Skip to main content
Download PDF
  • Research article
  • Open access
  • Published:

Alpha synuclein co-pathology is associated with accelerated amyloid-driven tau accumulation in Alzheimer’s disease

Molecular Neurodegeneration volume 20, Article number: 31 (2025) Cite this article

Abstract

Background

Aggregated alpha-Synuclein (αSyn) is a hallmark pathology in Parkinson’s disease but also one of the most common co-pathologies in Alzheimer’s disease (AD). Preclinical studies suggest that αSyn can exacerbate tau aggregation, implying that αSyn co-pathology may specifically contribute to the Aβ-induced aggregation of tau that drives neurodegeneration and cognitive decline in AD. To investigate this, we combined a novel CSF-based seed-amplification assay (SAA) to determine αSyn positivity with amyloid- and tau-PET neuroimaging in a large cohort ranging from cognitively normal individuals to those with dementia, examining whether αSyn co-pathology accelerates Aβ-driven tau accumulation and cognitive decline.

Methods

In 284 Aβ-positive and 308 Aβ-negative subjects, we employed amyloid-PET, Flortaucipir tau-PET, and a CSF-based αSyn seed-amplification assay (SAA) to detect in vivo αSyn aggregation. CSF p-tau181 measures were available for 384 subjects to assess earliest tau abnormalities. A subset of 155 Aβ-positive and 135 Aβ-negative subjects underwent longitudinal tau-PET over approximately 2.5 years. Using linear regression models, we analyzed whether αSyn SAA positivity was linked to stronger Aβ-related increases in baseline fluid and PET tau biomarkers, faster Aβ-driven tau-PET increase, and more rapid cognitive decline.

Results

αSyn SAA positivity was more common in Aβ + vs. Aβ- subjects and increased with clinical severity (p < 0.001). Most importantly, αSyn positivity was also associated with greater amyloid-associated CSF p-tau181 increases (p = 0.005) and higher tau-PET levels in AD-typical brain regions (p = 0.006). Longitudinal analyses confirmed further that αSyn positivity was associated with faster amyloid-related tau accumulation (p = 0.029) and accelerated amyloid-related cognitive decline, potentially driven driven by stronger tau pathology.

Conclusions

Our findings suggest that αSyn co-pathology, detectable via CSF-based SAAs, is more prevalent in advanced AD and contributes to the development of aggregated tau pathology thereby driving faster cognitive decline. This highlights that a-Syn co-pathology may specifically accelerate amyloid-driven tau pathophysiology in AD, underscoring the need to consider αSyn in AD research and treatment strategies.

Introduction

Alzheimer’s disease (AD) is neuropathologically defined by the presence of amyloid-beta (Aβ) plaques and neurofibrillary tau tangles [1]. The development of AD is currently understood as a cascade of pathophysiological events, where initial Aβ aggregation is assumed to trigger the subsequent trans-neuronal spread of tau pathology, ensuing neurodegeneration and cognitive decline [2,3,4,5]. However, post mortem studies have shown that the AD-defining pathologies Aβ and tau are rarely found in isolation, but that concomitance of proteinopathies, including TDP-43, Lewy body pathology and cerebral amyloid angiopathy is the rule rather than the exception [1, 6,7,8,9]. The frequency of co-pathologies increases with age, with the large majority of AD patients showing at least one co-pathology at autopsy, questioning the existence of pure AD pathology especially in older individuals, but also in autosomal dominant AD [1, 8,9,10]. Therefore, it is crucial to understand how these molecular co-pathologies interact with the core AD pathologies Aβ and tau and how they contribute to disease progression. Lewy body pathology consisting of alpha-synuclein (αSyn) aggregates, i.e. the hallmark pathology of Parkinson’s disease and Lewy body dementia [11], is one of the most common co-pathologies found in ~ 50% of AD cases at autopsy [6, 7, 9] and concomitant αSyn has been shown to exacerbate cerebral glucose hypometabolism, cognitive impairment and rate of decline in AD patients [7, 12,13,14]. Post mortem studies have further shown that the degree of αSyn co-pathology in AD is related to the severity of both Aβ and tau burden [8], suggesting a close link between AD and αSyn co-pathology.

Previous research has reported that αSyn may interact with tau pathology in AD. Specifically, tau and αSyn are both intracellular proteins that are highly abundant in neurons [15, 16], and αSyn has been shown to be capable of inducing tau hyperphosphorylation [17,18,19,20], i.e., one of the earliest hallmarks of pathophysiological tau alterations in AD [21]. Further, both proteins have been shown to mutually promote each other’s fibrilization in vitro and in vivo [22,23,24,25] and to co-aggregate in neurons and their synaptic terminals [23, 26, 27]. Recent studies in PS19 mice have further shown that αSyn specifically accelerates the spreading of tau pathology, whereas the presence of tau pathology did not promote the progression of αSyn aggregates [27, 28]. In addition, the knock-down of αSyn reduced the effect of αSyn seeds on the appearance and spread of tau pathology [27], together suggesting that αSyn co-pathology may promote tau aggregation and spread in AD, thereby contributing to neurodegeneration and faster cognitive decline.

However, this question could not be addressed in AD patients previously, since reliable in vivo biomarkers of αSyn were not readily available [29]. Recently, advances in biomarker development have demonstrated that αSyn pathology can be assessed in patients based on cerebrospinal fluid (CSF) seed amplification assays (SAA), that quantify the seeding and self-replicative aggregation potential of αSyn seeds present in the CSF of patients [30]. These αSyn SAAs can identify patients with αSyn pathology of the Lewy-type (e.g., Parkinson’s disease, Lewy body dementia) already in prodromal disease stages and discriminate those Synucleinopathies from non-αSyn-related diseases [31, 32]. Previous research in AD patients has shown that ante-mortem performed CSF-based αSyn SAAs have a particularly high sensitivity and specificity in detecting cortical rather than focal subcortical αSyn co-pathology in patients with AD post-mortem [33, 34], which is potentially relevant for a physical interaction between αSyn and tau, given the primary cortical appearance and spreading of tau in AD [35,36,37,38]. Studies employing αSyn SAAs in AD patient cohorts have confirmed higher rates of αSyn co-pathology in patients with an AD-typical biomarker profile and have reported synergistic effects of αSyn and AD pathology on cognitive decline [33, 39,40,41], where αSyn SAA positive individuals show earlier cognitive decline after onset of amyloidosis [42]. These findings therefore support previous post mortem evidence of αSyn co-pathology contributing to clinical severity in AD [7,8,9, 33]. However, it is still unclear whether αSyn co-pathology may specifically promote tau pathology in AD patients and thereby contribute to disease progression.

Thus, in the current study, we examined (i) whether the presence of αSyn co-pathology as assessed via CSF-based SAAs promotes tau pathophysiology and aggregation in an AD context, and (ii) whether the putative αSyn-associated acceleration of tau aggregation contributes to faster cognitive decline. To achieve this, we analyzed data from 592 subjects ranging from cognitively normal to dementia from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), with available cross-sectional amyloid-PET and tau-PET data to assess fibrillar Aβ and tau pathology, as well as CSF-based αSyn SAA data to identify αSyn pathology. In this dataset, we tested whether αSyn co-pathology was linked to increased tau-PET tracer signal in the context of abnormal Aβ. Additionally, in a subset of 384 subjects with CSF p-tau181 data, we explored whether αSyn co-pathology was associated with elevated tau hyperphosphorylation and p-tau release from neurons [43, 44], a process that may specifically precede and drive tau aggregation [45]. Lastly, we utilized longitudinal tau-PET and longitudinal cognitive data from a subset of 290 subjects to determine whether αSyn co-pathology specifically accelerates Aβ-related tau aggregation rates and cognitive decline over time in AD patients.

Methods

Sample

592 individuals were included from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, based on availability of clinical data, baseline 18 F-Florbetapir/Florbetaben amyloid-PET, 3T MRI and 18 F-Flortaucipir tau-PET data. Individuals with major neurological diseases than AD or severe psychiatric conditions that may affect cognition are excluded from ADNI. A detailed overview of ADNI inclusion and exclusion criteria can be found online (https://adni.loni.usc.edu/wp-content/themes/freshnews-dev-v2/documents/clinical/ADNI3_Protocol.pdf). All baseline data had to be obtained within a timeframe of 6 months, in line with our previous studies using ADNI data [46,47,48,49,50]. This time window was chosen to maximize observations with complete neuroimaging and clinical data within a given timeframe. Participants diagnostic status was determined by ADNI as cognitively normal (CN; Mini Mental State Examination [MMSE] ≥ 24, Clinical Dementia Rating [CDR] = 0, non-depressed), mildly cognitively impaired (MCI; MMSE ≥ 24, CDR = 0.5, objective memory-impairment on education-adjusted Wechsler Memory Scale II, preserved activities of daily living) and demented (MMSE = 20–26, CDR ≥ 0.5, National Institute of Neurological and Communicative Disorders and Stroke/Alzheimer’s Disease and Related Disorders Association criteria for probable AD). 410 out of the total sample of 592 subjects also had CSF measures of p-tau181 available to determine earliest tau pathophysiology. P-tau181 values were adjusted to Aβ1−40 levels, which are considered to be relatively stable and serve as a reference protein, following a previous suggestion that the p-tau181/Aβ1−40 ratio is a better measure of tau pathophysiology than p-tau181 alone [51]. All CSF measures were determined by the ADNI biomarker core on the Roche Elecsys Cobas e 601 platform (for a methods description, please see https://adni.bitbucket.io/reference/docs/UPENNBIOMK12_2020/ADNI_UPENNBIOMK12_Methods_2020_Roche_Elecsys_ADNI3_CSFs.pdf). A subset of 290 subjects had longitudinal 18 F-Flortaucipir data available to model longitudinal tau accumulation. Amyloid status was determined on global amyloid-PET SUVRs using tracer-specific cut-offs (i.e. Aβ + = SUVR > 1.11/1.08 for Florbetapir/Florbetaben) previously established in the ADNI cohort [52, 53]. All study procedures were conducted in accordance with the declaration of Helsinki, ethical approval was obtained by ADNI investigators. All study participants provided written informed consent.

αSyn seed amplification assay

The αSyn SAAs were performed as described previously [33] in the Amprion Clinical Laboratory (CLIA ID No. 05D2209417; CAP No. 8168002) using a method validated for clinical use in accordance with Clinical Laboratory Improvement Amendment (CLIA) requirements. All αSyn SAA data were provided by the ADNI biomarker core. Each sample was analyzed by Amprion in triplicate in a 96-well plate using a reaction mixture comprised of 100mM PIPES pH 6.5, 0.5 M NaCl, 0.1% sarkosyl, 10µM ThT, 0.3 mg/mL recombinant αSyn, and 40µL CSF, in a final volume of 100µL. Two silicon nitride beads are included in each well, and positive and negative assay quality control samples are included on each plate. Plates are sealed with optical adhesive film, placed into the chamber of a BMG LABTECH FLUOstar Ω Microplate Reader, and incubated at 42 °C with cycles of 1 min of shaking followed by 14 min of rest with fluorescence measured after every shaking cycle (excitation wavelength 440 nm, emission 490 nm). After a total incubation time of 20 h, the maximum fluorescence for each well is determined and an algorithm applied to the triplicate determinations for each sample for result classification. Samples were considered positive when all triplicates showed seeding activity and negative if no seeding activity was observed. Undetermined samples in which only a subset of the three triplicates was positive were excluded from the study.

Neuroimaging acquisition

Structural MRI was acquired on 3T scanners. T1-weighted structural scans were collected using an MPRAGE sequence (TR = 2300ms; Voxel size = 1 × 1 × 1 mm; for parameter details see: https://adni.loni.usc.edu/wp-content/uploads/2017/07/ADNI3-MRI-protocols.pdf). PET data was assessed using post intravenous injection of 18F-labeled tracers (Flortaucipir: 6 × 5 min time-frames, 75–105 min post-injection; Florbetapir: 4 × 5 min time-frames, 50–70 min post-injection; Florbetaben: 4 × 5 min time-frames, 90–110 min post-injection; for more information see http://adni.loni.usc.edu/methods/pet-analysis-method/pet-analysis/).

Image processing

All images were screened for artifacts before preprocessing. T1-weighted structural MRI scans were bias-corrected, segmented, and non-linearly warped to Montreal Neurological Institute (MNI) space using the CAT12 toolbox (https://neuro-jena.github.io/cat12-help/). Harmonized PET images were downloaded from the ADNI loni database (https://ida.loni.usc.edu/). The harmonization has been implemented by the ADNI PET core (described online https://adni.loni.usc.edu/data-samples/adni-data/neuroimaging/pet/) and includes realignment of dynamic PET scans as well as averaging to obtain single Flortaucipir/Florbetapir image. For harmonization, all images are smoothed to a common resolution using scanner-specific 3D-Gaussian filters derived by the University of Michigan team using Hoffman phantom scans carried out at each site. The effective resolution was selected by the ADNI PET core based on the lowest resolution scanners in ADNI (i.e. 8 mm Full width at half maximum). Resulting downloaded images have a standardized voxel size and spatial resolution. These images were rigidly registered to the T1-weighted MRI scan. Reference regions (i.e., inferior cerebellar grey for Flortaucipir, whole cerebellum for Florbetapir/Florbetaben) [54] and the cortical Schaefer atlas including 200 regions of interest (ROIs) were warped from MNI to T1-native space using the CAT12-derived non-linear normalization parameters, masked with subject-specific grey matter and applied to PET data to determine standardized uptake value ratios (SUVRs) for each region of the Schaefer 200 atlas [55]. Global and regional Florbetapir/Florbetaben SUVRs were converted to centiloid using equations provided by ADNI.

Statistical analysis

All statistical analyses were performed in R (Version 4.3.1). Patient characteristics for the cross-sectional and longitudinal datasets were compared between groups stratified by amyloid and diagnostic status (i.e. CN, MCI, Dementia) using Chi-squared tests for nominal and ANOVAs for continuous measures. Logistic regression was further used to determine αSyn SAA positivity differences between diagnostic groups while additionally adjusting for age as a confound. To determine longitudinal tau-PET changes (i.e., for the 200 Schaefer ROIs, Braak-stage specific ROIs and temporal meta-ROI) and cognitive change rates (i.e., for the ADAS13), we employed linear mixed models controlling for random slope and intercept as described previously [37, 38].

To address our main aims, linear regression analyses were performed to determine whether the αSyn SAA status modulated the effect of global amyloid-PET centiloid levels on (i) the p-tau181/Aβ40 ratio (i.e., αSyn SAA x centiloid interaction), (ii) tau-PET in the temporal meta ROI, (iii) tau-PET change rates in the temporal meta ROI. Exploratory analyses were conducted for Braak-stage specific tau-PET ROIs and 200 ROIs of the Schaefer atlas (FDR-corrected to account for 200 regions). To determine whether αSyn SAA status modulated AD-related cognitive decline via elevated tau pathology we further determined the (iv) αSyn SAA x centiloid or (v) αSyn SAA x temporal meta tau-PET interaction on ADAS13 change rates. Exploratory sub-analyses were conducted using MMSE scores. Regression models were controlled for age, sex and study site for cross-sectional analyses, and additionally for follow-up years for analyses using longitudinal data. For our main five analyses described above, we applied FDR-correction to account for multiple testing (correcting for five tests). For confirmatory purposes, we further performed ANCOVAs to determine main effects of αSyn SAA status on tau-PET SUVRs, stratified by amyloid-PET status. ANCOVA models were controlled for age, sex, study site and centiloid levels.

Results

We included 331 cognitively normal (CN) individuals, 196 patients with mild cognitive impairment (MCI) and 65 patients with clinically diagnosed dementia all with available baseline amyloid-PET (i.e., [18F]florbetaben/[18F]florbetapir, n = 197/395), [18F]flortaucipir tau-PET and CSF-based αSyn data based on a pre-established SAA (Amprion, San Diego, CA) to determine the αSyn status [30]. All amyloid-PET SUVR data was transformed to centiloids to harmonize across the two amyloid-PET tracers [56]. A subset of 384 subjects had cross-sectional CSF p-tau181 levels measured on the Roche Elecsys platform for assessing earliest tau pathophysiology which were referenced to CSF Aβ1 − 40 levels to adjust for overall CSF protein concentrations [51]. Further, 290 subjects (CN/MCI/dementia = 178/84/28) had longitudinal flortaucipir tau-PET and cognitive assessments over 2.9 ± 1.4 years. Baseline amyloid-PET centiloids and tau-PET SUVRs as well as longitudinal tau-PET change rates stratified by Aβ and diagnostic status are shown in Fig. 1, illustrating AD-typical temporo-parietal tau-PET uptake with increased clinical disease severity in the Aβ-positive (Aβ+) groups, while no tau-PET increase was found in Aβ-negative (Aβ-) groups. Sample demographics, biomarker and clinical data are shown in Table 1 for both the cross-sectional (N = 592) and longitudinal samples (N = 290). Cross-sectionally, we found that the prevalence of αSyn positivity increased with more severe clinical impairment and was particularly pronounced in Aβ+ (i.e., CN/MCI/dementia = 20/23/45%) vs. Aβ- subjects (i.e., CN/MCI/dementia = 14/12/22%, chi-squared-test, p < 0.001, Fig. 2A). This result was consistent when additionally controlling for age in a logistic regression model (p < 0.001), suggesting that αSyn co-pathology is more common in clinically advanced AD, regardless of age. No difference in amyloid-PET centiloids was found between SAA-positive vs. negative subjects for Ab+ (F = 0.162, p = 0.688) and Ab- subjects (F = 2.424, p = 0.113), controlling for age, sex and site.

Fig. 1
figure 1

Surface renderings of (A) baseline amyloid-PET centiloids and (B) tau-PET baseline as well as (C) annualized tau-PET rates of change, stratified by diagnostic group and amyloid-PET status at baseline

Full size image
Table 1 Sample characteristics
Full size table
Fig. 2
figure 2

Bar plot illustrating the probability of αSyn SAA positivity stratified by amyloid status and clinical syndrome severity. Statistical significance was determined via logistic regression controlling for age (A). Scatterplot illustrating the interaction effect between amyloid-PET and αSyn SAA status on cross-sectional levels of CSF p-tau181/Aβ1 − 40 as an indicator of earliest tau pathophysiology. Diagnostic groups are indicated by shape, the cut-point of amyloid-PET positivity is indicated by the dashed red line at 25 centiloids. The beta value indicates the strength of the amyloid-PET x CSF αSyn SAA interaction effect as determined by linear regression, controlling for age, sex and study site. FDR-correction for multiple comparisons (p < 0.05) was applied for the main analyses (B), adjusting for five statistical tests

Full size image

αSyn SAA positivity is linked to elevated p-tau in the context of Ab

We first tested whether SAA positivity was associated with changes in the earliest signs of tau pathophysiology in AD, i.e., increases of hyperphosphorylated p-tau in CSF that typically precede tau tangle formation. This analysis was performed in 384 subjects with available cross-sectional p-tau181/Aβ1 − 40 data. We found a significant SAA-positivity status-by-centiloid interaction effect on the p-tau181/Aβ1 − 40 ratio when controlling for age, sex and study site, showing that the p-tau181/Aβ1 − 40 increase in response to Aβ deposition was stronger in SAA–positive subjects compared to SAA-negative subjects (β = 0.161, puncorrected=0.005, pFDR−corrected=0.010, Fig. 2). This result was consistent when controlling for diagnosis (β = 0.126, p = 0.0246) or when considering only p-tau181 instead of the p-tau181/Aβ1 − 40 ratio as a dependent variable (β = 0.11, p = 0.035), while additionally controlling for Aβ1 − 40 levels. Additionally controlling for vascular co-pathology (WMH volume) in a subset of 136 subjects, yielded largely consistent results (β = 0.196, p = 0.065). Together, these results suggest that αSyn SAA positivity is associated with stronger p-tau181 release in response to Aβ pathology.

αSyn SAA positivity is associated with higher tau-PET tracer signal in the context of AD pathology

Next, we investigated whether SAA positivity was linked to stronger tau-PET tracer signal in an AD context, given that αSyn seeds have been proposed exacerbate tau aggregation [22,23,24,25,26,27]. Supporting this view, we found a significant interaction effect between amyloid-PET centiloid levels and SAA positivity on tau-PET SUVRs in the temporal meta-ROI that captures AD-typical tau accumulation, controlling for age, sex and study site (β = 0.147, puncorrected=0.006, pFDR−corrected=0.010). As shown in Fig. 3A, SAA-positive individuals showed a greater increase of tau-PET SUVRs at higher amyloid-PET levels compared to SAA-negative individuals at similar amyloid-PET levels. An exploratory extension of this analysis to the pre-defined Braak-stage regions that capture tau progression [48] yielded consistent results for the centiloid-by-SAA-interaction across BraakI (β = 0.119, p = 0.0226, Fig. 3B), BraakIII/IV (β = 0.146, p = 0.008, Fig. 3C) and BraakV/VI ROIs (β = 0.144, p = 0.017, Fig. 3D), indicating that SAA-positivity-related aggravation of tau deposition in an AD context not confined to a particularly vulnerable brain region. Results remained largely consistent when additionally controlling for diagnosis, except for BraakI (temporal meta/BraakI/III−IV/V−VI, β = 0.104/0.079/0.112/0.120, p = 0.045/0.116/0.041/0.035). This was further substantiated by ROI-based analyses, showing widespread SAA-by-centiloid interaction effects predominantly on temporo-frontal tau-PET uptake (Fig. 3E). To further confirm that SAA positivity is specifically related to higher tau in the presence of abnormal Aβ levels, we additionally tested for a main effect of SAA positivity on tau-PET SUVRs stratified by Aβ status, using ANCOVAs including the covariates age, sex, study site and centiloid levels (tau-PET SUVRs stratified by SAA and amyloid status are shown in Fig. 4A). Here, we found that SAA positivity was associated with increased temporal meta tau-PET SUVRs in Aβ + subjects (p = 0.008) but not in Aβ- subjects (p = 0.889). Consistent results were detected for regional analyses in Braak-stage-specific ROIs for BraakI (Aβ+/-, p = 0.004/0.369), BraakIII/IV (Aβ+/-, p = 0.008/0.961) and BraakV/VI (Aβ+/-, p = 0.021/0.521). Together, these findings suggest that SAA positivity is associated with increased Aβ-associated tau deposition in individuals on the AD spectrum.

Fig. 3
figure 3

Scatterplots illustrating the interaction effect between global amyloid-PET (i.e. centiloid) and aSyn SAA status on tau-PET SUVRs for meta-ROIs (A-D) and regional analyses (E), as well as for annual tau-PET SUVR change rates (F-J). Diagnostic groups are indicated by shape, the cut-point of amyloid-PET positivity is indicated by the dashed red line at 25 centiloids. Beta values indicate the strength of the amyloid-PET x CSF αSyn SAA interaction effect, as determined by linear regression, controlling for age, sex and study site (A-E) as well as maximum tau-PET follow-up time (F-J). FDR-correction for multiple comparisons (p < 0.05) was applied for the main analyses (A, F), adjusting for five statistical tests. In addition, ROI-wise assessments were also FDR-corrected at p < 0.05

Full size image
Fig. 4
figure 4

Surface renderings of tau-PET uptake (A) and annual tau-PET change rates (B) stratified by amyloid-PET and αSyn SAA status

Full size image

αSyn SAA positivity is associated with faster Aβ-related Tau accumulation

Next, we tested whether SAA positivity was not only linked to higher cross-sectional tau-PET levels in the presence of Aβ, but also to faster tau accumulation rates, indicative of accelerated Aβ-related tau seeding and spread. To this end, we used linear regression models to test the SAA-status-by-centiloid-interaction on annual tau-PET change rates, using the subset of 290 subjects with longitudinal flortaucipir tau-PET data. Congruent with the cross-sectional results, we found that SAA positivity was related to faster Aβ-related tau-PET change rates in the temporal meta-ROI (β = 0.175, puncorrected=0.029, pFDR−corrected=0.0363, Fig. 3F). Exploratorily extending this analysis to Braak-stage specific regions showed faster Aβ-related tau accumulation in BraakIII/IV (β = 0.171, p = 0.035, Fig. 3H) and BraakV/VI (β = 0.185, p = 0.027, Fig. 3I) but not in BraakI (β = 0.075, p = 0.333, Fig. 3G). Again, these results were largely consistent when additionally controlling for diagnosis (temporal meta/BraakI/III−IV/V−VI, β = 0.160/0.045/0.167/0.172, p = 0.039/0.551/0.040/0.042). Confirming that the effects of SAA positivity on accelerated tau accumulation were driven by subjects on the AD spectrum (i.e. Aβ+), we found that SAA positivity had a significant main effect on faster tau-PET change rates in the temporal meta-ROI in the Aβ+ (p = 0.037) but not in the Aβ- subjects (p = 0.899), controlling for age, sex, study site and centiloid levels. This result pattern was congruent for BraakI (Aβ+/Aβ-, p = 0.047/0.795), BraakIV/V (Aβ+/Aβ-, p = 0.039/0.883) and trend-level for BraakV/VI (Aβ+/Aβ-, p = 0.071/0.891). Together, these findings support the view that SAA positivity is related to faster Aβ-related accumulation of fibrillar tau pathology over time in subjects on the AD spectrum.

αSyn SAA positivity is associated with accelerated Aβ-related cognitive decline

Lastly, we tested whether LB co-pathology was associated with accelerated AD-related cognitive decline. Supporting this, we found a significant centiloid-by SAA-αSyn-status-interaction on annual change rates in ADAS13 global cognitive scores (β = 0.253, puncorrected=0.003, pFDR−corrected=0.010, Fig. 5A), controlling for age, sex and study site. This result remained consistent when additionally controlling for diagnosis (β = 0.132, p = 0.0246) or tau-PET in the temporal meta ROI (β = 0.153, p = 0.030), or when using annual change rates in the MMSE score as an alternative measure of cognitive decline (β=-0.194, p = 0.039, available for a subset of N = 247 individuals). In contrast, no interaction between temporal meta tau-PET SUVRs and αSyn SAA positivity was found on ADAS13 change rates (β=-0.020, puncorrected=0. 0.972, pFDR−corrected=0.972, Fig. 5B), controlling for age, sex and centiloid levels. However, there was a main effect of αSyn positivity on ADAS13 change rates (p = 0.003; controlling for age, sex, temporal meta-ROI tau-PET and centiloid), suggesting that SAA positivity is related to overall faster cognitive decline. This effect was present at lower tau-PET levels and vanished at higher tau-PET levels. Taken together, this suggests that SAA positivity is related to faster cognitive decline in AD, and that this may be particularly driven by higher SAA-positivity-related tau-PET burden in individuals with high Aβ burden.

Fig. 5
figure 5

Scatterplot illustrating the effect of αSyn SAA status on the association between amyloid-PET centiloid (A) and tau-PET (B) at baseline on subsequent change rates in the ADAS13 score of global cognition. Diagnostic groups are indicated by shape, the cut-point of amyloid-PET positivity is indicated by the dashed red line at 25 centiloids. Beta values indicate the strength of the amyloid-PET x CSF αSyn SAA interaction effect (A) or the tau-PET x CSF αSyn SAA interaction effect (B), as determined by linear regression, controlling for age, sex and study site and maximum follow up time of cognitive assessments. FDR-correction for multiple comparisons (p < 0.05) was applied for the main regression analyses, adjusting for five statistical tests

Full size image

Discussion

The major aim of this study was to investigate whether αSyn Lewy-body pathology, one of the most common co-pathologies found post-mortem in AD patients [6, 7, 9], accelerates the development of tau pathology in AD. This was motivated by previous evidence from animal and in vitro studies suggesting that αSyn aggregates exacerbate tau pathophysiology, promoting its hyperphosphorylation [18, 20], fibrillization and spread, thereby potentially contributing to AD progression [27, 28]. Consistent with previous cohort studies [33, 39], we observed that positive αSyn seeding activity in the CSF, indicative of diffuse cortical αSyn co-pathology [33, 34], was more frequent in individuals across the AD spectrum (i.e., amyloid-PET positive) compared to controls, particularly in those with more advanced clinical impairment. Our first main finding was that αSyn SAA positivity was associated with elevated Aβ-related CSF p-tau181 levels, suggesting enhanced tau hyperphosphorylation and secretion of p-tau in response to Aβ in AD patients with evidence of Lewy-body co-pathology. Second, we found that αSyn SAA positivity was linked to stronger Aβ-associated fibrillar tau deposition in AD-typical brain regions, as assessed by flortaucipir tau-PET imaging. This was further substantiated by longitudinal tau-PET analyses, showing that αSyn SAA positivity at baseline was related to faster rates of Aβ-driven tau accumulation in AD typical brain regions, overall supporting the hypothesis that αSyn co-pathology exacerbates the Aβ-driven formation of AD-type neurofibrillary tau pathology. Third, we found that αSyn co-pathology was related to faster AD-related cognitive decline, which was potentially driven by faster tau accumulation in αSyn SAA positive individuals on the AD spectrum (i.e. amyloid-PET positive). Collectively, these findings suggest that αSyn co-pathology, as detected via CSF-based αSyn SAAs, is associated with an acceleration of Aβ-induced tau pathophysiology across the AD spectrum ensuing faster cognitive decline, overall positioning αSyn as a significant modulator of tauopathy in the context of Aβ pathology, as well as clinical disease progression in AD.

Congruent with previous neuropathological studies highlighting a prevalence of up to 50% of αSyn co-pathology in AD patients [6, 7, 9], we found increased αSyn SAA positivity rates in individuals across the AD spectrum (i.e., Aβ+) compared to controls (i.e., Aβ-), with αSyn SAA positivity rates rising alongside clinical severity up to 44% in AD dementia. This finding aligns with previous results from the larger overall ADNI CSF database (N ~ 1600) [33, 42], and with data from European cohorts, reporting increased αSyn SAA positivity across the AD spectrum with 36–45% αSyn SAA positivity rates in AD dementia patients [41, 57]. Therefore, our results converge with post mortem neuropathological evidence [6, 7, 9], pinpointing to αSyn as a key and highly prevalent molecular co-pathology throughout the AD spectrum that can be detected via CSF-based αSyn SAAs.

Addressing our key goal to determine the role of αSyn co-pathology in AD-related tau pathophysiology, our first major finding was that Aβ-associated CSF p-tau181 levels were higher in αSyn SAA positive vs. negative individuals. CSF p-tau increases have previously been shown to be more closely linked to PET-assessed fibrillar Aβ than to fibrillar tau pathology [58] and to reflect Aβ-associated active secretion of newly synthesized p-tau molecules, rather than passive spill out from dead neurons [43, 59]. In this context, it is possible that αSyn co-pathology may strengthen the Aβ-driven neuronal release of hyperphosphorylated p-tau in AD. Tau is released from neurons in an activity-dependent manner, e.g., via entering synaptic vesicles [60,61,62], and Aβ has been found to trigger aberrant neuronal hyperactivity [63, 64], e.g., by impairing glutamate re-uptake [65] and causing decreased GABA sensitivity [66]. Pathomechanistically, Aβ-induced neuronal hyperactivity may therefore promote the synaptic release of p-tau seeds that enter downstream neurons, inducing template-based tau misfolding and aggregation, ensuing a cascade of tau spread across interconnected neurons [45, 61]. Supporting this, we showed recently that higher Aβ triggers neuronal hyperconnectivity, thereby promoting faster tau spread [67]. αSyn is typically located in presynaptic terminals and has been shown to co-regulate the activity-dependent release of neurotransmitters, e.g., via modulating the assembly of SNARE complexes that are key mediators of presynaptic vesicle fusion and neurotransmitter release [68,69,70,71]. Supporting a role of αSyn in neuronal activity, studies in transgenic mice expressing human mutant αSyn found aberrant network hyperexcitability [72, 73], and extracellular αSyn oligomers have been shown to trigger excessive astrocytic glutamate release, which may further drive aberrant neuronal activity and neuronal p-tau release [74]. Yet again, other studies have suggested that pathologically altered αSyn disrupts synaptic signaling and attenuates neuronal activity [75, 76]. Given these opposing findings, the exact role of αSyn in modulating the activity-dependent neuronal release of p-tau in the presence of Aβ deposition remains to be determined. An alternative explanation for our findings is that αSyn may accelerate intra-neuronal tau phosphorylation as shown by several pre-clinical studies [17,18,19,20], suggesting hyperphosphorylated tau seeds being released from neurons. Preliminary evidence along those lines suggests slight increases in CSF and plasma p-tau181 biomarker levels in Parkinson’s disease patients when compared to controls [77, 78]. Yet, the exact mechanisms of how αSyn co-pathology may exacerbate the Aβ-related secretion of p-tau in the context of neuronal activity changes remains to be determined in future studies, where our findings can act as a key starting point to motivate this research.

Our second major finding was that αSyn SAA positivity was associated with stronger Aβ-related aggregation of cortical tau pathology, as shown by elevated Aβ-related tau-PET tracer binding in αSyn SAA positive vs. negative individuals. This association was widespread and found consistently throughout brain regions corresponding to Braak stages I-VI which are commonly used to determine the spatial distribution of tau pathology in AD [35, 48, 79]. This cross-sectional result was further substantiated by longitudinal tau-PET analyses, showing faster Aβ-related tau accumulation in αSyn SAA positive individuals throughout key tau vulnerable brain regions beyond the medial temporal lobe. These results support our central hypothesis that αSyn co-pathology may facilitate the Aβ-driven aggregation and spread of tau in AD and thereby contribute to the progression of AD pathophysiology. Our results are in agreement with previous findings from animal and cell culture models, showing that the induction of pre-formed αSyn fibrils can act as a co-seeding factor for tau, promoting its aggregation into fibrillar forms [23, 24, 27], while knockdown of endogenous αSyn attenuated tau aggregation and spread [27]. Additionally, as described above, αSyn pathology can enhance tau phosphorylation (e.g. via activating the tau specific kinase GSK-3β), thereby potentially rendering tau more aggregation-prone [18]. Further, higher CSF p-tau levels are linked to faster trans-neuronal spread of tau pathology [45], hence the αSyn-pathology related CSF p-tau secretion may also contribute to accelerated tau aggregation and spread. Therefore, αSyn co-pathology may accelerate tau aggregation through both direct interactions such as co-seeding as well as kinase-mediated hyperphosphorylation pathways or increased p-tau secretion ensuing faster tau spreading [23, 24, 27, 45, 80]. Our results are of significant clinical relevance, as tau pathology is highly prognostic of future neurodegeneration [81] and cognitive decline in AD [48, 82]. Results from a successful recent phase 3 anti-Aβ trial have shown further that the clinical efficacy of monoclonal anti-Aβ antibodies is limited by the presence of advanced fibrillar tau pathology [83]. More specifically, the removal of Aβ may no longer yield clinical benefits once tau pathology has accumulated to a substantial degree where it enters a self-driving auto-aggregation cycle that is detached from Aβ pathology [45, 84]. Since our results have shown that αSyn co-pathology accelerates the Aβ-associated aggregation of tau pathology in AD, the presence of αSyn co-pathology may be a limiting factor for anti-Aβ drugs to prevent downstream tau aggregation.

Lastly, we found that CSF αSyn SAA positivity is linked to faster AD-related cognitive decline. This finding recapitulates previous post mortem evidence that αSyn co-pathology contributes to the overall cognitive burden in AD patients [7, 12, 13] and similarly, previous longitudinal cohort studies have shown that CSF αSyn SAA positive patients with an AD biomarker profile show faster cognitive decline, regardless of clinical status [39, 40, 42]. Here, more recent findings from the ADNI cohort could show that αSyn SAA positive individuals show earlier decline in cognition after the onset of amyloidosis, and that cognitive decline accelerates in individuals who convert from αSyn SAA negative to positive after conversion [42]. However, we found only a synergistic effect between αSyn and amyloid-PET, but not between αSyn and tau-PET levels, on faster cognitive decline. Since we found αSyn SAA positivity to be related to faster Aβ-related tau accumulation, this result pattern suggests that αSyn co-pathology accelerates cognitive deterioration in AD primarily by accelerating the Aβ-related aggregation of fibrillar tau pathology and associated symptom worsening. Nevertheless, we also detected an independent main effect of αSyn SAA positivity next to tau pathology on cognitive decline, suggesting that individuals with concomitant αSyn pathology show generally stronger cognitive deficits at any given level of tau severity. Importantly, we only investigated changes in global cognition, and did not specifically assess symptoms that are more specific for αSyn pathology, such as hallucinations, fluctuations in attention and alertness, or motor dysfunction. Here, previous studies have emphasized that αSyn SAA positive AD patients show more pronounced αSyn-related symptoms on top of AD-related cognitive deficits [40], supporting the view that αSyn co-pathology is associated with a more complex clinical syndrome characterized by mixed AD and αSyn-related symptomatology [85]. This finding of concomitant αSyn co-pathology affecting cognition is potentially relevant for patient-level prognosis and clinical trials, which should optimally factor in αSyn pathology as a contributor to cognitive deterioration, next to other key co-pathologies such as small-vessel disease [86] that accelerate cognitive decline in older individuals.

While the overall results provide a converging picture of αSyn contributing to Aβ-related tau pathophysiology and cognitive decline across the AD spectrum, several limitations should be considered when interpreting the results of the current study. First, CSF-based αSyn SAAs determine the presence or absence of αSyn co-pathology as a binary measure, based on seeding activity of αSyn in the CSF [31]. However, αSyn co-pathology is most likely a continuum ranging from low to high αSyn burden, and quantitation of αSyn severity using SAAs is not yet established. Therefore, we cannot determine whether more severe αSyn co-pathology further increases the effect of Aβ on tau accumulation. In addition, a synergistic effect of αSyn on promoting tau aggregation potentially requires co-localization and close interaction between both proteins. This view is supported by in vitro and animal studies [24, 28, 87] and potentially showcased by a case report of an atypical AD patient with strongly lateralized and co-localized αSyn and tau deposition at autopsy. Since CSF-based αSyn SAAs do not encode any spatial information about the pattern of αSyn co-pathology, we can, however, not determine whether local αSyn promotes co-localized tau accumulation until reliable PET tracers for αSyn become available. Investigating the spatial relationship between αSyn deposits and tau aggregation and spread will therefore be a major endeavor for future PET investigations on the role of αSyn co-pathology in AD pathophysiology once αSyn tracers are established. However, CSF-based αSyn SAAs typically show highest sensitivity for detecting diffuse cortical rather than focal subcortical or brainstem αSyn co-pathology in AD, as shown by post-mortem assessments [33, 34]. Therefore, a positive αSyn SAA result likely indicates diffuse cortical αSyn co-pathology, thereby increasing the likelihood of αSyn co-pathology promoting the cortical aggregation and spread of tau. Nevertheless, protein-protein interactions cannot be mapped in living humans, hence the exact mechanisms by which αSyn and tau interact to promote tau aggregation and spread remain to be investigated by studies employing in vitro or animal model systems. In addition, the current study did not include longitudinal CSF p-tau181 data due to limited availability, therefore these results remain to be confirmed by future studies investigating whether aSyn co-pathology drives faster and earlier p-tau increases in the context of Aβ pathology. Lastly, we determined the impact of aSyn co-pathology on global cognition using ADAS13 or MMSE assessments. Yet, αSyn co-pathology in AD may manifest in motor symptoms beyond AD-typical cognitive manifestations. Since standardized assessment of Parkinsonian sypmtoms (e.g. UPDRS) is not part of the clinical ADNI workflows, addressing this remains to be determined by future studies.

In conclusion, our findings suggest that αSyn co-pathology, as detected via CSF-based αSyn SAAs, plays a critical role in accelerating Aβ-induced tau pathophysiology and cognitive decline across the AD spectrum. Our findings are a critical extension of previous pre-clinical and in vitro investigations on the interaction between Aβ, tau and αSyn, overall confirming the idea that αSyn co-pathology may actively modulate the amyloid cascade and accelerate the transition from amyloidosis to tauopathy. These findings have implications for disease prognostication, since αSyn co-pathology could be considered as a factor that may additionally promote tau aggregation and spread, thereby contributing to the development of AD dementia. Yet, the contribution of αSyn SAA positivity to individualized disease prognostication models should be investigated in future studies. Together, our results should motivate further research, assessing the exact mechanisms by which αSyn may accelerate the Aβ-tau axis, which could help us understand how to prevent the transition from amyloidosis to tauopathy in AD and potentially establish αSyn co-pathology as a treatment target in AD.

Data availability

The data that support the findings of this study are available from the ADNI database (adni.loni.usc.edu) upon registration and compliance with the data use agreement.

Abbreviations

AD:

Alzheimer’s Disease

Aβ:

Amyloid-beta

αSyn:

Alpha-Synuclein

SAA:

Seed Amplification Assay

PET:

Positron Emission Tomography

CSF:

Cerebrospinal Fluid

p-tau181:

Phosphorylated tau at threonine 181

SUVR:

Standardized Uptake Value Ratio

MMSE:

Mini-Mental State Examination

CDR:

Clinical Dementia Rating

MCI:

Mild Cognitive Impairment

CN:

Cognitively Normal

MRI:

Magnetic Resonance Imaging

ADNI:

Alzheimer’s Disease Neuroimaging Initiative

GSK-3β:

Glycogen Synthase Kinase 3 Beta

References

  1. Trejo-Lopez JA, Yachnis AT, Prokop S. Neuropathology of Alzheimer’s disease. Neurotherapeutics. 2022;19:173–85.

    Article  CAS  PubMed  Google Scholar 

  2. DeTure MA, Dickson DW. The neuropathological diagnosis of Alzheimer’s disease. Mol Neurodegener. 2019;14:32.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Jack CR Jr., Andrews JS, Beach TG, Buracchio T, Dunn B, Graf A, Hansson O, Ho C, Jagust W, McDade E, et al. Revised criteria for diagnosis and staging of Alzheimer’s disease: Alzheimer’s association workgroup. Alzheimers Dement. 2024;20:5143–69.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Hardy JA, Higgins GA. Alzheimer’s disease: the amyloid cascade hypothesis. Science. 1992;256:184–5.

    Article  CAS  PubMed  Google Scholar 

  5. Gibbons GS, Lee VMY, Trojanowski JQ. Mechanisms of Cell-to-Cell transmission of pathological Tau: A review. JAMA Neurol. 2019;76:101–8.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Hamilton RL. Lewy bodies in Alzheimer’s disease: a neuropathological review of 145 cases using alpha-synuclein immunohistochemistry. Brain Pathol. 2000;10:378–84.

    Article  CAS  PubMed  Google Scholar 

  7. Robinson JL, Lee EB, Xie SX, Rennert L, Suh E, Bredenberg C, Caswell C, Van Deerlin VM, Yan N, Yousef A, et al. Neurodegenerative disease concomitant proteinopathies are prevalent, age-related and APOE4-associated. Brain. 2018;141:2181–93.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Robinson JL, Richardson H, Xie SX, Suh E, Van Deerlin VM, Alfaro B, Loh N, Porras-Paniagua M, Nirschl JJ, Wolk D, et al. The development and convergence of co-pathologies in Alzheimer’s disease. Brain. 2021;144:953–62.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Spina S, La Joie R, Petersen C, Nolan AL, Cuevas D, Cosme C, Hepker M, Hwang JH, Miller ZA, Huang EJ, et al. Comorbid neuropathological diagnoses in early versus late-onset Alzheimer’s disease. Brain. 2021;144:2186–98.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Robinson JL, Xie SX, Baer DR, Suh E, Van Deerlin VM, Loh NJ, Irwin DJ, McMillan CT, Wolk DA, Chen-Plotkin A, et al. Pathological combinations in neurodegenerative disease are heterogeneous and disease-associated. Brain. 2023;146:2557–69.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Calabresi P, Mechelli A, Natale G, Volpicelli-Daley L, Di Lazzaro G, Ghiglieri V. Alpha-synuclein in Parkinson’s disease and other synucleinopathies: from overt neurodegeneration back to early synaptic dysfunction. Cell Death Dis. 2023;14:176.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kraybill ML, Larson EB, Tsuang DW, Teri L, McCormick WC, Bowen JD, Kukull WA, Leverenz JB, Cherrier MM. Cognitive differences in dementia patients with autopsy-verified AD, lewy body pathology, or both. Neurology. 2005;64:2069–73.

    Article  CAS  PubMed  Google Scholar 

  13. Olichney JM, Galasko D, Salmon DP, Hofstetter CR, Hansen LA, Katzman R, Thal LJ. Cognitive decline is faster in lewy body variant than in Alzheimer’s disease. Neurology. 1998;51:351–7.

    Article  CAS  PubMed  Google Scholar 

  14. Collij LE, Mastenbroek SE, Mattsson-Carlgren N, Strandberg O, Smith R, Janelidze S, Palmqvist S, Ossenkoppele R, Hansson O. Lewy body pathology exacerbates brain hypometabolism and cognitive decline in Alzheimer’s disease. Nat Commun. 2024;15:8061.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Burré J, Sharma M, Südhof TC. Cell biology and pathophysiology of α-Synuclein. Cold Spring Harb Perspect Med. 2018;8(3):a024091. https://doiorg.publicaciones.saludcastillayleon.es/10.1101/cshperspect.a024091. PMID: 28108534; PMCID: PMC5519445.

  16. Paterno G, Bell BM, Gorion KM, Prokop S, Giasson BI. Reassessment of neuronal Tau distribution in adult human brain and implications for Tau pathobiology. Acta Neuropathol Commun. 2022;10:94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Shim KH, Kang MJ, Youn YC, An SSA, Kim S. Alpha-synuclein: a pathological factor with Abeta and Tau and biomarker in Alzheimer’s disease. Alzheimers Res Ther. 2022;14:201.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Duka T, Duka V, Joyce JN, Sidhu A. Alpha-Synuclein contributes to GSK-3beta-catalyzed Tau phosphorylation in Parkinson’s disease models. FASEB J. 2009;23:2820–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kawakami F, Suzuki M, Shimada N, Kagiya G, Ohta E, Tamura K, Maruyama H, Ichikawa T. Stimulatory effect of alpha-synuclein on the tau-phosphorylation by GSK-3beta. FEBS J. 2011;278:4895–904.

    Article  CAS  PubMed  Google Scholar 

  20. Duka T, Rusnak M, Drolet RE, Duka V, Wersinger C, Goudreau JL, Sidhu A. Alpha-synuclein induces hyperphosphorylation of Tau in the MPTP model of parkinsonism. FASEB J. 2006;20:2302–12.

    Article  CAS  PubMed  Google Scholar 

  21. Wegmann S, Biernat J, Mandelkow E. A current view on Tau protein phosphorylation in Alzheimer’s disease. Curr Opin Neurobiol. 2021;69:131–8.

    Article  CAS  PubMed  Google Scholar 

  22. Moussaud S, Jones DR, Moussaud-Lamodière EL, Delenclos M, Ross OA, McLean PJ. Alpha-synuclein and Tau: teammates in neurodegeneration? Mol Neurodegener. 2014;9:43.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Giasson BI, Forman MS, Higuchi M, Golbe LI, Graves CL, Kotzbauer PT, Trojanowski JQ, Lee VM. Initiation and synergistic fibrillization of Tau and alpha-synuclein. Science. 2003;300:636–40.

    Article  CAS  PubMed  Google Scholar 

  24. Guo JL, Covell DJ, Daniels JP, Iba M, Stieber A, Zhang B, Riddle DM, Kwong LK, Xu Y, Trojanowski JQ, Lee VM. Distinct alpha-synuclein strains differentially promote Tau inclusions in neurons. Cell. 2013;154:103–17.

    Article  CAS  PubMed  Google Scholar 

  25. Lu J, Zhang S, Ma X, Jia C, Liu Z, Huang C, Liu C, Li D. Structural basis of the interplay between alpha-synuclein and Tau in regulating pathological amyloid aggregation. J Biol Chem. 2020;295:7470–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Arima K, Mizutani T, Alim MA, Tonozuka-Uehara H, Izumiyama Y, Hirai S, Ueda K. NACP/alpha-synuclein and Tau constitute two distinctive subsets of filaments in the same neuronal inclusions in brains from a family of parkinsonism and dementia with lewy bodies: double-immunolabeling fluorescence and electron microscopic studies. Acta Neuropathol. 2000;100:115–21.

    Article  CAS  PubMed  Google Scholar 

  27. Bassil F, Meymand ES, Brown HJ, Xu H, Cox TO, Pattabhiraman S, et al. α-Synuclein modulates tau spreading in mouse brains. J Exp Med. 2021;218(1):e20192193. https://doiorg.publicaciones.saludcastillayleon.es/10.1084/jem.20192193. PMID: 33091110; PMCID: PMC7588140.

  28. Williams T, Sorrentino Z, Weinrich M, Giasson BI, Chakrabarty P. Differential cross-seeding properties of Tau and alpha-synuclein in mouse models of Tauopathy and synucleinopathy. Brain Commun. 2020;2:fcaa090.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Magalhaes P, Lashuel HA. Opportunities and challenges of alpha-synuclein as a potential biomarker for Parkinson’s disease and other synucleinopathies. NPJ Parkinsons Dis. 2022;8:93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Concha-Marambio L, Pritzkow S, Shahnawaz M, Farris CM, Soto C. Seed amplification assay for the detection of pathologic alpha-synuclein aggregates in cerebrospinal fluid. Nat Protoc. 2023;18:1179–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Bellomo G, De Luca CMG, Paoletti FP, Gaetani L, Moda F, Parnetti L. α-Synuclein seed amplification assays for diagnosing synucleinopathies: the way forward. Neurology. 2022;99:195–205.

    Article  CAS  PubMed  Google Scholar 

  32. Fernandes Gomes B, Farris CM, Ma Y, Concha-Marambio L, Lebovitz R, Nellgard B, Dalla K, Constantinescu J, Constantinescu R, Gobom J, et al. alpha-Synuclein seed amplification assay as a diagnostic tool for parkinsonian disorders. Parkinsonism Relat Disord. 2023;117:105807.

    Article  CAS  PubMed  Google Scholar 

  33. Tosun D, Hausle Z, Iwaki H, Thropp P, Lamoureux J, Lee EB, MacLeod K, McEvoy S, Nalls M, Perrin RJ, et al. A cross-sectional study of alpha-synuclein seed amplification assay in Alzheimer’s disease neuroimaging initiative: prevalence and associations with Alzheimer’s disease biomarkers and cognitive function. Alzheimers Dement. 2024;20:5114–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Levin J, Baiardi S, Quadalti C, Rossi M, Mammana A, Voglein J, Bernhardt A, Perrin RJ, Jucker M, Preische O, et al. alpha-Synuclein seed amplification assay detects lewy body co-pathology in autosomal dominant Alzheimer’s disease late in the disease course and dependent on lewy pathology burden. Alzheimers Dement. 2024;20:4351–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 1991;82:239–59.

    Article  CAS  PubMed  Google Scholar 

  36. Vogel JW, Young AL, Oxtoby NP, Smith R, Ossenkoppele R, Strandberg OT, La Joie R, Aksman LM, Grothe MJ, Iturria-Medina Y, et al. Four distinct trajectories of Tau deposition identified in Alzheimer’s disease. Nat Med. 2021;27:871–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Franzmeier N, Dewenter A, Frontzkowski L, Dichgans M, Rubinski A, Neitzel J, et al. Patientcentered connectivity-based prediction of tau pathology spread in Alzheimer’s disease. Sci Adv. 2020;6(48):eabd1327. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/sciadv.abd1327. PMID: 33246962; PMCID: PMC7695466.

  38. Franzmeier N, Neitzel J, Rubinski A, Smith R, Strandberg O, Ossenkoppele R, Hansson O, Ewers M. Alzheimer’s disease neuroimaging I: functional brain architecture is associated with the rate of Tau accumulation in Alzheimer’s disease. Nat Commun. 2020;11:347.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Palmqvist S, Rossi M, Hall S, Quadalti C, Mattsson-Carlgren N, Dellavalle S, Tideman P, Pereira JB, Nilsson MH, Mammana A, et al. Cognitive effects of lewy body pathology in clinically unimpaired individuals. Nat Med. 2023;29:1971–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Quadalti C, Palmqvist S, Hall S, Rossi M, Mammana A, Janelidze S, Dellavalle S, Mattsson-Carlgren N, Baiardi S, Stomrud E, et al. Clinical effects of lewy body pathology in cognitively impaired individuals. Nat Med. 2023;29:1964–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Bellomo G, Toja A, Paolini Paoletti F, Ma Y, Farris CM, Gaetani L, Salvadori N, Chiasserini D, Wojdaƚa AL, Concha-Marambio L, Parnetti L. Investigating alpha-synuclein co-pathology in Alzheimer’s disease by means of cerebrospinal fluid alpha-synuclein seed amplification assay. Alzheimers Dement. 2024;20:2444–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Tosun D, Hausle Z, Thropp P, Concha-Marambio L, Lamoureux J, Lebovitz R, Shaw LM, Singleton AB, Weiner MW, Alzheimer’s Disease Neuroimaging I, Blauwendraat C. Association of CSF alpha-synuclein seed amplification assay positivity with disease progression and cognitive decline: A longitudinal Alzheimer’s Disease Neuroimaging Initiative study. Alzheimers Dement 2024, 20:8444–8460.

  43. Sato C, Barthelemy NR, Mawuenyega KG, Patterson BW, Gordon BA, Jockel-Balsarotti J, Sullivan M, Crisp MJ, Kasten T, Kirmess KM, et al. Tau kinetics in neurons and the human central nervous system. Neuron. 2018;97:1284–e12981287.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Groot C, Smith R, Stomrud E, Binette AP, Leuzy A, Wuestefeld A, Wisse LEM, Palmqvist S, Mattsson-Carlgren N, Janelidze S, et al. Phospho-tau with subthreshold Tau-PET predicts increased Tau accumulation rates in amyloid-positive individuals. Brain. 2023;146:1580–91.

    Article  PubMed  Google Scholar 

  45. Pichet Binette A, Franzmeier N, Spotorno N, Ewers M, Brendel M, Biel D, Strandberg O, Janelidze S, Palmqvist S, Mattsson-Carlgren N, et al. Amyloid-associated increases in soluble Tau relate to Tau aggregation rates and cognitive decline in early Alzheimer’s disease. Nat Commun. 2022;13:6635.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Steward A, Biel D, Brendel M, Dewenter A, Roemer S, Rubinski A, Luan Y, Dichgans M, Ewers M, Franzmeier N. Alzheimer’s disease neuroimaging I: functional network segregation is associated with attenuated Tau spreading in Alzheimer’s disease. Alzheimers Dement. 2023;19:2034–46.

    Article  PubMed  Google Scholar 

  47. Steward A, Biel D, Dewenter A, Roemer S, Wagner F, Dehsarvi A, et al. ApoE4 and connectivity-mediated spreading of Tau pathology at lower amyloid levels. JAMA Neurol. 2023;80(12):1295–306. https://doiorg.publicaciones.saludcastillayleon.es/10.1001/jamaneurol.2023.4038. PMID: 37930695; PMCID: PMC10628846.

  48. Biel D, Brendel M, Rubinski A, Buerger K, Janowitz D, Dichgans M, Franzmeier N. Alzheimer’s disease neuroimaging I: Tau-PET and in vivo Braak-staging as prognostic markers of future cognitive decline in cognitively normal to demented individuals. Alzheimers Res Ther. 2021;13:137.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Franzmeier N, Dehsarvi A, Steward A, Biel D, Dewenter A, Roemer SN, Wagner F, Gross M, Brendel M, Moscoso A, et al. Elevated CSF GAP-43 is associated with accelerated Tau accumulation and spread in Alzheimer’s disease. Nat Commun. 2024;15:202.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Franzmeier N, Ossenkoppele R, Brendel M, Rubinski A, Smith R, Kumar A, Mattsson-Carlgren N, Strandberg O, Duering M, Buerger K, et al. The BIN1 rs744373 Alzheimer’s disease risk SNP is associated with faster Abeta-associated Tau accumulation and cognitive decline. Alzheimers Dement. 2022;18:103–15.

    Article  CAS  PubMed  Google Scholar 

  51. Guo T, Korman D, La Joie R, Shaw LM, Trojanowski JQ, Jagust WJ, Landau SM. Alzheimer’s disease neuroimaging I: normalization of CSF pTau measurement by Abeta(40) improves its performance as a biomarker of Alzheimer’s disease. Alzheimers Res Ther. 2020;12:97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Landau SM, Mintun MA, Joshi AD, Koeppe RA, Petersen RC, Aisen PS, Weiner MW, Jagust WJ. Alzheimer’s disease neuroimaging I: amyloid deposition, hypometabolism, and longitudinal cognitive decline. Ann Neurol. 2012;72:578–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Royse SK, Minhas DS, Lopresti BJ, Murphy A, Ward T, Koeppe RA, Bullich S, DeSanti S, Jagust WJ, Landau SM. Alzheimer’s disease neuroimaging I: validation of amyloid PET positivity thresholds in centiloids: a multisite PET study approach. Alzheimers Res Ther. 2021;13:99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Baker SL, Maass A, Jagust WJ. Considerations and code for partial volume correcting [(18)F]-AV-1451 Tau PET data. Data Brief. 2017;15:648–57.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Schaefer A, Kong R, Gordon EM, Laumann TO, Zuo XN, Holmes AJ, Eickhoff SB, Yeo BTT. Local-Global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cereb Cortex. 2018;28:3095–114.

    Article  PubMed  Google Scholar 

  56. Klunk WE, Koeppe RA, Price JC, Benzinger TL, Devous MD, Sr., Jagust WJ, Johnson KA, Mathis CA, Minhas D, Pontecorvo MJ, et al. The centiloid project: standardizing quantitative amyloid plaque Estimation by PET. Alzheimers Dement. 2015;11:1–e1511.

    Article  PubMed  Google Scholar 

  57. Pilotto A, Bongianni M, Tirloni C, Galli A, Padovani A, Zanusso G. CSF alpha-synuclein aggregates by seed amplification and clinical presentation of AD. Alzheimers Dement. 2023;19:3754–9.

    Article  CAS  PubMed  Google Scholar 

  58. Therriault J, Vermeiren M, Servaes S, Tissot C, Ashton NJ, Benedet AL, Karikari TK, Lantero-Rodriguez J, Brum WS, Lussier FZ, et al. Association of phosphorylated Tau biomarkers with amyloid positron emission tomography vs Tau positron emission tomography. JAMA Neurol. 2023;80:188–99.

    Article  PubMed  Google Scholar 

  59. Brunello CA, Merezhko M, Uronen RL, Huttunen HJ. Mechanisms of secretion and spreading of pathological Tau protein. Cell Mol Life Sci. 2020;77:1721–44.

    Article  CAS  PubMed  Google Scholar 

  60. Liu L, Drouet V, Wu JW, Witter MP, Small SA, Clelland C, Duff K. Trans-synaptic spread of Tau pathology in vivo. PLoS ONE. 2012;7:e31302.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Wu JW, Hussaini SA, Bastille IM, Rodriguez GA, Mrejeru A, Rilett K, Sanders DW, Cook C, Fu H, Boonen RA, et al. Neuronal activity enhances Tau propagation and Tau pathology in vivo. Nat Neurosci. 2016;19:1085–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Pooler AM, Phillips EC, Lau DH, Noble W, Hanger DP. Physiological release of endogenous Tau is stimulated by neuronal activity. EMBO Rep. 2013;14:389–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Busche MA, Eichhoff G, Adelsberger H, Abramowski D, Wiederhold KH, Haass C, Staufenbiel M, Konnerth A, Garaschuk O. Clusters of hyperactive neurons near amyloid plaques in a mouse model of Alzheimer’s disease. Science. 2008;321:1686–9.

    Article  CAS  PubMed  Google Scholar 

  64. Hector A, Brouillette J. Hyperactivity induced by soluble Amyloid-beta oligomers in the early stages of Alzheimer’s disease. Front Mol Neurosci. 2020;13:600084.

    Article  CAS  PubMed  Google Scholar 

  65. Zott B, Simon MM, Hong W, Unger F, Chen-Engerer HJ, Frosch MP, Sakmann B, Walsh DM, Konnerth A. A vicious cycle of beta amyloid-dependent neuronal hyperactivation. Science. 2019;365:559–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Limon A, Reyes-Ruiz JM, Miledi R. Loss of functional GABA(A) receptors in the alzheimer diseased brain. Proc Natl Acad Sci U S A. 2012;109:10071–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Roemer-Cassiano SN, Wagner F, Evangelista L, Rauchmann BS, Dehsarvi A, Steward A, Dewenter A, Biel D, Zhu Z, Pescoller J, et al. Amyloid-associated hyperconnectivity drives Tau spread across connected brain regions in Alzheimer’s disease. Sci Transl Med. 2025;17:eadp2564.

    Article  CAS  PubMed  Google Scholar 

  68. Stefanis L. alpha-Synuclein in Parkinson’s disease. Cold Spring Harb Perspect Med. 2012;2:a009399.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Hawk BJD, Khounlo R, Shin YK. Alpha-Synuclein continues to enhance SNARE-Dependent vesicle Docking at exorbitant concentrations. Front Neurosci. 2019;13:216.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Burre J, Sharma M, Tsetsenis T, Buchman V, Etherton MR, Sudhof TC. Alpha-synuclein promotes SNARE-complex assembly in vivo and in vitro. Science. 2010;329:1663–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Burre J. The synaptic function of alpha-Synuclein. J Parkinsons Dis. 2015;5:699–713.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Tweedy C, Kindred N, Curry J, Williams C, Taylor JP, Atkinson P, Randall F, Erskine D, Morris CM, Reeve AK, et al. Hippocampal network hyperexcitability in young Transgenic mice expressing human mutant alpha-synuclein. Neurobiol Dis. 2021;149:105226.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Al-Musawi I, Dennis BH, Clowry GJ, LeBeau FEN. Evidence for prodromal changes in neuronal excitability and neuroinflammation in the hippocampus in young alpha-synuclein (A30P) Transgenic mice. Front Dement. 2024;3:1404841.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Trudler D, Sanz-Blasco S, Eisele YS, Ghatak S, Bodhinathan K, Akhtar MW, Lynch WP, Pina-Crespo JC, Talantova M, Kelly JW. Lipton SA: alpha-Synuclein oligomers induce glutamate release from astrocytes and excessive extrasynaptic NMDAR activity in neurons, thus contributing to synapse loss. J Neurosci. 2021;41:2264–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Calo L, Wegrzynowicz M, Santivanez-Perez J, Grazia Spillantini M. Synaptic failure and alpha-synuclein. Mov Disord. 2016;31:169–77.

    Article  CAS  PubMed  Google Scholar 

  76. Fonseca-Ornelas L, Viennet T, Rovere M, Jiang H, Liu L, Nuber S, Ericsson M, Arthanari H, Selkoe DJ. Altered conformation of alpha-synuclein drives dysfunction of synaptic vesicles in a synaptosomal model of Parkinson’s disease. Cell Rep. 2021;36:109333.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Batzu L, Rota S, Hye A, Heslegrave A, Trivedi D, Gibson LL, Farrell C, Zinzalias P, Rizos A, Zetterberg H, et al. Plasma p-tau181, neurofilament light chain and association with cognition in Parkinson’s disease. NPJ Parkinsons Dis. 2022;8:154.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Mollenhauer B, Caspell-Garcia CJ, Coffey CS, Taylor P, Shaw LM, Trojanowski JQ, Singleton A, Frasier M, Marek K, Galasko D. Parkinson’s progression marker I: longitudinal CSF biomarkers in patients with early Parkinson disease and healthy controls. Neurology. 2017;89:1959–69.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Scholl M, Lockhart SN, Schonhaut DR, O’Neil JP, Janabi M, Ossenkoppele R, Baker SL, Vogel JW, Faria J, Schwimmer HD, et al. PET imaging of Tau deposition in the aging human brain. Neuron. 2016;89:971–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Waxman EA, Giasson BI. Induction of intracellular Tau aggregation is promoted by alpha-synuclein seeds and provides novel insights into the hyperphosphorylation of Tau. J Neurosci. 2011;31:7604–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. La Joie R, Visani AV, Baker SL, Brown JA, Bourakova V, Cha J, et al. Prospective longitudinal atrophy in Alzheimer’s disease correlates with the intensity and topography of baseline tau-PET. Sci Transl Med. 2020;12(524):eaau5732. https://doiorg.publicaciones.saludcastillayleon.es/10.1126/scitranslmed.aau5732. PMID: 31894103; PMCID: PMC7035952.

  82. Ossenkoppele R, Smith R, Mattsson-Carlgren N, Groot C, Leuzy A, Strandberg O, Palmqvist S, Olsson T, Jogi J, Stormrud E, et al. Accuracy of Tau positron emission tomography as a prognostic marker in preclinical and prodromal alzheimer disease: A Head-to-Head comparison against amyloid positron emission tomography and magnetic resonance imaging. JAMA Neurol. 2021;78:961–71.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Sims JR, Zimmer JA, Evans CD, Lu M, Ardayfio P, Sparks J, Wessels AM, Shcherbinin S, Wang H, Monkul Nery ES, et al. Donanemab in early symptomatic alzheimer disease: the TRAILBLAZER-ALZ 2 randomized clinical trial. JAMA. 2023;330:512–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Meisl G, Hidari E, Allinson K, Rittman T, DeVos SL, Sanchez JS, Xu CK, Duff KE, Johnson KA, Rowe JB, et al. In vivo rate-determining steps of Tau seed accumulation in Alzheimer’s disease. Sci Adv. 2021;7:eabh1448.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Hansen L, Salmon D, Galasko D, Masliah E, Katzman R, DeTeresa R, Thal L, Pay MM, Hofstetter R, Klauber M, et al. The lewy body variant of Alzheimer’s disease: a clinical and pathologic entity. Neurology. 1990;40:1–8.

    Article  CAS  PubMed  Google Scholar 

  86. Dichgans M, Leys D. Vascular cognitive impairment. Circ Res. 2017;120:573–91.

    Article  CAS  PubMed  Google Scholar 

  87. Köppen J, Schulze A, Machner L, Wermann M, Eichentopf R, Guthardt M, et al. Amyloid-beta peptides trigger aggregation of alpha-Synuclein in vitro. Molecules. 2020;25(3):580. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/molecules25030580. PMID: 32013170; PMCID: PMC7037551.

Download references

Acknowledgements

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of 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 at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.

Funding

This work was supported by grants of the Bright Focus Foundation (A2021026S), Alzheimer’s Association (AARG-22-973496), the German Parkinson Foundation and the Gerhard and Ilse Schick Stiftung awarded to NF.

Author information

Author notes

  1. Johannes Levin, Matthias Brendel and Günter U. Höglinger contributed equally to this work.

Authors and Affiliations

  1. Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany

    Nicolai Franzmeier, Sebastian Niclas Roemer-Cassiano, Amir Dehsarvi, Anna Dewenter, Anna Steward, Davina Biel, Lukas Frontzkowski, Zeyu Zhu, Julia Pescoller, Fabian Wagner, Fabian Hirsch & Hannah de Bruin

  2. Munich Cluster for Systems Neurology (SyNergy), Munich, Germany

    Nicolai Franzmeier, Johannes Levin, Matthias Brendel & Günter U. Höglinger

  3. The Sahlgrenska Academy, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, University of Gothenburg, Mölndal and Gothenburg, Sweden

    Nicolai Franzmeier & Michael Schöll

  4. Department of Neurology, LMU University Hospital, University Hospital, LMU Munich, Munich, Germany

    Sebastian Niclas Roemer-Cassiano, Alexander Maximilian Bernhardt, Carla Palleis, Johannes Levin & Günter U. Höglinger

  5. German Center for Neurodegenerative Diseases (DZNE), Munich, Germany

    Alexander Maximilian Bernhardt, Johannes Levin, Matthias Brendel & Günter U. Höglinger

  6. Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany

    Lukas Frontzkowski, Johannes Gnörich & Matthias Brendel

  7. Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands

    Hannah de Bruin & Rik Ossenkoppele

  8. Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands

    Hannah de Bruin & Rik Ossenkoppele

  9. Clinical Memory Research Unit, Lund University, Lund, Sweden

    Rik Ossenkoppele

  10. Center for Neuropathology and Prion Research, University Hospital, LMU Munich, Munich, Germany

    Felix Strübing

  11. Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden

    Michael Schöll

  12. Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK

    Michael Schöll

  13. Department of Neuropsychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden

    Michael Schöll

Authors
  1. Nicolai Franzmeier
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Sebastian Niclas Roemer-Cassiano
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Alexander Maximilian Bernhardt
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Amir Dehsarvi
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Anna Dewenter
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Anna Steward
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Davina Biel
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Lukas Frontzkowski
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Zeyu Zhu
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Johannes Gnörich
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Julia Pescoller
    View author publications

    You can also search for this author inPubMed Google Scholar

  12. Fabian Wagner
    View author publications

    You can also search for this author inPubMed Google Scholar

  13. Fabian Hirsch
    View author publications

    You can also search for this author inPubMed Google Scholar

  14. Hannah de Bruin
    View author publications

    You can also search for this author inPubMed Google Scholar

  15. Rik Ossenkoppele
    View author publications

    You can also search for this author inPubMed Google Scholar

  16. Carla Palleis
    View author publications

    You can also search for this author inPubMed Google Scholar

  17. Felix Strübing
    View author publications

    You can also search for this author inPubMed Google Scholar

  18. Michael Schöll
    View author publications

    You can also search for this author inPubMed Google Scholar

  19. Johannes Levin
    View author publications

    You can also search for this author inPubMed Google Scholar

  20. Matthias Brendel
    View author publications

    You can also search for this author inPubMed Google Scholar

  21. Günter U. Höglinger
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

NF: study concept and design data analysis, drafting the manuscript, SNR, AMB, data analysis, critical revision of the manuscript. ADew, ADeh, AS, DB, LF, ZZ, JG, JP, FW, FH, data processing, critical revision of the manuscript, HdB, RO, CP, FS, MS, critical revision of the manuscript, JL, MB, GUH, study concept and design, drafting the manuscript.

Corresponding author

Correspondence to Nicolai Franzmeier.

Ethics declarations

Ethics approval and consent to participate

All study procedures were conducted in accordance with the declaration of Helsinki, ethical approval was obtained by ADNI investigators. All study participants provided written informed consent.

Consent for publication

Not applicable.

Competing interests

None.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Franzmeier, N., Roemer-Cassiano, S.N., Bernhardt, A.M. et al. Alpha synuclein co-pathology is associated with accelerated amyloid-driven tau accumulation in Alzheimer’s disease. Mol Neurodegeneration 20, 31 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13024-025-00822-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13024-025-00822-3

Molecular Neurodegeneration

ISSN: 1750-1326