Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2024 Mar 14.
Published in final edited form as: J Vasc Surg. 2021 Dec 16;75(5):1643–1650. doi: 10.1016/j.jvs.2021.11.061

Lack of association between cognitive impairment and systemic inflammation in asymptomatic carotid stenosis

Sarasijhaa K Desikan a,b, Minerva Mayorga-Carlin a, Moira C Dux c, Vicki L Gray d, John Anagnostakos a, Amir A Khan e, Siddhartha Sikdar e, Dawn Barth a, Sophie Harper a, John D Sorkin f,g, Brajesh K Lal a,b
PMCID: PMC10939009  NIHMSID: NIHMS1969302  PMID: 34921963

Abstract

Background:

Asymptomatic carotid atherosclerotic stenosis (ACAS) is associated with cognitive impairment. Systemic inflammation occurs in patients with systemic atherosclerosis and is also associated with cognitive impairment. The goal of this study was to determine if cognitive impairment in patients with ACAS is the result of systemic inflammation.

Methods:

A cross-sectional analysis of 104 patients (63 patients with ACAS, 41 controls) with cognitive function and inflammatory biomarker assessments was performed. Venous blood was assayed for proinflammatory biomarkers (IL-1β, IL-6, IL-6R, IL-8, IL-17, tumor necrosis factor-α, matrix metalloproteinase [MMP]-1, MMP-2, MMP-7, MMP-9, vascular cell adhesion molecule, and high-sensitivity C-reactive protein). The patients also underwent comprehensive cognitive testing to compute five domain-specific cognitive scores per patient. We first assessed the associations between carotid stenosis and cognitive function, and between carotid stenosis and systemic inflammation in separate regression models. We then determined whether cognitive impairments persisted in patients with carotid stenosis after accounting for inflammation by adjusting for inflammatory biomarker levels in a combined model.

Results:

Patients with ACAS and control patients differed in age, race, coronary artery disease prevalence, and education. Stenosis patients had worse cognitive scores in two domains: learning and memory (P = .05) and motor and processing speed (P = .002). Despite adjusting for inflammatory biomarker levels, patients with ACAS still demonstrated deficits in the domains of learning and memory and motor and processing speed.

Conclusions:

Although systemic atherosclerosis-induced inflammation is a well-recognized cause for cognitive impairment, our data suggest that it is not the primary underlying mechanism behind cognitive impairments seen in ACAS. Cognitive impairments in learning and memory and motor and processing speed seen in patients with ACAS persist after adjusting for systemic inflammation. Thus, alternative mechanisms should be explored to account for the observed functional impairments.

Keywords: Asymptomatic carotid stenosis, Systemic inflammation, Cognitive function

Asymptomatic carotid atherosclerotic stenosis (ACAS), characterized by ≥50% luminal narrowing of the internal carotid artery (ICA) due specifically to atherosclerotic plaque, affects 7% to 14% of adults ≥60 years of age.1,2 We have found that approximately one-half of patients with ACAS demonstrate dysfunction in at least two cognitive domains.3 Other studies have also implicated ACAS as a potential risk factor for global cognitive impairment.4–6 These findings are of significant public health concern because cognitive impairment contributes to increased functional disability, decreased quality of life, and increased health care costs.7–9 Further, adults with cognitive impairment are at higher risk for developing dementia.10–13 Although aging contributes to cognitive decline, there are other risk factors associated with ACAS that may also accelerate declines in cognitive function. Elucidating these mechanisms will help to develop targeted treatment strategies to improve cognitive function in patients with ACAS.

Growing evidence links systemic inflammation to dementia, cognitive impairment,14–16 and specific neuropathological conditions such as Alzheimer’s disease14,15 and Parkinson’s disease.17 Cognitive decline in these conditions is thought to occur at least partially through the activation of cerebral microglia with the downstream production of proinflammatory cytokines, leading to neurodegeneration.18,19 The underlying pathology of ACAS is atherosclerosis, which is inherently linked to chronic inflammation.20–22 Accumulation of minimally oxidized low-density lipoproteins stimulates the endothelial production of proinflammatory and adhesion molecules, which recruit macrophages and T cells to amplify the inflammatory response.22–24 Patients with ACAS demonstrate elevated circulating high-sensitivity C-reactive protein (hsCRP), vascular cell adhesion molecule-1 (VCAM-1), and IL-6 compared with healthy controls.25,26 Therefore, a potential mechanism for the cognitive impairments seen in ACAS could be systemic inflammation. Thus, this study aimed to determine whether cognitive impairments observed in patients with ACAS were related to systemic inflammatory biomarker levels.

METHODS

Study patients and design.

We conducted a cross-sectional analysis of a subset of patients enrolled in the Asymptomatic Carotid Stenosis and Cognitive Function (ACCOF) study from 2011 to 2014.3 The ACCOF was a prospective, observational study comparing cognitive function in patients with asymptomatic carotid stenosis (stenosis group) with a control group without stenosis, but having similar vascular risk factors (control group). There is significant literature demonstrating an association between vascular risk factors and the development of cognitive impairment.7,27 By selecting a control group with similar vascular risk factors, we aimed to limit these confounders and evaluate the actual impact of the stenosis on cognitive function. This study consists of patients enrolled in the ACCOF study who had both cognitive function and inflammatory biomarker testing. There is overlap of patients from our prior publication3; however, the inflammatory biomarker data presented here have not been published previously. The study was reviewed and approved by the Institutional Review Board at the University of Maryland, Baltimore, and informed consent was obtained from all participants.

Patients included in the stenosis group had ≥50% ICA stenosis documented by duplex ultrasound (DUS) examination in our Intersocietal Accreditation Commission-accredited vascular laboratory. Asymptomatic status was confirmed by medical history and a score of zero on the National Institutes of Health Stroke Scale.28 Patients with a history of stroke, transient ischemic attack, prior carotid revascularization, contralateral arterial occlusion, vertebrobasilar or intracranial stenosis or occlusion, clinically documented dementia, or medical conditions precluding complete testing were excluded from the study. Control patients had one or more vascular risk factors, but <50% carotid stenosis. Demographic data, vascular risk factors, and neurologic history were recorded. Patients underwent DUS examination to assess the degree of stenosis, a comprehensive battery of neuropsychological tests to assess domain-specific cognitive function, and collection of venous blood samples to assess inflammatory biomarker levels.

DUS examination.

The proximal, mid, and distal segments of the ICA were evaluated by DUS examination. The highest peak systolic velocity (PSV), representing the area of maximum stenosis, was used to determine the degree of stenosis. Patients were determined to have <50% stenosis when the ICA PSV was <125 cm/s; 50% to 69% stenosis when the ICA PSV was 125 to 230 cm/s; and ≥70% stenosis when ICA PSV was >230 cm/s.29

Inflammatory biomarker assessment.

Venous blood from 104 patients (n = 63 stenosis, n = 41 control) was drawn in the morning after a 10-hour overnight fast. Blood samples were immediately frozen at −20°C and stored until the assays were batch processed. A total of 12 proinflammatory biomarkers were selected for assay. Ten proinflammatory biomarkers were assayed from serum using Millipore Multiplex kits (Burlington, Mass) and read using the Luminex 100 reader with BioPlex software for data calculations: IL-1β, IL-6, IL-8, IL-17, tumor necrosis factor alpha, matrix metalloproteinases (MMP)-1, MMP-2, MMP-7, MMP-9, and VCAM. IL-6R and hsCRP were analyzed using single biomarker ELISA kits from ICL, Inc, Hycult Biotech (Uden, the Netherlands) and Sigma (St. Louis, Mo), respectively. These kits were read using a Molecular Devices E-Max plate reader and SoftMax Pro Software. The results for each biomarker were reported as numeric values. Out-of-range data as determined by the SoftMax Pro Software were excluded from the analysis. Thus, the sample size is not the same in all of the models.

Cognitive testing.

A battery of 10 standardized neuropsychological tests was administered to assess 5 cognitive domains: learning and memory, motor and processing speed, executive and visuospatial function, attention and working memory, and language (Table I). Testing was conducted by a master’s-level neuropsychologist under the supervision of a faculty neuropsychologist. Tests were administered in a quiet room and in a consistent order. The total testing time varied from 70 to 90 minutes, based on individual completion times for tests without time limits. The tests were scored by a single neuropsychologist.

Table I.

Cognitive function test battery and domains

Cognitive domain Cognitive test
Learning and memory aHopkins Verbal Learning Test-Revised32
aBrief Visuospatial Memory Test-Revised33
Motor and processing speed aTrail Making Test-Part A34
aGrooved Pegboard Test, dominant vs. nondominant hand35
Executive and visuospatial function aTrail Making Test-Part B34
aRey Complex Figure Test36
Attention and working memory aWechsler Adult Intelligence Scale-III: Digit Span Forward37
aWechsler Adult Intelligence Scale-III: Digit Span Backward27
Language bVerbal Fluency (phonemic and semantic)31
bBoston Naming Test, 2nd edition.38
Open in a new tab
a

Raw scores adjusted for age, sex, education, and race using calibrated Neuropyschological Normative System.30

b

Raw scores adjusted using Heaton.31

Statistical analysis.

The clinical characteristics are presented as percentages for categorical variables and means and standard deviations for continuous variables. Contingency table analysis using Pearson’s χ2 statistic was used to determine whether prevalence of risk factors differed between the groups (stenosis vs controls) for categorical variables. The Student t-test was used for determining the difference for continuous variables. Data analysis was performed using SAS version 9.4 (SAS Institute Inc., Cary, NC). All P values were reported as two-tailed, and significance was set at P ≤ .05.

Relationship between stenosis and cognitive function.

Raw cognitive test scores were adjusted for age, sex, education, and race, and transformed into standardized t-scores using normative data.30,31 Five cognitive domain t-scores were computed by averaging the t-scores of the relevant cognitive tests (Table I). The learning and memory domain t-score was obtained by averaging t-scores from the Hopkins Verbal Learning Test32 and the Brief Visuospatial Memory Test.33 The motor and processing speed domain t-score was obtained by averaging t-scores from Part A of the Trail Making Test34 and the Grooved Pegboard Test.35 The executive and visuospatial function domain t-score was obtained by averaging t-scores from Part B of the Trail Making Test34 and the Rey Complex Figure Test.36 The attention and working memory domain t-score was obtained by averaging t-scores from the two parts of the Wechsler Adult Intelligence Scale-III,37 the Digit Span Forward and Digit Span Backward. Finally, the language domain t-score was obtained by averaging t-scores from the Verbal fluency (Phonemic and semantic) test31 and the second edition of the Boston Naming Test.38 Independent sample Student t-tests were used to compare standardized cognitive domain t-scores between the control and stenosis groups.

Relationship between inflammation and stenosis.

Inflammatory biomarker data were log-transformed. Multivariable linear regression adjusted for age, sex, race, and coronary artery disease (CAD) was used to compare each log-transformed inflammatory biomarker level between the stenosis and control groups.

Relationship between inflammation and cognitive function.

Multivariable linear regression adjusted for CAD was used to determine the association between each log-transformed inflammatory biomarker level and each of the cognitive domain t-scores.

Relationship between stenosis and cognitive function after adjusting for inflammation.

Multivariable linear regression was used to compare each of the cognitive domain t-scores across the stenosis and control groups, adjusting for each of the inflammatory biomarkers. For each model, we present the beta estimate, which quantifies the difference in cognitive function between patients in the stenosis group and those in the control group, as well as the standard error associated with that estimate. A negative beta estimate for a cognitive domain indicates worse performance in patients with ACAS. The greater the absolute beta estimate value, the greater the difference in performance between the ACAS and control patients.

RESULTS

Clinical characteristics.

Of the 144 patients who participated in the ACCOF prospective study, 104 (63 patients with ACAS and 41 controls) had complete cognitive and inflammatory biomarker assessments and were evaluated in this cross-sectional analysis. The mean age was lower in the control group (P = .01) (Table II). The stenosis group had more white patients (P = .04) and a higher prevalence of CAD (P = .01). Patients in the control group achieved a higher education (P = .01). There were no significant differences across the two groups in the remaining clinical characteristics.

Table II.

Clinical characteristics of patients

Risk factors Asymptomatic
 P value
Carotid stenosis (n = 63) Controls (n = 41)
Age, years 69.4 ± 7 65.5 ± 6.4 .01
Male sex 98% 95 .56
White race 73 51 .04
Diabetes 58 53 .68
Hypertension 90 92 .99
Dyslipidemia 73 71 .99
CADa 67 38 .01
Peripheral vascular disease 59 44 .19
Smoking 76 74 .82
Antiplatelet treatment 75 61 .19
Lipid-lowering treatmentb 92 93 .99
Education, years 12.2 ± 2.2 13.3 ± 1.8 .01
Stenosis side
 Left 41.3 - -
 Right 58.7 - -
Open in a new tab

CAD, Coronary artery disease.

Categorical variables are presented as percentages.

Continuous variables are presented as mean ± standard deviation.

Boldface entries indicate values that are statistically significant (P < .05).

a

Coronary artery disease was defined as a positive history of myocardial infarction or angina.

b

Use of lipid-lowering medication was recorded only in those who were noted to have dyslipidemia.

Relationship between carotid stenosis and cognitive function.

After adjusting for age, sex, race, and education based on standardized normative data, patients with ACAS had significantly lower scores indicating worse performance on tests assessing the cognitive domains of learning and memory (P = .05) and motor and processing speed (P = .002) (Table III). No significant differences were noted in the domains of executive and visuospatial function, attention and working memory, or language.

Table III.

Domain-specific cognitive function in patients with asymptomatic carotid atherosclerotic stenosis (ACAS) versus control patients with similar vascular risk factors

Asymptomatic
Cognitive domain tested Carotid stenosis (n = 63) Controls (n = 41) P value
Learning and memory 44.3 (8.3) 47.4 (7.1) .05
Motor and processing speed 43.5 (8.1) 48.8 (8.3) .002
Executive and visuospatial function 41.7 (8.8) 44.2 (7.2) .13
Attention and working memory 47.0 (9.1) 47.9 (9.5) .64
Language 49.9 (7.8) 50.8 (7.3) .58
Open in a new tab

Values are mean (standard deviation).

Boldface entries indicate statistical significance.

Scores have been adjusted for age, sex, race, and education based on standardized normative data.

Relationship between inflammation and carotid stenosis.

Inflammatory biomarker levels for IL-1β, IL-6, and IL-17 were significantly lower among patients with ACAS compared with controls after adjusting for age, sex, race, and CAD (P < .0001, P = .05, and P = .001 respectively). The other inflammatory biomarkers did not demonstrate significant relationships with stenosis.

Relationship between inflammation and cognitive function.

IL-6 (P = .05) and IL-17 (P = .05) levels were directly related to attention and working memory, whereas MMP-7 (P = .02) and MMP-9 (P = .04) levels were inversely correlated. There were no significant relationships between any of the 12 inflammatory biomarkers and motor and processing speed or executive and visuospatial function. MMP-7 levels were inversely correlated with learning and memory (P = .04); no other inflammatory biomarkers reached statistical significance in this domain. MMP-7 and hsCRP levels were inversely correlated with language (P = .03, P = .01 respectively); none of the other 10 biomarkers demonstrated a significant relationship with cognition.

Relationship between carotid stenosis and cognitive function after adjusting for inflammation.

We analyzed the two neuropsychological domains in which worse cognitive function was noted in patients with ACAS: learning and memory, and motor and processing speed (Table III). The association between stenosis and lower scores in the learning and memory domain either remained significant or trended toward significance (P = .03–.08), even after adjusting for each inflammatory biomarker tested. Similarly, the association between the presence of stenosis and lower scores in the motor and processing speed domain remained either significant or close to significant (P = .02–.06), even after adjusting for each of the inflammatory biomarkers tested. Estimates for effect size can be found in Table IV.

Table IV.

Difference in cognitive domain scores in asymptomatic carotid atherosclerotic stenosis (ACAS) patients versus those without stenosis after adjusting for systemic inflammation

No. Learning and memory
 Motor and processing speed
Stenosis β (SE) P value Stenosis β (SE) P value
IL-1β 71 −4.8 (2.3) .04 −5.7 (2.5) .02
IL-6 78 −3.4 (1.9) .08 −4.2 (2) .04
IL-6R 86 −4.0 (1.8) .03 −3.9 (1.9) .05
IL-8 86 −4.0 (1.8) .03 −3.8 (1.9) .05
IL-17 83 −3.7 (2) .07 −4.7 (2.1) .03
TNF-α 86 −4 (1.8) .03 −3.9 (1.9) .05
MMP-1 86 −3.7 (1.8) .04 −3.8 (1.9) .05
MMP-2 86 −4.0 (1.8) .03 −3.6 (1.9) .06
MMP-7 83 −3.4 (1.8) .07 −4.7 (1.9) .02
MMP-9 71 −3.6 (2) .07 −4.5 (2.1) .04
VCAM 86 −4.1 (1.8) .03 −3.9 (1.9) .05
hsCRP 86 −3.8 (1.8) .04 −3.7 (1.9) .05
Open in a new tab

hsCRP, High-sensitivity C-reactive protein; MMP, matrix metalloproteinase; standard error; TNF, tumor necrosis factor; VCMA, polyvinyl chloridemethyl acrylate.

β is the beta estimate or the difference in cognitive function score in the patients with asymptomatic carotid stenosis compared with controls after adjusting for coronary artery disease and the cytokine listed in the first column; negative values indicate worse performance in patients with ACAS.

P values represent the probability that the observed relationship between cognitive function and the presence of stenosis, after adjusting for inflammation and coronary artery disease, is actually due to random variation alone.

Boldface entries indicate values that are statistically significant (P < .05).

DISCUSSION

There is growing evidence that asymptomatic carotid stenosis is associated with cognitive impairment.3,6,18–20 The development of therapeutic strategies to address cognitive impairment requires the identification of mechanisms underlying the observed deficits. In this study, we demonstrate that carotid stenosis remains an independent predictor of cognitive dysfunction, even after adjusting for inflammation, with impairments primarily seen in the cognitive domains of learning and memory, and motor and processing speed. To our knowledge, this study is first to demonstrate the persistence of cognitive impairments in patients with ACAS when compared with controls with similar vascular risk factors, even after adjusting for systemic inflammation.

We did not observe a consistent association between inflammatory biomarker levels and the presence of carotid stenosis. Although there is convincing evidence that atherosclerosis is associated with elevated systemic inflammation,21–24,39 the literature is much more limited and mixed with regard to the association between carotid atherosclerosis and systemic inflammation. One study demonstrated higher serum concentrations of IL-6, fibrinogen, and CRP in individuals with asymptomatic carotid stenosis when compared with healthy controls.40 Another showed higher levels of hsCRP, VCAM, and IL-6 in patients scheduled for carotid endarterectomy versus age- and sex-matched controls.26 As opposed to the healthy controls in prior reports, the control group in the present study was composed of patients with vascular risk factors, but no carotid stenosis. Patients with vascular risk factors including atherosclerosis, hyperlipidemia, hypertension, diabetes, and the metabolic syndrome are known to have elevated levels of systemic inflammatory biomarkers.21,22,41–46 The inflammatory biomarker levels in our study support these reports. For example, the mean IL-6 and hsCRP concentrations for our control group were both higher than what is reported in patients without vascular risk factors. The mean IL-6 and hsCRP values were 41,820 pg/mL and 37,989 ng/mL, respectively, whereas values in healthy patients without vascular risk factors are normally below 5 pg/mL for IL-646 and between 200 and 680 ng/mL for hsCRP.47 Thus, the presence of vascular risk factors in our control group may explain why we did not see a significant difference in inflammation between our control and stenosis groups. Regardless, the finding of cognitive dysfunction in the stenosis group compared with the control group despite no significant difference in inflammatory biomarker levels between groups argues that inflammation is unlikely to be the primary mechanism behind the cognitive deficits in patients with carotid stenosis.

Although there were some associations noted between specific biomarkers and certain cognitive domains, no consistent patterns were observed between inflammatory biomarker levels and cognitive function in our patients. Conversely, in the Health, Aging and Body Composition study, patients with the highest serum IL-6 or CRP tertile had a baseline Modified Mini-Mental Status Examination score that was on average two points lower compared with those in the lowest tertile.48 A meta-analysis of 5717 participants showed that increased levels of CRP and IL-6 were associated with a 45% and 32% increased risk of dementia, respectively.7 These studies demonstrate the association between inflammation and global cognition as measured by a cognitive screening test; however, they do not test the association between inflammation and more specific cognitive domains, such as those assessed in our study. This difference in study design may explain why we did not see significant overarching associations between inflammatory biomarker levels and cognitive function.

Studies evaluating individual cognitive domains are far more limited and heterogenous. The Memory and Morbidity in Augsburg Elderly Study showed that higher levels of IL-8 were associated with poorer performance in memory, speed, and motor function.21 Our study did not demonstrate any association between IL-8 levels and cognitive domain scores. Associations have also been demonstrated between elevated CRP levels and worse performance in executive and visuospatial function, learning and memory, and language.49,50 We did find that higher hsCRP levels were associated with worse function in the language domain. Finally, elevated IL-6 has been associated with reduced domain scores for abstraction and language.50 We did not observe this association in our patients. The differences in our findings compared with the cited studies may be due to differences in patient populations, study design, and the measures used to assess cognitive domains. Standardization of the cognitive assessment in this patient population is necessary to definitively determine the association between inflammatory biomarker levels and cognitive function. Regardless, based on the collective body of literature demonstrating a relationship between increased inflammation and lower cognitive domain scores, we felt it imperative to determine whether levels of systemic inflammation were driving the cognitive impairments seen in our patients with ACAS.

Even after we adjusted for inflammatory biomarker levels in our multivariable models, we found that impairments in the cognitive domains of learning and memory and motor and processing speed persisted. This finding indicates that mechanisms other than inflammation are important in generating the cognitive impairments observed in patients with asymptomatic carotid stenosis. Alternative mechanisms that may underlie cognitive impairments observed in patients with ACAS include cerebral hemodynamic impairment as a result of diameter-reducing carotid plaque coupled with inadequate cross-collateralization, and silent brain infarction or subclinical microembolization. Although these mechanisms were not evaluated in the current analysis, our prior publication in a similar cohort did not find a correlation between microembolization on transcranial Doppler (TCD) examination and cognitive impairment. Further, a recently published systematic review found no clear association between cognitive impairment in patients with ACAS and microembolization on TCD examination or white matter hyperintensities on magnetic resonance imaging.51 Studies, including our own, have demonstrated a correlation between impaired cerebral perfusion measures and cognitive impairments in patients with ACAS.22,23,52 Although cerebral perfusion was not directly assessed in the ACCOF study, we used TCD examination to assess the breath-holding index as an indirect measure of cerebral perfusion. We found that 40% of patients with ACAS demonstrated a breath-holding index of <0.69, and that this finding was associated with worse performance in several cognitive domains.3 Our recently published analysis of a different patient cohort demonstrated that 16 of 18 patients with ≥70% ACAS exhibited impaired cerebral perfusion to the ipsilateral hemisphere on magnetic resonance imaging.52 Furthermore, some studies also suggest that increased cerebral perfusion is associated with improved cognitive performance after carotid revascularization,24–26,28 supporting the notion that hypoperfusion may be an underlying mechanism. Although these data provide preliminary evidence, further studies are necessary and ongoing to delineate the exact mechanisms leading to cognitive impairment in patients with ACAS.

The results from the current study are significant; the association between cognitive impairment in patients with ACAS and systemic inflammation has not been reported previously. Our findings indicate that inflammation is unlikely to be the primary mechanism underlying cognitive impairments in patients with ACAS. Because this work is a proof-of-concept study, these findings do not completely eliminate inflammation as a contributor to cognitive dysfunction in carotid stenosis, but rather confirm that alternate mechanisms are also contributing to the impairment. This finding is clinically relevant because it furthers the argument that targeted therapies at improving cerebral perfusion, for instance, could mitigate or prevent cognitive declines in this patient population.

Our study is limited; it is a cross-sectional assessment. In addition, inflammatory biomarker levels are variable, and their measurements can be affected by multiple factors for which we may not have controlled. We did, however, test levels on fasting blood samples obtained in the morning to minimize variability. In addition, the SoftMax Pro Software used to obtain the inflammatory biomarker concentrations either provided adjudicated numerical values or a non-numerical out-of-range reading for markers that were on the upper or lower limit of the reading range. During our analysis, adjudicated values were used for the analysis, which may have decreased variance. Measurements that were found to be out of range for the biomarker tests were excluded, which could have skewed the results. To account for this factor, we also adjudicated the non-numeric, out-of-range values to the highest and lowest detected values. Sensitivity analyses with those values provided similar results. To avoid redundancy, those analyses are not presented in this article. In addition, given that many models were evaluated, we must recognize the potential for multiplicities identifying relationships that may not in fact be present. Finally, although cognitive dysfunction remains significant or nearly significant after adjusting for inflammation in this study, a larger analysis is needed to strengthen the findings from our group. Despite these limitations, this serves study as a valuable exploratory work to evaluate the role of inflammation in cognitive dysfunction observed in patients with ACAS.

CONCLUSIONS

Patients with ACAS demonstrate impairment in learning and memory, and motor and processing speed. These cognitive impairments persist after accounting for systemic inflammation. These findings suggest that inflammation is not the primary mechanism underlying the cognitive impairments observed in patients with ACAS, and underscores the need for further research to delineate the exact mechanisms leading to cognitive impairment. Further research is also needed to elucidate whether the presence of cognitive impairment should be an indication for carotid stenosis screening and/or carotid revascularization. The current study adds to the evidence prompting future investigations, which could address these key points.

ARTICLE HIGHLIGHTS.

  • Type of Research: Single-center prospective observational study.

  • Key Findings: Compared with controls with vascular risk factors (n = 41), patients with asymptomatic carotid stenosis (n = 63) demonstrated lower scores in the domains of learning and memory (P = .03–.08) and motor and processing speed (P = .02–.06), even after adjusting for inflammatory biomarker levels.

  • Take Home Message: Cognitive impairments in patients with asymptomatic carotid stenosis persist after accounting for the systemic inflammation observed in these patients. These findings suggest that systemic inflammation is not the primary mediator of cognitive impairment observed in this subset of patients.

Acknowledgments

Funded by the Veterans Affairs Merit Award CSRD CX000407 to B.K.L. B.K.L is also funded by Veterans Affairs awards HSRD C19-20-407, RRD RX000995 and CX001621, and National Institutes of Health (NIH) awards NS080168, NS097876, and AG000513. J.D.S. is also funded by the NIH awards AG028747, DK072488, and Baltimore VA Medical Center GRECC.

Footnotes

Author conflict of interest: none.

The editors and reviewers of this article have no relevant financial relationships to disclose per the JVS policy that requires reviewers to decline review of any manuscript for which they may have a conflict of interest.

REFERENCES

  • 1.Colgan MP, Strode GR, Sommer JD, Gibbs JL, Sumner DS. Prevalence of asymptomatic carotid disease:results of duplex scanning in 348 unselected volunteers. J Vasc Surg 1988;8:674–8. [DOI] [PubMed] [Google Scholar]
  • 2.de Weerd M, Greving JP, de Jong AWF, Buskens E, Bots ML. Prevalence of asymptomatic carotid artery stenosis according to age and sex: systematic review and metaregression analysis. Stroke 2009;40:1105–13. [DOI] [PubMed] [Google Scholar]
  • 3.Lal BK, Dux MC, Sikdar S, Goldstein C, Khan AA, Yokemick J, et al. Asymptomatic carotid stenosis is associated with cognitive impairment. J Vasc Surg 2017;66:1083–92. [DOI] [PubMed] [Google Scholar]
  • 4.Johnston SC, O’Meara ES, Manolio TA, Lefkowitz D, O’Leary DH, Goldstein S, et al. Cognitive impairment and decline are associated with carotid artery disease in patients without clinically evident cerebrovascular disease. Ann Intern Med 2004;140:237–47. [DOI] [PubMed] [Google Scholar]
  • 5.Romero JR, Beiser A, Seshadri S, Benjamin EJ, Polak JF, Vasan RS, et al. Carotid artery atherosclerosis, MRI indices of brain ischemia, aging, and cognitive impairment: the Framingham study. Stroke 2009;40:1590–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Balestrini S, Perozzi C, Altamura C, Vernieri F, Luzzi S, Bartolini M, et al. Severe carotid stenosis and impaired cerebral hemodynamics can influence cognitive deterioration. Neurology 2013;80:2145–50. [DOI] [PubMed] [Google Scholar]
  • 7.Lyketsos CG, Lopez O, Jones B, Fitzpatrick AL, Breitner J, Dekosky S. Prevalence of neuropsychiatric symptoms in dementia and mild cognitive impairment: results from the cardiovascular health study. JAMA 2002;288:1475–83. [DOI] [PubMed] [Google Scholar]
  • 8.Tabert MH, Albert SM, Borukhova-Milov L, Camacho Y, Pelton G, Liu X, et al. Functional deficits in patients with mild cognitive impairment: prediction of AD. Neurology 2002;58:758–64. [DOI] [PubMed] [Google Scholar]
  • 9.Albert SM, Glied S, Andrews H, Stern Y, Mayeux R. Primary care expenditures before the onset of Alzheimer’s disease. Neurology 2002;59:573–8. [DOI] [PubMed] [Google Scholar]
  • 10.Petersen RC, Stevens JC, Ganguli M, Tangalos EG, Cummings JL, Dekosky ST. Practice parameter: early detection of dementia: mild cognitive impairment (an evidence-based review). Report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 2001;56:1133–42. [DOI] [PubMed] [Google Scholar]
  • 11.Petersen RC. Mild cognitive impairment as a diagnostic entity. J Intern Med 2004;256:183–94. [DOI] [PubMed] [Google Scholar]
  • 12.Edland SD, Rocca WA, Petersen RC, Cha RH, Kokmen E. Dementia and Alzheimer disease incidence rates do not vary by sex in Rochester, Minn. Arch Neurol 2002;59:1589–93. [DOI] [PubMed] [Google Scholar]
  • 13.Plassman BL, Langa KM, Fisher GG, Heeringa SG, Weir DR, Ofstedal MB, et al. Prevalence of cognitive impairment without dementia in the United States. Available at: http://hrsonline.isr.umich.edu/adams/overview/summary_2.htm. Accessed July 15, 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Koyama A, O’Brien J, Weuve J, Blacker D, Metti AL, Yaffe K, et al. The role of peripheral inflammatory markers in dementia and alzheimer’s disease: a meta-analysis. J Gerontol A Biol Sci Med Sci 2013;68:433–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Simone MJ, Tan ZS. The role of inflammation in the pathogenesis of delirium and dementia in older adults: a review. CNS Neurosci Ther 2011;17:506–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Yaffe K, Lindquist K, Penninx, Simonsick EM, Pahor M, Kritchevsky S, et al. Inflammatory markers and cognition in well-functioning African-American and white elders. Neurology 2003;61:76–80. [DOI] [PubMed] [Google Scholar]
  • 17.Stojkovska I, Wagner BM, Morrison BE. Minireview Parkinson’s disease and enhanced inflammatory response. Exp Biol Med 2015;240:1387–95. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Kawamoto Y, Akiguchi I, Tomimoto H, Shirakashi Y, Honjo Y, Budka H. Upregulated expression of 14-3-3 proteins in astrocytes from human cerebrovascular ischemic lesions. Stroke 2006;37:830–5. [DOI] [PubMed] [Google Scholar]
  • 19.Saggu R, Schumacher T, Gerich F, Rakers C, Tai K, Delekate A, et al. Astroglial NF-kB contributes to white matter damage and cognitive impairment in a mouse model of vascular dementia. Acta Neuropathol Commun 2016;4:76. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Glass C, Witztum JL. Atherosclerosis: the road ahead review. Cell 2001;104:503–16. [DOI] [PubMed] [Google Scholar]
  • 21.Paoletti R, Gotto AM, Hajjar DP. Inflammation in atherosclerosis and implications for therapy. Circulation 2004;109(23 Suppl 1):III50–7. [DOI] [PubMed] [Google Scholar]
  • 22.Libby P Inflammation in atherosclerosis. Nature 2002;420:868–74. [DOI] [PubMed] [Google Scholar]
  • 23.Lusis AJ. Atherosclerosis. Nature 2000;407:233–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Wong BW, Meredith A, Lin D, McManus BM. The biological role of inflammation in atherosclerosis. Can J Cardiol 2012;28:631–41. [DOI] [PubMed] [Google Scholar]
  • 25.Wang TJ, Nam B-H, Wilson PWF, Wolf PA, Levy D, Polak JF, et al. Association of C-reactive protein with carotid atherosclerosis in men and women: the Framingham Heart Study. Arterioscler Thromb Vasc Biol 2002;22:1662–7. [DOI] [PubMed] [Google Scholar]
  • 26.Debing E, Peeters E, Demanet C, De Waele M, Van den Brande P. Markers of inflammation in patients with symptomatic and asymptomatic carotid artery stenosis: a case-control study. Vasc Endovascular Surg 2008;42:122–7. [DOI] [PubMed] [Google Scholar]
  • 27.Beeri MS, Ravona-Springer R, Silverman JM, Haroutunian V. The effects of cardiovascular risk factors on cognitive compromise. Dialogues Clin Neurosci 2009;11:201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Brott T, Adams HP Jr, Olinger CP, Marler JR, Barsan WG, Biller J, et al. Measurements of acute cerebral infarction: a clinical examination scale. Stroke 1989;20:864–70. [DOI] [PubMed] [Google Scholar]
  • 29.Grant EG, Benson CB, Moneta GL, Alexandrov AV, Baker JD, Bluth EI, et al. Carotid artery stenosis: gray-scale and Doppler US diagnosis—Society of Radiologists in Ultrasound Consensus Conference. Radiology 2003;229:340–6. [DOI] [PubMed] [Google Scholar]
  • 30.Schretlen D, Testa S, Pearlson G. Calibrated neuropsychological normative system professional manual. Lutz, FL: Psychological Assessment Resources; 2010. [Google Scholar]
  • 31.Gladsjo J, Schuman C, Evans J, Peavy G, Miller S, Heaton R. Norms for letter and category fluency: demographic corrections for age, education, and ethnicity. Lutz, FL: Psychological Assessment Resources; 1999. p. 147–78. [DOI] [PubMed] [Google Scholar]
  • 32.Benedict RHB, Brandt J. Hopkins Verbal Learning Test-Revised (HVLT-R): professional manual. Lutz, FL: Psychological Assessment Resources; 2001. [Google Scholar]
  • 33.Benedict H Brief visuospatial memory test-revised professional manual. In: Odessa F, editor. Lutz, FL: Psychological Assessment Resources; 1997. [Google Scholar]
  • 34.Reitan R Validity of the trail making test as an indicator of organic brain damage. Percept Mot Skills 1958;8:271–6. [Google Scholar]
  • 35.Ruff RM, Parker SB. Gender- and age-specific changes in motor speed and eye-hand coordination in adults: normative values for the Finger Tapping and Grooved Pegboard Tests. Percept Mot Skills 1993;76:1219–30. [DOI] [PubMed] [Google Scholar]
  • 36.Meyers J, Meyers K. Rey Complex figure and recognition trial: professional manual. Odessa, Fl: Psychological Assessment Resources; 1995. [Google Scholar]
  • 37.Wechsler D Wechsler Adult Intelligence Scale (WAIS-III). 3rd ed. San Antonio, Tex: The Psychological Corporation; 1997. [Google Scholar]
  • 38.Kaplan EF, Goodglass H, Weintraub S. The Boston Naming Test. 2nd ed. New York: Springer; 2001. [Google Scholar]
  • 39.Bäck M, Yurdagul A, Tabas I, Öörni K, Kovanen PT. Inflammation and its resolution in atherosclerosis: mediators and therapeutic opportunities. Nat Rev Cardiol 2019;16:389–406. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Puz P, Lasek-Bal A, Ziaja D, Kazibutowska Z, Ziaja K. Inflammatory markers in patients with internal carotid artery stenosis. Arch Med Sci 2013;9:254–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Ridker PM. Hyperlipidemia as an instigator of inflammation: inaugurating new approaches to vascular prevention. J Am Heart Assoc 2012;1:3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.De Miguel C, Rudemiller NP, Abais JM, Mattson DL. Inflammation and hypertension: new understandings and potential therapeutic targets. Curr Hypertens Rep 2014;17:507. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Harrison DG, Guzik TJ, Lob HE, Madhur MS, Marvar PJ, Thabet SR, et al. Inflammation, immunity, and hypertension. Hypertension 2011;57:132–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Tsalamandris S, Antonopoulos AS, Oikonomou E, Papamikroulis GA, Vogiatzi G, Papaioannou S, et al. The role of inflammation in diabetes: current concepts and future perspectives. Eur Cardiol Rev 2019;14:50–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Lumeng CN, Saltiel AR. Inflammatory links between obesity and metabolic disease. J Clin Invest 2011;21:2111–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Giannoudis PV, Smith MR, Evans RT, Bellamy MC, Guillou PJ. Serum CRP and IL-6 levels after trauma. Not predictive of septic complications in 31 patients. Acta Orthop Scand 1998;69:184–8. [DOI] [PubMed] [Google Scholar]
  • 47.Chenillot O, Henny J, Steinmetz J, Herbeth B, Wagner C, Siest G. High sensitivity C-reactive protein: biological variations and reference limits. Clin Chem Lab Med 2000;38:1003–11. [DOI] [PubMed] [Google Scholar]
  • 48.Baune BT, Ponath G, Golledge J, Varga G, Arolt V, Rothermundt M, et al. Association between IL-8 cytokine and cognitive performance in an elderly general population-The MEMO-Study. Neurobiol Aging 2008;29:937–44. [DOI] [PubMed] [Google Scholar]
  • 49.Ravaglia G, Forti P, Maioli F, Arnone G, Pantieri G, Cocci C, et al. The clock-drawing test in elderly Italian community dwellers: associations with sociodemographic status and risk factors for vascular cognitive impairment. Dement Geriatr Cogn Disord 2003;16:287–95. [DOI] [PubMed] [Google Scholar]
  • 50.Teunissen CE, Van Boxtel MPJ, Bosma H, Bosmans E, Delanghe J, De Bruijn C, et al. Inflammation markers in relation to cognition in a healthy aging population. J Neuroimmunol 2003;134:142–50. [DOI] [PubMed] [Google Scholar]
  • 51.Paraskevas KI, Faggioli G, Ancetti S, Naylor AR. Editor’s choice - asymptomatic carotid stenosis and cognitive impairment: a systematic review. Eur J Vasc Endovasc Surg 2021;61:888–99. [DOI] [PubMed] [Google Scholar]
  • 52.Khan AA, Patel J, Desikan S, Chrencik M, Martinez-Delcid J, Caraballo B, et al. Asymptomatic carotid artery stenosis is associated with cerebral hypoperfusion. J Vasc Surg 2021;73:1611–21. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES