Fig. 1.

Composite CRIq according to global cognitive function. Significant differences were observed in the median composite CRIq scores between the two groups, stratified according to MoCA scores. CRIq, Cognitive Reserve Index questionnaire; MoCA, Montreal Cognitive Assessment.

Fig. 1.

Composite CRIq according to global cognitive function. Significant differences were observed in the median composite CRIq scores between the two groups, stratified according to MoCA scores. CRIq, Cognitive Reserve Index questionnaire; MoCA, Montreal Cognitive Assessment.

Close modal

Associations between Composite CRIq Score and Cognitive Function

Participants with cognitive impairment had significantly lower raw scores across most cognitive domains (except for the DST-backward, RCFT-DR, and DSC scores) after adjusting for age, sex, and years of education, as detailed in Table 2. Although the composite CRIq score was not significantly associated with overall cognitive performance, significant associations were observed in specific cognitive domains. The Korean version of the BNT (β = 0.56, p = 0.002), SVLT-DR (β = 0.45, p = 0.001), and TMT-B (β = 0.35, p = 0.03) were independently and positively correlated with the composite CRIq score (Table 3).

Table 2.

Neuropsychological assessment according to MoCA group

MoCA groupMoCA score <26 (n = 26)MoCA score ≥26 (n = 27)p value
DST (forward) 5.2±1.3 6.8±1.4 0.004 
DST (backward) 4.0 (3.0–4.0) 4.0 (4.0–6.0) 0.30 
BNT 47.5 (40.0–52.0) 53.0 (49.0–55.5) 0.03 
RCFT copying 30.5 (28.0–33.5) 33.0 (32.0–35.0) 0.02 
SVLT (DR) 4.8±2.9 8.3±2.0 <0.001 
RCFT (DR) 12.1±5.0 16.6±6.1 0.11 
COWAT (phonemic) 18.4±9.2 27.9±8.7 0.005 
Stroop Test (color reading) 83.5 (73.0–92.0) 111.0 (99.0–112.0) <0.001 
DSC 47.5 (42.0–58.0) 71.0 (58.0–86.0) 0.07 
TMT part A 20.7±6.1 15.1±4.1 0.01 
TMT part B 50.5 (28.0–65.0) 22.0 (18.0–25.0) 0.02 
MoCA groupMoCA score <26 (n = 26)MoCA score ≥26 (n = 27)p value
DST (forward) 5.2±1.3 6.8±1.4 0.004 
DST (backward) 4.0 (3.0–4.0) 4.0 (4.0–6.0) 0.30 
BNT 47.5 (40.0–52.0) 53.0 (49.0–55.5) 0.03 
RCFT copying 30.5 (28.0–33.5) 33.0 (32.0–35.0) 0.02 
SVLT (DR) 4.8±2.9 8.3±2.0 <0.001 
RCFT (DR) 12.1±5.0 16.6±6.1 0.11 
COWAT (phonemic) 18.4±9.2 27.9±8.7 0.005 
Stroop Test (color reading) 83.5 (73.0–92.0) 111.0 (99.0–112.0) <0.001 
DSC 47.5 (42.0–58.0) 71.0 (58.0–86.0) 0.07 
TMT part A 20.7±6.1 15.1±4.1 0.01 
TMT part B 50.5 (28.0–65.0) 22.0 (18.0–25.0) 0.02 

Data are presented as means ± standard deviations or medians (interquartile ranges). p value adjusted for age, sex, and educational years.

MoCA, Montreal Cognitive Assessment; DST,digit span test; BNT, Boston Naming Test; RCFT, Rey-Osterrieth Complex Figure Test; SVLT, Seoul Verbal Learning Test; COWAT, Controlled Oral Word Association Test; DSC, Digit Symbol Coding; TMT, Trail Making Test.

Table 3.

Associations between composite CRIq score and specific cognitive domain determined via multivariable linear regression analysis

Cognitive variablesComposite CRIq score
standardized beta coefficient (β)p valueadjusted R-squared
MoCA 0.22 0.17 0.40 
DST (forward) 0.24 0.18 0.25 
DST (backward) 0.09 0.59 0.29 
BNT 0.56 0.002 0.30 
RCFT copying −0.13 0.48 0.26 
SVLT (DR) 0.45 0.001 0.35 
RCFT (DR) 0.22 0.26 0.13 
COWAT (phonemic) 0.23 0.22 0.21 
Stroop Test (color reading) 0.16 0.34 0.35 
DSC 0.13 0.37 0.52 
TMT part A −0.17 0.28 0.44 
TMT part B 0.35 0.03 0.40 
Cognitive variablesComposite CRIq score
standardized beta coefficient (β)p valueadjusted R-squared
MoCA 0.22 0.17 0.40 
DST (forward) 0.24 0.18 0.25 
DST (backward) 0.09 0.59 0.29 
BNT 0.56 0.002 0.30 
RCFT copying −0.13 0.48 0.26 
SVLT (DR) 0.45 0.001 0.35 
RCFT (DR) 0.22 0.26 0.13 
COWAT (phonemic) 0.23 0.22 0.21 
Stroop Test (color reading) 0.16 0.34 0.35 
DSC 0.13 0.37 0.52 
TMT part A −0.17 0.28 0.44 
TMT part B 0.35 0.03 0.40 

Adjusted for age, sex, educational years, hypertension, diabetes mellitus, dyslipidemia, Suzuki stage, history of stroke, and white matter hyperintensity.

MoCA, Montreal Cognitive Assessment; DST, digit span test; BNT, Boston Naming Test; RCFT, Rey-Osterrieth Complex Figure Test; SVLT, Seoul Verbal Learning Test; COWAT, Controlled Oral Word Association Test; DSC, Digit Symbol Coding; TMT, Trail Making Test.

In our sample of patients with MMD who had not undergone surgical revascularization, 49% (n = 26) exhibited an impaired global cognition. The composite CRIq scores were significantly lower in the group with cognitive impairment than those in the group with normal cognition. Although no significant associations between general cognition and CR were observed, language function, verbal memory, and executive function were significantly associated with CR after adjusting for confounding factors that may influence cognitive function. To the best of our knowledge, this study is the first to characterize the association of CR and cognitive function in adult patients with MMD who have not undergone revascularization surgery.

The prevalence of cognitive impairment in patients with MMD varies across different studies, likely owing to differing patient characteristics, such as whether they had undergone revascularization surgery or experienced a stroke, and the use of different cognitive functional assessment methods. A recent meta-analysis of a combined sample of approximately 1,190 individuals with MMD revealed a potential cognitive impairment rate of approximately 54.59% [23]. Similarly, in another study conducted on patients with MMD who had not had a stroke and using a MoCA cutoff similar to that in our study, cognitive impairment was identified in approximately 67% of cases [24]. In our study, we observed a cognitive impairment prevalence of approximately 49%, which is consistent with the results of other studies.

Previous studies have demonstrated that, in patients with MMD who had experienced prolonged hypoperfusion, cognitive impairments are chiefly noted in areas of intelligence that affect a wide range of cognitive functions, including processing speed, visuospatial function, executive function, and memory [5, 24‒27]. The discrepancies in research outcomes can be attributed to the diverse methodologies used to categorize or assess participants. We compared raw scores across specific cognitive domains between individuals with normal cognitive function and those with impaired cognitive function, while controlling for age, sex, and years of education. We revealed that, within the cognitive impairment group, attention, visuospatial function, verbal memory, and executive function were affected, as previously documented; moreover, language abilities, such as naming, were also significantly lower among patients with cognitive impairment. Previous studies revealed impairments in specific cognitive domains associated with anterior circulation involvement, decreased perfusion in the left hemisphere, and cognitive impairment related to moyamoya vessels originating from the left hemisphere [28]. Therefore, we hypothesize that linguistic abilities are also affected by MMD. Nonetheless, further research is required to thoroughly investigate specific impairments across cognitive domains and their corresponding neural correlates.

CR is consistently linked to higher neuropsychological testing scores in cross-sectional studies, regardless of a diagnosis of central nervous system disease or injury [29]. As expected, individuals with cognitive impairment, according to a cutoff score of 26 for the MoCA, had significantly lower composite scores and scores in the education domain than those with normal cognitive function. However, after controlling for all risk factors via multivariable linear regression, CR was not identified as a significant factor for overall cognitive impairment, as assessed using the MoCA, in patients with MMD. Although the MoCA is known to correlate well with neuropsychological test batteries [30], it primarily serves as a cognitive screening tool for overall cognitive function and is not a diagnostic tool. Furthermore, while the concept of CR typically suggests that individuals with a higher CR should exhibit better cognitive performance and have higher cognitive functioning, previous studies have revealed that CR benefits certain individual cognitive domains, but not overall cognitive function [31]. Therefore, a neurocognitive battery that assesses individual cognitive domains was used to obtain a more detailed understanding of how CR may affect various cognitive domains. In our study, among the various cognitive domains, expressive language performance measured with the BNT [32], verbal memory measured with the SVLT-DR, and executive functioning measured with the TMT-B were independently associated with CR in patients with MMD who had not undergone revascularization surgery.

Among the several executive functional tasks, the TMT-B was the only test independently associated with CR. This may be because the TMT-B can be used to evaluate a broad range of functions, including psychomotor speed, visual searching, attention, and other executive abilities, such as set-shifting and cognitive flexibility [33, 34]. These results align with those reported by Ihle et al. [35] in their longitudinal study, which highlighted the positive impact of CR on the performance of older adults in the TMT. Furthermore, results from previous studies on the relationship between CR and various cognitive domains in healthy older individuals are consistent with our findings. In terms of separate cognitive domains, research on older adults suggests that CR can directly influence executive functions, such as inhibitory control, working memory maintenance and manipulation, and cognitive flexibility, thereby indirectly impacting language comprehension performance [36]. In another study focused on neurocognitive aging, the moderating effect of CR was highlighted, displaying its capacity to reduce the adverse effects of aging on verbal episodic memory and executive functions [37]. The authors of that study proposed that adults with high levels of CR employ more complex learning and cognitive strategies, which indirectly enhances not only their executive functions but also their memory performance. A recent study of 167 participants in which structural equation modeling was used emphasized the crucial role of CR in enhancing memory, language, and executive functions among older adults, reinforcing its protective impact against age-related cognitive decline [38]. We hypothesize that the independent relationships between CR and specific cognitive domains – language, verbal memory, and executive function – can be explained by prior research results, in which the advantageous impacts of CR were not evident in more basic cognitive processes but were manifested in more sophisticated levels of cognitive processing [39].

Given that this study represents, to our knowledge, the first investigation of the impact of CR on cognitive function in patients with MMD, direct comparisons with previous studies could not be made. Examination of traditional risk factors influencing cognitive function in MMD – including age of onset, disease duration, chronic hypoperfusion, and the extent of white matter hyperintensities – emphasized the multifaceted contributors to cognitive outcomes [7, 40, 41]. CR may contribute not only to recovery from cognitive impairments after a stroke but also to slowing cognitive decline [8]. Therefore, one must look beyond the clinical risk factors for vascular dementia and brain imaging features of cerebrovascular integrity and focus on the impact of CR on cognitive function and the factors that comprise CR, especially in patients with MMD. A longitudinal study on MMD has demonstrated that cognitive function tends to initially decrease to a moderate level before stabilizing, with no significant alterations over an extended period [6]. This observation warrants further investigation into the role of CR in the initial decline of cognitive function in patients with MMD. Additionally, long-term research is essential to elucidate how chronic hypoperfusion and personal variations in CR synergistically affect cognitive trajectories in patients with MMD. This highlights the importance of adopting a comprehensive perspective that includes the potential protective aspects of CR, in conjunction with conventional clinical and imaging evaluations, to improve our understanding and management of cognitive outcomes in MMD.

The main strength of this study is that it is, to our knowledge, the first investigation of the association of CR with presurgical cognitive function in patients with MMD. However, this study has several limitations. First, as this was a retrospective study, selection bias might have occurred. Second, as this was a single-center study, the small sample size posed a challenge. Third, this study included both asymptomatic and symptomatic patients with MMD. However, the prevalence of stroke did not differ between individuals with normal cognition and those with impaired cognition. Furthermore, we adjusted for stroke history when we explored the relationship between CR and preoperative cognitive function. To exclude the impact of stroke history, multicenter studies with sufficient sample sizes should be conducted, analyzing the relationship between CR and cognitive function separately in symptomatic and asymptomatic groups. Finally, MMD progression was assessed using Suzuki staging, but hemodynamics-related imaging data were not collected, suggesting the need for further investigation in this area. Future research may benefit from a multifaceted approach, incorporating neurophysiological and neuroradiological correlates of cognitive impairment alongside traditional neuropsychological evaluations. Additionally, postoperative cognitive evaluations may elucidate the impact of preoperative CR on cognitive changes after revascularization surgery, offering valuable insights toward the improvement of patient care and treatment strategies.

To our knowledge, this is the first study on the effect of CR on preoperative cognitive function in patients with MMD. Expressive language performance, verbal memory, and executive functioning were independently associated with CR in patients who had not undergone revascularization surgery. Pioneering in its approach, this study underscores the significance of CR in predicting cognitive function in patients with MMD who have not undergone revascularization surgery. Long-term studies will be needed to explore the combined effects of CR and other risk factors on the cognitive function of patients with MMD.

The author would like to express their deepest gratitude to Jun-Young Lee, MD, PhD, for granting permission to use the Korean version of the Cognitive Reserve Index questionnaire in this study and generously providing the necessary materials. This contribution has been pivotal in facilitating our research. Additionally, the author is sincerely thankful to Clinical Psychologist Yoon Sun Mi for her substantial assistance in conducting all the tests associated with this study.

The study protocol was approved by the Institutional Review Board (IRB) of the Incheon St. Mary’s Hospital (IRB number: OC24RISI0021). The IRB waived the requirement for informed consent owing to the retrospective nature of the study.

The author has no conflicts of interest to declare.

The author wishes to acknowledge the financial support of the Catholic Medical Center Research Foundation made in the program year of 2023. The funder had no role in the design, data collection, data analysis, and reporting of this study.

Young-Ah Choi was responsible for the conception and design of the study, acquisition and analysis of data, drafting the text, and preparing the tables and figures. The author read and approved the final manuscript.

Data of this study are not publicly available due to privacy reasons but are available from corresponding author upon reasonable request. Further inquiries can be directed to the corresponding author.

1.
Scott
RM
,
Smith
ER
.
Moyamoya disease and moyamoya syndrome
.
N Engl J Med
.
2009
;
360
(
12
):
1226
37
.
2.
Kronenburg
A
,
Van Den Berg
E
,
Van Schooneveld
MM
,
Braun
KP
,
Calviere
L
,
Van Der Zwan
A
, et al
.
Cognitive functions in children and adults with moyamoya vasculopathy: a systematic review and meta-analysis
.
J Stroke
.
2018
;
20
(
3
):
332
41
.
3.
Karzmark
P
,
Zeifert
PD
,
Bell-Stephens
TE
,
Steinberg
GK
,
Dorfman
LJ
.
Neurocognitive impairment in adults with moyamoya disease without stroke
.
Neurosurgery
.
2012
;
70
(
3
):
634
8
.
4.
Festa
JR
,
Schwarz
LR
,
Pliskin
N
,
Cullum
CM
,
Lacritz
L
,
Charbel
FT
, et al
.
Neurocognitive dysfunction in adult moyamoya disease
.
J Neurol
.
2010
;
257
(
5
):
806
15
.
5.
He
S
,
Duan
R
,
Liu
Z
,
Ye
X
,
Yuan
L
,
Li
T
, et al
.
Characteristics of cognitive impairment in adult asymptomatic moyamoya disease
.
BMC Neurol
.
2020
;
20
(
1
):
322
.
6.
Chan
E
,
Gal
A-M
,
Van Harskamp
N
,
Adams
ME
,
Brown
MM
,
Werring
DJ
, et al
.
Long-term study of the cognitive profile of Moyamoya Disease in adults
.
J Stroke Cerebrovasc Dis
.
2023
;
32
(
6
):
107064
.
7.
Hsu
Y-H
,
Kuo
M-F
,
Hua
M-S
,
Yang
C-C
.
Selective neuropsychological impairments and related clinical factors in children with moyamoya disease of the transient ischemic attack type
.
Childs Nerv Syst
.
2014
;
30
(
3
):
441
7
.
8.
Stern
Y
.
What is cognitive reserve? Theory and research application of the reserve concept
.
J Int Neuropsychol Soc
.
2002
;
8
(
3
):
448
60
.
9.
Stern
Y
.
The concept of cognitive reserve: a catalyst for research
.
J Clin Exp Neuropsychol
.
2003
;
25
(
5
):
589
93
.
10.
Barulli
D
,
Stern
Y
.
Efficiency, capacity, compensation, maintenance, plasticity: emerging concepts in cognitive reserve
.
Trends Cogn Sci
.
2013
;
17
(
10
):
502
9
.
11.
Stern
Y
,
Arenaza-Urquijo
EM
,
Bartrés-Faz
D
,
Belleville
S
,
Cantilon
M
,
Chetelat
G
, et al
.
Whitepaper: defining and investigating cognitive reserve, brain reserve, and brain maintenance
.
Alzheimers Dement
.
2020
;
16
(
9
):
1305
11
.
12.
Rami González
L
,
Valls-Pedret
C
,
Bartrés-Faz
D
,
Caprile Elola-Olaso
C
,
Solé-Padullés
C
,
Castellví Sampol
M
, et al
.
Cognitive reserve questionnaire. Scores obtained in a healthy elderly population and in one with Alzheimer’s disease
.
Rev Neurol
.
2011
;
52
(
04
):
195
201
.
13.
Sumowski
JF
,
Chiaravalloti
N
,
Krch
D
,
Paxton
J
,
DeLuca
J
.
Education attenuates the negative impact of traumatic brain injury on cognitive status
.
Arch Phys Med Rehabil
.
2013
;
94
(
12
):
2562
4
.
14.
Tao
C
,
Yuan
Y
,
Xu
Y
,
Zhang
S
,
Wang
Z
,
Wang
S
, et al
.
Role of cognitive reserve in ischemic stroke prognosis: a systematic review
.
Front Neurol
.
2023
;
14
:
1100469
.
15.
Kartschmit
N
,
Mikolajczyk
R
,
Schubert
T
,
Lacruz
ME
.
Measuring Cognitive Reserve (CR)–A systematic review of measurement properties of CR questionnaires for the adult population
.
PLoS One
.
2019
;
14
(
8
):
e0219851
.
16.
Nucci
M
,
Mapelli
D
,
Mondini
S
.
Cognitive Reserve Index questionnaire (CRIq): a new instrument for measuring cognitive reserve
.
Aging Clin Exp Res
.
2012
;
24
(
3
):
218
26
.
17.
Nunnari
D
,
De Cola
MC
,
Costa
A
,
Rifici
C
,
Bramanti
P
,
Marino
S
.
Exploring cognitive reserve in multiple sclerosis: new findings from a cross-sectional study
.
J Clin Exp Neuropsychol
.
2016
;
38
(
10
):
1158
67
.
18.
Maiovis
P
,
Ioannidis
P
,
Gerasimou
G
,
Gotzamani-Psarrakou
A
,
Karacostas
D
.
Cognitive reserve hypothesis in frontotemporal dementia: evidence from a brain SPECT study in a series of Greek frontotemporal dementia patients
.
Neurodegener Dis
.
2018
;
18
(
2–3
):
69
73
.
19.
Basagni
B
,
Di Rosa
E
,
Bertoni
D
,
Mondini
S
,
De Tanti
A
.
Long term effects of severe acquired brain injury: a follow-up investigation on the role of cognitive reserve on cognitive outcomes
.
Appl Neuropsychol Adult
.
2023
:
1
6
.
20.
Von Elm
E
,
Altman
DG
,
Egger
M
,
Pocock
SJ
,
Gøtzsche
PC
,
Vandenbroucke
JP
;
STROBE Initiative
.
The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies
.
Lancet
.
2007
;
370
(
9596
):
1453
7
.
21.
Choi
CH
,
Park
S
,
Park
H-J
,
Cho
Y
,
Sohn
BK
,
Lee
J-Y
.
Study on cognitive reserve in korea using Korean version of cognitive reserve Index questionnaire
.
J Korean Neuropsychiatr Assoc
.
2016
;
55
(
3
):
256
63
.
22.
Kang
Y
,
Na
D
,
Hahn
S
.
Seoul neuropsychological screening battery
.
Incheon
:
Human Brain Research & Consulting Co
;
2003
.
23.
Toh
KZX
,
Koh
MY
,
Loh
EDW
,
Sia
C-H
,
Chong
Y
,
Yeo
LLL
, et al
.
Prevalence and associations of cognitive impairment in adult patients with moyamoya disease: a systematic review and meta-analysis
.
J Alzheimers Dis
.
2024
;
97
(
2
):
541
52
.
24.
Shen
X-X
,
Zhang
H-D
,
Fu
H-G
,
Xu
J-L
,
Zhang
H-T
,
Hou
L
, et al
.
Association of cognitive function and hypoperfusion in Moyamoya disease patients without stroke
.
J Cereb Blood Flow Metab
.
2023
;
43
(
4
):
542
51
.
25.
Liu
Z
,
He
S
,
Xu
Z
,
Duan
R
,
Yuan
L
,
Xiao
C
, et al
.
Association between white matter impairment and cognitive dysfunction in patients with ischemic Moyamoya disease
.
BMC Neurol
.
2020
;
20
(
1
):
302
.
26.
Roder
C
,
Haas
P
,
Fudali
M
,
Milian
M
,
Ernemann
U
,
Meyer
PT
, et al
.
Neuropsychological impairment in adults with moyamoya angiopathy: preoperative assessment and correlation to MRI and H215O PET
.
Neurosurg Rev
.
2020
;
43
(
6
):
1615
22
.
27.
Shi
Z
,
Wen
Y-J
,
Huang
Z
,
Yu
L-B
,
Zhang
D
.
Different aspects of cognitive function in adult patients with Moyamoya disease and its clinical subtypes
.
Stroke Vasc Neurol
.
2020
;
5
(
1
):
86
96
.
28.
Sun
J
,
Shi
Z
,
Yu
L
,
Wen
Y
,
Zhang
D
.
Predictors of preoperative cognitive dysfunction in adults with Moyamoya disease: a preliminary research
.
BMC Neurol
.
2022
;
22
(
1
):
12
.
29.
Jammula
VR
,
Leeper
H
,
Gilbert
MR
,
Cooper
D
,
Armstrong
TS
.
Effects of cognitive reserve on cognition in individuals with central nervous system disease
.
Cogn Behav Neurol
.
2021
;
34
(
4
):
245
58
.
30.
Lam
B
,
Middleton
LE
,
Masellis
M
,
Stuss
DT
,
Harry
RD
,
Kiss
A
, et al
.
Criterion and convergent validity of the Montreal cognitive assessment with screening and standardized neuropsychological testing
.
J Am Geriatr Soc
.
2013
;
61
(
12
):
2181
5
.
31.
Lavrencic
LM
,
Churches
OF
,
Keage
HAD
.
Cognitive reserve is not associated with improved performance in all cognitive domains
.
Appl Neuropsychol Adult
.
2018
;
25
(
5
):
473
85
.
32.
Kaplan
E
,
Goodglass
H
,
Weintraub
S
.
Boston Naming Test-2 (BNT-2)
.
Austin, TX
:
Pro-Ed
;
2001
.
33.
Strauss
E
,
Sherman
EMS
,
Spreen
O
.
A compendium of neuropsychological tests: administration, norms, and commentary
.
Oxford
:
American chemical society
;
2006
.
34.
Salthouse
TA
.
What cognitive abilities are involved in trail-making performance
.
Intelligence
.
2011
;
39
(
4
):
222
32
.
35.
Ihle
A
,
Gouveia
ÉR
,
Gouveia
BR
,
Kliegel
M
.
Cognitive reserve moderates the predictive role of memory complaints for subsequent decline in executive functioning
.
Dement Geriatr Cogn Dis Extra
.
2020
;
10
(
2
):
69
73
.
36.
Delgado-Losada
ML
,
Rubio-Valdehita
S
,
Lopez-Higes
R
,
Rodríguez-Rojo
IC
,
Prados Atienza
JM
,
García-Cid
S
, et al
.
How cognitive reserve influences older adults’ cognitive state, executive functions and language comprehension: a structural equation model
.
Arch Gerontol Geriatr
.
2019
;
84
:
103891
.
37.
Giogkaraki
E
,
Michaelides
MP
,
Constantinidou
F
.
The role of cognitive reserve in cognitive aging: results from the neurocognitive study on aging
.
J Clin Exp Neuropsychol
.
2013
;
35
(
10
):
1024
35
.
38.
Feldberg
C
,
Barreyro
JP
,
Tartaglini
MF
,
Hermida
PD
,
Moya García
L
,
Benetti
L
, et al
.
Estimation of cognitive reserve and its impact on cognitive performance in older adults
.
Appl Neuropsychol Adult
.
2024
;
31
(
2
):
117
27
.
39.
Salthouse
TA
.
The processing-speed theory of adult age differences in cognition
.
Psychol Rev
.
1996
;
103
(
3
):
403
28
.
40.
Ishii
R
,
Takeuchi
S
,
Ibayashi
K
,
Tanaka
R
.
Intelligence in children with moyamoya disease: evaluation after surgical treatments with special reference to changes in cerebral blood flow
.
Stroke
.
1984
;
15
(
5
):
873
7
.
41.
Shen
J
,
Xu
Z
,
Liu
Z
,
Duan
Y
,
Wei
W
,
Chang
J
.
Association between white matter hyperintensities burden and cognitive function in adult asymptomatic Moyamoya disease
.
J Clin Med
.
2023
;
12
(
3
):
1143
.