G.-X. Yu1,#, Y.-N. Ou2,#, Y.-L. Bi3, Y.-H. Ma2, H. Hu2, Z.-T. Wang2, X.-H. Hou2, W. Xu2, L. Tan1,2, J.-T. Yu4
1. Department of Neurology, Qingdao Municipal Hospital, Dalian Medical University, Dalian, China; 2. Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China; 3. Department of Anesthesiology, Qingdao Municipal Hospital, Qingdao University, China; 4. Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China; # Contributed equally to this work.
Corresponding Author: Prof. Jin-Tai Yu, Department of Neurology, Huashan Hospital, Fudan University, No. 12 Wulumuqi Road, Shanghai, China; Prof. Lan Tan, Department of Neurology, Qingdao Municipal Hospital, Dalian Medical University, No.5 Donghai Middle Road, Qingdao, China, E-mail addresses: email@example.com (J.T. Yu); firstname.lastname@example.org (L. Tan), Tel: +86 21 52888160; Fax: +86 21 62483421
J Prev Alz Dis 2021;
Published online September 20, 2021, http://dx.doi.org/10.14283/jpad.2021.55
BACKGROUND: Studies suggested that vascular dysfunction might increase the risk of developing Alzheimer’s disease (AD), but the underlying mechanisms still remain obscure.
Objective: To evaluate the associations of vascular risk burden with AD core pathologies and investigate the effects of AD core pathologies on relationships between vascular risk burden and cognitive impairments.
Design: The Chinese Alzheimer’s Biomarker and LifestyLE (CABLE) study was principally focusing on aging, as well as the risk factors and biomarkers of AD initiated in 2017.
Setting: The CABLE study was a large cohort study established in Qingdao, China.
Participants: A total of 618 non-demented elders were obtained from CABLE study.
Measurements: The general vascular risk burden was assessed by the Framingham General Cardiovascular Risk Score (FGCRS). Multivariate linear regression analyses were performed to evaluate the associations of FGCRS with cerebrospinal fluid (CSF) AD biomarkers and cognition. Casual mediation analyses were performed to investigate the mediating effects of AD biomarkers on cognition.
Results: Increased FGCRS was related to higher levels of CSF total tau (t-tau, p < 0.001), phosphorylated tau (p-tau, p < 0.001) as well as the ratio of t-tau and amyloid-β 42 (t-tau/Aβ42, p = 0.010), and lower Chinese-Modified Mini-Mental State Examination (CM-MMSE, p = 0.010) score. Stratified analysis indicated that age modified the associations, with FGCRS being significantly associated with tau pathology (p < 0.001 for t-tau and p-tau) in middle-aged group (<65 years old), instead of older group. The influences of FGCRS on cognitive impairments were partially mediated by tau pathologies (a maximum proportion of 20.9%).
Conclusions: Tau pathology might be a pivotal mediator for effects of vascular risk on cognitive decline. Early and comprehensive intervention for vascular risk factors might be a potential approach to delaying or preventing cognitive impairment and AD.
Key words: Alzheimer’s disease, vascular risk burden, biomarkers, cognitive impairment, mediation.
Alzheimer’s disease (AD) is an age-related neurodegenerative disorder which is characterized by progressive cognitive impairment. The pathologic hallmarks of AD are neuritic plaques composed of aggregated amyloid-β (Aβ), and neurofibrillary tangles (NFT) harboring hyper-phosphorylated tau and diffuse plaques (1-3). AD has traditionally been regarded as a neurodegenerative disorder affecting neurons, and vascular damage has also been implicated in AD as a potentially modifiable factor of cognitive decline (4). Autopsy studies indicated that intracranial vascular damage often co-occurred with the AD core pathologies in sporadic late-onset AD and that vascular impairment might lower the threshold for dementia (5). In addition, considering the brain’s critical dependence on finely regulated blood supply and blood-brain barrier (BBB) exchange, the vascular alterations could play an essential part in neuronal dysfunction which is a mechanism underlying dementia (6). Accumulating evidence demonstrated that vascular risk factors had a key role in the progression of AD (7). Most vascular risk factors were implicated in AD, including hypertension, diabetes mellitus, smoking and hypercholesterolemia (8-11).
It has been a challenge to establish a direct causal relationship of vascular risk burden with human core AD pathologies. The underlying mechanisms by which these risk factors worsen cognition are still unclear. This might be achieved by their direct influences on AD-related neurodegeneration, or by leading to other cerebral damage which in conjunction with ongoing neurodegeneration could result in cognitive decline (12, 13). However, AD cerebrospinal fluid (CSF) biomarkers provide an opportunity to assess the relationships between vascular risk burden and AD core pathologies. According to the 2018 National Institute on Aging-Alzheimer’s Association (NIA-AA) Research Framework (14), the AD core biomarkers included CSF Aβ42, total tau (t-tau) and phosphorylated tau (p-tau). Previous studies showed that CSF Aβ42 or tau levels changed in twenty years before AD onset (15, 16). Moreover, cognitive decline was used to stage the severity of AD according to the NIA-AA Research Framework (14). Therefore, understanding the associations of vascular risk burden with CSF AD biomarkers and cognition is critical to establishing prevention strategies in preclinical AD.
However, there were inconsistent results on the associations of vascular risk burden with AD core pathologies (13, 17-21). Framingham General Cardiovascular Risk Score (FGCRS) was a well-validated, multivariable risk algorithms of vascular risk burden (22). Herein, in a cohort of non-demented Han Chinese elders, the purposes of our research were: 1) to assess whether FGCRS was associated with CSF AD biomarkers and cognition; 2) to investigate the influences of age and sex on the above associations; and 3) to examine whether AD core pathologies mediated the effects of FGCRS on cognitive impairments.
Non-demented northern Han Chinese participants were recruited from the Chinese Alzheimer’s Biomarker and LifestyLE (CABLE) study. CABLE study is a large cohort principally focusing on aging, as well as the risk factors and biomarkers of AD since 2017. Participants were patients in several departments of Qingdao Municipal Hospital. They signed informed consent at study entry, and agreed to provide cerebrospinal fluid (CSF) and blood samples for further detection, and underwent a series of clinical and neuropsychological assessments to evaluate their cognitive status. All participants were aged from 40 to 90 years. The exclusion criteria include: 1) cranial injury, infections of the central nervous system, epilepsy, multiple sclerosis or other major neurological diseases; 2) major psychological diseases; 3) severe systemic diseases which may have influences on AD biomarkers; and 4) family history of genetic diseases. Approval of CABLE study was obtained from the Institutional Review Board of Qingdao Municipal Hospital. The present study included non-demented participants who provided adequate information to calculate FGCRS and data of core CSF biomarkers. Their cognitive diagnoses were in compliance with the NIA-AA workgroup diagnostic criteria (23). The thresholds of the adapted Chinese-Modified Mini-Mental State Examination (CM-MMSE) to exclude participants with dementia tendency were 17 for illiterate participants, 20 for participants with 1 to 6 years of education, and 24 for participants with 7 or more years of education (24).
Framingham General Cardiovascular Risk Score
FGCRS was calculated based on a weighted summary of age, sex, systolic blood pressure, treatment for hypertension, smoking attitude, total cholesterol, high-density lipoprotein cholesterol and diabetes (22). The score for age ranges from 0 to 12; systolic blood pressure -3 to 7; total cholesterol 0 to 5; high-density lipoprotein cholesterol -2 to 2; smoker 0 to 3; and diabetes 0 to 4 in woman. And in man, the score for age ranges from 0 to 15; systolic blood pressure -2 to 5; total cholesterol 0 to 4; high-density lipoprotein cholesterol -2 to 2; smoker 0 to 4; and diabetes 0 to 3. The total FGCRS ranged from -5 to 33 for woman, and ranged from -4 to 33 for man. FGCRS was a multivariable risk factor algorithm for the prediction of 10-year risk of vascular events (22). When the risk is greater than 20% (FGCRS of 17 points for women and 14 points for men), professional intervention is warranted (22).
CSF AD biomarkers
In CABLE, CSF specimens were collected in 10 ml polypropylene tubes via lumbar puncture and then transported to the laboratory within 2 hours collection. These specimens were centrifuged at 2000×g for 10 minutes and stored in an enzyme-free EP (Eppendorf) tube at -80℃. CSF Aβ42, t-tau, and p-tau levels were measured by the ELISA kit (Innotest β-AMYLOID (1-42), hTAU-Ag, and PHOSPHO-TAU (181p); Fujirebio, Ghent, Belgium) on the microplate reader (Thermo Scientific™ Multiskan™ MK3). The mean intra-batch coefficient of variation (CV) was <5% (4.9% for Aβ42, 4.5% for t-tau, and 2.4% for p-tau). The mean inter-batch CV was <15% (13.3% for Aβ42, 13.8% for t-tau, and 10.9% for p-tau).
APOE and cognitive assessment
DNA was obtained from overnight fasting blood specimens using the QIAamp®DNA Blood Mini Kit (250). APOE ε4 genotyping was conducted using restriction fragment length polymorphism (RFLP) technology on the basis of 2 specific loci associated with APOE ε4 status, rs7412 and rs429358. Participants were finally divided into APOE ε4 carriers and non-carriers. The global cognitive functioning of all the participants was assessed by CM-MMSE score. Total CM-MMSE scores ranged from 0 to 30. The greater the total score was, the better the cognitive performance was.
CSF values situated outside 3 standard deviations (SD) were excluded for further analysis. Participants were further dichotomized into high and vascular risk groups based on a cut-off of a predicted risk of 20%. Demographic factors were compared using Chi-square tests for categorical variables and Kruskal-Wallis test for continuous variables, respectively. The skewed independent or dependent variables were log10-transformed to normalize the distributions.
Multivariate linear regression analyses were used to evaluate the relationships of FGCRS with CSF AD biomarkers, with the score regarded both as continuous and dichotomous. We further calculated t-tau/Aβ42 and p-tau/Aβ42 which were regarded as better predictors of AD and cognitive impairment (25, 26). As age and sex were incorporated into FGCRS calculation, model 1 only included educational level, APOE ε4 status, CM-MMSE score, and history of stroke. We further additionally adjusted age and sex in the model 2. Age and sex were not only associated with AD, but also played an important part in vascular burden. Subgroup analyses stratified by age (mid-life stage and late-life stage based on a cut-off of 65 years old) and sex (female vs male) to investigate the effects of age and sex on the association between FGCRS and AD pathology were conducted.
We further evaluated the association between FGCRS and CM-MMSE score by multivariate linear regression analyses. Then the influences of CSF AD biomarkers on relationships between FGCRS and CM-MMSE score were assessed by a mediation analysis (27). If all the following 4 criteria were satisfied simultaneously, the mediation effects existed: 1) FGCRS was significantly associated with CSF AD biomarkers; 2) FGCRS was significantly associated with CM-MMSE score; 3) CSF AD biomarkers were significantly associated with CM-MMSE score; and 4) the relationship between FGCRS and CM-MMSE score was weakened after additional adjustment for CSF AD biomarkers. We further estimated the attenuation or indirect effect, with the significance determined using 10,000 bootstrapped iterations. Adjusted covariants included educational level, APOE ε4 status, and history of stroke in the above analyses. Statistical analyses were performed with R version 3.6.1 software. And a two-tailed p value < 0.05 was considered significant.
Characteristics of participants
The demographic characteristics of the total population included in our analysis were summarized in Table 1. A total of 618 non-demented participants were enrolled with an average age of 61.93±10.21 years, including 253 (40.9%) females and 93 (15.0%) APOE ε4 carriers. The mean FGCRS was 14.14±4.85 and there were 243 (39.3%) individuals in high vascular risk burden group.
P values of between-group comparisons were obtained using the Chi-square tests for categorical variables and Kruskal-Wallis test for continuous variables; Abbreviations: APOE, apolipoprotein E; CM-MMSE, Chinese-modified mini-mental state examination; Total-C, total cholesterol; HDL-C, high-density lipoprotein cholesterol; SBP, systolic blood pressure; FGCRS, Framingham General Cardiovascular Risk Score; Aβ42, β-amyloid 42; t-tau, total tau; p-tau, phosphorylated tau.
Associations between FGCRS and CSF AD biomarkers
We found that increased FGCRS was related to higher levels of CSF t-tau (β = 0.190, p <0.001), p-tau (β = 0.099, p <0.001) and t-tau/Aβ42 (β = 0.121, p = 0.010) after adjustment for educational level, APOE ε4 status, CM-MMSE score, and history of stroke (Model 1 in Table 2). No significant associations between FGCRS and levels of CSF Aβ42 (β = 0.069, p = 0.113) or p-tau/Aβ42 (β = 0.030, p = 0.488) were observed. Moreover, high vascular risk showed closer associations with increased levels of CSF t-tau (β = 0.046, p < 0.001), p-tau (β = 0.020, p = 0.007) and t-tau/Aβ42 (β = 0.049, p = 0.002) than low vascular risk (Figure 1B, 1C and 1D). High vascular risk group had non-significant associations with CSF Aβ42 (β = -0.003, p = 0.850) and p-tau/Aβ42 (β = 0.023, p = 0.111) levels compared with low vascular risk group (Figure 1A, 1E). In the fully adjusted model, increased FGCRS was still related to higher CSF p-tau (β = 0.059, p = 0.044; Model 2 in Table 2). The associations of FGCRS with other AD CSF biomarkers became non-significant.
Model 1 was adjusted for education level, APOE ε4 status, CM-MMSE score, and history of stroke. Model 2 was adjusted for age, sex, educational level, APOE ε4 status, CM-MMSE score, and history of stroke; * Model 1 was adjusted for education level, APOE ε4 status, and history of stroke. Model 2 was adjusted for age, sex, educational level, APOE ε4 status, and history of stroke. Abbreviations: FGCRS, Framingham General Cardiovascular Risk Score; AD, Alzheimer’s disease; CSF, cerebrospinal fluid; Aβ42, β-amyloid 42; t-tau, total tau; p-tau, phosphorylated tau, CM-MMSE, Chinese-modified mini-mental state examination; APOE, apolipoprotein E.
Compared to low vascular risk group, significant associations of increased FGCRS with higher t-tau (B), p-tau (C) and t-tau/Aβ42 (D) levels were found, but no significant relationships with Aβ42 (A) or p-tau/Aβ42 (E) levels were found. Abbreviations: FGCRS, Framingham General Cardiovascular Risk Score; AD, Alzheimer’s disease; CSF, cerebrospinal fluid; Aβ42, β-amyloid42; t-tau, total tau; p-tau, phosphorylated tau.
Subgroup analyses stratified by age and sex
Considering that age and sex not only associate with AD, but also play important roles in vascular risk burden, we conducted subgroup analyses stratified by age (mid-life stage and late-life stage based on a cut-off of 65 years old) and sex (female vs male) to investigate the effects of age and sex on the association between FGCRS and AD pathology. Results indicated that FGCRS was significantly associated with tau pathology (β = 0.159, p < 0.001 for t-tau; β = 0.120, p < 0.001 for p-tau) in middle-aged group, instead of older group (Table 3). However, sex didn’t modify the above associations. Higher FGCRS was associated with tau pathology in both female (β = 0.179, p < 0.001 for t-tau; β = 0.097, p = 0.001 for p-tau) and male (β = 0.275, p < 0.001 for t-tau; β = 0.130, p = 0.001 for p-tau) participants. FGCRS was also associated with t-tau/Aβ42 (β = 0.246, p = 0.002) in the male participants.
NOTE: Associations of FGCRS between CSF AD biomarkers and CM-MMSE score were accessed by multiple linear regression models; All models were adjusted for education level, CM-MMSE score, history of stroke and APOE ε4 status; * CM-MMSE was adjusted for education level, history of stroke and APOE ε4 status; Abbreviations: FGCRS, Framingham General Cardiovascular Risk Score; AD, Alzheimer’s disease; CSF, cerebrospinal fluid; Aβ42, β-amyloid42; t-tau, total tau; p-tau, phosphorylated tau; CM-MMSE, China-modified mini-mental state examination; APOE, apolipoprotein E.
Causal Mediation Analyses
In all individuals, there was a significant association between FGCRS and CM-MMSE score (β = -0.019, p = 0.010) after adjustment for education level, APOE ε4 status, and history of stroke. According to the above analyses, we found FGCRS was significantly associated with both tau pathologies and cognition. We further explored whether the FGCRS contributed to cognitive decline via mediating tau pathologies (Figure 2). The association of FGCRS and CM-MMSE score was weakened after separately additional adjustment for CSF t-tau, p-tau and t-tau/Aβ42 levels. Thus, tau pathology was identified as a significant mediator for effects of vascular risk burden on cognitive impairments. Moreover, we considered the effects as partial mediation. The mediation proportions were 20.9% for p-tau with a significant indirect effect (p = 0.006), 10.9% for t-tau/Aβ42 with a significant indirect effect (p = 0.017), and 15.9% for t-tau with a marginally significant indirect effect (p = 0.064).
The association between FGCRS and CM-MMSE score was mediated by tau pathologies; Abbreviations: IE, indirect effect; FGCRS, Framingham General Cardiovascular Risk Score; CM-MMSE, China-modified mini-mental state examination; Aβ42, β-amyloid42; t-tau, total tau; p-tau, phosphorylated tau.
This is a population-based cross-sectional study, which aimed to explore the associations between FGCRS and a series of AD CSF biomarkers in a cohort of non-demented Han Chinese elders. The primary findings of our research were as follows: 1) FGCRS was positively associated with tau pathologies, which was more evident in the middle-aged individuals; 2) FGCRS was negatively associated with cognitive performance; 3) the influence of FGCRS on cognitive impairments was partially mediated by tau pathologies.
Our results are in line with the finding of many previous studies that individual vascular risk burden could lead to increased tau pathologies (18, 28). Long-term exposure to vascular risk factors can lead to cerebral small vessel diseases (CSVDs), including lacunar infarcts, white matter hyperintensities (WMHs), microinfarcts, and BBB disruption. These diseases are important mechanisms underlying cognitive impairment and dementia. Increased vascular risk burden might lead to atherosclerosis, infarction and other vascular damage, therefore lowering cerebral blood flow (CBF) (29) and further resulting in increased tau pathology (30-32). Our results raised the possibility that cerebrovascular dysfunction might be associated with pre-symptomatic AD pathology (33). Nevertheless, we found no clear association between vascular risk burden and Aβ burden, which was consistent with previous studies (18, 21, 28). Our findings supported the possibility that separate amyloid and vascular pathways might both enhance neurodegeneration (34, 35). Furthermore, CSF t-tau/Aβ42 ratio has been proposed to provide more accurate risk assessments for the development of AD (26, 36). The ratio reflects two aspects of AD pathology: amyloid plaques (Aβ42) and neurodegeneration (tau) (37). P-tau is a marker of axonal damage and neuronal degeneration, and it has stronger associations with AD pathophysiology and the formation of neurofibrillary tangles than t-tau (38). However, our study found that FGCRS was related to higher levels of t-tau/Aβ42 rather than p-tau/Aβ42, possibly because a composite of vascular risk factors in the FGCRS may affect the effects of individual risk factors. Using the same analytical population of CABLE database, previous studies have found that blood pressure(39) and dyslipidemia (40) mainly affect tau pathology, whereas blood glucose (41) affects Aβ pathology. Notably, the underlying mechanisms in which vascular risk mediates Aβ or tau pathology warrant further investigation.
Higher FGCRS was associated with cognitive decline, which was in line with several large longitudinal studies (17, 18, 42). Using casual mediation analysis, we further found that tau pathology was a mediator of the effect of FGCRS on cognitive impairment. Imaging studies suggested that the influences of CBF and soluble platelet-derived growth factor receptor beta (sPDGFRβ), two biomarkers of vascular health, on global cognition were partially mediated by tau pathologies (43). Several potential mechanisms in which tau pathologies mediate the association of vascular risk burden with cognitive impairments have been identified. According to a neuropathological study, microvessels obtained from human AD prefrontal cortex with increased tau pathology upregulate genes participating in endothelial senescence and recruitment of leukocytes into the endothelium, contributing to AD-related cerebrovascular damage and decreased CBF (44). Studies also found that reduced CBF was associated with cognitive decline (45, 46). Moreover, previous studies found that vascular risk burden would become more related to CSF neurofilament light (NFL) in the context of greater CSF t-tau or p-tau levels (47). NFL was also supposed to be an AD biomarker and higher CSF NFL levels were posited to reflect axonal injury and cognitive impairment (48, 49). In conjunction with vascular risk burden, tau pathology could aggravate the impairment of nerve function. Furthermore, greater tau levels were related to decreased levels of claudin-5 (CLDN5) and occludin (OCLN) which played an important part in regulating endothelial barrier integrity (50). Decreased levels of CLDN5 and OCLN indicated BBB damage which was found to be associated with human cognitive dysfunction (51).
Although single vascular risk factors could be particularly effective in the neurovascular unit, but a cluster of them could lead to the final vascular derangement (52, 53). FGCRS was a simple and reliable instrument for assessing the general vascular risk burden, in which most indicators were preventable. It has been confirmed that FGCRS is superior to the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) dementia risk score for the application in prevention programs for evaluating cognitive impairments and targeting modifiable factors (54). Moreover, studies have shown that AD has a long asymptomatic period during which there is accumulation and progression of pathologies and brain structural changes. Symptoms appear when compensatory mechanisms have been overcome, initially as mild cognitive impairment (MCI) and ultimately as dementia (2). This present study focused on the non-demented elders might give us a hint that vascular risk factors may be mainly associated with higher CSF biomarkers in the stage without severe cognitive impairment. Till now, there is a lack of effective drugs to prevent or treat AD. Therefore, findings from this work might highlight the importance of early and integrated management of vascular risk burden to protect cognitive health or delay dementia.
There were several limitations that should be mentioned. Firstly, the associations of FGCRS with CSF AD biomarkers and cognition were only evaluated cross-sectionally in the CABLE cohort. Therefore, the temporality for the associations is unclear. Secondly, some data were obtained from self-reports of participants, such as the history of stroke and diabetes, which might lead to reporting bias. Thirdly, the CABLE is a hospital registry-based study with a specific population profile. The conclusions have a limited power to be generalizable to the general population, but the present findings may have important implications for AD prevention and early warning. Moreover, it is still controversial whether to adjust for age and sex when using the FGCRS, because these variables have been controlled for within the FGCRS calculation. Our results were obtained without correction for age and sex. Lastly, ethnic homogeneity of Chinese Northern Han subjects limited the generalizability of our findings to other studies with different ethnicities. It is necessary to further confirm our results in longitudinal cohorts with multiracial participants.
In summary, our study emphasized the close associations of vascular risk burden with tau pathologies and cognitive impairments. Tau pathologies partially mediated the influences of vascular risk burden on cognitive impairments. Our findings suggesting that early and comprehensive intervention for vascular risk factors might be a potential approach to delaying or preventing cognitive impairment and AD.
Acknowledgements: The authors thank all participants of the present study as well as all members of staff of the CABLE study for their role in data collection.
Fundings: This study was supported by grants from the National Natural Science Foundation of China (81971032), the National Key R&D Program of China (2018YFC1314700), Shanghai Municipal Science and Technology Major Project (No.2018SHZDZX01) and ZHANGJIANG LAB, Tianqiao and Chrissy Chen Institute, and the State Key Laboratory of Neurobiology and Frontiers Center for Brain Science of Ministry of Education, Fudan University.
Conflict of interest: The authors declare that they have no competing interests.
Ethical Standards: The CABLE database was conducted in accordance with the Helsinki declaration, and the research program was approved by the Institutional Ethics Committee of Qingdao Municipal Hospital. All subjects or their proxies provided written consents.
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