Abstract

   Dystrophic neurites (also termed axonal spheroids) are found around
   amyloid deposits in Alzheimer’s disease (AD), where they impair axonal
   electrical conduction, disrupt neural circuits and correlate with AD
   severity. Despite their importance, the mechanisms underlying spheroid
   formation remain incompletely understood. To address this, we developed
   a proximity labeling approach to uncover the proteome of spheroids in
   human postmortem and mouse brains. Additionally, we established a human
   induced pluripotent stem cell (iPSC)-derived AD model enabling
   mechanistic investigation and optical electrophysiology. These
   complementary approaches revealed the subcellular molecular
   architecture of spheroids and identified abnormalities in key
   biological processes, including protein turnover, cytoskeleton dynamics
   and lipid transport. Notably, the PI3K/AKT/mTOR pathway, which
   regulates these processes, was activated in spheroids. Furthermore,
   phosphorylated mTOR levels in spheroids correlated with AD severity in
   humans. Notably, mTOR inhibition in iPSC-derived neurons and mice
   ameliorated spheroid pathology. Altogether, our study provides a
   multidisciplinary toolkit for investigating mechanisms and therapeutic
   targets for axonal pathology in neurodegeneration.

   Subject terms: Molecular neuroscience, Cellular neuroscience,
   Alzheimer's disease, Ageing
     __________________________________________________________________

   Axonal spheroids disrupt neural circuits in Alzheimer’s disease. In
   this study, using subcellular proximity labeling proteomics in human
   brain and iPSC modeling, the authors link spheroid formation to
   dysregulated mTOR, cytoskeletal and lipid transport signaling.

Main

   A major hallmark in Alzheimer’s disease (AD) is the accumulation of
   aggregated extracellular β-amyloid (Aβ) peptide deposits^[66]1.
   However, the mechanisms by which these deposits trigger neuronal
   changes and contribute to cognitive deficits remain unclear. Amyloid
   plaques are known to cause synapse loss^[67]2 and dendritic spine
   reduction in their vicinity^[68]3, but a less understood and
   potentially critical feature is the formation of axonal spheroids
   around plaques. Hundreds of axons, but not dendrites, near individual
   plaques develop enlarged spheroid-like structures (traditionally termed
   dystrophic neurites)^[69]4–[70]10. These plaque-associated axonal
   spheroids (PAASs) correlate well with AD severity^[71]4,[72]11, disrupt
   axonal electrical conduction^[73]4,[74]12,[75]13, impair neuronal
   networks^[76]4 and may contribute to cognitive decline. PAASs contain
   enlarged, enzyme-deficient endolysosomal vesicles^[77]4,[78]14–[79]16
   and autophagosomes^[80]15,[81]17. Spheroid enlargement may result from
   the accumulation of these vesicles^[82]4 and disruption of axonal
   cytoskeleton and transport^[83]16,[84]18–[85]22. Ultimately, the
   presence of axonal spheroids may further impair axonal trafficking,
   leading to downstream synaptic dysfunction and axonal
   degeneration^[86]3,[87]23–[88]25. Additionally, PAASs may contribute to
   the propagation of tau pathology through neuronal networks^[89]26.
   Thus, PAASs may represent a critical neuropathological hub, driving
   circuit disruption and proteinopathy and contributing to cognitive
   decline in AD^[90]3,[91]4,[92]12,[93]13,[94]23,[95]27.

   Axonal spheroids can form as a result of a variety of insults and are
   observed across acute neural injuries and age-related neurodegenerative
   conditions. Although they share morphological and subcellular
   cytoskeletal and organelle features, including the accumulation of
   proteins such as amyloid precursor protein (APP) and
   cathepsins^[96]14,[97]22, mechanistic differences exist given the
   diversity of pathological processes involved. In neural injury models,
   spheroid formation involves cytoskeletal disruption, membrane tension
   changes^[98]22,[99]28 and phosphatidylserine exposure, leading to glial
   phagocytosis^[100]22,[101]29. In contrast, in AD, PAASs persist for
   very long intervals without significant glial
   clearance^[102]4,[103]30–[104]32.

   Despite these observations, PAASs have not been a major focus of
   mechanistic investigations, and the cell biological processes
   underlying their formation remain poorly understood. In the present
   study, we developed a proteomics approach to investigate the molecular
   composition of PAASs, by employing proximity labeling to selectively
   isolate the subcellular proteome of PAASs in human postmortem and mouse
   brains. This analysis revealed protein turnover, cytoskeleton dynamics
   and lipid transport as key biological processes in PAASs. Additionally,
   we identified hundreds of previously unknown proteins and signaling
   pathways expressed in PAASs, some of which could play important roles
   in their formation.

   To investigate the structural dynamics, functional consequences and
   reversibility of PAASs, we established a human induced pluripotent stem
   cell (iPSC)-derived AD model that recapitulates PAAS pathology. This
   model enabled longitudinal imaging and optical electrophysiology,
   revealing patterns of spheroid growth and action potential conduction
   disruption. To further examine the mechanisms driving spheroid growth,
   we focused on the mTOR signaling pathway, identified through PAAS
   proteomics and confirmed to be expressed within PAASs in vivo. Genetic
   and pharmacological inhibition of mTOR in iPSC neurons and in mice led
   to marked reduction in PAAS pathology. As mTOR is a master regulator of
   protein turnover, lipid metabolism and axonal cytoskeletal
   remodeling^[105]33–[106]35, these findings highlight the importance of
   these biological processes in PAAS formation.

   Altogether, the integration of subcellular proteomics in postmortem
   human brain, human iPSC AD modeling and molecular manipulation of PAASs
   in human neurons and mice provides new insights into the complex cell
   biology and reversibility of axonal pathology in AD.

Results

Proximity labeling of axonal spheroids in AD human brains

   Proximity labeling is a methodology used to biotinylate proteins within
   specific cellular or subcellular compartments using genetic expression
   of localized peroxidases or biotin ligases^[107]36–[108]40, enabling
   the selective protein biotinylation, isolation and identification of
   proteomes using liquid chromatography with tandem mass spectrometry
   (LC–MS/MS)^[109]41,[110]42. Recently, this approach was adapted for
   fixed tissues by targeting subcellular compartments with horseradish
   peroxidase (HRP)-conjugated antibodies, enabling localized protein
   biotinylation^[111]43–[112]46. Leveraging these advancements, we
   devised and refined an antibody-based proximity labeling approach to
   characterize the PAAS proteome in postmortem AD human brains and 5×FAD
   mice (Fig. [113]1, Extended Data Figs. [114]1 and [115]2, Supplementary
   Figs. [116]1 and [117]2 and [118]Supplementary Movie).

Fig. 1. Proximity labeling of proteins within plaque-associated axonal
spheroids.

   [119]Fig. 1
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   a, Schematic showing axons with spheroids (red) around an amyloid
   plaque (blue). Spheroids disrupt axonal electric conduction, causing
   delays and blockages^[121]4. b, FIB/SEM image of a 5×FAD mouse brain
   showing spheroids (red) around an amyloid plaque (blue). Scale bar,
   20 μm. Related to [122]Supplementary Movie. c, Immunofluorescence
   confocal deconvolved image demonstrating that PLD3 is highly enriched
   in axonal spheroids (red, PLD3) around amyloid plaques (blue,
   thioflavinS) in postmortem AD human brain. d, Schematic of the pipeline
   for proximity labeling PAAS proteomics in postmortem brains. AD human
   or mouse brain sections were incubated with a primary antibody against
   PLD3 and an HRP-conjugated secondary antibody, followed by a
   biotinylation reaction in the presence of Biotin-XX-Tyramide and
   H[2]O[2]. e–h, Proximity labeling biotinylation of proteins within
   PAASs: human AD brains (e) and 5×FAD mouse brains (f). e,f,
   Biotinylated proteins were visualized using streptavidin–Alexa Fluor
   647. g,h, Control conditions include no-H[2]O[2] (g) or no-antibody
   labeling (h), both of which showed markedly reduced biotinylation.
   Scale bar, 5 μm. i, Streptavidin–HRP western blot showing efficient
   streptavidin bead pulldown of biotinylated proteins, including PLD3
   (protein bait) and known axonal spheroid proteins RAGC and cathepsin B.
   See also Extended Data Figs. [123]1 and [124]2 and Supplementary Figs.
   [125]1 and [126]2.

Extended Data Fig. 1. PLD3 expression and proximity labeling of axonal
spheroids versus neuronal somata.

   [127]Extended Data Fig. 1
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   A-B. Proximity labeling of PLD3 (red) in (A) axonal spheroids versus
   (B) neuronal somata. C. Proximity labeling of NeuN (green, a neuronal
   soma marker). (A-C) Scale bar 5 μm. D. No biotinylation reaction
   control shows that the streptavidin signal was eliminated. Scale bar 50
   μm. E-G. Comparison of PLD3 expression in axonal spheroids versus
   neuronal soma. Representative images of PLD3 immunofluorescence
   staining in AD postmortem brains with (E) dense amyloid plaques
   (ThioflavinS stained) and (F) sparse amyloid plaques. Inserts show
   axonal spheroid halos around amyloid plaques (yellow squares) or
   neuronal soma (blue squares). Scale bar 50 μm. G. Quantification of
   PLD3 expression in axonal spheroids versus neuronal soma/neuropil in AD
   human postmortem brains (n = 3 brains). Data are presented as mean
   values with SEM.

Extended Data Fig. 2. Super-resolution STED imaging reveals high spatial
precision of proximity labeling in AD human brain.

   [129]Extended Data Fig. 2
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   A. Imaging of beads illustrates the resolution contrast between
   confocal microscopy (250 nm) and STED microscopy (50 nm). Scale bar =
   250 nm. B-C. Representative confocal and STED images showing proximity
   labeling of axonal spheroids (magenta, anti-PLD3 labeled) in AD human
   postmortem brains. Biotinylated proteins were labeled by streptavidin
   (green). Scale bar = 2 μm. C. A line plot representative of the radius
   measurements illustrates the signals from both the secondary antibody
   channel (magenta) and the streptavidin channel (green). D. Dot plot
   depicting the radius ratio between the secondary antibody channel
   (magenta) and the streptavidin channel (green). Average radius ratio =
   141.0 nm, average ratio = 1.04, standard deviation = 0.04. The median
   value is represented by the orange line, the lower and upper edges
   corresponding to the 25th (Q1) and 75th (Q3) percentiles, respectively.
   Whiskers extend to the minima and maxima within 1.5 times the IQR from
   the lower and upper quartiles. Data points beyond the whiskers are
   plotted as individual outliers (denoted by pink circles), and are
   subsequently excluded. Each dot represents a spheroid, n = 39.

   Our approach was based on the observation that phospholipase D3 (PLD3),
   an endolysosomal protein, is highly abundant within PAASs (Fig. [131]1c
   and Extended Data Fig. [132]1e–g)^[133]4,[134]47–[135]50, specifically
   expressed in neurons^[136]4,[137]47 and absent in glial cells^[138]4.
   Although low levels of PLD3 are found in neuronal cell bodies (Extended
   Data Fig. [139]1), quantitative immunofluorescence demonstrated that
   most PLD3 originates from PAASs (Extended Data Fig. [140]1g).
   Leveraging this finding, we used PLD3 as a protein bait for proximity
   labeling proteomics of PAASs. This involved sequential incubation of
   postmortem AD human or mouse brains with a primary antibody against
   PLD3 and an HRP-conjugated secondary antibody, followed by a
   peroxidation reaction with H[2]O[2] and Biotin-XX-Tyramide (Fig.
   [141]1d). This process resulted in robust biotinylation of proteins
   within PAASs, confirmed by streptavidin labeling with minimal
   background outside axonal spheroids (Fig. [142]1e–h). To validate the
   spatial precision of proximity labeling, we employed stimulated
   emission depletion (STED) super-resolution imaging, which confirmed the
   high precision of proximity biotinylation of axonal spheroids (Extended
   Data Fig. [143]2). Additionally, to demonstrate subcellular
   specificity, we conducted parallel proximity labeling experiments using
   the neuronal nuclear and perinuclear cytoplasm marker NeuN as a protein
   bait (Extended Data Fig. [144]1c,d).

   We also optimized the protein lysis method, significantly improving
   protein extraction efficiency compared to previous studies^[145]43.
   This protocol involved increased sodium dodecyl sulfate (SDS)
   concentration to 2% in basic Tris-HCl solution (pH 8.0), which enhanced
   protein extraction by effectively de-crosslinking proteins in fixed
   postmortem tissue (Supplementary Fig. [146]2a and [147]Methods). Using
   this approach, we performed pulldown of biotinylated proteins and
   detected them via streptavidin–HRP western blotting. The analysis
   revealed a diverse array of proteins, including the baits PLD3 and NeuN
   as well as axonal spheroid proteins RAGC and cathepsin B (Fig. [148]1i
   and Supplementary Figs. [149]2b–d). Thus, the refined proximity
   labeling method provides a robust approach for isolating proteins
   enriched in axonal spheroids, enabling comprehensive proteomic
   profiling.

Proteomic analysis of plaque-associated axonal spheroids

   To uncover the proteome of axonal spheroids, samples from individuals
   with AD and unaffected controls were processed for PLD3 proximity
   labeling protein biotinylation (Fig. [150]2a and Extended Data Fig.
   [151]3). Human frontal cortex postmortem samples were obtained from 39
   individuals from the Yale Alzheimer’s Research Center (n = 8 AD and
   n = 2 control) and the Banner Sun Health Research Institute (n = 17 AD
   and n = 12 control), with detailed clinical and neuropathological data
   (Supplementary Fig. [152]1). Individuals with AD exhibited high amyloid
   plaque load, whereas controls had minimal or no plaque burden. For
   proteomics, we selected six individuals with AD (three females and
   three males) with the highest amyloid plaque burden (Supplementary Fig.
   [153]1c) and eight unaffected controls (three females and five males).
   An additional 25 AD cases (13 females and 12 males) and seven controls
   (two females and five males) were used for immunofluorescence
   validation.

Fig. 2. Proteomic analysis of plaque-associated axonal spheroids in humans
with AD and 5×FAD mice.

   [154]Fig. 2
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   a, Schematic of the technical pipeline for PAAS proteomic analysis.
   Gray matter regions with high plaque load were microdissected from
   brain sections from human AD; gray matter was also dissected from
   unaffected controls under a fluorescence stereomicroscope. b,
   Statistical pipeline used to identify PAAS proteomes in humans (related
   to Fig. 2c and Extended Data Fig. [156]1e–g). The same pipeline was
   applied to uncover PAAS proteomes in 5×FAD mice. c, Table showing
   statistical cutoffs and summary of identified proteomic hits in humans
   with AD and 5×FAD mice. The human PAAS proteome includes 821 proteins
   (all with FC > 1.95), whereas the mouse PAAS proteome includes 856
   proteins (all with FC > 1.66). d, Volcano plot showing proteins that
   passed statistical cutoffs (orange dots) in humans with AD. The top 10
   proteomic hits, with the lowest P values and highest FCs, are labeled
   by their gene names in black. Selected known PAAS proteins are
   highlighted as red dots with red gene names. Black dots among yellow
   ones represent proteins filtered out by the statistical pipeline (Fig.
   2b) (see Supplementary Table [157]1 for the full list of proteomic
   hits). c,d, Quantification was performed two-sided. See also Extended
   Data Figs. [158]3–[159]7 and Supplementary Figs. [160]3–[161]6. Ctrl,
   control.

Extended Data Fig. 3. Correlation analysis of proteomics samples in humans
and mice.

   [162]Extended Data Fig. 3
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   Correlation analysis among biological replicates of PLD3-labeled and no
   antibody-labeled proteomic samples in (A) humans and (B) mice. Pearson
   correlation coefficient R^2 of each comparison is listed in each box.

   Proteomic analysis identified 2,360 proteins through a three-step
   process (Fig. [164]2b,c). First, non-specific protein binders to beads
   were removed by comparing PLD3-labeled samples to no-antibody controls,
   using cutoffs of P < 0.05, false discovery rate (FDR) < 0.1 and fold
   change (FC) > 1.5. To ensure data stringency, we compared normalized
   total precursor intensity (NTPI) and normalized total spectra count
   (NTSC) methods (Supplementary Fig. [165]3). This analysis identified
   870 proteins (NTSC) and 965 proteins (NTPI) after applying these
   statistical cutoffs, with 849 proteins shared between the two methods,
   which were then used for downstream analysis. Second, we searched for
   glial cell–specific proteins and found only two, which were excluded
   from the dataset. Third, we aimed to exclude proteins specific to
   neuronal soma and neuropil, by comparing the proteomes of PLD3-labeled
   AD samples to unaffected controls, using P < 0.05 and FC > 1.5 or
   FC < 0.67. Given that the PLD3 labeling in controls originates from
   neuronal soma and neuropil (due to the absence of plaques), proteins
   with FC > 1.5 (98 proteins) represented those enriched in PAASs and/or
   broadly increased in AD. Proteins with FC < 0.67 (51 proteins)
   represented those specific to neuronal soma and neuropil and/or those
   decreased in AD. To increase stringency, proteins with FC < 0.67 were
   removed from the PAAS proteomic dataset (Fig. [166]2b). As a result,
   821 proteins remained, representing the PAAS proteome in AD, all
   exhibiting an FC enrichment > 1.95 (Fig. [167]2b,c, Supplementary Figs.
   [168]4–[169]6 and Supplementary Tables [170]1 and [171]2).

   For comparative analysis, parallel experiments were conducted with
   15-month-old 5×FAD mice (Extended Data Fig. [172]4). Using a similar
   proteomic strategy, we identified 856 PAAS proteins in mice (Fig.
   [173]2a–c, Extended Data Fig. [174]4a and Supplementary Table [175]1).
   All 856 proteins exhibited FC > 1.66 (Supplementary Table [176]1), with
   476 overlapping between humans with AD and 5×FAD mice (Extended Data
   Fig. [177]4b). Proteomic analyses in both humans and mice revealed
   hundreds of proteins previously unknown to be expressed in PAASs,
   alongside those already reported (Fig. [178]2d, Extended Data Fig.
   [179]4a, Supplementary Fig. [180]6 and Supplementary Table [181]2).

Extended Data Fig. 4. Proteomics analysis of PLD3-labeled PAAS proteomes in
5XFAD mice.

   [182]Extended Data Fig. 4
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   A. Volcano plot show proteins (represented by their gene names) that
   passed the statistical cutoffs (yellow dots) in 5XFAD mice. The top 10
   proteomic hits with the lowest p-value and highest fold changes are
   indicated by their gene names in black. The selected known PAAS
   proteins are labeled as green dots and their gene names in green. The
   black dots among the yellow ones represent proteins being filtered by
   the statistical cutoff as shown in Fig. [184]2b. (See Table [185]S1 for
   full list of proteomic hits). B. Venn diagram shows shared proteomics
   hits between AD humans and mice. C. Pathway enrichment analysis of PAAS
   proteome in 5XFAD mice. The Enrichment Map represents a network of
   pathways where edges connect pathways with many shared genes. Node
   color reflects the FDR of each pathway. The theme labels were curated
   based on the main pathways of each subnetwork. Subnetworks with a
   minimum of four pathways connected by edges are shown. D. IPA pathway
   analysis of the PAAS proteome in 5XFAD mice. Top 30 CNS-related
   signaling pathways are shown. The signaling pathways are summarized as
   4 modules. The alluvium plot shows different modules connect to the
   differentially expressed genes (DEGs) and the DEGs connects to the
   pathways that they are involved. E. IPA pathways related to the three
   modules with a p-value less than 0.01 are listed. Heatmaps indicate
   either the -log[10] (p-value) or the z score of each signaling pathway
   (pathways with a z score in red are predicted to be activated while
   blue ones are predicted to be inhibited). (A, E) Quantification was
   performed two-sided.

   Various controls ensured specificity, including additional proteomics
   using Lamp1 as a bait in 5×FAD mice, which detected 510 overlapping
   hits with PLD3 but also identified numerous glial-derived proteins
   (Extended Data Fig. [186]5), consistent with Lamp1 expression in glial
   cells. To confirm the robustness of proteomic hits, anti-biotin bead
   pulldown of biotinylated peptides produced results consistent with
   streptavidin bead pulldown (Extended Data Fig. [187]6). To further
   examine subcellular specificity, we used NeuN, a neuronal nuclei and
   perinuclear cytoplasm marker^[188]51, as a control bait. Unlike the
   PLD3-labeled PAAS proteome, the NeuN-labeled proteome showed distinct
   specificity to nuclei and neuronal soma (Extended Data Fig. [189]7 and
   Supplementary Table [190]1).

Extended Data Fig. 5. Comparison between anti-Lamp1 antibody labeled proteome
with the anti-PLD3 antibody labeled PAAS proteomes in 5XFAD mice.

   [191]Extended Data Fig. 5
   [192]Open in a new tab

   A-B. Proximity labeling of Lamp1 (red) in (A) 5XFAD and (B) wild type
   mice. Lamp1 (red) labeled (A) axonal spheroid halo in 5XFAD mice and
   (B) lysosomes in neuronal cell bodies. Biotinylated proteins were
   labeled by streptavidin. Scale bar 5 μm. C. Volcano plot shows proteins
   that passed the statistical cutoffs (yellow dots) in 5XFAD mice. The
   gene names of the top 10 proteomic hits with the lowest p-value and
   highest fold changes are shown in black. The selected known PAAS
   proteins are shown as dark blue dots with their gene names labeled in
   blue. Quantification was performed two-sided. (See Table [193]S1 for
   full list of proteomic hits). D. Venn diagram showing comparison of the
   anti-Lamp1 antibody labeled proteomes with the anti-PLD3 antibody
   labeled PAAS proteomes in 5XFAD mice. Selected known PAAS proteins are
   shown in blue, newly identified proteins are shown in black, glial
   marker proteins are shown in purple and dendritic marker protein is
   shown in green.

Extended Data Fig. 6. Comparison between anti-biotin beads pulldown with
streptavidin beads pulldown of anti-PLD3 antibody labeled proteomes in AD
human brains.

   [194]Extended Data Fig. 6
   [195]Open in a new tab

   A. Schematic showing pipelines for using streptavidin beads or
   anti-biotin beads to pulldown anti-PLD3 antibody labeled proteomes in
   AD human brains. For streptavidin beads, tissue sections were lysed and
   then incubated with streptavidin beads. For anti-biotin beads, protein
   lysate was digested prior to anti-biotin beads pull down. B. Comparison
   of the proteomes captured using anti-biotin beads and those captured
   with streptavidin beads. Among the total 821proteomic hits identified
   in the human PAAS proteome, 665 hits were pulldown by both the
   streptavidin beads method and the anti-biotin beads method. Selected
   known PAAS proteins (blue) and newly identified proteins (black) are
   shown in the box.

Extended Data Fig. 7. Proteomics analysis of NeuN-labeled neuronal nuclei and
perinuclear cytoplasm proteomes in mice.

   [196]Extended Data Fig. 7
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   A. The NeuN-labeled neuronal nuclei and perinuclear cytoplasm proteomes
   in wildtype C57BL/6 J mice contain 292 proteomic hits. Comparison
   between the NeuN-labeled proteome and the PLD3-labeled PAAS proteome in
   mice showed 159 proteins are shared. Among the 133 unique protein hits
   in the anti-NeuN-labeled proteome, the protein bait and neuronal soma
   marker NeuN was detected, along with many nuclear and ribosomal
   proteins. B Gene Ontology analysis shows the top ranked biological
   process terms of the anti-NeuN-labeled proteomic dataset.

Uncovering key signaling pathways in axonal spheroids

   To gain insights into the molecular mechanisms associated with axonal
   spheroid pathology, we conducted Gene Ontology (GO) annotation of
   biological process, molecular function and cellular component using the
   human PAAS proteomics dataset of 821 proteins, followed by pathway
   enrichment analysis. Results showed that proteomic hits were primarily
   associated with axons, synapses, cytoskeleton, lysosomes and proteasome
   complex (Fig. [198]3a and Supplementary Table [199]4). These findings
   reflect the axonal origin of PAASs and the accumulation of
   endolysosomal organelles, as shown by immunofluorescence and electron
   microscopy (Fig. [200]1b,c and [201]Supplementary
   Movie)^[202]4,[203]14. Many synapse-related proteins, such as the SNARE
   complex, are involved in both vesicle fusion and endolysosomal
   function. Because PAAS structures lack pre-synaptic and post-synaptic
   features ([204]Supplementary Movie), SNARE complex proteins and other
   synapse-related signatures likely indicate vesicle fusion processes
   within the endolysosomal pathway.

Fig. 3. Pathway analyses reveal proteins involved in protein turnover and
cytoskeleton as key components of PAASs.

   [205]Fig. 3
   [206]Open in a new tab

   a, Pathway enrichment analysis of the PAAS proteome in AD human brains.
   The Enrichment Map represents a network of pathways, with edges
   connecting pathways that share many genes. Node color reflects the FDR
   of each pathway. Theme labels were curated based on the main pathways
   of each subnetwork. Subnetworks with a minimum of four pathways
   connected by edges are shown. b, IPA pathway analysis of the PAAS
   proteome in humans with AD. Top-ranking CNS-related signaling pathways
   are shown. The signaling pathways are summarized as four modules. The
   alluvium plot shows color-coded modules connecting to the
   differentially expressed genes (DEGs), and the DEGs connect to the
   pathways that they are involved in. c, IPA pathways related to the
   three modules (synapse/vesicle fusion, protein turnover and
   cytoskeleton) with P < 0.01 are listed. Heatmaps indicate either the
   −log[10] (P value) or the z-score of each signaling pathway (pathways
   with a z-score in red are predicted to be activated, whereas blue ones
   are predicted to be inhibited). d, Bar chart shows representative
   proteomic hits from the signaling pathways in c. Newly identified
   proteins are shown in red; known PAAS proteins are shown in black.
   n = 6 human AD brains and n = 8 unaffected human control brains were
   analyzed. Error bars indicate s.e.m. c,d, Quantification was performed
   two-sided. e, Representative immunofluorescence confocal images of
   newly identified proteins (red) expressed in spheroids (gray) in AD
   postmortem brains. Scale bar, 5 μm. Zoom-out images are shown in
   Supplementary Fig. [207]7. Quantification was performed in n = 10 AD
   human brains. Protein expression quantifications can be found in
   Supplementary Table [208]2. See also Extended Data Fig. [209]4 and
   Supplementary Fig. [210]7. Ctrl, control.

   We performed signaling pathway analysis using the human PAAS proteome
   and found that 10 of the top 17 central nervous system (CNS)-related
   pathways involved three main modules, synapse/vesicle fusion, protein
   turnover and cytoskeleton (Fig. [211]3b), consistent with GO analysis
   findings (Fig. [212]3a). These included five pathways related to the
   cytoskeleton (for example, axonal guidance), three to synapse/vesicle
   fusion (for example, synaptogenesis) and two to protein turnover (for
   example, phagosome maturation) (Fig. [213]3b and Supplementary Table
   [214]5). Additional pathways included those related to synapse and
   vesicle fusion, such as clathrin-mediated endocytosis signaling and
   cytoskeleton growth and dynamics, such as actin cytoskeletal signaling
   and Rho family GTPase signaling (Fig. [215]3c). Pathways involved in
   protein turnover, including ubiquitination, autophagy and phagosome
   formation, were also identified. We also noted activation of the
   PI3K/AKT and mTOR pathways and inhibition of PTEN signaling (Fig.
   [216]3c), which have all been implicated in regulation of protein
   turnover and axonal growth^[217]52. Notably, subsets of proteomic hits
   from these pathways showed increased expression in humans with AD
   compared to controls (Fig. [218]3d).

   To confirm the expression of proteomic hits in PAASs, we validated
   selected proteins from various pathways using high-resolution
   immunofluorescence confocal microscopy. These included proteins linked
   to synaptogenesis, vesicle fusion and calcium signaling (for example,
   SYT11 and CAMK2A) and cytoskeleton dynamics (for example, SPTBN1) (Fig.
   [219]3e, Supplementary Fig. [220]7 and Supplementary Table [221]2). A
   complete list of validated proteins is provided in Supplementary Fig.
   [222]6 and Supplementary Table [223]2. For immunofluorescence
   validation, we used SMI312 or PLD3 to visualize PAAS structures.
   SMI312, a neurofilament and pan-axonal marker, typically highlights
   axonal morphology but also accumulates in PAASs under AD conditions,
   reflecting cytoskeletal abnormalities. SMI312 is widely validated as a
   PAAS marker in pathological conditions^[224]15,[225]16 and is
   particularly useful for co-localization studies with other antibodies.
   However, SMI312 is expressed in only a subset of spheroids^[226]14.
   Similarly, newly validated proteins from our proteomic dataset
   exhibited heterogeneous expression levels. This variability in protein
   expression within spheroids suggests a potential mechanistic sequence
   of events occurring at different stages of spheroid formation and
   growth.

   We also conducted parallel PAAS proteomics analysis in 5×FAD mice.
   Similar to the human PAAS proteome, GO terms related to axon,
   cytoskeleton, SNARE binding, lysosome and endosome transport were
   identified (Extended Data Fig. [227]4c). Additionally, signaling
   pathways associated with synapse/vesicle fusion, protein turnover and
   cytoskeleton dynamics were captured in the 5×FAD mouse PAAS proteome
   (Extended Data Fig. [228]4d,e).

Lipid transport signaling is markedly upregulated in axonal spheroids

   To investigate aberrant signaling in PLD3-labeled AD brains compared to
   controls, we performed gene set enrichment analysis (GSEA) (Fig.
   [229]4a and Supplementary Table [230]6). GSEA revealed significant
   upregulation of lipid transport–related biological processes (Fig.
   [231]4a,b). Top-ranked proteins associated with these processes
   included ATP8A1, C3, APOE, ATG9A, ATP8A2, TMEM30A, HEXB and HDLBP (Fig.
   [232]4c), all of which were identified in the PAAS proteome and
   increased in AD (Fig. [233]4d, related to Fig. [234]2b and
   Supplementary Fig. [235]6). Conversely, GSEA showed downregulation of
   ribosome, translation and RNA metabolism in PLD3-labeled AD brains
   compared to controls (Fig. [236]4a). Because PLD3-labeled signals in
   unaffected brains are derived from neuronal soma and neuropil, the
   downregulated processes in unaffected controls likely correspond to
   protein functions specific to these subcellular compartments.

Fig. 4. Proteins involved in lipid transport are upregulated in PAASs.

   [237]Fig. 4
   [238]Open in a new tab

   a, GSEA was performed to compare PLD3-labeled proteins between humans
   with AD and unaffected controls. Pathway enrichment analysis was
   performed to cluster GSEA nodes. Each node represents a biological
   process or cellular component. The name of each cluster was curated
   based on the main GSEA biological processes and cellular components
   within each cluster. See also Supplementary Table [239]6. b, Detailed
   information on the lipid transport cluster. The biological process or
   cellular component of each node is listed. c, The eight top-ranked
   proteomic hits involved in the lipid transport cluster. The bar chart
   shows the FC and FDR of these hits by comparing PLD3-labeled humans
   with AD versus unaffected controls. d, Venn diagram showing that the
   eight top-ranked lipid transport–related proteins are shared between
   the human PAAS proteomes (821 proteins) and the AD upregulated proteins
   (98 proteins). A total of 75 proteins are shared between these two
   datasets. e,f, Representative zoomed-out (e) and zoomed-in (f)
   immunofluorescence confocal images of the top-ranked lipid-related
   proteomic hits in AD human brain, including C3, APOE, HDLBP, HEXB and
   TMEM30A. Scale bar, 5 μm. Zoomed-out images of all the proteins are
   shown in Extended Data Fig. [240]8. Quantification was performed in
   n = 3 AD human brains. Protein expression quantifications can be found
   in Supplementary Table [241]2. g, Representative immunofluorescence
   confocal images showing the anti-co-localized distribution of HDLBP
   (red) and the pan-axonal marker SMI312 (gray) within thickened axons in
   the AD human postmortem brain (n = 3). Scale bar, 5 μm. Ctrl, control.

   To validate the enrichment of top-ranked lipid-related proteomic hits
   in PAASs, including APOE, HDLBP, C3, HEXB and TMEM30A, we performed
   immunofluorescence confocal imaging (Fig. [242]4e,f and Extended Data
   Fig. [243]8a). Notably, APOE, the strongest genetic risk factor for AD
   and a lipid transporter^[244]53, was among the top hits. We observed
   varying levels of expression of these proteins in axonal spheroids in
   AD human brains (Fig. [245]4e,f, Extended Data Fig. [246]8a and
   Supplementary Table [247]2). Complement C3 (C3), APOE and high-density
   lipid binding protein (HDLBP) exhibited the highest expression in
   axonal spheroids and aberrant axons around amyloid plaques, with much
   lower expression in axons away from plaques (Fig. [248]4e, Extended
   Data Fig. [249]8a and Supplementary Table [250]2). These proteins were
   also detected in cell bodies and in neuropil and plaque regions,
   aligning with their known distribution patterns (Extended Data Fig.
   [251]8a and Supplementary Table [252]2). Notably, HDLBP exhibited a
   distinct pattern of segregation within a subset of thickened axonal
   segments where the pan-axonal marker SMI312 was absent (Fig. [253]4g),
   suggesting that lipid metabolism dysregulation may precede spheroid
   enlargement. Regarding HEXB, which is primarily expressed in microglia
   in mice^[254]54, we found it expressed in PAASs and neuronal cell
   bodies in human brains (Extended Data Fig. [255]8b), consistent with
   human single-cell transcriptional profiles^[256]55.

Extended Data Fig. 8. Lipid transport-related proteins are expressed in
axonal spheroids around amyloid plaques in AD human postmortem brains.

   [257]Extended Data Fig. 8
   [258]Open in a new tab

   A. Representative immunofluorescence confocal images of the top-ranked
   lipid-related proteomic hits, including APOE, HDLBP, C3, HEXB and
   TMEM30A in AD humans. Lipid transport-related proteins are shown in
   red. Neurofilament marker SMI312 (grey) indicates the neuronal
   branches, and axonal spheroid structures around amyloid plaques
   (ThioflavinS, blue). Scale bar = 5 μm. Quantification was performed in
   n = 3 AD human brains. Protein expression quantifications can be found
   in Table [259]S2. B. Immunofluorescence confocal image shows HEXB
   (grey) expressed in neuronal cell bodies (NeuN, green) and axonal
   spheroids (SMI312, green) in AD human postmortem brain (n = 3). Two
   different HEXB antibodies were used for validation. Scale bar = 5 μm.

mTOR signaling in axonal spheroids

   The PAAS proteomics analysis highlighted the activation of the
   PI3K/AKT/mTOR axis within axonal spheroids (Fig. [260]3c and Extended
   Data Fig. [261]4e). This pathway is a master regulator of mRNA
   translation, metabolism and protein turnover^[262]35,[263]52.
   Consistent with these roles, our proteomic analysis identified protein
   turnover, lipid metabolism and axonal cytoskeleton dynamics as
   prominent signatures (Figs. [264]3 and [265]4 and Extended Data Fig.
   [266]4d,e)^[267]33–[268]35. Key proteins in the PI3K/AKT/mTOR axis were
   selected for validation. Among these, mTOR, RAGA (RRAGA), RAGC (RRAGC),
   LAMTOR1 and AKT1 were detected in the PAAS proteomes of humans and/or
   mice, whereas PIK3R4, RHEB and RAPTOR were not (Supplementary Fig.
   [269]6 and Supplementary Tables [270]1 and [271]2). Immunofluorescence
   staining confirmed the presence of all selected proteins in axonal
   spheroids in both postmortem AD human brains and 5×FAD mice (Fig.
   [272]5a). Proteins detected in the proteomes showed moderate to high
   immunofluorescence signals in PAASs, whereas those that were not
   detected exhibited moderate to low expression (Fig. [273]5a and
   Supplementary Table [274]2). Notably, phosphorylated-mTOR-S2448, a
   marker of mTOR activation, was expressed in axonal spheroids in AD
   human brains but not in unaffected controls (Fig. [275]5b–d). This
   finding suggests that phosphorylated-mTOR-S2448 may serve as a
   potential marker for disease progression. Overall, these results
   underscore the activation and involvement of the PI3K/AKT/mTOR axis in
   axonal spheroids in AD.

Fig. 5. mTOR signaling is expressed in axonal spheroids and is associated
with Alzheimer’s pathology.

   [276]Fig. 5
   [277]Open in a new tab

   a, Immunofluorescence confocal imaging validation of selected proteomic
   hits and the related proteins in the PI3K/AKT/mTOR axis reveals that
   signaling molecules of this axis are expressed in PAASs in both humans
   with AD and 5×FAD mice. PAASs were labeled using traditional markers,
   including neurofilament SMI312, cathepsin B (CatB), cathepsin D (CatD)
   or Lamp1. PAASs are outlined in yellow. Scale bar, 5 μm. Protein
   expression quantification results can be found in Supplementary Table
   [278]2. b, Phosphorylated-mTOR-S2448 (red) is highly enriched within
   PAASs (gray, SMI312) around amyloid plaques (blue, thioflavinS) in
   advanced AD. Scale bar, 5 μm. c, Quantification of the mean
   fluorescence intensity levels of p-mTOR-S2448 within axonal spheroid
   halos normalized to background fluorescence, comparing humans with AD
   (n = 13 brains) and unaffected controls (n = 8 brains). Mann–Whitney
   test, two-tailed, ****P < 0.0001. Black dashed line indicates the
   median. d, Receiver operating characteristic (ROC) curve demonstrates
   that the p-mTOR-S2448 level in PAASs significantly distinguishes AD
   brains from unaffected controls. Area under the ROC curve = 0.962,
   standard error = 0.038, 95% confidence interval: 0.888–1.000,
   P = 0.0005. Quantification was performed two-sided. Ctrl, control;
   ThioS, thioflavin S.

Human iPSC modeling replicates axonal spheroid pathology

   To establish a comprehensive strategy for investigating selected
   proteomic hits and their roles in spheroid formation, we developed a
   long-term human iPSC-derived neuron and astrocyte co-culture AD
   model^[279]56 (Fig. [280]6a,b and Extended Data Fig. [281]9a–d). A
   similar approach was recently shown to replicate axonal spheroid
   formation with exogenous aggregated Aβ1–42 (ref. ^[282]57). We
   simplified the induction protocol using the NGN2-induced glutamatergic
   neuron method^[283]56, making it more accessible for most laboratories.
   Increasing the overall neuronal density enhanced the similarity to
   axonal spheroid halos observed around amyloid plaques in the human
   brain. Our optimized model generated thioflavin S–positive amyloid
   deposits surrounded by abundant axonal spheroids (Fig. [284]6b,
   Extended Data Figs. [285]9e,f and [286]10a–c and Supplementary Fig.
   [287]8a). These spheroids accumulated lysosomes and autophagosomes
   (Fig. [288]6b,c) and expressed phosphorylated Tau S235, S396 and S404
   (Extended Data Fig. [289]9g), closely resembling human axonal
   spheroids^[290]4,[291]58.

Fig. 6. A human iPSC-derived AD model demonstrates that mTOR signaling
inhibition reduces PAAS pathology.

   [292]Fig. 6
   [293]Open in a new tab

   a, Workflow of the human iPSC-derived AD model. b, Image showing axonal
   spheroids (SMI312, gray) around amyloid deposits (thioflavinS, blue)
   and expressing ATG9A (red). c, Time-lapse imaging shows a spheroid
   forming (arrowhead) from a neurite (AAV9-hSyn-mCherry labeled) near Aβ
   deposits (gray) and enlarging over time. Lysosomes (AAV2-CMV-LAMP1-GFP
   labeled) accumulate within spheroids. d–h, Neuronal GCaMP8f imaging in
   the human iPSC AD model. d, Images of CAMKII-GCaMP8f-labeled neuronal
   processes with (upper) or without (lower) axonal spheroids and
   representative traces of calcium dynamics. y axis indicates ΔF/F, and
   dotted black lines indicate the calcium rise slope. Quantification of
   calcium rise time (e) and calcium rise speed (f). Each dot represents a
   neuronal process from three independent experiments (two-tailed
   Mann–Whitney test). g, Images showing that calcium decay time is slower
   in spheroids (pink asterisk) than in neuronal processes (blue
   asterisks). h, Quantification of calcium decay time in neuronal soma
   (blue), processes with (light pink) or without (light blue) spheroids
   and spheroids (pink). Each dot represents a neuronal process from three
   independent experiments (one-way ANOVA). i, mTOR signaling in
   iPSC-derived axonal spheroids (SMI312). j, Western blot showing that
   Torin1 treatment reduces mTOR downstream effectors phosphorylated
   4E-BP1 and phosphorylated p70 S6K, whereas their total protein levels
   remain unchanged. k–r, Torin1 reduced axonal spheroids (SMI312) around
   Aβ deposits (thioflavin S). l–p, Pre-Aβ administration Torin1 treatment
   quantification: l, axon with spheroid percentage (n = 3 in each group).
   Paired t-test two-tailed, P = 0.005. m, spheroid size (paired t-test
   two-tailed, P = 0.013, n = 4 per group). Dots represent experiments
   (20–30 ROIs). n, Axon number around plaques in each ROI (Torin1 n = 56;
   vehicle n = 55; unpaired t-test two-tailed, P = 0.880). o, Soma size.
   Dots represent neuronal somata (Torin1 n = 298, vehicle n = 316.
   Unpaired t-test two-tailed, P = 0.927; related to Extended Data Fig.
   [294]8i). p, Plaque size. Dots represent amyloid plaques (Torin1
   n = 201, vehicle n = 253. Unpaired t-test two-tailed, P = 0.419). q,r,
   Post-Aβ administration Torin1 treatment (related to Extended Data Fig.
   [295]10). Spheroid number normalized to axon density (q) and spheroid
   size (r) (Mann–Whitney test, two-tailed, n = 4 per group). Scale bar,
   5 μm, except scale bar, 10 μm in g. e,f,h,l–r, Data presented as mean
   values ± s.e.m. See also Extended Data Figs. [296]9 and [297]10 and
   Supplementary Fig. [298]8. NS, not significant; ThioS, thioflavin S.

Extended Data Fig. 9. Characterization of the human iPSC-derived
neuron-astrocyte coculture AD model.

   [299]Extended Data Fig. 9
   [300]Open in a new tab

   A. Immunofluorescence confocal deconvolved image shows iPSC-derived
   human neurons (neurofilament H (NFH) labeled) robustly expressing pre-
   and post-synaptic markers (Synapsin1/2 and PSD95) at day 150 of
   coculture. Scale bar 2.5 μm. B-C. Immunofluorescence confocal image
   shows neuronal cell bodies and dendritic processes (MAP2 labeled), as
   well as axonal processes (SMI312 labeled) of iPSC-derived human
   neurons. (B) A low-zoom field of view (FOV). Scale bar 50 μm. (C) Two
   high-zoom FOVs showing dendritic and axonal processes. Scale bar 5 μm.
   D. Immunofluorescence confocal image shows the presence of both neurons
   (grey, SMI312) and astrocytes (red, S100b) in the coculture. Scale bar
   50 μm. E. Immunofluorescence confocal images show 6e10 positive (grey)
   and ThioflavinS positive (blue) amyloid beta deposits formed in human
   iPSC-derived AD model following treatment with amyloid beta 1-42
   peptides. Axonal processes were labeled with neurofilament (NFH, red).
   Scale bar 5 μm. F. Immunofluorescence confocal image shows axonal
   processes formed spheroids (NFH, red) around amyloid plaque deposit
   (ThioflavinS, blue). Scale bar 5 μm. G. Immunofluorescence confocal
   deconvolved images show phosphorylated Tau S235, S396 and S404 (red)
   expression in PAAS derived from human neurons (grey, SMI312). Zoom out
   images were maximum projected, while the zoom in images show a single
   plane. Scale bar 5 μm. H-I. Immunofluorescence confocal deconvolved
   images of AAV2-CB7-GFP infected (H) human neurons with abundant axonal
   spheroids (green, anti-GFP staining), co-stained with the axonal
   spheroid marker SMI312 (grey); (I) cell bodies of human neurons, as
   revealed by both anti-GFP (green) and anti-NeuN (grey) staining,
   related to Fig. [301]6o. Scale bar (H) 5 μm and (I) 50 μm.

Extended Data Fig. 10. High throughput automated quantification of axonal
spheroids, axons and amyloid plaques in human iPSC-derived AD model.

   [302]Extended Data Fig. 10
   [303]Open in a new tab

   A. Schematic showing the workflow of immunofluorescence labeling of
   axonal spheroids, axons and amyloid plaques in human iPSC-derived AD
   model, followed by confocal imaging and machine learning-based image
   analysis and quantification. B-C. Zoom in (B) and zoom out (C) images
   of immunofluorescence confocal imaging showing SMI312 antibody labeled
   axonal spheroids and axons (white), ThioflavinS labeled amyloid plaque
   (blue). Objects of axonal spheroids (red), axons (yellow) and amyloid
   plaques (purple) were generated according to the raw images after image
   annotation and analysis. Scale bars = 100 μm. D-E. Quantification
   showing (D) axon and (E) amyloid plaque volume (related to the
   experiment in Figs. [304]6q and [305]6r). Mann Whitney test
   (two-tailed) was used for all the statistical analysis. Data are
   presented as mean values +/- SEM.

   This culture system enabled longitudinal structural and functional
   imaging, providing insights into the dynamics and consequences of
   spheroid pathology. Using reporter adeno-associated viruses (AAVs) to
   label neurons and lysosomes, we tracked spheroid formation after Aβ1–42
   administration. Confocal microscopy of individual axons revealed
   gradual spheroid formation and lysosomal accumulation starting on day
   1, with spheroids increasing in size over a 7-day observation period
   (Fig. [306]6c).

   We also investigated the functional repercussions of spheroid formation
   in this human iPSC-derived model. Using calcium imaging with the
   reporter GCaMP8f, we measured Ca^2+ rise times in axonal segments on
   both sides of axonal spheroids after electrical stimulation. Axonal
   segments with spheroids showed a significantly reduced calcium rise
   slope compared to those without spheroids (Fig. [307]6d–f), consistent
   with impaired action potential conduction across spheroids, as seen in
   our earlier in vivo findings in 5×FAD mice^[308]4. Additionally, axon
   segments with spheroids exhibited prolonged calcium decay times
   compared to normal processes and somata, indicating disrupted calcium
   homeostasis within spheroids (Fig. [309]6g,h).

mTOR inhibition reduces spheroid pathology in human neurons

   We investigated the role of PI3K/AKT/mTOR signaling in axonal spheroid
   development and enlargement using the human iPSC-derived AD model.
   Consistent with findings in postmortem human brains (Fig. [310]5), we
   detected expression of proteins associated with the PI3K/AKT/mTOR
   pathway localized within axonal spheroids (Fig. [311]6i and
   Supplementary Fig. [312]8).

   To evaluate the impact of mTOR inhibition, we treated 3-month-old
   iPSC-derived neuron and astrocyte co-cultures with Torin1, an inhibitor
   of both mTORC1 and mTORC2 (refs. ^[313]59,[314]60). A 7-day treatment
   with Torin1 significantly suppressed mTOR signaling, as evidenced by
   reduced phosphorylation of downstream effectors p-p70 S6K (Thr 389) and
   p-4E BP1 (Thr 37/46), without affecting total protein levels (Fig.
   [315]6j and Supplementary Fig. [316]9). To assess the effects of Torin1
   on spheroid formation and reversal, cultures were treated either before
   or after Aβ exposure. Pre-treatment with Torin1 before Aβ substantially
   decreased both the number and size of spheroids (Fig. [317]6k–p).
   Post-treatment with Torin1 after Aβ exposure reduced the number of
   spheroids but did not affect their size (Fig. [318]6q,r and Extended
   Data Fig. [319]10a–c). Notably, these effects were not due to axonal
   loss (Fig. [320]6n and Extended Data Fig. [321]10d), changes in
   neuronal density or amyloid plaque size (Fig. [322]6o,p and Extended
   Data Figs. [323]9h and [324]10e). These results indicate that mTOR
   signaling is critical for amyloid-induced spheroid formation and
   suggest that targeting mTOR could be a promising approach for both
   preventing and reversing spheroid pathology.

Amelioration of spheroid pathology in 5×FAD mice

   To investigate the role of mTOR signaling in axonal spheroid pathology
   in vivo, we employed a viral-mediated Cre/lox-based approach to induce
   Mtor knockout in 5×FAD mice (Fig. [325]7a–c and Supplementary Fig.
   [326]1a–d). Using heterozygous Mtor-floxed 5×FAD mice^[327]61 and
   AAV9-hsyn-cre-2a-tdTomato, we achieved partial loss of mTOR in infected
   neurons. Sparse neuronal infection enabled clear visualization of
   individual spheroids (Fig. [328]7d,e), showing a significant reduction
   in spheroid size after heterozygous Mtor knockout (Fig. [329]7f,g).

Fig. 7. mTOR signaling inhibition reduces axonal spheroid pathology in vivo.

   [330]Fig. 7
   [331]Open in a new tab

   a, Schematic of neuronal-specific conditional knockout of Mtor in
   heterozygous floxed mice. b,c, Images showing neuronal-specific
   Cre-mediated Mtor knockout: homozygous (b) and heterozygous (c), using
   AAV9-hSyn-Cre-2A-tdTomato or AAV PHPeB-hSyn-Cre-EGFP in Mtor-floxed
   mice, respectively. b, mTOR expression (gray) was absent in
   Cre-expressing neurons compared to adjacent NeuN-labeled neurons
   without Cre expression. c, mTOR expression was reduced in
   Cre-expressing neurons compared to neurons without Cre expression.
   Scale bar, 5 μm. d, Experimental design to study mTOR knockout effects
   on individual spheroids. e, Images showing AAV9-hSyn-Cre-2A-tdTomato
   sparsely labeling individual spheroids (red) within a spheroid halo
   (Lamp1, gray). f, Quantification of spheroid size. Dots represent
   animals (mTOR-flox-AD n = 5, 5×FAD n = 4. Unpaired t-test, two-tailed,
   P = 0.027). g, Using the same data in f, comparison of spheroid size
   distribution and visualization using a quantile–quantile (Q–Q) plot.
   Dashed lines indicate spheroid area at 10 µm^2. 5×FAD mice have
   significantly more large spheroids (area > 10 µm^2) compared to
   mTOR-KO-AD (two-sample test for equality of proportions with continuity
   correction, two-tailed, P = 0.0004). h, Experimental design to assess
   the effect of Mtor knockout on spheroid halo size. i, Quantification of
   spheroid halo size. Dots represent animals (n = 3; unpaired t-test,
   two-tailed, P = 0.041). j, Quantified by axonal spheroid halos
   (knockout group n = 66 and control group n = 109. Unpaired t-test,
   two-tailed, P < 0.0001). k, Quantification of neuronal soma size. Dots
   represent animals (n = 3). Unpaired t-test, two-tailed, P = 0.90. l–o,
   Investigation of mTOR heterozygous knockout downstream signaling
   effectors. Immunofluorescence intensity of TFEB (l), LC3B (m), P-p70S6K
   Thr389 (n) and p70S6K (o). Littermates and sex were paired in l–o,
   paired t-test. Dots represent animals (n = 3 in each group). p,
   RNAscope in 5×FAD mice cortices showing mRNA species (poly(A) probe,
   magenta) present in spheroids (NHS ester-labeled, yellow, and DAPI
   negative). NHS ester (yellow) labels the spheroid halo and amyloid
   plaques. Nuclei are labeled with DAPI (blue). Scale bar, 5 µm. q,
   Quantification of poly(A) probe fluorescence intensity versus negative
   control probe within spheroids in cortices of 5×FAD mice (n = 3).
   Unpaired t-test, parametric, two-tailed, P = 0.001. r, Representative
   images showing puromycin labeling. Scale bar, 5 µm. s, Quantification
   of puromycin fluorescence intensity in axonal spheroids of 5×FAD mice
   (n = 3). Unpaired t-test, parametric, two-tailed, P = 0.028. j,q,s,
   Data are presented as mean values ± s.e.m. See also Supplementary Figs.
   [332]10–[333]12. mo, months; NS, not significant.

   To evaluate the overall impact on spheroid size and number, we measured
   the axonal spheroid halo size around individual amyloid plaques. We
   infected Mtor-floxed 5×FAD mice with AAV-PHP.eB-hSyn-Cre-GFP virus to
   achieve dense neuronal infection, inducing widespread Mtor heterozygous
   knockout in neurons (Fig. [334]7h and Supplementary Fig. [335]10b,d,e).
   This intervention significantly reduced the axonal spheroid halo size
   around plaques without affecting amyloid plaque size (Fig. [336]7i,j
   and Supplementary Fig. [337]10e–h). Notably, despite the role of mTOR
   in cell growth and maturation^[338]35,[339]59, heterozygous Mtor
   knockout did not change the size of neuronal cell bodies (Fig. [340]7k
   and Supplementary Fig. [341]10f). These findings in vivo, consistent
   with the results from human iPSC-derived neurons, underscore the
   potential of targeting PI3K/AKT/mTOR signaling for mitigating axonal
   spheroid pathology in AD.

   Signaling pathways involved in lysosome biogenesis and autophagy likely
   contribute to the accumulation of aberrant endolysosomes in spheroids.
   Additionally, local mRNA translation, which has been shown to modulate
   axonal outgrowth, may play a role in spheroid
   formation^[342]62,[343]63. Considering the known effects of mTOR on
   lysosome biogenesis, autophagy and local mRNA
   translation^[344]35,[345]52, we investigated related downstream
   molecules. Using AAV-PHPeB-hSyn-Cre, we achieved extensive neuronal
   infection in mTOR heterozygous floxed 5×FAD mice, enabling widespread
   mTOR heterozygous knockout in neurons (Fig. [346]7a–c,h).
   Immunofluorescence confocal imaging assessed expression levels of TFEB
   (lysosomal biogenesis transcription factor), p-p70S6K (regulator of
   local protein synthesis) and LC3B (autophagy marker) in neuronal
   somata. Automated quantitative analysis compared mTOR heterozygous
   knockout mice to controls (Fig. [347]7l–o). Results showed increased
   TFEB and LC3B expression (Fig. [348]7l,m), indicating enhanced
   lysosomal biogenesis and autophagy. Additionally, we observed decreased
   p-p70S6K (Fig. [349]7n,o), which may be associated with reduced local
   mRNA translation^[350]52.

   We investigated whether local mRNA translation occurs in axonal
   spheroids. Using RNAscope in 5×FAD mice, we probed for mRNA species in
   axonal spheroids with a poly(A) tail probe and compared it to a
   scrambled control probe (Fig. [351]7p and Supplementary Fig. [352]11a).
   The poly(A) probe showed signal localization within axonal spheroids,
   whereas the control probe did not, confirming the presence of mRNA in
   these structures (Fig. [353]7q and Supplementary Fig. [354]11b–d). To
   examine local mRNA translation, we performed an in vivo puromycylation
   assay in 5×FAD mice (Fig. [355]7r and Supplementary Fig. [356]12a).
   Nascent proteins labeled by puromycin were detected in axonal
   spheroids, and treatment with the protein translation inhibitor
   anisomycin reduced the degree of labeling (Fig. [357]7s and
   Supplementary Fig. [358]12a–c), indicating that local mRNA translation
   occurs within spheroids. To test whether mTOR can regulate nascent
   protein production in spheroids, we applied both pharmacological and
   genetic approaches. Treatment with Torin1 to inhibit mTOR in 5×FAD mice
   did not alter the puromycin signal. Additionally, we used mTOR-floxed
   mice and a PHPeB-hSyn-Cre virus to genetically knock out mTOR in
   neurons. Neither the heterozygous nor homozygous mTOR deletion
   significantly affected the puromycin signal (Fig. [359]7a–c and
   Supplementary Figs. [360]10a–d and [361]12d–f). These results indicate
   that, under our experimental conditions (Supplementary Fig.
   [362]12d–f), mTOR does not appear to control local protein translation
   within axonal spheroids. These experiments indicate that the reduction
   in axonal spheroid size and number observed after mTOR inhibition is
   likely due to its enhancement of lysosomal biogenesis and autophagy
   rather than modulation of local protein translation in spheroids.

Discussion

   Plaque-associated axonal spheroids, also known as dystrophic neurites,
   have been recognized as a hallmark of AD for over a
   century^[363]10,[364]11,[365]14,[366]64,[367]65, but their molecular
   composition and the mechanisms driving their progression remain largely
   unexplored due to methodological limitations. In the present study, we
   implemented a comprehensive approach to investigate the molecular and
   cellular mechanisms of PAAS formation. We developed a subcellular
   proximity labeling proteomics method for postmortem human and mouse
   brains^[368]43, enabling detailed analysis of the protein composition
   and signaling pathways operating within PAASs (Fig. [369]8,
   Supplementary Fig. [370]6 and Supplementary Table [371]2).
   Bioinformatics analysis and high-resolution confocal imaging identified
   hundreds of proteins and pathways newly associated with PAASs,
   including lipid transport, protein turnover and cytoskeletal dynamics,
   with the PI3K/AKT/mTOR pathway emerging as a key regulator of these
   biological processes in PAASs. To explore the functional implications
   of these findings, we implemented an optimized human iPSC-derived AD
   model^[372]57 that replicates amyloid plaque and PAAS formation.
   Pharmacological and genetic inhibition of mTOR signaling in this model
   and in AD-like mice significantly reduced PAAS pathology. Altogether,
   our study reveals the molecular architecture and functional impact of
   PAASs in human neurons and implicates the PI3K/AKT/mTOR axis as a key
   signaling pathway in PAAS formation and growth. It also suggests new
   therapeutic targets for mitigating axonal pathology independently of
   amyloid removal.

Fig. 8. Schematic of the molecular architecture of plaque-associated axonal
spheroids.

   [373]Fig. 8
   [374]Open in a new tab

   Proximity labeling proteomics reveals proteins associated with various
   subcellular organelles, the ubiquitin–proteosome system and
   cytoskeleton. These proteins and their signaling pathways are linked to
   biological functions, including protein turnover and vesicle fusion
   (green box); cytoskeletal dynamics (yellow box); lipid localization and
   transport (red box); and others (gray box). Highlighted here are
   selected newly identified and validated proteins, alongside those
   previously known to be enriched in PAASs, such as lysosomal proteins
   LAMP1 (ref. ^[375]4), cathepsin B and D^[376]14, RAGC^[377]14 and PLD3
   (refs. ^[378]47,[379]48); autophagosome protein ATG9A^[380]112;
   endoplasmic reticulum proteins RTN3 (ref. ^[381]112) and RTN1 (ref.
   ^[382]113); cytoskeletal neurofilament protein^[383]114; microtubule
   protein TUBB3 (ref. ^[384]20); synaptic proteins synaptophysin^[385]5
   and VAMP2 (ref. ^[386]14); as well as APP^[387]31, Tau (MAPT)^[388]26
   and ubiquitin^[389]71,[390]112 (Supplementary Table [391]2).

   Proximity labeling proteomics with subcellular resolution overcame the
   cellular and subcellular specificity limitations of conventional tissue
   proteomics, including those using micro-dissected amyloid
   plaques^[392]66–[393]68. Using an antibody-based biotinylation
   method^[394]43,[395]44, we tagged proteins in axonal spheroids without
   requiring exogenous peroxidase or biotin ligase
   overexpression^[396]36,[397]37,[398]41, enabling comparative proteomics
   from widely available postmortem tissues. PLD3 was chosen as the
   antibody bait due to its high enrichment in PAASs of both humans and
   mice^[399]47,[400]48 and its neuron-predominant
   expression^[401]4,[402]47, minimizing contamination from other cell
   types. Comparison of PLD3-labeled and Lamp1-labeled proteomes in 5×FAD
   mice confirmed that the PLD3-labeled proteome is highly specific for
   neuronal and axonal structures (Extended Data Fig. [403]5).

   Using this proteomic strategy, we identified numerous proteins enriched
   in PAASs, including previously unknown ones, alongside those already
   associated with these structures (Fig. [404]8, Supplementary Fig.
   [405]6 and Supplementary Tables [406]1 and [407]2). Proteomic analysis
   in humans with AD revealed three key biological processes likely
   involved in PAAS formation and growth (Figs. [408]3 and [409]4). (1)
   Proteolysis Dysfunction: This was indicated by the accumulation of
   proteins related to endocytosis, phagosome, proteosome,
   ubiquitin-mediated proteolysis and lysosome acidification (Figs.
   [410]3, [411]5 and [412]8 and Supplementary Table [413]2). Previous
   studies demonstrated that accumulation of enlarged protease-deficient
   lysosomes and autophagosomes within PAASs^[414]14 mediates spheroid
   growth^[415]4, highlighting the critical role of impaired lysosomal
   function. Some of the identified proteins are also expressed in
   synapses, raising the possibility that PAASs may originate from
   pre-synaptic structures, although electron microscopy did not reveal
   pre-synaptic or post-synaptic features in PAASs ([416]Supplementary
   Movie). (2) Cytoskeletal Dysregulation: Activated signaling pathways,
   such as actin cytoskeletal signaling, RAC signaling and actin
   nucleation by the ARP–WASP complex, were enriched within PAASs, whereas
   pathways such as RHOGDI signaling, which regulates Rho family GTPase,
   were inhibited (Fig. [417]3c and Extended Data Fig.
   [418]4e)^[419]69,[420]70. These findings suggest that ongoing
   cytoskeletal reorganization and plasticity within PAASs play a key role
   their formation and enlargement. Moreover, these cytoskeletal changes
   may disrupt retrograde and anterograde axonal cargo transport, leading
   to accumulation of endolysosomal vesicles^[421]18,[422]28,[423]71 and
   further spheroid expansion. (3) Lipid Transport and Metabolism:
   Lipid-related signaling was highly activated in PAASs (Fig. [424]4a–d),
   with proteins involved in lipid transport and metabolisms, such as
   APOE, HDLBP and C3, prominently expressed in PAASs and aberrant axons
   (Fig. [425]4b–g and Extended Data Fig. [426]8a). Among these, APOE, the
   most significant AD risk gene, acts as a lipid carrier^[427]53.
   TMEM30A, ATP8A1 and ATP8A2 (Fig. [428]4c,e), which form the P4–ATPase
   complex, regulate asymmetric membrane lipid distribution, membrane
   stability and vesicle-mediated protein transport^[429]72. These
   proteins are likely related to the massive accumulation of
   endolysosomal vesicles within PAASs, requiring active lipid transport,
   synthesis and metabolism and aligning with findings that lipids
   participate in axonal lysosome delivery and spheroid formation^[430]21.
   Interestingly, complement C3, crucial for complement system
   activation^[431]73 and lipid metabolism^[432]74,[433]75, exhibited the
   highest expression in axonal spheroids and aberrant axons (Fig.
   [434]4e,f and Extended Data Fig. [435]8a). This aligns with prior
   research linking complement proteins to dystrophic neurites around
   compact amyloid plaques^[436]76–[437]78 and suggests a potential
   connection between complement pathway activation and spheroid
   formation. On the basis of our previous work showing that microglia
   rarely engulf spheroids and that spheroids persist for long
   periods^[438]4,[439]31,[440]32, we propose that C3 is playing a role
   independent of traditional neuroimmune interactions, warranting further
   investigation.

   The PI3K/AKT/mTOR was identified as a key activated signaling pathway
   within PAASs (Fig. [441]3c and Extended Data Fig. [442]4e), with its
   activation in human postmortem brains strongly correlating with AD
   severity (Fig. [443]5b,c). The PI3K/AKT/mTOR pathway is known to
   inhibit autophagy, endosome and autophagosome maturation^[444]79,
   lysosomal biogenesis and proteasome assembly^[445]52 while promoting
   axonal outgrowth^[446]62,[447]63,[448]80 and lipid
   synthesis^[449]52,[450]81. Interestingly, lipids such as phosphatidic
   acid and cholesterol can activate the mTORC1 complex^[451]82,[452]83,
   suggesting that lipids within PAASs may mediate mTOR activation. This,
   in turn, could modulate PAAS formation by regulating the three key
   biological processes that we identified in PAASs: lipid transport,
   protein turnover and cytoskeletal dynamics (Figs. [453]3 and [454]4).

   Our findings demonstrate that pharmacological inhibition of mTOR
   signaling in the human iPSC-derived AD model significantly reduced PAAS
   pathology (Fig. [455]6). Separate in vivo experiments with
   neuron-specific mTOR heterozygous knockout in 5×FAD mice excluded glial
   contributions, confirming a neuronal cell-autonomous effect of mTOR on
   PAASs (Fig. [456]7). Investigation of downstream mechanisms revealed
   that mTOR knockdown enhanced autophagy, likely acting both at the whole
   cell level and locally within axonal spheroids, consistent with the
   extensive accumulation of endolysosmal vesicles in these structures.
   Additionally, the presence of mRNA and nascent proteins in axonal
   spheroids suggested potential for local translation at these sites.
   However, although mTOR signaling is known to modulate local translation
   in neurons^[457]62,[458]63,[459]84, our study did not detect changes in
   local translation levels after mTOR knockout or pharmacological
   inhibition (Supplementary Fig. [460]12d–f).

   In addition to PI3K/AKT/mTOR, we observed activation of other signaling
   pathways within PAASs, including calcium signaling and amyloid
   processing (Figs. [461]3c and [462]8). Proteins involved in calcium
   signaling, such as CAMK2 and calmodulin, were identified in PAASs (Fig.
   [463]3e, Supplementary Fig. [464]7 and Supplementary Table [465]2),
   suggesting a role for local calcium signaling dysregulation in PAAS
   pathogenesis. This is supported by our longitudinal calcium imaging in
   human neurons, which showed that axonal spheroids disrupt calcium rise
   and decay times after electrical stimulation, indicating impaired
   action potential conduction and calcium homeostasis within PAASs.
   Additionally, recent studies have shown that abnormal local calcium
   efflux from de-acidified late endosomes and amphisomes can disrupt
   axonal transport of these vesicles^[466]85, highlighting the complex
   interplay between calcium signaling and other pathways during PAAS
   development.

   The human iPSC-derived AD model effectively replicated PAAS pathology,
   characterized by abundant spheroid formation around thioflavin
   S–positive amyloid plaques and significant accumulation of
   endolysosomal vesicles, cytoskeletal elements and phosphorylated tau
   within PAASs. The administration of exogenous Aβ in this model (Fig.
   [467]6a–d) supports the theory that spheroids form in response to
   extracellular amyloid deposition rather than acting as the source of
   these deposits^[468]18,[469]86. Longitudinal imaging of individual
   axons in human neurons revealed rapid spheroid formation and lysosome
   accumulation within days of Aβ administration, with axons exhibiting
   active growth during spheroid formation rather than a dying-back
   pattern (Fig. [470]6c), consistent with previous in vivo mouse
   studies^[471]4. Despite widespread exposure to oligomeric Aβ in this
   model, axonal spheroids were predominantly observed next to compact
   thioflavin S–positive plaques (Fig. [472]6b and Extended Data Figs.
   [473]9e,f and [474]10b,c). This is consistent with human observations,
   where diffuse amyloid deposits (thioflavin S negative) rarely induce
   PAASs, whereas thioflavin S–positive deposits are closely associated
   with PAAS pathology^[475]31. These findings suggest that specific β
   amyloid conformations are critical for triggering PAAS formation.

   This study has several potential limitations. First, although STED
   super-resolution imaging showed that the radius of antibody-based
   proximity labeling in brain tissue was less than 50 nm, some proteins
   distal to PLD3 may not have been captured in the PAAS proteome.
   However, the high enrichment of PLD3 in axonal spheroids likely
   increased biotinylation efficiency, resulting in our ability to capture
   most proteins previously described in PAASs, including
   endolysosomal-related proteins as well as cytoskeletal proteins (for
   example, SPTBN1) and cell surface receptors (for example, NTRK2) (Figs.
   [476]2d and [477]8, Extended Data Fig. [478]4a, Supplementary Fig.
   [479]6 and Supplementary Table [480]2). Second, although PLD3 is
   abundant in spheroids in both AD human and mouse brains, some labeling
   does occur at neuronal cell bodies and neuropil (~27% of PLD3 signal)
   (Extended Data Fig. [481]1e–g). We addressed this by excluding proteins
   potentially originating from neuronal cell bodies (Fig. [482]2b and
   [483]Methods), but the presence of some neuronal cell body–specific
   proteins in the PAAS proteome cannot be entirely ruled out. For
   instance, a protein upregulated in AD but expressed solely in the
   neuronal soma could theoretically appear as a false positive, although
   we have not found such cases so far. Third, the low number of plaques
   and axonal spheroids in early-stage AD limited our ability to compare
   levels of the various PAAS proteins across disease stages due to
   insufficient protein yield. Future studies could leverage multiplexed
   high-resolution quantitative imaging^[484]87 for comparisons at
   different disease stages. Finally, the human iPSC-derived AD model in
   our study recapitulates spheroid formation around amyloid plaques but
   does so through a rapid process that may not fully mimic in vivo
   mechanisms. Refining these models to allow for more chronic amyloid
   buildup and incorporating co-cultures with other cell types, such as
   microglia, could better replicate the in vivo plaque microenvironment.

   Altogether, the proteomics resources and methodologies developed in
   this study enable the investigation of axonal pathology in human
   postmortem brains, iPSC-derived human neurons and in vivo mouse models.
   Although this study focused on amyloid plaque-associated axonal
   spheroids, similar structures are observed in other neurodegenerative
   disorders^[485]21,[486]88–[487]90. Therefore, the multidisciplinary
   strategies, and the datasets generated, mapping the molecular
   architecture of axonal spheroids will facilitate studies into the
   diverse mechanisms underlying axonal spheroid pathology in AD and other
   neurodegenerative conditions, providing a foundation for hypothesis
   generation and therapeutic target testing.

Methods

Human postmortem brain tissue

   Snap-frozen postmortem human brain specimens of frontal cortices from
   patients with AD and age-matched controls were obtained from the Yale
   Alzheimer’s Disease Research Center and the Banner Sun Health Research
   Institute. Detailed demographic and clinical information can be found
   in Supplementary Fig. [488]1. For proximity labeling proteomics, six AD
   cases with intermediate to high AD level^[489]64 and eight age-matched
   unaffected controls were used. To reduce inter-sample variability and
   maximize signal to noise by avoiding brains with low-density amyloid
   deposition, we carefully inspected approximately 40 individual
   postmortem brains using microscopy and selected for proteomic analysis
   six AD brains with the highest density of amyloid plaques and axonal
   spheroids within the frontal cortex. The gray matter regions with high
   plaque load were microdissected out from AD brain sections under visual
   guidance using a fluorescence stereomicroscope (Leica). Similarly, the
   gray matter regions were dissected from unaffected control brain
   sections. For immunofluorescence proteomic validations, 25 severe AD
   and 14 unaffected control cases were used (Supplementary Fig. [490]1).

Human iPSC line and human primary astrocytes

   Two fully characterized, de-identified control human iPSC lines,
   NSB3182-3 (female) and NSB2607 (male), were used in all
   experiments^[491]91. NGN2-induced glutamatergic neurons^[492]56 were
   generated and co-cultured with human primary astrocytes (Thermo Fisher
   Scientific, N7805200, or ScienCell, 1800) for all experiments^[493]57.

Mice

   All animal procedures were approved by the Institutional Animal Care
   and Use Committee at Yale University. Animals were housed at the Yale
   University Animal Facility, with a 12-hour light/dark cycle,
   temperature at 65–75 °F and with 40–60% humidity. Wild-type (WT)
   (C57BL/6J) mice, 5×FAD (Tg6799) mice^[494]92 and mTOR-flox (The Jackson
   Laboratory (JAX), 011009) mice^[495]61 were obtained from JAX. 5×FAD
   and WT mice, used for proximity labeling proteomics, were euthanized at
   15 months of age, followed by transcardial perfusion. Three male mice
   per genotype (WT and 5×FAD) were used. Animals used for
   immunofluorescence proteomic validation were euthanized at 2–3 months
   or 12–15 months of age, with three biological replicates per
   experiment. mTOR-flox mice were cross-bred with 5×FAD mice to create an
   mTOR-flox 5×FAD line. For AAV-mediated mTOR heterozygous knockout
   experiments, mTOR-flox 5×FAD mice were injected with AAVs at 6 weeks of
   age. Five biological replicates (combining male and female mice) in
   each group were used for the AAV9-hSyn-cre-2a-tdT experiment, and three
   male mice in each group were used for the AAV-PHPeB experiment.

Antibodies and reagents

   The full list of primary antibodies for newly validated and known PAAS
   proteins can be found in Supplementary Table [496]2, including catalog
   number, RRID, dilution factors and brief staining instructions. In
   brief, anti-PLD3 antibody, anti-SMI312 and anti-cathepsin D were used
   to label PAASs in both mice and humans. Anti-Lamp1 and anti-cathepsin B
   antibodies were used to label PAASs in mice. For proteomic hits
   validation, anti-GAA, anti-GBA, anti-TPP1, anti-ATP6V0A1, anti-SYT11,
   anti-G3BP1, anti-G3BP2, anti-ITM2B, anti-SPTBN1, anti-SV2A,
   anti-ATP2B3, anti-CAMK2A, anti-calmodulin, anti-SYT1, anti-CACNA2D1,
   anti-CACNA1B, anti-NTRK2, anti-mTOR, anti-p-mTOR S2448, anti-PIK3R4,
   anti-AKT1, anti-LAMTOR, anti-RAGA, anti-RAGC, anti-RHEB, anti-RAPTOR,
   anti-HDLBP, anti-APOE, anti-C3, anti-HEXB and anti-TMEM30A were used
   for validating newly identified PAAS proteins. Anti-RAGC, anti-ATG9A,
   anti-ubiquitin, anti-RTN3, anti-PKC, anti-synaptophysin, anti-SNAP25,
   anti-VAMP2 and anti-beta tubulin III were used for immunostaining of
   known PAAS proteins. To reveal GFP and tdTomato protein expression,
   anti-GFP (1:500, RRID: AB_10000240) and anti-RFP (1:200, RRID:
   AB_2209751) were used, respectively. For staining neuronal and glial
   markers in iPSC-derived human neurons, anti-neurofilament H (1:1,000,
   RRID: AB_2149761), anti-NeuN (1:1,000, RRID: AB_10711040), anti-NeuN
   (1:200, RRID: AB_2532109), anti-Synapsin1/2 (1:500, RRID: AB_2622240),
   anti-PSD95 (1:200, RRID: AB_10807979), anti-S100b (1:500, RRID:
   AB_2814881) and anti-IBA1 (1:100, RRID: AB_2891289) were used. To stain
   Aβ deposits, anti-6e10 (1:200, RRID: AB_2565328) was used. To stain
   phosphorylated Tau, anti-phospho-Tau S235 (1:1,000; Thermo Fisher
   Scientific), anti-phospho-Tau S396 (1:200) and anti-phospho-Tau S404
   (1:200) were used (see RRIDs in Supplementary Table [497]2). Dendritic
   marker MAP2 (1:200, RRID: AB_776174) was used. To detect mTOR signaling
   substrates such as phosphor-4E-BP1 and p70S6K, an mTOR substrate
   antibody sampler kit (Cell Signaling Technology (CST), 9862) and
   anti-4E-BP1 antibody (CST, 9452) were used. For puromycylation,
   anti-puromycin 647 (1:1,000, RRID: AB_2736876) was used. Thioflavin S
   (Sigma-Aldrich, T1892, 2% w/v stock solution, 1:10,000 staining) was
   used to label amyloid plaques. Alexa Fluor dye-conjugated secondary
   antibodies were used (1:600; Thermo Fisher Scientific).

Tissue fixation

   We compared the impact of different tissue fixation approaches on the
   proximity labeling efficacy and protein extraction efficiency. For
   human brain samples, snap-frozen postmortem human brains coupled with
   fresh fixation in 4% paraformaldehyde (PFA) at 4 °C for approximately
   24 hours worked the best. For mice, freshly perfused mouse brains and
   fixed in 4% PFA at 4 °C for approximately 24 hours performed the best
   in both proximity labeling efficacy and protein extraction efficiency.
   We found that long-term fixation and storage with the formalin-fixed
   paraffin-embedded (FFPE) method markedly reduced both proximity
   labeling and protein extraction efficiencies.

Proximity labeling in brain tissue

   Proximity labeling in human and mouse tissue was performed based on
   ref. ^[498]43 with optimizations. Detailed procedures are described
   below. Axonal spheroids were proximity labeled by using anti-PLD3 or
   anti-Lamp1 antibodies in mice and humans. Neuronal soma were proximity
   labeled using anti-NeuN antibody. In brief, frozen postmortem human
   brain specimens were fixed by submerging into ice-cold 4% PFA and put
   onto a shaker at 4 °C for approximately 24 hours. For mice, after
   transcardial perfusion, brains were fixed in 4% PFA at 4 °C for
   approximately 24 hours while shaking. Human and mouse brains were
   vibratome sectioned at 50-μm thickness. Ten sections (approximately
   1 cm × 0.8 cm each) for human or mouse brain were used in each reaction
   per biological replicate. Human sections contained mostly gray matter.
   Six to eight human biological replicates were used in each group, and
   three biological replicates were used in each mouse group. Sections
   were permeabilized by PBS with 0.5% Triton X-100 for 7 minutes,
   followed by rinsing with PBST (0.1% Tween 20 in PBS). To quench the
   endogenous peroxidase activity, sections were incubated in 0.1%
   H[2]O[2]for 10 minutes, followed by rinsing with PBST twice. Primary
   antibody diluted in blocking buffer (0.1% Tween 20 with 1% BSA in PBS)
   was incubated overnight at 4 °C on a shaker, followed by PBST washes
   for three times at 20 minutes per wash. Secondary antibodies conjugated
   with HRP were incubated in blocking buffer for 1 hour at room
   temperature, followed by PBST washes for three times at approximately
   40 minutes per wash. Proximity labeling was performed by using
   Biotin-XX-Tyramide dissolved in 50 mM Tris-HCl buffer (pH 7.4) with
   H[2]O[2] for 5 minutes, according to the user’s manual (Thermo Fisher
   Scientific, [499]B40921). Specifically, every 1 ml of reaction solution
   was made of 10 μl of 1× Biotin-XX-Tyramide and 10 μl of 1× H[2]O[2] in
   50 mM Tris-HCl buffer. Biotinylation reactions were terminated by
   rinsing sections with freshly made 500 mM sodium ascorbate for three
   times, followed by PBST washes for three times.

Enrichment of biotinylated proteins using streptavidin beads

   We performed proximity labeling proteomics on fixed brain specimens,
   which may reduce the protein extraction yield compared to other
   proximity labeling methods using fresh tissue. Thus, we optimized the
   protein extraction protocol and largely increased the protein
   extraction yield compared to previously published methods
   (Supplementary Fig. [500]2a)^[501]43. Specifically, brain sections from
   proximity labeling experiments were lysed and de-crosslinked in 100 mM
   Tris-HCl buffer (pH 8.0) with 2% SDS and protease inhibitor (Roche) at
   95 °C for 45 minutes with constant shaking. For every 10 brain
   sections, 500 µl of lysis buffer was used. Protein lysate was sonicated
   using Sonic Dismembrator Model 500 (Thermo Fisher Scientific) for three
   times, 3 seconds per time at 4 °C. Protein lysate was centrifuged at
   12,000 relative centrifugal force (rcf) for 5 minutes. Then, 450 µl of
   protein lysate supernatant was collected from each sample, incubated
   with 550 µl of PBST containing 200 µl of pre-washed streptavidin
   magnetic beads (Thermo Fisher Scientific, 88817), protease inhibitor
   and phosphatase inhibitor, to meet a final 1-ml volume. Samples were
   then incubated on a 360° rotator at 4 °C overnight. The rest of protein
   lysates were used for protein concentration measurement by BCA (Thermo
   Fisher Scientific). After incubation, beads were sequentially washed
   once with PBST, twice with PBST with 1 M NaCl and twice with PBS.
   Biotinylated proteins were eluted in elution buffer (20 µl of 20 mM
   dithiothreitol (DTT) and 2 mM biotin in 1× NuPAGE LDS lysis buffer
   (Thermo Fisher Scientific) with protease inhibitor and phosphatase
   inhibitor) at 95 °C for 5 minutes. Supernatant was collected and
   centrifuged at 12,000 rcf for 1 minute, followed by running into a
   4–20% Tris-glycine gel (Invitrogen) at constant 150 V until all the
   proteins had run into the gel (approximately 10 minutes). Gel was
   rinsed once in ultrapure water (AmericanBio) and incubated in
   approximately 50 ml of Coomassie blue R-250 staining solution (Bio-Rad)
   for 1-hour incubation. Gel was de-stained with Coomassie blue R-250
   destaining solution (Bio-Rad) for 2 hours with three times buffer
   changes. Gel was rinsed with ultrapure water for three times. Gel
   containing protein samples was visualized, cut with clean blades and
   kept at −20 °C.

Enrichment of biotinylated peptides using anti-biotin antibody

   The labeled tissue was lysed using 100 mM Tris-HCl buffer (pH 8.0) with
   2% SDS and protease inhibitor (Roche). The lysates were sonicated and
   then centrifuged at 16,500g for 10 minutes at 4 °C. The proteins were
   precipitated using acetone, and the pellet was dissolved in 8 M urea
   and 50 mM ammonium bicarbonate (ABC) and then sonicated for 30 seconds
   to re-solubilize the proteins. A Bradford assay was performed to
   determine protein concentration, and 2 mg of protein was used to
   process further. Proteins were reduced with 5 mM DTT for 45 minutes at
   room temperature and subsequently carbamidomethylated with 10 mM
   iodoacetamide for 30 minutes at room temperature in the dark. Before
   digestion, the urea concentration was reduced to 2 M with 50 mM ABC and
   digested with trypsin at an enzyme:substrate ratio of 1:50 overnight at
   37 °C. After digestion, samples were acidified with 10% formic acid and
   de-salted using Nest Group C18 macro-spin columns (HMMS18V) as per the
   manufacturer’s instructions. Biotinylated peptides were enriched using
   anti-biotin antibody-based immunoprecipitation. The peptides were
   dissolved in IAP buffer containing 50 mM MOPS, 10 mM HNa[2]PO[4] and
   50 mM NaCl at pH 7.5. Anti-biotin beads (ImmuneChem Pharmaceuticals)
   were washed twice in IAP buffer before the samples were added to the
   beads for incubation on a rotator for 2 hours at 4 °C. The beads were
   washed twice with IAP buffer and twice with water (high-performance
   liquid chromatography (HPLC) grade). The biotinylated peptides were
   eluted from the beads using 80% acetonitrile (ACN) and 0.15%
   trifluoroacetic acid (TFA) with vortexing, followed by a 10-minute
   incubation at room temperature. The elution was repeated twice, and the
   supernatants were collected and vacuum dried.

Western blotting

   For western blotting, 4–20% Tris-glycine gels (Invitrogen) were used
   for protein electrophoresis following the manufacturer’s protocol.
   Proteins were transferred to nitrocellulose membranes (Bio-Rad) at
   constant 350 mA for approximately 50 minutes. After blocking with 5%
   BSA in TBST (Tris-buffered saline with 0.1% Tween 20) for 1 hour,
   membranes were incubated with primary antibodies (anti-PLD3 1:250;
   anti-CatB 1:1,000; anti-RAGC 1:1,000; anti-NeuN 1:1,000; anti-GAPDH
   1:1,000) diluted in 5% BSA in TBST on a shaker at 4 °C overnight,
   followed by three times of 15-minute washes with TBST. Membranes were
   then incubated with HRP-conjugated secondary antibodies diluted in 5%
   BSA in TBST for 1 hour at room temperature, followed by three times of
   15-minute washes with TBST. To blot biotinylated proteins on the same
   membrane, stripping buffer (Thermo Fisher Scientific, 46430) was used
   to cover the whole membrane and incubated at room temperature with
   shaking for 10–12 minutes, followed by rinsing with PBST for three
   times. HRP-conjugated streptavidin (1:1,000) was diluted in blocking
   buffer for 1–2 hours at room temperature or 4 °C overnight. Clarity
   Western ECL blotting substrate (Bio-Rad) and ChemiDoc MP Imaging System
   (Bio-Rad) were used for chemiluminescence development and detection.

In-gel digestion

   Gel slices were cut into small pieces and washed with 600 µl of water
   on a tilt table for 10 minutes, followed by 20-minute wash with 600 µl
   of 50% ACN/100 mM NH[4]HCO[3] (ABC). The samples were reduced by the
   addition of 100 µl of 4.5 mM DTT in 100 mM ABC with incubation at 37 °C
   for 20 minutes. The DTT solution was removed, and the samples were
   cooled to room temperature. The samples were alkylated by the addition
   of 100 µl of 10 mM iodoacetamide (IAN) in 100 mM ABC with incubation at
   room temperature in the dark for 20 minutes. The IAN solution was
   removed, and the gels were washed for 20 minutes with 600 µl of 50%
   ACN/100 mM ABC and then washed for 20 minutes with 600 µl of 50%
   ACN/25 mM ABC. The gels were briefly dried by SpeedVac and then
   resuspended in 100 µl of 25 mM ABC containing 500 ng of digestion-grade
   trypsin (Promega, V5111) and incubated at 37 °C for 16 hours. The
   supernatants containing the tryptic peptides were transferred to new
   Eppendorf tubes. Residual peptides in the gel bands were extracted with
   250 µl of 80% ACN/0.1% TFA for 15 minutes and then combined with the
   original digests and dried in a SpeedVac. Peptides were dissolved in
   24 µl of MS loading buffer (2% ACN, 0.2% TFA), with 5 µl injected for
   LC–MS/MS analysis.

LC–MS/MS data collection

   LC–MS/MS analysis was performed on a Thermo Fisher Scientific Q
   Exactive Plus equipped with a Waters nanoAcquity UPLC system using a
   binary solvent system (A: 100% water, 0.1% formic acid; B: 100% ACN,
   0.1% formic acid). Trapping was performed at 5 µl min^−1, 99.5% buffer
   A for 3 minutes using an ACQUITY UPLC M-Class Symmetry C18 Trap Column
   (100 Å, 5 µm, 180 µm × 20 mm, 2G, V/M; Waters, 186007496). Peptides
   were separated at 37 °C using an ACQUITY UPLC M-Class Peptide BEH C18
   Column (130 Å, 1.7 µm, 75 µm × 250 mm; Waters, 186007484) and eluted at
   300 nl min^−1 with the following gradient: 3% buffer B at initial
   conditions; 5% B at 2 min; 25% B at 140 min; 40% B at 165 min; 90% B at
   170 min; 90% B at 180 min; return to initial conditions at 182 minutes.
   MS scans were acquired in profile mode over the 300–1,700 m/z range
   using one microscan, 70,000 resolution, AGC target of 3 × 10^6 and a
   maximum injection time of 45 ms. Data-dependent MS/MS scans were
   acquired in centroid mode on the top 20 precursors per MS scan using
   one microscan, 17,500 resolution, AGC target of 1 × 10^5, maximum
   injection time of 100 ms and an isolation window of 1.7 m/z. Precursors
   were fragmented by HCD activation with a collision energy of 28%. MS/MS
   scans were collected on species with an intensity threshold of
   1 × 10^4, charge states 2–6 and peptide match preferred. Dynamic
   exclusion was set to 30 seconds.

Peptide identification

   Data were analyzed using Proteome Discoverer software version 2.2
   (Thermo Fisher Scientific). Data searching was performed using the
   Mascot algorithm (version 2.6.1) (Matrix Science) against the SwissProt
   database with taxonomy restricted to human (20,368 sequences) or mouse
   (17,034 sequences) as well as a streptavidin sequence. The search
   parameters included tryptic digestion with up to two missed cleavages,
   10-ppm precursor mass tolerance and 0.02-Da fragment mass tolerance and
   variable (dynamic) modifications of methionine oxidation and
   carbamidomethyl cysteine. Normal and decoy database searches were run,
   with the confidence level set to 95% (P < 0.05). Scaffold version 5.1.2
   (Proteome Software) was used to validate MS/MS-based peptide and
   protein identifications. Peptide identifications were accepted if they
   could be established at greater than 95.0% probability by the Scaffold
   Local FDR algorithm. Protein identifications were accepted if they
   could be established at greater than 99.0% probability and contained at
   least two identified peptides (one uniquely assignable to the protein).
   Proteins that contained similar peptides and could not be
   differentiated based on MS/MS analysis alone were grouped to satisfy
   the principles of parsimony. Proteins sharing significant peptide
   evidence were grouped into clusters. Label-free quantification was
   performed with Scaffold software. Spectral intensity values were used
   for protein quantification between groups.

   To search for biotinylation sites in the anti-biotin antibody pulldown
   samples, the variable modifications of Biotin-XX-Tyramide were
   configured to account for marker ions resulting from fragmentation of
   biotinylated peptides. These marker ions have the following m/z values
   and elemental composition losses from the fully modified amino acid:
   dehyrdrobiotin (m/z 227.08), Biotin-X ion (m/z 340.25), Biotin-XX ion
   (m/z 453.25), immonium of tyrosine-Bxxp with loss of ammonia (m/z
   706.38) and immonium of tyrosine-Bxxp (m/z 723.38).

Proteomic data analysis

   Before the data analysis, missing values were removed. For example, if
   a protein A had 0 spectra count detected in all the samples, including
   tests and controls, then protein A was removed from the list. NTSC and
   NTPI are two common methods for proteomic quantification. For
   PLD3-labeled PAAS proteomes in humans, we compared NTSC and NTPI
   methods and used the shared proteomic hits for downstream analysis. For
   PLD3-labeled PAAS proteomes in mice, Lamp1-labeled proteomes in mice
   and NeuN-labeled neuronal nuclei and perinuclear cytoplasm proteomes in
   mice, we used NTSC for quantification. To obtain the PAAS proteome,
   differentially expressed proteins were analyzed by comparing proteomic
   hits obtained from PLD3-labeled samples versus those from control
   samples using no antibody. This allowed the filtering of endogenously
   biotinylated proteins and non-specific binders to streptavidin beads.
   To obtain the optimal cutoff values for the statistical analysis, we
   tested different degrees of stringency for FDR (0.1, 0.05 and 0.01) and
   FC (1 and 1.5). An optimum cutoff P < 0.05, FDR < 0.1 and FC > 1.5 was
   used for these datasets, as it captures the maximum numbers of known
   PAAS proteins while excluding the maximum numbers of potential
   contaminants. Post-cutoff proteomic lists were scrutinized for possible
   glial contaminations by cross-validations using single-cell RNA
   sequencing (scRNA-seq) transcriptomics in mice^[502]55 and
   humans^[503]93 and Tissue Atlas in the Human Protein Atlas^[504]94.
   When a gene had a fragments per kilobase of transcript per million
   mapped reads (FPKM) < 10 in neurons and an FPKM > 10 in other cell
   types in the mice scRNA-seq dataset^[505]55, or the mean expression
   level was less than 0.03 in neurons but greater than 0.03 in glia in
   the AD pathology human scRNA-seq dataset^[506]93, and protein
   expression was not detected in neurons from the Tissue Atlas^[507]94,
   this gene was excluded from the proteomic results. Two such genes
   (EPHX1 and PSAT1) were excluded from the PAAS proteome in humans with
   AD, and five such genes (Gsn, Ephx2, Gfap, Myh9 and Anxa2) were
   excluded from the PAAS proteome in AD mice. Proteomic hits that passed
   these thresholds were considered the final PAAS proteomes in humans
   with AD or AD mice. Lists of raw and filtered proteomic hits of PAASs
   and neuronal soma proteomes in humans with AD and AD mice can be found
   in Supplementary Table [508]1.

   For GO analysis (Fig. [509]3a and Extended Data Figs. [510]4c and
   [511]7b), we uploaded the final proteomes to
   [512]https://geneontology.org/ (refs. ^[513]95,[514]96),
   g:profiler^[515]97 or the ToppGene Suite search portal^[516]98 and
   plotted the top 10 or top 20 retrieved terms on cellular compartment or
   biological process with the lowest FDRs. Pathway enrichment analysis
   was performed by retrieving GO biological process, cellular component
   and molecular function terms from g:profiler^[517]97 using terms size
   5–200. The enrichment map was visualized in Cytoscape (version
   3.9.1)^[518]99. For Ingenuity Pathway Analysis (IPA) (Fig. [519]3b,c
   and Extended Data Fig. [520]4d,e), the human or mouse PAAS proteome was
   imported into IPA software (Qiagen, 2022 release version)^[521]100 for
   canonical pathway analysis. The top IPA pathways with the lowest FDRs
   and potential relevance to PAAS pathology are listed. For GSEA (Fig.
   [522]4a), PLD3-labeled proteomes of humans with AD and unaffected
   controls were uploaded into Broad Institute GSEA software 4.3.2 (ref.
   ^[523]101) to perform GO analysis using default values, except the size
   was set to 200 to remove the larger sets from analysis. GSEA results
   were loaded into Cytoscape (version 3.9.1) for pathway enrichment
   analysis using EnrichmentMap^[524]102 and AutoAnnotate^[525]103 plugins
   with default values. Principal component analysis was performed using
   Qlucore Omics Explorer version 3.6 (Qlucore AB).

Immunofluorescence of fixed specimens and human iPSC-derived co-culture

   The complete list of antibodies, dilution factors and
   immunofluorescence instructions for immunofluorescence staining of
   fixed specimens of humans and mice can be found in Supplementary Table
   [526]2. In brief, for mouse and human brains, fixation and vibratome
   sectioning was the same as described in the ‘Proximity labeling in
   brain tissue’ subsection. Heat-induced sodium citrate antigen retrieval
   was performed when necessary (see immunofluorescence instructions in
   Supplementary Table [527]2). Immunofluorescence staining was then
   performed with the following protocol: tissue was boiled in 50 mM
   sodium citrate with 0.05% Tween 20 at 95 °C for 45 minutes, followed by
   a 30-minute cool down at room temperature and rinse with PBS for three
   times. Primary antibody incubation was 12 hours to 3 days at 4 °C in
   blocking buffer (PBS with 1% BSA and 0.1% Tween 20), and secondary
   antibodies were incubated in blocking buffer at 4 °C overnight.
   Thioflavin S (Sigma-Aldrich, T1892, 2% w/v stock solution, 1:10,000
   staining) was used for labeling amyloid deposits. Three times washes
   with PBST were performed before mounting tissues on slides with
   PermaFluor (Thermo Fisher Scientific, TA-030-FM).

   For immunofluorescence of human iPSC-derived neuron–astrocyte
   co-culture, cells were washed three times with pre-warmed PBS before
   fixing with 4% PFA (ice cold) at room temperature for 20 minutes. Cells
   were washed with PBS for 15 minutes three times and were blocked with
   blocking buffer (1% BSA in PBS, plus 0.1% Tween 20) for 1 hour. Primary
   antibodies were diluted in blocking buffer and incubated with cells at
   4 °C overnight. Cells were washed with PBST for 15 minutes three times.
   Secondary antibodies were diluted in blocking buffer and incubated with
   cells at 4 °C overnight. Thioflavin S (2% w/v stock solution, 1:10,000
   staining) was diluted in PBS and incubated with cells at room
   temperature for 5 min. Cells were washed with PBST for 15 min three
   times before imaging.

Fixed tissue and live cell time-lapse confocal microscopy imaging

   An upright or an inverted Leica SP8 confocal microscope was used to
   generate all images. Laser and detector settings (GaAsP hybrid
   detection system, photon counting mode) were maintained constant. For
   all analyses, single z-stack images or tiled images were obtained in
   the somatosensory cortex in mice. All images were obtained using a ×63
   oil immersion objective (numerical aperture (NA) 1.40), ×40 water
   immersion objective (NA 1.10) or ×25 water immersion objective (NA
   0.95) at 1,024 × 1,024-pixel resolution and z-step size of 1 μm, as we
   previously described^[528]31. When indicated, deconvolution was
   performed using the default setting in Leica SP8 LAS X software. For
   time-lapse imaging of spheroid growth in human neurons, 96-well plates
   were imaged in a Leica SP8 incubator, with the temperature set at 37 °C
   and supplied with CO[2]. Tilling images were obtained using a ×63 oil
   immersion objective (NA 1.40) at 512 × 512-pixel resolution, zoom
   factor at 3 and z-step size of 1 μm or 1.5 μm at every day for 7 days.

Lentivirus plasmid purification, lentivirus production and concentration

   Escherichia coli stocks for pMDLg/pRRE (MDL), pRSV-Rev (Rev),
   pCMV-VSV-G (VSVG), FUW-M2rtTA and pLV-TetO-hNGN2-eGFP-Puro were
   purchased from Addgene (12251, 12253, 8454, 20342 and 79823,
   respectively). Bacteria was grown in 500 ml of LB broth (Thermo Fisher
   Scientific, DF0446-07-5) with 100 µg ml^−1 ampicillin (Sigma-Aldrich,
   A9518) overnight at 37 °C with shaking. The next day, bacterial cells
   were pelleted by centrifugation at 4,000g for 10 minutes at 4 °C. The
   supernatant was discarded, and plasmids were purified using a PureLink
   HiPure Plasmid Filter Maxiprep Kit (Invitrogen, K210017), following the
   manufacturerʼs instructions.

   Third-generation lentiviral vectors were produced as we previously
   described^[529]104. In brief, HEK293T cells (Invitrogen, R700-07) were
   grown in 15-cm plates (Falcon, 353025) in DMEM (Gibco, 12430054)
   supplemented with 10% FBS (Gibco, 10438026) until reaching 70–80%
   confluency. For cell transfection, the following solution was prepared
   in 500 µl of pre-warmed Opti-MEM (Gibco, 31985062) per plate: 12.2 µg
   of transfer plasmid, 8.1 µg of MDL, 3.1 µg of Rev, 4.1 µg of VSVG and
   110 µL of polyethylenimine (1 µg µl^−1; Polysciences, 23966-2). This
   solution was incubated for 10 minutes at room temperature, vortexed
   gently and added dropwise onto HEK293T cells for transfection. Medium
   was changed after 6 hours of incubation and harvested at 48 hours and
   72 hours after transfection. Media containing viral particles were
   sterile filtered and concentrated using a Lenti-X Concentrator (Takara
   Bio, 631231), according to the manufacturerʼs instructions.

Human neuron–astrocyte co-culture AD model

   Human iPSC control lines 3182-3 and 2607 were used in this study, as we
   first described this line in ref. ^[530]91. Maintenance and passaging
   of human iPSCs were performed as we previously described^[531]105.
   Human primary astrocytes (Thermo Fisher Scientific, N7805200, or
   ScienCell, 1800) were maintained as described in the user manual.
   iPSC-derived NGN2-induced glutamatergic neuron generation was performed
   as we previously described^[532]105. In brief, human iPSCs maintained
   in six-well plates were harvested by incubating in Accutase (Innovative
   Cell Technologies, AT104) 1 ml per well plus 10 µM ROCK inhibitor THX
   (RI) (Tocris, 1254) at 37 °C for 20 minutes. Dissociated iPSCs were
   then collected in a 50-ml Falcon tube and mixed well with DMEM (Thermo
   Fisher Scientific, 11966025) (preferably 1:3 Accutase: DMEM). iPSCs
   were centrifuged for 4 minutes at room temperature at 1,000g. iPSCs
   were resuspended in 1–2 ml of StemFlex (Thermo Fisher Scientific) with
   10 µM RI and counted and diluted in StemFlex with THX to a cell
   suspension concentration of 1 × 10^6 cells per milliliter. Lentiviruses
   NGN2-Puro and rtTA (titer 4.40 × 10^10 gc ml^−1) at 50 µl per 10^6
   cells of suspension were added. Cells were mixed and dispensed at
   120,000 cells per well (six-well size) coated with 1× Geltrex (Thermo
   Fisher Scientific). Cells were incubated at 37 °C in an incubator
   overnight. Days in vitro (DIV) 1: media were replaced with induction
   media (DMEM F-12 with GlutaMAX and sodium pyruvate (Thermo Fisher
   Scientific, 10565018), 1% N-2 (Thermo Fisher Scientific, 17502048), 2%
   B-27-RA (Thermo Fisher Scientifiic, 12587010) and doxycycline for a
   final concentration of 1 µg ml^−1). DIV2 and DIV3: media were replaced
   with induction media containing puromycin (2 µg ml^−1) on each day.
   DIV4: neurons were dissociated with Accutase plus 10 µM RI for
   20 minutes, washed off with 1:3 DMEM, resuspended and centrifuged at
   1,000g for 5 minutes. Pellet was resuspended at a concentration of
   1 × 10^6 cells per milliliter in neuron media (BrainPhys; STEMCELL
   Technologies, 05790), 1% N-2, 2% B-27-RA, 1 μg ml^−1 Natural Mouse
   Laminin (Thermo Fisher Scientific, 23017015), 20 ng ml^−1 BDNF (R&D
   Systems, 248), 20 ng ml^−1 GDNF (R&D Systems, 212), 250 μg ml^−1
   dibutyryl cyclic-AMP (Sigma-Aldrich, D0627), 200 μM L-ascorbic acid
   (Sigma-Aldrich, A4403) and 1× Anti-Anti (Thermo Fisher Scientific) with
   doxycycline 1 μg ml^−1, puromycin 2 μg ml^−1, 4 µM AraC (Sigma-Aldrich,
   C6645) and 10 µM RI. Neurons were re-plated onto 2× Geltrex-coated
   96-well-plates (PerkinElmer, 6055302) and seeded at 1 × 10^5 per well
   (96-well plate size). DIV5: media were replaced with neuron medium
   containing puromycin 2 μg ml^−1 and AraC 4 μM. DIV6: media were
   replaced with neuron medium with 4 μM AraC. DIV8: media were replaced
   with neuron medium with 2 μM AraC. DIV10: human primary astrocytes were
   dissociated with TrypLE (Thermo Fisher Scientific), washed with DMEM,
   centrifuged at 400 rcf for 5 minutes, counted and plated into NGN2
   neurons culture at 20,000 cells per well (96-well plate size). Human
   iPSC-derived neuron–astrocyte co-culture was maintained as previously
   described^[533]57 with modifications. In brief, human neuron–astrocyte
   co-cultures were maintained in neuron media plus 1.5% FBS for 1 week
   and then FBS was reduced to 0.5% for another week. Media were
   half-changed every other day. After that, human neuron–astrocyte
   co-cultures were maintained in neuron maintenance medium (1× BrainPhys
   Basal (STEMCELL Technologies), 1× B27 with vitamin A (Thermo Fisher
   Scientific), 1× N2 (Thermo Fisher Scientific), 5 μg ml^−1 cholesterol
   (Sigma-Aldrich), 1 mM creatine (Sigma-Aldrich), 10 nM β-estradiol,
   200 nM ascorbic acid, 1 mM cAMP (Sigma-Aldrich), 20 ng ml^−1 BDNF
   (PeproTech), 20 ng ml^−1 GDNF (PeproTech), 1 μg ml^−1 laminin, 0.5 mM
   GlutaMAX (Thermo Fisher Scientific), 1 ng ml^−1 TGF-β1 (PeproTech), 1×
   normocin (InvivoGen), 50 U ml^−1 penicillin– streptomycin (Thermo
   Fisher Scientific)) with half-change of media every other day until
   harvest or other assays. For AD modeling, Aβ1–42 peptide (AnaSpec,
   AS-72216) was oligomerized to prepare soluble Aβ species as previously
   described^[534]57,[535]106. In brief, soluble Aβ species were added to
   the neuron maintenance medium at a final concentration of 5 μM and
   applied to the human neuron–astrocyte co-culture for 7 days, with
   half-change of media every other day as previously described^[536]57.

   For mTOR signaling inhibition, Torin1 (Tocris, 4247) or vehicle DMSO
   was added to the neuron maintenance medium at a final concentration of
   250 nM (ref. ^[537]59) and applied to the human neuron–astrocyte
   co-culture 3 days before Aβ treatment. Then, Torin1 or vehicle DMSO was
   added to the neuron maintenance medium at 250 nM concentration, along
   with soluble Aβ species at 5 μM concentration, and applied to the human
   neuron–astrocyte co-culture for 7 days, with a half-change of media
   every other day. For Torin1 treatment after axon spheroid formation,
   soluble Aβ species at 5 μM concentration was applied to the human
   neuron–astrocyte co-culture for 7 days, and then Torin1 or vehicle DMSO
   was added to the neuron maintenance medium at 250 nM concentration for
   another 7 days.

   For time-lapse imaging of spheroid growth in human neurons,
   AAV9-hSyn-mCherry (Addgene, 114472) and AAV2-CAG-LAMP1-GFP (home
   produced as we previously described^[538]4) were co-transduced at
   2 × 10^9 vg per 100 μl of medium in 4-month-old co-cultures. Human
   neuron–glia co-cultures were treated with amyloid at day 150.
   Time-lapse confocal imaging was performed several hours before the
   treatment and imaged every day after treatments.

Calcium imaging in iPSC-derived human neurons

   AAV1-CAMKII-GCamp8f (Addgene, 176750, 7 × 10^12 vg ml^−1) was
   transduced in 2-month-old iPSC-derived human neurons, along with
   AAV9-CB7-mCherry (Addgene, 105544, 1 × 10^13 vg ml^−1) at 1 μl per 0.2
   Mio cells. Transduced cells were maintained with regular media changes.
   Calcium imaging was performed 1 month after transduction. Calcium
   imaging was performed using an Andor Dragonfly spinning disk confocal
   on a Nikon Ti2-E microscope. A ×20/0.75 NA air objective and a Zyla
   scientific complementary metaloxide semiconductor (sCMOS) camera were
   used. Imaging was performed in culture medium, and a stage-top
   incubator and objective heater (Oko-Lab) maintained the sample
   temperature at 37 °C. For stimulated calcium imaging, a pair of tinfoil
   wire electrodes separated approximately 1.5 mm apart were placed in the
   bottom of the well using a micromanipulator and used for electrical
   stimulation. Electric stimulation was performed using the trigger out
   function in the Andor software. GCaMP8f-labeled neurons were imaged
   through excitation at 488-nm wavelength with the acquisition speed of
   20 Hz and 512 × 512 resolution. Stimulation trains of 20-ms pulses were
   delivered to the electrodes at 50 Hz (20-ms interval) with 300–700-μA
   currents for 1 second. Electric stimulation was triggered automatically
   at the 100-frame timepoint, and image for 300–500 frames in total. The
   calcium responses within the imaging window were monitored upon
   stimulation.

   Calcium imaging raw data were de-noised using DeepCAD-RT^[539]107. The
   denoising model was trained with the different datasets acquired with
   the same imaging conditions. The denoised GCaMP8f fluorescence
   intensity was normalized to ΔF/F for analysis. Several regions of
   interest (ROIs) were selected on each axon. The average ΔF before
   stimulation was used as the baseline measurement. The raw fluorescence
   intensity over time (F(t)) contained background noise. To isolate the
   stimulus-evoked signal, we first calculated the average background
   fluorescence intensity (F[0]) using data from before stimulus
   presentation. We then normalized the signal by subtracting F[0] at each
   timepoint:
   [MATH: <mrow><mfrac><mrow><mi
   mathvariant="normal">Δ</mi><mi>F</mi></mrow><mrow><mi>F</mi></mrow></mf
   rac><mo>≡</mo><mfrac><mrow><mi>F</mi><mrow><mfenced close=")"
   open="("><mrow><mi>t</mi></mrow></mfenced></mrow><mo>−</mo><msub><mrow>
   <mi>F</mi></mrow><mrow><mn>0</mn></mrow></msub></mrow><mrow><msub><mrow
   ><mi>F</mi></mrow><mrow><mn>0</mn></mrow></msub></mrow></mfrac></mrow>
   :MATH]

   This normalized signal was smoothed using a Savitzky–Golay filter with
   a window length of 21 data points (1 second) and a polynomial order of
   3. This filtering reduced noise while preserving the overall shape of
   the signal. To quantify the rising slope of the calcium response, we
   identified the peak of the smoothed signal. The timepoint halfway to
   this peak (
   [MATH:
   <msub><mrow><mi>t</mi></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow
   ></msub> :MATH]
   ) was then determined. A linear regression was performed using the nine
   data points surrounding
   [MATH:
   <msub><mrow><mi>t</mi></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow
   ></msub> :MATH]
   . The slope of this regression line provided an estimate of the rising
   slope of the calcium signal in response to the sensory stimulus.

   graphic file with name 43587_2025_823_Figa_HTML.gif

   To determine the onset time of the response for each ROI after
   electrical stimulation, we employed an exponential growth model to fit
   the rising phase of the signal. Before reaching its peak, the
   normalized calcium trace can be effectively approximated using the
   following piecewise function:
   [MATH: <mrow><mi>f</mi><mfenced close=")"
   open="("><mrow><mi>t</mi></mrow></mfenced><mo>=</mo><mfenced
   open="{"><mrow><mtable><mtr><mtd
   columnalign="center"><msub><mrow><mi>f</mi></mrow><mrow><mn>0</mn></mro
   w></msub><mo>,</mo><mspace
   width="1.0em"></mspace><mi>t</mi><mo><</mo><msub><mrow><mi>t</mi></mrow
   ><mrow><mi>s</mi></mrow></msub></mtd></mtr><mtr><mtd
   columnalign="center"><msub><mrow><mi>f</mi></mrow><mrow><mn>0</mn></mro
   w></msub><mo>+</mo><mfenced close=")" open="("><mrow><mspace
   width="0.25em"></mspace><msub><mrow><mi>f</mi></mrow><mrow><mi>max</mi>
   </mrow></msub><mo>−</mo><msub><mrow><mi>f</mi></mrow><mrow><mn>0</mn></
   mrow></msub></mrow></mfenced><mfenced close=")"
   open="("><mrow><mn>1</mn><mo>−</mo><msup><mrow><mi>e</mi></mrow><mrow><
   mo>−</mo><mrow><mo>(</mo><mrow><mi>t</mi><mo>−</mo><msub><mrow><mi>t</m
   i></mrow><mrow><mi>s</mi></mrow></msub></mrow><mo>)</mo></mrow><mo>/</m
   o><mi>τ</mi></mrow></msup></mrow></mfenced><mo>,</mo><mspace
   width="1.0em"></mspace><mi>t</mi><mo>≥</mo><msub><mrow><mi>t</mi></mrow
   ><mrow><mi>s</mi></mrow></msub></mtd></mtr></mtable></mrow></mfenced></
   mrow> :MATH]

   The curve fitting procedure was performed using the curve_fit function
   available in the scipy.optimize package. In this context,
   [MATH: <msub><mrow><mi>f</mi></mrow><mrow><mn>0</mn></mrow></msub>
   :MATH]
   and
   [MATH: <msub><mrow><mi>f</mi></mrow><mrow><mi>max</mi></mrow></msub>
   :MATH]
   represent the baseline and maximum normalized calcium signals,
   respectively. The parameter
   [MATH: <mi>τ</mi> :MATH]
   characterizes the timescale of the rising phase, and
   [MATH: <msub><mrow><mi>t</mi></mrow><mrow><mi>s</mi></mrow></msub>
   :MATH]
   denotes the response time—the specific timepoint at which the calcium
   signal initiates its ascent.

   The calcium decay time constant (τ) was estimated by fitting 2.5-second
   calcium trace beginning from the peak to an exponential equation:
   Y = a × exp(−x / τ).

Viral-mediated Mtor heterozygous knockout in Mtor-floxed 5×FAD mice

   mTOR is known to be a regulator of cell growth^[540]35,[541]59, and
   previous studies showed that cell size was indistinguishable between
   the Mtor heterozygous knockout and WT cells^[542]108, which suggests
   that the effects of Mtor knockout on cell size is Mtor gene copy dose
   dependent. Thus, we obtained Mtor heterozygous floxed AD mice to
   achieve conditional Mtor heterozygous knockout, which had no effect on
   cell body size (Fig. [543]6o and Supplementary Fig. [544]10d). To
   achieve global neuronal Mtor heterozygous knockout in Mtor-floxed 5×FAD
   mice, 10 μl of AAV-PHPeB-hsyn-cre-eGFP (Addgene, 105540, titer
   ~1 × 10^13 vg ml^−1) or AAV-PHPeB-CAG-GFP (Addgene, 37825, titer
   ~1 × 10^13 vg ml^−1) was retro-orbitally injected into 6-week-old
   Mtor-floxed 5×FAD mice. To achieve sparse neuronal Mtor heterozygous
   knockout, 1 μl of AAV9-hsyn-cre-2a-tdT (Addgene, 107738, titer
   ~1 × 10^13 vg ml^−1) was diluted with 3 μl of PBS and injected into the
   subarachnoid space of one hemisphere at the level of somatosensory
   cortex in Mtor-floxed 5×FAD mice, as we previously described^[545]31.
   Mouse brains were collected 2 months after virus injection in the
   AAV-PHPeB experiment or at 2.5 months for the
   AAV9-hsyn-cre-2a-tdT-injected mice. Brains were sliced, stained and
   imaged with confocal microscopy as mentioned above and as we previously
   described^[546]31. For sparsely PHP.eB-hSyn-Cre-GFP virus labeling in
   mouse brains, 3 μl of AAV-PHPeB-hsyn-cre-eGFP (Addgene, 105540, titer
   ~1 × 10^13 vg ml^−1) was diluted in 30 μl of PBS and retro-orbitally
   injected.

RNAscope in 5×FAD mice brain slices

   5×FAD mice brains were freshly dissected and immediately froze in
   Tissue-Tek optimal cutting temperature (OCT) compound (Sakura) and kept
   in dry ice with 70% ethanol for 5 –10 minutes and then transferred to
   −80 °C for long-term storage. Frozen brain blocks were sectioned at
   10-μm thickness by cryostat (Leica). RNAscope was performed using an
   RNAscope Multiplex Fluorescent Kit V2 (ACD, 323270) according to the
   fresh frozen tissue protocol. Poly(A) probe (ACD, 318631) or negative
   control probe (ACD, 320871) was used during probe incubation. Before
   counterstain with DAPI and mounting media, Atto 657 NHS ester
   (Millipore, 07376) was diluted 1:100, and brain sections were stained
   for 10 minutes, followed by three-times PBS washes, 5 minutes per wash.
   Negative control samples were used to set the baseline parameters for
   confocal imaging, before imaging the poly(A) probe samples.

   NHS ester was used to label the spheroid halo, because when we
   attempted to perform RNAscope and co-stain with axonal spheroid
   markers, such as PLD3, SMI312, APP, RAGC, ATP9A, and ATP6V0A1, we found
   that these antibodies were not compatible with the RNAscope protocol, a
   well-known limitation of this technique. Therefore, we leveraged the
   knowledge from pan-expansion microscopy^[547]109 that NHS ester can be
   used to non-specifically label tissues and reveal subcellular
   structures using confocal imaging. We applied NHS ester after RNAscope,
   ensuring that the NHS ester staining did not interfere with the poly(A)
   probe signal from RNAscope. Interestingly, in the cortex of 5×FAD mice,
   NHS ester highlighted the neuritic plaque nicely, allowing us to use it
   as a marker for spheroids, especially at the periphery of the halo.

Puromycylation in live mouse brains

   Puromycylation was performed as previously described^[548]110 with a
   few modifications. In brief, 25 mg of puromycin (Sigma-Aldrich, P7255)
   was diluted in 278 μl of DMSO to make the puromycin stock solution.
   Puromycin working solution includes 10 μl of puromycin stock solution,
   10 μl of DMSO and 80 μl of PEG400 (puromycin final concentration at
   9 mg ml^−1). Anisomycin (Sigma-Aldrich, 9789) stock solution was made
   as follows: 20 μl of DMSO was added to 5 mg of anisomycin and
   centrifuged at 200g for 3 minutes. Heat in a 42 °C water bath for
   2–3 minutes, until the pipette completely dissolves. Then, 40 μl of
   PEG400 was added dropwise with agitation. Solution should be kept clear
   with no precipitation. Anisomycin working solution was made as follows:
   30 μl of anisomycin stock solution, 10 μl of puromycin stock solution
   (or DMSO vehicle) and 60 μl of PEG400. To make Torin1 stock solution,
   10 mg of Torin1 was added to 3.292 ml of DMSO and 3.292 ml of PEG400
   (Torin1 final concentration at 2.5 mM). Torin1 working solution was
   made as follows: 30 μl of Torin1 stock, 10 μl of puromycin stock (or
   DMSO vehicle) and 60 μl of PEG400. All the reagents were freshly made
   and checked that there was no precipitation during the experiment. Mice
   craniotomy at the somatosensory cortex was done as we previously
   described^[549]4. After removing dura, vehicle or anisomycin or Torin1
   working solution was topically applied to the cranial window. For
   anisomycin assay, solution was applied for 30 minutes and then quickly
   removed and replaced with anisomycin plus puromycin solution for
   10 minutes. After quick PBS washes, mice were transcardially perfused
   with PBS and 4% PFA. For Torin1 treatment, drugs were incubated for
   2 hours, with reapplication three times to avoid drying. Brains were
   vibratome sectioned at 50-μm thickness. Sections were incubated for
   20 minutes with co-extraction buffer (50 mM Tris-HCl, pH 7.5, 5 mM
   MgCl[2], 25 mM KCl, protease inhibitor (Roche) and 0.015% digitonin
   (Wako Chemicals, 043-21376)). After three rinses with PBS, sections
   were incubated in blocking buffer (0.05% saponin, 10 mM glycine and 5%
   FBS in PBS) for 30 minutes. Then, sections were incubated in blocking
   buffer with puromycin 647 antibody (Millipore, MAB E343-AF647,
   1:1,000), NeuN antibody (Abcam, ab177487, 1:200) or Lamp1
   (Developmental Studies Hybridoma Bank, 1D4B, 1:200) for 72 hours at
   4 °C. Sections were washed with PBS 3 × 10 minutes and then incubated
   with secondary antibodies along with puromycin 647 at 4 °C overnight,
   followed by PBS washes 3 × 15 minutes.

STED imaging

   STED imaging was performed as we previously described^[550]111. In
   brief, human postmortem brain tissues underwent processing using
   immunofluorescence staining and proximity labeling techniques outlined
   in the ‘Proximity labeling in brain tissue’ and ‘Immunofluorescence of
   fixed specimens’ subsections until the stage involving secondary
   antibodies and streptavidin labeling. The axonal spheroids and
   biotinylated proteins were labeled using STED-compatible secondary
   antibody Atto 594 (Sigma-Aldrich) (1:100 dilution) and Atto
   647N–streptavidin (Sigma-Aldrich) (1:100 dilution). Subsequently, the
   tissues were mounted with Prolong Gold (Thermo Fisher Scientific)
   following the user manual and left in the dark at room temperature for
   24–72 hours before imaging. STED imaging was carried out using a Leica
   SP8 STED 3X equipped with a pulsed white light laser (NKT Photonics,
   SuperK Extreme EXW-12) for excitation and a 775-nm pulsed laser for
   depletion (Onefive Katana-08HP). The alignment of excitation and STED
   beams was accomplished using 200-nm Crimson FluoSpheres (Thermo Fisher
   Scientific, F8782). Sample imaging was performed using the following
   parameters: Sequence 1: 594-nm laser was at 1.15 µW. Sequence 2: 646-nm
   laser was at 6.4 µW. Sequence 3: 646-nm laser was at 34 µW. Sequence 4:
   594-nm laser was 14 µW. Sequences 3 and 4: 775-nm STED laser was at
   33 mW.

Samples for focus ion beam/scanning electron microscopy

   Mice brains or fixed postmortem human brains were vibratome sectioned
   into 50-μm thickness as described in the ‘Proximity labeling in brain
   tissue’ subsection^[551]4. Trimmed tissue samples were fixed in 2.5%
   glutaraldehyde and 2% PFA in 0.1 M sodium cacodylate buffer, pH 7.4,
   containing 2 mM calcium chloride for 1 hour and then rinsed in buffer
   and post-fixed in 1% osmium tetroxide and 1.5% potassium ferrocyanide
   for another hour. After rinsing well, the samples were immersed in
   aqueous 1% thiocarbohydrazide for 30 minutes and then well rinsed. They
   were then placed in 1% osmium tetroxide in water for 1 hour at room
   temperature, followed by rinsing in distilled water. An overnight en
   bloc stain in aqueous 1% uranyl acetate was followed by rinsing in
   distilled water, and then the samples were placed into warm lead
   aspartate and kept at 600 °C for 1 hour. After 1 hour of rinsing in
   distilled water, the samples were dehydrated through an ethanol series
   to 100%, followed by 100% propylene oxide. The samples were infiltrated
   with Durcupan (Electron Microscopy Sciences) resin over 2 days and then
   placed in silicone molds and baked at 600 °C for at least 48 hours. The
   resin block was trimmed to a rough area of interest, and the surface
   was cleanly cut. The entire pyramid was carefully removed with a fine
   blade and mounted on an aluminum stub using conductive carbon adhesive
   and silver paint (Electron Microscopy Sciences) and then sputtered with
   approximately 15-nm Platinum/Palladium (80/20) using Cressington HR
   sputter coating equipment (Ted Pella) to reduce charging effects.

   A dual-beam focus ion beam/scanning electron microscopy (FIB/SEM)
   instrument (Zeiss, CrossBeam 550) using a gallium ion source was used
   to mill, and an SE2 secondary electron detector was used to image the
   samples. A SmartSEM (Zeiss) was used to set up initial parameters and
   to find the ROIs by SEM images at 10 kV, 45-μm width and 30-μm height.
   The actual depth was 22 μm with 10 nm per pixel and 10 nm per slice. A
   platinum protective layer was deposited at the ROI with the FIB (30 kV,
   3 nA) to protect the structure and reduce charging. Milling and
   highlighting were done at 30 kV and 50 pA, with a carbon deposit
   (30 kV, 3 nA). A course trench was milled (30 kV, 30 nA), followed by
   fine milling (30 kV, 3 nA), and, for final acquisition, a cuboid the
   area of interest was milled at 30 kV and 300 pA. After milling each
   slice, an image was taken by detecting backscattered electrons of a
   primary electron beam (acceleration voltage of 1.5 kV, imaging current
   of 2 nA and aperture diameter of 100 µm) with a pixel dwell time of
   3 µs Atlas5 (Zeiss) was used for preliminary SEM stack alignment, and
   FIB/SEM image stacks were saved as tiff and MRC files. The images were
   imported into Dragonfly software (Object Research Systems) for further
   alignment, segmentation and three-dimensional (3D) video.

FIB/SEM image annotation and segmentation

   Images from the z-stack at different z-locations were imported into
   APEER (Zeiss). Spheroids and plaques within the images were then
   manually annotated. After annotating 37 images, models were trained to
   predict each object. Then, individual spheroid and plaque segmentation
   models were downloaded and imported into Vision4D 4.1.0 (Arivis) for
   object segmentation. The entire z-stack was then segmented in the
   analysis pipeline via the Deep Learning Segmenter operation with all
   the z-stacks within the dataset. Next, non-specific and overlapping
   annotations were manually corrected using the Draw Objects tool. Object
   color and opacity were modified using the Set Object Style tab to show
   raw data. The z-stack was then played using the Movie Player and
   recorded using Capture.

Image analysis and quantification

   All analyses were processed with FIJI (ImageJ) software, unless
   otherwise described.
    1. Quantification of PLD3 raw integrated fluorescence intensity in
       human brain. After PLD3 immunolabeling, we compared the number and
       intensity of pixels corresponding to the PAAS halo versus the rest
       of the field of view, representing mostly neuronal soma and
       neuropil. For this, we used three AD postmortem brains that had
       been used for PAAS proteomics. Immunofluorescence staining of PLD3
       and thioflavin S staining were performed, followed by confocal
       imaging. Background autofluorescence signals were measured in
       unstained brain slices and subtracted from all subsequent image
       quantifications to better reflect true PLD3 signal. PAAS halos were
       manually circled, and the raw integrated intensity (RawInt) was
       measured. The RawInt was also measured for the whole field of view.
       The sum of RawInt derived from PAAS halos was subtracted from the
       RawInt from the whole field of view. By subtracting the halo RawInt
       from the total RawInt, we obtained a measurement of the PLD3
       labeling outside of plaques, which mainly consists of neuronal cell
       bodies, neuropil and any minimal background fluorescence.
    2. p-mTOR S2448 fluorescence intensity measurement. In human AD or
       no/mild AD postmortem brains, each zoom 1 z-stack image, containing
       SMI312-positive axonal spheroids around amyloid plaques, was
       maximum projected. Then, SMI312-positive spheroid halos were
       circled, and mean fluorescence intensity of the p-mTOR S2448
       channel was measured within the selected circle. In the same field
       of view, regions without spheroids were considered as background.
       Three such background regions were selected and circled, and p-mTOR
       mean intensity was measured. The three ‘background’ p-mTOR mean
       intensity values from each field of view were averaged. Mean
       intensity (p-mTOR dystrophy halo) / mean intensity (p-mTOR
       background) was calculated to represent the p-mTOR expression level
       in each axonal spheroid halo. Three fields of view were quantified
       in each patient with severe AD, and 1–3 fields of view were
       quantified in each patient with no/mild AD. The averaged p-mTOR
       expression level in each patient was used for statistical analysis.
    3. Measurement of the size of individual axon spheroids in human
       iPSC-derived neurons in the Torin1 treatment experiment. SMI312 was
       used to label spheroids, and thioflavin S was used to label amyloid
       plaques. Tiling images were taken in each well from a 96-well plate
       and were maximum projected. For Torin1 treatment before amyloid
       plaque and spheroid formation, individual axonal spheroids were
       circled using the freehand tool in ImageJ, and the circle area was
       measured. The total number of axonal spheroid halos analyzed ranged
       from 50 to 150 within each tilling image. Two technical replicate
       wells were analyzed in each experiment, and three batches of
       experiments were performed for quantification. For Torin1 treatment
       after amyloid plaque and spheroid formation, machine-learning-based
       image analysis software Aivia version 12 (Leica) was used to
       quantify the size and number of spheroids and amyloid plaques as
       well as axon density in an automated fashion. The pixel classifier
       tool was used to classify each channel.
    4. Measurement of the percentage of axonal segments with spheroids in
       human iPSC-derived neurons in the Torin1 treatment experiment. The
       SMI312 staining revealed both axonal spheroids (the spheroid shape)
       and axons (the linear shape), therefore allowing us to recognize
       individual axon segments. To quantify axons with spheroids, we
       traced individual axon segments with linear and continuous signal
       across the z-stacks within the field of view. An axon with one or
       more spheroids formed was defined as axon with spheroid, whereas
       axon segments without spheroids observed within the z-stack were
       defined as axons without spheroids. In Fig. [552]6l, the percentage
       of axons with spheroids was calculated by comparing the number of
       axonal segments with spheroids over the total number of axonal
       segments that were observed within the field of view.
    5. Measurement of human neuron cell body size with or without Torin1
       treatment. iPSC co-cultures were infected by AAV2-CB7-GFP (Addgene,
       105542) at titer ~7 × 10^9 vg ml^−1 1 week before Torin1 and Aβ
       treatment. Cells were stained with NeuN and GFP antibodies. Large
       field tilling imaging was performed in each well. Tilling images
       were maximum projected, and neurons with both NeuN and GFP positive
       signals were measured by size, using the freehand tool in ImageJ.
       Three technical replicate wells were analyzed in each experiment,
       and two batches of experiments were done for quantification.
    6. Individual axonal spheroid size measurement in the
       AAV9-hSyn-cre-2a-tdT infected Mtor-flox 5×FAD mice. Anti-Lamp1
       antibody was used for immunofluorescence staining to showcase the
       spheroid halo around amyloid plaques; thioflavin S was used to
       label amyloid plaques; and anti-RFP antibody was used to reveal the
       tdTomato expression in infected neurons. Tilling images were taken
       at the somatosensory cortex of each animal. Three serial brain
       sections were used for tilling imaging for each mouse. An
       individual spheroid was counted when it was both tdTomato positive
       and Lamp1 positive. The individual spheroid size was measured using
       the freehand tool in ImageJ to circle the outline of spheroids,
       where it had the maximum diameter, followed by measurement of the
       circled area. The total number of axonal spheroid halos analyzed
       ranged from 50 to 150 in each tilling image.
    7. Measurement of spheroid halo size in the AAV-PHPeB-infected
       Mtor-flox 5×FAD experiment. Anti-Lamp1 antibody was used for
       immunofluorescence staining to showcase the spheroid halo around
       the amyloid plaque, and thioflavin S was used to label amyloid
       plaques. Tilling images were taken at the somatosensory cortex of
       each animal. Three serial brain sections were used for tilling
       imaging for each mouse. A customized ImageJ macro was used to
       segment individual Lamp1-positive spheroid halos and amyloid
       plaques. Using a customized MATLAB program, the segmented images
       were processed to measure the area of individual spheroid halos and
       amyloid plaque area, automatically. The spheroid halo area was
       excluding the area in the center occupied by the amyloid plaque.
       The number of axonal spheroid halos and amyloid plaques analyzed
       ranged from 30 to 70 in each tilling image from the Mtor-flox 5×FAD
       experiment.
    8. Measurement of RNA signals within axonal spheroids. The ImageJ
       freehand tool was used to circle axonal spheroid structures labeled
       by Atto 647 NHS ester, and fluorescence intensity from poly(A)
       probe channel or negative control probe channel was measured. For
       measuring puromycin signals within axonal spheroids or neuronal
       cell bodies, similarly, the ImageJ freehand tool was used to circle
       axonal spheroid or cell bodies labeled by Lamp1 or NeuN,
       respectively, and fluorescence intensity from puromycin channel was
       measured.
    9. Measurement of NeuN-positive neuronal cell soma area in
       AAV-PHPeB-infected Mtor-flox 5×FAD mice. A customized CellProfiler
       program was used for automated measurement. In brief, tilling
       images were taken from one hemisphere of the somatosensory cortex.
       Tilling images were maximum projected before importing them into
       CellProfiler (Broad Institute). The NeuN channel was set as the
       primary object and was used as the marker for size measurement.
       Three tilling images were taken from three brain sections of each
       animal. Three animals were used in each group.
   10. Investigation of mTOR heterozygous knockout downstream signaling
       effectors in mTOR-floxed 5×FAD mice. Similarly, a customized
       CellProfiler program was used for automated measurement. Tilling
       images were maximum projected before analysis. To analyze
       fluorescence intensity in the nuclei, we used DAPI staining as the
       primary object and measured signals from the NeuN-positive cells.
       To measure fluorescence intensity from the cell bodies, the NeuN
       channel was set as the primary object and was used as the marker
       for fluorescence intensity measurement. We compared mice injected
       with PHPeB-hSyn-cre-GFP viruses to those injected with control
       viruses PHPeB-CAG-GFP. The littermates and sex were paired for
       comparison. Immunofluorescence intensity of TFEB was measured in
       neuronal nuclei, whereas LC3B, P-p70S6K Thr389 and p70S6K were
       measured in neuronal soma in an automated fashion.

Statistics and reproducibility

   Each experiment was repeated independently for at least three times
   with similar results. Human or mouse samples were grouped by disease
   stages or ages. Mice were paired by littermate and sex, as indicated in
   the figure legends. No statistical method was used to predetermine
   sample size, but our sample sizes were similar to those generally
   employed in the field. No data were excluded from the analyses. The
   investigators were not blinded to allocation during experiments and
   outcome assessment, but we used codes or software to analyze data in an
   automated and unbiased way whenever possible. Excel (Microsoft), Prism
   (GraphPad Software), Qlucore Omics Explorer version 3.6 (Qlucore AB),
   CellProfiler version 4.2.1 (Broad Institute), MATLAB and RStudio
   (4.0.2) were used for data analysis and plotting. Statistical methods
   used and P values are described in the figure legend of each relevant
   panel. All statistical tests were two-sided, including all figures and
   tables in the main text, extended data or supplementary data.

Reporting summary

   Further information on research design is available in the [553]Nature
   Portfolio Reporting Summary linked to this article.

Supplementary information

   [554]Supplementary Figs. 1–12^ (5.3MB, pdf)

   Titles of Supplementary Tables 1–6 and title and caption of
   Supplementary Movie.
   [555]Reporting Summary^ (4MB, pdf)
   [556]Supplementary Table 1^ (12.5MB, xlsx)

   Raw and analyzed proteomics results of PAASs, Lamp1 labeling proximity
   labeling proteomics and neuronal soma in humans and mice.
   [557]Supplementary Table 2^ (14.9KB, xlsx)

   Lists of newly identified and known PAAS proteins as well as details
   and instructions of antibodies and immunofluorescence staining.
   [558]Supplementary Table 3^ (10.9KB, xlsx)

   Proteomic sample information.
   [559]Supplementary Table 4^ (103.5KB, xlsx)

   Pathway enrichment analysis of GO of PAAS proteomes in AD humans and
   mice.
   [560]Supplementary Table 5^ (88.5KB, xlsx)

   IPA signaling pathways of PAAS proteomes in AD humans and mice.
   [561]Supplementary Table 6^ (1.2MB, xlsx)

   GSEA analysis of PLD3-labeled proteomes in humans with AD versus
   unaffected control humans.
   [562]Supplementary Movie^ (30.8MB, mp4)

   A 3D video captured using FIB/SEM from a 12-month-old 5×FAD mouse shows
   spheroids (magenta) filled with a large number of vesicles, located
   around amyloid plaques (cyan).

Acknowledgements