Cerebrospinal Fluid α-Synuclein Predicts Neurodegeneration and Clinical Progression in Prodromal Alzheimer's Disease

Accumulating reports suggest that α-synuclein is involved in Alzheimer disease (AD) pathogenesis. Cerebrospinal uid (CSF) α-synuclein could be a potential biomarker of AD. We sought to test whether CSF α-synuclein is associated with other AD biomarkers and could predict neurodegeneration and clinical progression in prodromal AD. Associations were investigated between CSF α-synuclein and other AD biomarkers at baseline in prodromal AD stage Chinese elders. The predictive values of CSF α-synuclein in longitudinal change in clinical outcomes and conversion risk of prodromal AD stage subjects were assessed using linear mixed effects models and multivariate Cox proportional hazard models, respectively, in Alzheimer's disease Neuroimaging Initiative (ADNI) database. CSF AD We found that high CSF α-synuclein level associated with high CSF t-tau (β = 0.56, P < 0.001) and p-tau (β = 0.35, P < 0.001) among nondemented subjects. However, there were no associations between CSF α-synuclein and CSF Aβ level at baseline. We also tested these relationships in subgroups. The results were the same in the CN group (CSF t-tau: β = 0.38, P < 0.001, CSF p-tau: β = 0.27, P < 0.001) and MCI group (CSF t-tau: β = 0.67, P < 0.001, CSF p-tau: β = 0.4, P < 0.001). Institute. The investigators within the ADNI contributed to the design and implementation of the ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found online (http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf).

biomarkers of neurodegeneration or neuronal injury labeled "N". [4] Besides the biomarkers mentioned above, additional novel biomarkers that re ect other disease mechanisms may provide insight into the different mechanisms implicated in AD pathogenesis and assist in identifying novel targets for therapies in the future. This was echoed by the 2018 NIA-AA research framework that "ATN" can be expanded to incorporate other proteinopathies which were also involved in AD pathogenesis or frequently co-occurred with AD pathologic changes. [5][6][7] This provided a multidimensional approach to diagnosing dementia and better clinical strati cation of patients for therapeutic trials. [8,9] α-synuclein, best known for its role in Parkinson's disease (PD) and dementia with Lewy bodies (DLB), has been reported to be implicated in AD pathogenesis. [10] Patients with AD and concomitant αsynuclein pathology typically had a more rapid rate of cognitive decline than subjects with AD alone. [11,12] α-synuclein was generally considered as pre-synaptic protein, which is also been found in human cerebrospinal uid (CSF). [13,14] Many studies found CSF α-synuclein was identi ed as an appropriate biomarker for PD and other synuclein-associated diseases, [15][16][17] especially for the diagnostic differentiation of different neurodegenerative diseases. [18,19] However, studies on the potential role of CSF α-synuclein as a biomarker for the presymptomatic phase of AD remains unclear.
In this study, we explored the associations between CSF α-synuclein and other AD biomarkers in nondemented Chinese elderly adults. We also tested whether CSF α-synuclein is altered in patients with AD and different AD pathophysiological pro les based on "ATN" classi cations and whether it is associated with other AD biomarkers, cognitive decline and imaging evidence of neurodegeneration in the ADNI database. The value of CSF α-synuclein as a predictor of disease progression and neurodegeneration at the presymptomatic stages of AD was also investigated.

Study participants
Six hundred and fty-one subjects in prodromal stage of AD who were northern Han Chinese in origin were derived from Chinese Alzheimer's Biomarker and Life style (CABLE) study. CABLE is a large cohort study mainly focusing on Alzheimer's risk factors and biomarkers in Chinese elderly adults. The samples in CABLE study were recruited at Qingdao Municipal Hospital, consisting of cognitively normal (CN) elders as well as individuals with MCI. All participants were Han Chinese in origin aged 50 to 90 years.
Controls had MiniMental State Examination (MMSE) scores of 24 or higher, where lower scores indicate more impairment and higher scores less impairment (range, 0-30), and a Clinical Dementia Rating (CDR) score of 0, where lower scores indicate less impairment and higher scores more impairment (range, 0-3). Patients with MCI had MMSE scores of 24 or higher, objective memory loss tested by delayed recall of the Wechsler Memory Scale (WMS) logical memory II (>1 SD below the normal mean), a CDR score of 0.5, preserved activities of daily living, and absence of dementia. The exclusion criteria were: (1) central nervous system infection, head trauma, epilepsy, multiple sclerosis or other major neurological disorders; (2) major psychological disorders (e.g., depression); (3) severe systemic diseases (e.g., malignant tumors) that may affect CSF or blood levels of AD biomarkers including Aβ and tau; (4) family history of genetic disease. All participants underwent clinical and neuropsychological assessments, biochemical testing, as well as blood and CSF sample collection. Demographic information, AD risk factor pro le and medical history were also collected by a comprehensive questionnaire and an electronic medical record system. Data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu), an independent replication cohort. The ADNI was launched in 2003 as a public-private partnership, led by Principal Investigator Michael W. Weiner, MD. The primary goal of ADNI has been to test whether serial magnetic resonance imaging (MRI), positron emission tomography (PET), other biological markers, as well as clinical and neuropsychological assessment can be combined to measure the progression of mild cognitive impairment (MCI) and early AD. For up-to-date information, see www.adni-info.org.
Our ADNI cohort included all CN controls, MCI patients and AD patients with available baseline CSF αsynuclein samples. Inclusion/exclusion criteria are described at http://www.adni-info.org. In our study, we strati ed the MCI group into stable MCI (sMCI) with no progression to AD dementia during at least 2-year follow-up, and progressive MCI (pMCI) with progression to AD dementia during at least 2-year follow-up. Therefore, we included the following 4 groups: CN controls, sMCI group, pMCI group and AD group. As to "ATN" binary (i.e., positive or negative) categories: amyloid positive (A+) and negative (A-) were separated by a cutoff value of 192 pg/ml for CSF Aβ level. Tau pathology positive (T+) and negative (T-) were separated by a cutoff value of 23 pg/ml for CSF phosphorylated tau (p-tau) level.
The CABLE study was approved by the Institutional Ethics Committees of Qingdao Municipal Hospital. Written informed consent was obtained from all study participants directly or from their caregivers. The ADNI study was approved by the Institutional Review Board at each of the participating centers, and all participants provided written informed consent.

CSF Measurements
CSF was taken by lumbar punctures through the L3/L4 interspace and gently mixed to avoid gradient effects. The samples were promptly centrifuged at 2000 g for 10 min to eliminate cells and other insoluble materials, aliquoted in 1 ml portions, snap frozen at -80•C until use. CSF was sampled between 08:00 and 09:00 in the morning in order to take into account a possible circadian rhythm effect. The CSF samples were stored at -80℃ until further analysis of Aβ and tau.
In CABLE study, CSF Aβ42, total tau (t-tau), p-tau and CSF total α-synuclein concentrations were measured separately using an enzyme-linked immunosorbent assay (ELISA) kit (Fujirebio, Ghent, Belgium). All the ELISA measurements were performed according to the manufacturers' instructions. The samples and standards were measured in duplicate, and the means of the duplicates were used for the statistical analyses.
In ADNI database, CSF Aβ 42 , t-tau and p-tau were measured at the ADNI biomarker core (University of Pennsylvania) using the multiplex xMAP Luminex platform (Luminex Corp, Austin, TX, USA) with the INNOBIA AlzBio3 kit (Fujirebio, Ghent, Belgium). Levels of CSF total α-synuclein concentrations in the ADNI cohort were measured by Luminex MicroPlex Microspheres (Luminex Corp, Austin, TX). A biotinylated goat antihuman α-syn antibody (R&D systems, Minneapolis, MN, USA) was used as the detection antibody. The α-synuclein Luminex assay demonstrated low day-to-day and plate-to-plate signal variability. The accuracy of the assay was further determined by the recovery of spiked α-synuclein protein, which was close to 93 %.

Neuroimaging
Structural MRI was performed only for the ADNI subjects using a Siemens Trio 3.0T scanner or Vision 1.5T scanner (GE, Siemens and Philips). Free-surfer software package version 4.3 and 5.1 image processing framework were used to process regional volume estimates for the 1.5 and 3.0T MRI images, respectively. ROIs included the hippocampus and ventricles.

Statistical analyses
We tested associations between CSF α-synuclein and demographic factors using the Mann-Whitney test and the Spearman rank correlation test. We tested the associations of CSF α-synuclein with CSF Aβ42, ttau, and p-tau levels using linear regression adjusted for age, gender, educational level, diagnosis and APOE ε4 genotype (with CSF α-synuclein as predictor). In the ADNI database, associations between CSF α-synuclein concentrations and the diagnostic groups were tested in an analysis of covariance model adjusted for age, gender, educational level and APOE ε4 genotype. Logistic regression analysis was used to assess the impact of different CSF analytes on the risk of conversion to AD. The receiver-operator curves and the area under the curves were derived from the predictive probabilities of the logistic regression models. We tested the associations of CSF α-synuclein concentrations with longitudinal cognition and brain structure using linear mixed-effects models. These models had random intercepts and slopes for time and an unstructured covariance matrix for the random effects and included the interaction between (continuous) time and CSF α-synuclein as predictor with adjustment for confounders. All tests were 2-sided. Statistical signi cance was set at P < 0.05. All regression analyses were corrected for age, gender, educational level, diagnosis, and APOE ε4 genotype. The following variables were natural log-transformed to ensure normality: CSF α-synuclein, p-tau, t-tau, Aβ and hippocampus volume. All statistical analyses were performed using a software program (R, version 3.4.0; The R Foundation).

Characteristics of Participants in CABLE Study
We included 651 subjects in prodromal stage of AD from the CABLE study consisting of 457 CN controls (238 women, 60.54 ± 10.46 years) and 194 MCI patients (109 women, 63.6 ± 9.72 years) ( Table 1). CN individuals were younger and more educated. CSF p-tau and t-tau levels were higher in MCI patients than CN individuals.

CSF α-synuclein in Different Diagnostic Groups in ADNI
With the advance of the disease stage, the level of CSF α-synuclein showed a rising trend. The CSF αsynuclein concentration was signi cantly higher in the AD and pMCI groups compared with CN controls (P < 0.0001 and P < 0.001 respectively). Higher CSF α-synuclein levels were also detected in the AD and pMCI groups compared with the sMCI group (P = 0.02 and P = 0.04, respectively) ( Figure 1A). We continued to compare CSF α-synuclein concentration among A-controls, A+ controls, A-patients with MCI, A+ patients with MCI and A+ patients with AD dementia ( Figure 1B). The A+ AD group had higher CSF α-synuclein levels than those of A-controls (P < 0.001), A+ controls (P < 0.001), and A-MCI group (P < 0.001). The A+ MCI had higher CSF α-synuclein levels than those of A-controls (P < 0.01), A+ controls (P < 0.01), and A-MCI group (P = 0.02). We further compared the CSF α-synuclein level between the A+T+ group with the A-T-group, which showed differences with more signi cant statistical power (P < 0.0001) ( Figure 1C).
We performed receiver-operating curves based on the logistic regression models adjusted for age at baseline, gender, educational level and APOE ε4 genotype to assess the predictive value of CSF αsynuclein and its combination with other established AD biomarkers in the risk of conversion to AD. The area under the curve (AUC) of the base model containing CSF α-synuclein, age at baseline, gender, educational level and APOE ε4 genotype was 0.76 in predicting the onset of AD among CN controls, and AUC was increased by the inclusion of CSF tau/Aβ ratio (AUC = 0.88) (Figure e

CSF α-synuclein and Longitudinal Clinical Outcomes Change and Progression in ADNI
Next, the linear mixed-effects models were utilized to test the associations between baseline CSF αsynuclein concentration and subsequent disease progression adjusted for age, gender, educational level, diagnosis, and APOE ε4 genotype. A Signi cant association of baseline CSF α-synuclein concentration with hippocampus volume was identi ed (β = -0.008, P = 0.001 longitudinally) ( Table 4, Figure 2A). Table 4 Modelling the association of CSF biomarkers on AD biomarkers and clinical outcomes in ADNI a  Figure 2B presents the results of a Kaplan-Meier analysis. The cox proportional hazards model was developed to estimate the predictive value of CSF α-synuclein in the conversion risk from MCI to incident AD dementia, controlling for baseline age, gender and years of education. MCI individuals with high CSF α-synuclein levels would satisfy the diagnostic criteria for AD at a comparatively earlier interval (HR 2.79, 95% CI 1.14 to 6.9, P = 0.03) ( Table 4).

Discussion
The main ndings of this study were that CSF α-synuclein concentration (1) associated with CSF t-tau and p-tau levels among nondemented elderly adults, (2) was elevated in AD dementia group and in Aβ/tau-positive group compared with control groups, (3) predicted longitudinal hippocampus atrophy and conversion from MCI to AD dementia. Taken together, these ndings suggest that CSF α-synuclein is a very early and potentially presymptomatic biomarker for AD. This biomarker may be helpful in AD diagnosis, predicting disease progression and staging severity of AD even in its preclinical stage. Our study also provided clues to how α-synuclein participated in the pathogenetic process in AD and provided evidence for drug development.
"Pure'' AD is characterized by the presence of both diffused neuritic plaques and intracellular neuro brillary tangles, which lacks abnormal α-synuclein inclusions or neuritis. However, more than 50 % AD patients exhibit abundant brain accumulation of α-synuclein-positive Lewy bodies, particularly in the amygdala. [10,20] The presence of α-synuclein does not appear to be innocuous, as these patients demonstrate an accelerated cognitive decline than subjects with AD alone. [12,21] Previous studies indicated that α-synuclein could be secreted into the surrounding media in the brain and then to the CSF. Studying CSF could provide clues to the mechanism of α-synuclein metabolism in brain.
Consistent with most studies, our study showed that CSF α-synuclein was higher in AD group compared with CN controls and MCI group. A possible hypothesis is that the higher level of α-synuclein in the AD group is caused by the higher expression of α-synuclein in the brains of AD patients. The higher expression of α-synuclein could induce a decrease in selected synaptic vesicle proteins and alteration of the protein composition of synaptic vesicles, thus causing neuronal damage in AD which, in turn, increases the release of α-synuclein from damaged cells into the CSF. [22] As CSF α-synuclein levels were signi cantly higher in patients with AD than in those with synucleinopathies (CSF α-synuclein was lower than controls), indicating α-synuclein might serve as a biomarker for differential dementia diagnosis.
Logistic regression analysis was used to assess the impact of CSF analytes on risk for progression to AD. The AUC (re ect predictive probabilities of the logistic regression models) of the model including CSF αsynuclein, age at baseline, gender, educational level and APOE ε4 genotype was great in predicting progression from CN to pMCI or AD. Recently, the NIA-AA committee recommended a different de nition of AD by pathophysiology which is independent from clinical symptoms. They proposed that as long as biomarker evidence of Aβ and tau pathology was present simultaneously, the term "Alzheimer's disease" would be applied. And the CSF α-synuclein model had high diagnostic accuracy for patients with the diagnosis of AD based on the "ATN" system (A+T+) vs controls (A-T-) (AUC = 0.84, which is comparable to other established CSF biomarkers).
Notably, α-synuclein inclusions are commonly observed in patients with familial Alzheimer's disease or Down's syndrome in which Aβ peptides are highly expressed. In both diseases, α-synuclein affects biological pathways and promotes the formation of Aβ aggregates. α-synuclein was supposed to be implicated in synaptic vesicle formation, axonal transport as well as dopamine synthesis and metabolism. [29] In the normal condition, the synaptic membrane is integrated and the α-synuclein is completely released to the cytosol. However, in the event of neuronal damage and synaptic membrane defect, both aggregated Aβ and α-synuclein might attach to synaptic membrane and accumulate in lipid rafts. Synaptic membrane-bound α-synuclein could not only induce cytosolic α-synuclein to aggregate as intracellular LBs but also interact with membrane-associated Aβ 40 and Aβ 42 peptides. [30] This could explain the low level of CSF α-synuclein in initial stages of AD to a certain extent. Moreover, an in vitro experiment demonstrated that interaction with Aβ 1-42 is su cient to induce the intracellular accumulation of α-synuclein, whereas interaction with Aβ 1-40 is not. [31] In our study, although we did not detect any association between CSF α-synuclein and CSF Aβ levels at baseline, the strong interaction between them in brain could not be denied. The reason may be that this mutual effect happens in the initial stages of the mixed pathology, however, it may take years or decades for intracellular α-synuclein to be available in extracellular space and eventually detectable in the CSF. We only studied CSF total αsynuclein level rather than the oligomeric or phosphorylated forms. Future study focusing on oligomeric or phosphorylated forms of α-synuclein may provide additional information.
Moreover, α-synuclein was also being observed in progressive supranuclear palsy [32] and frontotemporal dementia. [33] Many studies proposed that α-synuclein and tau interact to promote each other's brillation and toxicity. [23] However, as α-synuclein could spontaneously polymerize into amyloidogenic brils, tau requires cofactors such as glycosaminoglycans or nucleic acids. [34] The α-synuclein polymers act as amyloidogenic "seeds" or as amyloidogenic chaperones that induce the formation of tau brillar inclusions even in the absence of α-synuclein coexpression. [23,24,35] Besides, Tau promots α-synuclein to polymerize into brils. Low concentrations of α-synuclein don't brillize without tau, however, in the presence of tau, most α-synuclein assembles into brils. Much attention has been paid to the relationship between CSF α-synuclein and tau. Most studies demonstrated that CSF α-synuclein was positively associated with CSF t-tau and p-tau. [22,26] Our study also indicated positive associations of CSF αsynuclein with CSF t-tau and p-tau levels in CABLE study. We noted that the mean values for CSF αsynuclein and CSF Aβ levels between controls in the 2 Chinese cohorts using similar assays are different.
This could partly be explained by differences in pre-analytical protocols, analytical procedures, assays quality together with discrepancies in absolute levels between assay formats [36]. Replication studies with larger sample sizes are warranted to con rm the present ndings.
Importantly, we found that the CSF α-synuclein levels might correlate with AD severity and progression.
Our nding was consistent with a recent study indicating that increased α-synuclein displayed a stronger association with cognitive impairment than soluble Aβ and tau levels. [37] It has been widely recognized that α-synuclein is a synaptic marker. α-synuclein is highly expressed in the pre-synaptic terminals [38,39] and it plays a role in the regulation of neurotransmitter release, synaptic function and plasticity. It could trigger synaptoxicity not only by directly damaging the synaptic membrane, but also by damaging mitochondria, lysosomes, or by disrupting microtubules. This then leads to dendritic and spine alterations, axonal dystrophy, and eventually neuronal loss. [40] Along with the synaptic damage, αsynuclein is released into the cerebrospinal uid. Therefore, it is reasonable to assume that CSF αsynuclein level correlates with cognitive decline in AD, since synaptic damage is supposed to be a strong predictor of cognitive decline. [41] Conclusions CSF α-synuclein was associated with CSF t-tau and p-tau levels among nondemented elderly adults. In ADNI database, CSF α-synuclein concentrations were increased with the severity of the disease. CSF αsynuclein predicted longitudinal hippocampus atrophy and conversion from MCI to AD dementia. The current ndings suggest CSF α-synuclein as a very early and potentially presymptomatic biomarker for AD, a prognostic marker in the clinic, and an outcome measure in clinical trials.