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Original research
Asymptomatic carotid artery stenosis is associated with increased Alzheimer’s disease and non-Alzheimer’s disease dementia risk
  1. Francesca Vitali1,2,
  2. Georgina Torrandell-Haro2,
  3. Gregory Branigan3,
  4. Juan Arias Aristizabal4,
  5. Eric Reiman5,
  6. Edward J Bedrick6,
  7. Roberta Diaz Brinton2,
  8. Craig Weinkauf4
  1. 1Neurology, The University of Arizona College of Medicine, Tucson, Arizona, USA
  2. 2Center for Innovation In Brain Science, The University of Arizona College of Medicine, Tucson, Arizona, USA
  3. 3The University of Arizona College of Medicine, Tucson, Arizona, USA
  4. 4Department of Surgery, The University of Arizona College of Medicine, Tucson, Arizona, USA
  5. 5Banner Alzheimer's Institute, Phoenix, Arizona, USA
  6. 6Center for Biomedical Informatics and Biostatistics, University of Arizona Medical Center - University Campus, Tucson, Arizona, USA
  1. Correspondence to Dr Craig Weinkauf; cweinkauf{at}surgery.arizona.edu

Abstract

Background In the absence of a cerebrovascular accident, whether asymptomatic extracranial carotid atherosclerotic disease (aECAD) affects Alzheimer’s disease (AD) and non-AD dementia risk is not clear. Understanding whether aECAD is associated with an increased risk for AD is important as it is present in roughly 10% of the population over 60 and could represent a modifiable risk factor for AD and non-AD dementia.

Methods This retrospective cohort study analysed Mariner insurance claims. Enrolment criteria included patients aged 55 years or older with at least 5 years of data and no initial dementia diagnosis. Subjects with and without aECAD were evaluated for subsequent AD and non-AD dementia diagnoses. Propensity score matching was performed using confounding factors identified by logistic regression. χ2 tests and Kaplan-Meier survival curves were used to evaluate the impact of aECAD diagnosis on AD and non-AD dementia risk over time.

Results 767 354 patients met enrolment criteria. After propensity score matching, 62 963 subjects with aECAD and 62 963 subjects without ECAD were followed through data records. The aECAD cohort exhibited an increased relative risk of 1.22 (95% CI 1.15 to 1.29, p<0.001) for AD and 1.48 (95% CI 1.38 to 1.59, p<0.001) for non-AD dementias compared with the propensity score-matched cohort without aECAD. The increased AD risk associated with aECAD was evident in patients younger than 75 years old and was less apparent in patients over 75 years of age.

Conclusions aECAD is associated with an increased risk of developing AD and non-AD dementias. These findings underscore the need for further prospective evaluation of interactions between aECAD and dementia, with potential implications for change of clinical care in both of these large patient populations.

  • Carotid Stenosis
  • Neurodegenerative Diseases
  • Risk Factors
  • Brain
  • History

Data availability statement

Data are available on reasonable request.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/svn-2024-003164

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    WHAT IS ALREADY KNOWN ON THIS TOPIC

    • Patients with asymptomatic carotid disease are not clinically evaluated for or treated for dementia-related outcomes as a standard of care. Furthermore, whether carotid stenosis, in the absence of stroke, is associated with AD risk is unknown.

    WHAT THIS STUDY ADDS

    • This study reveals that in the absence of stroke, asymptomatic carotid disease increases risk for both AD and non-AD dementia.

    HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

    • Outcomes from this study should prompt further prospective studies aimed at better testing and treatment of patients with asymptomatic carotid stenosis. Additionally, it underscores the importance of improved evaluation of carotid stenosis in patients at risk for AD and related dementias.

    Introduction

    Alzheimer’s disease (AD) is the most common form of dementia.1 As of 2022, 6.55 million people in the USA had AD alone.2 Non-Alzheimer’s dementias comprise a large group of dementias that include vascular, Lewy-Body, frontotemporal and other dementias.3 There is a growing appreciation that vascular disease and associated vascular risk factors contribute to dementia risk.4 5

    Vascular contributions to cognitive impairment and dementia (VCID) encompass a broad group of systemic vascular processes impacting brain health.4–6 Research in VCID has predominantly focused on cerebral small vessel disease (cSVD)7 8 and vascular risk factors including age, hypertension (HTN), hyperlipidaemia (HLD) and smoking.2 8–10 In contrast to cSVD, extracranial carotid atherosclerotic disease (ECAD) is characterised by large vessel atherosclerosis at the common carotid artery bifurcation and the internal carotid artery, leading to arterial stenosis.

    Emboli from ECAD can cause cerebrovascular accidents, which have immediate effects on brain tissue and cognition and are associated with a well-defined long-term risk for dementia.11 Patients with ECAD who have no recent history of stroke or transient ischaemic attack (TIA) attributed to ECAD are considered asymptomatic. The prevalence of asymptomatic ECAD (aECAD) is approximately 7.5% for moderate ECAD (defined as 50%–70% stenosis) and 3% for severe ECAD (>70% stenosis) in individuals over 60 years of age, with higher predominance in men.12 Current treatment for aECAD primarily focuses on managing comorbidities (eg, smoking, HTN, HLD and diabetes) and on stroke prevention.13 However, there is no clinical evaluation or treatment goals targeting dementia outcomes. This is due to the lack of a well-established association between aECAD and dementia.

    Few studies have focused on evaluating the impact of carotid disease on AD.14–20 Of these studies, five reported a positive association between carotid disease and AD,14–19 and one not confirming this association.20 Key limitations of these studies include (1) most rely on small cohorts; (2) use of non-clinical indicators of carotid atherosclerosis, such as carotid intima–media thickness ratio and common carotid plaque counting; (3) they do not control for cardiovascular confounders such as HTN, smoking, diabetes and heart disease and (4) inclusion of patients with both symptomatic and asymptomatic carotid disease. These studies, including the Rotterdam study,15 contributed significantly to the AD field by highlighting the importance of vascular disease and vascular risk factors in AD physiology. However, whether asymptomatic carotid stenosis is associated with AD and non-AD dementia risk remains unclear.

    Defining the association between aECAD and AD as well as other forms of dementia is crucial considering the availability of effective treatments for aECAD that are currently not used for reducing the risk of AD and non-AD dementias. Furthermore, a deeper understanding of the cognitive effects of ECAD could inform clinical trials aimed at modifying the management of carotid disease. Cognition is a critical outcome to document in the aECAD population, as cognitive dysfunction results in increased disability, dependence, decreased medication adherence, higher healthcare costs and higher caregiving needs.2

    This study evaluated the hypothesis that aECAD is associated with an elevated risk of AD and non-AD dementias leveraging longitudinal data with a US-based population insurance claims records.

    Methods

    Data source

    The Mariner database is an insurance claims dataset that serves the USA with patient populations from all US states and territories.21 Pearl Diver is for-fee research software that facilitates interaction with commercial, state-based Medicaid, Medicare stand-alone prescription drug plan, group Medicare Advantage and individual Medicare Advantage data. The Mariner dataset contains patient demographic characteristics and numerous other data points for patients with Current Procedural Terminology, International Classification of Diseases, 9th Revision (ICD-9-CM) and ICD and Related Health Problems, 10th Revision (ICD-10-CM) codes. Mariner encompasses all diagnoses and represents 161 million patients throughout the duration of the set with claims from 2010 to April 2022.

    This report follows the Strengthening the Reporting of Observational Studies in Epidemiology reporting guidelines.

    Study design and variables

    Similar to previous studies,22 23 a subset of 7 133 677 patients diagnosed with non-melanoma skin cancer was selected for medical informatic analysis from the Mariner database as this medical condition is not associated with neurodegenerative disease or cardiovascular diseases, its treatment does not require chemotherapy or surgical anaesthesia which can impact the risk of AD or non-AD dementias, and it occurs with sufficient frequency in the general population to enable robust analyses. Additionally, patients diagnosed with melanoma, the more aggressive form of skin cancer, were specifically excluded.

    The outcome variable was determined by identifying the first diagnosis of AD and non-AD dementias using ICD-9-CM and ICD-10-CM codes in the patient’s medical claims data. Detailed ICD procedural codes used to identify the diagnosis of AD and non-AD dementias are reported in online supplemental table 1.

    Supplemental material

    For the aECAD group, patients were defined as those with three or more ICD code diagnosis claims for aECAD who did not undergo carotid endarterectomy (CEA) or carotid artery stenting (CAS) surgical interventions. The ICD procedural codes for aECAD, CEA and CAS are provided in online supplemental table 1. Conversely, the control group included subjects without any aECAD or CEA or CAS ICD procedural codes. Patients younger than 55 years old, with a history of AD, dementia, brain cancer or neurosurgery were excluded from the study (ICD codes for these conditions are provided in online supplemental table 1).

    To ensure a robust population, an active enrolment criterion of a minimum of 6 months before and 5 years after the diagnosis of aECAD was required, accounting for potential factors such as patients leaving, dying or switching insurance providers (figure 1). The index dates were defined as the first record of aECAD diagnosis for the treatment group and 6 months after the first patient claim record in the database for the control group. The 6 months prior to the index date were used to calculate baseline comorbidities in both groups. A start date of 1 year after the index date was selected to survey records for AD and non-AD dementia diagnoses to focus on long-term impact on disease progression.

    Figure 1
    Figure 1

    Study design and patient breakdown.

    Statistical analysis

    Statistical analyses were conducted between 12 May 2023 and 10 January 2024. Patient demographic statistics (table 1) and incidence statistics were analysed using unpaired two-tailed t-tests or χ2 tests, as appropriate, to test the significance of the differences between continuous and categorical variables. In all analyses, a two-sided p<0.05 was considered statistically significant.

    View this table:
    Table 1

    Baseline characteristics and comorbidities of patients not diagnosed and diagnosed with aECAD

    A propensity score-matched population was generated by using a logistic regression to identify confounding factors for the diagnosis of aECAD status between the exposure and non-exposure groups. The resulting confounding factors included age, region, Charlson Comorbidity Index (CCI) rank, as well as variable comorbidities listed in online supplemental table 1. These factors were integrated into the matching process using a 1:1 ratio, matching patients in the aECAD group to those in the control (no aECAD) group to minimise confounding variables in the two populations. Kaplan-Meier survival curves for disease-free survival were created using the propensity score-matched population in the Bellwether-Pearl Diver interface.

    Patient and public involvement

    This study is a retrospective review of an insurance claims database. All data were deidentified and there was no patient involvement in the study, its design, recruitment or the outcomes. Data are publicly available with a subscription at http://www.pearldiverinc.com/.

    Results

    Of the 17 133 677 patients in the Mariner’s data subset, 767 354 met the inclusion and exclusion criteria and the claims enrolment period requirements for our study (figure 1). Of the 125 926 patients who met the propensity score matching criteria, 62 963 patients were assigned to the treatment group and 62 963 were assigned to the control group. Patients were evaluated for a diagnosis of AD or non-AD dementia 12 months after the index date (figure 1).

    Demographics and comorbidities for the unadjusted populations are summarised in table 1. In the unadjusted cohort, 207 159 individuals (mean (SD) age, 67.6 (7.1) years) were diagnosed with aECAD (defined by at least three consecutive aECAD diagnosis codes), whereas 560 195 individuals (mean (SD) age, 63.7 5.0) years) did not have any diagnosis of aECAD (table 1). The majority of patient records in the study were from individuals aged 70–74 years (table 1). There were significant differences in comorbidities between patients with aECAD and those without (asthma, 1.47% vs 9.71%; chronic obstructive pulmonary disease, 23.91% vs 26.70%; chronic kidney disease 10.60% vs 15.90%; congestive heart failure, 9.15% vs 6.72%; coronary artery disease, 45.00% vs 27.16%; deep vein thrombosis, 0.18% vs 2.02%; diabetes, 37.44% vs 35.85%; HTN, 75.64% vs 70.87%; obesity, 10.35% vs 24.98%; pulmonary heart disease, 4.08% vs 6.98% and tobacco use, 14.69% vs 25.28%) (table 1).

    Logistic regression analysis for potential confounders associated with aECAD identified the following confounding factors and comorbidities: age, gender, region, CCI score, asthma, chronic obstructive pulmonary disease, chronic kidney disease, congestive heart failure, coronary artery disease, deep vein thrombosis, diabetes, HTN, obesity, pulmonary heart disease and tobacco use (online supplemental table 1).

    Propensity score matching was used to create groups that controlled for identified confounding factors between the aECAD and control groups. Demographic characteristics and comorbidities of propensity score-matched populations are detailed in table 1. In the matched dataset, 62 963 individuals (mean (SD) age, 67.3 (2.8) years) comprised the aECAD group and were matched with an equal number of control individuals (mean (SD) age, 67.3 (2.8) years) without aECAD (table 1). Patient demographics and comorbidities, as well as CCI scores, did not exhibit statistically significant differences between the matched groups (table 1).

    Analysis of unadjusted population data indicated that a diagnosis of aECAD was associated with a significantly higher incidence of AD compared with controls (9803 (4.51%) vs 12 814 (2.17%); relative risk (RR), 2.07; 95% CI 2.02 to 2.13; p<0.001) and a significant increased risk of developing non-AD dementia (7777 (3.58%) vs 8498 (1.44%); RR 2.49; 95% CI 2.41 to 2.56; p<0.001) (figure 2a and b). Results of the χ2 analysis in the propensity score-matched populations indicated that aECAD diagnosis was associated with a significantly higher incidence of AD (2384 (3.79%) vs 1962 (3.12%); RR 1.22; 95% CI 1.15 to 1.29; p<0.001) and non-AD dementia (1879 (2.98%) vs 1271 (2.02%); RR 1.48; 95% CI 1.38 to 1.59; p<0.001) compared with controls (figure 2a and c).

    Figure 2
    Figure 2

    Relative risk (RR) of patients diagnosed with aECAD to develop AD and non-AD Dementia. (A) Statistics of the unadjusted and adjusted (propensity score-matched) cohorts. (B, C) Plots and statistics of relative risk of developing AD and non-AD dementia, respectively. aECAD was associated with a significantly increased RR for non-AD dementia compared with patients without a diagnosis of aECAD. AD, Alzheimer’s disease; aECAD, asymptomatic extracranial carotid atherosclerotic disease.

    The propensity score-matched population was used to generate Kaplan-Meier survival curves for AD-free survival and non-AD dementia-free survival to assess the rate and proportion of the population developing these conditions over a period of 5 years (figure 3a,b). Changes in disease incidence rates between patients diagnosed with aECAD and controls mirrored the χ2 analysis results. aECAD diagnosis was associated with a higher incidence and faster progression to AD (figure 3a) and non-AD dementia (figure 3b) over 5 years; CIs did not overlap in the 5-year analysis and were divergent. AD-free survival over 5 years was also stratified by age (figure 4), exhibiting a more evident increased risk in patients aged 60–74 years (figure 4a–c), where the greater risk was more apparent in those aged 70–74 years (figure 4c). In contrast, patients older than 75 years of age did not exhibit a significant difference in AD risk (figure 4d).

    Figure 3
    Figure 3

    Kaplan-Meier survival curves of AD-free survival. (A, B) Kaplan-Meier curves along with the number of patients falling in each time group for AD and non-AD dementia, respectively. aECAD, asymptomatic extracranial carotid atherosclerotic disease.

    Figure 4
    Figure 4

    Kaplan-Meier survival curves of AD-free survival by age. (A–D) Kaplan-Meier curves along with the number of AD-free survival by age 60–64 (A), 65–69 (D), 70–74 (C) and 75–79 (D). Increased risk was more evident in patients from 60–74 years of age (A–C), where the greater risk was more apparent in patients aged 70–74 years (C). In contrast, patients older than 75 years of age did not exhibit a significant difference in AD risk (D). AD, Alzheimer’s disease; aECAD, asymptomatic extracranial carotid atherosclerotic disease.

    Discussion

    The impact of AD and non-AD dementias is growing worldwide, and its incidence is expected to triple over the next three decades.2 Vascular diseases have emerged as crucial contributors to dementia risk.4 5 8 24 The majority of current research related to vascular contributions to dementia focuses on cSVD and associated cardiovascular risk factors,4–6 8 with few studies investigating the specific contribution of ECAD to dementia and none of them differentiating between asymptomatic and symptomatic ECAD.14–19 This study addressed the limitations of prior research by using US-based Mariner insurance claims of a large clinical population of 7 133 677 individuals to evaluate the specific impact of aECAD on the risk of developing AD and non-AD dementias. This approach used clinically defined carotid stenosis as a marker of carotid atherosclerosis (overcoming limitations of indirect indicators, such as carotid intima–media thickness ratio and common carotid plaque counting) and assured the exclusion of symptomatic patients with stroke or TIA. Distinguishing between symptomatic and asymptomatic carotid disease is crucial, as stroke and TIA are independent risk factors for dementia25 26 and, therefore, key confounders.

    Propensity score matching was used to mitigate potential confounders between aECAD cohort and controls. Regression analysis identified confounding factors associated with aECAD including established aECAD risk factors, such as age, HTN, HLD, smoking, statin therapy and coronary artery disease, as well as unexpected factors, such as deep vein thrombosis, asthma and pulmonary heart disease. This strategy for identifying potential confounders promotes unbiased selection. Both the unmatched and propensity score-matched aECAD cohorts exhibited similarities to those in classic carotid studies, such as the Carotid Revascularization Endarterectomy versus Stenting Trial (CREST trial, including high incidence of HTN and heart diseases.27 Interestingly, we observed slightly higher rates of diabetes and lower rates of smoking in the aECAD cohorts, which likely reflect changing demographics of the USA.

    Within the propensity score-matched 125 926 individuals, aECAD was associated with a 22% increased risk of developing AD and a 48% increased risk of developing non-AD dementias. Higher non-AD dementia risk compared with AD may be due to the inclusion of vascular dementia in this category. Furthermore, the matching approach indicated that aECAD was associated with increased risk of dementia independently of general cardiovascular diseases, suggesting that distinct mechanisms related to aECAD risk impact dementia risk.

    Potential mechanisms by which aECAD influences dementia pathophysiology include decreased cerebral perfusion, which is considered an early contributor to AD pathology including neurofibrillary tangle (NFT) and β-amyloid (Aβ) accumulation.28 29 Supporting this, previous studies have shown that aECAD is associated with cerebral hypoperfusion30 and increased NFT accumulation.31 Additionally, we hypothesise that subclinical microembolic events, which occur in 10%–15% of patients with aECAD32 and do not result in TIA or stroke, may contribute to endothelial dysfunction, blood–brain barrier impairment and neuroinflammation, all mechanisms that contributor to AD pathophysiology.33 Endothelial inflammation is another mechanism that may contribute to AD risk in individuals with aECAD. Chronic endothelial inflammation, often observed in patients with aECAD,34 35 creates a proinflammatory environment that can exacerbate vascular and neural damage. The resulting endothelial dysfunction contributes to a cycle of inflammation, oxidative stress and vascular impairment, all of which are implicated in the progression of dementia.36

    Findings from the survival analysis indicated that the largest difference in AD risk between aECAD and non-aECAD cohorts occurred in the age group of 70–74 years (figure 4), slightly younger than the typical peak age range for AD incidence, which peaks at 80 years old.37 This earlier peak aligns with evidence suggesting that combined vascular disease may accelerate AD onset and progression38 39 emphasising the importance of early aECAD diagnosis and highlighting a key window for intervention that could mitigate AD risk.

    Outcomes from this study have broad implications across medical disciplines.40 Currently, aECAD evaluation and treatment do not routinely consider neurodegenerative outcomes such as AD or non-AD dementia. Our data suggest that these outcomes are relevant and that aECAD should be regularly considered as a risk factor in AD and dementia evaluation. The intervention and treatment of AD and dementia risk factors, including aECAD, could represent a new target for risk modification and contribute to delay the onset and progression of AD and dementia. Delaying AD onset by 5 years would reduce total health and long-term care spending for people with Alzheimer’s by 33%.2 This 5-year delay is also highly relevant considering that a difference between mild and moderate dementia is loss of independent living.2

    Limitations of this study include the retrospective analysis of insurance claims, potentially excluding patients receiving service outside the database. Furthermore, insurance claims do not include indicators of carotid disease severity, therefore, the analyses reported here likely include a mixed population of subjects with both moderate and severe stenosis. Additionally, this study relied on clinical diagnoses for aECAD, AD and non-AD dementia included in the claim insurance data which may result in less reliable diagnoses than in prospective studies. To mitigate this limitation and increase the likelihood that patients have clinically relevant carotid stenosis, three consecutive diagnoses of aECAD were required for inclusion of aECAD patients in the study. Moreover, the inclusion of 62 963 patients in both propensity-matched cohorts mitigates these limitations.

    Future retrospective research could confirm, validate and address the limitations of this study by using comprehensive datasets that include both patient diagnosis, medication data, laboratory values and imaging data that quantify the severity of the carotid disease. Additionally, well-designed prospective trials will be needed to confirm the role of aECAD in dementia risk.

    In summary, this study evaluated whether asymptomatic carotid stenosis is associated with dementia risk using matched cohorts of a total of 125 926 patients from insurance claim records. The outcomes of this study indicated that aECAD is associated with an increased risk of AD and non-AD dementia over 5 years independent from other cardiovascular risks. As roughly 10% of the population over the age of 65 have aECAD, these are clinically relevant results and should prompt a closer evaluation of aECAD-specific effects on brain health and how aECAD-specific interventions can impact AD onset and progression.

    Data availability statement

    Data are available on reasonable request.

    Ethics statements

    Patient consent for publication

    Ethics approval

    This study was approved by the University of Arizona Institutional Review Board. Requirements for informed consent were waived as the data were deidentified.

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    Footnotes

    • Contributors CW is the guarantor is responsible for the overall content. Concept and design: FV, CW and EJB. Data acquisition, analysis or interpretation of data: GT-H, GB, FV, CW and EJB. Drafting of the manuscript: all authors. Critical revision of the manuscript for important intellectual content: all authors. Statistical analysis: GT-H, GB, FV and EJB. Obtained funding: CW and RDB. Administrative, technical or material support: CW. Supervision: CW.

    • Funding This study was supported by grants from the National Institute on Aging including 1R01AG070987 (Extracranial Carotid Atherosclerosis Contributions to Cognitive Impairment and Alzheimer’s Disease Risk) to CW and P01AG026572 (Peri-menopause in Brain Aging and Alzheimer’s Disease), T32AG061897 (Translational Research in Alzheimer’s Disease and Related Dementias (TRADD)) and the Women’s Alzheimer’s Movement to Dr RDB. University of Arizona Career Development Award in support of CW. Arizona Alzheimer’s Consortium (Carotid Atherosclerosis in Alzheimer’s Patients). Dick and Jan Highberger, private donation.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.