Alpha-Synuclein co-pathology in Alzheimer’s Disease drives tau accumulation

Alpha-Synuclein co-pathology in Alzheimer’s Disease drives tau accumulation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Alpha-Synuclein co-pathology in Alzheimer’s Disease drives tau accumulation Felix L. Struebing, Xiaoxuan Song, Teodoro De Vecchi, Jeannine Widmann, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6494882/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The molecular basis for accelerated cognitive decline seen in Alzheimer’s Disease (AD) cases presenting with cortical alpha-Synuclein (SNCA/⍺-Syn) co-pathology is not well understood. We show that such AD co-pathology brains are characterized by an increased polygenic risk score for Parkinson’s Disease (PD), which is related to an enrichment in the MAPT H1 haplotype as well as risk factors known to increase SNCA transcription. AD + ASYN brains express higher levels of ⍺-Syn and neuronal microtubule-associated protein tau (MAPT), and increasing SNCA expression is sufficient to drive transcription, translation and phosphorylation of tau. In addition, tau is significantly elevated in subjects with a positive cerebrospinal fluid ⍺-Syn seeding aggregation assay. Our results reveal a hitherto unknown link between the pathogenesis of AD and PD whereby tau and ⍺-Syn synergistically drive dementia-related pathology. Alzheimer’s Disease Parkinson’s Disease Genetic Risk Multiomics Bioinformatics tau alpha-synuclein iPSCs Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Alzheimer’s Disease (AD) is the most common neurodegenerative disorder leading to dementia 1 . Neuropathologically, AD is characterized by insoluble deposits of β-Amyloid and tau protein in specific brain regions. Parkinson’s Disease (PD) is another frequent neurodegenerative disorder that initially presents with movement disorder, but PD can also lead to dementia 2 . Unlike AD, the pathognomonic substrates of PD are aggregates of the protein alpha-Synuclein (⍺-Syn). However, there is substantial cross-talk between AD and PD pathology, with tau or β-Amyloid deposits being sometimes observed in PD, and ⍺-Syn pathology being present in up to 50% of AD cases 3 , 4 . While a diagnosis of AD can be made intra vitam with the help of plasma, CSF and imaging biomarkers, autopsy of post-mortem brain tissue often yields additional co-pathologies and thus represents the gold standard in classifying neurodegenerative syndromes 5 . The strongest molecular correlate to cognitive impairment, a unifying late symptom across most neurodegenerative disorders, is brain tau load 6 , 7 . Interestingly, isolated tau pathology is rare 8 , and the association with cognitive impairment is stronger when β-Amyloid plaques are also present, such as in AD. It has been known that AD cases presenting with ⍺-Syn co-pathology have a faster course of cognitive impairment and functional decline 9 – 11 . This notion is corroborated by experiments demonstrating worse behavioral and cognitive outcomes in mouse and in vitro models of tau/⍺-Syn co-pathology 12 – 14 . However, a molecular explanation for this phenomenon in humans is still lacking. In this study, we re-evaluate neuropathologically diagnosed late-onset AD patients who had donated their brain tissue to the NeuroBioBank Munich for ⍺-Syn pathology as defined by McKeith 15 and Braak 10 . In a cohort of 135 cases, we find that approximately 25% show neocortical ⍺-Syn pathology, representing the highest Braak stage 6. Using a hypothesis-free approach, we discover altered polygenic risk scores for AD patients with ⍺-Syn co-pathology. Following up on this lead, we demonstrate an intimate dialog between the genes encoding ⍺-Syn ( SNCA ) and tau ( MAPT ), and we uncover that SNCA expression is sufficient to increase pathogenic tau. Our results illuminate the molecular basis for ⍺-Syn co-pathology in AD, and they offer mechanistic insight on the accelerated cognitive decline seen in this group of dementias. Results Altered polygenic risk scores distinguish AD from AD + ASYN From the inventory of the NeuroBioBank Munich, we selected 135 cases that were neuropathologically diagnosed with AD (Supp. Table 1). Of these, 35 had neocortical ⍺-Syn pathology (hereafter as a group referred to as AD + ASYN), corresponding to the highest Braak stage 6, whereas 100 had no appreciable ⍺-Syn pathology (hereafter termed AD, Fig. 1 a). There was no difference in APOE genotypes between the AD and the AD + ASYN groups (p = 0.33), and they did not differ in the distribution of tau (Braak&Braak) stages 17 (p = 0.15, Fig. 1 b). To explore the genetic contributions related to ⍺-Syn co-pathology, we performed whole genome sequencing (WGS) and calculated polygenic risk scores (PRS) for a variety of traits using genome-wide association study (GWAS) summary statistics. Since both groups received the neuropathological diagnosis of AD and familial cases were excluded, we tested how their risk scores for late-onset AD compared to a control group, consisting of 200 randomly picked WGS samples from a healthy, neuropathology-free aging cohort, called the “Wellderly” study 18 . Both the AD and AD + ASYN groups showed a significantly increased PRS for late-onset AD compared to healthy agers 19 , which was expected (Fig. 1 c). However, there was no difference between the AD and the co-pathology condition in this comparison, suggesting that GWAS for late-onset AD do not capture an increased genomic risk for the accumulation of ⍺-Syn. Aggregation of ⍺-Syn into Lewy Bodies or Lewy Neurites, commonly referred to as Lewy Body Pathology (LBP), is not only the hallmark of PD but also characterizes the main neuropathological difference between the AD and the AD + ASYN cohort. An important differential diagnosis for AD + ASYN that can only be distinguished upon autopsy is Dementia with Lewy Bodies (DLB), another neurodegenerative disorder that shares the neuropathological hallmarks of AD and PD 20 . In DLB, ⍺-Syn aggregates are usually more prominent compared to the often-concomitant tau and/or β-Amyloid pathology. To assess polygenic risk scores for DLB, we used the largest and most recent WGS-based study 21 . While we found a much lower PRS for individuals from the Wellderly Study, the AD and AD + ASYN groups did not differ in DLB risk, suggesting that AD + ASYN is genetically not more similar to DLB than AD (Supp. Figure 1 ). We then tested our WGS data for associations with PD, and found a statistically higher PRS for Parkinson’s disease 22 in the AD + ASYN group, hinting at a role for PD-related risk factors in the manifestation of ⍺-Syn co-pathology (Fig. 1 d). The summary statistics for this PD study included 103 variants, therefore, we wondered which set of variants this significant difference was driven by. Linear regression of the PD PRS percentile on all risk and protective variants revealed a significant underrepresentation of four protective and an overrepresentation of two risk variants in the AD + ASYN group (p < 0.05, Fig. 1 e, Sup. Table X). Interestingly, all four protective variants were located on chromosome 17q21.31. The 17q21.31 locus is a well-known GWAS locus for PD and primary tauopathies, and among others contains the tau-encoding gene MAPT . Population-wide genomic data suggest the existence of two main haplotypes within this locus, termed H1 and H2. H1 is more prevalent, with approximately 75–80% of the population carrying it, and is characterized by an approximately mega-base long inversion. H1 homozygosity is associated with increased PD risk, while the rarer H2 haplotype confers protection 23 . We thus tested whether the significantly elevated PD risk score in the AD + ASYN group was associated with an overrepresentation of the H1 haplotype, and indeed found a significant relationship (chi-square test, p = 0.015, Fig. 1 f, Supp. Table 1). Conversely, when we checked the 2 significantly overrepresented risk alleles, both mapped to chromosome 1q22, a locus that has been suggested to mark carriers with non-synonymous GBA1 mutations 24 . GBA1 , also known as Glucocerebrosidase, is a lysosomal gene whose reduced activity has been consistently implicated in the development of PD 25 . While 12 patients (9%) from our WGS cohort carried coding GBA1 mutations, there was no clear enrichment for one of the two groups: 6 donors were heterozygote for the E365K mutation (4 AD, 2 AD + ASYN) and 3 carried a heterozygous T408M mutation (2 AD, 1 AD + ASYN). Two patients from the AD + ASYN group had rare GBA1 mutations, (L483P, N409S), and one AD donor tested positive for GBA1 R434H. None of the GBA1 mutation carriers showed compound heterozygosity (Supp. Table 1). The most significant genome-wide risk factors for PD, rs356182 and rs356168, reside on chromosome 4q21, a locus that contains the gene encoding ⍺-Syn ( SNCA ) 22 , 26 . We queried our whole genome sequencing data to test whether the higher PRS for PD in the AD + ASYN group could be explained by an enrichment of homozygous risk alleles within this region and found a suggestive association for rs356182 (Fisher’s exact test, p = 0.077). This relationship became significant for rs356168 (p = 0.044), where 25% of cases in the AD + ASYN group were homozygous for the risk allele, in contrast to only 10% of AD cases (Fig. 1 g). Our dissection of genetic risk associated with the occurrence of ⍺-Syn co-pathology in AD revealed significantly altered polygenic risk scores for PD, and within that, enrichments for the MAPT H1 haplotype and variants located in the SNCA locus. The SNCA rs356168 risk variant was previously demonstrated to increase SNCA mRNA levels through the creation of new transcription factor binding sites 26 , thereby acting as expression quantitative trait locus. Interestingly, an increased expression of SNCA and its protein product ⍺-Syn was recently reported in iPSC neurons from patients with a homozygous MAPT H1 haplotype 27 , and similar increases of SNCA on the MAPT H1 background were found in post-mortem studies of AD, DLB and PD cases 28 , 29 . Extrapolation from these results and the cited literature suggests that ⍺-Syn co-pathology in AD could be genetically explained by a putative increase in SNCA gene transcription. Single nucleus RNA-sequencing reveals upregulated MAPT transcription in co-pathology patients Overexpression of SNCA represents a widely used animal and cell culture PD model, and additional SNCA copy numbers in humans are steadily associated with familial PD 30 , 31 . To test whether AD + ASYN cases showed an increase in SNCA transcription, we performed single nucleus RNA-sequencing (snRNA-seq) of the superior frontal gyrus (SFG) in a subset (n = 8) of AD and AD + ASYN cases that were matched in age and APOE genotype (Supp. Table 2). Unsupervised clustering and annotation using transformer models 32 (Supp. Figure 2 )revealed the typical neocortical cell type composition, with large clusters of excitatory or inhibitory neurons, and smaller clusters of micro- or macroglia as well as vascular cells with a characteristic marker gene configuration (Figs. 2 a + b). We then performed differential expression testing using pseudobulk aggregates per group and cluster. Multidimensional scaling revealed that the leading log fold-changes per sample and cluster were consistent within excitatory and inhibitory neurons, unlike glial cells, which showed more heterogeneous changes (Fig. 2 c). Neuronal clusters had the highest number of differentially expressed genes (DEGs), while for glia, there was only one upregulated gene in the AD + ASYN Oligo cluster (Fig. 2 d, Supp. Table 3). Even though many clusters, especially the excitatory ones, showed a slight increase in SNCA expression, this difference was never statistically significant (Fig. 2 e), suggesting that neocortical ⍺-Syn co-pathology is either not due to local overexpression of its gene product, or due to spatiotemporally variable SNCA expression, rendering differences invisible in post-mortem tissue. Support for the latter notion comes from a study that systematically analyzed the expression of SNCA in relation to post-mortem intervals, where an inverse correlation has been found 33 . The cluster with the highest numbers of DEGs was excitatory cluster 7 (Ex-7). Strikingly, we found an almost two-fold upregulation (log 2 fold-change: 0.89) of MAPT , the gene encoding tau, within this cluster (Fig. 2 f). In fact, MAPT transcripts were expressed at varyingly higher levels in all neuronal clusters, but significance was only reached for Ex-7. Molecular annotation of the DEGs from this cluster using Gene Ontology enrichments revealed significant overlaps with cytosolic translation and nonsense-mediated decay (Fig. 2 g), hinting at a recently described role of SNCA in controlling cap-dependent protein translation by increasing mRNA stability 34 . Given the above results, we wondered about the simultaneous expression of SNCA and MAPT within the same cell and calculated co-expression scores by summing up normalized read counts for both genes (Fig. 2 h). Linear models revealed a significantly higher co-expression score of SNCA and MAPT in 14 of the 22 clusters for the AD + ASYN group (p < 0.05), suggesting that their expression patterns are correlated under co-pathology conditions. ⍺-Syn, total and phosphorylated tau species are increased in AD + ASYN patients ⍺-Syn, total and phosphorylated tau species are increased in AD + ASYN patients To validate our findings on the protein level, we first tested SFG brain lysates from soluble and insoluble fractions for ⍺-Syn protein expression (Fig. 3 ). As expected, the expression of ⍺-Syn and ⍺-Syn phosphorylated at Serine residue (pS129 ⍺-Syn) was significantly increased in the insoluble protein fraction from AD + ASYN brains, with a trend for increased ⍺-Syn expression in the soluble fraction (Figs. 3 a + b). These results demonstrate a higher abundance of misfolded ⍺-Syn protein in AD + ASYN and are thus consistent with the histological evaluation. Since our analysis also yielded higher MAPT RNA levels in AD + ASYN brains, we tested brain lysates for the expression of its associated protein product tau, using antibodies against different (phospho-) epitopes. We did not find higher levels of AT8, recognizing hyperphosphorylated tau, or T22, supposedly specific for oligomeric tau, in AD + ASYN brains (Fig. 3 c, Supp. Figure 3 ). However, there was a significant increase in the expression of total tau (antibody HT7) in soluble and insoluble protein fractions. We also found tau phosphorylated at Serine residue 396 (pS396) to be strongly increased in the soluble protein fraction of AD + ASYN brains. Validation of findings in an external cohort We then sought out to validate our findings in a larger cohort of post-mortem brain samples with varying stages of AD-related tau pathology, the Mount Sinai Brain Bank (MSBB) study 35 . This dataset provides neocortical proteome and transcriptome data from hundreds of replicates along with genotyping data (Fig. 4 a). There was a strong, significant correlation in the protein expression of ⍺-Syn and different tau isoforms (Fig. 4 b). Likewise, we saw a positive relationship between MAPT and SNCA transcript counts in a subset of patients for whom neocortical RNA-seq data was available (R = 0.4, p = 1.7e-5, Fig. 4 c). Stratification by presence of rs356168, the SNCA allele previously found to be overrepresented in AD + ASYN brains of our whole-genome sequencing cohort, revealed higher SNCA expression for heterozygous and homozygous carriers of the risk allele (Fig. 2 d), mirroring the experimental results from Soldner et al 26 . While there was no information on LBP status in the MSBB cohort, these results still demonstrate that SNCA and MAPT as well their protein products are tightly linked with each other in AD. Tau-PET signal is increased in patients with a positive ⍺-Syn seeding aggregation assay We then investigated the effect of MAPT haplotype on intra vitam tau abundance, using a dataset from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) that consisted of 231 cases with data available for the following measures: CSF ⍺-Syn seeding aggregation assay (SAA) status and tau load measured by Flortaucipir PET averaged over the 200 regions of interest of an established cortical brain atlas 36 . Not only did we find an enhanced tau PET signal for SAA-positive patients in the superior frontal cortex (Fig. 4 e), but linear models adjusted for age and sex revealed a significant increase of tau signal for patients who also had a positive ⍺-Syn seeding status in 178/200 (89%) cortical parcels (Supp. Figure 4 ). While the ⍺-Syn SAA in this study can only serve as proxy for LBP, previous studies have found substantial agreement between SAA status and the presence of LBP specifically in (neo)cortical areas, with specificities and sensitivities exceeding 97% 37 . Taken together, these data add support to our WGS-based results finding SNCA and MAPT genetic variants associated with ⍺-Syn status, and they reproduce strong relationships between SNCA and MAPT gene and protein expression. In post-mortem brains, ⍺-Syn co-pathology in AD was related to enhanced SNCA and MAPT transcription, translation and phosphorylation, thus posing the intriguing question whether SNCA by itself is able to increase tau pathology. SNCA overexpression is sufficient to drive MAPT and tau accumulation To unequivocally define SNCA as a driver for MAPT expression, we overexpressed wildtype human SNCA in Lund Human Mesencephalic cells (LUHMES), a human dopaminergic cell line, by transduction with an adenovirus either carrying full-length human SNCA or GFP as control 38 (Fig. 5 a). Droplet digital PCR assays 7 days after transduction showed a significant increase in MAPT transcripts upon SNCA but not GFP transduction (Fig. 5 b). This difference was mirrored on the proteome level: SNCA overexpression led not only to a higher abundance of ⍺-Syn and pS129 ⍺-Syn, but also to an increased expression of pS396 tau (Fig. 5 c). While there was a trend towards increased total tau (HT7) levels, this was not statistically significant. These results indicate that MAPT is rapidly upregulated and phosphorylated under SNCA overexpression conditions. To exclude adenovirus-induced overexpression artefacts, we differentiated neurons from an induced pluripotent stem cell (iPSC) line either carrying four copies of the SNCA gene (AST, ⍺-Syn triplication) or an isogenic control line in which a normal SNCA copy number had been restored (CAS, corrected ⍺-Syn, Fig. 6 a) 39 . Both lines were homozygous for the MAPT H1 haplotype and the APOE e3 genotype, and heterozygous for the SNCA variants rs356168 and rs356182 (see Methods). Differentiation of iPSCs to neurons was done using an accelerated maturation protocol, under which neurons were reported to take on a mature-like phenotype after about 50 days in culture 40 . At that timepoint, we found significantly higher transcript counts for SNCA and MAPT (Fig. 6 b). Both 3-repeat and 4-repeat tau contributed to the increase of total MAPT , with approximately twice as many mRNA copies in AST compared to CAS. Immunofluorescent stainings and Western Blots against tau and ⍺-Syn revealed a similar picture: Both ⍺-Syn and tau were significantly upregulated in the AST compared to the CAS cell line (Figs. 6 c + e). Tau is known to be phosphorylated by the kinase GSK3-β 41 , which itself becomes phosphorylated at residue Y216 when active 42 ; therefore, we stained for and also quantified the levels of pGSK3-β (Figs. 6 d + e). As expected, we did not only find higher levels of pS396 tau – mirroring the LUHMES results – but also of pGSK3-β, suggesting that endogenous SNCA overexpression alone is able to drive MAPT transcription, tau translation and phosphorylation. To better mirror the cell type diversity of adult brains, we also raised cortical organoids from AST and CAS cell lines. Automated capillary Western blots of organoid lysates taken at different time points revealed a consistently higher expression of ⍺-Syn in the AST line (Supp. Figure 5 ). After 70 days in culture, tau expression was also significantly increased in AST compared to CAS; however, the difference was not as striking as in cultured neurons from the same cell lines, suggesting that MAPT/tau and SNCA/⍺-Syn expression patters are especially correlated in neurons compared to other CNS cell types. To compare our results on an epigenetic level, we ultimately performed ATAC-sequencing in 50-day-old AST and CAS iPSC neurons and single-nucleus ATAC-seq in the same AD vs. AD + ASYN brains that also received snRNA-seq. We related log 2 fold-changes between AST/CAS neurons and AD/AD + ASYN brains and found a significant positive relationship for excitatory neurons (r = 0.15, p < 0.0001, Supp. Figure 6 ), demonstrating that the accessible chromatin landscape under SNCA triplication conditions is more comparable to the post-mortem AD + ASYN brain than the AD brain without ⍺-Syn co-pathology. Collectively, these data demonstrate a strong relationship between SNCA and MAPT that starts at the epigenetic level and is conserved all the way down to translation and posttranslational modifications of its protein products, a phenomenon that is fully recapitulating the central dogma of biology and is at least partially driven by genetic risk factors associated with increased SNCA expression. Discussion The presence of ⍺-Syn co-pathology in AD, the classic form of which is exclusively characterized by tau and ß-Amyloid plaques, has puzzled the field for almost 40 years 43 . Previous large-scale studies have demonstrated earlier disease onset, faster cognitive decline and earlier death for subjects with ⍺-Syn co-pathology in AD 11 , 44 , 45 . Mouse studies have laid out a foundation for a putative mechanism: In the absence of tau, ⍺-Syn spreading was reduced, but not the other way around, suggesting that an increased amount of ⍺-Syn accelerates the disease phenotype 13 . This was even more enhanced in an AD mouse model that produces β-Amyloid plaques, demonstrating that the classical AD protein aggregation landscape is a fertile ground for the manifestation of feeding-forward co-pathologies 46 . While mouse experiments can add mechanistic insight to the interaction of ⍺-Syn, tau, and β-Amyloid, they cannot fully recapitulate endogenous risk factors with smaller effect sizes present in humans, since they usually rely on the injection of pre-formed fibrils into brains of mice with a fixed, i.e. inbred genetic background, thus encompassing a highly artificial and genetically static model. To our knowledge, our study is the first one to interrogate the pathophysiology of ⍺-Syn co-pathology in AD on all genomic levels from DNA over RNA to proteins and their posttranslational modifications. Our data bring previous findings to the smallest common denominator, suggesting that increased SNCA transcription leads to upregulation of its protein product ⍺-Syn, and that this upregulation is sufficient to drive accumulation of pathogenic tau, by upregulating its transcripts and protein products from the MAPT locus and activating kinases known to phosphorylate tau. In essence, the resulting feed-forward mechanism can be explained by the presence of certain genetic risk factors. Following this logic, a question that immediately comes to a neuropathologist’s mind is why an increased accumulation of tau had not been found earlier in AD with ⍺-Syn co-pathology, given that such cohorts with high numbers of replicates have been characterized intensely – at least on an immunohistochemical level – since the early 2000s 4 , 43 , 47 . Interestingly, our data did not reveal higher levels of tau using the antibody AT8, which recognizes hyperphosphorylated tau and is canonically used in neuropathology departments all over the world for Braak tau staging. However, in addition to increased total tau using the antibody HT7, we also found increased pS396 tau in AD + ASYN brains. This marker has been known to accumulate at synapses of AD, PD and DLB brains prior to the occurrence of neurofibrillary tangles and is therefore thought to represent an early pathology marker strongly associated with dementia progression 48 – 53 . How heightened pS396 tau levels do not automatically lead to elevated AT8 in AD + ASYN is unclear and deserves more research. We found that carriers of the PD-associated MAPT H1 haplotype on chromosome 17q21.31 were much more likely to be affected by ⍺-Syn co-pathology in AD. Not only has the chromosome 17q21.31 signal been repeatedly linked to PD in large-scale, autopsy-confirmed GWAS 22 , 56 since its discovery more than 20 years ago 54 , but recent publications have even demonstrated tau to pre-date ⍺-Syn pathology in PD 57 , thus posing the provocative but interesting question whether PD should be re-classified as a tauopathy 58 . Previous studies have also investigated the involvement of the 17q21.31 locus in AD, but results are conflicting: While some publications report enrichments for the H1 haplotype in AD 59 , 60 , others found no association or even an opposite relationship 61 , 62 . We believe that this discrepancy can be explained by different inclusion criteria. Even if autopsy-confirmed data are used, staging schemes could differ among brain banks, and the presence of LBP might prompt even seasoned neuropathologists to favor the diagnosis of DLB over AD presenting with ⍺-Syn co-pathology. To circumvent this problem in our study, every staging-relevant brain region was evaluated for AD and PD pathognomonic lesions, and a diagnosis of AD + ASYN was preferred over DLB when the concomitant AD pathology was overall more prominent than the Lewy pathology 63 . The lack of an increased DLB polygenic risk score for our AD + ASYN cohort argues for the validity of our approach. It additionally suggests that ⍺-Syn co-pathology in AD could be understood as a true mixed pathology on the AD/PD genetic risk spectrum, and that DLB might be a distinct disease entity in this regard 21 . In some cases, GWAS-nominated risk loci overlap with genes known to cause Mendelian inheritance. SNCA is such an example, as SNCA multiplications or non-synonymous mutations are known to result in early-onset, dominantly inherited PD, and risk variants located around or within the SNCA gene are enriched in late-onset PD with complex inheritance. In our AD + ASYN cases, we found an overrepresentation for the G allele in SNCA -overlapping variant rs356168. This variant was described to enhance SNCA transcription in CRISPR/Cas9-edited iPSCs, but an opposite effect, although weak, was found when post-mortem brain tissue was tested for SNCA expression 26 , 64 . While we did see a significant increase of rs356168-conditioned SNCA expression in the MSBB cohort, we could not observe an upregulation of SNCA transcript in our snRNA-seq data. However, SNCA levels are also known to be modulated by the post-mortem interval 33 . We believe that cell culture experiments are better suited for the investigation of such effects, because it is hypothesized that during neurodegeneration, continuous exposure to dysregulated gene expression programs antecedes the occurrence of symptoms by decades 65 . Therefore, models that recapitulate some form of development – like our iPSC assays – are needed to inform about the time course of gene expression. On the protein side, our post-mortem data demonstrated an upregulation of ⍺-Syn and tau in co-pathology brains, which was recapitulated by in vitro assays applying either virus-mediated or endogenous overexpression of ⍺-Syn. These cell culture model systems are typically used in PD research, but they cannot reproduce the accumulation of β-Amyloid, which is a shortcoming of this study. Future experiments should clarify the additional impact of β-Amyloid under these conditions. Nevertheless, we could validate our findings in two external cohorts with varying degrees of AD pathology, and we were also able to show that chromatin accessibility under increased SNCA gene dosage is more similar to AD + ASYN as compared to AD brains. In conclusion, our data demonstrate a role for ⍺-Syn co-pathology in driving tau accumulation and phosphorylation in AD, and because tau load is strongly correlated to cognitive decline, they offer an elegant mechanistic explanation for a finding already noted by clinicians and neuropathologists decades ago. Upcoming experiments will characterize the genomic networks kickstarted by SNCA transcription in more detail. This will not only bring us closer to a comprehensive understanding of the complex molecular cascades taking part during neurodegeneration, but might also have the potential to define pathways targeting early ⍺-Syn accumulation in AD. Online Methods Human cohort and neuropathological assessment All participants included in the study had given informed consent to donate their brain according to the Code of Conduct laid out by the BrainNet Europe 66 . At autopsy, brain hemispheres were treated differently: The left hemisphere was fixed in formalin for a duration of two weeks or longer, while the right hemisphere was snap-frozen immediately. From the former, paraffin-embedded specimen sampled across the whole cerebrum, brain stem, cerebellum, and spinal cord were used for diagnostic examination 63 . Tau staging was performed according to Braak&Braak 17 by staining appropriate areas with the monoclonal antibody AT8 (ThermoFisher, #MN1020). Alpha-Synuclein pathology was assessed as defined by Braak 16 and McKeith 15 using clone 42 (abcam, ab280377). All specimens were evaluated by at least two board-certified neuropathologists and only samples neuropathologically diagnosed with AD entered the study. Importantly, subjects with a neuropathological diagnosis of Lewy Body Disease (DLB/PDD), significant co-pathology besides ⍺-Syn co-pathology, or unclear cases were excluded from the study. AD + ASYN brains included samples with neocortical Lewy Body or Lewy Neurite pathology (Fig. 1 b). Sample information for the WGS cohort can be found in Supplemental Table 1. Whole genome sequencing, variant calling and polygenic risk scores DNA was isolated from 1 cm 3 large tissue cubes taken from fresh-frozen cerebellum using the QIAmp DNA Mini Kit (Qiagen, 51304). Library preparation was performed with the TruSeq PCR-free genomic DNA library prep kit (Illumina, FC-121-3003) according to the manufacturer’s instructions. Libraries underwent 2x150 bp paired-end sequencing on an Illumina NovaSeq machine until a minimum depth of 35X was reached. Alignment and variant calling were performed using a Snakemake pipeline incorporating the GATK best practices. Briefly, after FastQC and adapter trimming, alignment to the hs1/T2T genome assembly (chm13v2.0) was performed with BWA-MEM2. Variant calling, recalibration and joint genotyping were done using GATK version 4.0 67 . Ultimately, samples with familial AD or PD mutations (PSEN1/2, APP, SNCA, MAPT) were excluded from the study. Polygenic risk scores were calculated with PRSKB 68 by supplying GWAS summary statistics from relevant studies after lifting over the vcf files from hs1 to hg38 (AD, AD + ASYN) or hg19 to hg38 (Wellderly). Single-nucleus RNA and ATAC sequencing Fresh-frozen human cortical tissue was microdissected, homogenized in NP40 buffer and filtered through a 70 µm strainer. After incubation on ice and centrifugation, nuclear pellets were resuspended in PBS with 1% BSA and RNase inhibitor, and nuclei were stained with 7AAD before being sorted into BSA containing RNase inhibitor using a Sony SH800 cell sorter. GEMs were generated on a 10x Chromium controller with a targeted nuclei number of ~ 4000 per sample to minimize doublet generation. RNA and ATAC library construction was performed with the 10X Multiome Kit (10X Genomics, PN-1000285) according to the manufacturer’s instructions. Following verification of correct insert sizes using a BioAnalyzer with the DNA High Sensitivity Chip (Agilent, 5067 − 4626), molarities were determined by droplet digital PCR (see below), and libraries were pooled in an equimolar fashion. Sequencing took place on an Illumina NovaSeq using two S2 flow cells with 2x150 cycles (RNA) or 2x100 cycles (ATAC). Bioinformatic and statistical analysis Single nucleus RNA libraries were aligned to the hs1/T2T genome (chm13v2.0) using STARSolo 69 while accounting for each sample’s variants by supplying sample-specific vcf files to the --varVCFfile argument. After QC, which included removing nuclei with small coverage or a large fraction of mitochondrial reads, we retained ~ 27,000 nuclei for downstream analysis. Each sample was normalized separately with the SCTransform v2 algorithm provided by the Seurat R package to account for differing library sizes 70 . Normalized samples were merged into one Seurat object, on which PCA and unsupervised clustering were carried out using the SNN algorithm on the top 50 principal components. Optimal cluster numbers and clustering stability were assessed by ClustAssess 71 . Top-level cluster annotations were retrieved by referencing our data set with CELLxGENE Geneformer 32 , a transformer-model-based, single cell sequencing-derived human cell type compendium, yielding excitatory, inhibitory, glial and vascular clusters (Supp. Figure 2 ). These clusters were further refined for glial cells by referencing known cell type markers for OPCs, astrocytes, microglia and oligodendrocytes, respectively, whereas neuronal clusters were numbered in ascending order according to their size. One small cluster, consisting of ~ 100 cells and random cell type annotations, was removed from the subsequent analysis (S. Figure 2 , ‘NA’). For visualization purposes, we removed batch effects by integrating samples with Harmony 72 , followed by dimensional reduction with UMAP. Pseudobulk testing was performed by aggregating log-normalized gene counts by cluster and group, removing genes with low coverage, fitting robust negative binomial generalized linear models and conducting quasi-likelihood tests using the edgeR package 73 . Nominal P-values were corrected for multiple comparisons using the Benjamini-Hochberg procedure. We considered genes with an absolute log 2 -fold-change of > 0.5 and an FDR < 0.1 as statistically significant. Computational analyses were performed on an HPC running Arch Linux and the R statistical programming environment version 4.3.3. Data processing pipelines and plots throughout the manuscript made heavy use of the tidyverse and ggplot2 packages for R. Unless otherwise noted, significance levels are denoted by asterisks: * = p < 0.05; ** = p < 0.01; *** = p < 0.001; **** = p < 0.0001. ATAC sequencing and analysis For the comparison of open chromatin between AST/CAS and post-mortem AD/AD + ASYN brains, we performed ATAC sequencing on 50-day-old iPSC neurons differentiated from AST and CAS cell lines using the Active Motif ATAC-Seq Kit (53150). After library preparation according to the manufacturer’s instructions (using approx. 100,000 cells from three replicates each), libraries were sequenced on an Illumina NovaSeq X 1.5B flow cell, and aligned to the hg38 genome assembly. We then used a sliding window count approach (150bps at a time) to sum up deduplicated reads and call differentially accessible peaks through the csaw 74 software package implemented in R. Counts aligning to the ENCODE blacklist were removed. The snATAC-seq data was aligned to the hg38 assembly, split into sample- and cluster-specific bams based on their snRNA-seq counterpart (similar to the pseudobulk approach), and reads were counted therein for the peaks pre-defined in the AST vs. CAS analysis described above. We then used edgeR quasi-likelihood models to calculate log2 fold-changes between AST/CAS, and AD/AD + ASYN respectively, and compared the log2 fold-changes to each other, resulting in the scatterplots shown in Supplementary Fig. 5. External data analysis - MSBB The results published here are in part based on data obtained from the AD Knowledge Portal ( https://adknowledgeportal.org/ ). These data were generated from postmortem brain tissue collected through the Mount Sinai VA Medical Center Brain Bank and were provided by Dr. Eric Schadt from Mount Sinai School of Medicine, and proteome data were provided by Dr. Levey from Emory University. After receiving the appropriate permissions, MSBB data was downloaded from www.synapse.org . Normalized proteome data was available for n = 310 individuals and ~ 90,000 Uniprot IDs, the gene symbols of which were retrieved by querying Uniprot’s REST API. RNA-seq data was downloaded for a subset of these cases for which both RNA counts and genotyping information (as a vcf file) was available (n = 107), and cases were joined on their unique individual identifier. Genotype and transcriptome data came aligned to the hg19 genome assembly, and featureCounts from the Rsubread package was used for assigning counts to genes with default arguments. External data analysis - ADNI The study included 231 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, selected based on the availability of clinical, neuroimaging, and biomarker data. Individuals with neurological diseases other than Alzheimer’s Disease (AD) or severe psychiatric conditions were excluded. For all participants, cerebrospinal fluid (CSF) measurements of p-tau181 were available, in addition to tau- PET imaging data using 18F-labeled tracers (Flortaucipir). Ethical approval was obtained, and all participants provided informed consent. The α-synuclein seed amplification assay (αSyn SAA) was conducted in a clinical laboratory following CLIA guidelines, with samples analyzed in triplicate for quality control 75 . Neuroimaging data were processed using standardized protocols described previously 76 . MRI scans were bias-corrected, segmented, and spatially normalized using the CAT12 toolbox. PET images were harmonized, realigned, and smoothed to a common resolution to ensure consistency across different scanners. PET images were registered to T1 MRI and spatially normalized using the T1 MRI-derived spatial normalization parameters. Standardized uptake value ratios (SUVRs) for tau-PET were calculated for 200 brain regions of the Schaefer atlas using the inferior cerebellar grey reference region. Protein isolation and Western blotting For automated capillary Western blots, homogenized iPSC-derived cerebral organoids were lysed in 1x RIPA Lysis Buffer (Merck, #20–188) with protease inhibitors (Roche, CO-RO) and phosphatase inhibitors (Roche, PHOSS-RO), and the protein levels of the homogenates were quantified by bicinchoninic acid assays (Sigma-Aldrich). Protein samples were reduced in Fluorescent Master Mix with 200 mM dithiothreitol (ProteinSimple) and run on a Jess Automated Western Blot System (ProteinSimple) using the 12–230 kDa Separation Module and 25-Capillary Cartridges (ProteinSimple). Proteins in the capillaries were blocked using Antibody Diluent 2 (ProteinSimple) and incubated with corresponding primary antibodies (anti-⍺ Synuclein (14H2L1) (Invitrogen, 1:50), anti-Tau (HT7) (Invitrogen, 1:50) for 90 minutes at room temperature and then with secondary HRP-conjugated antibodies (anti-rabbit and anti-mouse (ProteinSimple)) for 30 minutes at room temperature. For chemiluminescence detection, proteins were incubated in Luminol-Peroxide Mix (ProteinSimple) and scanned by the Jess Automated Western Blot System (ProteinSimple). For regular Western blots from post-mortem brain tissue and iPSC-derived neurons, samples were homogenized in 1x RIPA lysis buffer supplemented with protease inhibitors and phosphatase inhibitors using a Mini Bead Mill Homogenizer (VWR). After 30 min incubation on ice, the lysates were centrifuged at 16,000g for 30 min at 4°C to obtain the soluble protein fraction. For post-mortem brain tissue, the remaining pellets were washed once with lysis buffer and re-homogenized in 1% sarkosyl-containing lysis buffer, rotated overnight at 4°C. The samples were again centrifuged at 16,000g for 30 min at 4°C and the supernatant was collected as insoluble protein fraction. The protein concentration was determined by the Pierce™ BCA Protein Assay (Thermo Scientific, #23225). 15µg of proteins for each sample were run on a 4–20% precast polyacrylamide gel (Bio-Rad, #4561094) and electrophoresis was run at 90V for 1h and then 120V for 1h. The proteins were transferred to 0.45µm PVDF membranes (Millipore, #IPVH00010) at 200mA for 2h. The membranes were post-fixed with 4% paraformaldehyde and 0.1% glutaraldehyde for 30 min, washed in TBS supplemented with 0.1% Tween-20 (Sigma-Aldrich, #93773, TBST) and then blocked with 5% BSA (Sigma-Aldrich, #A7030) in TBST for 1h at room temperature (RT). The membranes were probed with primary antibodies diluted in the blocking solution overnight at 4°C. The next day, the membranes were washed 3 times with TBST and incubated with secondary antibodies for 1h at RT. After washing 3 times, the blots were developed with Pierce™ ECL Western Blotting Substrate (Thermo Scientific, #32109) and imaged on the ChemiDoc MP Imaging System (Bio-Rad). For stripping, the blots were washed 3 times with TBST and then incubated in stripping buffer (ThermoFisher, #46430) for 15 minutes at RT. Thereafter, the blots were washed and re-probed as before. The following primary and secondary antibodies were used: HT7 anti-Tau (ThermoFisher, #MN1000), AT8 anti-phosphorylated Tau (ThermoFisher, #MN1020), T22 anti-Tau oligomer (Sigma-Aldrich, #ABN454), pS396 anti-phosphorylated tau (ThermoFisher, #44-752G), 14H2L1 anti-⍺ synuclein (ThermoFisher, #701085), PS129 anti-phosphorylated ⍺ synuclein (Abcam, #ab51253), pY216 anti-phosphorylated GSK-3β (BD Biosciences, #612313), anti-β actin (ThermoFisher, #AM4302), anti-mouse IgG HRP-conjugate (Sigma-Aldrich, #12–349), anti-rabbit IgG HRP-conjugate (Promega, #W4011). Quantification of band densities was analyzed by FIJI software. Each target protein was normalized to β actin. A two-tailed unpaired t-test was performed to analyze the z-scored data. RNA isolation and digital droplet PCR Single-nucleus RNA-seq and ATAC-seq libraries were quantified using the ddPCR Library Quantification Kit for Illumina TruSeq (Bio-Rad, #186–3040) according to the manufacturer’s instructions. For gene expression assays, total RNA was isolated with the RNeasy Mini Kit (Qiagen, #74104) and quantified by fluorometry using the Qubit dsDNA HS assay (ThermoFisher, Q33230) before 1 ng of RNA were retrotranscribed with the QuantiTect Reverse Transcription Kit (Qiagen, #205311). After droplet generation with 1 µL of RT reaction, 10 µL of 2X ddPCR EvaGreen Supermix (Bio-Rad, #1864033), 1 µL of each 10 µM forward and reverse primer and 7 µL of H2O, PCR was performed with a Tm of 60C on a Bio-Rad C1000 Touch Thermal Cycler. Ultimately, droplets were read on a QX200 droplet reader (Bio-Rad). Primer sequences are given in Supp. Table 4. LUHMES cell culture experiments LUHMES cells were seeded into appropriate culture vessels pre-coated with 1% of PLO 100x (10 mg/ml) (Sigma-Aldrich, P3655) and 99% of DPBS without calcium and magnesium (Thermo-Fisher, 14190144). Cell culture media for LUHMES was composed of DMEM/F12 (Thermo-Fisher, 11330032), 1% N2 supplement 100x (Thermo-Fisher, 17502001) and bFGF (25 µg/ml) (Thermo-Fisher, 11330032). For differentiation, the PLO solution was removed from the culture vessel, washed 3 times with DPBS, and a solution of 0,5% Fibronectin (5 µg/ml) (Sigma-Aldrich, F0895) in UltraPure DNase/RNase-Free Distilled Water (Invitrogen, 10977023). 100 ml of the medium used for differentiation into post-mitotic neuronal cells were composed of 98 ml of DMEM/F12, 1 ml of N2 supplement 100x, 1 ml of dibutryl cAMP (49 mg/ml) (Sigma-Aldrich, D0627), 40 µl of glial cell derived neurotrophic factor (GNDF) (5 ng/µl) (R&D System, 212-GD-010) and 100 µl of Tetracycline (1 mg/ml) (Sigma-Aldrich, T7660). To split 70–80% confluent cells, they were washed once with DPBS and afterwards incubated for 5 minutes at 37°C with Trypsin-EDTA 0,05%. Trypsinization was blocked by adding an equivalent volume of a solution made with 10% FCS or FBS and 90% DMEM-F12. Trypan-Blue-stained cells were counted using a Neubauer counting chamber. For differentiation with a density of 1 million cells per well of a 6-well-plate, cells were left growing for 3 days in a T75 flask in order to arrive at confluence. 100 µl of a solution composed of differentiation medium and an adenovirus expressing either human wild-type SNCA or eGFP under the control of a CMV promoter was added to each well at a multiplicity of infection of 1.5 at day 2 after initiation of the differentiation process. After 24 hours, the cells were washed once with DPBS and medium was replaced with 2 ml of differentiation medium per well. iPSC culture and cerebral organoids Induced pluripotent stem cell (iPSC) lines were a gift from Tilo Kunath, University of Edinburgh. The first iPS cell line used in this study was derived from fibroblasts of an Iowan family with early-onset PD harbouring a SNCA triplication 31 and is herein referred as AST (α-Synuclein triplication iPS cell line). The second line used is an isogenic, CRISPR-Cas9 corrected iPSC line with a normal SNCA copy number, that has been generated from the AST cell line and is herein referred to as CAS 77 (corrected α-Syn triplication iPS cell line). Both the AST and CAS iPSC lines and subsequently differentiated cells were maintained in an incubator at 37°C with 5% CO 2 throughout the experiments. Cell culture vessels for iPSC culture were coated with Matrigel (Corning) diluted 1:100 in DMEM/F12 (Thermo Fischer) The Matrigel-DMEM/F12 solution was applied to the culture vessels covering the surface and the plates were incubated for 1h at 37°C. Before thawing and plating the cells, the culture vessels were washed three times with DPBS -/- (Thermo Fisher). mTesR + medium (STEMCELL Technologies) with 10 µM Rock-Inhibitor (Merck) was added in each well and incubated at 37°C. Frozen iPSCs were thawed in a 37°C water bath until the ice block detached from the tube. The cells were decanted into a 15 ml centrifuge tube with 10 ml pre-warmed DMEM/F12 and the empty cryovial was washed with 1 ml DMEM/F12. The 15 ml tube was gently tilted to mix the cells and subsequently pelleted at 300 x g for 5 minutes at RT. The supernatant was removed and the pellet was carefully resuspended in 0.5 ml mTesR + medium per well. The cell suspension was applied onto the plate, carefully moved with quick side movements to evenly distribute the cells and placed in the incubator. After 24 hours, the medium was changed to remove cellular debris and Rock-Inhibitor. Until expansion of the cells, the medium was changed every second day until the cells reached confluency for passaging. Cells were passaged on prepared multi-well plates coated with Matrigel diluted 1:100 in DMEM/F12 for 1 h at 37°C. For routine cell passaging, iPSCs being 70–80% confluent were passaged as colonies using ReLeSR (STEMCELL Technologies). The consumed medium was aspirated, replaced with 1 ml ReLeSR reagent and incubated for 1 minute at room temperature. ReLeSR was removed and the plate was placed in the incubator for 5 minutes. Cell colonies were detached by firmly tapping the side of the well plate and collected in 2 ml DMEM/F12 medium, centrifuged for 5 minutes at 300 x g at RT, resuspended in the desired mTesR + volume and evenly distributed with quick side movements. Cells were routinely passaged in ratios between 1:3 and 1:6. When starting experiments with a pre-defined number of cells, iPS cells were harvested using Gentle Cell Dissociation Reagent (GCDR) (STEMCELL Technologies) to obtain single cells. The consumed medium was aspirated and replaced with 1 ml GCDR and incubated for 5–8 minutes at RT. After incubation, 1 ml of DMEM/F12 was added to the wells and the cells were scratched off using a cell scraper. The cells were collected and counted using a Neubauer counting chamber system, centrifuged for 5 minutes at 300 x g and eventually plated at the desired density. Being re-plated as single cells, Rock-Inhibitor at 10 µM final concentration was added to the culture medium for 24 hours. Cerebral organoids (CO) were cultured following the Lancaster Protocol 78 using the Cerebral Organoid Kit and Cerebral Organoid Maturation Kit (STEMCELL Technologies) for subsequent maturation of the organoids. On day 0, CO generation was started with embryoid body (EB) formation. Therefore, one 70–80% confluent well of a 6-well plate of iPSC cells was washed with PBS and harvested with Gentle Cell Dissociation Reagent (STEMCELL Technologies). Cells were resuspended in EB seeding medium and 100 µl of cell suspension were plated into each well of a 96-well round-bottom ultra-low attachment plate (Corning) with a concentration of 90.000 cells/well. On day 2 and 4, 100 µl EB formation medium was added per well. On day 5, small formed EBs were transferred with a wide-bore pipette tip onto an ultra-low attachment 24-well plate (Corning) with 500 µl of fresh induction medium. At day 7, the EBs were collected with a wide-bore pipette tip and placed on an embedding sheet (STEMCELL Technologies). Excess medium was removed and a 15 µl Matrigel (Corning) droplet was added to the EB, which was subsequently positioned in the center of the drop. After 30 minutes incubation at 37°C for Matrigel polymerization, the Matrigel-embedded EBs were washed off the embedding sheet with expansion medium into an ultra-low attachment 6-well plate (Corning) and incubated for 3 days. At day 10, the consumed medium was replaced with fresh maturation medium and the well plate was transferred to an orbital shaker at 75 rpm at 37°C. Media changes were performed routinely every 2–3 days. Organoids ready for harvesting were taken from the plate using a 1000 µl wide bore pipette tip. PCR Mycoplasma tests (Promokine) were performed routinely to exclude cell culture contamination. Generation of iPSC-derived Neurons Neural progenitor cells (NPCs) were induced using an optimized protocol without the formation of EBs. IPSCs were dissociated and plated onto a Matrigel-coated plate in mTesR + medium supplemented with 10 µM Rock-Inhibitor. After 24 hours, with a confluency of 15–25%, the medium was completely replaced with PSC Neural Induction Medium (NIM) consisting of 98% Neurobasal Medium and 2% Neural Induction Supplement (ThermoFisher, #A1647801). From then on, the NIM medium was completely refreshed every 2 days. After 7 days of induction, NPCs were passaged with Accutase (Stemcell Technologies, #07920) and seeded onto a Matrigel-coated plate with complete Neural Expansion Medium (NEM) containing 49% Neurobasal Medium, 49% DMEM/F12 (ThermoFisher, #12634), 2% Neural Induction Supplement and 5 µM Rock-Inhibitor. After overnight incubation, Rock-inhibitor was removed and NPCs were fed every other day by half-medium changes of NEM. After 4–6 days, NPCs reached confluency and were ready for either cryopreservation or further differentiation. Before neuronal differentiation, NPCs were dissociated and plated onto plates coated with 50ug/ml PolyD-Lysine (PDL, ThermoFisher, #A3890401) and 2ug/ml laminin (Corning, #354232) in N2/B27 medium (1:1 ratio of DMEM/F12 to Neurobasal medium with 1× N2 and B27 minus vitamin A, ThermoFisher, #17502001, #12587001) in the presence of 5 µM Rock-Inhibitor. The next day, the medium was refreshed without Rock-Inhibitor. After 48 hours of plating, 4 µM GSK343 (Sigma, #SML0766) was added to the N2/B27 medium for 8 days for promoting rapid differentiation 40 . Half of the medium was replaced every 1–2 days according to cell density. 8 days later, GSK343 was washed out and the treated NPCs were ready for neuronal generation. At this point (day 0), treated NPCs were detached and directly seeded onto PDL/laminin coated plates with 5 µM Rock-Inhibitor and Neuronal Differentiation Medium (NDM) containing 48% Neurobasal Medium, 48% DMEM/F12 with GlutaMax (ThermoFisher, #10565018), 1x N2 supplement, 1x B27 supplement minus Vitamin A, 1x Culture One supplement (ThermoFisher, #A33202-01), 20 ng/ml BDNF (Peprotech, #450-02), 10 ng/ml GDNF (Peprotech,#450 − 10), 2 µg/ml laminin, 200 µM Ascobic acid (Merck, #A8960), 1µM dcAMP (Merck, #D0627) and 1% Penicillin-Streptomycin (ThermoFisher, #15070-63). The next day, the medium was refreshed without Rock-inhibitor. To generate sychronized neurons, 10 µM DAPT (ThermoFisher, #J65864.MA) was added to NDM for 10 days. From day 2 on, NDM was refreshed by performing a half-medium change every 3–4 days until harvest or fixed. Immunofluorescence To stain LUHMES cells, a coated coverslip was placed into a well of 24-well plate and cells were added (0.2 x 10 6 for LUHMES and 0.5 x 10 6 for differentiated neuronal cells). The coverslip was moved to another plate and washed once with DPBS. Afterwards, it was incubated for 15 minutes with 4% paraformaldehyde (PFA) and washed 3 times for 10 minutes each with PBS. Incubation followed with 200 µl of a 1:200 primary antibody dilution (Anti βIII-Tubulin Rabbit) with 0.05% Tween 20 and 2% I-Block reagent (Sigma). The coverslip was incubated at 4°C overnight and then washed 3 times with PBS. 200 µl of a secondary antibody (Anti-Rabbit Alexa 488) and DAPI (both in 1 1:1000 dilution) were added and the coverslip was incubated for 2 hours at room temperature. After 3 washes in DPBS, each lasting 5 minutes, the coverslip was mounted on microscopy slides using mounting medium (Histo-Line laboratories, PMT030) and sealed with nail polish. Cortical organoids were fixed in 4% PFA, embedded in paraffin and cut to 10 µm thick sections. For deparaffinization, the slides were immersed in Xylene twice for 10 min, 100% Ethanol twice for 10 min, 95% Ethanol for 5 min, 70% Ethanol for 5 min, 50% Ethanol for 5 min, followed by a quick rinse with deionized H2O and incubation in PBS for 10 min. Antigen retrieval was performed by immersing the slides in 1x Sodium Citrate solution (Abcam, #ab64214) and placing them in a pressure cooker at high pressure for 20 min. The sections were cooled to RT and washed in PBS 3 times for 5 min. For permeabilization, the slides were then incubated with 0.2% Triton X-100 (Sigma-Aldrich, #T9284) in PBS for 10 min. After washing 3 times with PBS, the slides were blocked with 0.3% Triton X-100 in PBS with 5% normal goat serum (Sigma-Aldrich, #G9023) for 2h at RT. Primary antibodies were diluted in blocking solution and incubated overnight at 4°C. The next day, slides were washed 3 times with PBS and then incubated with diluted secondary antibodies in blocking solution for 2h at RT. The following primary and secondary antibodies were used: HT7 anti-Tau, 14H2L1 anti-⍺ synuclein, anti-MAP2 (SYSY antibodies, #188004), Alexa 647 (ThermoFisher, #A32787), Alexa 555 (ThermoFisher, #A21429) and Alexa 488 (ThermoFisher, #A11073). The sections were washed 3 times with PBS and covered with ROTI® Mount FluorCare DAPI (ROTH, #HP20.1). IPSC-derived neurons were cultured on µ-Slide 8 Well plates (Ibidi, #80826) for staining. Cells were fixed in 4% PFA for 15 min at RT, washed three times with PBS, permeabilized and blocked in PBS solution consisting of 2% BSA, 5% donkey serum (Sigma, #D9663), 5% goat serum and 0.2% Triton-X-100 for 2h at RT. Primary antibodies diluted in the same blocking solution were added to cells overnight at 4°C. The used primary antibodies included: HT7 anti-Tau, pS396 anti-phosphorylated tau, 14H2L1 anti-⍺ synuclein, pY216 anti-phosphorylated GSK-3β and anti-β-III Tubulin (Novus Biologicals, #NB100-1612). Secondary antibodies conjugated with Alexa 647, Alexa 555 and Alexa 488 were incubated for 1h at RT. After washing, cells were mounted with ROTI® Mount FluorCare DAPI. All images were acquired using the confocal microscope Stellaris 5 (Leica). For each immunofluorescence reaction, secondary-only controls were verified to be absent of fluorescent signal before proceeding. Laser power and detector gain levels remained unchanged between imaging sessions across groups. Declarations Data and Code availability All code used in this study is available under https://github.com/fstrueb/MAPT_SNCA. Human sequencing data can be shared upon request after appropriate review by the LMU Institutional Review Board. Access to MSBB data can be gained after institutional review, see www.synapse.org. Acknowledgements Human induced pluripotent stem cells were a gift from Dr. Tilo Kunath (University of Edinburgh, UK). We would like to thank Dr. Christian Haass and the SyNergy consortium for their commitment and support in supplying whole genome sequencing data from the NBM inventory. We would like to acknowledge Vanessa Boll for DNA isolation, Dr. Norbert Buresch for dissection of fresh-frozen brain tissue, and Michael Schmidt for his help with immunohistochemistry and slide scanning. We would also like to thank Dr. Oliver Keppler for granting us access to the SimpleWestern™ apparatus. Whole genomes were sequenced by the Helmholtz Munich Core Facility Genomics (lead by Dr. Inti Alberto de la Rosa Velazquez) and generously sponsored by the Munich SyNergy consortium. We are thankful to Dr. Paul Feyen, Dr. Lars Paeger, Dr. Nils Briel, Antonia Neubauer and Dr. Patrick Harter for inspiring discussions. Ultimately, we are deeply indebted to the hundreds of patients who chose to donate their brains to research, including their families. Author contributions FLS and JH conceived the project. JH, VR, TA and SR evaluated brains of the WGS cohort for ⍺-synuclein pathology. JuWi and JH organized and oversaw WGS. OW supplied material from the Munich Brain Bank. FLS generated snRNA- and snATAC-seq data for suitable cases as identified by VR. FLS performed WGS variant calling and all bioinformatic and statistical analyses. Digital droplet PCR assays were run by FLS, TDV, JeaWi and XXS. JeaWi raised cortical organoids and performed Mycoplasma testing. TDV performed all SimpleWestern™ experiments and assisted in growing cortical organoids. FF, QLT and TK ran LUHMES experiments. XXS performed Western blots, immunofluorescent stainings of organoids and neurons, differentiation of AST and CAS cell lines to neurons and ATAC-seq. AD, MB and NF contributed ADNI and SAA data. FLS wrote the first draft of the manuscript and designed figures with significant input from JH, TDV and XXS. All authors read, improved and approved the final manuscript. Funding information FLS was supported by European Union Marie-Curie Actions (H2020-MSCA-IF-2017: NOJUNKDNA; 792832) at the start of experiments and is currently supported by the German Research Foundation (DFG, grant number STR 1537/3-1). FF was supported by the Erasmus+/KA1 Program (Convention n. 2020-1-IT02-KA103-077708 Agreement 2020/2021 n.17). This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy–ID 390857198). Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. 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Genomewide association study for susceptibility genes contributing to familial Parkinson disease. Hum Genet. 2009;124:593–605. Charlesworth G, et al. Tau acts as an independent genetic risk factor in pathologically proven PD. Neurobiol Aging. 2012;33:e8387–11. Chu Y, et al. Nigrostriatal tau pathology in parkinsonism and Parkinson’s disease. Brain J Neurol awad. 2023;388. 10.1093/brain/awad388 . Espay AJ, Lees AJ. Are we entering the ‘ Tau -lemaic’ era of Parkinson’s disease? Brain. 2024;147:330–2. Desikan RS, et al. Genetic overlap between Alzheimer’s disease and Parkinson’s disease at the MAPT locus. Mol Psychiatry. 2015;20:1588–95. Allen M, et al. Association of MAPT haplotypes with Alzheimer’s disease risk and MAPT brain gene expression levels. Alzheimers Res Ther. 2014;6:39. Moskvina V, et al. Analysis of genome-wide association studies of Alzheimer disease and of Parkinson disease to determine if these 2 diseases share a common genetic risk. JAMA Neurol. 2013;70:1268–76. 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Lun ATL, Smyth GK. csaw: a Bioconductor package for differential binding analysis of ChIP-seq data using sliding windows. Nucleic Acids Res. 2016;44:e45. Tosun D, et al. Association of CSF α-synuclein seed amplification assay positivity with disease progression and cognitive decline: A longitudinal Alzheimer’s Disease Neuroimaging Initiative study. Alzheimers Dement J Alzheimers Assoc. 2024;20:8444–60. Franzmeier N, et al. Alpha synuclein co-pathology is associated with accelerated amyloid-driven tau accumulation in Alzheimer’s disease. Mol Neurodegener. 2025;20:31. Chen Y, et al. Engineering synucleinopathy-resistant human dopaminergic neurons by CRISPR-mediated deletion of the SNCA gene. Eur J Neurosci. 2019;49:510–24. Lancaster MA, Knoblich JA. Generation of cerebral organoids from human pluripotent stem cells. Nat Protoc. 2014;9:2329–40. Additional Declarations No competing interests reported. Supplementary Files AllSuppFigures.pdf STable1.xlsx STable2.xlsx STable3.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6494882","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":458994444,"identity":"7b7c67b4-0729-42fd-95bf-19635006e78c","order_by":0,"name":"Felix L. 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Munich","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Arzberger","suffix":""},{"id":458994456,"identity":"acfe61cb-88d2-42b3-9ecd-9cb5fc5fa1ab","order_by":8,"name":"Sigrun Roeber","email":"","orcid":"","institution":"Ludwig Maximilian University of Munich","correspondingAuthor":false,"prefix":"","firstName":"Sigrun","middleName":"","lastName":"Roeber","suffix":""},{"id":458994460,"identity":"c72cfb35-e835-433e-9579-0a13e7cfc8a7","order_by":9,"name":"Thomas Koeglsperger","email":"","orcid":"","institution":"University Hospital, Ludwig Maximilian University of Munich","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Koeglsperger","suffix":""},{"id":458994462,"identity":"4ec8ce72-ba23-46d2-a305-b77b63f7fcc8","order_by":10,"name":"Otto Windl","email":"","orcid":"","institution":"Ludwig Maximilian University of Munich","correspondingAuthor":false,"prefix":"","firstName":"Otto","middleName":"","lastName":"Windl","suffix":""},{"id":458994464,"identity":"438aefb0-7ead-419f-952d-5f68bdbfc29e","order_by":11,"name":"Amir Dehsarvi","email":"","orcid":"","institution":"University Hospital, LMU Munich","correspondingAuthor":false,"prefix":"","firstName":"Amir","middleName":"","lastName":"Dehsarvi","suffix":""},{"id":458994465,"identity":"db515727-1554-4d57-b688-79591397f04f","order_by":12,"name":"Matthias Brendel","email":"","orcid":"","institution":"University Hospital, LMU Munich","correspondingAuthor":false,"prefix":"","firstName":"Matthias","middleName":"","lastName":"Brendel","suffix":""},{"id":458994466,"identity":"175aebc6-a322-470c-bc17-25e59c18b46e","order_by":13,"name":"Nicolai Franzmeier","email":"","orcid":"","institution":"University Hospital, LMU Munich","correspondingAuthor":false,"prefix":"","firstName":"Nicolai","middleName":"","lastName":"Franzmeier","suffix":""},{"id":458994467,"identity":"de08793e-ff5e-463f-a847-3ab566116d49","order_by":14,"name":"Juliane Winkelmann","email":"","orcid":"","institution":"Helmholtz Zentrum München, German Research Center for Environmental Health","correspondingAuthor":false,"prefix":"","firstName":"Juliane","middleName":"","lastName":"Winkelmann","suffix":""},{"id":458994469,"identity":"9689cff3-cfd0-4a28-b62c-ef0cfcdbab57","order_by":15,"name":"Jochen Herms","email":"","orcid":"","institution":"Ludwig Maximilian University of Munich","correspondingAuthor":false,"prefix":"","firstName":"Jochen","middleName":"","lastName":"Herms","suffix":""}],"badges":[],"createdAt":"2025-04-21 09:53:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6494882/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6494882/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83211429,"identity":"0009b656-e6e0-4b3d-8d61-35cbac605483","added_by":"auto","created_at":"2025-05-21 08:35:00","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":471421,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Examples of ⍺-Syn co-pathology in AD. FFPE specimen were stained against ⍺-synuclein (clone 42), and designated as AD+ASYN on presence of Lewy Bodies or Lewy neurites. Scale bar for ⍺-Syn = 20 µm, scale bar for AT8 and 4G8 = 50 µm. (b). Distribution of Braak tau stages and APOE genotypes. (c) LOAD polygenic risk scores (PRS) for AD and AD+ASYN. (d) PRS for PD, the WLDY identifier corresponds to the Wellderly cohort. (e) Over- and underrepresented variants in AD+ASYN. (f) \u003cem\u003eMAPT\u003c/em\u003e haplotype distributions. (g) Odds ratios for the two most significant PD risk factors (aligning to the \u003cem\u003eSNCA\u003c/em\u003e gene) in AD+ASYN.\u003c/p\u003e","description":"","filename":"AllFigures1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/9c8f883f5cdc1adfd12b2a75.jpg"},{"id":83214231,"identity":"d0facfee-97a1-4c27-9bc2-008e30f45f7a","added_by":"auto","created_at":"2025-05-21 08:51:00","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":697334,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Dimensional reduction projection of single nucleus RNA-seq profiles. (b) Heatmap showing the top 3 unique marker genes per cluster. (c) Distribution of leading log2 fold-changes after pseudobulk aggregation and multidimensional scaling. (d) Distribution of differentially expressed genes per cluster. (e) Heatmaps demonstrating cluster-wise \u003cem\u003eSNCA \u003c/em\u003eexpression. (f) Heatmaps demonstrating cluster-wise \u003cem\u003eMAPT\u003c/em\u003e expression\u003cem\u003e.\u003c/em\u003e (g) Gene ontology annotations for DEGs in cluster Ex-7. (h) Co-expression of \u003cem\u003eMAPT\u003c/em\u003eand \u003cem\u003eSNCA\u003c/em\u003e in AD+ASYN clusters.\u003c/p\u003e","description":"","filename":"AllFigures3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/0ee7deaed358fc246183a29f.jpg"},{"id":83215264,"identity":"38e6869d-09c4-4950-8cae-d00ca4e2cffb","added_by":"auto","created_at":"2025-05-21 08:59:00","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":506005,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Western Blots of AD and AD+ASYN cases using antibodies against ⍺-Syn (14H2L1) and ⍺-Syn phosphorylated at residue P129 (PS129) in the Sarkosyl-soluble protein fractions. (b) Like (a), but using the insoluble protein fraction. (c) Western blots against total tau (HT7), hyperphosphorylated tau (AT8), and tau phosphorylated at Serine 396 (pS396) in soluble and insoluble fractions, normalized to ß-Actin.\u003c/p\u003e","description":"","filename":"AllFigures5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/8e6ddab0248507bcea380c65.jpg"},{"id":83214230,"identity":"ede0b2ad-6f6b-4bd7-85e5-538f1db9d617","added_by":"auto","created_at":"2025-05-21 08:51:00","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":411639,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Distribution of tau stages in the MSBB dataset with number of samples on the x-axis. (b) Correlation of ⍺-Syn and tau protein in the MSBB proteomic dataset. Uniprot IDs for different tau isoforms are given on the bottom. (c) Correlation of \u003cem\u003eMAPT\u003c/em\u003e and \u003cem\u003eSNCA\u003c/em\u003e transcripts by RNA-seq. (d) Allele-specific expression for \u003cem\u003eSNCA\u003c/em\u003e stratified by presence of rs356168. PROT = protective allele associated with decreased transcription. HET = heterozygote carriers. RISK = homozygous for the risk allele associated with increased \u003cem\u003eSNCA\u003c/em\u003e transcription. (e) Tau PET signal adjusted for sex and age, partitioned by participants with a positive or negative ⍺-Syn CSF seeding status, and representative SUVR renderings.\u003c/p\u003e","description":"","filename":"AllFigures7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/0d9b2bf9db655c0f521221c1.jpg"},{"id":83211431,"identity":"41ce143c-3148-471e-a47f-a02ff85e6ca1","added_by":"auto","created_at":"2025-05-21 08:35:00","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":323213,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Immunofluorescence stainings for LUHMES progenitors and differentiated LUHMES neurons. DAPI stains nuclei and TUJ1 β-III-tubulin. (b) Absolute concentration of \u003cem\u003eSNCA\u003c/em\u003e and \u003cem\u003eMAPT\u003c/em\u003e transcripts after transduction with adenovirus carrying full-length \u003cem\u003eSNCA\u003c/em\u003e or eGFP as control measured by digital droplet PCR. (c) Western Blots and quantifications of LUHMES-transduced cells\u003c/p\u003e","description":"","filename":"AllFigures9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/84462fd004587c25589bd3a7.jpg"},{"id":83213026,"identity":"633d924c-d086-4cbc-a685-d9cbba5f4526","added_by":"auto","created_at":"2025-05-21 08:43:00","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":680587,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Description and timeline of iPSC experiments for the ⍺-synuclein triplication (AST) and CRISPR-corrected (CAS) lines. (b) Gene expression by ddPCR for \u003cem\u003eSNCA\u003c/em\u003e, \u003cem\u003eMAPT\u003c/em\u003e, 3-repeat (3R)-\u003cem\u003eMAPT\u003c/em\u003e and 4-repeat (4R) -\u003cem\u003eMAPT\u003c/em\u003e. (c) Immunofluorescent (IF) stainings and quantifications of induced neurons for tau and ⍺-Syn. (d) IF and quantifications against pGSK3-β (Y216) and pS396-tau. (e) Western Blots and quantifications against ⍺-Syn, tau, pS396-tau and pGSK3-β (Y216).\u003c/p\u003e","description":"","filename":"AllFigures11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/a3dd39a42d5d6a438b92de63.jpg"},{"id":84834202,"identity":"d9029664-6820-46b1-ac6f-3995cc1d2e88","added_by":"auto","created_at":"2025-06-17 20:46:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4178036,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/cf68225f-5694-4166-a90c-4483aa7b3873.pdf"},{"id":83211426,"identity":"6ab9aebb-196c-45a8-b39f-d3182e7aa35c","added_by":"auto","created_at":"2025-05-21 08:35:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1875648,"visible":true,"origin":"","legend":"","description":"","filename":"AllSuppFigures.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/a5bdb255e06e49021484227f.pdf"},{"id":83213020,"identity":"d6827f8b-b6df-422a-8d58-191f0a4eeb76","added_by":"auto","created_at":"2025-05-21 08:43:00","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23487,"visible":true,"origin":"","legend":"","description":"","filename":"STable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/43b971e0a78f7bfc50f64178.xlsx"},{"id":83211433,"identity":"a46af210-24f4-413b-a86d-22ecb39cfcc0","added_by":"auto","created_at":"2025-05-21 08:35:00","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10606,"visible":true,"origin":"","legend":"","description":"","filename":"STable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/83fa48e730c6b3d9c1f59ec2.xlsx"},{"id":83211457,"identity":"215c071d-8d3c-46b6-83cb-095ae7ae7034","added_by":"auto","created_at":"2025-05-21 08:35:01","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":15114361,"visible":true,"origin":"","legend":"","description":"","filename":"STable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6494882/v1/98aa9e32cd3461ad64170506.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Alpha-Synuclein co-pathology in Alzheimer’s Disease drives tau accumulation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlzheimer\u0026rsquo;s Disease (AD) is the most common neurodegenerative disorder leading to dementia\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Neuropathologically, AD is characterized by insoluble deposits of β-Amyloid and tau protein in specific brain regions. Parkinson\u0026rsquo;s Disease (PD) is another frequent neurodegenerative disorder that initially presents with movement disorder, but PD can also lead to dementia\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Unlike AD, the pathognomonic substrates of PD are aggregates of the protein alpha-Synuclein (⍺-Syn). However, there is substantial cross-talk between AD and PD pathology, with tau or β-Amyloid deposits being sometimes observed in PD, and ⍺-Syn pathology being present in up to 50% of AD cases\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. While a diagnosis of AD can be made \u003cem\u003eintra vitam\u003c/em\u003e with the help of plasma, CSF and imaging biomarkers, autopsy of post-mortem brain tissue often yields additional co-pathologies and thus represents the gold standard in classifying neurodegenerative syndromes\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe strongest molecular correlate to cognitive impairment, a unifying late symptom across most neurodegenerative disorders, is brain tau load\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Interestingly, isolated tau pathology is rare\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, and the association with cognitive impairment is stronger when β-Amyloid plaques are also present, such as in AD. It has been known that AD cases presenting with ⍺-Syn co-pathology have a faster course of cognitive impairment and functional decline\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. This notion is corroborated by experiments demonstrating worse behavioral and cognitive outcomes in mouse and \u003cem\u003ein vitro\u003c/em\u003e models of tau/⍺-Syn co-pathology\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. However, a molecular explanation for this phenomenon in humans is still lacking.\u003c/p\u003e \u003cp\u003eIn this study, we re-evaluate neuropathologically diagnosed late-onset AD patients who had donated their brain tissue to the NeuroBioBank Munich for ⍺-Syn pathology as defined by McKeith\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and Braak\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In a cohort of 135 cases, we find that approximately 25% show neocortical ⍺-Syn pathology, representing the highest Braak stage 6. Using a hypothesis-free approach, we discover altered polygenic risk scores for AD patients with ⍺-Syn co-pathology. Following up on this lead, we demonstrate an intimate dialog between the genes encoding ⍺-Syn (\u003cem\u003eSNCA\u003c/em\u003e) and tau (\u003cem\u003eMAPT\u003c/em\u003e), and we uncover that \u003cem\u003eSNCA\u003c/em\u003e expression is sufficient to increase pathogenic tau. Our results illuminate the molecular basis for ⍺-Syn co-pathology in AD, and they offer mechanistic insight on the accelerated cognitive decline seen in this group of dementias.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAltered polygenic risk scores distinguish AD from AD\u0026thinsp;+\u0026thinsp;ASYN\u003c/h2\u003e \u003cp\u003eFrom the inventory of the NeuroBioBank Munich, we selected 135 cases that were neuropathologically diagnosed with AD (Supp. Table\u0026nbsp;1). Of these, 35 had neocortical ⍺-Syn pathology (hereafter as a group referred to as AD\u0026thinsp;+\u0026thinsp;ASYN), corresponding to the highest Braak stage 6, whereas 100 had no appreciable ⍺-Syn pathology (hereafter termed AD, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). There was no difference in APOE genotypes between the AD and the AD\u0026thinsp;+\u0026thinsp;ASYN groups (p\u0026thinsp;=\u0026thinsp;0.33), and they did not differ in the distribution of tau (Braak\u0026amp;Braak) stages\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e (p\u0026thinsp;=\u0026thinsp;0.15, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eTo explore the genetic contributions related to ⍺-Syn co-pathology, we performed whole genome sequencing (WGS) and calculated polygenic risk scores (PRS) for a variety of traits using genome-wide association study (GWAS) summary statistics. Since both groups received the neuropathological diagnosis of AD and familial cases were excluded, we tested how their risk scores for late-onset AD compared to a control group, consisting of 200 randomly picked WGS samples from a healthy, neuropathology-free aging cohort, called the \u0026ldquo;Wellderly\u0026rdquo; study\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Both the AD and AD\u0026thinsp;+\u0026thinsp;ASYN groups showed a significantly increased PRS for late-onset AD compared to healthy agers \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, which was expected (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). However, there was no difference between the AD and the co-pathology condition in this comparison, suggesting that GWAS for late-onset AD do not capture an increased genomic risk for the accumulation of ⍺-Syn.\u003c/p\u003e \u003cp\u003eAggregation of ⍺-Syn into Lewy Bodies or Lewy Neurites, commonly referred to as Lewy Body Pathology (LBP), is not only the hallmark of PD but also characterizes the main neuropathological difference between the AD and the AD\u0026thinsp;+\u0026thinsp;ASYN cohort. An important differential diagnosis for AD\u0026thinsp;+\u0026thinsp;ASYN that can only be distinguished upon autopsy is Dementia with Lewy Bodies (DLB), another neurodegenerative disorder that shares the neuropathological hallmarks of AD and PD\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. In DLB, ⍺-Syn aggregates are usually more prominent compared to the often-concomitant tau and/or β-Amyloid pathology. To assess polygenic risk scores for DLB, we used the largest and most recent WGS-based study\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. While we found a much lower PRS for individuals from the Wellderly Study, the AD and AD\u0026thinsp;+\u0026thinsp;ASYN groups did not differ in DLB risk, suggesting that AD\u0026thinsp;+\u0026thinsp;ASYN is genetically not more similar to DLB than AD (Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe then tested our WGS data for associations with PD, and found a statistically higher PRS for Parkinson\u0026rsquo;s disease\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e in the AD\u0026thinsp;+\u0026thinsp;ASYN group, hinting at a role for PD-related risk factors in the manifestation of ⍺-Syn co-pathology (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). The summary statistics for this PD study included 103 variants, therefore, we wondered which set of variants this significant difference was driven by. Linear regression of the PD PRS percentile on all risk and protective variants revealed a significant underrepresentation of four protective and an overrepresentation of two risk variants in the AD\u0026thinsp;+\u0026thinsp;ASYN group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003ee, Sup. Table X). Interestingly, all four protective variants were located on chromosome 17q21.31. The 17q21.31 locus is a well-known GWAS locus for PD and primary tauopathies, and among others contains the tau-encoding gene \u003cem\u003eMAPT\u003c/em\u003e. Population-wide genomic data suggest the existence of two main haplotypes within this locus, termed H1 and H2. H1 is more prevalent, with approximately 75\u0026ndash;80% of the population carrying it, and is characterized by an approximately mega-base long inversion. H1 homozygosity is associated with increased PD risk, while the rarer H2 haplotype confers protection\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. We thus tested whether the significantly elevated PD risk score in the AD\u0026thinsp;+\u0026thinsp;ASYN group was associated with an overrepresentation of the H1 haplotype, and indeed found a significant relationship (chi-square test, p\u0026thinsp;=\u0026thinsp;0.015, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003ef, Supp. Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eConversely, when we checked the 2 significantly overrepresented risk alleles, both mapped to chromosome 1q22, a locus that has been suggested to mark carriers with non-synonymous \u003cem\u003eGBA1\u003c/em\u003e mutations\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eGBA1\u003c/em\u003e, also known as Glucocerebrosidase, is a lysosomal gene whose reduced activity has been consistently implicated in the development of PD\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. While 12 patients (9%) from our WGS cohort carried coding \u003cem\u003eGBA1\u003c/em\u003e mutations, there was no clear enrichment for one of the two groups: 6 donors were heterozygote for the E365K mutation (4 AD, 2 AD\u0026thinsp;+\u0026thinsp;ASYN) and 3 carried a heterozygous T408M mutation (2 AD, 1 AD\u0026thinsp;+\u0026thinsp;ASYN). Two patients from the AD\u0026thinsp;+\u0026thinsp;ASYN group had rare \u003cem\u003eGBA1\u003c/em\u003e mutations, (L483P, N409S), and one AD donor tested positive for \u003cem\u003eGBA1\u003c/em\u003e R434H. None of the \u003cem\u003eGBA1\u003c/em\u003e mutation carriers showed compound heterozygosity (Supp. Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eThe most significant genome-wide risk factors for PD, rs356182 and rs356168, reside on chromosome 4q21, a locus that contains the gene encoding ⍺-Syn (\u003cem\u003eSNCA\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. We queried our whole genome sequencing data to test whether the higher PRS for PD in the AD\u0026thinsp;+\u0026thinsp;ASYN group could be explained by an enrichment of homozygous risk alleles within this region and found a suggestive association for rs356182 (Fisher\u0026rsquo;s exact test, p\u0026thinsp;=\u0026thinsp;0.077). This relationship became significant for rs356168 (p\u0026thinsp;=\u0026thinsp;0.044), where 25% of cases in the AD\u0026thinsp;+\u0026thinsp;ASYN group were homozygous for the risk allele, in contrast to only 10% of AD cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eg).\u003c/p\u003e \u003cp\u003eOur dissection of genetic risk associated with the occurrence of ⍺-Syn co-pathology in AD revealed significantly altered polygenic risk scores for PD, and within that, enrichments for the \u003cem\u003eMAPT\u003c/em\u003e H1 haplotype and variants located in the \u003cem\u003eSNCA\u003c/em\u003e locus. The \u003cem\u003eSNCA\u003c/em\u003e rs356168 risk variant was previously demonstrated to increase \u003cem\u003eSNCA\u003c/em\u003e mRNA levels through the creation of new transcription factor binding sites\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, thereby acting as expression quantitative trait locus. Interestingly, an increased expression of \u003cem\u003eSNCA\u003c/em\u003e and its protein product ⍺-Syn was recently reported in iPSC neurons from patients with a homozygous \u003cem\u003eMAPT\u003c/em\u003e H1 haplotype\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, and similar increases of \u003cem\u003eSNCA\u003c/em\u003e on the \u003cem\u003eMAPT\u003c/em\u003e H1 background were found in post-mortem studies of AD, DLB and PD cases\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Extrapolation from these results and the cited literature suggests that ⍺-Syn co-pathology in AD could be genetically explained by a putative increase in \u003cem\u003eSNCA\u003c/em\u003e gene transcription.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSingle nucleus RNA-sequencing reveals upregulated\u003c/b\u003e \u003cb\u003eMAPT\u003c/b\u003e \u003cb\u003etranscription in co-pathology patients\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOverexpression of \u003cem\u003eSNCA\u003c/em\u003e represents a widely used animal and cell culture PD model, and additional \u003cem\u003eSNCA\u003c/em\u003e copy numbers in humans are steadily associated with familial PD\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. To test whether AD\u0026thinsp;+\u0026thinsp;ASYN cases showed an increase in \u003cem\u003eSNCA\u003c/em\u003e transcription, we performed single nucleus RNA-sequencing (snRNA-seq) of the superior frontal gyrus (SFG) in a subset (n\u0026thinsp;=\u0026thinsp;8) of AD and AD\u0026thinsp;+\u0026thinsp;ASYN cases that were matched in age and \u003cem\u003eAPOE\u003c/em\u003e genotype (Supp. Table\u0026nbsp;2). Unsupervised clustering and annotation using transformer models\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e (Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e)revealed the typical neocortical cell type composition, with large clusters of excitatory or inhibitory neurons, and smaller clusters of micro- or macroglia as well as vascular cells with a characteristic marker gene configuration (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003ea\u0026thinsp;+\u0026thinsp;b).\u003c/p\u003e \u003cp\u003eWe then performed differential expression testing using pseudobulk aggregates per group and cluster. Multidimensional scaling revealed that the leading log fold-changes per sample and cluster were consistent within excitatory and inhibitory neurons, unlike glial cells, which showed more heterogeneous changes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Neuronal clusters had the highest number of differentially expressed genes (DEGs), while for glia, there was only one upregulated gene in the AD\u0026thinsp;+\u0026thinsp;ASYN Oligo cluster (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003ed, Supp. Table\u0026nbsp;3). Even though many clusters, especially the excitatory ones, showed a slight increase in \u003cem\u003eSNCA\u003c/em\u003e expression, this difference was never statistically significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003ee), suggesting that neocortical ⍺-Syn co-pathology is either not due to local overexpression of its gene product, or due to spatiotemporally variable \u003cem\u003eSNCA\u003c/em\u003e expression, rendering differences invisible in post-mortem tissue. Support for the latter notion comes from a study that systematically analyzed the expression of \u003cem\u003eSNCA\u003c/em\u003e in relation to post-mortem intervals, where an inverse correlation has been found\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe cluster with the highest numbers of DEGs was excitatory cluster 7 (Ex-7). Strikingly, we found an almost two-fold upregulation (log\u003csub\u003e2\u003c/sub\u003e fold-change: 0.89) of \u003cem\u003eMAPT\u003c/em\u003e, the gene encoding tau, within this cluster (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003ef). In fact, \u003cem\u003eMAPT\u003c/em\u003e transcripts were expressed at varyingly higher levels in all neuronal clusters, but significance was only reached for Ex-7. Molecular annotation of the DEGs from this cluster using Gene Ontology enrichments revealed significant overlaps with cytosolic translation and nonsense-mediated decay (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eg), hinting at a recently described role of SNCA in controlling cap-dependent protein translation by increasing mRNA stability\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGiven the above results, we wondered about the simultaneous expression of \u003cem\u003eSNCA\u003c/em\u003e and \u003cem\u003eMAPT\u003c/em\u003e within the same cell and calculated co-expression scores by summing up normalized read counts for both genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eh). Linear models revealed a significantly higher co-expression score of \u003cem\u003eSNCA\u003c/em\u003e and \u003cem\u003eMAPT\u003c/em\u003e in 14 of the 22 clusters for the AD\u0026thinsp;+\u0026thinsp;ASYN group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting that their expression patterns are correlated under co-pathology conditions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e⍺-Syn, total and phosphorylated tau species are increased in AD + ASYN patients\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003e⍺-Syn, total and phosphorylated tau species are increased in AD\u0026thinsp;+\u0026thinsp;ASYN patients\u003c/div\u003e \u003cp\u003eTo validate our findings on the protein level, we first tested SFG brain lysates from soluble and insoluble fractions for ⍺-Syn protein expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). As expected, the expression of ⍺-Syn and ⍺-Syn phosphorylated at Serine residue (pS129 ⍺-Syn) was significantly increased in the insoluble protein fraction from AD\u0026thinsp;+\u0026thinsp;ASYN brains, with a trend for increased ⍺-Syn expression in the soluble fraction (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ea\u0026thinsp;+\u0026thinsp;b). These results demonstrate a higher abundance of misfolded ⍺-Syn protein in AD\u0026thinsp;+\u0026thinsp;ASYN and are thus consistent with the histological evaluation.\u003c/p\u003e \u003cp\u003eSince our analysis also yielded higher \u003cem\u003eMAPT\u003c/em\u003e RNA levels in AD\u0026thinsp;+\u0026thinsp;ASYN brains, we tested brain lysates for the expression of its associated protein product tau, using antibodies against different (phospho-) epitopes. We did not find higher levels of AT8, recognizing hyperphosphorylated tau, or T22, supposedly specific for oligomeric tau, in AD\u0026thinsp;+\u0026thinsp;ASYN brains (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, there was a significant increase in the expression of total tau (antibody HT7) in soluble and insoluble protein fractions. We also found tau phosphorylated at Serine residue 396 (pS396) to be strongly increased in the soluble protein fraction of AD\u0026thinsp;+\u0026thinsp;ASYN brains.\u003c/p\u003e\n\u003ch3\u003eValidation of findings in an external cohort\u003c/h3\u003e\n\u003cp\u003eWe then sought out to validate our findings in a larger cohort of post-mortem brain samples with varying stages of AD-related tau pathology, the Mount Sinai Brain Bank (MSBB) study\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. This dataset provides neocortical proteome and transcriptome data from hundreds of replicates along with genotyping data (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). There was a strong, significant correlation in the protein expression of ⍺-Syn and different tau isoforms (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Likewise, we saw a positive relationship between \u003cem\u003eMAPT\u003c/em\u003e and \u003cem\u003eSNCA\u003c/em\u003e transcript counts in a subset of patients for whom neocortical RNA-seq data was available (R\u0026thinsp;=\u0026thinsp;0.4, p\u0026thinsp;=\u0026thinsp;1.7e-5, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Stratification by presence of rs356168, the \u003cem\u003eSNCA\u003c/em\u003e allele previously found to be overrepresented in AD\u0026thinsp;+\u0026thinsp;ASYN brains of our whole-genome sequencing cohort, revealed higher \u003cem\u003eSNCA\u003c/em\u003e expression for heterozygous and homozygous carriers of the risk allele (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003ed), mirroring the experimental results from Soldner et al\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. While there was no information on LBP status in the MSBB cohort, these results still demonstrate that \u003cem\u003eSNCA\u003c/em\u003e and \u003cem\u003eMAPT\u003c/em\u003e as well their protein products are tightly linked with each other in AD.\u003c/p\u003e\n\u003ch3\u003eTau-PET signal is increased in patients with a positive ⍺-Syn seeding aggregation assay\u003c/h3\u003e\n\u003cp\u003eWe then investigated the effect of MAPT haplotype on \u003cem\u003eintra vitam\u003c/em\u003e tau abundance, using a dataset from the Alzheimer\u0026rsquo;s Disease Neuroimaging Initiative (ADNI) that consisted of 231 cases with data available for the following measures: CSF ⍺-Syn seeding aggregation assay (SAA) status and tau load measured by Flortaucipir PET averaged over the 200 regions of interest of an established cortical brain atlas\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Not only did we find an enhanced tau PET signal for SAA-positive patients in the superior frontal cortex (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003ee), but linear models adjusted for age and sex revealed a significant increase of tau signal for patients who also had a positive ⍺-Syn seeding status in 178/200 (89%) cortical parcels (Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). While the ⍺-Syn SAA in this study can only serve as proxy for LBP, previous studies have found substantial agreement between SAA status and the presence of LBP specifically in (neo)cortical areas, with specificities and sensitivities exceeding 97%\u003csup\u003e37\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTaken together, these data add support to our WGS-based results finding \u003cem\u003eSNCA\u003c/em\u003e and \u003cem\u003eMAPT\u003c/em\u003e genetic variants associated with ⍺-Syn status, and they reproduce strong relationships between \u003cem\u003eSNCA\u003c/em\u003e and \u003cem\u003eMAPT\u003c/em\u003e gene and protein expression. In post-mortem brains, ⍺-Syn co-pathology in AD was related to enhanced \u003cem\u003eSNCA\u003c/em\u003e and \u003cem\u003eMAPT\u003c/em\u003e transcription, translation and phosphorylation, thus posing the intriguing question whether \u003cem\u003eSNCA\u003c/em\u003e by itself is able to increase tau pathology.\u003c/p\u003e\n\u003ch3\u003eSNCA overexpression is sufficient to drive MAPT and tau accumulation\u003c/h3\u003e\n\u003cp\u003eTo unequivocally define \u003cem\u003eSNCA\u003c/em\u003e as a driver for \u003cem\u003eMAPT\u003c/em\u003e expression, we overexpressed wildtype human \u003cem\u003eSNCA\u003c/em\u003e in Lund Human Mesencephalic cells (LUHMES), a human dopaminergic cell line, by transduction with an adenovirus either carrying full-length human \u003cem\u003eSNCA\u003c/em\u003e or GFP as control\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Droplet digital PCR assays 7 days after transduction showed a significant increase in \u003cem\u003eMAPT\u003c/em\u003e transcripts upon \u003cem\u003eSNCA\u003c/em\u003e but not GFP transduction (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). This difference was mirrored on the proteome level: \u003cem\u003eSNCA\u003c/em\u003e overexpression led not only to a higher abundance of ⍺-Syn and pS129 ⍺-Syn, but also to an increased expression of pS396 tau (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). While there was a trend towards increased total tau (HT7) levels, this was not statistically significant. These results indicate that MAPT is rapidly upregulated and phosphorylated under \u003cem\u003eSNCA\u003c/em\u003e overexpression conditions.\u003c/p\u003e \u003cp\u003eTo exclude adenovirus-induced overexpression artefacts, we differentiated neurons from an induced pluripotent stem cell (iPSC) line either carrying four copies of the \u003cem\u003eSNCA\u003c/em\u003e gene (AST, ⍺-Syn triplication) or an isogenic control line in which a normal \u003cem\u003eSNCA\u003c/em\u003e copy number had been restored (CAS, corrected ⍺-Syn, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea)\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Both lines were homozygous for the \u003cem\u003eMAPT\u003c/em\u003e H1 haplotype and the \u003cem\u003eAPOE\u003c/em\u003e e3 genotype, and heterozygous for the \u003cem\u003eSNCA\u003c/em\u003e variants rs356168 and rs356182 (see Methods).\u003c/p\u003e \u003cp\u003eDifferentiation of iPSCs to neurons was done using an accelerated maturation protocol, under which neurons were reported to take on a mature-like phenotype after about 50 days in culture\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. At that timepoint, we found significantly higher transcript counts for \u003cem\u003eSNCA\u003c/em\u003e and \u003cem\u003eMAPT\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). Both 3-repeat and 4-repeat tau contributed to the increase of total \u003cem\u003eMAPT\u003c/em\u003e, with approximately twice as many mRNA copies in AST compared to CAS. Immunofluorescent stainings and Western Blots against tau and ⍺-Syn revealed a similar picture: Both ⍺-Syn and tau were significantly upregulated in the AST compared to the CAS cell line (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec\u0026thinsp;+\u0026thinsp;e). Tau is known to be phosphorylated by the kinase GSK3-β\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, which itself becomes phosphorylated at residue Y216 when active\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e; therefore, we stained for and also quantified the levels of pGSK3-β (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed\u0026thinsp;+\u0026thinsp;e). As expected, we did not only find higher levels of pS396 tau \u0026ndash; mirroring the LUHMES results \u0026ndash; but also of pGSK3-β, suggesting that endogenous \u003cem\u003eSNCA\u003c/em\u003e overexpression alone is able to drive \u003cem\u003eMAPT\u003c/em\u003e transcription, tau translation and phosphorylation.\u003c/p\u003e \u003cp\u003eTo better mirror the cell type diversity of adult brains, we also raised cortical organoids from AST and CAS cell lines. Automated capillary Western blots of organoid lysates taken at different time points revealed a consistently higher expression of ⍺-Syn in the AST line (Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). After 70 days in culture, tau expression was also significantly increased in AST compared to CAS; however, the difference was not as striking as in cultured neurons from the same cell lines, suggesting that MAPT/tau and SNCA/⍺-Syn expression patters are especially correlated in neurons compared to other CNS cell types.\u003c/p\u003e \u003cp\u003eTo compare our results on an epigenetic level, we ultimately performed ATAC-sequencing in 50-day-old AST and CAS iPSC neurons and single-nucleus ATAC-seq in the same AD vs. AD\u0026thinsp;+\u0026thinsp;ASYN brains that also received snRNA-seq.\u0026nbsp;We related log\u003csub\u003e2\u003c/sub\u003e fold-changes between AST/CAS neurons and AD/AD\u0026thinsp;+\u0026thinsp;ASYN brains and found a significant positive relationship for excitatory neurons (r\u0026thinsp;=\u0026thinsp;0.15, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), demonstrating that the accessible chromatin landscape under \u003cem\u003eSNCA\u003c/em\u003e triplication conditions is more comparable to the post-mortem AD\u0026thinsp;+\u0026thinsp;ASYN brain than the AD brain without ⍺-Syn co-pathology.\u003c/p\u003e \u003cp\u003eCollectively, these data demonstrate a strong relationship between SNCA and MAPT that starts at the epigenetic level and is conserved all the way down to translation and posttranslational modifications of its protein products, a phenomenon that is fully recapitulating the central dogma of biology and is at least partially driven by genetic risk factors associated with increased \u003cem\u003eSNCA\u003c/em\u003e expression.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe presence of ⍺-Syn co-pathology in AD, the classic form of which is exclusively characterized by tau and \u0026szlig;-Amyloid plaques, has puzzled the field for almost 40 years\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Previous large-scale studies have demonstrated earlier disease onset, faster cognitive decline and earlier death for subjects with ⍺-Syn co-pathology in AD\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Mouse studies have laid out a foundation for a putative mechanism: In the absence of tau, ⍺-Syn spreading was reduced, but not the other way around, suggesting that an increased amount of ⍺-Syn accelerates the disease phenotype\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. This was even more enhanced in an AD mouse model that produces β-Amyloid plaques, demonstrating that the classical AD protein aggregation landscape is a fertile ground for the manifestation of \u003cem\u003efeeding-forward\u003c/em\u003e co-pathologies\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile mouse experiments can add mechanistic insight to the interaction of ⍺-Syn, tau, and β-Amyloid, they cannot fully recapitulate endogenous risk factors with smaller effect sizes present in humans, since they usually rely on the injection of pre-formed fibrils into brains of mice with a fixed, i.e. inbred genetic background, thus encompassing a highly artificial and genetically static model. To our knowledge, our study is the first one to interrogate the pathophysiology of ⍺-Syn co-pathology in AD on all genomic levels from DNA over RNA to proteins and their posttranslational modifications. Our data bring previous findings to the smallest common denominator, suggesting that increased \u003cem\u003eSNCA\u003c/em\u003e transcription leads to upregulation of its protein product ⍺-Syn, and that this upregulation is sufficient to drive accumulation of pathogenic tau, by upregulating its transcripts and protein products from the \u003cem\u003eMAPT\u003c/em\u003e locus and activating kinases known to phosphorylate tau. In essence, the resulting feed-forward mechanism can be explained by the presence of certain genetic risk factors.\u003c/p\u003e \u003cp\u003eFollowing this logic, a question that immediately comes to a neuropathologist\u0026rsquo;s mind is why an increased accumulation of tau had not been found earlier in AD with ⍺-Syn co-pathology, given that such cohorts with high numbers of replicates have been characterized intensely \u0026ndash; at least on an immunohistochemical level \u0026ndash; since the early 2000s\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Interestingly, our data did not reveal higher levels of tau using the antibody AT8, which recognizes hyperphosphorylated tau and is canonically used in neuropathology departments all over the world for Braak tau staging. However, in addition to increased total tau using the antibody HT7, we also found increased pS396 tau in AD\u0026thinsp;+\u0026thinsp;ASYN brains. This marker has been known to accumulate at synapses of AD, PD and DLB brains prior to the occurrence of neurofibrillary tangles and is therefore thought to represent an early pathology marker strongly associated with dementia progression\u003csup\u003e\u003cspan additionalcitationids=\"CR49 CR50 CR51 CR52\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. How heightened pS396 tau levels do not automatically lead to elevated AT8 in AD\u0026thinsp;+\u0026thinsp;ASYN is unclear and deserves more research.\u003c/p\u003e \u003cp\u003eWe found that carriers of the PD-associated \u003cem\u003eMAPT\u003c/em\u003e H1 haplotype on chromosome 17q21.31 were much more likely to be affected by ⍺-Syn co-pathology in AD. Not only has the chromosome 17q21.31 signal been repeatedly linked to PD in large-scale, autopsy-confirmed GWAS\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e since its discovery more than 20 years ago\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, but recent publications have even demonstrated tau to pre-date ⍺-Syn pathology in PD\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, thus posing the provocative but interesting question whether PD should be re-classified as a tauopathy\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Previous studies have also investigated the involvement of the 17q21.31 locus in AD, but results are conflicting: While some publications report enrichments for the H1 haplotype in AD\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e, others found no association or even an opposite relationship\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e,\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. We believe that this discrepancy can be explained by different inclusion criteria. Even if autopsy-confirmed data are used, staging schemes could differ among brain banks, and the presence of LBP might prompt even seasoned neuropathologists to favor the diagnosis of DLB over AD presenting with ⍺-Syn co-pathology. To circumvent this problem in our study, every staging-relevant brain region was evaluated for AD and PD pathognomonic lesions, and a diagnosis of AD\u0026thinsp;+\u0026thinsp;ASYN was preferred over DLB when the concomitant AD pathology was overall more prominent than the Lewy pathology\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. The lack of an increased DLB polygenic risk score for our AD\u0026thinsp;+\u0026thinsp;ASYN cohort argues for the validity of our approach. It additionally suggests that ⍺-Syn co-pathology in AD could be understood as a true mixed pathology on the AD/PD genetic risk spectrum, and that DLB might be a distinct disease entity in this regard\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn some cases, GWAS-nominated risk loci overlap with genes known to cause Mendelian inheritance. \u003cem\u003eSNCA\u003c/em\u003e is such an example, as \u003cem\u003eSNCA\u003c/em\u003e multiplications or non-synonymous mutations are known to result in early-onset, dominantly inherited PD, and risk variants located around or within the \u003cem\u003eSNCA\u003c/em\u003e gene are enriched in late-onset PD with complex inheritance. In our AD\u0026thinsp;+\u0026thinsp;ASYN cases, we found an overrepresentation for the G allele in \u003cem\u003eSNCA\u003c/em\u003e-overlapping variant rs356168. This variant was described to enhance \u003cem\u003eSNCA\u003c/em\u003e transcription in CRISPR/Cas9-edited iPSCs, but an opposite effect, although weak, was found when post-mortem brain tissue was tested for \u003cem\u003eSNCA\u003c/em\u003e expression\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. While we did see a significant increase of rs356168-conditioned \u003cem\u003eSNCA\u003c/em\u003e expression in the MSBB cohort, we could not observe an upregulation of \u003cem\u003eSNCA\u003c/em\u003e transcript in our snRNA-seq data. However, \u003cem\u003eSNCA\u003c/em\u003e levels are also known to be modulated by the post-mortem interval\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. We believe that cell culture experiments are better suited for the investigation of such effects, because it is hypothesized that during neurodegeneration, continuous exposure to dysregulated gene expression programs antecedes the occurrence of symptoms by decades\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. Therefore, models that recapitulate some form of development \u0026ndash; like our iPSC assays \u0026ndash; are needed to inform about the time course of gene expression.\u003c/p\u003e \u003cp\u003eOn the protein side, our post-mortem data demonstrated an upregulation of ⍺-Syn and tau in co-pathology brains, which was recapitulated by in vitro assays applying either virus-mediated or endogenous overexpression of ⍺-Syn. These cell culture model systems are typically used in PD research, but they cannot reproduce the accumulation of β-Amyloid, which is a shortcoming of this study. Future experiments should clarify the additional impact of β-Amyloid under these conditions. Nevertheless, we could validate our findings in two external cohorts with varying degrees of AD pathology, and we were also able to show that chromatin accessibility under increased \u003cem\u003eSNCA\u003c/em\u003e gene dosage is more similar to AD\u0026thinsp;+\u0026thinsp;ASYN as compared to AD brains.\u003c/p\u003e \u003cp\u003eIn conclusion, our data demonstrate a role for ⍺-Syn co-pathology in driving tau accumulation and phosphorylation in AD, and because tau load is strongly correlated to cognitive decline, they offer an elegant mechanistic explanation for a finding already noted by clinicians and neuropathologists decades ago. Upcoming experiments will characterize the genomic networks kickstarted by \u003cem\u003eSNCA\u003c/em\u003e transcription in more detail. This will not only bring us closer to a comprehensive understanding of the complex molecular cascades taking part during neurodegeneration, but might also have the potential to define pathways targeting early ⍺-Syn accumulation in AD.\u003c/p\u003e"},{"header":"Online Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eHuman cohort and neuropathological assessment\u003c/h2\u003e \u003cp\u003eAll participants included in the study had given informed consent to donate their brain according to the Code of Conduct laid out by the BrainNet Europe\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. At autopsy, brain hemispheres were treated differently: The left hemisphere was fixed in formalin for a duration of two weeks or longer, while the right hemisphere was snap-frozen immediately. From the former, paraffin-embedded specimen sampled across the whole cerebrum, brain stem, cerebellum, and spinal cord were used for diagnostic examination\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. Tau staging was performed according to Braak\u0026amp;Braak\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e by staining appropriate areas with the monoclonal antibody AT8 (ThermoFisher, #MN1020). Alpha-Synuclein pathology was assessed as defined by Braak\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e and McKeith\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e using clone 42 (abcam, ab280377). All specimens were evaluated by at least two board-certified neuropathologists and only samples neuropathologically diagnosed with AD entered the study. Importantly, subjects with a neuropathological diagnosis of Lewy Body Disease (DLB/PDD), significant co-pathology besides ⍺-Syn co-pathology, or unclear cases were excluded from the study. AD\u0026thinsp;+\u0026thinsp;ASYN brains included samples with neocortical Lewy Body or Lewy Neurite pathology (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Sample information for the WGS cohort can be found in Supplemental Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWhole genome sequencing, variant calling and polygenic risk scores\u003c/h2\u003e \u003cp\u003eDNA was isolated from 1 cm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e large tissue cubes taken from fresh-frozen cerebellum using the QIAmp DNA Mini Kit (Qiagen, 51304). Library preparation was performed with the TruSeq PCR-free genomic DNA library prep kit (Illumina, FC-121-3003) according to the manufacturer\u0026rsquo;s instructions. Libraries underwent 2x150 bp paired-end sequencing on an Illumina NovaSeq machine until a minimum depth of 35X was reached. Alignment and variant calling were performed using a Snakemake pipeline incorporating the GATK best practices. Briefly, after FastQC and adapter trimming, alignment to the hs1/T2T genome assembly (chm13v2.0) was performed with BWA-MEM2. Variant calling, recalibration and joint genotyping were done using GATK version 4.0\u003csup\u003e67\u003c/sup\u003e. Ultimately, samples with familial AD or PD mutations (PSEN1/2, APP, SNCA, MAPT) were excluded from the study. Polygenic risk scores were calculated with PRSKB\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e by supplying GWAS summary statistics from relevant studies after lifting over the vcf files from hs1 to hg38 (AD, AD\u0026thinsp;+\u0026thinsp;ASYN) or hg19 to hg38 (Wellderly).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSingle-nucleus RNA and ATAC sequencing\u003c/h2\u003e \u003cp\u003eFresh-frozen human cortical tissue was microdissected, homogenized in NP40 buffer and filtered through a 70 \u0026micro;m strainer. After incubation on ice and centrifugation, nuclear pellets were resuspended in PBS with 1% BSA and RNase inhibitor, and nuclei were stained with 7AAD before being sorted into BSA containing RNase inhibitor using a Sony SH800 cell sorter. GEMs were generated on a 10x Chromium controller with a targeted nuclei number of ~\u0026thinsp;4000 per sample to minimize doublet generation. RNA and ATAC library construction was performed with the 10X Multiome Kit (10X Genomics, PN-1000285) according to the manufacturer\u0026rsquo;s instructions. Following verification of correct insert sizes using a BioAnalyzer with the DNA High Sensitivity Chip (Agilent, 5067\u0026thinsp;\u0026minus;\u0026thinsp;4626), molarities were determined by droplet digital PCR (see below), and libraries were pooled in an equimolar fashion. Sequencing took place on an Illumina NovaSeq using two S2 flow cells with 2x150 cycles (RNA) or 2x100 cycles (ATAC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatic and statistical analysis\u003c/h2\u003e \u003cp\u003eSingle nucleus RNA libraries were aligned to the hs1/T2T genome (chm13v2.0) using STARSolo\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e while accounting for each sample\u0026rsquo;s variants by supplying sample-specific vcf files to the --varVCFfile argument. After QC, which included removing nuclei with small coverage or a large fraction of mitochondrial reads, we retained\u0026thinsp;~\u0026thinsp;27,000 nuclei for downstream analysis. Each sample was normalized separately with the SCTransform v2 algorithm provided by the Seurat R package to account for differing library sizes\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. Normalized samples were merged into one Seurat object, on which PCA and unsupervised clustering were carried out using the SNN algorithm on the top 50 principal components. Optimal cluster numbers and clustering stability were assessed by ClustAssess\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. Top-level cluster annotations were retrieved by referencing our data set with CELLxGENE Geneformer\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, a transformer-model-based, single cell sequencing-derived human cell type compendium, yielding excitatory, inhibitory, glial and vascular clusters (Supp. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These clusters were further refined for glial cells by referencing known cell type markers for OPCs, astrocytes, microglia and oligodendrocytes, respectively, whereas neuronal clusters were numbered in ascending order according to their size. One small cluster, consisting of ~\u0026thinsp;100 cells and random cell type annotations, was removed from the subsequent analysis (S. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u0026lsquo;NA\u0026rsquo;). For visualization purposes, we removed batch effects by integrating samples with Harmony\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, followed by dimensional reduction with UMAP. Pseudobulk testing was performed by aggregating log-normalized gene counts by cluster and group, removing genes with low coverage, fitting robust negative binomial generalized linear models and conducting quasi-likelihood tests using the edgeR package\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. Nominal P-values were corrected for multiple comparisons using the Benjamini-Hochberg procedure. We considered genes with an absolute log\u003csub\u003e2\u003c/sub\u003e-fold-change of \u0026gt;\u0026thinsp;0.5 and an FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.1 as statistically significant.\u003c/p\u003e \u003cp\u003eComputational analyses were performed on an HPC running Arch Linux and the R statistical programming environment version 4.3.3. Data processing pipelines and plots throughout the manuscript made heavy use of the tidyverse and ggplot2 packages for R. Unless otherwise noted, significance levels are denoted by asterisks: * = p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ** = p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *** = p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; **** = p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eATAC sequencing and analysis\u003c/h2\u003e \u003cp\u003eFor the comparison of open chromatin between AST/CAS and post-mortem AD/AD\u0026thinsp;+\u0026thinsp;ASYN brains, we performed ATAC sequencing on 50-day-old iPSC neurons differentiated from AST and CAS cell lines using the Active Motif ATAC-Seq Kit (53150). After library preparation according to the manufacturer\u0026rsquo;s instructions (using approx. 100,000 cells from three replicates each), libraries were sequenced on an Illumina NovaSeq X 1.5B flow cell, and aligned to the hg38 genome assembly. We then used a sliding window count approach (150bps at a time) to sum up deduplicated reads and call differentially accessible peaks through the \u003cem\u003ecsaw\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e software package implemented in R. Counts aligning to the ENCODE blacklist were removed. The snATAC-seq data was aligned to the hg38 assembly, split into sample- and cluster-specific bams based on their snRNA-seq counterpart (similar to the pseudobulk approach), and reads were counted therein for the peaks pre-defined in the AST vs. CAS analysis described above. We then used edgeR quasi-likelihood models to calculate log2 fold-changes between AST/CAS, and AD/AD\u0026thinsp;+\u0026thinsp;ASYN respectively, and compared the log2 fold-changes to each other, resulting in the scatterplots shown in Supplementary Fig.\u0026nbsp;5.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eExternal data analysis - MSBB\u003c/h2\u003e \u003cp\u003eThe results published here are in part based on data obtained from the AD Knowledge Portal (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://adknowledgeportal.org/\u003c/span\u003e\u003cspan address=\"https://adknowledgeportal.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). These data were generated from postmortem brain tissue collected through the Mount Sinai VA Medical Center Brain Bank and were provided by Dr. Eric Schadt from Mount Sinai School of Medicine, and proteome data were provided by Dr. Levey from Emory University. After receiving the appropriate permissions, MSBB data was downloaded from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"https://adknowledgeportal.org/\" target=\"_blank\"\u003ewww.synapse.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.synapse.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Normalized proteome data was available for n\u0026thinsp;=\u0026thinsp;310 individuals and ~\u0026thinsp;90,000 Uniprot IDs, the gene symbols of which were retrieved by querying Uniprot\u0026rsquo;s REST API. RNA-seq data was downloaded for a subset of these cases for which both RNA counts and genotyping information (as a vcf file) was available (n\u0026thinsp;=\u0026thinsp;107), and cases were joined on their unique individual identifier. Genotype and transcriptome data came aligned to the hg19 genome assembly, and featureCounts from the Rsubread package was used for assigning counts to genes with default arguments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eExternal data analysis - ADNI\u003c/h2\u003e \u003cp\u003eThe study included 231 participants from the Alzheimer\u0026rsquo;s Disease Neuroimaging Initiative (ADNI) database, selected based on the availability of clinical, neuroimaging, and biomarker data. Individuals with neurological diseases other than Alzheimer\u0026rsquo;s Disease (AD) or severe psychiatric conditions were excluded. For all participants, cerebrospinal fluid (CSF) measurements of p-tau181 were available, in addition to tau- PET imaging data using 18F-labeled tracers (Flortaucipir). Ethical approval was obtained, and all participants provided informed consent. The α-synuclein seed amplification assay (αSyn SAA) was conducted in a clinical laboratory following CLIA guidelines, with samples analyzed in triplicate for quality control\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. Neuroimaging data were processed using standardized protocols described previously\u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e. MRI scans were bias-corrected, segmented, and spatially normalized using the CAT12 toolbox. PET images were harmonized, realigned, and smoothed to a common resolution to ensure consistency across different scanners. PET images were registered to T1 MRI and spatially normalized using the T1 MRI-derived spatial normalization parameters. Standardized uptake value ratios (SUVRs) for tau-PET were calculated for 200 brain regions of the Schaefer atlas using the inferior cerebellar grey reference region.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eProtein isolation and Western blotting\u003c/h2\u003e \u003cp\u003eFor automated capillary Western blots, homogenized iPSC-derived cerebral organoids were lysed in 1x RIPA Lysis Buffer (Merck, #20\u0026ndash;188) with protease inhibitors (Roche, CO-RO) and phosphatase inhibitors (Roche, PHOSS-RO), and the protein levels of the homogenates were quantified by bicinchoninic acid assays (Sigma-Aldrich). Protein samples were reduced in Fluorescent Master Mix with 200 mM dithiothreitol (ProteinSimple) and run on a Jess Automated Western Blot System (ProteinSimple) using the 12\u0026ndash;230 kDa Separation Module and 25-Capillary Cartridges (ProteinSimple).\u003c/p\u003e \u003cp\u003eProteins in the capillaries were blocked using Antibody Diluent 2 (ProteinSimple) and incubated with corresponding primary antibodies (anti-⍺ Synuclein (14H2L1) (Invitrogen, 1:50), anti-Tau (HT7) (Invitrogen, 1:50) for 90 minutes at room temperature and then with secondary HRP-conjugated antibodies (anti-rabbit and anti-mouse (ProteinSimple)) for 30 minutes at room temperature. For chemiluminescence detection, proteins were incubated in Luminol-Peroxide Mix (ProteinSimple) and scanned by the Jess Automated Western Blot System (ProteinSimple).\u003c/p\u003e \u003cp\u003eFor regular Western blots from post-mortem brain tissue and iPSC-derived neurons, samples were homogenized in 1x RIPA lysis buffer supplemented with protease inhibitors and phosphatase inhibitors using a Mini Bead Mill Homogenizer (VWR). After 30 min incubation on ice, the lysates were centrifuged at 16,000g for 30 min at 4\u0026deg;C to obtain the soluble protein fraction. For post-mortem brain tissue, the remaining pellets were washed once with lysis buffer and re-homogenized in 1% sarkosyl-containing lysis buffer, rotated overnight at 4\u0026deg;C. The samples were again centrifuged at 16,000g for 30 min at 4\u0026deg;C and the supernatant was collected as insoluble protein fraction. The protein concentration was determined by the Pierce\u0026trade; BCA Protein Assay (Thermo Scientific, #23225). 15\u0026micro;g of proteins for each sample were run on a 4\u0026ndash;20% precast polyacrylamide gel (Bio-Rad, #4561094) and electrophoresis was run at 90V for 1h and then 120V for 1h. The proteins were transferred to 0.45\u0026micro;m PVDF membranes (Millipore, #IPVH00010) at 200mA for 2h. The membranes were post-fixed with 4% paraformaldehyde and 0.1% glutaraldehyde for 30 min, washed in TBS supplemented with 0.1% Tween-20 (Sigma-Aldrich, #93773, TBST) and then blocked with 5% BSA (Sigma-Aldrich, #A7030) in TBST for 1h at room temperature (RT). The membranes were probed with primary antibodies diluted in the blocking solution overnight at 4\u0026deg;C. The next day, the membranes were washed 3 times with TBST and incubated with secondary antibodies for 1h at RT. After washing 3 times, the blots were developed with Pierce\u0026trade; ECL Western Blotting Substrate (Thermo Scientific, #32109) and imaged on the ChemiDoc MP Imaging System (Bio-Rad). For stripping, the blots were washed 3 times with TBST and then incubated in stripping buffer (ThermoFisher, #46430) for 15 minutes at RT. Thereafter, the blots were washed and re-probed as before. The following primary and secondary antibodies were used: HT7 anti-Tau (ThermoFisher, #MN1000), AT8 anti-phosphorylated Tau (ThermoFisher, #MN1020), T22 anti-Tau oligomer (Sigma-Aldrich, #ABN454), pS396 anti-phosphorylated tau (ThermoFisher, #44-752G), 14H2L1 anti-⍺ synuclein (ThermoFisher, #701085), PS129 anti-phosphorylated ⍺ synuclein (Abcam, #ab51253), pY216 anti-phosphorylated GSK-3β (BD Biosciences, #612313), anti-β actin (ThermoFisher, #AM4302), anti-mouse IgG HRP-conjugate (Sigma-Aldrich, #12\u0026ndash;349), anti-rabbit IgG HRP-conjugate (Promega, #W4011). Quantification of band densities was analyzed by FIJI software. Each target protein was normalized to β actin. A two-tailed unpaired t-test was performed to analyze the z-scored data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eRNA isolation and digital droplet PCR\u003c/h2\u003e \u003cp\u003eSingle-nucleus RNA-seq and ATAC-seq libraries were quantified using the ddPCR Library Quantification Kit for Illumina TruSeq (Bio-Rad, #186\u0026ndash;3040) according to the manufacturer\u0026rsquo;s instructions. For gene expression assays, total RNA was isolated with the RNeasy Mini Kit (Qiagen, #74104) and quantified by fluorometry using the Qubit dsDNA HS assay (ThermoFisher, Q33230) before 1 ng of RNA were retrotranscribed with the QuantiTect Reverse Transcription Kit (Qiagen, #205311). After droplet generation with 1 \u0026micro;L of RT reaction, 10 \u0026micro;L of 2X ddPCR EvaGreen Supermix (Bio-Rad, #1864033), 1 \u0026micro;L of each 10 \u0026micro;M forward and reverse primer and 7 \u0026micro;L of H2O, PCR was performed with a Tm of 60C on a Bio-Rad C1000 Touch Thermal Cycler. Ultimately, droplets were read on a QX200 droplet reader (Bio-Rad). Primer sequences are given in Supp. Table\u0026nbsp;4.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eLUHMES cell culture experiments\u003c/h2\u003e \u003cp\u003eLUHMES cells were seeded into appropriate culture vessels pre-coated with 1% of PLO 100x (10 mg/ml) (Sigma-Aldrich, P3655) and 99% of DPBS without calcium and magnesium (Thermo-Fisher, 14190144). Cell culture media for LUHMES was composed of DMEM/F12 (Thermo-Fisher, 11330032), 1% N2 supplement 100x (Thermo-Fisher, 17502001) and bFGF (25 \u0026micro;g/ml) (Thermo-Fisher, 11330032). For differentiation, the PLO solution was removed from the culture vessel, washed 3 times with DPBS, and a solution of 0,5% Fibronectin (5 \u0026micro;g/ml) (Sigma-Aldrich, F0895) in UltraPure DNase/RNase-Free Distilled Water (Invitrogen, 10977023). 100 ml of the medium used for differentiation into post-mitotic neuronal cells were composed of 98 ml of DMEM/F12, 1 ml of N2 supplement 100x, 1 ml of dibutryl cAMP (49 mg/ml) (Sigma-Aldrich, D0627), 40 \u0026micro;l of glial cell derived neurotrophic factor (GNDF) (5 ng/\u0026micro;l) (R\u0026amp;D System, 212-GD-010) and 100 \u0026micro;l of Tetracycline (1 mg/ml) (Sigma-Aldrich, T7660). To split 70\u0026ndash;80% confluent cells, they were washed once with DPBS and afterwards incubated for 5 minutes at 37\u0026deg;C with Trypsin-EDTA 0,05%. Trypsinization was blocked by adding an equivalent volume of a solution made with 10% FCS or FBS and 90% DMEM-F12. Trypan-Blue-stained cells were counted using a Neubauer counting chamber. For differentiation with a density of 1\u0026nbsp;million cells per well of a 6-well-plate, cells were left growing for 3 days in a T75 flask in order to arrive at confluence. 100 \u0026micro;l of a solution composed of differentiation medium and an adenovirus expressing either human wild-type SNCA or eGFP under the control of a CMV promoter was added to each well at a multiplicity of infection of 1.5 at day 2 after initiation of the differentiation process. After 24 hours, the cells were washed once with DPBS and medium was replaced with 2 ml of differentiation medium per well.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eiPSC culture and cerebral organoids\u003c/h2\u003e \u003cp\u003eInduced pluripotent stem cell (iPSC) lines were a gift from Tilo Kunath, University of Edinburgh. The first iPS cell line used in this study was derived from fibroblasts of an Iowan family with early-onset PD harbouring a \u003cem\u003eSNCA\u003c/em\u003e triplication\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e and is herein referred as AST (α-Synuclein triplication iPS cell line). The second line used is an isogenic, CRISPR-Cas9 corrected iPSC line with a normal \u003cem\u003eSNCA\u003c/em\u003e copy number, that has been generated from the AST cell line and is herein referred to as CAS\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e (corrected α-Syn triplication iPS cell line).\u003c/p\u003e \u003cp\u003eBoth the AST and CAS iPSC lines and subsequently differentiated cells were maintained in an incubator at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e throughout the experiments. Cell culture vessels for iPSC culture were coated with Matrigel (Corning) diluted 1:100 in DMEM/F12 (Thermo Fischer) The Matrigel-DMEM/F12 solution was applied to the culture vessels covering the surface and the plates were incubated for 1h at 37\u0026deg;C.\u003c/p\u003e \u003cp\u003eBefore thawing and plating the cells, the culture vessels were washed three times with DPBS -/- (Thermo Fisher). mTesR\u0026thinsp;+\u0026thinsp;medium (STEMCELL Technologies) with 10 \u0026micro;M Rock-Inhibitor (Merck) was added in each well and incubated at 37\u0026deg;C. Frozen iPSCs were thawed in a 37\u0026deg;C water bath until the ice block detached from the tube. The cells were decanted into a 15 ml centrifuge tube with 10 ml pre-warmed DMEM/F12 and the empty cryovial was washed with 1 ml DMEM/F12. The 15 ml tube was gently tilted to mix the cells and subsequently pelleted at 300 x g for 5 minutes at RT. The supernatant was removed and the pellet was carefully resuspended in 0.5 ml mTesR\u0026thinsp;+\u0026thinsp;medium per well. The cell suspension was applied onto the plate, carefully moved with quick side movements to evenly distribute the cells and placed in the incubator. After 24 hours, the medium was changed to remove cellular debris and Rock-Inhibitor. Until expansion of the cells, the medium was changed every second day until the cells reached confluency for passaging.\u003c/p\u003e \u003cp\u003eCells were passaged on prepared multi-well plates coated with Matrigel diluted 1:100 in DMEM/F12 for 1 h at 37\u0026deg;C. For routine cell passaging, iPSCs being 70\u0026ndash;80% confluent were passaged as colonies using ReLeSR (STEMCELL Technologies). The consumed medium was aspirated, replaced with 1 ml ReLeSR reagent and incubated for 1 minute at room temperature. ReLeSR was removed and the plate was placed in the incubator for 5 minutes. Cell colonies were detached by firmly tapping the side of the well plate and collected in 2 ml DMEM/F12 medium, centrifuged for 5 minutes at 300 x g at RT, resuspended in the desired mTesR\u0026thinsp;+\u0026thinsp;volume and evenly distributed with quick side movements. Cells were routinely passaged in ratios between 1:3 and 1:6. When starting experiments with a pre-defined number of cells, iPS cells were harvested using Gentle Cell Dissociation Reagent (GCDR) (STEMCELL Technologies) to obtain single cells. The consumed medium was aspirated and replaced with 1 ml GCDR and incubated for 5\u0026ndash;8 minutes at RT. After incubation, 1 ml of DMEM/F12 was added to the wells and the cells were scratched off using a cell scraper. The cells were collected and counted using a Neubauer counting chamber system, centrifuged for 5 minutes at 300 x g and eventually plated at the desired density. Being re-plated as single cells, Rock-Inhibitor at 10 \u0026micro;M final concentration was added to the culture medium for 24 hours.\u003c/p\u003e \u003cp\u003eCerebral organoids (CO) were cultured following the Lancaster Protocol\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e using the Cerebral Organoid Kit and Cerebral Organoid Maturation Kit (STEMCELL Technologies) for subsequent maturation of the organoids. On day 0, CO generation was started with embryoid body (EB) formation. Therefore, one 70\u0026ndash;80% confluent well of a 6-well plate of iPSC cells was washed with PBS and harvested with Gentle Cell Dissociation Reagent (STEMCELL Technologies). Cells were resuspended in EB seeding medium and 100 \u0026micro;l of cell suspension were plated into each well of a 96-well round-bottom ultra-low attachment plate (Corning) with a concentration of 90.000 cells/well. On day 2 and 4, 100 \u0026micro;l EB formation medium was added per well. On day 5, small formed EBs were transferred with a wide-bore pipette tip onto an ultra-low attachment 24-well plate (Corning) with 500 \u0026micro;l of fresh induction medium. At day 7, the EBs were collected with a wide-bore pipette tip and placed on an embedding sheet (STEMCELL Technologies). Excess medium was removed and a 15 \u0026micro;l Matrigel (Corning) droplet was added to the EB, which was subsequently positioned in the center of the drop. After 30 minutes incubation at 37\u0026deg;C for Matrigel polymerization, the Matrigel-embedded EBs were washed off the embedding sheet with expansion medium into an ultra-low attachment 6-well plate (Corning) and incubated for 3 days. At day 10, the consumed medium was replaced with fresh maturation medium and the well plate was transferred to an orbital shaker at 75 rpm at 37\u0026deg;C. Media changes were performed routinely every 2\u0026ndash;3 days. Organoids ready for harvesting were taken from the plate using a 1000 \u0026micro;l wide bore pipette tip. PCR Mycoplasma tests (Promokine) were performed routinely to exclude cell culture contamination.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eGeneration of iPSC-derived Neurons\u003c/h2\u003e \u003cp\u003eNeural progenitor cells (NPCs) were induced using an optimized protocol without the formation of EBs. IPSCs were dissociated and plated onto a Matrigel-coated plate in mTesR\u0026thinsp;+\u0026thinsp;medium supplemented with 10 \u0026micro;M Rock-Inhibitor. After 24 hours, with a confluency of 15\u0026ndash;25%, the medium was completely replaced with PSC Neural Induction Medium (NIM) consisting of 98% Neurobasal Medium and 2% Neural Induction Supplement (ThermoFisher, #A1647801). From then on, the NIM medium was completely refreshed every 2 days. After 7 days of induction, NPCs were passaged with Accutase (Stemcell Technologies, #07920) and seeded onto a Matrigel-coated plate with complete Neural Expansion Medium (NEM) containing 49% Neurobasal Medium, 49% DMEM/F12 (ThermoFisher, #12634), 2% Neural Induction Supplement and 5 \u0026micro;M Rock-Inhibitor. After overnight incubation, Rock-inhibitor was removed and NPCs were fed every other day by half-medium changes of NEM. After 4\u0026ndash;6 days, NPCs reached confluency and were ready for either cryopreservation or further differentiation. Before neuronal differentiation, NPCs were dissociated and plated onto plates coated with 50ug/ml PolyD-Lysine (PDL, ThermoFisher, #A3890401) and 2ug/ml laminin (Corning, #354232) in N2/B27 medium (1:1 ratio of DMEM/F12 to Neurobasal medium with 1\u0026times; N2 and B27 minus vitamin A, ThermoFisher, #17502001, #12587001) in the presence of 5 \u0026micro;M Rock-Inhibitor. The next day, the medium was refreshed without Rock-Inhibitor. After 48 hours of plating, 4 \u0026micro;M GSK343 (Sigma, #SML0766) was added to the N2/B27 medium for 8 days for promoting rapid differentiation\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Half of the medium was replaced every 1\u0026ndash;2 days according to cell density. 8 days later, GSK343 was washed out and the treated NPCs were ready for neuronal generation. At this point (day 0), treated NPCs were detached and directly seeded onto PDL/laminin coated plates with 5 \u0026micro;M Rock-Inhibitor and Neuronal Differentiation Medium (NDM) containing 48% Neurobasal Medium, 48% DMEM/F12 with GlutaMax (ThermoFisher, #10565018), 1x N2 supplement, 1x B27 supplement minus Vitamin A, 1x Culture One supplement (ThermoFisher, #A33202-01), 20 ng/ml BDNF (Peprotech, #450-02), 10 ng/ml GDNF (Peprotech,#450\u0026thinsp;\u0026minus;\u0026thinsp;10), 2 \u0026micro;g/ml laminin, 200 \u0026micro;M Ascobic acid (Merck, #A8960), 1\u0026micro;M dcAMP (Merck, #D0627) and 1% Penicillin-Streptomycin (ThermoFisher, #15070-63). The next day, the medium was refreshed without Rock-inhibitor. To generate sychronized neurons, 10 \u0026micro;M DAPT (ThermoFisher, #J65864.MA) was added to NDM for 10 days. From day 2 on, NDM was refreshed by performing a half-medium change every 3\u0026ndash;4 days until harvest or fixed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence\u003c/h2\u003e \u003cp\u003eTo stain LUHMES cells, a coated coverslip was placed into a well of 24-well plate and cells were added (0.2 x 10\u003csup\u003e6\u003c/sup\u003e for LUHMES and 0.5 x 10\u003csup\u003e6\u003c/sup\u003e for differentiated neuronal cells). The coverslip was moved to another plate and washed once with DPBS. Afterwards, it was incubated for 15 minutes with 4% paraformaldehyde (PFA) and washed 3 times for 10 minutes each with PBS. Incubation followed with 200 \u0026micro;l of a 1:200 primary antibody dilution (Anti βIII-Tubulin Rabbit) with 0.05% Tween 20 and 2% I-Block reagent (Sigma). The coverslip was incubated at 4\u0026deg;C overnight and then washed 3 times with PBS. 200 \u0026micro;l of a secondary antibody (Anti-Rabbit Alexa 488) and DAPI (both in 1 1:1000 dilution) were added and the coverslip was incubated for 2 hours at room temperature. After 3 washes in DPBS, each lasting 5 minutes, the coverslip was mounted on microscopy slides using mounting medium (Histo-Line laboratories, PMT030) and sealed with nail polish.\u003c/p\u003e \u003cp\u003eCortical organoids were fixed in 4% PFA, embedded in paraffin and cut to 10 \u0026micro;m thick sections. For deparaffinization, the slides were immersed in Xylene twice for 10 min, 100% Ethanol twice for 10 min, 95% Ethanol for 5 min, 70% Ethanol for 5 min, 50% Ethanol for 5 min, followed by a quick rinse with deionized H2O and incubation in PBS for 10 min. Antigen retrieval was performed by immersing the slides in 1x Sodium Citrate solution (Abcam, #ab64214) and placing them in a pressure cooker at high pressure for 20 min. The sections were cooled to RT and washed in PBS 3 times for 5 min. For permeabilization, the slides were then incubated with 0.2% Triton X-100 (Sigma-Aldrich, #T9284) in PBS for 10 min. After washing 3 times with PBS, the slides were blocked with 0.3% Triton X-100 in PBS with 5% normal goat serum (Sigma-Aldrich, #G9023) for 2h at RT. Primary antibodies were diluted in blocking solution and incubated overnight at 4\u0026deg;C. The next day, slides were washed 3 times with PBS and then incubated with diluted secondary antibodies in blocking solution for 2h at RT. The following primary and secondary antibodies were used: HT7 anti-Tau, 14H2L1 anti-⍺ synuclein, anti-MAP2 (SYSY antibodies, #188004), Alexa 647 (ThermoFisher, #A32787), Alexa 555 (ThermoFisher, #A21429) and Alexa 488 (ThermoFisher, #A11073). The sections were washed 3 times with PBS and covered with ROTI\u0026reg; Mount FluorCare DAPI (ROTH, #HP20.1).\u003c/p\u003e \u003cp\u003eIPSC-derived neurons were cultured on \u0026micro;-Slide 8 Well plates (Ibidi, #80826) for staining. Cells were fixed in 4% PFA for 15 min at RT, washed three times with PBS, permeabilized and blocked in PBS solution consisting of 2% BSA, 5% donkey serum (Sigma, #D9663), 5% goat serum and 0.2% Triton-X-100 for 2h at RT. Primary antibodies diluted in the same blocking solution were added to cells overnight at 4\u0026deg;C. The used primary antibodies included: HT7 anti-Tau, pS396 anti-phosphorylated tau, 14H2L1 anti-⍺ synuclein, pY216 anti-phosphorylated GSK-3β and anti-β-III Tubulin (Novus Biologicals, #NB100-1612). Secondary antibodies conjugated with Alexa 647, Alexa 555 and Alexa 488 were incubated for 1h at RT. After washing, cells were mounted with ROTI\u0026reg; Mount FluorCare DAPI.\u003c/p\u003e \u003cp\u003eAll images were acquired using the confocal microscope Stellaris 5 (Leica). For each immunofluorescence reaction, secondary-only controls were verified to be absent of fluorescent signal before proceeding. Laser power and detector gain levels remained unchanged between imaging sessions across groups.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cu\u003eData and Code availability\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll code used in this study is available under https://github.com/fstrueb/MAPT_SNCA. Human sequencing data can be shared upon request after appropriate review by the LMU Institutional Review Board. Access to MSBB data can be gained after institutional review, see www.synapse.org.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAcknowledgements\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman induced pluripotent stem cells were a gift from Dr. Tilo Kunath (University of Edinburgh, UK). We would like to thank Dr. Christian Haass and the SyNergy consortium for their commitment and support in supplying whole genome sequencing data from the NBM inventory. We would like to acknowledge Vanessa Boll for DNA isolation, Dr. Norbert Buresch for dissection of fresh-frozen brain tissue, and Michael Schmidt for his help with immunohistochemistry and slide scanning. We would also like to thank Dr. Oliver Keppler for granting us access to the SimpleWestern\u0026trade; apparatus. Whole genomes were sequenced by the Helmholtz Munich Core Facility Genomics (lead by Dr. Inti Alberto de la Rosa Velazquez) and generously sponsored by the Munich SyNergy consortium. We are thankful to Dr. Paul Feyen, Dr. Lars Paeger, Dr. Nils Briel, Antonia Neubauer and Dr. Patrick Harter for inspiring discussions. Ultimately, we are deeply indebted to the hundreds of patients who chose to donate their brains to research, including their families.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAuthor contributions\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFLS and JH conceived the project. JH, VR, TA and SR evaluated brains of the WGS cohort for\u0026nbsp;⍺-synuclein pathology. JuWi and JH organized and oversaw WGS. OW supplied material from the Munich Brain Bank. FLS generated snRNA- and snATAC-seq data for suitable cases as identified by VR. FLS performed WGS variant calling and all bioinformatic and statistical analyses. Digital droplet PCR assays were run by FLS, TDV, JeaWi and XXS. JeaWi raised cortical organoids and performed Mycoplasma testing. TDV performed all SimpleWestern\u0026trade; experiments and assisted in growing cortical organoids. FF, QLT and TK ran LUHMES experiments. XXS performed Western blots, immunofluorescent stainings of organoids and neurons, differentiation of AST and CAS cell lines to neurons and ATAC-seq. AD, MB and NF contributed ADNI and SAA data. FLS wrote the first draft of the manuscript and designed figures with significant input from JH, TDV and XXS. All authors read, improved and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eFunding information\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFLS was supported by European Union Marie-Curie Actions (H2020-MSCA-IF-2017: NOJUNKDNA; 792832) at the start of experiments and is currently supported by the German Research Foundation (DFG, grant number STR 1537/3-1). FF was supported by the Erasmus+/KA1 Program (Convention n. 2020-1-IT02-KA103-077708 Agreement 2020/2021 n.17). This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany\u0026rsquo;s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy\u0026ndash;ID 390857198).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eConflict of Interest\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGBD 2021 Nervous System Disorders Collaborators. Global, regional, and national burden of disorders affecting the nervous system, 1990\u0026ndash;2021: a systematic analysis for the Global Burden of Disease Study 2021. 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Nat Protoc. 2014;9:2329\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Alzheimer’s Disease, Parkinson’s Disease, Genetic Risk, Multiomics, Bioinformatics, tau, alpha-synuclein, iPSCs","lastPublishedDoi":"10.21203/rs.3.rs-6494882/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6494882/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe molecular basis for accelerated cognitive decline seen in Alzheimer\u0026rsquo;s Disease (AD) cases presenting with cortical alpha-Synuclein (SNCA/⍺-Syn) co-pathology is not well understood. We show that such AD co-pathology brains are characterized by an increased polygenic risk score for Parkinson\u0026rsquo;s Disease (PD), which is related to an enrichment in the \u003cem\u003eMAPT\u003c/em\u003e H1 haplotype as well as risk factors known to increase \u003cem\u003eSNCA\u003c/em\u003e transcription. AD\u0026thinsp;+\u0026thinsp;ASYN brains express higher levels of ⍺-Syn and neuronal microtubule-associated protein tau (MAPT), and increasing \u003cem\u003eSNCA\u003c/em\u003e expression is sufficient to drive transcription, translation and phosphorylation of tau. In addition, tau is significantly elevated in subjects with a positive cerebrospinal fluid ⍺-Syn seeding aggregation assay. Our results reveal a hitherto unknown link between the pathogenesis of AD and PD whereby tau and ⍺-Syn synergistically drive dementia-related pathology.\u003c/p\u003e","manuscriptTitle":"Alpha-Synuclein co-pathology in Alzheimer’s Disease drives tau accumulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-21 08:34:55","doi":"10.21203/rs.3.rs-6494882/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"78b51b68-14aa-4b56-9e43-040c4ca1ed4e","owner":[],"postedDate":"May 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-17T20:38:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-21 08:34:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6494882","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6494882","identity":"rs-6494882","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}