Cerebrovascular Disease and Associations with ATN Biomarkers and Cognition in Young Onset Dementia

Background: Cerebrovascular (CVD) frequently coexist however the mechanism by which they collectively affect cognition remains unclear, particularly in young onset dementia (YOD). We investigated associations between CVD and AD biomarkers, namely amyloid, tau and neurodegeneration (ATN) in YOD, and explored how CVD and ATN interact to affect cognition. Methods: 80 YOD individuals with mild dementia, mean age 57.73 (SD = 6.01) years were recruited from a memory clinic. MRI visual ratings were used to operationalize CVD burden (CVD+) as a score >1 on the Staals CVD scale. ATN biomarkers were measured using cerebrospinal fluid (CSF) and cognition was measured using neuropsychological assessments. Results: CVD+ individuals had lower CSF Aβ 1-42 compared to CVD- (t[78] = -1.97, p = .05), while demographics, cognition, cardiovascular risk factors, brain volumes and tau were consistent across the groups. CVD+ was associated with lower CSF Aβ 1-42 (B = -.20, 95%CI: -.32 to -.08) and greater neurodegeneration, indexed as lower grey matter (B = -.15, 95%CI: -.28 to .02) and hippocampal volume (B = -.24, 95%CI: -.40 to -.04). CVD+ was not associated with p-tau or t-tau. Cognitive impairment was associated with CSF Aβ 1-42 (B = -.35, 95%CI: -.55 to -.18) but not CVD. Rather, CVD was indirectly associated with cognition via reduced CSF Aβ 1-42 , specifically with global cognition (B = -.03, 95%CI: -.09 to -.01) and memory (B = .08, 95%CI: -.09 to -.01). CVD was further indirectly associated with cognition via increased neurodegeneration in total grey matter (Global cognition: B = -.06, 95%CI: -.09 to -.03; Memory: B Conclusion: In YOD, CVD burden is linked to upstream AD mechanisms, such as CSF Aβ 1-42 , as well as downstream neurodegeneration. CVD indirectly contributes to cognitive impairment via these AD mechanisms. Clinical implications support the aggressive management of CVD to delay AD in young adults.


INTRODUCTION
Young-onset dementia (YOD) represents individuals with dementia onset before the age of 65 years. YOD is associated with greater economic burden 1 , more rapid cognitive deterioration and shorter survival compared to late-onset dementia (LOD) 2 . In addition, patients with YOD are likely to be in paid employment with significant financial commitments and with young children and elders to support. To improve clinical outcomes for this vulnerable group, it is critical to understand disease mechanisms in the young population.
The most common etiology of YOD is Alzheimer's disease (AD), followed by cerebrovascular disease (CVD) 3 . Both AD and CVD frequently co-exist and are strong predictors of cognitive impairment and dementia 4,5 . Imaging biomarkers of CVD include white matter hyperintensities (WMH), lacunes, microbleeds and periventricular spaces 6,7 . Each of these biomarkers increase the risk of cognitive impairment 8− 11 , with executive dysfunctions being the most vulnerable 12 .
Biomarkers of AD pathophysiology involve cerebrospinal fluid (CSF) Aβ 1− 42 plaque deposition, tau accumulation and neurodegeneration 13,14 , which are collectively referred to as ATN. Each ATN biomarker has been associated with cognitive decline, 15 with 60%-80% predictive sensitivity compared to healthy controls 16 .
The association between CVD and AD pathology remains controversial. Studies have shown that CVD risk factors, such as pulse pressure, hypertension and diabetes, are associated with abnormal CSF Aβ 1− 42 levels 17,18 while other studies show that CVD is associated with CSF Tau, independent to Aβ 1− 42 19 . On the other hand, several studies show that CVD is not associated with CSF Aβ 1− 42 5, 19− 22 . The interaction between Aβ 1− 42 and CVD in the process of cognitive impairment also remains unclear. Some suggest cognitive impairment includes the synergistic effect of both Aβ 1− 42 and CVD 21 , while others suggest both pathologies have independent effects on cognition 5,20,22 . Most of these studies have focused on sporadic LOD. As such, little is known about the associations of CVD with AD pathology in patients with YOD. Given young age is a strong moderator of vascular injury and AD pathology 21 it is imperative to determine the associations between CVD and AD pathophysiology, and their effect on cognition in patients with YOD.
Here, in a cross-sectional study of YOD patients with mild AD, we tested the associations of CVD and ATN biomarkers. We further investigated how CVD and ATN biomarkers interact to affect cognition using moderation and mediation models. We hypothesized that the prevalence of CVD would be associated with a greater burden of ATN biomarkers. We further hypothesized that CVD would moderate the effect of ATN biomarkers on cognition, that is strengthen the associations between ATN and cognition. We also hypothesized a mediation effect where CVD would indirectly be related to cognitive impairment via increasing burden ATN biomarkers.

Ethics approvals and patient consents
The SYNC study was approved by the Singhealth Centralized Review Board. Informed written consent was obtained from all participants according to Declaration of Helsinki and local clinical research regulations.

Measures
Demographic characteristics, including the participants' age, gender, race and years of education, were collected using a structured interview with the patient or next of kin.  37 ; and global cortical atrophy using the Pasquier scale 38 . CVD burden was calculated using the Staals score 6 which combines WMH, lacunes, microbleeds and periventricular spaces into a total CVDrelated brain damage score, ranging from 0 -4. Visual-ratings were performed by independent trained raters and any difference in rating scores were addressed and resolved by consensus.

Statistical analysis
Data preparation involved imputing variables with less than 30% missing data, based on recommendations by the American Psychological Association Task Force on Statistical Inference 39 . Multiple imputation using the five chained equations procedure was used to perform logistic regression with original weights to estimate grey matter volumes (19%% missing) using the predictors age, gender, education, MoCa, CSF Aβ 1-42 , Fazekas, lacunes, microbleeds and global cortical atrophy.
Patients were grouped as CVD burden (CVD +) based on a Staals score 6 ≥ 1 or the no CVD (CVD -) based on a Staals score of 0. Skewed variables included Staals score, ptau and total tau, and were log transformed. For variables containing 0 (Staals score), a 1 was added prior to transformation.
Main statistical analysis

1.
Group differences between patients with CVD+ and CVD-were determined for demographics, cardiovascular disease risk factors, cognition, CSF biomarkers, grey and white matter volume and CVD markers visually rated from MRI scans.
T-test was used for continuous variables, with Welsh adjustment for unequal variances, and χ 2 test used for categorical variables.

2.
Association between CVD and components of ATN were assessed using a path analysis linear regression model. All ATN components were included in one regression model in order to control for each other. Neurodegeneration was indexed as total tau, total grey matter volume (as a measure of general neurodegeneration) and hippocampal volume (as a measure of AD-specific neurodegeneration). To control for demographics and cardiovascular risk factors, the Framingham cardiovascular risk score was included as a covariate.
A post-hoc exploratory analysis investigated the association between CVD and CSF Aβ 1-42 on hippocampal atrophy.

3.
The direct association of CVD and ATN with cognition was assessed using path analysis regression models, where CVD and ATN components were the predictors and cognition was the outcome. Cognitive outcomes included global cognition, memory, executive functions and visuospatial skills, which were each assessed in independent models. All ATN components were included in each model in order to control for each other and an additional covariate included Framingham risk score. Composite scores for each cognitive domain were created by z-scoring each test and averaging the scores. Population norms were not used to create z-score because the young age range did not fit in with the locally published norms.

Moderation analysis to determine whether CVD affects the strength or direction of the relationship between ATN and cognition.
To test this a-priori hypothesis, first CVD and ATN components were centered. Next CVD was multiplied with each component of ATN to create the interaction variable. This interaction variable was the predictor in the regression analysis and cognition was the outcome, with Framingham cardiovascular risk score as the covariate.
An independent analysis was run for each CVD and ATN interaction variable, and for each cognitive outcome (global cognition and cognitive domains). A

post-hoc exploratory analysis investigated the interaction between CVD and
Aβ 1-42 with hippocampal volume as the outcome.

Mediation analysis to determine whether CVD indirectly affects cognition via
the ATN pathway. This a-priori hypothesis was tested using regression mediation models where the predictor was CVD burden, the outcome was cognitive impairment (indexed using global cognition or cognitive domains) and the mediators were CSF Aβ 1-42 , CSF tau, CSF total tau and hippocampal volume given it was the only neurodegeneration marker significantly associated with CVD. Each mediator and cognitive outcome was assessed in an independent model with Framingham cardiovascular risk as the covariate.

Data availability
Deidentified participant data will be made available upon reasonable request from the corresponding author.

Group differences
Compared

Associations between CVD and ATN
The path analysis regression model with CVD as the predictor and ATN as individual outcomes had excellent model fit according to recommended criteria 44 .

Direct associations between CVD, ATN and cognition
The path analysis regression models with CVD and ATN components as the predictors and cognition as the outcome had good model fit according to recommended criteria 44 .

The moderating role of ATN on the effect of CVD and cognition
The path analysis regression models with CVD interacting with ATN as the predictors and cognition or hippocampal volume as the outcome had excellent model fit according to recommended criteria 44 .
CVD did not interact with CSF Aβ 1-42 , ptau or total tau to affect global cognition or cognitive domains. A post-hoc analysis indicated that CVD did not interact with CSF Aβ 1-42 to affect hippocampal volumes.

The mediating role of ATN on the effect of CVD on cognition
The path analysis regression models with CVD as the predictor, ATN as the mediators and cognition or hippocampal volume as the outcome had excellent model fit according to recommended criteria 44 .
Global cognition: An indirect association was observed between CVD and global cognition, as mediated by CSF Aβ 1-42 , controlling for cardiovascular risk factors, ptau and total tau (table 2). CVD was also indirectly related to global cognition as mediated by total grey matter volume and hippocampal atrophy, while controlling for cardiovascular risk factors, CSF Aβ 1-42 and ptau.
Memory: An indirect association was observed between CVD and memory, as mediated by CSF Aβ 1-42 , while controlling for cardiovascular risk factors, ptau and hippocampal atrophy (table 2). CVD was also mediated by total grey mater volume and hippocampal atrophy in its association with memory.
Executive functions/Visuospatial functions: CVD was not indirectly related to executive functions or visuospatial functions, as mediated by ATN.

Main findings
In a young cohort of patients with mild AD, we showed that the prevalence of CVD burden was highly concomitant with the prevalence of low CSF Aβ 1− 42, even after controlling for age, gender, education, cognition, cardiovascular risk factors and grey and white matter volume. CVD was associated with lower CSF Aβ 1− 42 and greater neurodegeneration in AD specific regions, namely the hippocampus.
Meanwhile no associations were observed between CVD and p-tau or total tau.
Cognitive impairment was directly associated with low CSF Aβ 1− 42 , but not with CVD. Rather, CVD was indirectly associated with global and memory impairment via reduced CSF Aβ 1− 42 levels and increased neurodegeneration in total grey matter and specifically in the hippocampus. CVD was not found to moderate the strength or direction of the relationship between ATN and cognition. Our findings suggest that CVD is linked to the ATN pathway in patients with YOD and indirectly drives cognitive impairment via this pathway.

Associations between CVD, Amyloid and Neurodegeneration
Amyloid is believed to be first in a line of upstream effects that cause AD-related dementia 13 . Our findings suggest that in YOD patients, CVD is associated with earlier mechanisms of the AD process, namely Aβ 1− 42 deposition. Possible mechanisms of this association may involve the vascular system promoting Aβ 1− 42 aggregation 23 , restricting clearance of Aβ 1− 42 24 and causing vascular-related Aβ 1− 42 25 . Our findings in YOD are in comparison to past research in patients with LOD, where CVD was found to exhibit a more delayed effect on the ATN sequelae by affecting tau aggregation 19 . Thus it appears that in young age, CVD precipitates the AD process by influencing Aβ 1− 42 , while in old age CVD may simply lower the threshold for AD symptomology.
CVD and CSF Aβ 1− 42 were each associated with AD-pattern neurodegeneration, namely hippocampal atrophy. CVD did not interact with Aβ 1− 42 to affect hippocampal atrophy, suggesting each mechanism had an independent effect on neurodegeneration. This is consistent with previous in-vivo studies demonstrating that while hippocampal volume loss is similar between AD and small vessel disease, the cause of neural loss differs; neural loss in AD was caused by amyloid deposition and neural loss in small vessel disease was caused by microvasculature pyramidal cell loss 47 . Therefore, CVD and CSF Aβ 1− 42 may each have additive effects on ADpattern neurodegeneration, resulting from different pathogenic mechanisms.

Associations between CVD and Amyloid with Cognition
Low CSF Aβ 1− 42 was associated with memory impairment. A moderate effect size suggests that YOD patients with low Aβ 1− 42 may exhibit observable memory deficits. On the contrary, mild CVD was not directly associated with cognitive impairment nor did it interact with Aβ 1− 42 to affect cognition. CVD also did not interact with Aβ 1− 42 to affect neurodegeneration. Thus despite being associated, CVD and Aβ 1− 42 work independently to effect both cognitive impairment and neurodegeneration. Comparatively, studies with LOD cohorts have demonstrated CVD predicts cognitive decline both alone 19 and in some cases synergistically with Aβ 1− 42 21 . Thus it is likely that young age may protect against the effects of mild CVD on cognition, however may not protect against the effects of AD pathology on cognition.
One mechanism by which CVD was related to cognitive impairment was indirectly via increasing neurodegeneration and lowering CSF Aβ 1− 42 . This was observed for both global cognition and memory. The former indirect effect suggests that neural loss may be critical for CVD to manifest clinically in YOD patients. The later indirect effect suggests that while CVD is not related to clinical outcomes in YOD, it is related to other disease mechanisms such as amyloid accumulation. We further note that the size of the mediation effect was small when the outcome was global cognitive impairment, while effect size was moderate when the outcome was memory; suggesting that the effect of CVD lowering CSF Aβ 1− 42 may be most detrimental for memory functions.

Limitations and future research
We note that the current study recruited patients from the SYNC cohort that underwent lumbar puncture. As a result, patients included in the study had lower cognition and greater depressive symptoms compared to the overall SYNC cohort, resulting in selection bias towards poorer functioning patients (supplementary materials). We note that the mean CSF Aβ 1− 42 level in our cohort was in the normal range, while the Tau levels were in the abnormal range, suggesting AD in our cohort could have been predominantly Tau driven. We note that these findings are relevant to a clinic based cohort and an Asian population. We further note we did not have a comparison group. Future research would benefit from comparing YOD with LOD from a single cohort to ensure consistency in methodology.

Conclusion
In YOD patients with mild AD, CVD and low CSF Aβ 1− 42 may co-exist. Cognitive impairment in this young population was directly associated with low CSF Aβ 1− 42 , but not with CVD. Rather, CVD precipitated upstream and downstream phases of the ATN pathway, which consequently led to cognitive impairment. Thus, CVD related mechanisms may accelerate AD pathology in younger patients with negative consequences on cognition at later ages. Clinical implications support the aggressive management of CVD as a potential approach to delay AD in young adults.

Ethics approval and consent to participate
The study was approved by the Singhealth Centralized Review Board. Informed written consent was obtained from all participants according to Declaration of Helsinki and local clinical research regulations.

Consent for publication
Not applicable

Availability of data and materials
The dataset analyzed during the current study are not publically available but is available upon reasonable request from the corresponding author.

Competing interests
The authors declare that they have no competing interests   The direct and indirect effect of CVD burden on cognitive impairment, via the ATN pathway.

Supplementary Files
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