Vascular risk factors may increase the risk of developing Alzheimer’s disease comorbid with cerebral small vessel disease

To the Editor: Alzheimer’s disease (AD) is a devastating neurodegenerative disorder frequently accompanied by cerebral small vessel disease (CSVD). The presence of CSVD in AD patients can complicate and intensify the treatment of AD.[1] To date, research has inadequately addressed the comorbidity of AD and CSVD, leading to a limited understanding of their characteristics and mechanisms. Further investigation into this comorbidity may help develop specific diagnostic and therapeutic strategies for AD patients with CSVD. Risk factor intervention is a key topic in dementia prevention and treatment. A considerable proportion of both AD and CSVD are linked to modifiable risk factors, particularly vascular risk factors (VRFs). Although some studies have found no association between VRFs and AD pathology,[2] a substantial number of epidemiological and Mendelian randomization studies demonstrate a close association between VRFs and AD. The relationship between VRFs and the comorbidity of AD and CSVD remains unclear. Given that VRFs are important modifiable factors, investigating their relationship with comorbidity may be particularly valuable for understanding the mechanisms of comorbidity and disease prevention. This study aimed to explore the relationship between VRFs and comorbidity, including hypertension, diabetes mellitus, body mass index (BMI), coronary heart disease (CHD), the emerging dementia risk factor short-term blood pressure variability (BPV), and the Framingham Heart Study (FHS) score. All procedures were approved by the Ethics Committee of the Second Affiliated Hospital of Chongqing Medical University (Approval No. 2023-84), and written informed consent was obtained from all participants. Participants with AD, with CSVD, and controls admitted to the Neurology Department of the Second Affiliated Hospital of Chongqing Medical University from January 2022 to August 2023 were enrolled. AD participants met the diagnostic criteria for Alzheimer’s clinical syndrome and the diagnostic requirements for mild cognitive impairment and dementia as defined by the National Institute on Aging-Alzheimer’s Association in 2018. These participants had a Mini-Mental State Examination (MMSE) score of ≤26 points. CSVD diagnosis primarily relied on imaging findings, including white matter hyperintensities (WMH), lacunar infarcts (LI), and severe enlarged perivascular spaces (EPVS), following the Standards for Reporting Vascular Changes on Neuroimaging criteria; participants with other brain disorders were excluded. In the control group, participants were in good physical health, had normal brain magnetic resonance imaging (MRI) results or only mild WMH with Fazekas grade 1, no cognitive complaints, and normal neuropsychological assessments (MMSE score ≥27 points). Participants with AD were further classified into the pure AD and AD + CSVD groups based on the presence of the following criteria: (1) the presence of two or more imaging markers of CSVD, including WMH, LI, and severe EPVS in the basal nuclei or centrum semiovale (grades 3–4); or (2) moderate to severe WMH (Fazekas grades 2–3). The indicators collected in this study included: (1) demographic data; (2) VRFs, including hypertension, diabetes mellitus, hypercholesterolemia, CHD, and BMI; office-based Framingham Heart Study (FHS1) and traditional risk factors-based Framingham Heart Study score (FHS2) scores were calculated to assess vascular risk, both of which are sex-specific; (3) medication use; (4) MMSE and Bristol Activities of Daily Living Scale (ADL) scores; (5) brain MRI data, including the severity of WMH, EPVS, medial temporal lobe atrophy (MTA) grades, and the presence of LI; and (6) for participants newly enrolled from January 2023 to August 2023, a 24-h ambulatory blood pressure monitoring was performed. Average ambulatory blood pressure (BP) and BPV were collected. All statistical analyses were conducted using R programming (version 4.2.2, Vienna, Austria). Statistical significance was set at a P-value <0.05. Binary logistic regression analysis was employed to investigate the association between VRFs and the diagnosis of AD + CSVD, with the control, CSVD, and pure AD groups as respective references for the outcome variable. The models included the following predictors: (1) age, sex, hypertension, diabetes mellitus, hypercholesterolemia, CHD, BMI, and years of education; (2) FHS1 score; or (3) FHS2 score and BMI. Supplementary Figure 1 [https://links.lww.com/CM9/C634] displays the study flowchart. Altogether, 99 cases of AD + CSVD, 102 cases of pure AD, 87 cases of CSVD, and 90 controls were recruited. Participants with AD + CSVD were older compared to the other groups [Supplementary Table 1, https://links.lww.com/CM9/C634]. Compared to controls, those with AD + CSVD had a higher prevalence of hypertension, lower hemoglobin levels and BMI, higher FHS and ADL scores, and lower MMSE scores. Compared to CSVD participants, those with AD + CSVD had lower BMI, lower MMSE scores, and higher ADL scores. Compared to pure AD participants, those with AD + CSVD had a higher prevalence of hypertension and a higher FHS score. The MTA grades and small vessel disease imaging markers in the AD + CSVD group were comparable to those in the pure AD and CSVD groups, respectively [Supplementary Tables 2 and 3, https://links.lww.com/CM9/C634]. Compared to the control, CSVD, and pure AD groups, the AD + CSVD group also exhibited higher systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP) variability [Supplementary Table 4, https://links.lww.com/CM9/C634]. These characteristics indicated that patients with comorbidity experience physical deterioration and fragility, underscoring the need for special attention and care. When using the control group as the reference for the outcome variable, logistic regression revealed that age (odds ratio [OR] 1.22, 95% confidence interval [CI]: [1.15, 1.30], P <0.001) and hypertension (OR: 4.65, 95% CI: [1.98, 11.65], P <0.001) were associated with higher odds of AD + CSVD, whereas CHD (OR: 0.31, 95% CI: [0.10, 0.87], P = 0.028) and BMI (OR: 0.85, 95% CI: [0.75, 0.97], P = 0.015) were associated with lower odds of AD + CSVD [Table 1]. After adjusting for the use of antiplatelet and statin medications, the association between CHD and AD + CSVD became insignificant (P = 0.264). When using the CSVD group as the reference, age (OR: 1.13, 95% CI: [1.08, 1.20], P <0.001) and hypercholesterolemia (OR: 2.49, 95% CI: [1.09, 5.96], P = 0.034) were associated with higher odds of AD + CSVD, while BMI (OR: 0.89, 95% CI: [0.79, 0.99], P = 0.041) was associated with lower odds of AD + CSVD. When using the pure AD group as the reference, age (OR: 1.12, 95% CI: [1.07, 1.18], P <0.001) and hypertension (OR: 3.33, 95% CI: [1.67, 6.85], P <0.001) were associated with higher odds of AD + CSVD. Additionally, when age was categorized into three groups (reference: 50–64 years, 65–74 years, and ≥75 years), in all models, being aged ≥75 years was associated with higher odds of comorbidity [Supplementary Table 5, https://links.lww.com/CM9/C634]. Both FHS1 and FHS2 scores were associated with AD + CSVD risk, with the likelihood ratio test indicating that combining FHS2 scores with BMI provided superior performance in predicting AD + CSVD risk compared to FHS1 scores. Additionally, higher SBP and PP variability were associated with higher odds of AD + CSVD rather than pure AD [Supplementary Table 6, https://links.lww.com/CM9/C634]. Table 1 - Association between VRFs and the risk of comorbidity between AD and CSVD. Variables OR (95% CI) P values Outcome reference: controls Age 1.22 (1.15, 1.30) <0.001 Hypertension 4.65 (1.98, 11.65) <0.001 CHD 0.31 (0.10, 0.87) 0.028 BMI 0.85 (0.75, 0.97) 0.015 FHS1* 1.20 (1.11, 1.31) <0.001 FHS2† 1.23 (1.13, 1.34) <0.001 BMI† 0.82 (0.73, 0.91) <0.001 Outcome reference: CSVD Age 1.13 (1.08, 1.20) <0.001 Hypercholesterolemia 2.49 (1.09, 5.96) 0.034 BMI 0.89 (0.79, 0.99) 0.041 FHS1* 1.05 (0.98, 1.14) 0.152 FHS2† 1.00 (0.93, 1.08) 0.905 BMI† 0.84 (0.76, 0.93) 0.001 Outcome reference: pure AD Age 1.12 (1.07, 1.18) <0.001 Hypertension 3.33 (1.67, 6.85) <0.001 FHS1* 1.19 (1.10, 1.29) <0.001 FHS2† 1.14 (1.06, 1.22) <0.001 BMI† 0.96 (0.87, 1.06) 0.429 *Represented the regression model with FHS1 score as predictor. †Represented the regression model with FHS2 score and BMI as predictors. AD: Alzheimer’s disease; BMI: Body mass index; CHD: Coronary heart disease; CI: Confidence interval; CSVD: Cerebral small vessel disease; FHS1 score: Office-based Framingham risk score; FHS2 score: Traditional risk factors-based Framingham risk score; OR: Odds ratio; VRFs: Vascular risk factors. Our study suggested that aging and VRFs, including hypercholesterolemia, hypertension, short-term BPV, CHD, BMI, and FHS score, were associated with the risk of clinically diagnosed comorbidity of AD and CSVD. Aging may exacerbate AD and CSVD pathology through mechanisms such as vascular aging, mitochondrial dysfunction, chronic inflammation, and oxidative stress. Hypercholesterolemia, which primarily involves atherosclerosis, is associated not only with vascular pathological changes and AD pathology but may also synergize with the apolipoprotein E (APOE) ε4 alleles to promote the occurrence of AD and vascular pathology.[3] This synergy helps explain the connection between hypercholesterolemia and comorbidity. Hypertension was also associated with comorbidity risk. Evidence suggests that hypertension may compromise the integrity of the blood-brain barrier, leading to the extravasation of vascular contents and promoting neuroinflammation,[4] which can also facilitate the Aβ deposition, thereby being associated with an increased risk of comorbidity. Additionally, BPV, particularly short-term BPV, has garnered significant attention. Short-term BPV primarily reflects the influences of central and reflex autonomic modulation. Few studies have explored the relationship between short-term BPV and AD. Our findings revealed an association between short-term BPV and AD, highlighting the potential link between autonomic nervous system dysfunction and AD. The association between CHD and AD remains debated. Logistic regression initially revealed that CHD was initially associated with a lower risk of comorbidity. However, this association became insignificant after adjusting for the use of statins and antiplatelet medications. These results indicated that statins and antiplatelet medications may ameliorate vascular pathology in CHD patients, potentially reducing the risk of developing AD + CSVD. Future research should clarify the effect of stroke prevention on AD patients with VRFs. We also found that lower BMI was linked to a lower risk of comorbidity. Previous studies have produced mixed results regarding the association between BMI and AD risk: some suggest that higher BMI reduces AD risk, while others indicate the opposite. This discrepancy may arise from interactions between AD pathology and BMI. A higher BMI might promote AD pathology, but advanced AD may reduce BMI.[5] We previously observed that in APOE ε4 carriers, BMI was positively associated with hippocampal volume and cognitive function. Therefore, maintaining a slightly higher BMI might benefit the elderly, especially those with comorbidity or APOE ε4. Additionally, using the FHS2 score (without the weight of BMI) in combination with BMI improved the predictive ability for AD + CSVD more than the FHS1 score, consistent with our prior findings. Lane et al[2] found that the office-based FHS score, which includes BMI as a negative factor for AD, was unrelated to the Aβ pathology. Given the potential protective effect of BMI on AD in the elderly, it is necessary to re-evaluate the role of BMI in future risk factor assessments to better understand the relationship between VRFs and AD. However, several flaws need to be noted. This study lacks information on APOE haplotypes, which could influence the results. Additionally, as a cross-sectional study, it cannot establish causality. In summary, our study indicated that VRFs were associated with a higher risk of clinical diagnosis of AD comorbid with CSVD. However, it is worth noting that this association may be influenced by factors such as APOE haplotypes, BMI, and the use of stroke prevention medications. Future research should explore the relationship between VRFs and AD + CSVD across different stages of cognitive decline, using diverse methodologies to gain a more comprehensive understanding of these associations. Acknowledgments We wish to thank the research participants for their contributions. Funding This research was funded grants from by the Chongqing Natural Science Fund Key Project (No. cstc2019jcyj-zdxmX0029) and the Kuanren Talents Program of the Second Affiliated Hospital of Chongqing Medical University. Conflicts of interest None.