Results
Catalog of alpha-synuclein proteoforms in the human appendix and SN
To determine whether the appendix contains alpha -synuclein proteoforms relevant to
disease pathology, we profiled the alpha -synuclein proteoforms in the appendix of
synucleinopathy patients and healthy individuals and performed comparisons to those present in
the SN. In total, 65 distinct alpha -synuclein proteoforms were identified in the human appendix
(Figure 1A), ranging from the full-length N-terminally acetylated proteoform (alpha-synucleinac1-
140) to truncated species 31 amino acids in length (alpha -synuclein78-109). There were truncated
species with N - or C -terminal cleavage only (n= 4 and 13 alpha -synuclein proteoforms,
respectively). However, the large majority, 46 alpha-synuclein proteoforms, were cleaved at both
ends: 23 with N - and C -terminal truncations and 23 with intra -NAC domain and C -terminal
truncations. In total, we identified 27 unique cleavage locations for alpha -synuclein proteoforms
in the appendix, of which 6 o ccurred within the N -terminus, 6 were in the NAC domain, and 15
were in the C-terminus. The most common truncation site was in the C -terminus at position 114,
which has been found to promote Lewy pathology formation in neurons (30), and other frequently
cleaved sites included positions 40, 73, 109 and 115 of alpha -synuclein (number of proteoforms
with cleavage site: 13, 9, 9, 8, 8, respectively). Of the 65 alpha -synuclein proteoforms identified
in the appendix, 56 were also detected in the SN. All proteoforms detected in the substantia nigra
were present in the appendix. We found 9 alpha -synuclein proteoforms that were present only in
the appendix, with most of these cleaved in both the NAC domain and C -terminus (alpha -
synuclein66-114, alpha -synuclein68-114, alpha -synuclein73-114, alpha -synuclein66-132, alpha -
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synuclein68-109, alpha-synuclein73-122, and alpha -synuclein73-125). Thus, the appendix contained a
diverse and distinct pool of alpha-synuclein truncation products.
We next compared the abundance of alpha-synuclein proteoforms in the appendix and SN
(Figure 1B, 1C). First, we determined whether the appendix and SN had quantitative differences
in common proteoforms (present in ≥50 samples). We found that alpha -synuclein proteoforms
with truncations at the C -terminus position 114/115 were significantly more common i n the
appendix than in the SN ( q<0.05 for alpha -synuclein68-115, alpha -synuclein1-114 and alpha -
synuclein1-115, linear regression). In contrast, the appendix had lower levels of other C -terminal
truncations, including at positions 103, 119, and 122, relative to the SN ( q<0.05 for alpha -
synuclein1-103, alpha-synuclein1-119 and alpha-synuclein1-122, linear regression). To analyze the rare
proteoforms, we determined whether each alpha -synuclein proteoform occurred more frequently
in the appendix or SN (Fig. 1C). We found that in the appendix several rare proteoforms were
more abundant (alpha -synucleinac1-125, alpha -synuclein40-115, alpha -synucleinac1-129, alpha -
synucleinac1-114) and conversely, several rare proteoforms were more abundant in the SN (alpha -
synucleinac1-121, alpha -synuclein58-101, alpha -synuclein54-115, alpha -synuclein58-104, alpha -
synuclein76-104, alpha-synuclein68-119, alpha-synuclein73-119). We also found that levels of reliably
detected proteoforms alpha -synucleinac1-122 and alpha-synuclein78-113 were significantly depleted
in synucleinopathy cases relative to controls (q<0.05, linear regression; Supplementary Figure S1).
We also detected instances of syn proteoforms that were unacetylated at the N-terminus for alpha-
synuclein1-140 and alpha -synuclein1-114, in addition to their abundant N -terminal acetylated
counterparts in both the appendix and SN (Fig. 1D). Therefore, both common and rare proteoforms
differed in relative abundance between appendix and SN. Through classifier model training, we
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predicted with an accuracy above 80% that alpha -synucleinac1-122 may be a highly relevant
predictor of synucleinopathy in both appendix and SN (Supplementary Figure S1).
We further investigated age-dependent changes in the alpha-synuclein proteoforms present
in the appendix and SN and found that synucleinopathy appendix had a significant gain in full -
length synuclein (alpha -synucleinac1-140) with age, which was not observed in the appendix of
unaffected controls (q<0.05, linear regression; Supplementary Figure S2). Finally, sample -wise
Pearson correlation showed that synuclein proteoforms in the appendix are more similar to those
in synucleinopathy SN than control SN (Supplementary Figure S3).
The aggregation propensity of alpha-synuclein in the appendix
Given that alpha -synuclein aggregation plays a central role in the development of
synucleinopathies, we sought to characterize the aggregation propensity of the proteoforms we
identified in the appendix and SN. We modelled the aggregation potential of each alpha-syuclein
proteoform using a computational approach that determines the energy requirements for amyloid
fibril formation (31). We then determined the alpha -synuclein aggregation propensity score for
each sample based on proteoform abundances and their aggregation potential. We found that the
aggregation propensity of alpha-synuclein in the appendix was significantly higher than in the SN
(p<10-10, linear regression; Figure 2A). Overall, this signifies that the appendix contains an
abundance of aggregation-prone alpha-synuclein proteoforms (32-35).
In parallel, we employed an enhanced alpha-synuclein-SAA to detect alpha -synuclein
seeding activity in postmortem appendix tissues from synucleinopathy patients compared to
matched controls. Using ThT fluorescence (AU) to measure seeding activity, we found 11 out of
16 (68.75%) Synucleinopathy appendices exhibited increased seeding activity (Figure 2D) as
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evidenced by increased ThT fluorescence (Figure 2B). In contrast, only 1 out of 15 controls (6.6%)
demonstrated detectable seeding activity. Over a period of 24 h, synucleinopathy appendices
showed a progressive increase in ThT fluorescence, whereas fluorescence in controls remained
lower (Figure 2B). Furthermore, the average Fmax recorded at the plateau was significantly higher
in synucleinopathy appendix as compared to controls (p=10 -4) (Figure 2C). These results show
significantly higher overall alpha-synuclein seeding activity in synucleinopathy appendix.
In the appendix and SN, we detected full -length alpha -synuclein lacking N -terminal
acetylation, which has been shown to substantially increase its aggregation potential while
reducing its lipid and synaptic vesicle binding affinity (32-35)(p<10-4; Figure 1D). Indeed, full -
length alpha-synuclein that lacked N-terminal acetylation comprised 17.9% of the total full-length
alpha-synuclein in the appendix and 3.8% in the SN. The only other N -terminal unacetylated
alpha-synuclein proteoform detected in our study was unAc -alpha-synuclein1-114, which was
primarily found in the appendix; present in 50.9% of appendix samples compared to only 21.1%
of SN samples (unAc -alpha-synuclein1-114 present in 27 of 53 appendix samples and 4 of 19 SN
samples; Figure 1D). Thus, delay in N-terminal acetylation in the appendix may accelerate alpha-
synuclein aggregation in this tissue. No differences in N -terminal unacetylated alpha -synuclein
were observed between synucleinopathy cases and controls (Supplementary Figure S4).
Differential gene expression in disease
A total of 22029 genes were assessed, out of which 137 genes were significantly
upregulated, and 113 genes were significantly downregulated in synucleinopathy appendix
compared to healthy appendix (p-adj<0.05) (Figure 3A) (supplementary table S1). We identified
dysregulation of genes related to heat shock and chaperone proteins associated with protein folding
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and degradation, immune response , as well as genes associated with cili a assembly and
organization (Table 1).
Gene Set Enrichment Analysis (GSEA) was performed to assess whether predefined gene
sets exhibit statistically significant differences between synucleinopathy and control samples.
Differentially expressed ( DE) genes in synucleinopathy appendix samples were found to be
enriched in a total of 384 pathways, categorized as follows: 303 in GO Biological Processes (GO
BP), 46 in GO Molecular Functions (GO MF), 31 in GO Cellular Components (GO CC), and 4 in
KEGG pathways (supplementary data files S2-S5). The analysis highlighted several key processes
involved in protein homeostasis and immune signaling that were significantly upregulated , and
some related to ciliary dynamics that were downregulated (Figure 3B, 3C, 3D).
Differential DNA methylation in disease
The overall distribution of differentially methylated regions (DMRs) across gene regions,
CpG regions, and the total methylation profile suggests a predominantly hypomethylated status in
synucleinopathy appendix samples compared to healthy controls (Figure 4B, 4C, 4D). Most CpG
sites were at promoter region transcription start site 1500 ( TSS1500)(67.29%), followed by 5’
untranslated region (5’UTR)(12.87%), transcription start site 200 ( TSS200)(10.99%), gene body
(6.43%), intergenic (1.61%) and 1st Exon (0.80%). In terms of CpG regions, the highest number
of CpG sites was at islands (68.90%), followed by shores (22.52%), open sea (6.97%), and shelves
(1.61%).
We found 46 unique genes in the vicinity of 45 DMRs- 39 genes were hypomethylated,
while 7 genes were hypermethylated (supplementary table S6). Methylation differences between
synucleinopathy and control appendices were subtle but aligned with our transcriptomic analysis;
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we found differentially methylated genes related to protein degradation, folding and homeostasis,
immune response, and ciliary and cytoskeletal dynamics (Table 2) . Additionally, we found
differential methylation in some genes associated with oxidative stress and mitochondrial function,
both of which have been implicated in neurodegeneration. GSEA revealed neuronal signaling and
development pathways that were enriched for hypomethylated genes, and stress response and cell
signaling pathways that were enriche d for hypermethylated genes in synucleinopathy appendix
(Figure 5) (supplementary tables S7-S10).
Functional clustering based on protein interactions in disease
Differentially expressed and methylated genes (p -adj<0.05) from RNA -seq and DNA
methylation analyses were analyzed using the STRING database to create a network map (Figure
6). Functional clusters identified through Markov Cluster Algorithm (MCL) aligned with key
pathways highlighted in GSEA analysis, including protein homeostasis (Unfolded protein binding
and Chaperone complex), immune response (Autoimmune disease), and ciliary structure
(Axonemal microtubule) networks.
Discussion
The vermiform appendix has emerged as a potential peripheral site where increased levels
of aggregated alpha-synuclein potentially appear early in the course of synucleinopathies (9). In
the presence of impaired autophagy-lysosomal function in the same tissue (13), aggregated alpha-
synuclein might propagate from enteric nerves to the CNS, making the appendix one possible site
for initiation of the first steps in the pathogenesis of synucleinopathies. Despite growing evidence,
the mechanisms causing alpha-synuclein aggregation in the appendix are poorly understood. To
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address this knowledge gap, we employed proteomic, transcriptomic, and epigenomic profiling of
appendices from synucleinopathy patients and healthy controls. Our findings reveal a distinct,
aggregation-prone pool of alpha -synuclein proteoforms in the synucleinopathy appendix, and
significant dysregulation in protein homeostasis, immune response , and ciliary function and
processes in the synucleinopathy appendix. These findings provide a novel molecular insight into
the vermiform appendix as a peripheral site where alpha-synuclein aggregates in the earliest stages
of the disease process.
To characterize the molecular features underlying synuclein pathology , we investigated
alpha-synuclein aggregation and truncation in appendix tissues and SN. When we modeled
aggregation propensity for the total pool of alpha-synuclein proteoforms identified using TD-MS,
we observed a higher aggregation propensity in the appendix in comparison to SN. This suggests
the unique proteolytic processing in the vermifo rm appendix “primes” the endogenous alpha -
synuclein pool for pathological aggregation, which may also be true of other peripheral tissues
where pathology has also been documented (36, 37). We then investigated this experimentally
using alpha-synuclein-SAA, where we detected seeding activity in 68.75% of synucleinopathy
appendix samples compared to 6.6% of healthy appendix samples. Importantly, fluorescence
kinetics revealed higher seeding activity, reflected by greater ThT signal and Fmax, in
synucleinopathy appendix relative to controls. These findings are consistent with previous studies
showing that gastrointestinal tissues from synucleinopathy patients exhibit more consistent
seeding activity compared to controls (38). Notably, our finding that 68.75% of synucleinopathy
appendices are SAA-positive aligns well with the proposed “body-first subtype” of Lewy body
diseases (39), in which pathology is hypothesized to begin in the enteric nervous system and ascend
to the brain via the vagus and sympathetic nerves. According to this model, approximately half of
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the Lewy body disease patients belong to the “body-first” subgroup, and the remaining fall into a
“brain-first” category, with around 70% cases of dementia with Lewy bodies (DLB) and only
~30% of PD cases exhibiting a body-first pattern (40). Since our synucleinopathy cohort was DLB-
rich (n=12 of 16), the observation that 68.75% of our synucleinopathy appendix samples were
SAA-positive is consistent with the expected proportion of body-first cases. Conversely, 31.25%
of synucleinopathy appendices were negative for seeding activity in alpha -synuclein-SAA,
suggesting a brain-first trajectory while exhibiting less peripheral involvement, demonstrating the
heterogeneity of alpha-synuclein pathology within synucleinopathies.
We previously identified the appendix as a reservoir of intraneuronal alpha -synuclein
aggregates that are enriched with truncated proteoforms (9), which raised questions about the
proteolytic turnover of alpha -synuclein in the appendix. Here we addressed those questions by
cataloging all detectable alpha -synuclein proteoforms using a TD -MS approach, similar to what
has been done in brain tissue (26). This study provides one of the most comprehensive catalogs of
alpha-synuclein truncation in human tissues to date. We compared alpha -synuclein proteoforms
between tissues and found proteoform abundance varied significantly between the appendix and
SN. Unexpectedly, 9 proteoforms were unique to the appendix and were not detected in any of the
SN samples. Conversely, two proteoforms, namely alpha -synuclein78-113 and alpha-synucleinac1-
122, were decreased in the synucleinopathy appendix compared to controls. The decrease in these
proteoforms can be attributed to either abnormal proteolytic turnover of alpha -synuclein in the
synucleinopathy appendix or possibly indicative of aggregation, as proteof orms that form
insoluble inclusions would not be detected with our methodology.
Several of the cleavage sites and proteoforms we identified have been described previously
(9, 21, 26), but we also characterize d proteoforms not yet described in literature. As truncated
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forms of alpha -synuclein are a substantial component of inclusions (41), characterization of the
proteoforms present in the appendix and SN may improve our understanding of the origins of
synucleinopathies. Truncation and N -terminal acetylation were the only detectable PTMs. Like
many eukaryotic proteins, the N -terminal methionine of mature alpha -synuclein is permanently
acetylated. Here, we made the interesting observation that full -length and some C -terminally
truncated alpha -synuclein species were unacetylated. Although the levels of N -terminally
unacetylated alpha -synuclein were relatively low in the brain and appendix, several appendix
samples showed a surprising abundance of this particular proteoform (~1:2). Furthermore,
unacetylated alpha-synuclein was the third most abundant proteoform we detected regardless of
synucleinopathy or tissue type. Unacetylated alpha-synuclein likely represents immature or newly
synthesized protein that has not yet been enzymatically modified. T hus, in some instances alpha-
synuclein was cleaved prior to becoming a mat ure protein. This raises the possibility that alpha -
synuclein truncation can be an early event in the protein's natural lifecycle. Of note, we did not
detect any phosphorylated proteoforms, including the disease -associated phosphoserine 129,
which is in agreement with prev ious studies showing very low levels of this modification in the
normal soluble alpha-synuclein pool (26). Furthermore, alpha-synuclein from the human appendix
was more abundant in truncated prote oforms when compared to the brain . Combined with our
previous observation of an impaired lysosomal autophagy system in the Parkinson’s disease
appendix (13), this might suggest that the turnover of alpha-synuclein was impaired, leading to an
accumulation of truncated proteoforms and the formation of proteopathic seeds that could initiate
the first steps of synucleinopathy.
Together, our results suggest that proteolytic degradation (i.e. turnover) of alpha-synuclein
is tissue-specific, and therefore some tissues, like the vermiform appendix, may be more likely to
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accumulate alpha-synuclein, including rare truncated proteoforms. Some important considerations
should be taken when interpreting our findings. First, immunopurification of alpha-synuclein was
conducted using clone 42 anti -alpha-synuclein antibody (BD Transduction Laboratories) which
maps to residues 91 -99 of human alpha -synuclein (42), and thus, all proteoforms detected
expectedly contain this epitope, and any proteoforms lacking this epitope would not be detected
here. The total alpha -synuclein signal intensity was similar between appendix and SN samples
despite relatively low expression of alpha -synuclein in the appendix, indicating that
immunopurification w as conducted at near -saturating conditions. As a result, our data are not
indicative of changes in total alpha-synuclein content of the tissues but instead are an indicator of
the proteoform signature of the samples. Because our analyses were performed on the triton x100
soluble fraction of alpha-synuclein, it is limited to proteoforms found outside of inclusion bodies.
Conceptually, proteoforms identified here are “pre -pathological” and provide insight into the
normal turnover of this protein in peripheral and CNS tissues.
Building on our TD-MS and seed amplification assay results, which indicate a heightened
aggregation potential in synucleinopathy appendix, we turned to multi -omics profiling to
investigate the transcriptional and epigenetic underpinnings of this phenomenon. We identified a
prominent alteration in genes involved in proteostasis and quality control, which suggests cellular
stress and activated mechanisms to counteract misfolded protein burden in the synucleinopathy
appendix. Activated pathways associated with molecular assemblies such as intracellular protein-
containing complex, transferase complex and ribonucleoprotein complex hint towards changes in
protein turnover, potentially instigated by aggregation of misfolded alpha-synuclein in the
synucleinopathy appendix. Molecular function pathways relevant to synuclein pathology such as
protein phosphorylated amino acid binding, phosphoprotein binding , and phosphotransferase
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activity were also upregulated. In the context of PD, these pathways are central to the recognition
of phosphorylated alpha-synuclein, and binding to 14-3-3 domain proteins to produce Lewy body
pathology (43), further highlighting a dysregulated proteostasis network. Simultaneously, protein
folding chaperone, and HSP/protein folding chaperone binding pathways were upregulated in
synucleinopathy appendix, suggesting a cellular attempt to attenuate misfolding and aggregation
of alpha-synuclein. Activation of pathways associated with lysosomal membrane and lytic vacuole
membrane indicates an increase in compensatory autophagic clearance. DNA methylation pathway
enrichment revealed hypomethylated (may indicate potentially increased activity) genes
associated with cation channel complex, as well as d ifferential methylation of calcium signaling
pathway genes (both hypo - and hyper -enriched), reflecting altered regulation of processes
implicated in alpha-synuclein aggregation (44). Additionally, hypermethylation ( may indicate
potentially decreased activity) of genes associated with Wnt signaling pathway and negative
regulation of autophagy is consistent with our previous observations at transcriptomic level. At the
gene level, these changes were reflected in the observed upregulation of several molecular
chaperones and co-chaperones of heat shock proteins (HSPs) such as AHA1, STIP1, METTL21A,
HSPA1L, and HSPA4 (45). The chaperones HSP70 and HSP90 play a crucial role in mitigating
cellular stress such as accumulation of misfolded proteins (46), degradation of toxic protein
aggregates (47), and modulating alpha -synuclein dynamics (48). We also observed
hypomethylation in promoter regions of several genes implicated in autophagy, lysosomal
trafficking, and stress signaling, such as CDK16, SH3GLB1, and ABCB9 in the synucleinopathy
appendix (49) (50) (51), and hypermethylation of DCUN1D1, which was previously identified as
a novel candidate gene in protein interactome-based PD studies (52).
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Immune response -related pathways such as T cell receptor signaling, lymphocyte
differentiation and activation, and adaptive immune response , were activated in transcriptomic
enrichment analysis, indicating a sustained state of immune activation in the synucleinopathy
appendix. Interestingly, immune response regulating pathways were also activated, potentially
suggesting a compensatory attempt to maintain immune balance in response to proteostatic stress.
Differential methylation of the stress and immune regulatory MAPK signaling pathway (both
hypo- and hyper -enriched), and hyper-enrichment of Toll -like receptor signaling also suggest
immune remodeling at the epigenetic level. Our observations at gene level, such as upregulation
of chemokine and interferon response genes CCL2, IRF7, IL7R, and the immunomodulatory
checkpoint gene VSIR, further reflect the complex immune environment within synucleinopathy
appendixes. Particularly, in the context of neurodegenerative disease, CCL2 and VSIR have been
associated with microglial activation and neuroinflammation (53, 54). We also found
hypomethylation in the promoter region of long noncoding RNA H19, the overexpression of which
has been associated with downregulation of tight junction proteins ZO-1 and occludin (55). This
may, in turn, compromise the integrity of the epithelial barrier in the synucleinopathy appendix
and further increase vulnerability to inflammation , while simultaneously allowing for microbial
products inside the appendix to circulate systemically . This so -called ‘leaky gut’ state, in
combination with the perturbed local immune environment, may contribute to systemic
inflammation and potentially influenc e alpha-synuclein pathology (56). These results are also
consistent with another recent study, where transcriptomic and epigenomic profiling of the colonic
mucosa revealed shared immune dysregulation in PD and inflammatory bowel disease patients
(57). Their findings also suggest that chronic peripheral inflammation can increase the risk for PD
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in inflammatory bowel disease patients, further strengthening the link between gut immune
dysregulation and neurodegeneration.
Our data also revealed consistent dysregulation of genes related to primary and motile
ciliary structure and function. Primary cilia are essential cellular organelles that are present on the
epithelial layer, as well as in the enteric neurons embedded inside the appendix (58). These
structures are involved in modulating the Sonic Hedgehog (Shh) pathway, which is crucial for
neurogenesis, and has been linked to PD (59, 60). Motile cilia, on the other hand, are found on
specialized cells and facilitate the movement of fluid over epithelial surfaces (61). In pathway
analysis, we observed significant disruption of cilia -related processes as well as other structural
components, as reflected by suppressed pathways associated with axoneme assembly, cilium
assembly and organization, ciliary plasm, mobile cilium, ciliary transition zone, cilium- or
flagellum-dependent cell motility, epithelial morphogenesis, and extracellular matrix . Beyond
dysfunctional signaling, disruption of these components would also have implications for barrier
integrity, corroborating our earlier observation. The hypo-enrichment of KEGG terms such as
regulation of actin cytoskeleton and focal adhesion may indicate compensatory activity of the
epigenetic machinery, which appears to mitigate transcriptomic suppression. The observed
downregulation of primary cilia stability gene SAXO1, and motile cilia function genes LCA5L,
CFAP45, and DNAI7, as well as hypomethylation of the downstream cellular regulators GLI4 and
GAS7, would further hint towards downstream disruption of Shh signaling and possibly, GI
motility, in synucleinopathy patients. Interestingly, GLI4 and GAS7 have been associated with
PD in previous studies (62, 63). Additionally, LRRK2 mutations, which are common in PD, have
also been found to interfere with cilia formation and Shh signaling, further suggesting a potential
mechanistic link between ciliary dysfunction and PD development (64).
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Although we observed no direct overlap between differentially methylated genes and
differentially expressed genes in our data after FDR correction, both datasets overlap substantially
in functional themes. This suggests that even subtle methylation changes in the synucleinopathy
appendix observed here could potentially influence gene expression, and the divergence could be
because of additional regulatory layers such as histone modifications or non-coding RNAs.
The present study provides new insights into the molecular landscape of the vermiform
appendix in PD, highlighting it as a potential contributor to pathology. The interplay between
impaired protein homeostasis , immune dysregulation, and ciliary dysfunction may prove
conducive to aggregation of alpha-synuclein, which could then lead to propagation of pathology
to the central nervous system. Further research into the identified dysregulated genes and
pathways, as well as aberrant alpha-synuclein processing in the appendix, may provide critical
insights and inform the development of therapeutics for synucleinopathies.
References
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Acknowledgements
We thank the Van Andel Institute’s Pathology and Biorepository, Genomics,
Bioinformatics and Biostatistics Cores, and the Michigan State University Genomics Core for
assistance with experimentation. We are grateful to the Oregon Brain Bank, Parkinson’s UK Brain
Bank, the NIH NeuroBioBank, LifeNet Health and Corewell Health for providing the tissues used
in this study. We would like to acknowledge Paul M. Thomas and Eva Boonen for their
contributions and support. Finally, we gratefully acknowledge the contributions of the late Dr .
Viviane Labrie, whose scientific vision and passion for advancing neurodegenerative disease
research significantly shaped this work.
Funding: This work was supported by the NIH -National Institute of Neurological Disorders and
Stroke grant R01NS114409 awarded to LB . The SAA studies were partially funded by
U24AG079685 grant to CS and a grant from Michael J. Fox Foundation to SP.
Author contributions:
Conceptualization: PB, LB
Methodology: CS, PB, LB, JHK, RDL
.CC-BY 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
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Investigation: EA, SZ, JWS, MS, PL, MP, SP, BAK
Visualization: PL, JWS, JG, MP, SP, BAK
Funding acquisition: PB, LB
Project administration: CS, PB, LB
Supervision: RDL, JHK, SP, CS, PB, LB
Writing – original draft: EA, SZ, JW, BAK
Writing – review & editing: EA, SZ, JW, PB, LB, BAK
Competing interests:
CS is a Founder, Chief Scientific Officer, consultant and shareholder of Amprion Inc., a
biotechnology company that focuses on the commercial use of seed amplification assays for high-
sensitivity detection of misfolded protein aggregates involved in various neurodegenerative
diseases. Sandra Pritzkow also has a conflict in relation to Amprion. The University of Texas
Health Science Center at Houston has licensed patents and patent applications to Amprion. During
the time that this study was being conducted, PB became an employee of F. Hoffmann-La Roche
and obtained stock in the company (one of the data were generated by F. Hoffmann -La Roche).
He also has ownership interests in Acousort AB, Axial Therapeutics, Enterin Inc and Kenai
Therapeutics.
Data and materials a vailability: Custom code for statistical analysis is available at
https://github.com/lipeipei0611/SynProteoforms. Due to the current U.S. government shutdown,
data deposition in publicly accessible repositories has been temporarily delayed. All datasets
supporting the findings of this study will be made publicly available in the designated repositories
.CC-BY 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
The copyright holder for this preprintthis version posted October 7, 2025. ; https://doi.org/10.1101/2025.10.07.680938doi: bioRxiv preprint
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as soon as repository services are restored. Data are available from the corresponding author upon
reasonable request until the repositories reopen.
Figure captions
Figure 1. Alpha -synuclein proteoforms in the appendix and substantia nigra (SN) (A) Bar
plot showing 65 alpha-synuclein proteoforms identified in the human appendix and SN. Acetylated
proteoforms are colored dark blue; unacetylated proteoforms are colored light blue. Nine
proteoforms, which were only found in the appendix, are denoted with *. (B) Bar plot showing
alpha-synuclein proteoforms distribution according to their abundance in the human appendix and
SN separately. X-axis shows the percentage of the abundance for each existing proteoform. Top 5
most abundant proteoforms are listed with thei r color codes. (C) Common alpha-synuclein and
rare proteoforms showing tissue differences. For common alpha -synuclein proteoforms, robust
linear regression was used for statistical analysis adjusting for diagnosis (synucleinopathy/control)
and age, with proteoform abundance as dependent variable (Y) and tissue as independent variable
(X). Proteoforms showing significant tissue differences after FDR q<0.05 are denoted with *. For
rare alpha-synuclein proteoforms robust linear regression was used for statistical analysis adjusting
for diagnosis (synucleinopathy/control) and age, with proteoform detection (TRUE or FALSE) as
dependent variable (Y) and tissue as independent variable (X). Only rare proteoforms showing
tissue difference after FDR q<0.05 are shown and denoted with *. (More in appendix in color dark
green; more in SN in color dark blue). (D) unAc1-140 increased in the appendix, unAc1 -114
increased in the SN. Robust linear regression was used for statistical analysis, adjusting for
diagnosis (synucleinopathy/control) and age.
.CC-BY 4.0 International licenseavailable under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
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Figure 2. Aggregation propensity and seeding activity of alpha -synuclein. (A) High
aggregation propensity of alpha -synuclein in the synucleinopathy (Syn) appendix compared to
substantia nigra (SN). Aggregation propensity for each proteoform was estimated using P ASTA
2.0. Robust linear regression was used for statistical analysis adjusting for diagnosis
(synucleinopathy/control) and age, with aggregation propensity as dependent variable and tissue
as independent variable. (B) Aggregation kinetics as measured by the assay demonstrated
significantly increased average ThT fluorescence (AU) in synucleinopathy appendixes (n=16) over
time compared to controls (n=15). This suggests the higher seeding activity of misfolded a lpha-
synuclein in synucleinopathy appendixes versus controls with no detectable seeding activity. (C)
The maximum fluorescence (Fmax) recorded at the plateau of aggregation was significantly higher
in synucleinopathy appendix as compared to controls (p<0.05). The graph includes data from all
3 replicates in each sample. Since positive/negative scores are defined by the number of replicates
positive, this explains why four individuals have higher average fluorescence, but only one is
considered positive. (D) In enhanced alpha-synuclein-SAA, positive seeding activity was detected
in 11 synucleinopathy and 1 control appendix, while 5 synucleinopathy and 14 control appendices
were negative for seeding activity. Mann -Whitney test was used to analyze average ThT
fluorescence, Fmax SAA positive activity. Data are presented as mean ± SEM.
Figure 3. Dysregulation of genes and pathways in synucleinopathy patients’ appendices. (A)
Volcano plot depicting differentially expressed genes in the appendix of synucleinopathy patients
(n=11) as compared to controls (n=13). The upregulated (red) and downregulated (blue) genes
with log2fold-change >2 (p-adj <0.05) are highlighted. The genes with no significant (NS) change
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are shown as grey dots. Gene Set Enrichment Analysis (GSEA) of Gene Ontology (GO) terms
identified pathways affected by the DE genes in PD appendices vs controls. (B) GO-Biological
Process, (C) GO-Cellular Components, and (D) GO-Molecular Function show activated (left) and
suppressed (right) pathways in the PD appendix. Most of the DE genes and dysregulated pathways
in synucleinopathy appendix contribute to immune responses, protein folding and cilia -related
processes.
Figure 4. Epigenetic dysregulations in synucleinopathy patients’ appendices. (A) The volcano
plot displays differential methylation between synucleinopathy appendices (n=11) and controls,
(n=13) with the x -axis showing beta value differences (synucleinopathy – control). Blue dots
represent observations that were significantly differen t in both p -value and beta value. (B) The
total number of hypomethylated and hypermethylated CpG sites exhibiting more hypomethylation
in synucleinopathy appendix as compared to controls. (C) The distribution of number of CpG sites
across various gene regions in synucleinopathy appendices compared to controls. (D) The
distribution of number of CpG sites across CpG regions in synucleinopathy appendices compared
to controls.
Figure 5. Gene Set Enrichment Analysis (GSEA) of Gene Ontology (GO) terms identified
pathways affected by the DM genes in the synucleinopathy appendices vs controls. (A)
Hypomethylated pathways mapped to GO database, (B) hypermethylated pathways mapped to GO
database. (C) Hypomethylated pathways mapped to KEGG database, (D) hypermethylated
pathways mapped to KEGG database.
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Figure 6. Protein –protein interaction network of significantly altered genes in
synucleinopathy appendix. Significant genes (p-adj. 0.05) identified from RNA -Seq and DNA
methylation analysis were analyzed using the STRING database. The plot excludes genes that lack
STRING-annotated functional connectivity. Nodes are colored according to whether the gene was
identified via RNA or DNA methylation analysis. Markov Cluster Algorithm (MCL) was used to
organize nodes, and the top statistically significant functional enrichment (i.e., lowest FDR value)
was displayed above each cluster.
Table 1. Subset of differentially expressed genes linked to synucleinopathy -associated processes
in appendix samples from synucleinopathy patients vs. controls
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Ensembl ID Gene Name Base
Mean
log2Fold
Change
SE p value p adj
ENSG00000132141.14 CCT6B 31.181 -2.0081 0.39032 2.68E-07 0.0014
ENSG00000145911.6 N4BP3 69.835 1.2763 0.29598 1.62E-05 0.0100
ENSG00000100591.8 AHSA1 866.744 1.4395 0.33509 1.74E-05 0.0100
ENSG00000110172.12 CHORDC1 3898.817 1.9982 0.47763 2.87E-05 0.0128
ENSG00000168439.16 STIP1 1651.987 1.5961 0.39216 4.70E-05 0.0169
ENSG00000144401.14 METTL21A 186.311 1.2672 0.317 6.40E-05 0.0198
ENSG00000173530.6 TNFRSF10D 272.469 1.1524 0.29374 8.73E-05 0.0227
ENSG00000213085.10 CFAP45 15.921 -2.9731 0.76333 9.82E-05 0.0239
ENSG00000204390.10 HSPA1L 77.397 1.5926 0.40962 1.01E-04 0.0239
ENSG00000117586.11 TNFSF4 59.429 -0.8860 0.22893 1.09E-04 0.0242
ENSG00000214279.13 SCART1 59.208 -1.2312 0.321 1.25E-04 0.0262
ENSG00000185507.21 IRF7 96.706 0.8967 0.23455 1.32E-04 0.0263
ENSG00000118307.19 DNAI7 40.386 -1.8829 0.49214 1.30E-04 0.0263
ENSG00000137441.8 FGFBP2 23.606 1.6575 0.4342 1.35E-04 0.0265
ENSG00000168685.15 IL7R 1761.234 1.9616 0.51572 1.43E-04 0.0275
ENSG00000004478.8 FKBP4 1658.254 1.8554 0.4877 1.42E-04 0.0275
ENSG00000143401.15 ANP32E 937.318 -0.5640 0.14873 1.49E-04 0.0285
ENSG00000157578.13 LCA5L 16.816 -1.7741 0.47723 2.01E-04 0.0308
ENSG00000155875.15 SAXO1 9.332 -2.1946 0.60949 3.17E-04 0.0389
ENSG00000108691.9 CCL2 790.439 -1.8356 0.51245 3.41E-04 0.0392
ENSG00000163468.15 CCT3 1434.118 0.8230 0.23049 0.000356 0.0399
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Table 2. Subset of differentially methylated genes linked to synucleinopathy-associated processes
in appendix samples from synucleinopathy patients vs. controls.
tpCombine Seg Chrm Seg Estimate p value p adj Relation to
Gene
Category
MIP chr12 -0.056460768 7.8464E-07 0.02640 5'UTR
H19 chr11 -0.045129478 5.1411E-12 2.2613E-06 TSS1500
GLI4 chr8 -0.040098331 1.5587E-06 0.02981 TSS1500,
Body
GAS7 chr17 -0.031342502 2.5995E-06 0.0420 TSS1500,
5'UTR
CDK16 chrX -0.030810321 1.1623E-09 2.5563E-04 TSS1500,
TSS200
TBL1X chrX -0.029706597 2.7826E-08 0.0041 TSS1500,
TSS200,
Body
ENSG00000170606.15 HSPA4 1702.360 1.1588 0.32499 3.63E-04 0.0405
ENSG00000107738.20 VSIR 516.399 0.6449 0.18304 4.26E-04 0.0444
ENSG00000251595.7 ABCA11P 28.998 -1.1861 0.33727 4.36E-04 0.0451
ENSG00000150753.12 CCT5 928.511 0.7997 0.22922 4.85E-04 0.0481
ENSG00000178927.18 CYBC1 379.918 0.7616 0.21822 4.82E-04 0.0481
ENSG00000086061.16 DNAJA1 2138.092 1.3378 0.38485 5.08E-04 0.0491
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TMC4 chr19 -0.02341605 2.9657E-06 0.0432 TSS200
EIF1AX chrX -0.011564424 1.4196E-06 0.0284 5'UTR
WBP11 chr12 -0.00582025 5.0605E-06 0.0495 TSS1500
NR4A1 chr12 -0.005543784 4.9188E-06 0.0495 Body
MRPL41 chr9 -0.005405291 4.7806E-07 0.0264 1stExon,
Body
TEX22 chr14 -0.005314138 3.9308E-07 0.0264 TSS1500
MTA1 chr14 -0.005314138 3.9308E-07 0.0264 TSS1500
SH3GLB1 chr1 -0.005202031 2.0330E-06 0.0358 TSS1500,
Body
AKR7A2 chr1 -0.005023715 4.0374E-06 0.0487 TSS1500
SLC66A1 chr1 -0.005023715 4.0374E-06 0.0487 TSS1500
ANXA5 chr4 -0.004686528 3.4229E-06 0.0470 TSS200,
5'UTR
ZMYND11 chr10 -0.004486106 6.0076E-07 0.0264 TSS1500,
TSS200,
Body
DPH3 chr3 -0.004301509 1.1084E-06 0.0284 TSS1500
OXNAD1 chr3 -0.004301509 1.1084E-06 0.0284 TSS1500
UBTF chr17 -0.003862467 2.7495E-06 0.0420 TSS1500
NAP1L1 chr12 -0.003581127 8.3028E-07 0.0264 TSS1500,
TSS200,
5'UTR
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ACBD3 chr1 -0.003069002 3.9148E-06 0.0487 5'UTR
ABCB9 chr12 -0.003039661 8.9398E-08 0.0079 TSS1500
LSM2 chr6 -0.002908889 4.2098E-06 0.0487 TSS1500,
TSS200,
5'UTR
DHX29 chr5 -0.002533829 1.0731E-06 0.0284 TSS1500
MTREX chr5 -0.002533829 1.0731E-06 0.0284 TSS1500
TRIM33 chr1 -0.002213311 1.3577E-06 0.0284 5'UTR
TOR3A chr1 -0.00137959 3.8652E-06 0.0487 TSS200,
Body
DNMT3A chr2 -1.27370184049748E-
04
4.1074E-06 0.0487 TSS1500,
5'UTR
TRNP1 chr1 -5.70366549201819E-
05
4.7327E-06 0.0495 TSS1500,
TSS200, 1st
Exon, Body
PPP2R2B chr5 0.019478798 2.3741E-06 0.0402 TSS1500,
TSS200,
5'UTR
R3HDM2 chr12 0.033485722 5.0267E-06 0.0495 5'UTR
DCUN1D1 chr3 0.071012065 1.2839E-06 0.0284 5'UTR
MEI1 chr22 0.351120112 6.7254E-07 0.0264 Body
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