Autophagy-lysosomal dysfunction, intraneuronal amyloidosis, and selective neuron death yield senile plaques in preclinical late-onset Alzheimer’s Disease

Autophagy-lysosomal dysfunction, intraneuronal amyloidosis, and selective neuron death yield senile plaques in preclinical late-onset Alzheimer’s Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Autophagy-lysosomal dysfunction, intraneuronal amyloidosis, and selective neuron death yield senile plaques in preclinical late-onset Alzheimer’s Disease Ralph Nixon, Ju-Hyun Lee, Philip Stavrides, Sandipkumar Darji, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5306901/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The autophagy-lysosomal pathway (ALP) is dysfunctional in Alzheimer’s Disease (AD) although pathogenic consequences remain unclear. Here, we identify exceptionally early ALP dysfunction in neocortical neurons of late-onset sporadic AD (LOAD) brains, leading to selective neuronal death yielding β-amyloid plaques. Proteomic ALP analyses of ROSMAP/Banner datasets revealed selective deficits in vATPase subunits and, in an snRNA database, diminished vATPase transcripts in excitatory neurons but not other cell-types. Biochemical, confocal, and immuno-EM human brain analyses confirm defective neuronal lysosomal clearance and intracellular β-amyloid formation within ER-related membrane tubules. Despite deficient clearance, persistent autophagy induction accelerates profuse buildup of Aβ-positive autolysosomes. In select neurons among broadly affected neocortical populations, extreme autophagic stress and intraneuronal β-amyloidosis cause cell death and transform these neurons into extracellular senile plaques. Thus, LOAD brain recapitulates PANTHOS pattern of ALP dysfunction in mouse AD models that arises from faulty-autolysosome acidification and underlies an intraneuronal (“inside-out”) origin of senile plaques. Biological sciences/Neuroscience/Diseases of the nervous system/Alzheimer's disease Health sciences/Diseases/Neurological disorders/Neurodegeneration Autophagy lysosome acidification late-onset AD amyloid plaque Aβ Alzheimer’s disease LC3 perikaryal blebbing neuronal cell death Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction AD is defined neuropathologically by intracellular aggregates of tau (neurofibrillary tangles) and extracellular (“senile”) plaques composed of focally swollen (dystrophic) neurites, β-amyloid, and hundreds of other proteins 1 – 4 . Disease onset is conventionally marked by the appearance of extracellular β-amyloid deposits in the brain during an asymptomatic (“preclinical” or “biochemical”) stage of the disease 5 . However, beyond the existing knowledge of amyloid precursor protein (APP) metabolic pathways, the antecedent pathobiology within neurons that elevates brain Aβ levels and triggers senile plaque formation in the common late-onset “sporadic” form of AD (LOAD) is unclear. In autosomal dominant inherited forms of AD in which Aβ and APP-βCTFs are over-produced from birth, the delayed emergence of disease until adulthood implies that additional causative clearance deficits are involved. Later prodromal and clinical (“cellular”) phases of disease, detected by rises in surrogate CSF or blood markers of neuronal injury such as neurofilament light subunit (NFL) and tau protein, are believed to reflect the onset of neuron injury from neurotoxic forms of extracellular Aβ/β-amyloid deposits, neuroinflammatory factors, and other responses to senile plaques 6 . This cellular phase results in neuron death that is widespread enough to be measured using conventional histological and stereological methods and coincides with the acceleration of cognitive decline 7 . The underlying cell death mechanisms, which are likely multifactorial and context-dependent 8 remain largely unclarified. Detecting the progressive compromise and possible death of select individual neurons at earlier pre-clinical stages of AD, however, is a technical challenge requiring suitable cell-type specific markers of the underlying pathobiological mechanisms and cell death programs involved. Beyond Aβ/β-amyloid or tau neuropathology, abnormalities of the endosomal-lysosomal (ELP) and autophagy-lysosomal pathways (ALP), the key pathways for production and intracellular clearance of β-amyloid and amyloidogenic proteins, are prominent pathological features of vulnerable neurons in AD 9 – 13 . The early emergence of these ALP and ELP abnormalities and their direct mechanistic links to proteins encoded by AD causative genes (APP and Presenilins 1 and 2) and factors that significantly increase AD risk (e.g. APOE4, aging) suggest their primary importance to AD pathogenesis 13 , 14 . Among its key etiologic actions, BACE1-cleaved C-terminal APP fragments (APP-βCTF or C99), known to be elevated in AD 15 , 16 , are implicated in the unique extreme ALP pathology and neuron death described in brains of mouse models of familial AD (FAD) β-amyloidosis, which emerges at an early “pre-plaque” stage of the disease. At elevated levels, APP-βCTF binding directly to the vATPase complex inhibits its activity, impairing both the lysosomal acidification and clearance of substrates, including APP-βCTF and Aβ 16 . We previously characterized evolving ALP deficits in AD model mice expressing an mRFP-eGFP-LC3 reporter for autophagy-related organelles 11 , 17 . In vulnerable cortical neuron populations, the accumulation of enlarged poorly acidified autolysosomes containing undegraded substrates, including APP-βCTF and Aβ, was associated with a striking deficiency of lysosomal vATPase complex activity and assembly 16 , 18 emerging well before the extracellular deposition of β-amyloid 11 . Moreover, selected neocortical neurons developed a build-up of autophagic vacuoles so extreme that they pack into large blebs protruding from the somal plasma membrane -- a unique pattern termed PANTHOS. Moreover, intraneuronal β-amyloid fibrillar aggregates form within ER membrane tubules of the neuron, culminating in its death and the transformation of its corpse into a senile plaque. These findings in mouse AD models, which support an intraneuronal (“inside-out”) sequence of events in β-amyloid plaque formation, raise critical questions about whether or not they translate to human disease, especially human late-onset AD (LOAD). In the current study, we show in the human LOAD brain that the same pathobiological sequence of events develops by using large-scale multi-omic interrogation of autophagy-lysosomal pathways, confocal microscopy, and multiplex immunocytochemistry with autophagy and APP metabolite markers, ultrastructural analysis and Immuno-Electron Microscopy (IEM) on neocortical biopsies, and additional validating biochemical measurements. Further evidence reveals significantly reduced levels of vATPase complex subunits in the AD brain and reduced vATPase subunit transcription selectively in excitatory neurons, thus supporting an underlying molecular basis of lysosomal acidification dysfunction. These findings suggest new strategies against intraneuronal targets to prevent AD by interrupting the very early lysosomal deficits that may lead to later AD pathogenesis. Results Transcriptomic and proteomic analyses of large AD databases identify early lysosomal acidification and substrate clearance deficits. We reassessed the Autophagy-Lysosome Pathway (ALP) 10 , 19 using the publicly available bulk-transcriptomic, bulk-proteomic, and single-nucleus RNA-seq (snRNA-seq) datasets from human AD brains as described in Methods. Large-scale transcriptomic data were obtained from the dorsolateral prefrontal cortex (DLPFC) region of 241 individuals (Control: N = 86; AD: N = 155) in the Religious Orders Study and Memory and Aging Project (ROSMAP) on AD (synapse.org, SynID: syn14237651). Proteomic data were collected from the DLPFC region of 310 individuals in the ROSMAP (Controls: N = 84; AD: N = 108) and Banner Cohort (Controls: N = 26; AD: N = 92) which identified 8,812 proteins using Tandem Mass Tag (TMT) proteomics 20 . Given the cellular heterogeneity of brain tissue, we further analyzed snRNA-seq datasets from the study by Mathys et al. 21 to investigate cell-type specific gene expression change. This snRNA-seq dataset includes 80,660 single-nucleus transcriptomes from the prefrontal cortex (Brodmann area 10) of 48 individuals from the ROSMAP cohort, with varying degrees of AD pathology (Fig. 1 a). An earlier reported enrichment analysis using conventional GO terms did not detect changes in ALP 20 . Using our curated 57 ALP gene sets comprising 1,096 genes 19 (Supplementary Table 1) to assess ALP in human AD brains more comprehensively, we performed Gene Set Enrichment Analysis (GSEA) on the aforementioned proteomic, bulk RNA-seq, and snRNA-seq data. These gene sets were curated to interrogate steps in the autophagic-lysosomal pathways, including processes such as autophagy induction, autophagy signaling and autophagic vacuole (AVs) formation, transcriptional activators of ALP, mitophagy, lysogenesis, and lysosome function. Our analysis also included the gene sets for monitoring autophagy induction via the assessment of mTOR activation status 19 , 22 , 23 . ALP status was further validated by applying the curated list of 838 unique high-confidence components of ALP (Supplementary Table 1) as defined in the Human Proteostasis Network 24 . To ensure that the majority of proteins were not differentially abundant in a biased manner, we examined the differentially abundant proteome and identified 1,217 proteins with increased levels and 1,711 proteins with decreased levels at FDR < 0.05 (Fig. 1 b) 20 . Most strikingly, our interrogation of the ALP proteome in the AD brain revealed a progressive deficiency of vATPase components essential for lysosomal acidification (Fig. 1 c, f). Levels of 12 of the 14 subunits of the vATPase complex are reduced, coinciding with evidence described below that deficient lysosomal proteolysis causes a profuse build-up of autophagic substrates (Fig. 1 c, d). Notably, most deficient are the membrane-anchored V0 subunits V0a1 and V0c, which along with lowered V0d1, form the platform for the association of the V1 subcomplex regulating vATPase activity (Fig. 1 d). Notably, the muted log2 fold change (log2FC) observed in the bulk proteomics data (Fig. 1 c and the first track of Extended Data Figs. 1 a, 1 b) is attributable to the compression of quantifiable change resulting from TMT (MS2-based) protein quantification. This compression does not impact the precision or directionality of coexpression in relative quantification and is an underestimation of the true fold differences for each protein. Immunoblot analysis, however, confirmed significant reductions in the V0a1 subunit by 51% (0.45 ± 0.11, p < 0.0001) and in the V0d1 subunit by 55% (0.49 ± 0.08, p < 0.0001) in Braak V brains, with similar trends of decline observed in Braak III brains. (Fig. 1 e). Most members of the V1 subcomplex are also lowered in AD brains (Fig. 1 f and Extended Data Fig. 1 a). Compared to the V0 component deficits in immuno-blot analysis, the smaller decreases of V1 subunits reflect in part their relative preservation in the cytoplasm upon dissociation from the complex 16 , making them available for re-assembly. The implied decrease in fully assembled vATPase complex in AD brains compares to that demonstrated in mouse AD models, where an abnormal extent of vATPase disassembly is accompanied by decreased vATPase activity and elevated pH of autolysosomes 11 , 16 . Further single-cell level analysis using the snRNA-seq dataset revealed that the transcripts encoding proteins involved in the vATPase complex and lysosomal acidification, are particularly reduced in excitatory neuronal populations in AD brains, with a more pronounced reduction observed in AD brains at an early disease stage (Fig. 1 f and Extended Data Fig. 1 a). Evidence of functional changes in lysosomes tied to the vATPase abnormalities in LOAD includes lowered Cathepsin D (CTSD)-specific activity (proteolytic activity/unit of CTSD protein) indicating a progressive inactivation of CTSD within lysosome-related compartments beginning at the pre-plaque stage of LOAD in Braak III neocortex (32%: p = 0.0095) and further declining by Braak stage V (53.6% : p < 0.0001) (Fig. 1 g). CTSD-specific activity is lowered in disease states where lysosomal pH rises above their pH optimum, especially if pH rises chronically and partly inactivates cathepsins requiring the most acidic environment for its activity 25 , 26 . Contrasting with the prominent vATPase and clearance deficits, proteins associated with upstream stages of ALP in AD brains are predominantly maintained or elevated. Higher autophagy induction signaling is reflected by broadly lowered levels of mTOR target proteins (Fig. 1 h and Extended Data Fig. 1 b). Elevated proteins include ones involved in autophagosome formation (e.g. ATG3, ATG4, ATG9), chaperone-mediated autophagy (e.g. CLU, HSPB8, BAG3, EEF1A1), docking and fusion of the autophagosome with lysosomes (e.g. VTI1A, ARL8B, VPS41, VPS39), and other proteins involved in autophagy (e.g. CYBB, HDAC2, DAPK, EIF2A) (Fig. 1 h and Extended Data Fig. 1 b). The coincidence of altered ATG family members and depressed levels of mTOR targets (e.g. MRPSs, RPSs, ELF2B1) prompted us to assess mTOR inhibition as an indicator of upstream ALP induction. Indeed, GSEA of the proteomic data uncovered significant decreases in structural (ribosomal) and elongation factors known to decrease with mTOR inhibition 23 (Extended Data Fig. 1 b). This observation aligns with the global suppression of protein synthesis reported in AD brain 27 and suggests that prolonged mTOR inhibition driving upstream ALP upregulation 10 , 28 contributes to the extreme autophagic stress of LOAD 10 . A previous report of markedly deficient Beclin 1 levels in AD brain 29 seemed to conflict with our evidence for competent autophagosome production in the LOAD brain. We resolved the discrepancy by showing that the RIPA buffer, which was used in the earlier investigation to assay only the soluble fraction of brain homogenates, incompletely extracts Beclin 1. Using the same protocol analyzed by Pickford et al. 29 , we found that levels of total Beclin1 and its complex partner Vps 34 in either whole homogenate (Fig. 1 i and Extended Data Fig. 2 c) or the combined RIPA extracted and unextracted fractions (Extended Data Fig. 2 a, b) were unchanged in LOAD. Additionally, we observed no significant correlation between Beclin 1 expression levels and aging in either human (PFC, Brodmann Area 9/10) or mouse brains (hemi-brain) (Extended Data Fig. 2 c, d) indicating that Beclin 1, a key regulator of autophagy initiation, maintains stable expression across different age groups as well. Collectively, our evidence demonstrates persistent upstream autophagy (induction) and autophagosome formation despite reduced downstream lysosomal clearance of autophagy substrates in LOAD brains. Substrate-filled autophagic vacuoles accumulate in neurons despite autolysosome-lysosome fusion. Quantitative immuno-blot analyses of neocortical gray matter homogenates confirmed our -omic evidence of a lysosomal clearance deficit in AD brains. LC3-II levels significantly increased by 33% (p = 0.0320) by the preclinical LOAD Braak III stage and further by Braak V stage (65%, p < 0.0001) compared to non-AD controls (Fig. 2 a). Sections of AD and control prefrontal cortex (Brodmann area 9 and 10) (Supplementary Table 2) were double immunolabeled with antibodies against CTSD to mark lysosomes and LC3 antibody to mark autophagic vacuoles (AV) and were stained with 4',6-diamidino-2-phenylindole (DAPI) to label nuclei, which enabled different ALP vesicle populations to be quantified. Autophagosomes (AP; LC3 + /CTSD - ) and autolysosomes (AL; LC3 + /CTSD + ) were infrequent in perikarya of neocortical neurons in neuropathologically normal control brains (Braak 0-I) (AP: 4.96/neuron, AL: 7.49/neuron) (Fig. 2 b). By comparison in Braak III brains, neocortical neurons display greatly increased numbers of APs (18.93/neuron, p < 0.0001) and ALs (22.53/neuron, p < 0.0001). Sizes of AP and AL vesicles also increased by Braak III stage of AD (AP: 5.13 µm 2 , p < 0.0452; AL: 15.4 µm 2 , p < 0.0001) compared to Braak 0-I stage (AP: 1.48 µm 2 , AL: 7.36 µm 2 ) (Fig. 2 b and Extended Data Fig. 3 a). Numbers of ALs, positive for both LC3 and CTSD, increased progressively with Braak stage, suggesting a compromised substrate clearance in autolysosomes in AD despite fusion with lysosomes. In neuronal somas, LC3/CTSD double-positive autolysosomes begin to emerge in the Braak II stage AD brains (Fig. 2 c), whereas in control brains (Braak I stage), LC3 positive vesicles are rarely observed (Fig. 2 b). Notably, whereas LC3/CTSD-positive vesicle abnormalities emerging in neurons at Braak II stage AD included APs (LC3 + /CTSD - ; green, arrows), as well as enlarged ALs (CTSD+/LC3+; yellow, arrowheads) (Fig. 2 c and Extended data Fig. 3 a), perikaryal AV accumulations were predominantly composed of enlarged ALs by Braak stage III, (Fig. 2 c, bottom and Extended Data Fig. 3 b). Ultrastructural analysis of AD brain biopsies (see Methods) revealed selected neuronal somas containing a mixture of double-membrane APs (blue arrowheads) and single-membrane ALs (red arrowheads) corresponding to the ALP pathology in neurons in Fig. 2 c third panels (Fig. 2 d). Collectively, these findings document a progressive accumulation of undigested material within proliferating ALs, consistent with compromised autophagy flux in human LOAD neocortical neurons similar to ALP abnormalities in AD mouse models. ALP dysfunction in select individual neurons in the LOAD brain evolves into PANTHOS with intraneuronal β-amyloidosis We previously described a unique form of extreme autophagic stress (PANTHOS) in AD mouse models 11 expressing a Thy1-driven mRFP-eGFP-LC3 reporter (tfLC3), which is a probe enabling the in situ characterization of sizes and relative proportions of autophagy-related organelles in neurons based on their pH and biomarker patterns. The dual fluorescence-tagged probe detected incompletely (poorly) acidified autolysosomes (pa-ALs) based on ratiometric measurement of fluorescence signals from eGFP and mRFP. A far red-tagged secondary antibody with pseudo-blue color imaging visualized CTSD-positive lysosomes. CTSD immunolabeling further distinguished unquenched eGFP-positive AVs as neutral pH (CTSD-negative) autophagosomes from autolysosomes that fused with lysosomes but failed to acidify completely, activate hydrolases, and digest autophagic substrates 17 . Appropriate autophagy and amyloid markers were applied at early disease stages before the extensive glial proliferation and plaque burden accumulating at later stages can considerably obscure the ALP patterns when individual neurons are evaluated immunocytochemically. This strategy targeting early disease stages allowed the emergence of ALP-related dysfunction and all key features of PANTHOS lesions to be readily documented in human LOAD. Accordingly, AD prefrontal cortex sections were immunolabeled with antibodies to LC3 and CTSD and, in various experiments, additional antibodies (e.g. 4G8 or 3D6 for Aβ, etc.). Nuclei are stained with DAPI or far-red nuclear dye (e.g. DRAQ5). As described in 5 different mouse AD models, poorly acidified autolysosomes in LOAD neocortical neurons accumulate undegraded substrates, including APP metabolites (e.g. Aβ, APP-βCTF), enlarge and progressively multiply 11 . In select neurons, incompletely acidified autolysosomes massively pack into affected perikarya causing the plasma membrane to bulge with numerous large fluorescently labeled blebs, a unique pattern termed PANTHOS ( p - poisonous, anthos - “flower” in Greek) (Fig. 3 a). Moreover, intraneuronal perinuclear Aβ/β-amyloid immunoreactivity, consisting of bundles of β-amyloid fibrils immunolabeled by a fibrillar amyloid-specific antibody mOC78 (Fig. 3 b). Closely resembling that in AD mouse model brains, a similar sequence of pathological events plays out in post-mortem human LOAD brains leading to PANTHOS profiles appearance beginning at the earliest (Braak II-III) stages of AD in the prefrontal cortex (Brodmann area 10) prior to the appearance of senile plaques in this region (Fig. 3 c). At these early stages, ALP dysfunction and Aβ immunoreactivity are quantitatively widespread across the most disease-vulnerable population of pyramidal neurons, compared to control neurons from age-matched asymptomatic, Braak 0-I controls. Although relatively infrequent in Braak II brains, PANTHOS profiles are nevertheless readily identifiable against the background, which is devoid of confounding microglia with high ALP content. Intra-neuronal 4G8 immunoreactivity is common in affected neurons at the pre-PANTHOS stage within LC3 + /CTSD + autolysosomes when they collect and begin to bulge the cell. At a later stage of compromise, additional Aβ/β-amyloid immunoreactivity concentrates around the nucleus (Fig. 3 c, PANTHOS and same neuron in Extended Data Fig. 4 a top) detected by DAPI and DRAQ5 within the center of a PANTHOS profile (Fig. 3 d, e). We further investigated the possibility that the DAPI signal is not from a nucleus but instead is blue autofluorescence, as suggested in an investigation 30 in which a blocker of autofluorescence was not applied as is considered essential in immunohistofluorescence (IHF) analyses of aging brain 31 and routine in our studies. As expected, under autofluorescence blocking conditions, blue autofluorescence in the UV channel was absent in the region of the nucleus (Extended Data Fig. 4 b, top panels) whereas DAPI staining of a serial adjacent section revealed typical morphology of a fluorescent nucleus (Extended Data Fig. 4 b, bottom panels). Furthermore, in human AD brains, we observed that the 3D6-positive amyloid immunoreactivity was distinctly separate from DAPI-positive nuclei signals within PANTHOS (Extended Data Fig. 4 c). These analyses underscore the importance of autofluorescence quenching to avoid technical artifacts in IHF studies. Serial z-stack confocal microscopic imaging reveals the uniquely huge AV-filled blebs projecting from the plasma membranes of neurons in AD human brains (Fig. 4 a, arrows) identical to those in the 5xFAD mouse model (Fig. 4 b, top panel). EM analysis confirmed the uninterrupted connection between blebs and the perikaryal cytoplasm and identified AVs as the primary constituents of blebs in human LOAD brain (Fig. 4 b, bottom panel), as also described in AD mouse models (Fig. 4 b, top panel) 11 . The evolution of this pathobiology is depicted diagrammatically in Fig. 4 c as compared to a confocal image of PANTHOS documenting perikaryal blebs containing AVs, including different proportions of autophagosomes and autolysosomes varying in degree of acidification. Ultrastructural imaging in the LOAD brain illustrates an intermediate stage of autophagy stress of a neuron before the emergence of PANTHOS. A large collection of autophagosomes (AP) and autolysosomes (AL) within the somal cytoplasm appears to bulge one side of the neuron, corresponding to confocal images and diagrams in Figs. 3 and 4 . Higher magnification reveals mainly immature single-membrane autolysosomes containing substrates at differing stages of incomplete digestion (Fig. 5 a). At the PANTHOS stage (Fig. 5 b), large AV-filled blebs (red arrowheads) project from a central internal region of the soma via narrow necks (light-blue arrowheads), similar to those seen in the neurons of AD mouse model brains 11 . Continuity is evident between AV-filled blebs and the endoplasmic reticulum (ER) tubule network containing amyloid fibrillar aggregates (Fig. 5 b, red arrowheads). Intraneuronal amyloid fibrillar aggregates, with a width (6 ± 1 nm) approximating estimated diameters of β-amyloid fibrils 11 , 32 , accumulate within membrane-bounded structures (light-blue arrowheads) (Fig. 5 c) that, by immuno-EM (IEM), are labeled by anti-ER antibody (calnexin) (Fig. 5 d, yellow arrows and Extended Data Fig. 5 f) and by anti-Aβ/amyloid antibodies (Fig. 5 e and Extended Data Fig. 5 e), similar to those seen in the neurons of AD mouse models (Extended Data Fig. 5 a-c) 11 . Fusion between AVs and the ER membrane network containing β-amyloid aggregates is also seen (Fig. 5 f and Extended Data Fig. 5 d). Coi ncidence of PANTHOS and amyloid plaque at early disease stages in LOAD neocortex. We conducted quantitative analyses of PANTHOS lesions identified by LC3 /CTSD IHF on sections of PFC from Braak II- III stage LOAD brains. Although ALP abnormalities are widespread among layer III-V pyramidal neurons (Fig. 6 a), advance to the extreme PANTHOS stage and death leading to a senile plaque is relatively infrequent, as expected; however, it is significantly more prevalent at Braak stage II (5.55 ± 0.68 mm 2 , n = 6) than at Braak stages 0-I (0.09 ± 0.06 mm 2 , n = 7. p < 0.0001) and progressively increases in frequency in Braak stage III (8.40 ± 0.68 mm 2 , n = 7. p = 0.0056) (Fig. 6 b). The frequencies of β-amyloid lesions and PANTHOS are highly correlated, with almost a 1:1 ratio during the preclinical LOAD stages (Braak II, III) of LOAD (Fig. 6 c, arrows and graph). This correlation reflects the fact that β-amyloid immunolabeling in PFC at these early Braak stages predominantly detects intraneuronal β-amyloid in a plaque-like configuration similar to an extracellular plaque. Upon the death of neurons exhibiting PANTHOS morphology, extracellular plaques with the same general morphologies as the intraneuronal plaque-like structures are seen. However, cross-sectional analysis of mouse AD models at different later ages has shown that once formed, the gradual maturation of the plaque due to glial invasion and clearance of the more protease-susceptible debris, coupled with recruitment of neighboring degenerating neurons into the plaque, can generate plaques of different morphology, size, and amyloid condensation 11 . To further investigate the maturation of PANTHOS lesions and their potential evolution into amyloid plaques in human AD brains, we immunolabeled brain sections with antibodies to the glial fibrillary acidic protein (GFAP), a marker for reactive astrocytes or Iba1, a microglial marker together with CTSD. Due to the technical limitations of the antibody combinations available, we utilized CTSD as a PANTHOS marker. CTSD and LC3 show highly colocalized within PANTHOS blebs, supporting the conclusion that CTSD can serve as an alternative marker for detecting PANTHOS and its characteristic morphology in conjunction with different antibody panels in IHF studies 11 . The association of astrocytes with either ALP-altered neurons or those exhibiting early PANTHOS morphologies is rare, as evidenced by the infrequent presence of GFAP-positive astrocytes (Fig. 7 , pre- and early-PANTHOS), nor a coordinate presence of IBA1-positive microglia and dystrophic neurite-like structures (Extended Data Fig. 6 ), even though early-PANTHOS exhibit amyloid deposits (Fig. 7 b, middle panels) in Braak III brains. In contrast, advanced PANTHOS are surrounded by reactive astrocytes (Fig. 7 b, bottom panels) and microglia as well as dystrophic neurite-like structures in Braak V brains (Extended Data Fig. 6 ). This pattern of late-stage astrocytic and microglial engagement suggests that these phagocytic cells are unlikely to serve as an initiating factor in the formation of PANTHOS in LOAD, but instead may respond to neuronal degeneration or plaque formation, as previously concluded from analyses of AD mouse models 11 . Senile plaques formed from dying PANTHOS neurons in LOAD brains. In the earliest stage of AD (Braak II), antibodies against LC3, CTSD, and amyloid (D54D2) reveal a distinctive pattern of amyloid deposition encircling the nucleus (Fig. 8 a and Extended Data Fig. 4 c) of affected neurons in human LOAD brains. At this stage, PANTHOS associated neurons are similar in size to their less affected neighbors (Fig. 8 a), though the circumference expands as blebs develop evenly in all dimensions (Fig. 8 b). PANTHOS-derived plaques at Braak stage III include both the nuclear ring pattern of amyloid aggregation (Fig. 8 c, stage i ) and also amyloid aggregate network dispersed centrifugally from the perinuclear β-amyloid (Fig. 8 c, stage ii-iv ), as similarly seen in mouse AD models 11 . Aβ immunoreactivity that ultrastructurally corresponds to the amyloid fibril-containing ER tubules (Fig. 5 d) also extends centrifugally creating a network of tubular profiles. This suggests that amyloid deposition becomes more organized and aggressive as Alzheimer's pathology advances, potentially contributing to increased neuronal toxicity and disease progression. These findings highlight the evolution of amyloid deposition within PANTHOS and its contribution to plaque development. Discussion Using a multidimensional analysis in human late-onset sporadic AD (LOAD), we identified progressive dysfunction of the autophagy-lysosome pathway (ALP) in neocortical neurons emerging at the earliest disease stages (Braak II-III) before conventional plaque and tangle pathology develop in this brain region. During this preclinical LOAD stage, as ALP declines broadly across vulnerable neuronal populations, select individual affected neurons advance to a unique state of extreme autophagic stress and morphological distortion (blebbing) of the perikaryon, termed PANTHOS, and associated with plaque-like β-amyloid fibrillar aggregates within an ER-related membrane tubular network. Upon the premature subacute death of these neurons, the corpse yields an extracellular senile (“amyloid”) plaque, a lesion known to be composed of hundreds of proteins 33 , including varied proteins originating from neurons 34 , 35 . Human LOAD thus recapitulates the pattern of ALP-related dysfunction, PANTHOS, intraneuronal β-amyloidosis, and senile plaque formation previously identified in mouse models of AD β-amyloidosis 11 . These findings validate in the most common sporadic late-onset form of AD as an “inside-out” sequence of senile plaque development 36 , 37 . Guided by the pattern of ALP abnormalities revealed in mouse AD models by our in vivo neuronal mRFP-eGFP-LC3 autophagy reporter, we traced evolving ALP dysfunction in LOAD human brains through its terminal PANTHOS stage by using LC3/CTSD double IHF and selected additional markers. Analysis at early Braak stages in the prefrontal cortex enabled the recognition of PANTHOS lesions before extensive invasion by LC3/CTSD-positive glial cells became a significant technical confound. Our results validated in LOAD an exceptionally early emergence of progressive ALP anomalies including massive build-up of enlarged substrate-laden autolysosomes encompassing a very large percentage of apparent total volume of PANTHOS-laden neurons, also characterized by extensive membrane blebbing, and invariable presence of a DAPI-positive neuronal nucleus, culminating in the PANTHOS phenotype in select neurons. Because neurons exhibiting PANTHOS accumulate APP-βCTF and Aβ in autolysosomes and plaque-like β-amyloid fibril bundles within ER or ER-related membrane tubules, they have been commonly misclassified as amyloid plaques presumed to originate from an extracellular seeding process when examined only by β-amyloid IHF or silver stains. During a protracted degenerative process, PANTHOS-positive neurons transition quantitatively from intraneuronal β-amyloid bearing neurons to give rise to the first generation of senile plaques in the neocortex. The same sequence of events can be recognized in late-stage disease although accumulation of slowly eliminated senile plaques and their continuous morphological changes associated with glial clearance processes and local secondary degenerative events are likely making quantitation more difficult. At this stage, glial dying after phagocytosing β-amyloid and related plaque debris could conceivably be a secondary source of senile plaques via a similar inside-out mechanism, although this has not yet been well established 38 . Dystrophic neuritic swellings, which predominantly accumulate immobilized endolysosomal vesicles containing APP secretases and APP metabolites, are an additional potential source of Aβ for diffuse extracellular plaque formation 39 – 41 but these are clearly distinguishable from AV-filled perikaryal blebs encircling the PANTHOS lesion. The possibility of multiple distinct origins of amyloid plaques underscores a potential factor contributing to the heterogeneity of plaque-associated microenvironments of the AD brains 42 . Early ALP dysfunction in APP-based mouse models of AD amyloidosis has been linked to deficient acidification due to declining lysosomal vATPase activity 16 . Our study builds on these earlier genetic and pathological analyses implicating vATPase as a likely molecular target in ALP failure and its pathological consequences in human LOAD 11 , 16 , 43 , 44 . Proteomic analyses of curated ALP gene sets in the human LOAD neocortex, demonstrated deficient levels of most subunits composing the 14 subunit vATPase complex. Most importantly, this includes the key membrane-anchored components of the V0 subcomplex, ATP6V0c, ATP6V0d, and ATP6V0a1, which provide the docking platform for the vATPase-containing V1 subcomplex. The regulated association of the V0 and V1 subcomplexes is a key determinant of vATPase activity and one targeted by etiologic factors in multiple disorders 14 . Immunoblot analyses of the same brain region confirmed deficient levels of the crucial membrane anchoring V0a1 and V0d1 subunits (suitable probes unavailable for ATP6V0c). Moreover, transcripts encoding vATPase subunits in the V1 subcomplex are reduced selectively in excitatory neurons among varied cell types analyzed in AD neocortex 28 . In further support, reduced levels of one or more specific vATPase subunits have been recently reported in AD brain or AD models by others 43 , 45 , 46 . The transmembrane V0a1 subunit, considered the critical anchoring subunit for vATPase assembly 47 , is the principal target of both the inhibitory binding of the complex by APP-βCTF 16 and the impaired V0a1 subunit maturation caused by Presenilin 1 loss of function mutations in early-onset AD 26 , 48 , 49 . Human cell derived FAD neurons 50 , 51 , like transgenic mouse models of FAD 11 , duplicate the build-up of autolysosomes and elevated levels of APP-βCTF that arise from poorly acidified autolysosomes 51 . APP-βCTF elevation in human AD brains 52 likely has a multifactorial basis, including elevated BACE 1 activity 53 , 54 , interactions with cholesterol affecting trafficking 55 , and reduced turnover in lysosomes 16 . Furthermore, pH dysregulation emerging at least as early as the Braak III stage is supported by autolysosomal build-up and enlargement resulting from impaired degradation of substrates, including LC3-II and less active forms of cathepsin D, a multifaceted cathepsin crucial for lysosomal proteolysis and implicated in multiple brain disorders 56 . Lowered cathepsin-specific activity is often seen in disease models where lysosomal pH rises above the pH optimum 57 or, when elevated chronically, inactivates the cathepsins and inhibits their turnover 26 , 58 . In contrast to the extensive lysosomal dysfunction of the LOAD brains, upstream autophagy processes, including induction and autophagosome formation, are competent and likely upregulated, consistent with some earlier studies 20 , 45 . In our proteome analyses of curated gene sets, “autophagic processes” upregulation is supported by elevations of autophagosome components ATGs (ATG3, 4, and ATG9) and Rab proteins (e.g., Rab3D, 6B, 9A, 32) involved in autophagosome biogenesis 59 , 60 . Furthermore, mTOR inhibition, which is connected to autophagy induction via TFEB and other transcript factors regulating ALP 61 , 62 , is evidenced by global decreases of structural (ribosomal) and elongation factor proteins 23 as well as down-regulation in neocortical neurons of transcripts encoding mTOR proteins targeting autophagosome formation and an up-regulation of AMPK 19 , 21 . Earlier reports of a substantial deficit of neocortical Beclin1 in human AD 29 , implying possible lowered autophagosome formation, were not confirmed by multiple lines of our evidence, including re-analysis of the same protocols used in the original report 63 , which both revealed no detectable alterations of total Beclin1 protein levels. We reconciled the disparity by showing that, in the original analysis, total Beclin1 was incompletely and differentially extracted from AD and control brain lysates when RIPA buffer was used for extraction 29 . Moreover, an age-dependent reduction in Beclin 1 levels was not observed in either human or mouse brains, in contrast to a previous study that reported a reduction when using milder extraction conditions 64 . Collectively, therefore, our evidence strongly supports an early underlying lysosomal proteolytic clearance deficit coupled with persisting, if not upregulated, autophagosome production, that drives the uniquely extreme PANTHOS pattern, resulting as a signature of autophagic stress, and its consequences in the most affected neurons from broadly affected populations. In several other neurodegenerative diseases (e.g. Parkinson’s and Huntington’s Disease) autophagy induction is lowered 65 , 66 , which could partially explain more moderate autophagic stress in neurons seen in these disorders that have declines in lysosomal function. Although an extracellular source of Aβ has been conventionally considered the origin for extracellular amyloid plaques 67 , intraneuronal accumulations of Aβ or Aβ oligomers are a well-known early pathological event that precedes amyloid plaque formation in AD 68 – 71 . In late-onset Alzheimer’s disease (LOAD), we observed that β-amyloid fibril bundles initially form within the calnexin-positive ER-related tubules by mechanisms currently under investigation similar to what we discovered in familial Alzheimer's disease (FAD) mouse models 11 . The ER is a site of highly active constitutive autophagic turnover, known as "ER-phagy" 72 , and progressive autophagic impairment may hinder the clearance of the ER, allowing the accumulation of misfolded or aggregated proteins that are poor substrates for the ER-associated degradation (ERAD) pathway. We observed that autophagic vacuoles (AVs) increasingly interact with the ER, with frequent instances of AV-ER fusion and an abundance of calnexin-positive ER-related membrane tubules that are strongly immunoreactive with antibodies to Aβ and β-amyloid fibrillar aggregates in LOAD. These observations suggest an intracellular origin of amyloid and other intracellular debris stemming from the death of PANTHOS neurons that originally contained similar ER membrane-enclosed amyloid. The emergence of ALP dysfunction during the “pre-plaque” stage of AD highlights the significance of early intraneuronal dysfunction marking the earliest phase of the preclinical LOAD stage. This understudied earliest phase of AD represents a critical knowledge gap in our understanding of AD etiology, and of the selective vulnerability of certain neurons during this phase 73 , as well as the origins of many-if not all-extracellular senile plaques. The evolution from PANTHOS to plaque deposition supports a paradigm shift toward a concept of “inside-out” neuron death as capable of initiating the development of plaque 36 , 37 , 74 – 76 . In this model, APP metabolites, notably APP-βCTF and Aβ, exert their most harmful effects within neurons by damaging ALP compartments and impeding lysosomal clearance in particular, which leads to proteostasis collapse, neuronal death, and the subsequent formation of extracellular plaques 77 . We show in this work that the initiation of PANTHOS precedes the activation of glial cells and dystrophic neurites (DNs), indicating that astrocytes and microglia become involved later in the disease. Having well-developed ALP and phagocytic capabilities 78 , glial cells are mobilized to clear extracellular debris as a secondary response in AD that underlies the cellular/immune-associated with plaque and tangle pathology. Evolving PANTHOS lesions have previously been misidentified as plaques due to their morphological similarities to senile plaques, which contain a dense core of Aβ-amyloid fibrils surrounded by dystrophic neurites and reactive glia 79 , 80 . PANTHOS blebs are distinguishable from other structures by their unique rosette configuration and asymmetric neck extensions from the perikaryon plasma membrane. Serial-sectioned neurons undergoing PANTHOS formation in AD mouse brains reveal that these blebs originate from the plasma membrane 11 . Lysosomal markers prominently label PANTHOS profiles, whereas dystrophic neurites exhibit lower lysosomal activity but higher cytoskeletal marker signals, highlighting the structural and functional differences between these entities 11 , 81 . In conclusion, our findings in human sporadic AD brains corroborate and affirm the extensive analyses in mouse models that have highlighted the exceptionally early development of ALP dysfunction stemming in major part from faulty lysosomal acidification. Consistent with the observations in AD mouse models, we document in human AD an essentially identical phenotype of ALP dysfunction associated with PANTHOS and with intraneuronal β-amyloidogenesis and neuron death, yielding extracellular plaque formation. This mechanism, defined by impaired autophagy and lysosomal dysfunction, likely precedes the classical extracellular amyloid seeding, providing new insights into the early intraneuronal origins of AD. Further investigation is necessary to delineate the connection between PANTHOS formation and neuronal subpopulations susceptible to ALP dysfunction, driving neurodegeneration in AD. Online Methods Mouse lines and animal care For TRGL ( T hy-1 m R FP e G FP L C3 ) mouse generation, targeting vector for tfLC3 was constructed by insertion of tfLC3 into Thy1.1 expression cassette 17, 82 . The tfLC3 was crossed with 5xFAD (Tg6799, C57BL/6NTAC), which express mutant human APP and PSEN1 (APP KM670/671NL: Swedish, I716V: Florida, V717I: London, PSEN1 M146L, L286V) 83 then tfLC3/5xFAD mice were studied together with age-matched controls. The Tg2576 mouse line (the B6;SJL. Tg(APPSWE)2576Kha), which expresses mutant human APP (Swedish K670N/M671L) and maintained on a B6;Dba/2F1;SW background. 17, 82 then tfLC3/ Tg2576 mice were studied together with age-matched controls. The mice were maintained in the Nathan Kline Institute (NKI) animal facility and housed in a 12-hour light/dark cycle. All animal experiments were performed according to “Principles of Animal Care” 84 and approved by the Institutional Animal Care and Use Committee (IACUC) at the NKI. Human brains Embedded AD cortical biopsy specimens were provided by Dr. Jerzy Wegiel (New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY, USA), Dr. Xiongwei Zhu (Case Western Reserve University, Cleveland, Ohio, USA), and Dr. George Perry (Univ. Texas at San Antonio, TX, USA) for EM/IEM. Embedded AD Autopsy specimens (PMI<8 hours) were provided by Dr. Thomas Beach (Banner Sun Health Research Institute, Sun City, AZ, USA) for EM/IEM. Paraformaldehyde-fixed tissue blocks and frozen tissues obtained from the prefrontal cortex (Brodmann’s Area 9/10) were kindly provided from Harvard Brain Tissue Resource Center (HBTRC, McLean Hospital, Belmont, MA, USA), Mount Sinai Brain Bank (MSBB, NY, USA), and Emory Alzheimer’s Disease Research Center Dr. Marla Gearing (ADRC/CND, GA, USA) with demographic information outlined in Supplementary Table 2 . Evaluation of proteomic and transcriptomic data from multiple cohorts of AD human brains. In this study, we examined both the transcriptomic and proteomic data reported from multiple cohorts of postmortem human brains , focusing on autophagic pathways and proteolysis. The RNA-seq data (https://doi.org/10.7303/syn14237651.1) were taken from The RNAseq Harmonization Study (rnaSeqReprocessing, synID: syn14237651) which is an AMP-AD consortium effort to harmonize RNAseq data generated through multiple grants. This includes the harmonization of RNA-seq data from 1. Religious Orders Study and Memory and Aging Project (ROSMAP), 2. Mayo RNAseq (MAYO) and 3. Mount Sinai Brain Bank (MSBB) cohorts. Only data from the ROSMAP cohort which are Dorsolateral Prefrontal Cortex (DLPFC), Brodmann area 9 were considered for our analyses and are total of 241 brains (Controls (Braak I-III): N=86 and AD (Braak III-VI): N=155). For the Differential Gene Expression (DGE) analysis, we used Diagnosis.Sex: a colinear model of both Diagnosis and Sex. Proteomic data were derived from Johnson et al., 2022 study 20 and is a set of DLPFC, Brodman area 9 from ROSMAP (Controls (Braak 0-III without dementia): N=84, AD (Braak III-VI with dementia): N=108) and Banner (Controls: N=26, AD: N=92) cohorts that identified 8,812 proteins using Tandem Mass Tag (TMT) proteomics, which was further analyzed for this study. The snRNA-seq data involve the prefrontal cortex (Brodmann area 10) of 48 individuals from ROSMAP with varying degrees of AD pathology (No pathology (CTRL: Braak I-IV with low amyloid): N=24; early-pathology (EARLY: Braak III-V with high amyloid): N=15; late-pathology (AD: Braak V-VI with high amyloid): N=9) across six major brain cell types 21 . According to Mathys et al., early pathology was defined as brains with amyloid burden, but modest neurofibrillary tangles and cognitive impairment; while late pathology as brains with higher amyloid, and also elevated neurofibrillary tangles, global pathology, and cognitive impairment. We used our in-house curated gene sets designed to interrogate all aspects of autophagy-lysosomal pathways coupled with gene sets published elsewhere 19, 23 to perform GSEA/Enrichment analysis on the aforementioned datasets. Antibodies and Reagents LC3 (MBL M152-3, 1/200) was from MBL Intl Corp. Rabbit anti-CTSD (Rudy4, 1/2000), Sheep anti-CTSD (D2.3 1/500) and NFL (21.4, 1/250) were produced in house (Lee et al., 2019). 4G8 (800701, 1/250) was from BioLegend, and 3D6 (ab205341, 1/200) was a generous gift from Dr. Marc Mercken (Janssen Pharmaceutica/Johnson & Johnson, Belgium). mOC78 (ab205341, 1/200) from Abcam. DRAQ5 (65-0880-92, 1/2000) from ThermoFisher Scientific, IbaI (019-19741, 1/250) from Wako. GFAP (3670, 1/500), β-amyloid (D54D2), and Vps34 (4263, 1/1000) were from Cell signaling technology. Beclin-1 (BD612112, 1/1000) from BD Bioscience. V0a1 (13828-1-AP, 1/1000) and V0d1 (18274-1-AP, 1/1000) form ProteinTech. V0C (NBP1-59654, 1/1000) and LIMP2 (NB400-129, 1/1000) from Novus Bio. V1A (ab118326, 1/1000) and V1C1 (ab272594, 1/1000) from Abcam. Actin (A1978, 1/5000) and Thioflavin-S (T1892) from Sigma. Calnexin (AD1-SPA-860-D, 1/500) from Enzo. HRP- linked Rabbit IgG (711-035-152, 1/5000), Mouse IgG (711-035-150, 1/5000), Rat IgG (712-035-150), and Goat IgG (705-035-003) secondary antibodies were purchased from Jackson ImmunoResearch. Prolong Diamond Antifade Mount (P36961), Goat anti-Mouse Alexa 647 (A21235), Goat anti-Rat Alexa 647 (A21247), Goat anti-Rabbit (A21245) Alexafluor 647, and Donkey anti-Rabbit Alexa 405 (A48254), Donkey anti-mouse 488 (A32766), 568 (A10037), Donkey anti-rabbit 488 (A32790), 647 (A32795), Donkey anti-sheep 568 (A21099) secondary antibodies were from ThermoFisher. Mouse on Mouse (M.O.M) detection kit (BMK-2201), normal-donkey (S-2000-20) and normal-goat (S-100) serum blocking solution were from Vector Lab. Western blotting Cerebral cortices from male 5xFAD and WT mouse brain were homogenized with buffer (20mM Tris-Cl, pH 7.4 with 250mM sucrose, 1mM EGTA, 1mM EDTA, 1mM MgCl 2 and protease and phosphatase inhibitor (Roche). The post-nuclear homogenates obtained by centrifugation (1,000 g, 10 min) were further fractionated into cytosolic and membrane/vesicle fractions by high-speed centrifugation (150,000 x g, 50 min), and equal proteins were loaded on a gel. The cerebral cortex from the human brain (0.5g) and mouse hemi brain (0.2g) were homogenized as previously described 85 in a buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 1mM each EDTA, EGTA, and DTT, 250mM sucrose, 1 mM β-glycerophosphate, 1 mM NaF, 0.2 mM NaVaO 4, 5µg/ml each leupeptin, antipain and pepstatin and 1mM each Benzamidine and PMSF). In addition to whole brain homogenate analysis, sequential extraction of Beclin was carried out as described 29, 86 . Briefly, the homogenates were sub-fractionated by centrifugation at 10,000g at 4 o C for 30 min, and supernatant (S-1) was used. The remaining pellet was further solubilized in RIPA buffer (50 mM Tris/HCl pH 7.4; 0.15M NaCl; 5mM EDTA; 1mM EGTA; 0.5% Sodium deoxycholate; 1% NP40 0.1% SDS with a mixture of protease and phosphatase inhibitors) followed by centrifugation at 10,000g for 30 min. The resulting supernatant (S-2) along with S-1 and the pellet (P) solubilized in Laemmli buffer were used for western blotting of Beclin and Vps34. In addition to the extraction described above a small subset of brains was extracted using a protocol employed by Masliah’s laboratory 63 . Brain homogenates were spun at 5,000g for 5 minutes initially to get a buffer insoluble pellet and the supernatants were further centrifuged at 100,000g for 1 hour at 4 o C. After 100,000g spun, supernatants were collected as a cytosolic fraction and the pellets were collected and further sonicated in the homogenizing buffer as a membrane fraction. Three fractions were analyzed for Beclin-I by western blotting with Laemmli buffer. Three fractions were analyzed for Beclin by western blotting. Protein content was determined using the BCA method. Samples were mixed with 2x SDS sample buffer and incubated for 5 min at 100°C. Following electrophoresis on 16% or 4-20 % Tris-glycine gradient gel (Invitrogen), proteins were transferred onto nitrocellulose (for V0a1, v0d1) otherwise 0.45 µm PVDF membranes (Millipore) for detection of all other proteins then incubated overnight in primary antibody. HRP conjugated secondary antibody was added the following morning and incubated for one hour at room temperature. The blot was developed using an Invitrogen ECL kit. Ultrastructural EM analyses Mice were perfused with 2.5% glutaraldehyde, and 2% paraformaldehyde in 0.1 M sodium cacodylate buffer, pH 7.4 (EMS). The brain was removed and sectioned using a vibratome into 50µm or 100µm sections placed in a fixative solution and stored at 4℃. Samples were then treated with 1% osmium tetroxide in 100 mM sodium cacodylate buffer pH 7.4 for 30 minutes, washed in distilled water four times (10 min/wash), and then treated with 2% aqueous uranyl acetate overnight at 4°C in the dark. Samples were then washed and sequentially dehydrated with increasing concentrations of ethanol (20, 30, 50, 70, 90, and 100 %) for 30 min each, followed by three additional treatments with 100% ethanol for 20 min each. Samples were then infiltrated with increasing concentrations of Spurr’s resin (25% for 1 h, 50% for 1 h, 75% for 1 h, 100% for 1 h, and 100% overnight at room temperature), and then incubated overnight at 70°C in a resin mold. For TEM ultrastructural analysis 70 nm sections were cut using a Leica Reichert Ultracut S ultramicrotome and a Diatome diamond knife, placed on grids, and then post-stained with 2% uranyl acetate and lead citrate. Images were taken using a Ceta Camera on a ThermoFisher Talos L120C transmission electron microscope operating at 120kV. Immuno EM The tissue was processed as described above. Sections of 70 nm were cut on a Leica ultramicrotome with a diamond knife. The sections were placed onto carbon formvar 75 mesh nickel grids and etched using 4% sodium metaperidotate for 10 minutes before being washed twice in distilled water and then blocked for one hour. Grids were incubated with either 3D6 (1/2 dilution), 4G8 (1/2 dilution), or Calnexine antibodies (1/10 dilution), at 4 ̊C overnight. The next day grids underwent seven washes in 1xPBS and were then incubated in anti-mouse or anti-rabbit 10 nm gold secondary (1/50 dilution) for 1 hour. After this, the grid was washed seven times in 1xPBS and twice in distilled water. Grids were then silver-enhanced for 5 minutes (Nanoprobes). Grids were finally post-stained with 1% uranyl acetate for 5 minutes followed by two washes in water and then stained with lead citrate for 5 minutes followed by a final two washes in distilled water. Samples were then imaged on a ThermoFisher Talos L120C operating at 120kV. Enzymatic assays in brain lysates: Cathepsin D was assayed at 37 o C at PH 4.0 by measuring the release of amc containing peptide, 7-methoxycoumarin-4-acetyl-Gly- Lys-Pro-Ile-Leu-Phe from 7-methoxycoumarin-4-acetyl-Gly- Lys-Pro-Ile-Leu-Phe-Phe-Arg-Leu-Lys (Dnp)-D-Arg-NH2 (BioMol-Enzo, Plymouth Reading, PA), according to the method of Yasuda et.al. 87 . Assays were performed in white microplates in a total volume of 100 ml of 0.1M sodium acetate buffer pH 4.0 containing 20 mM substrate with and without 3 mg of pepstatin for one hour. The fluorescence released was read in a Wallac Victor-2 Spectrofluorimetric plate reader with a filter optimized for detection of amc standard solution with excitation at 365nm and emission at 440nm. However, instead of using amc standard, a quenched standard 7-methoxycoumarin-4-acetyl-Pro-Leu-OH was used for expressing enzyme activity to account for the release of peptide containing amc instead of free amc. Enzyme activity was expressed as the relative amount of quenched standard released per hour per mg protein.The specific activity of cathepsins was calculated by calculating the ratio of Enzyme activity to the densitometric data obtained from western blots for each enzyme. Confocal laser scanning microscopy Immunocytochemistry was performed as previously described 26 . Animals were anesthetized and perfused with Perfusion Fixative Super Reagent (Electron Microscopy Sciences, 1223SK) followed by a wash with Perfusion Wash Super Reagent (Electron Microscopy Sciences, 1222SK). Brains were dissected and immersed in the same fixative for 24 hrs and then 40 µm sagittal sections were made using a vibratome. Brain sections were further stained with indicated antibody overnight and then visualized with Alexafluor conjugated secondary antibody. Imaging was performed using a plan-Apochromat 20x or 40x/1.4 oil objective lens on an LSM880 laser scanning confocal microscope with the following parameters: eGFP/Alexafluor488 (ex: 488, em: 490-560 with MBS 488), mRFP/Alexafluor568 (ex: 561, em: 582-640 with MBS 458/561), Alexa fluor 647 (ex: 633, em: 640-710 with MBS 488/561/633), DAPI (ex: 405, em: 410-483) with best signal scanning model to exclude crosstalk between each wavelength; Image acquisition with frame (1024x1024) scanning mode with averaging 4 line-scan, speed 6. Thioflavin-S staining: confocal imaged sections were dehydrated and incubated with 1% aqueous Thio-S for 8 minutes. Wash with 80 % ethanol (2 x 3 min), 95 % ethanol (3 min), and ddH 2 0 (3 times). Analyze the slide with the combination of the DAPI/eGFP/mRFP filter set. Human AD brain : 40 µm free-floating sections cut on vibratome from fixed tissue blocks were washed once in 1 x Tris-buffered saline (TBS, pH 7.4) buffer and rinsed twice in ddH 2 O followed by incubation in 70 % (V: V) formic acid for 12 min at 27 ̊C for amyloid staining. Otherwise, sections were only incubated for 30 min at 90 ̊C in R-universal epitope recovery butter (AP0530-500) from Aptum Biologics Ltd to unmask antigens and allowed to cool to 27 ̊C on the bench, followed by 2 x 10 min rinse in TBS buffer. Sections were blocked for 60 min in 20% Normal Horse Serum (V: V) in TBS and incubated with primary antibodies for 24 hrs at 4 ̊C in 4 % Normal Horse Serum (V: V) and 0.1 % Tween-20 for LC3 IHF or 0.3 % Triton X-100 for others in TBS blocking buffer followed by washing 2 x 10 min in 1 x TBS buffer. Incubation in appropriate secondary antibodies (Invitrogen Alexafluor), diluted 1:500 in Blocking Buffer for 2 hrs at 27 ̊C was followed by washing 2 x 10 min in TBS buffer and autofluorescence was blocked by Autofluorescence Blocker (Trueblack Plus, #23014, Biotium) following manufacturers protocol to avoid non-specific blue-autofluorescence. Sections were washed 3 x 5 min at 27 ̊C and stained with DAPI in 0.2 M N 2 APO 4 , 0.1 M citrate buffer, pH 7.5 for 15 minutes. Bioinformatic analyses Differentially expressed genes for the bulk transcriptomics data were determined as those with an estimated FDR below 5% from the original study. The significantly up and downregulated proteins from the original proteomics data 20 were chosen based on the originally reported BH-corrected p-value significance i.e., FDR < 0.05, while the significance for genes from snRNA-seq data was defined with 2-sided Wilcoxon-rank-sum test, FDR0.25, Poisson mixed-model FDR<0.05 as defined in the original paper 21 . Enrichment analysis or more commonly Gene Set Enrichment Analysis (GSEA) was conducted in R (R version 4.3.1) with R/Bioconductor package GeneOverlap (version 1.36.0) (Shen L, Sinai ISoMaM (2023). GeneOverlap: Test and visualize gene overlaps. R package version 1.36.0) which conducts one-sided Fisher’s Exact Test (FET) on gene sets to be tested. The significance of the test was determined based on BH-corrected P-values (adj.p-values or FDR) with alpha of 0.05 unless otherwise mentioned. Quantification and statistical analyses Statistical parameters including the definitions and value of sample size (n), deviations, and p values are reported in the figures and corresponding figure legends. Statistical analyses using Prism 8 (GraphPad Software) were conducted on data originating from at least three independent experimental replicates. Statistical analyses between the two groups were performed by a paired t-test. Statistical analyses involving comparisons among more than three groups were conducted using a one-way ANOVA. Data are expressed as mean ±SEM. Differences were considered significant with p<0.05. The Pearson correlation method was used for correlation analyses. Declarations Acknowledgments This work was supported by NIH P01AG017617 and R01AG062376 to R.A.N. The author sincerely acknowledges Mrs. Swati Jain for assistance in preparing the diagrams and Rosemarie LoFaro for administrative support. We are very grateful to Dr. Tamotsu Yoshimori (Osaka University, Japan) for the mRFP-eEGFP-LC3 construct used in transgenic mice, Dr. Jerzy Wegiel (New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York, USA), Sandra Siedlak (Case Western Reserve University, Cleveland, Ohio, USA) for human AD cortical biopsy specimens, Dr. Thomas Beach (Banner Sun Health Research Institute, Sun City, Arizona, USA) for AD autopsy (PMI<8hrs) brains. Human AD brain from Harvard Brain Tissue Resource Center (HBTRC, McLean Hospital, Belmont, MA), Mount Sinai Brain Bank (MSBB) part of NIH NeuroBioBank, and Dr. Marla Gearing Research Center/Center for Neurodegenerative Disease (ADRC/CND) with support from ADRC grant (P50 AG025688). The results published here are in whole or in part based on data obtained from the AD Knowledge Portal (https://adknowledgeportal.org). Authors’ contributions J.H.L. and R.A.N. were equally responsible for experimental design and data interpretation and mainly contributed to writing and revising the manuscript. J.H.L., P.S., P.J., and M.B. conducted the experiments. P.S.M. conducted CTSD enzyme essay and Beclin-related experiments. D. Y. and C.N.G. performed EM/IEM. S.D. performed omic analysis and data interpretation. P.S., C.B., M.B., and P.S.M. conducted tissue processing and contributed to data interpretation. P.R., E.B.D., N.T.S., and G.P. contributed to the data interpretation. X.Z. provides human AD biopsy specimens. J.P. maintained animals and carried out genotyping. Competing Interest statement All authors declare no competing interests. References Kawai, M. et al. Subcellular localization of amyloid precursor protein in senile plaques of Alzheimer's disease. Am J Pathol 140, 947–958 (1992). Cras, P. et al. Senile plaque neurites in Alzheimer disease accumulate amyloid precursor protein. Proc. Natl Acad. Sci. 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Intracellular amyloid and the neuronal origin of Alzheimer neuritic plaques. Neurobiol Dis 71, 53–61 (2014). D'Andrea, M.R., Nagele, R.G., Wang, H.Y., Peterson, P.A. & Lee, D.H.S. Evidence that neurones accumulating amyloid can undergo lysis to form amyloid plaques in Alzheimer's disease. Histopathology 38, 120–134 (2001). Armstrong, R.A. Plaques and tangles and the pathogenesis of Alzheimer's disease. Folia Neuropathol 44, 1–11 (2006). Ditaranto, K., Tekirian, T.L. & Yang, A.J. Lysosomal membrane damage in soluble Abeta-mediated cell death in Alzheimer's disease. Neurobiol Dis 8, 19–31 (2001). Li, G., Sherchan, P., Tang, Z. & Tang, J. Autophagy & Phagocytosis in Neurological Disorders and their Possible Cross-talk. Curr Neuropharmacol 19, 1912–1924 (2021). Walker, L.C. Aβ Plaques. Free Neuropathol 1, 31 (2020). Critchley, M. Critical Review: THE NATURE AND SIGNIFICANCE OF SENILE PLAQUES. J Neurol Psychopathol 10, 124–139 (1929). Lie, P.P.Y. et al. Post-Golgi carriers, not lysosomes, confer lysosomal properties to pre-degradative organelles in normal and dystrophic axons. Cell Rep 35, 109034 (2021). Hsiao, K. et al. Correlative memory deficits, Abeta elevation, and amyloid plaques in transgenic mice. Science 274, 99–102 (1996). Oakley, H. et al. Intraneuronal beta-Amyloid Aggregates, Neurodegeneration, and Neuron Loss in Transgenic Mice with Five Familial Alzheimer's Disease Mutations: Potential Factors in Amyloid Plaque Formation. J Neurosci 26, 10129–10140 (2006). NIH Laboratory animal welfare; U.S. government principles for the utilization and care of vertebrate animals used in testing, research and training; notice. Fed Regist 50, 20864–20865 (1985). Schmidt, S.D., Jiang, Y., Nixon, R.A. & Mathews, P.M. Tissue processing prior to protein analysis and amyloid-beta quantitation. Methods Mol Biol 299, 267–278 (2005). Jaeger, P.A. et al. Regulation of amyloid precursor protein processing by the Beclin 1 complex. PLoS One 5, e11102 (2010). Yasuda, Y. et al. Characterization of new fluorogenic substrates for the rapid and sensitive assay of cathepsin E and cathepsin D. J Biochem 125, 1137–1143 (1999). Korte, M. & Koster, R.W. Opening the box of PANTHORA in Alzheimer's disease. Signal Transduct Target Ther 7, 344 (2022). Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryTable1Inhousecurated57ALPgenesetsandProteostasisNetwork838genes.pdf SupplementaryTable2.HumanADBrainList1072024.pdf Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5306901","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":373081317,"identity":"aa76a248-2916-487c-afb0-7d5a18e53431","order_by":0,"name":"Ralph Nixon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYBAC+wbmBmYGhsM8QDbjA6K0GBxgBGl5DNLCbECKls8gNpsEcVqOH2x7XMDwWcbgeO+x6sK2w9H8DczHPn7Bo8W+J7HdeAbDbR7JnnNpt2e2Hc6dcYAtebYMHi12DIlt0jxALfwSOWa3eYFaNjDwGDPjc6Ix/0OQlvM8bEAtxURpMZwBtuU42BZmmBbGD/i8f+NhuzGPwXGgX84YS/OcS8+dcZgtmRmPDgaD88nHHvNUHLY3ON5j+JmnzDq3v735MOMPfHqA0QHUCGUyAtkMQCuYeQhqgYM/UK0EbBkFo2AUjIKRBQB8gUr3Vqqs7gAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-5124-1021","institution":"New York University Grossman School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Ralph","middleName":"","lastName":"Nixon","suffix":""},{"id":373081318,"identity":"800294dc-8187-4e42-8941-195dd8eff64d","order_by":1,"name":"Ju-Hyun Lee","email":"","orcid":"https://orcid.org/0000-0002-0280-8375","institution":"Nathan Kline Institute for Psychiatric Research","correspondingAuthor":false,"prefix":"","firstName":"Ju-Hyun","middleName":"","lastName":"Lee","suffix":""},{"id":373081319,"identity":"1757c6c5-8b44-4eec-8366-ab386825e4b8","order_by":2,"name":"Philip Stavrides","email":"","orcid":"","institution":"Nathan S. 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Kline Institute for Psychiatric Research","correspondingAuthor":false,"prefix":"","firstName":"Pureum","middleName":"","lastName":"Jeon","suffix":""},{"id":373081328,"identity":"b3f99954-6cbb-4d06-8f96-4e31965a278e","order_by":11,"name":"James Peddy","email":"","orcid":"","institution":"Nathan Kline Institute for Psychiatric Research","correspondingAuthor":false,"prefix":"","firstName":"James","middleName":"","lastName":"Peddy","suffix":""},{"id":373081329,"identity":"eea43a0c-2b69-4143-a2b9-cef8ce8900ad","order_by":12,"name":"Xiongwei Zhu","email":"","orcid":"https://orcid.org/0000-0003-2092-6508","institution":"Case Western Reserve University","correspondingAuthor":false,"prefix":"","firstName":"Xiongwei","middleName":"","lastName":"Zhu","suffix":""},{"id":373081330,"identity":"b6e37bb2-66c4-48a3-bfd1-d70e0f703102","order_by":13,"name":"George Perry","email":"","orcid":"https://orcid.org/0000-0002-6547-0172","institution":"University of Texas at San Antonio","correspondingAuthor":false,"prefix":"","firstName":"George","middleName":"","lastName":"Perry","suffix":""},{"id":373081331,"identity":"643331a2-e163-466c-adda-84f149144caf","order_by":14,"name":"Eric Dammer","email":"","orcid":"https://orcid.org/0000-0003-2947-7606","institution":"Emory University","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"","lastName":"Dammer","suffix":""},{"id":373081332,"identity":"463638f3-8b95-4758-9e18-cb946ede4958","order_by":15,"name":"Nicholas Seyfried","email":"","orcid":"https://orcid.org/0000-0002-4507-624X","institution":"Emory University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Nicholas","middleName":"","lastName":"Seyfried","suffix":""}],"badges":[],"createdAt":"2024-10-21 20:30:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5306901/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5306901/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68235859,"identity":"d74be198-4c9f-4944-937e-d07e9ccd6695","added_by":"auto","created_at":"2024-11-05 07:01:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":591396,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscriptomic and proteomic analyses of ALP identify early deficits of lysosomal acidification and substrate clearance in human AD brains. a.\u003c/strong\u003eStudies used for \u003cem\u003ein-silico\u003c/em\u003e investigation of ALP. The tissue analyzed for the original studies is denoted by the blue area shown within the brain which indicates the Dorso-Lateral Pre-frontal Cortex (DLPFC), Brodmann area 9 for transcriptomics and proteomics, and prefrontal cortex, Brodmann area 10 for snRNA-seq. \u003cstrong\u003eb.\u003c/strong\u003e A volcano plot shows differentially abundant proteins in AD brains compared to those in control DLPFC brains from the proteomics cohort. Red dots represent significantly upregulated proteins, blue dots represent significantly downregulated proteins, and grey dots represent unchanged proteins. Significance is determined at an adjusted p-value \u0026lt; 0.05 (FDR \u0026lt; 5%) using the Benjamini-Hochberg multiple test correction. The black horizontal line is a cutoff of significance at FDR \u0026lt; 5%. Purple and black lettering are related to upstream and downstream/clearance of ALP-related proteins, respectively. \u003cstrong\u003ec.\u003c/strong\u003eThe heat map shows Log2FC as the color of tiles for AD compared to the control for the proteomics cohort for vATPase complex proteins. The asterisks indicate different levels of significance for each protein for AD vs control comparison. Adj. p-value (BH-corrected) *\u0026lt;0.05, **\u0026lt;0.01, ***\u0026lt;0.005. \u003cstrong\u003ed\u003c/strong\u003e. vATPase complex with significantly decreased subunits in proteomic analysis colored blue. \u003cstrong\u003ee\u003c/strong\u003e. Decreased levels of vATPase V0 subunits in AD brain lysates. (n= 6 (Braak 0-I), 6 (Braak III), 6 (Braak V). Significance is determined by one-way ANOVA.\u003cstrong\u003e f.\u003c/strong\u003eHeatmap showing Log2FC as color of tiles for gene sets related to ALP downstream/clearance events for AD versus control comparison from the proteomics and snRNA-seq cohorts. The asterisks indicate levels of significance and represent adj.p-value (BH-correction). Proteom. denotes proteomics. Adj.p-Val *\u0026lt;0.05, **\u0026lt;0.01, ***\u0026lt;0.005. \u003cstrong\u003eg\u003c/strong\u003e. CTSD in an abnormally lowered activity state accumulates in AD. CTSD-specific activity decreased at Braak III stage (n=14, 67.87±5.59, \u003cem\u003ep\u003c/em\u003e=0.0095) and further in Braak V brains (n=16, 46.43±4.95, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001) compared to Braak 0-I (n=8, 100±11). CTSD activity decreased at Braak III stage (n=14, 74.91±5.37, \u003cem\u003ep\u003c/em\u003e=0.0378) and further in Braak V brains (n=16, 63.92±5.37, \u003cem\u003ep=\u003c/em\u003e0.0014) versus Braak 0-I (n=8, 100±8.57). CTSD protein levels increased at Braak V stage (n=14, 1.39±0.05, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001) but not in Braak III brains (n=16, 1.09±0.04, \u003cem\u003ep\u003c/em\u003e=0.5574) compared to Braak 0-I (n=8, 1±0.03). \u003cstrong\u003eh.\u003c/strong\u003eHeatmap showing Log2FC as color of tiles for gene sets related to upstream events of ALP for AD versus control brains from the proteomics and snRNA-seq cohorts. The asterisks (“*”) and plus (“+”) sign indicate levels of significance and represent adj. p-value (BH-correction). Proteom. denotes proteomics. Adj.p-Val +\u0026lt;0.1, *\u0026lt;0.05, **\u0026lt;0.01, ***\u0026lt;0.005. \u003cstrong\u003ei\u003c/strong\u003e. Representative immunoblot analysis shows levels of Beclin and Beclin complex protein Vps34 are not altered in human AD brain lysates (n= 9 (Braak 0-I), 9 (Braak III), 10 (Braak V). Significance is determined by one-way ANOVA.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/9b76689b585de554be3ed74b.png"},{"id":68236811,"identity":"c3fe3349-e6d8-4689-9941-df3a4448dbc5","added_by":"auto","created_at":"2024-11-05 07:17:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":996064,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProgressive AV accumulation and lysosomal enzyme activity decline in human LOAD brains. a.\u003c/strong\u003e Autophagy marker LC3-II levels in control Braak 0-1 brains (n=8, 1±0.06) increase progressively by Braak III stage (n=14, 1.33±0.08, \u003cem\u003ep\u003c/em\u003e=0.0320) and further in Braak V brains (n=14, 1.65±0.08, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001). \u003cstrong\u003eb.\u003c/strong\u003e Quantitative confocal analysis of human AD neocortical brain sections from Braak stage 0-I (control) and stage III brains double-immunolabeled with antibodies against LC3 and CTSD (see Methods). Respectively, both median number and total occupied areas of autophagosomes (AP, LC3\u003csup\u003e+\u003c/sup\u003e/CTSD\u003csup\u003e-\u003c/sup\u003e vesicles, green) increase from Braak 0-1 stage (4.96/neuron; 1.48 um\u003csup\u003e2\u003c/sup\u003e) to Braak stage III (8.93/neuron, p\u0026lt;0.0001; 5.13 um\u003csup\u003e2\u003c/sup\u003e, p\u0026lt;0.0001). Autolysosomes (AL, LC3\u003csup\u003e+\u003c/sup\u003e/CTSD\u003csup\u003e+\u003c/sup\u003e vesicles, yellow) greatly increase in number and total area from Braak 0-1: 7.49/neuron; 7.36 um\u003csup\u003e2\u003c/sup\u003e) to Braak stage III (22.53/neuron, p\u0026lt;0.0001; 15.4 um\u003csup\u003e2\u003c/sup\u003e,\u003csup\u003e \u003c/sup\u003ep\u0026lt;0.0001). n= 95 neurons from 4 brains (Braak 0-I), 58 neurons from 4 brains (Braak III). Significance was determined by one-way ANOVA.\u003cstrong\u003e c.\u003c/strong\u003e Higher magnification confocal microscope images of neurons from neocortical layer V neocortex at Braak 0-I (control) and early stage II- III brains AD brains double- immunofluorescence labeled with antibodies against LC3 and CTSD and co-stained with the nuclear marker DAPI. Images depict stages in the progression of ALP compromise in pyramidal neurons prior to conversion to the extreme PANTHOS morphology illustrated in \u003cstrong\u003eFig. 3\u003c/strong\u003e. Arrows denote CTSD-negative autophagosomes (green) and arrowheads denote CTSD-positive autolysosomes (yellow). Scale bar: 20 µm. \u003cstrong\u003ed.\u003c/strong\u003e Representative EM image of APs and ALs accumulation in affected neurons of biopsy human AD brains (blue-arrowheads: autophagosomes, red-arrowheads: autolysosomes) matches the similar pathology in the IHF image of \u003cstrong\u003eFig. 3c\u003c/strong\u003e third panels. Scale bar 5 µm.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/ea2cf8e3145beb833cd1cc78.png"},{"id":68235863,"identity":"57672ebe-a9a3-4519-9be4-275c00492d74","added_by":"auto","created_at":"2024-11-05 07:01:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":818402,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvolution of ALP dysfunction to PANTHOS and intraneuronal ß-amyloidosis in LOAD human brains versus 5xFAD mice. a. \u003c/strong\u003eProgression from healthy appearing state to stages of pre-PANTHOS and PANTHOS neurodegenerative morphology shown in representative images of\u003cstrong\u003e \u003c/strong\u003eneocortical\u003cstrong\u003e \u003c/strong\u003eneurons immunolabeled with antibodies to the lysosome (CTSD) marker (pseudo blue) and amyloid-β (4G8) (cyan) in 2.7-month-old 5xFAD/TRGL expressing mRFP-eGFP-LC3 mice. In healthy neurons, LC3-positive APs rapidly fuse with CTSD-positive lysosomes (blue) forming ALs (purple in merged image) as eGFP fluorescence is quenched by acidification. Substrates, including β-amyloid, are degraded. Pre-PANTHOS ALP pattern detected in a large subpopulation of neocortical neurons is evidenced by accumulations of enlarged poorly acidified-ALs (pa-ALs) (white) reflected by unquenched eGFP and mRFP and blue fluorescence that is preserved in less acidic conditions. ALs enlarge as poorly degraded substrates, including 4G8 -positive Aβ/β-amyloid and APP-βCTF peptides, accumulate. At the PANTHOS stage, pa-ALs build up massively and become densely packed large projecting plasma membrane blebs. In addition, Aβ (4G8) immunoreactivity (IR) localizes in AVs and concentrated IR develops centrally around the nucleus. Scale bar 20 µm. \u003cstrong\u003eb.\u003c/strong\u003e Similar PANTHOS morphology in a 12-month-old Tg2576/TRGL brain section depicting TRGL (mRFP-eGFP-LC3) and lysosome (CTSD) marker as in panel \u003cstrong\u003ea\u003c/strong\u003e but 4G8 antibody is replaced by labeling with mOC78, an antibody against specifically the fibrillar form of β-amyloid. Scale bar 20 µm. \u003cstrong\u003ec.\u003c/strong\u003e Corresponding stages of ALP dysfunction and intraneuronal β-amyloidosis in neurons in sections from LOAD neocortex at Braak stage III which are triple-immunolabeled with antibodies against LC3 (green), CTSD (red), and β-amyloid (4G8, blue). The pathological stages of progressive ALP dysfunction, PANTHOS morphology, and intraneuronal β-amyloidosis in human AD closely resemble those in mouse AD models (panels \u003cstrong\u003ea, b\u003c/strong\u003e). Scale bar 20 µm. \u003cstrong\u003ed-e.\u003c/strong\u003e Representative IHF images of LC3/CTSD-positive PANTHOS in AD human brains counterstained with (\u003cstrong\u003ed\u003c/strong\u003e) DAPI or \u0026nbsp;(\u003cstrong\u003ee\u003c/strong\u003e) DRAQ5 which is the deep-red spectrum (\u0026gt;665 nm) confirm the invariable presence of a central nucleus at PANTHOS stage. Scale bar 10 µm. \u003cstrong\u003ef.\u003c/strong\u003e Intraneuronal perinuclear accumulation of Aβ (4G8) IR within a PANTHOS neuron in a 2.3-month-old 5xFAD/TRGL mouse brain showing the merged fluorescence of mRFP-eGFP-LC3 and co-immunolabeling with CTSD and Aβ (4G8) antibodies. Scale bar 20 µm. \u003cstrong\u003eg.\u003c/strong\u003e In the AD human brain, intraneuronal β-amyloidosis in PANTHOS lesions closely resembles that in mouse models when neocortical sections are triple-immunolabeled with antibodies to LC3, CTSD, and Aβ (4G8). Scale bar 20 µm.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/544440c228d6131d4573fce7.png"},{"id":68236615,"identity":"a4673c41-9b18-49b7-b7e9-60ec8f0c8ccb","added_by":"auto","created_at":"2024-11-05 07:09:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":799459,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUnique features of PANTHOS profiles seen in mouse AD models are recapitulated in human LOAD brains. a.\u003c/strong\u003e Serial z-stacked confocal image (1 µm thick) of a human AD PANTHOS lesion details the unique extensive perikaryal blebbing of PANTHOS, as revealed by LC3 and CTSD co-immunolabeling. Large blebs are filled with LC3/CTSD-positive autolysosomes and/or LC3-positive/CTSD-negative APs projecting centrifugally from the soma via tapered neck regions (arrows). \u003cstrong\u003eb. \u003c/strong\u003eUltrastructure of PANTHOS profiles from a neuron in the human AD brain (layer V, Brodmann area 9, Braak III stage) (bottom panel)\u0026nbsp; and a similar profile from a 5xFAD/TRGL mouse model (top panel), each demonstrating similar AV-filled blebs extending from the central cytoplasmic region of the neuron containing the membrane tubular network and shown\u0026nbsp; (e.g. \u003cstrong\u003eFig. 5\u003c/strong\u003e) to abundantly accumulate fibrillar β-amyloid. Red arrowheads outline the boundaries of the peripheral plasmalemmal blebs. Scale bar 20 µm. \u003cstrong\u003ec.\u003c/strong\u003e Diagrams in panels \u003cstrong\u003eFig. 3a-c \u003c/strong\u003edepict PANTHOS formation. Left panel: Accumulated acidification-deficient ALs migrate toward the periphery, causing the plasma membrane to bulge and form AV-filled blebs. Middle panel: internally in still viable PANTHOS neurons, Aβ and APP-βCTF accumulate with AVs, and β-amyloid fibrillar aggregates form in a tubular network surrounding the nucleus. Right panel: Example of PANTHOS in the still intact neuron of a 5xFAD mouse expressing mRFP-eGFP-LC3 autophagy reporter. Modified from Lee J-H, Nat Neurosci. \u003csup\u003e11\u003c/sup\u003e and Korte M, Signal Transduct Targeted Ther \u003csup\u003e88\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/ef14c804f5e55adf364698ab.png"},{"id":68236812,"identity":"efa60c9f-ecbf-4b36-b5e8-e6db1174e90c","added_by":"auto","created_at":"2024-11-05 07:17:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1189170,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUltrastructure of pre-PANTHOS and PANTHOS in human LOAD brains. a. \u003c/strong\u003eRepresentative transmission electron microscopy images of pre-PANTHOS and PANTHOS\u003cstrong\u003e \u003c/strong\u003efrom biopsied Alzheimer's brain. Panel \u003cstrong\u003ea \u003c/strong\u003edepicts an affected neuron at an intermediate stage of autophagy stress (pre-PANTHOS), corresponding in staging specificity to confocal images in \u003cstrong\u003eFig. 3\u003c/strong\u003e. Compared to an adjacent typical healthy appearing neuron lacking ALP pathology, the ultrastructure of the affected neuron reveals collections of autophagosomes (AP) and autolysosomes (AL) within the somal cytoplasm, in this case, appearing to bulge one side of the neuron. At higher magnification, the right panel confirms the morphological identities of these ALP organelles. \u003cstrong\u003eb\u003c/strong\u003e. At the PANTHOS morphology stage, large AV-filled blebs (red arrowheads in the right panel) projecting via narrow tapering necks from the central internal region of the soma (light-blue arrowheads-left side), similar to blebs projecting from the surface of a 3D-reconstructed neuron in a mouse model of AD-related β-amyloidosis \u003csup\u003e11\u003c/sup\u003e. Scale bar 2 µm. \u003cstrong\u003ec\u003c/strong\u003e. Intraneuronal membrane-bound amyloid lesions (light-blue arrowheads) denote the membrane boundary of amyloid lesions. Scale bar 1 µm. \u003cstrong\u003ed.\u003c/strong\u003e IEM images of human LOAD brains demonstrating accumulating intraneuronal membrane-bound Aβ/β-amyloid which is positively labeled by anti-ER antibody (calnexin). Scale bar 1 µm. \u003cstrong\u003ee.\u003c/strong\u003e Representative IEM image from human LOAD brain demonstrating 4G8-positive intraneuronal membrane-bound Aβ/β-amyloid accumulation. Scale bar 500 nm. \u003cstrong\u003ef\u003c/strong\u003e. A central tubular network containing β-amyloid appears to have plausibly elongated in part from the fusions of cytoplasmic AVs in AD human brains. AV: autophagic vacuole, ER: endoplasmic reticulum, MITO: mitochondria. Scale bar 500 nm.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/9986ebfd810afaddc57f68a9.png"},{"id":68235860,"identity":"c4cb6b17-01d3-4bc5-be80-406871c8e713","added_by":"auto","created_at":"2024-11-05 07:01:41","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1175617,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePANTHOS frequency in human AD brains at early Braak stages.\u003c/strong\u003e \u003cstrong\u003ea.\u003c/strong\u003e Low magnification images of brain sections co-immunolabeled with antibodies to LC3 and CTSD reveal PANTHOS profiles in early AD human brains (arrows) confirmed by their typical morphologies at higher magnification relative to healthy neurons and to neurons exhibiting varying severities of ALP pathology prior to development of PANTHOS stage. Scale bar 200 µm. \u003cstrong\u003eb.\u003c/strong\u003e Quantitative analysis of PANTHOS number per square millimeter (mm\u003csup\u003e2\u003c/sup\u003e) in sections at low magnification from LOAD brains at Braak stages II versus III documents an increasing frequency of PANTHOS lesions at these successive early disease stages. n=7 (Braak 0-I), 6 (Braak II), and n=7 (Braak III) brains.\u003cstrong\u003e c.\u003c/strong\u003e Low magnification images of brain sections co-immunolabeled with antibodies to CTSD and 4G8 reveal a correlation between PANTHOS profiles and β-amyloid lesions in early AD human brains (arrows). \u003cstrong\u003ed.\u003c/strong\u003e Frequency of β-amyloid lesions (4G8) as a ratio of the frequency of PANTHOS profiles identified by CTSD co-immunolabeling, morphology, and lesion size in LOAD brains reveals a high nearly 1:1 coincidence (colocalization and frequency) (Braak II: 96.8 % and III: 81.8 %). 4G8 positive structures counted: n=100 (Braak 0-I from 3 brains), 125 (Braak II from 3 brains), and 165 (Braak III from 3 brains), reflecting the fact that β-amyloid immunolabeling in PFC at these early Braak stages is predominantly detecting intraneuronal β-amyloid in a plaque-like configuration. Arrows denote PANTHOS. Scale bar 500 µm.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/2b044396b1d4e656aa497867.png"},{"id":68235865,"identity":"7b9f64c4-c745-4223-8448-ea800b420d37","added_by":"auto","created_at":"2024-11-05 07:01:41","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1245939,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePANTHOS neuron proliferation with glia in the brain of human AD patients. a. \u003c/strong\u003eThe brain of an individual with early-stage AD (Braak III) was subjected to staining using nucleus (DAPI), amyloid (D54D2), glia (GFAP), and PANTHOS (CTSD) markers. Arrows highlight the presence of PANTHOS and yellow arrowheads denote pre-PANTHOS in this area. Scale bar 200 µm. \u003cstrong\u003eb.\u003c/strong\u003e The enlarged neuron of the square marked pre-PANTHOS neuron, early-PANTHOS, and advanced-PANTHOS in panel\u003cstrong\u003e a\u003c/strong\u003e. Infrequent association of GFAP-positive astrocytes occurs in both pre-and early-PANTHOS stage, whereas advanced PANTHOS are surrounded by reactive astrocytes in LOAD brains. Scale bar 20 µm.\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/c5577284bca66a1196311977.png"},{"id":68235861,"identity":"65a69ea8-3fa5-4379-b6d2-767361cb7cfb","added_by":"auto","created_at":"2024-11-05 07:01:41","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":899353,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProgressive maturation of PANTHOS in LOAD brains: transition to extracellular amyloid plaques of varying morphology. a.\u003c/strong\u003eLC3/CTSD positive PANTHOS with amyloid ring adjacent to amyloid-negative neuron displaying ALP pathology at a “pre-PANTHOS” level in human AD brain. Scale bar 20 µm. \u003cstrong\u003eb.\u003c/strong\u003e In Braak II brains, amyloid deposits marked by D54D2 are found surrounding the nucleus within LC3/CTSD positive PANTHOS (top two panel sets). In Braak III brains, along with PATHOS showing amyloid deposits around the nucleus, a more dispersed network of amyloid was observed (bottom panel). Scale bar 20 µm. \u003cstrong\u003ec. \u003c/strong\u003eMultiple intraneuronal β-amyloid immunoreactivity patterns in human AD brains\u003cstrong\u003e.\u003c/strong\u003e PANTHOS co-immunolabeled using CTSD and Aβ (3D6) antibodies on sections from the preclinical LOAD stage (Braak II, III) of human AD brains reveals sequential events in plaque development. In the early stages of PANTHOS, 3D6-positive amyloid coronas formed around neurons. These amyloid accumulations were primarily confined to the intracellular space, indicative of the initial phase of amyloid deposition (stage \u003cem\u003ei-ii\u003c/em\u003e). As PANTHOS progresses, the amyloid network becomes more dispersed. This network encircled perikaryal blebs and extended beyond the neurons, overlapping with the conversion to extracellular lesions. During this transition, a significant loss of neuronal structural integrity was observed (stage \u003cem\u003eiii-iv\u003c/em\u003e). Scale bar 20 µm.\u003c/p\u003e","description":"","filename":"Fig8.png","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/59043d689769bfca7f7cec67.png"},{"id":90440244,"identity":"9669526d-430d-4d7d-83e8-c59a0c6afb25","added_by":"auto","created_at":"2025-09-02 18:08:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10471330,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/1494d09b-b354-4933-a6a5-fc01ad10bd98.pdf"},{"id":68235869,"identity":"32cdd1ae-188e-4d02-8b63-3d3b4586116a","added_by":"auto","created_at":"2024-11-05 07:01:41","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":226160,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTable1Inhousecurated57ALPgenesetsandProteostasisNetwork838genes.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/133bb23517c68778aa68109d.pdf"},{"id":68236617,"identity":"aa75898c-fef6-4235-b440-0a2d800bf882","added_by":"auto","created_at":"2024-11-05 07:09:41","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":150236,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.HumanADBrainList1072024.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5306901/v1/a8329a5d15fc02735cd8ab09.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Autophagy-lysosomal dysfunction, intraneuronal amyloidosis, and selective neuron death yield senile plaques in preclinical late-onset Alzheimer’s Disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAD is defined neuropathologically by intracellular aggregates of tau (neurofibrillary tangles) and extracellular (\u0026ldquo;senile\u0026rdquo;) plaques composed of focally swollen (dystrophic) neurites, β-amyloid, and hundreds of other proteins \u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Disease onset is conventionally marked by the appearance of extracellular β-amyloid deposits in the brain during an asymptomatic (\u0026ldquo;preclinical\u0026rdquo; or \u0026ldquo;biochemical\u0026rdquo;) stage of the disease \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, beyond the existing knowledge of amyloid precursor protein (APP) metabolic pathways, the antecedent pathobiology within neurons that elevates brain Aβ levels and triggers senile plaque formation in the common late-onset \u0026ldquo;sporadic\u0026rdquo; form of AD (LOAD) is unclear. In autosomal dominant inherited forms of AD in which Aβ and APP-βCTFs are over-produced from birth, the delayed emergence of disease until adulthood implies that additional causative clearance deficits are involved.\u003c/p\u003e \u003cp\u003eLater prodromal and clinical (\u0026ldquo;cellular\u0026rdquo;) phases of disease, detected by rises in surrogate CSF or blood markers of neuronal injury such as neurofilament light subunit (NFL) and tau protein, are believed to reflect the onset of neuron injury from neurotoxic forms of extracellular Aβ/β-amyloid deposits, neuroinflammatory factors, and other responses to senile plaques \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. This cellular phase results in neuron death that is widespread enough to be measured using conventional histological and stereological methods and coincides with the acceleration of cognitive decline \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The underlying cell death mechanisms, which are likely multifactorial and context-dependent \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e remain largely unclarified. Detecting the progressive compromise and possible death of select individual neurons at earlier pre-clinical stages of AD, however, is a technical challenge requiring suitable cell-type specific markers of the underlying pathobiological mechanisms and cell death programs involved.\u003c/p\u003e \u003cp\u003eBeyond Aβ/β-amyloid or tau neuropathology, abnormalities of the endosomal-lysosomal (ELP) and autophagy-lysosomal pathways (ALP), the key pathways for production and intracellular clearance of β-amyloid and amyloidogenic proteins, are prominent pathological features of vulnerable neurons in AD \u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The early emergence of these ALP and ELP abnormalities and their direct mechanistic links to proteins encoded by AD causative genes (APP and Presenilins 1 and 2) and factors that significantly increase AD risk (e.g. APOE4, aging) suggest their primary importance to AD pathogenesis \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Among its key etiologic actions, BACE1-cleaved C-terminal APP fragments (APP-βCTF or C99), known to be elevated in AD \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, are implicated in the unique extreme ALP pathology and neuron death described in brains of mouse models of familial AD (FAD) β-amyloidosis, which emerges at an early \u0026ldquo;pre-plaque\u0026rdquo; stage of the disease. At elevated levels, APP-βCTF binding directly to the vATPase complex inhibits its activity, impairing both the lysosomal acidification and clearance of substrates, including APP-βCTF and Aβ \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe previously characterized evolving ALP deficits in AD model mice expressing an mRFP-eGFP-LC3 reporter for autophagy-related organelles \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. In vulnerable cortical neuron populations, the accumulation of enlarged poorly acidified autolysosomes containing undegraded substrates, including APP-βCTF and Aβ, was associated with a striking deficiency of lysosomal vATPase complex activity and assembly \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e emerging well before the extracellular deposition of β-amyloid \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Moreover, selected neocortical neurons developed a build-up of autophagic vacuoles so extreme that they pack into large blebs protruding from the somal plasma membrane -- a unique pattern termed PANTHOS. Moreover, intraneuronal β-amyloid fibrillar aggregates form within ER membrane tubules of the neuron, culminating in its death and the transformation of its corpse into a senile plaque.\u003c/p\u003e \u003cp\u003eThese findings in mouse AD models, which support an intraneuronal (\u0026ldquo;inside-out\u0026rdquo;) sequence of events in β-amyloid plaque formation, raise critical questions about whether or not they translate to human disease, especially human late-onset AD (LOAD). In the current study, we show in the human LOAD brain that the same pathobiological sequence of events develops by using large-scale multi-omic interrogation of autophagy-lysosomal pathways, confocal microscopy, and multiplex immunocytochemistry with autophagy and APP metabolite markers, ultrastructural analysis and Immuno-Electron Microscopy (IEM) on neocortical biopsies, and additional validating biochemical measurements. Further evidence reveals significantly reduced levels of vATPase complex subunits in the AD brain and reduced vATPase subunit transcription selectively in excitatory neurons, thus supporting an underlying molecular basis of lysosomal acidification dysfunction. These findings suggest new strategies against intraneuronal targets to prevent AD by interrupting the very early lysosomal deficits that may lead to later AD pathogenesis.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eTranscriptomic and proteomic analyses of large AD databases identify early lysosomal acidification and substrate clearance deficits.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe reassessed the Autophagy-Lysosome Pathway (ALP) \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e using the publicly available bulk-transcriptomic, bulk-proteomic, and single-nucleus RNA-seq (snRNA-seq) datasets from human AD brains as described in Methods. Large-scale transcriptomic data were obtained from the dorsolateral prefrontal cortex (DLPFC) region of 241 individuals (Control: N\u0026thinsp;=\u0026thinsp;86; AD: N\u0026thinsp;=\u0026thinsp;155) in the Religious Orders Study and Memory and Aging Project (ROSMAP) on AD (synapse.org, SynID: syn14237651). Proteomic data were collected from the DLPFC region of 310 individuals in the ROSMAP (Controls: N\u0026thinsp;=\u0026thinsp;84; AD: N\u0026thinsp;=\u0026thinsp;108) and Banner Cohort (Controls: N\u0026thinsp;=\u0026thinsp;26; AD: N\u0026thinsp;=\u0026thinsp;92) which identified 8,812 proteins using Tandem Mass Tag (TMT) proteomics \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Given the cellular heterogeneity of brain tissue, we further analyzed snRNA-seq datasets from the study by Mathys et al. \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e to investigate cell-type specific gene expression change. This snRNA-seq dataset includes 80,660 single-nucleus transcriptomes from the prefrontal cortex (Brodmann area 10) of 48 individuals from the ROSMAP cohort, with varying degrees of AD pathology (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAn earlier reported enrichment analysis using conventional GO terms did not detect changes in ALP \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Using our curated 57 ALP gene sets comprising 1,096 genes \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e (Supplementary Table\u0026nbsp;1) to assess ALP in human AD brains more comprehensively, we performed Gene Set Enrichment Analysis (GSEA) on the aforementioned proteomic, bulk RNA-seq, and snRNA-seq data. These gene sets were curated to interrogate steps in the autophagic-lysosomal pathways, including processes such as autophagy induction, autophagy signaling and autophagic vacuole (AVs) formation, transcriptional activators of ALP, mitophagy, lysogenesis, and lysosome function. Our analysis also included the gene sets for monitoring autophagy induction via the assessment of mTOR activation status \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. ALP status was further validated by applying the curated list of 838 unique high-confidence components of ALP (Supplementary Table\u0026nbsp;1) as defined in the Human Proteostasis Network \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. To ensure that the majority of proteins were not differentially abundant in a biased manner, we examined the differentially abundant proteome and identified 1,217 proteins with increased levels and 1,711 proteins with decreased levels at FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMost strikingly, our interrogation of the ALP proteome in the AD brain revealed a progressive deficiency of vATPase components essential for lysosomal acidification (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec, f). Levels of 12 of the 14 subunits of the vATPase complex are reduced, coinciding with evidence described below that deficient lysosomal proteolysis causes a profuse build-up of autophagic substrates (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec, d). Notably, most deficient are the membrane-anchored V0 subunits V0a1 and V0c, which along with lowered V0d1, form the platform for the association of the V1 subcomplex regulating vATPase activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Notably, the muted log2 fold change (log2FC) observed in the bulk proteomics data (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec and the first track of Extended Data Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) is attributable to the compression of quantifiable change resulting from TMT (MS2-based) protein quantification. This compression does not impact the precision or directionality of coexpression in relative quantification and is an underestimation of the true fold differences for each protein. Immunoblot analysis, however, confirmed significant reductions in the V0a1 subunit by 51% (0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and in the V0d1 subunit by 55% (0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) in Braak V brains, with similar trends of decline observed in Braak III brains. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). Most members of the V1 subcomplex are also lowered in AD brains (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Compared to the V0 component deficits in immuno-blot analysis, the smaller decreases of V1 subunits reflect in part their relative preservation in the cytoplasm upon dissociation from the complex\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, making them available for re-assembly. The implied decrease in fully assembled vATPase complex in AD brains compares to that demonstrated in mouse AD models, where an abnormal extent of vATPase disassembly is accompanied by decreased vATPase activity and elevated pH of autolysosomes \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Further single-cell level analysis using the snRNA-seq dataset revealed that the transcripts encoding proteins involved in the vATPase complex and lysosomal acidification, are particularly reduced in excitatory neuronal populations in AD brains, with a more pronounced reduction observed in AD brains at an early disease stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eEvidence of functional changes in lysosomes tied to the vATPase abnormalities in LOAD includes lowered Cathepsin D (CTSD)-specific activity (proteolytic activity/unit of CTSD protein) indicating a progressive inactivation of CTSD within lysosome-related compartments beginning at the pre-plaque stage of LOAD in Braak III neocortex (32%: p\u0026thinsp;=\u0026thinsp;0.0095) and further declining by Braak stage V (53.6% : p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg). CTSD-specific activity is lowered in disease states where lysosomal pH rises above their pH optimum, especially if pH rises chronically and partly inactivates cathepsins requiring the most acidic environment for its activity \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eContrasting with the prominent vATPase and clearance deficits, proteins associated with upstream stages of ALP in AD brains are predominantly maintained or elevated. Higher autophagy induction signaling is reflected by broadly lowered levels of mTOR target proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Elevated proteins include ones involved in autophagosome formation (e.g. ATG3, ATG4, ATG9), chaperone-mediated autophagy (e.g. CLU, HSPB8, BAG3, EEF1A1), docking and fusion of the autophagosome with lysosomes (e.g. VTI1A, ARL8B, VPS41, VPS39), and other proteins involved in autophagy (e.g. CYBB, HDAC2, DAPK, EIF2A) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The coincidence of altered ATG family members and depressed levels of mTOR targets (e.g. MRPSs, RPSs, ELF2B1) prompted us to assess mTOR inhibition as an indicator of upstream ALP induction. Indeed, GSEA of the proteomic data uncovered significant decreases in structural (ribosomal) and elongation factors known to decrease with mTOR inhibition\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). This observation aligns with the global suppression of protein synthesis reported in AD brain \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e and suggests that prolonged mTOR inhibition driving upstream ALP upregulation \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e contributes to the extreme autophagic stress of LOAD \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA previous report of markedly deficient Beclin 1 levels in AD brain\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e seemed to conflict with our evidence for competent autophagosome production in the LOAD brain. We resolved the discrepancy by showing that the RIPA buffer, which was used in the earlier investigation to assay only the soluble fraction of brain homogenates, incompletely extracts Beclin 1. Using the same protocol analyzed by Pickford et al. \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, we found that levels of total Beclin1 and its complex partner Vps 34 in either whole homogenate (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ei and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec) or the combined RIPA extracted and unextracted fractions (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, b) were unchanged in LOAD. Additionally, we observed no significant correlation between Beclin 1 expression levels and aging in either human (PFC, Brodmann Area 9/10) or mouse brains (hemi-brain) (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, d) indicating that Beclin 1, a key regulator of autophagy initiation, maintains stable expression across different age groups as well.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCollectively, our evidence demonstrates persistent upstream autophagy (induction) and autophagosome formation despite reduced downstream lysosomal clearance of autophagy substrates in LOAD brains.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSubstrate-filled autophagic vacuoles accumulate in neurons despite autolysosome-lysosome fusion.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eQuantitative immuno-blot analyses of neocortical gray matter homogenates confirmed our -omic evidence of a lysosomal clearance deficit in AD brains. LC3-II levels significantly increased by 33% (p\u0026thinsp;=\u0026thinsp;0.0320) by the preclinical LOAD Braak III stage and further by Braak V stage (65%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) compared to non-AD controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eSections of AD and control prefrontal cortex (Brodmann area 9 and 10) (Supplementary Table\u0026nbsp;2) were double immunolabeled with antibodies against CTSD to mark lysosomes and LC3 antibody to mark autophagic vacuoles (AV) and were stained with 4',6-diamidino-2-phenylindole (DAPI) to label nuclei, which enabled different ALP vesicle populations to be quantified. Autophagosomes (AP; LC3\u003csup\u003e+\u003c/sup\u003e/CTSD\u003csup\u003e-\u003c/sup\u003e) and autolysosomes (AL; LC3\u003csup\u003e+\u003c/sup\u003e/CTSD\u003csup\u003e+\u003c/sup\u003e) were infrequent in perikarya of neocortical neurons in neuropathologically normal control brains (Braak 0-I) (AP: 4.96/neuron, AL: 7.49/neuron) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). By comparison in Braak III brains, neocortical neurons display greatly increased numbers of APs (18.93/neuron, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and ALs (22.53/neuron, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Sizes of AP and AL vesicles also increased by Braak III stage of AD (AP: 5.13 \u0026micro;m\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0452; AL: 15.4 \u0026micro;m\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) compared to Braak 0-I stage (AP: 1.48 \u0026micro;m\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, AL: 7.36 \u0026micro;m\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Numbers of ALs, positive for both LC3 and CTSD, increased progressively with Braak stage, suggesting a compromised substrate clearance in autolysosomes in AD despite fusion with lysosomes. In neuronal somas, LC3/CTSD double-positive autolysosomes begin to emerge in the Braak II stage AD brains (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), whereas in control brains (Braak I stage), LC3 positive vesicles are rarely observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Notably, whereas LC3/CTSD-positive vesicle abnormalities emerging in neurons at Braak II stage AD included APs (LC3\u003csup\u003e+\u003c/sup\u003e/CTSD\u003csup\u003e-\u003c/sup\u003e; green, arrows), as well as enlarged ALs (CTSD+/LC3+; yellow, arrowheads) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and Extended data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea), perikaryal AV accumulations were predominantly composed of enlarged ALs by Braak stage III, (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, bottom and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Ultrastructural analysis of AD brain biopsies (see Methods) revealed selected neuronal somas containing a mixture of double-membrane APs (blue arrowheads) and single-membrane ALs (red arrowheads) corresponding to the ALP pathology in neurons in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec third panels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCollectively, these findings document a progressive accumulation of undigested material within proliferating ALs, consistent with compromised autophagy flux in human LOAD neocortical neurons similar to ALP abnormalities in AD mouse models.\u003c/p\u003e \u003cp\u003e \u003cb\u003eALP dysfunction in select individual neurons in the LOAD brain evolves into PANTHOS with intraneuronal β-amyloidosis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe previously described a unique form of extreme autophagic stress (PANTHOS) in AD mouse models \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e expressing a Thy1-driven mRFP-eGFP-LC3 reporter (tfLC3), which is a probe enabling the \u003cem\u003ein situ\u003c/em\u003e characterization of sizes and relative proportions of autophagy-related organelles in neurons based on their pH and biomarker patterns. The dual fluorescence-tagged probe detected incompletely (poorly) acidified autolysosomes (pa-ALs) based on ratiometric measurement of fluorescence signals from eGFP and mRFP. A far red-tagged secondary antibody with pseudo-blue color imaging visualized CTSD-positive lysosomes. CTSD immunolabeling further distinguished unquenched eGFP-positive AVs as neutral pH (CTSD-negative) autophagosomes from autolysosomes that fused with lysosomes but failed to acidify completely, activate hydrolases, and digest autophagic substrates \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAppropriate autophagy and amyloid markers were applied at early disease stages before the extensive glial proliferation and plaque burden accumulating at later stages can considerably obscure the ALP patterns when individual neurons are evaluated immunocytochemically. This strategy targeting early disease stages allowed the emergence of ALP-related dysfunction and all key features of PANTHOS lesions to be readily documented in human LOAD. Accordingly, AD prefrontal cortex sections were immunolabeled with antibodies to LC3 and CTSD and, in various experiments, additional antibodies (e.g. 4G8 or 3D6 for Aβ, etc.). Nuclei are stained with DAPI or far-red nuclear dye (e.g. DRAQ5). As described in 5 different mouse AD models, poorly acidified autolysosomes in LOAD neocortical neurons accumulate undegraded substrates, including APP metabolites (e.g. Aβ, APP-βCTF), enlarge and progressively multiply \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In select neurons, incompletely acidified autolysosomes massively pack into affected perikarya causing the plasma membrane to bulge with numerous large fluorescently labeled blebs, a unique pattern termed PANTHOS (\u003cb\u003ep\u003c/b\u003e- poisonous, \u003cb\u003eanthos\u003c/b\u003e- \u0026ldquo;flower\u0026rdquo; in Greek) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Moreover, intraneuronal perinuclear Aβ/β-amyloid immunoreactivity, consisting of bundles of β-amyloid fibrils immunolabeled by a fibrillar amyloid-specific antibody mOC78 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eClosely resembling that in AD mouse model brains, a similar sequence of pathological events plays out in post-mortem human LOAD brains leading to PANTHOS profiles appearance beginning at the earliest (Braak II-III) stages of AD in the prefrontal cortex (Brodmann area 10) prior to the appearance of senile plaques in this region (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). At these early stages, ALP dysfunction and Aβ immunoreactivity are quantitatively widespread across the most disease-vulnerable population of pyramidal neurons, compared to control neurons from age-matched asymptomatic, Braak 0-I controls. Although relatively infrequent in Braak II brains, PANTHOS profiles are nevertheless readily identifiable against the background, which is devoid of confounding microglia with high ALP content. Intra-neuronal 4G8 immunoreactivity is common in affected neurons at the pre-PANTHOS stage within LC3\u003csup\u003e+\u003c/sup\u003e/CTSD\u003csup\u003e+\u003c/sup\u003e autolysosomes when they collect and begin to bulge the cell. At a later stage of compromise, additional Aβ/β-amyloid immunoreactivity concentrates around the nucleus (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, PANTHOS and same neuron in Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea top) detected by DAPI and DRAQ5 within the center of a PANTHOS profile (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, e). We further investigated the possibility that the DAPI signal is not from a nucleus but instead is blue autofluorescence, as suggested in an investigation \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e in which a blocker of autofluorescence was not applied as is considered essential in immunohistofluorescence (IHF) analyses of aging brain \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e and routine in our studies. As expected, under autofluorescence blocking conditions, blue autofluorescence in the UV channel was absent in the region of the nucleus (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, top panels) whereas DAPI staining of a serial adjacent section revealed typical morphology of a fluorescent nucleus (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, bottom panels). Furthermore, in human AD brains, we observed that the 3D6-positive amyloid immunoreactivity was distinctly separate from DAPI-positive nuclei signals within PANTHOS (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). These analyses underscore the importance of autofluorescence quenching to avoid technical artifacts in IHF studies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSerial z-stack confocal microscopic imaging reveals the uniquely huge AV-filled blebs projecting from the plasma membranes of neurons in AD human brains (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, arrows) identical to those in the 5xFAD mouse model (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, top panel). EM analysis confirmed the uninterrupted connection between blebs and the perikaryal cytoplasm and identified AVs as the primary constituents of blebs in human LOAD brain (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, bottom panel), as also described in AD mouse models (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, top panel) \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The evolution of this pathobiology is depicted diagrammatically in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec as compared to a confocal image of PANTHOS documenting perikaryal blebs containing AVs, including different proportions of autophagosomes and autolysosomes varying in degree of acidification.\u003c/p\u003e \u003cp\u003eUltrastructural imaging in the LOAD brain illustrates an intermediate stage of autophagy stress of a neuron before the emergence of PANTHOS. A large collection of autophagosomes (AP) and autolysosomes (AL) within the somal cytoplasm appears to bulge one side of the neuron, corresponding to confocal images and diagrams in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Higher magnification reveals mainly immature single-membrane autolysosomes containing substrates at differing stages of incomplete digestion (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). At the PANTHOS stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb), large AV-filled blebs (red arrowheads) project from a central internal region of the soma via narrow necks (light-blue arrowheads), similar to those seen in the neurons of AD mouse model brains \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Continuity is evident between AV-filled blebs and the endoplasmic reticulum (ER) tubule network containing amyloid fibrillar aggregates (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb, red arrowheads). Intraneuronal amyloid fibrillar aggregates, with a width (6\u0026thinsp;\u0026plusmn;\u0026thinsp;1 nm) approximating estimated diameters of β-amyloid fibrils \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, accumulate within membrane-bounded structures (light-blue arrowheads) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec) that, by immuno-EM (IEM), are labeled by anti-ER antibody (calnexin) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed, yellow arrows and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ef) and by anti-Aβ/amyloid antibodies (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee), similar to those seen in the neurons of AD mouse models (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-c)\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Fusion between AVs and the ER membrane network containing β-amyloid aggregates is also seen (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ef and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCoi\u003c/strong\u003e \u003cp\u003e \u003cb\u003encidence of PANTHOS and amyloid plaque at early disease stages in LOAD neocortex.\u003c/b\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003eWe conducted quantitative analyses of PANTHOS lesions identified by LC3 /CTSD IHF on sections of PFC from Braak II- III stage LOAD brains. Although ALP abnormalities are widespread among layer III-V pyramidal neurons (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea), advance to the extreme PANTHOS stage and death leading to a senile plaque is relatively infrequent, as expected; however, it is significantly more prevalent at Braak stage II (5.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68 mm\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, n\u0026thinsp;=\u0026thinsp;6) than at Braak stages 0-I (0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 mm\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, n\u0026thinsp;=\u0026thinsp;7. \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and progressively increases in frequency in Braak stage III (8.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68 mm\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, n\u0026thinsp;=\u0026thinsp;7. \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0056) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe frequencies of β-amyloid lesions and PANTHOS are highly correlated, with almost a 1:1 ratio during the preclinical LOAD stages (Braak II, III) of LOAD (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec, arrows and graph). This correlation reflects the fact that β-amyloid immunolabeling in PFC at these early Braak stages predominantly detects intraneuronal β-amyloid in a plaque-like configuration similar to an extracellular plaque. Upon the death of neurons exhibiting PANTHOS morphology, extracellular plaques with the same general morphologies as the intraneuronal plaque-like structures are seen. However, cross-sectional analysis of mouse AD models at different later ages has shown that once formed, the gradual maturation of the plaque due to glial invasion and clearance of the more protease-susceptible debris, coupled with recruitment of neighboring degenerating neurons into the plaque, can generate plaques of different morphology, size, and amyloid condensation \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo further investigate the maturation of PANTHOS lesions and their potential evolution into amyloid plaques in human AD brains, we immunolabeled brain sections with antibodies to the glial fibrillary acidic protein (GFAP), a marker for reactive astrocytes or Iba1, a microglial marker together with CTSD. Due to the technical limitations of the antibody combinations available, we utilized CTSD as a PANTHOS marker. CTSD and LC3 show highly colocalized within PANTHOS blebs, supporting the conclusion that CTSD can serve as an alternative marker for detecting PANTHOS and its characteristic morphology in conjunction with different antibody panels in IHF studies \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe association of astrocytes with either ALP-altered neurons or those exhibiting early PANTHOS morphologies is rare, as evidenced by the infrequent presence of GFAP-positive astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, pre- and early-PANTHOS), nor a coordinate presence of IBA1-positive microglia and dystrophic neurite-like structures (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), even though early-PANTHOS exhibit amyloid deposits (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb, middle panels) in Braak III brains. In contrast, advanced PANTHOS are surrounded by reactive astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb, bottom panels) and microglia as well as dystrophic neurite-like structures in Braak V brains (Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). This pattern of late-stage astrocytic and microglial engagement suggests that these phagocytic cells are unlikely to serve as an initiating factor in the formation of PANTHOS in LOAD, but instead may respond to neuronal degeneration or plaque formation, as previously concluded from analyses of AD mouse models \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSenile plaques formed from dying PANTHOS neurons in LOAD brains.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the earliest stage of AD (Braak II), antibodies against LC3, CTSD, and amyloid (D54D2) reveal a distinctive pattern of amyloid deposition encircling the nucleus (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea and Extended Data Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec) of affected neurons in human LOAD brains. At this stage, PANTHOS associated neurons are similar in size to their less affected neighbors (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea), though the circumference expands as blebs develop evenly in all dimensions (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eb). PANTHOS-derived plaques at Braak stage III include both the nuclear ring pattern of amyloid aggregation (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec, stage \u003cem\u003ei\u003c/em\u003e) and also amyloid aggregate network dispersed centrifugally from the perinuclear β-amyloid (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec, stage \u003cem\u003eii-iv\u003c/em\u003e), as similarly seen in mouse AD models \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Aβ immunoreactivity that ultrastructurally corresponds to the amyloid fibril-containing ER tubules (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed) also extends centrifugally creating a network of tubular profiles. This suggests that amyloid deposition becomes more organized and aggressive as Alzheimer's pathology advances, potentially contributing to increased neuronal toxicity and disease progression. These findings highlight the evolution of amyloid deposition within PANTHOS and its contribution to plaque development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eUsing a multidimensional analysis in human late-onset sporadic AD (LOAD), we identified progressive dysfunction of the autophagy-lysosome pathway (ALP) in neocortical neurons emerging at the earliest disease stages (Braak II-III) before conventional plaque and tangle pathology develop in this brain region. During this preclinical LOAD stage, as ALP declines broadly across vulnerable neuronal populations, select individual affected neurons advance to a unique state of extreme autophagic stress and morphological distortion (blebbing) of the perikaryon, termed PANTHOS, and associated with plaque-like β-amyloid fibrillar aggregates within an ER-related membrane tubular network. Upon the premature subacute death of these neurons, the corpse yields an extracellular senile (\u0026ldquo;amyloid\u0026rdquo;) plaque, a lesion known to be composed of hundreds of proteins \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, including varied proteins originating from neurons \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Human LOAD thus recapitulates the pattern of ALP-related dysfunction, PANTHOS, intraneuronal β-amyloidosis, and senile plaque formation previously identified in mouse models of AD β-amyloidosis \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. These findings validate in the most common sporadic late-onset form of AD as an \u0026ldquo;inside-out\u0026rdquo; sequence of senile plaque development \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGuided by the pattern of ALP abnormalities revealed in mouse AD models by our \u003cem\u003ein vivo\u003c/em\u003e neuronal mRFP-eGFP-LC3 autophagy reporter, we traced evolving ALP dysfunction in LOAD human brains through its terminal PANTHOS stage by using LC3/CTSD double IHF and selected additional markers. Analysis at early Braak stages in the prefrontal cortex enabled the recognition of PANTHOS lesions before extensive invasion by LC3/CTSD-positive glial cells became a significant technical confound. Our results validated in LOAD an exceptionally early emergence of progressive ALP anomalies including massive build-up of enlarged substrate-laden autolysosomes encompassing a very large percentage of apparent total volume of PANTHOS-laden neurons, also characterized by extensive membrane blebbing, and invariable presence of a DAPI-positive neuronal nucleus, culminating in the PANTHOS phenotype in select neurons. Because neurons exhibiting PANTHOS accumulate APP-βCTF and Aβ in autolysosomes and plaque-like β-amyloid fibril bundles within ER or ER-related membrane tubules, they have been commonly misclassified as amyloid plaques presumed to originate from an extracellular seeding process when examined only by β-amyloid IHF or silver stains. During a protracted degenerative process, PANTHOS-positive neurons transition quantitatively from intraneuronal β-amyloid bearing neurons to give rise to the first generation of senile plaques in the neocortex. The same sequence of events can be recognized in late-stage disease although accumulation of slowly eliminated senile plaques and their continuous morphological changes associated with glial clearance processes and local secondary degenerative events are likely making quantitation more difficult. At this stage, glial dying after phagocytosing β-amyloid and related plaque debris could conceivably be a secondary source of senile plaques via a similar inside-out mechanism, although this has not yet been well established \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Dystrophic neuritic swellings, which predominantly accumulate immobilized endolysosomal vesicles containing APP secretases and APP metabolites, are an additional potential source of Aβ for diffuse extracellular plaque formation \u003csup\u003e\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e but these are clearly distinguishable from AV-filled perikaryal blebs encircling the PANTHOS lesion. The possibility of multiple distinct origins of amyloid plaques underscores a potential factor contributing to the heterogeneity of plaque-associated microenvironments of the AD brains \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEarly ALP dysfunction in APP-based mouse models of AD amyloidosis has been linked to deficient acidification due to declining lysosomal vATPase activity \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Our study builds on these earlier genetic and pathological analyses implicating vATPase as a likely molecular target in ALP failure and its pathological consequences in human LOAD \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Proteomic analyses of curated ALP gene sets in the human LOAD neocortex, demonstrated deficient levels of most subunits composing the 14 subunit vATPase complex. Most importantly, this includes the key membrane-anchored components of the V0 subcomplex, ATP6V0c, ATP6V0d, and ATP6V0a1, which provide the docking platform for the vATPase-containing V1 subcomplex. The regulated association of the V0 and V1 subcomplexes is a key determinant of vATPase activity and one targeted by etiologic factors in multiple disorders \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Immunoblot analyses of the same brain region confirmed deficient levels of the crucial membrane anchoring V0a1 and V0d1 subunits (suitable probes unavailable for ATP6V0c). Moreover, transcripts encoding vATPase subunits in the V1 subcomplex are reduced selectively in excitatory neurons among varied cell types analyzed in AD neocortex \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In further support, reduced levels of one or more specific vATPase subunits have been recently reported in AD brain or AD models by others \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe transmembrane V0a1 subunit, considered the critical anchoring subunit for vATPase assembly \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, is the principal target of both the inhibitory binding of the complex by APP-βCTF \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e and the impaired V0a1 subunit maturation caused by Presenilin 1 loss of function mutations in early-onset AD \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Human cell derived FAD neurons \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, like transgenic mouse models of FAD \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, duplicate the build-up of autolysosomes and elevated levels of APP-βCTF that arise from poorly acidified autolysosomes \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. APP-βCTF elevation in human AD brains \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e likely has a multifactorial basis, including elevated BACE 1 activity \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, interactions with cholesterol affecting trafficking \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, and reduced turnover in lysosomes \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Furthermore, pH dysregulation emerging at least as early as the Braak III stage is supported by autolysosomal build-up and enlargement resulting from impaired degradation of substrates, including LC3-II and less active forms of cathepsin D, a multifaceted cathepsin crucial for lysosomal proteolysis and implicated in multiple brain disorders \u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Lowered cathepsin-specific activity is often seen in disease models where lysosomal pH rises above the pH optimum \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e or, when elevated chronically, inactivates the cathepsins and inhibits their turnover \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn contrast to the extensive lysosomal dysfunction of the LOAD brains, upstream autophagy processes, including induction and autophagosome formation, are competent and likely upregulated, consistent with some earlier studies \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. In our proteome analyses of curated gene sets, \u0026ldquo;autophagic processes\u0026rdquo; upregulation is supported by elevations of autophagosome components ATGs (ATG3, 4, and ATG9) and Rab proteins (e.g., Rab3D, 6B, 9A, 32) involved in autophagosome biogenesis \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Furthermore, mTOR inhibition, which is connected to autophagy induction via TFEB and other transcript factors regulating ALP \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e, is evidenced by global decreases of structural (ribosomal) and elongation factor proteins \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e as well as down-regulation in neocortical neurons of transcripts encoding mTOR proteins targeting autophagosome formation and an up-regulation of AMPK \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Earlier reports of a substantial deficit of neocortical Beclin1 in human AD \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, implying possible lowered autophagosome formation, were not confirmed by multiple lines of our evidence, including re-analysis of the same protocols used in the original report \u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e, which both revealed no detectable alterations of total Beclin1 protein levels. We reconciled the disparity by showing that, in the original analysis, total Beclin1 was incompletely and differentially extracted from AD and control brain lysates when RIPA buffer was used for extraction \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Moreover, an age-dependent reduction in Beclin 1 levels was not observed in either human or mouse brains, in contrast to a previous study that reported a reduction when using milder extraction conditions \u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCollectively, therefore, our evidence strongly supports an early underlying lysosomal proteolytic clearance deficit coupled with persisting, if not upregulated, autophagosome production, that drives the uniquely extreme PANTHOS pattern, resulting as a signature of autophagic stress, and its consequences in the most affected neurons from broadly affected populations. In several other neurodegenerative diseases (e.g. Parkinson\u0026rsquo;s and Huntington\u0026rsquo;s Disease) autophagy induction is lowered \u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e, which could partially explain more moderate autophagic stress in neurons seen in these disorders that have declines in lysosomal function.\u003c/p\u003e \u003cp\u003eAlthough an extracellular source of Aβ has been conventionally considered the origin for extracellular amyloid plaques \u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e, intraneuronal accumulations of Aβ or Aβ oligomers are a well-known early pathological event that precedes amyloid plaque formation in AD \u003csup\u003e\u003cspan additionalcitationids=\"CR69 CR70\" citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. In late-onset Alzheimer\u0026rsquo;s disease (LOAD), we observed that β-amyloid fibril bundles initially form within the calnexin-positive ER-related tubules by mechanisms currently under investigation similar to what we discovered in familial Alzheimer's disease (FAD) mouse models \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The ER is a site of highly active constitutive autophagic turnover, known as \"ER-phagy\" \u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, and progressive autophagic impairment may hinder the clearance of the ER, allowing the accumulation of misfolded or aggregated proteins that are poor substrates for the ER-associated degradation (ERAD) pathway. We observed that autophagic vacuoles (AVs) increasingly interact with the ER, with frequent instances of AV-ER fusion and an abundance of calnexin-positive ER-related membrane tubules that are strongly immunoreactive with antibodies to Aβ and β-amyloid fibrillar aggregates in LOAD. These observations suggest an intracellular origin of amyloid and other intracellular debris stemming from the death of PANTHOS neurons that originally contained similar ER membrane-enclosed amyloid.\u003c/p\u003e \u003cp\u003eThe emergence of ALP dysfunction during the \u0026ldquo;pre-plaque\u0026rdquo; stage of AD highlights the significance of early intraneuronal dysfunction marking the earliest phase of the preclinical LOAD stage. This understudied earliest phase of AD represents a critical knowledge gap in our understanding of AD etiology, and of the selective vulnerability of certain neurons during this phase \u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e, as well as the origins of many-if not all-extracellular senile plaques. The evolution from PANTHOS to plaque deposition supports a paradigm shift toward a concept of \u0026ldquo;inside-out\u0026rdquo; neuron death as capable of initiating the development of plaque \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan additionalcitationids=\"CR75\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e. In this model, APP metabolites, notably APP-βCTF and Aβ, exert their most harmful effects within neurons by damaging ALP compartments and impeding lysosomal clearance in particular, which leads to proteostasis collapse, neuronal death, and the subsequent formation of extracellular plaques \u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. We show in this work that the initiation of PANTHOS precedes the activation of glial cells and dystrophic neurites (DNs), indicating that astrocytes and microglia become involved later in the disease. Having well-developed ALP and phagocytic capabilities \u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e, glial cells are mobilized to clear extracellular debris as a secondary response in AD that underlies the cellular/immune-associated with plaque and tangle pathology.\u003c/p\u003e \u003cp\u003eEvolving PANTHOS lesions have previously been misidentified as plaques due to their morphological similarities to senile plaques, which contain a dense core of Aβ-amyloid fibrils surrounded by dystrophic neurites and reactive glia \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. PANTHOS blebs are distinguishable from other structures by their unique rosette configuration and asymmetric neck extensions from the perikaryon plasma membrane. Serial-sectioned neurons undergoing PANTHOS formation in AD mouse brains reveal that these blebs originate from the plasma membrane \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Lysosomal markers prominently label PANTHOS profiles, whereas dystrophic neurites exhibit lower lysosomal activity but higher cytoskeletal marker signals, highlighting the structural and functional differences between these entities \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn conclusion, our findings in human sporadic AD brains corroborate and affirm the extensive analyses in mouse models that have highlighted the exceptionally early development of ALP dysfunction stemming in major part from faulty lysosomal acidification. Consistent with the observations in AD mouse models, we document in human AD an essentially identical phenotype of ALP dysfunction associated with PANTHOS and with intraneuronal β-amyloidogenesis and neuron death, yielding extracellular plaque formation. This mechanism, defined by impaired autophagy and lysosomal dysfunction, likely precedes the classical extracellular amyloid seeding, providing new insights into the early intraneuronal origins of AD. Further investigation is necessary to delineate the connection between PANTHOS formation and neuronal subpopulations susceptible to ALP dysfunction, driving neurodegeneration in AD.\u003c/p\u003e"},{"header":"Online Methods","content":"\u003cp\u003e\u003cstrong\u003eMouse lines and animal care\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor TRGL\u0026nbsp;(\u003cstrong\u003e\u003cu\u003eT\u003c/u\u003e\u003c/strong\u003ehy-1 m\u003cstrong\u003e\u003cu\u003eR\u003c/u\u003e\u003c/strong\u003eFP e\u003cstrong\u003e\u003cu\u003eG\u003c/u\u003e\u003c/strong\u003eFP \u003cstrong\u003e\u003cu\u003eL\u003c/u\u003e\u003c/strong\u003eC3\u003cstrong\u003e\u003cu\u003e)\u003c/u\u003e\u003c/strong\u003e mouse generation,\u0026nbsp;targeting vector for tfLC3 was constructed by insertion of tfLC3 into Thy1.1 expression cassette\u0026nbsp;\u003csup\u003e17, 82\u003c/sup\u003e. The tfLC3 was crossed with 5xFAD (Tg6799, C57BL/6NTAC), which express mutant human APP and PSEN1 (APP KM670/671NL: Swedish, I716V: Florida, V717I: London, PSEN1 M146L, L286V)\u003csup\u003e83\u003c/sup\u003e then tfLC3/5xFAD mice were studied together with age-matched controls. The Tg2576 mouse line (the B6;SJL. Tg(APPSWE)2576Kha), which expresses mutant human APP (Swedish K670N/M671L)\u0026nbsp;and maintained on a B6;Dba/2F1;SW background.\u0026nbsp;\u003csup\u003e17, 82\u003c/sup\u003e then tfLC3/ Tg2576 mice were studied together with age-matched controls. The mice were maintained in the Nathan Kline Institute (NKI) animal facility and housed in a 12-hour light/dark cycle. All animal experiments were performed according to \u0026ldquo;Principles of Animal Care\u0026rdquo;\u0026nbsp;\u003csup\u003e84\u003c/sup\u003e and approved by the Institutional Animal Care and Use Committee (IACUC) at the NKI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman brains\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEmbedded AD cortical biopsy specimens were provided by Dr. Jerzy Wegiel (New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY, USA), Dr. Xiongwei Zhu (Case Western Reserve University, Cleveland, Ohio, USA),\u0026nbsp;and Dr. George Perry (Univ. Texas at San Antonio, TX, USA) for EM/IEM.\u0026nbsp;Embedded AD Autopsy specimens (PMI\u0026lt;8 hours) were provided by Dr. Thomas Beach (Banner Sun Health Research Institute, Sun City, AZ, USA)\u0026nbsp;for EM/IEM. Paraformaldehyde-fixed tissue blocks and frozen tissues obtained from the prefrontal cortex (Brodmann\u0026rsquo;s Area 9/10) were kindly provided from Harvard Brain Tissue Resource Center (HBTRC, McLean Hospital, Belmont, MA, USA),\u0026nbsp;Mount Sinai Brain Bank (MSBB, NY, USA),\u0026nbsp;and Emory Alzheimer\u0026rsquo;s Disease Research Center Dr. Marla Gearing (ADRC/CND, GA, USA)\u0026nbsp;with demographic information outlined in\u0026nbsp;Supplementary\u003cstrong\u003e\u0026nbsp;Table\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEvaluation of proteomic and transcriptomic data from multiple cohorts\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of AD human brains.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, we examined\u0026nbsp;\u003cstrong\u003eboth the transcriptomic and proteomic data reported\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003efrom\u0026nbsp;multiple cohorts of postmortem human brains\u003c/strong\u003e\u003cstrong\u003e, focusing on\u003c/strong\u003e autophagic pathways and proteolysis. The RNA-seq data (https://doi.org/10.7303/syn14237651.1) were taken from The RNAseq Harmonization Study (rnaSeqReprocessing, synID: syn14237651) which is an AMP-AD consortium effort to harmonize RNAseq data generated through multiple grants. This includes the harmonization of RNA-seq data from \u0026nbsp;1. Religious Orders Study and Memory and Aging Project (ROSMAP), 2. Mayo RNAseq (MAYO) and 3. Mount Sinai Brain Bank (MSBB) cohorts. Only data from the ROSMAP cohort which are Dorsolateral Prefrontal Cortex (DLPFC), Brodmann area 9 were considered for our analyses and are total of 241 brains (Controls (Braak I-III): N=86 and AD (Braak III-VI): N=155). For the Differential Gene Expression (DGE) analysis, we used Diagnosis.Sex: a colinear model of both Diagnosis and Sex. Proteomic data were derived from Johnson et al., 2022 study \u003csup\u003e20\u003c/sup\u003e and is a set of DLPFC, Brodman area 9 from ROSMAP (Controls\u0026nbsp;(Braak 0-III without\u0026nbsp;dementia): N=84,\u0026nbsp;AD\u0026nbsp;(Braak III-VI with\u0026nbsp;dementia): N=108) and Banner (Controls: N=26,\u0026nbsp;AD: N=92) cohorts that identified 8,812 proteins using Tandem Mass Tag (TMT) proteomics, which was further analyzed for this study.\u0026nbsp;The snRNA-seq data involve the prefrontal cortex (Brodmann area 10) of 48 individuals from ROSMAP with varying degrees of AD pathology (No pathology (CTRL: Braak I-IV with low amyloid): N=24; early-pathology (EARLY: Braak III-V with high amyloid): N=15; late-pathology (AD: Braak V-VI with high amyloid): N=9) across six major brain cell types\u0026nbsp;\u003csup\u003e21\u003c/sup\u003e. According to Mathys et al., early pathology was defined as brains with amyloid burden, but modest neurofibrillary tangles and cognitive impairment; while late pathology as brains with higher amyloid, and also elevated neurofibrillary tangles, global pathology, and cognitive impairment.\u0026nbsp;We used our\u0026nbsp;in-house curated gene sets designed to interrogate all aspects of autophagy-lysosomal pathways coupled with gene sets published elsewhere\u0026nbsp;\u003csup\u003e19, 23\u003c/sup\u003e to perform GSEA/Enrichment analysis on the aforementioned datasets.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntibodies and Reagents\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLC3 (MBL M152-3, 1/200) was from MBL Intl Corp. Rabbit anti-CTSD (Rudy4, 1/2000), Sheep anti-CTSD (D2.3 1/500) and \u0026nbsp;NFL (21.4, 1/250) were produced in house (Lee et al., 2019). 4G8 (800701, 1/250) was from BioLegend, and 3D6 (ab205341, 1/200) was a generous gift from Dr. Marc Mercken (Janssen Pharmaceutica/Johnson \u0026amp; Johnson, Belgium).\u0026nbsp;mOC78 (ab205341, 1/200) from Abcam. DRAQ5 (65-0880-92, 1/2000) from ThermoFisher Scientific,\u0026nbsp;IbaI (019-19741, 1/250) from Wako. GFAP (3670, 1/500), \u0026beta;-amyloid (D54D2), and Vps34 (4263, 1/1000) were from Cell signaling technology. Beclin-1 (BD612112, 1/1000) from BD Bioscience.\u0026nbsp;V0a1 (13828-1-AP, 1/1000) and V0d1 (18274-1-AP, 1/1000) form ProteinTech. V0C (NBP1-59654, 1/1000) and LIMP2 (NB400-129, 1/1000) from Novus Bio. V1A (ab118326, 1/1000) and V1C1 (ab272594, 1/1000) from Abcam.\u0026nbsp;Actin (A1978, 1/5000)\u0026nbsp;and\u0026nbsp;Thioflavin-S (T1892)\u0026nbsp;from\u0026nbsp;Sigma. Calnexin (AD1-SPA-860-D, 1/500) from Enzo.\u0026nbsp;HRP- linked Rabbit IgG (711-035-152, 1/5000), Mouse IgG (711-035-150, 1/5000), Rat IgG (712-035-150), and Goat IgG (705-035-003) secondary antibodies were purchased from Jackson ImmunoResearch. Prolong Diamond Antifade Mount (P36961),\u0026nbsp;Goat anti-Mouse Alexa 647 (A21235), Goat anti-Rat Alexa 647 (A21247), Goat anti-Rabbit (A21245) Alexafluor 647, and Donkey anti-Rabbit Alexa 405 (A48254), Donkey anti-mouse 488 (A32766), 568 (A10037), Donkey anti-rabbit 488 (A32790), 647 (A32795), Donkey anti-sheep 568 (A21099) secondary antibodies were from ThermoFisher. Mouse on Mouse (M.O.M) detection kit (BMK-2201), normal-donkey (S-2000-20) and normal-goat (S-100) serum blocking solution were from Vector Lab.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern blotting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCerebral cortices from male 5xFAD and WT mouse brain were homogenized with buffer (20mM Tris-Cl, pH 7.4 with 250mM sucrose, 1mM EGTA, 1mM EDTA, 1mM MgCl\u003csub\u003e2\u003c/sub\u003e and protease and phosphatase inhibitor (Roche). The post-nuclear homogenates obtained by centrifugation (1,000 g, 10 min) were further fractionated into cytosolic and membrane/vesicle fractions by high-speed centrifugation (150,000 x g, 50 min), and equal proteins were loaded on a gel.\u0026nbsp;The cerebral cortex from the human brain (0.5g) and mouse hemi brain (0.2g) were homogenized as previously described\u0026nbsp;\u003csup\u003e85\u003c/sup\u003e in a buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 1mM each EDTA, EGTA, and DTT, 250mM sucrose, 1 mM \u0026beta;-glycerophosphate, 1 mM NaF, 0.2 mM NaVaO\u003csub\u003e4,\u003c/sub\u003e 5\u0026micro;g/ml each leupeptin, antipain and pepstatin and 1mM each Benzamidine and PMSF). In addition to whole brain homogenate analysis, sequential extraction of\u0026nbsp;Beclin was carried out as described\u0026nbsp;\u003csup\u003e29, 86\u003c/sup\u003e. Briefly, the homogenates were sub-fractionated by centrifugation at 10,000g at 4\u003csup\u003eo\u003c/sup\u003eC for 30 min, and supernatant (S-1) was used. The remaining pellet was further solubilized in RIPA buffer (50\u0026nbsp;mM Tris/HCl pH 7.4; 0.15M NaCl; 5mM EDTA; 1mM EGTA; 0.5% Sodium deoxycholate; 1% NP40 0.1% SDS with a mixture of protease and phosphatase inhibitors) followed by centrifugation at 10,000g for 30 min. The resulting supernatant (S-2) along with S-1 and the pellet (P) solubilized in Laemmli buffer were used for western blotting of\u0026nbsp;Beclin and Vps34.\u0026nbsp;In addition to the extraction described above a small subset of brains was extracted using a protocol employed by Masliah\u0026rsquo;s laboratory\u0026nbsp;\u003csup\u003e63\u003c/sup\u003e. Brain homogenates were spun at 5,000g for 5 minutes initially to get a buffer insoluble pellet and the supernatants were further centrifuged at 100,000g for 1 hour at 4\u003csup\u003eo\u003c/sup\u003eC. After 100,000g spun, supernatants were collected as a cytosolic fraction and the pellets were collected and further sonicated in the homogenizing buffer as a membrane fraction. Three fractions were analyzed for Beclin-I by western blotting with Laemmli buffer. Three fractions were analyzed for Beclin by western blotting.\u0026nbsp;Protein content was determined using the BCA method. Samples were\u0026nbsp;mixed\u0026nbsp;with\u0026nbsp;2x\u0026nbsp;SDS\u0026nbsp;sample\u0026nbsp;buffer\u0026nbsp;and\u0026nbsp;incubated for 5\u0026nbsp;min\u0026nbsp;at 100\u0026deg;C. Following electrophoresis\u0026nbsp;on 16% or\u0026nbsp;4-20\u0026nbsp;%\u0026nbsp;Tris-glycine\u0026nbsp;gradient\u0026nbsp;gel\u0026nbsp;(Invitrogen),\u0026nbsp;proteins\u0026nbsp;were transferred\u0026nbsp;onto\u0026nbsp;nitrocellulose (for V0a1, v0d1) otherwise\u0026nbsp;0.45\u0026nbsp;\u0026micro;m\u0026nbsp;PVDF membranes\u0026nbsp;(Millipore) for detection of all other proteins\u0026nbsp;then\u0026nbsp;incubated\u0026nbsp;overnight\u0026nbsp;in\u0026nbsp;primary antibody. HRP\u0026nbsp;conjugated\u0026nbsp;secondary antibody was added the following morning and incubated for one hour at room temperature.\u0026nbsp;The\u0026nbsp;blot\u0026nbsp;was\u0026nbsp;developed\u0026nbsp;using\u0026nbsp;an\u0026nbsp;Invitrogen\u0026nbsp;ECL kit.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUltrastructural EM analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMice were perfused with 2.5% glutaraldehyde, and 2% paraformaldehyde in 0.1 M sodium cacodylate buffer, pH 7.4 (EMS). The brain was removed and sectioned using a vibratome into 50\u0026micro;m or 100\u0026micro;m sections placed in a fixative solution and stored at 4℃. Samples were then treated with 1% osmium tetroxide in 100 mM sodium cacodylate buffer pH 7.4 for\u0026nbsp;30 minutes, washed in distilled water four times (10 min/wash), and then treated with 2% aqueous uranyl acetate overnight at 4\u0026deg;C in the dark. Samples were then washed and sequentially dehydrated with increasing concentrations of\u0026nbsp;ethanol (20, 30, 50, 70, 90, and 100 %) for 30 min each, followed by three additional treatments with 100%\u0026nbsp;ethanol for 20 min each. Samples were then infiltrated with increasing concentrations of Spurr\u0026rsquo;s resin (25% for 1 h, 50% for 1 h, 75% for 1 h, 100% for 1 h, and 100% overnight at room temperature), and then incubated overnight at 70\u0026deg;C in a resin mold. For TEM ultrastructural analysis 70 nm sections were cut using a Leica Reichert Ultracut S ultramicrotome and a Diatome diamond knife, placed on grids, and then post-stained with 2% uranyl acetate and lead citrate. Images were taken using a Ceta Camera on a ThermoFisher Talos L120C transmission electron microscope operating at 120kV.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmuno EM\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe tissue was processed as described above. Sections of 70 nm were cut on a Leica ultramicrotome with a diamond knife. \u0026nbsp;The sections were placed onto carbon formvar 75 mesh nickel grids and etched using 4% sodium metaperidotate for 10 minutes before being washed twice in distilled water and then blocked for one hour. Grids were incubated with either 3D6 (1/2 dilution), 4G8 (1/2 dilution), or Calnexine antibodies (1/10 dilution), at 4\u0026nbsp;̊C\u0026nbsp;overnight. The next day grids underwent seven washes in 1xPBS and were then incubated in anti-mouse or anti-rabbit 10 nm gold secondary (1/50 dilution) for 1 hour. After this, the grid was washed seven times in 1xPBS and twice in distilled water. Grids were then silver-enhanced for 5 minutes (Nanoprobes). Grids were finally post-stained with 1% uranyl acetate for 5 minutes followed by two washes in water and then stained with lead citrate for 5 minutes followed by a final two washes in distilled water. \u0026nbsp;Samples were then imaged on a ThermoFisher Talos L120C operating at 120kV.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnzymatic assays in brain lysates:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCathepsin D was assayed at 37\u003csup\u003eo\u003c/sup\u003eC at PH 4.0 by measuring the release of amc containing peptide, 7-methoxycoumarin-4-acetyl-Gly- Lys-Pro-Ile-Leu-Phe from 7-methoxycoumarin-4-acetyl-Gly- Lys-Pro-Ile-Leu-Phe-Phe-Arg-Leu-Lys (Dnp)-D-Arg-NH2 (BioMol-Enzo, Plymouth Reading, PA), according to the method of Yasuda et.al.\u0026nbsp;\u003csup\u003e87\u003c/sup\u003e. Assays were performed in white microplates in a total volume of 100 ml of 0.1M sodium acetate buffer pH 4.0 containing 20 mM substrate with and without 3 mg of pepstatin for one hour. The fluorescence released was read in a Wallac Victor-2 Spectrofluorimetric plate reader with a filter optimized for detection of amc standard solution with excitation at 365nm and emission at 440nm. However, instead of using amc standard, a quenched standard 7-methoxycoumarin-4-acetyl-Pro-Leu-OH was used for expressing enzyme activity to account for the release of peptide containing amc instead of free amc. Enzyme activity was expressed as the relative amount of quenched standard released per hour per mg protein.The specific activity of cathepsins was calculated by calculating the ratio of Enzyme activity to the densitometric data obtained from western blots for each enzyme.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConfocal laser scanning microscopy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eImmunocytochemistry was performed as previously described\u0026nbsp;\u003csup\u003e26\u003c/sup\u003e. Animals were anesthetized\u0026nbsp;and perfused with Perfusion Fixative Super Reagent (Electron Microscopy Sciences, 1223SK) followed by a wash with Perfusion Wash Super Reagent (Electron Microscopy Sciences, 1222SK). Brains were dissected and immersed in the same fixative for 24 hrs and then 40 \u0026micro;m\u0026nbsp;sagittal sections were made using a vibratome. Brain sections were further stained with indicated antibody overnight and then visualized with Alexafluor conjugated secondary antibody. Imaging was performed\u0026nbsp;using a plan-Apochromat 20x or 40x/1.4 oil objective lens on an LSM880 laser scanning confocal microscope with the following parameters: eGFP/Alexafluor488 (ex: 488, em: 490-560 with MBS 488), mRFP/Alexafluor568 (ex: 561, em: 582-640 with MBS 458/561), Alexa fluor 647 (ex: 633, em: 640-710 with MBS 488/561/633), DAPI (ex: 405, em: 410-483) with best signal scanning model to exclude crosstalk between each wavelength; Image acquisition with frame (1024x1024) scanning mode with averaging 4 line-scan, speed 6. \u003cstrong\u003eThioflavin-S staining:\u003c/strong\u003e confocal imaged sections were dehydrated and incubated with 1% aqueous Thio-S for 8 minutes. Wash with 80 % ethanol (2 x 3 min), 95 % ethanol (3 min), and ddH\u003csub\u003e2\u003c/sub\u003e0 (3 times). Analyze the slide with the combination of the DAPI/eGFP/mRFP filter set. \u003cstrong\u003eHuman AD brain\u003c/strong\u003e:\u0026nbsp;40 \u0026micro;m free-floating sections cut on vibratome from fixed tissue blocks were washed once in 1 x Tris-buffered saline (TBS, pH 7.4) buffer and rinsed twice in ddH\u003csub\u003e2\u003c/sub\u003eO followed by incubation in 70 % (V: V) formic acid for 12 min at 27 \u0026nbsp;̊C for amyloid staining. Otherwise, sections were only incubated for 30 min at 90 ̊C in R-universal epitope recovery butter (AP0530-500) from Aptum Biologics Ltd to unmask antigens and allowed to cool to 27 \u0026nbsp;̊C on the bench, followed by 2 x 10 min rinse in TBS buffer. Sections were blocked for 60 min in 20% Normal Horse Serum (V: V) in TBS and incubated with primary antibodies for 24 hrs at 4 ̊C in 4 % Normal Horse Serum (V: V) and 0.1 % Tween-20 for LC3 IHF or 0.3 % Triton X-100 for others in TBS blocking buffer followed by washing 2 x 10 min in 1 x TBS buffer. Incubation in appropriate secondary antibodies (Invitrogen Alexafluor), diluted 1:500 in Blocking Buffer for 2 hrs at 27 \u0026nbsp;̊C was followed by washing 2 x 10 min in TBS buffer and autofluorescence was blocked by Autofluorescence Blocker (Trueblack\u0026nbsp;Plus, #23014, Biotium) following manufacturers protocol to avoid non-specific blue-autofluorescence. Sections were washed 3 x 5 min at 27 \u0026nbsp;̊C and stained with DAPI in 0.2 M N\u003csub\u003e2\u003c/sub\u003eAPO\u003csub\u003e4\u003c/sub\u003e, 0.1 M citrate buffer, pH 7.5 for 15 minutes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioinformatic analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferentially expressed genes for the bulk transcriptomics data were determined as those with an estimated FDR below 5% from the original study. The significantly up and downregulated proteins from the original proteomics data\u0026nbsp;\u003csup\u003e20\u003c/sup\u003e were chosen based on the originally reported BH-corrected p-value significance i.e., FDR \u0026lt; 0.05, while the significance for genes from snRNA-seq data was defined with 2-sided Wilcoxon-rank-sum test, FDR\u0026lt;0.01, logFC\u0026gt;0.25, Poisson mixed-model FDR\u0026lt;0.05 as defined in the original paper\u0026nbsp;\u003csup\u003e21\u003c/sup\u003e. Enrichment analysis or more commonly Gene Set Enrichment Analysis (GSEA) was conducted in R (R version 4.3.1) with R/Bioconductor package GeneOverlap (version 1.36.0) (Shen L, Sinai ISoMaM (2023). GeneOverlap: Test and visualize gene overlaps. R package version 1.36.0) which conducts one-sided Fisher\u0026rsquo;s Exact Test (FET) on gene sets to be tested. The significance of the test was determined based on BH-corrected P-values (adj.p-values or FDR) with alpha of 0.05 unless otherwise mentioned.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantification and statistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical parameters including the definitions and value of sample size (n), deviations, and \u003cem\u003ep\u003c/em\u003e values are reported in the figures and corresponding figure legends. Statistical analyses using Prism 8 (GraphPad Software) were conducted on data originating from at least three independent experimental replicates. Statistical analyses between the two groups were performed by a paired t-test. Statistical analyses involving comparisons among more than three groups were conducted using a one-way ANOVA. Data are expressed as mean \u0026plusmn;SEM. Differences were considered significant with p\u0026lt;0.05. The Pearson correlation method was used for correlation analyses.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by NIH P01AG017617 and R01AG062376 to R.A.N. The author sincerely acknowledges Mrs. Swati Jain for assistance in preparing the diagrams and Rosemarie LoFaro for administrative support. We are very grateful to Dr. Tamotsu Yoshimori (Osaka University, Japan) for the mRFP-eEGFP-LC3 construct used in transgenic mice, \u0026nbsp;Dr. Jerzy Wegiel (New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York, USA), Sandra Siedlak (Case Western Reserve University, Cleveland, Ohio, USA) for human AD cortical biopsy specimens, Dr. Thomas Beach (Banner Sun Health Research Institute, Sun City, Arizona, USA) for AD autopsy (PMI\u0026lt;8hrs) brains. Human AD brain from Harvard Brain Tissue Resource Center (HBTRC, McLean Hospital, Belmont, MA), Mount Sinai Brain Bank (MSBB) part of NIH NeuroBioBank, and Dr. Marla Gearing Research Center/Center for Neurodegenerative Disease (ADRC/CND) with support from ADRC grant (P50 AG025688). The results published here are in whole or in part based on data obtained from the AD Knowledge Portal (https://adknowledgeportal.org).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.H.L. and R.A.N. were equally responsible for experimental design and data interpretation and mainly contributed to writing and revising the manuscript. J.H.L., P.S., P.J., and M.B. conducted the experiments. P.S.M. conducted CTSD enzyme essay and Beclin-related experiments. D. Y. and C.N.G. performed EM/IEM. S.D. performed omic analysis and data interpretation. P.S., C.B., M.B., and P.S.M. conducted tissue processing and contributed to data interpretation. P.R., E.B.D., N.T.S., and G.P. contributed to the data interpretation. X.Z. provides human AD biopsy specimens. J.P. maintained animals and carried out genotyping.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKawai, M. \u003cem\u003eet al.\u003c/em\u003e Subcellular localization of amyloid precursor protein in senile plaques of Alzheimer's disease. Am J Pathol 140, 947\u0026ndash;958 (1992).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCras, P. \u003cem\u003eet al.\u003c/em\u003e Senile plaque neurites in Alzheimer disease accumulate amyloid precursor protein. \u003cem\u003eProc. Natl Acad. Sci. 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Signal Transduct Target Ther 7, 344 (2022).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Autophagy, lysosome, acidification, late-onset AD, amyloid plaque, Aβ, Alzheimer’s disease, LC3, perikaryal blebbing, neuronal cell death","lastPublishedDoi":"10.21203/rs.3.rs-5306901/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5306901/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe autophagy-lysosomal pathway (ALP) is dysfunctional in Alzheimer\u0026rsquo;s Disease (AD) although pathogenic consequences remain unclear. Here, we identify exceptionally early ALP dysfunction in neocortical neurons of late-onset sporadic AD (LOAD) brains, leading to selective neuronal death yielding β-amyloid plaques. Proteomic ALP analyses of ROSMAP/Banner datasets revealed selective deficits in vATPase subunits and, in an snRNA database, diminished vATPase transcripts in excitatory neurons but not other cell-types. Biochemical, confocal, and immuno-EM human brain analyses confirm defective neuronal lysosomal clearance and intracellular β-amyloid formation within ER-related membrane tubules. Despite deficient clearance, persistent autophagy induction accelerates profuse buildup of Aβ-positive autolysosomes. In select neurons among broadly affected neocortical populations, extreme autophagic stress and intraneuronal β-amyloidosis cause cell death and transform these neurons into extracellular senile plaques. Thus, LOAD brain recapitulates PANTHOS pattern of ALP dysfunction in mouse AD models that arises from faulty-autolysosome acidification and underlies an intraneuronal (\u0026ldquo;inside-out\u0026rdquo;) origin of senile plaques.\u003c/p\u003e","manuscriptTitle":"Autophagy-lysosomal dysfunction, intraneuronal amyloidosis, and selective neuron death yield senile plaques in preclinical late-onset Alzheimer’s Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-05 07:01:36","doi":"10.21203/rs.3.rs-5306901/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-neuroscience","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"neuro","sideBox":"Learn more about [Nature Neuroscience](http://www.nature.com/neuro/)","snPcode":"","submissionUrl":"","title":"Nature Neuroscience","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"be7692cf-aa82-4004-b333-2d80d7bcdf89","owner":[],"postedDate":"November 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":39715345,"name":"Biological sciences/Neuroscience/Diseases of the nervous system/Alzheimer's disease"},{"id":39715346,"name":"Health sciences/Diseases/Neurological disorders/Neurodegeneration"}],"tags":[],"updatedAt":"2026-04-16T15:12:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-05 07:01:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5306901","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5306901","identity":"rs-5306901","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}