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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 325 records · Page 18Linked to original sources

bioRxiv2022

Is Tau the Initial Pathology in Dopaminergic Nigrostriatal Degeneration? Studies in Parkinsonism and Parkinson ' Disease

While Parkinsons disease (PD) remains clinically defined by cardinal motor symptoms resulting from nigrostriatal degeneration, it is now appreciated that PD consists of multiple pathologies, but it is unclear which occurs first and which are responsible for the nigrostriatal degeneration. For the past number of years, we have been studying a well-characterized cohort of subjects with motor impairment that we have termed mild motor deficits (MMD). Motor deficits were determined on a modified and validated Unified Parkinsons Disease Rating Scale III (UPDRS III), but they occur to a degree insufficient to diagnose PD. We consider this population to have prodromal PD. However, in past studies, cases in this cohort had a selection bias as both a clinical syndrome in between no motor deficits and PD, plus nigral Lewy pathology as defined post-mortem, were required for inclusion. Therefore, in this study, we only based inclusion on a clinical phenotype intermediate between no motor impairment and PD. Then, we divided this group further based upon whether or not they had a synucleinopathy. Here we demonstrate that loss of nigral dopaminergic neurons, loss of putamenal dopaminergic innervation, loss of TH-phenotype in the substantia nigra and putamen, and changes in axonal transport occur equally in groups with and without nigral alpha-synuclein aggregates. Indeed, the common feature of these two groups is that both have similar degrees of AT8-expressing phospho-tau, a pathology not seen in the nigrostriatal system of aged-matched controls. These finding were confirmed with early (CP13) and late (PHF1) tau markers. This suggests that the initiation of nigrostriatal dopaminergic neurodegeneration occurs independently of alpha-synuclein aggregation and is likely tau mediated.

pathology↗

bioRxiv2023

Pathology of naturally acquired high pathogenicity avian influenza virus H5N1 infection in seabirds

The re-emergence of the high pathogenicity avian influenza virus (HPAIV) subtype H5N1 in the United Kingdom in 2021-2022 has caused unprecedented epizootic events in wild birds and poultry. During the summer of 2022 there was a shift in virus transmission dynamics resulting in increased HPAIV infection in seabirds and consequently a profound impact on seabird populations. To understand the pathological impact of HPAIV in seabirds, we have evaluated the virus distribution and associated pathological changes in the tissues of great skua (Stercorarius skua, n=8), long tailed skua (Stercorarius longicaudus, n=1), European herring gull (Larus argentatus, n=5), and black-headed gull (Chroicocephalus ridibundus, n=4). Grossly there was gizzard ulceration in one great skua and pancreatic necrosis in four herring gulls, which were confirmed for virus infection in situ by immunohistochemistry. Microscopical analysis revealed neuro-, pneumo-, lymphoidand cardiotropism of HPAIV H5N1, with the most common virus-associated pathological changes being pancreatic and splenic necrosis. Examination of the reproductive tract of the great skua revealed HPAIV-associated oophoritis and salpingitis, and virus replication within the oviductal epithelium. Across the birds, epitheliotropism was evident in the intestine, nasal turbinate, and trachea. This was, in contrast, not observed in the 2021 summer mortality event in great skuas and may be significant for the disease epidemiology observed in 2022. The emergence of HPAIV in seabirds, particularly during summer 2022, has challenged the dogma of HPAIV dynamics, posing a significant threat to wild bird life with potential implications to the reproductive performance of seabirds of conservation importance.

pathology↗

bioRxiv2023

Leveraging medical Twitter to build a visual-language foundation model for pathology AI

The lack of annotated publicly available medical images is a major barrier for innovations. At the same time, many de-identified images and much knowledge are shared by clinicians on public forums such as medical Twitter. Here we harness these crowd platforms to curate OpenPath, a large dataset of 208,414 pathology images paired with natural language descriptions. This is the largest public dataset for pathology images annotated with natural text. We demonstrate the value of this resource by developing PLIP, a multimodal AI with both image and text understanding, which is trained on OpenPath. PLIP achieves state-of-the-art zero-shot and transfer learning performances for classifying new pathology images across diverse tasks. Moreover, PLIP enables users to retrieve similar cases by either image or natural language search, greatly facilitating knowledge sharing. Our approach demonstrates that publicly shared medical information is a tremendous resource that can be harnessed to advance biomedical AI.

pathology↗

bioRxiv2023

Endothelial SARS-CoV-2 infection is not the underlying cause of COVID19-associated vascular pathology in mice

Endothelial damage and vascular pathology have been recognized as major features of COVID-19 since the beginning of the pandemic. Two main theories regarding how Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) damages endothelial cells and causes vascular pathology have been proposed: direct viral infection of endothelial cells or indirect damage mediated by circulating inflammatory molecules and immune mechanisms. However, these proposed mechanisms remain largely untested in vivo. Here, we utilized a set of new mouse genetic tools1 developed in our lab to test both the necessity and sufficiency of endothelial human angiotensin-converting enzyme 2 (hACE2) in COVID19 pathogenesis. Our results demonstrate that endothelial ACE2 and direct infection of vascular endothelial cells does not contribute significantly to the diverse vascular pathology associated with COVID-19.

pathology↗

bioRxiv2023

Open-top Bessel beam two-photon light sheet microscopy for three-dimensional pathology

Nondestructive pathology based on three-dimensional (3D) optical microscopy holds promise as a complement to traditional destructive hematoxylin and eosin (H&E) stained slide-based pathology by providing cellular information in high throughput manner. However, conventional techniques provided superficial information only due to shallow imaging depths. Herein, we developed open-top two-photon light sheet microscopy (OT-TP-LSM) for intraoperative 3D pathology. An extended depth of field two-photon excitation light sheet was generated by scanning a nondiffractive Bessel beam, and selective planar imaging was conducted with cameras at 400 frames/s max during the lateral translation of tissue specimens. Intrinsic second harmonic generation was collected for additional extracellular matrix (ECM) visualization. OT-TP-LSM was tested in various human cancer specimens including skin, pancreas, and prostate. High imaging depths were achieved owing to long excitation wavelengths and long wavelength fluorophores. 3D visualization of both cells and ECM enhanced the ability of cancer detection. Furthermore, an unsupervised deep learning network was employed for the style transfer of OT-TP-LSM images to virtual H&E images. The virtual H&E images exhibited comparable histological characteristics to real ones. OT-TP-LSM may have the potential for histopathological examination in surgical and biopsy applications by rapidly providing 3D information.

pathology↗

bioRxiv2024

ComPRePS: An Automated Cloud-based Image Analysis tool to democratize AI in Digital Pathology

Digital pathology using whole slide imaging (WSI) and artificial intelligence (AI) has the potential to transform diagnostic workflows, but adoption remains limited by technical complexity and scalability. We developed the Computational Renal Pathology Suite (ComPRePS), a scalable cloud-based platform that automates WSI ingestion, compartmental segmentation, feature extraction, and AI-assisted interpretation through an integrated high-performance architecture. ComPRePS was evaluated in two use cases. First, using 213 procurement biopsies, we compared conventional assessments with automated AI analyses and a hybrid AI-assisted expert workflow. ComPRePS AI-assisted methods achieved higher precision and significantly improved interobserver agreement for key lesions, including global glomerulosclerosis, interstitial fibrosis and tubular atrophy, and arterial intimal thickening. Second, ComPRePS enabled high-throughput quantitative profiling of glomerular and tubular features across minimal change disease, diabetic nephropathy, and amyloid nephropathy revealing disease-specific phenotypic patterns inaccessible to manual evaluation. Overall, ComPRePS improves reproducibility, interpretability, and objectivity in renal pathology, bridging computation with clinical practice.

pathology↗

bioRxiv2024

Lewy-MSA hybrid fold drives distinct neuronal a-synuclein pathology

The ordered assembly of -synuclein protein into filaments encoded by SNCA characterizes neurodegenerative diseases called synucleinopathies. Lewy body disease (LBD) shows predominantly neuronal -synuclein pathology and multiple system atrophy (MSA) predominantly oligodendrocytic -synuclein pathology affecting subcortical brain structures. Based on cryo-electron microscopy, it was reported that structures of -synuclein filaments from LBD differ from MSA and juvenile onset synucleinopathy (JOS) caused by a 21-nucleotide duplication in the second exon of one allele of SNCA gene 1-3. Importantly, a rare subtype of MSA, called atypical MSA4 shows abundant neuronal argyrophilic -synuclein inclusions in the limbic system. Current concepts indicate that disease entities are characterized by unique protofilament folds. Here we demonstrate that in addition to the MSA fold, -synuclein can form a new Lewy-MSA hybrid fold in the same brain region, leading to the atypical histopathological form of MSA. Distinct biochemical characteristics of -synuclein, as demonstrated by protease-sensitivity digestion assay, seed amplification assays (SAAs) and conformational stability assay (CSA), are also linked to cytopathological differences (e.g. neuronal or oligodendroglial). We expand the current structure-based classification of -synucleinopathies and propose that cell-specific protein pathologies can be associated with distinct filament folds.

pathology↗

bioRxiv2025

Progression of the cardiac phenotype of the DE50-MD dog model of Duchenne Muscular Dystrophy, corroborating results of cardiac magnetic resonance imaging with pathology up to 36 months of age.

Cardiomyopathy is an expected consequence of the invariably fatal, X-linked muscle-wasting disease, Duchenne Muscular Dystrophy, (DMD) but onset and progression vary between individuals. Cardiac magnetic resonance imaging (CMR) is invaluable for identification of subclinical myocardial abnormalities, to stratify disease and to identify patients needing early therapeutic intervention. The dystrophin-deficient DE50-MD canine model harbours a mutation in the major hot spot region for mutations in DMD patients and mimics the preclinical cardiac and skeletal muscle of DMD boys. We performed serial parametric (T1, T2 and extracellular volume) mapping and late gadolinium enhancement (LGE) studies to characterise myocardial pathology in 15-to-36-month-old DE50-MD, (n=8) and wild type (WT, n=6) dogs. In 6/8 DE50-MD dogs left ventricular (LV) subepicardial LGE identified myocardial fibrofatty infiltration, (confirmed with histopathology post-mortem) with the characteristic distribution reported in DMD cardiomyopathy. Parametric mapping techniques exposed diffuse myocardial pathology that was most pronounced in DE50-MD dogs of 30 months and older and supported extracellular matrix expansion due to fibrosis, with or without regional myocardial oedema and /or fatty infiltration in individual dogs. All CMR markers of fibrosis worsened with age in DE50-MD dogs and paralleled deterioration in ventricular function evaluated with conventional and speckle tracking (circumferential strain) echocardiography, the burden of fragmented QRS complexes in 12-lead electrocardiography studies and the severity of pathological lesions. LGE and parametric mapping studies accurately identified a spectrum of myocardial abnormalities encountered in young DE50-MD dogs, further validating the relevance of these dogs as a preclinical model of DMD cardiomyopathy.

pathology↗

bioRxiv2025

Detection of prostate cancer in 3D pathology datasets via generative immunolabeling

Recent advancements in nondestructive 3D pathology offer a complement to standard histology by enabling comprehensive volumetric analyses of intact clinical specimens (e.g. biopsies). Prior studies have demonstrated the added prognostic value of 3D pathology for prostate cancer risk stratification by correlating 3D microarchitectural features with long-term patient outcomes. However, these analyses relied on coarse manual annotations of cancer-enriched regions for downstream analysis without fine-grained delineation between often-intermixed cancerous and benign glands. To address these limitations, we have developed a 3D computational pipeline: Synthetic Immunolabeling for Generative Heatmaps of Tumor (SIGHT). SIGHT relies on deep learning-based 3D image translation models, trained in a fully supervised fashion, to convert H&E-analog 3D pathology datasets into multiplexed 3D immunofluorescence datasets that facilitate tumor detection. Our implementation of SIGHT synthetically labels two cytokeratin markers that are differentially expressed in cancerous and benign prostate glands, which are used to generate explainable 3D heatmaps of cancer-enriched regions in prostate tissues. Validation of SIGHT against ground-truth annotations from a panel of genitourinary pathologists yields an average F1 score of 0.88 which is comparable to the average inter-pathologist agreement F1 score of 0.90. To demonstrate the value of SIGHT, we developed machine classifiers of recurrence risk based on 3D glandular histomorphometric features from 75 patients. Volumetric glandular analysis in SIGHT-identified cancer-enriched regions vs. all tissue regions yields an average Kaplan-Meier hazard ratio of 3.57 (1.6 - 7.9 CI) vs. 0.92 (0.45 - 1.89 CI).

pathology↗

bioRxiv2025

Single-vessel transcriptome map pathological landscapes and reveal NR2F2-mediated smooth muscle cell phenotype acquisition in capillary malformations

BackgroundCapillary malformation (CM) is a congenital vascular anomaly affecting the skin, mucosa, and brain, yet the understanding of its vascular pathogenesis remains limited. MethodsWe applied spatial whole-transcriptome profiling (GeoMx) and gene set enrichment analysis within CM lesions at single vasculature level. Differentially expressed genes were validated by immunofluorescence staining. Phosphoproteomics was profiled to uncover lesion- wide phosphorylation sites on proteins. Single-cell RNA sequencing was performed on CM- derived induced pluripotent stem cells (iPSCs) to determine differentiation trajectories of lesional vascular lineages. In silico gene perturbation was used to predict candidate genes for modulating vascular pathological progression, followed by functional validation in CM iPSC-derived endothelial cells (ECs) using a Tet-on system. ResultsA spatial transcriptomic atlas was constructed, and pathological landscape of individual CM vasculature was delineated. CM vessels exhibited hallmarks of endothelial-to-mesenchymal transition (EndMT), including disruption of adherens junctions (AJs), vascular identity transitions, and metabolic remodeling. Phosphoproteomics confirmed that differentially phosphorylated proteins were enriched in EndMT- and AJ-related pathways. Aberrant expression of venous transcriptional factor NR2F2 was observed in lesional ECs and correlated with progressive enlargement from capillaries to larger-caliber vessels containing multiple layers of smooth muscle cells (SMCs). In CM iPSCs, differentiation course yielded reduced ECs but increased SMCs. In silico knockout simulation predicted NR2F2 as a crucial regulator of facilitating SMC phenotype in CM. Consistently, enforced NR2F2 expression during iPSC differentiation suppressed endothelial markers while inducing SMC-associated genes. ConclusionsSingle CM vasculature displays pathological hallmarks characterized by EndMT and AJ disruption, leading to progressive vascular remodeling. NR2F2 functions as a central regulatory factor orchestrating the acquisition of the SMC phenotype, thereby representing a potential therapeutic target in CM.

pathology↗

bioRxiv2025

Pathological Angiogenesis Precedes the Onset of Aortic Dissection

Aortic dissection (AD) is a severe, life-threatening disease that occurs abruptly1. Although remodeling and inherent vulnerability of the aortic media, as observed in heritable connective tissue disorders such as Marfan syndrome, have been implicated in the onset of AD, the precise pathological mechanisms underlying the non-heritable form, which accounts for most cases, remains largely unknown2. Here, using hyperacute AD patient-derived samples, we show that pathological angiogenesis within the aortic media precedes the onset of dissection. Integrating single-cell transcriptomic analysis of aortic medial endothelial cells with high-resolution imaging revealed temporal changes preceding dissection. Hypoxic alterations in the media triggered osteochondrogenic changes in smooth muscle cells, promoted hydroxyapatite deposition, and induced angiogenesis via VEGF secretion from AD-specific CD14+CD68+CD163+MRC1(CD206)neg-low macrophages. Atomic force microscopy revealed that these processes culminated in the formation of a soft capillary layer, potentially concentrating stress on this region and contributing to AD onset. H&E staining of archived specimens revealed that non-heritable AD can be classified into angiogenic or non-angiogenic subtypes, with more than half exhibiting the former. In contrast, acute AD cases associated with Marfan syndrome typically exhibit a non-angiogenic pattern, suggesting distinct underlying mechanisms. This study reports angiogenesis as a key pathological driver in non-heritable AD and highlight potential targets for early diagnosis, prevention, and treatment.

pathology↗

bioRxiv2017

Dietary and behavioral inferences from dental pathology and non-masticatory wear on dentitions from a British medieval town

Dental pathology and wear data can provide valuable insights into diet, cultural practices, and the health of populations. In this study, various dental pathologies and types of wear were recorded for 41 individuals (914 permanent teeth), excavated from the medieval cemetery of St. Owens Church in Southgate Street, Gloucester. Teeth were studied macroscopically with a 10x hand lens to confirm the presence of specific pathologies. Relatively high rates of antemortem chipping on the anterior teeth, and the presence of maxillary central incisor notches, suggested that the Gloucester population commonly used their teeth for non-masticatory activities. Abscessing and antemortem tooth loss fell within previously reported ranges for British medieval sites (2.6% and 6% respectively). However, the sample exhibits extremely high levels of carious lesions and calculus. Nearly 24% of teeth have at least one carious lesion, and the presence of calculus was recorded in 74% of teeth within the sample. Overall caries frequency is similar to sites from later time periods. This frequency may reflect Gloucesters location as a large port town. Remains from the same area, but the earlier Roman period, also shows high rates of both caries and calculus, suggesting a continuation of consuming certain cariogenic foods is likely.

pathology↗

bioRxiv2026

Distinct Hippocampal Cellular Pathologies Influence Cognition Across Diagnostic Categories, also distinguishing Schizophrenia from Affective Psychoses

Introduction: Total and social cognition deficits independently predict functioning in psychosis, but targeting these in clinical trials are unsuccessful in improving function. The admixture of schizophrenia and affective psychoses cases could be a roadblock if these differ in cellular pathology. Methods: We examined cognitive functioning (MATRICS) and hippocampal cellular pathologies based on metabolite biomarker concentrations (1H-MRSI), using categorical and transdiagnostic classifications in 80 participants: 22 non-psychotic affective disorder (NP-aff), 25 healthy controls (HC), and 33 with psychosis (Psy), including 20 schizophrenia and 13 affective psychoses (aff-P) cases. Results: NP-aff and HC had similar total cognition (46.64{+/-}12.01 vs 41.10{+/-}17.88), both superior to Psy (28.34{+/-} 12.34; p's<0.01). Mean metabolite concentrations were similar across all groups but showed significant within-group associations to cognitive tests. For HC, total cognition, working memory and reasoning deficits were associated with reduced neuronal integrity (-.414, -.422, -.433, p's<.05), although no biomarker predicted total cognition in the clinical groups. FFor NP-aff, elevated myelin/membrane concentrations accompanied cognitive deficits; significantly so for visual learning deficits (.446, p<.05), which were also associated with decreased glia (-.503, p<.05). Opposite NP-aff, reduced myelin/membrane concentrations predicted cognitive deficits in Psy (-.514, p<.05). Separating schizophrenia from aff-P on social cognition showed reduced glutamate/excitation in schizophrenia (-.673, p<.05) ibut higher myelin/membrane turnover and neuronal integrity concentrations in aff-P (.575, .581, p's<.05). Conclusions: Schizophrenia and affective psychosis significantly differed for biomarkers of cellular pathology related to social cognition. Distinctly different underpinnings for cognition were also identified for other groups, aligning with DSM-5 and ICD disorder based categories. These findings include support for heterogeneous, but not transdiagnostic, conceptualizations of cognition and psychosis.

pathology↗

bioRxiv2026

Prototype-based AI triage for 3D pathology

Non-destructive 3D pathology enables high-resolution slide-free imaging of intact clinical specimens, providing comprehensive visualization of tissue structures beyond what conventional slide-based 2D histopathology can provide. However, the scale and complexity of volumetric datasets make exhaustive manual review impractical, motivating AI-assisted triage methods to select a small number of high-risk 2D slices for pathologist review. While prior triage models have shown promise, interpretability is poor and performance can be suboptimal, especially in the nascent field of 3D pathology in which labeled data is limited. We present SCOPE, a Segmentation-guided CrOss-slice PrototypE learning framework for comprehensive risk assessment of 2D levels within 3D pathology datasets. SCOPE combines (i) clustering-based pretraining on large-scale unlabeled volumetric data to initialize morphology-aware prototypes, (ii) segmentation-derived structural priors from publicly available models to guide proto-type learning, and (iii) cross-slice (2.5D) prototype aggregation across neighboring slices to generate slice-level risk predictions. In prostate and esophageal data cohorts, SCOPE consistently outperforms attention-based and prototype-based multiple instance learning baselines for both binary and multiclass prediction tasks, enabling depth-resolved risk profiling for 3D triage based on morphological prototypes that are interpretable to pathologists.

pathology↗

bioRxiv2026

Automated Virtual Pathology Panels for Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) records rich molecular spectra at each pixel, but pathology-oriented interpretation requires visualizations analogous to complementary histopathological stains. We present an expert-aligned framework for constructing multi-view MSI panels. Soft Landmark Contrast Edges (SoLaCE) extracts molecular boundaries directly from high-dimensional spectra. Because standard visualization metrics correlated poorly with rankings from a single expert pathologist, we combine luminance contrast and chromatic diversity with SpecEdge-Dice, a boundary-aware measure of agreement between visualization edges and SoLaCE boundaries. Parametric MiCS+LMC (pMiCS) uses a neural network trained on subsampled data to distill multiple MSI segmentations into a reusable spectral-to-RGB mapping, enabling rapid full-image inference, out-of-sample projection, and more consistent color semantics across aligned images. A concept-based interpretation procedure explains pMiCS outputs through sparse mixtures of spectral concepts. In a blinded benchmark, pMiCS ranked highest among the compared methods. We integrate these components into Virtual Pathology Panels, which use hyperparameter optimization to select high-performing or spatially complementary views. This framework supports future workflows that combine morphology-oriented tissue assessment and molecular analysis within a single MSI acquisition. TeaserVirtual pathology panels transform MSI spectra into complementary views for scalable, interpretable tissue analysis.

pathology↗

bioRxiv2026

Stain Normalisation Does Not Consistently Improve Matched-Location Retrieval with Pathology Foundation Models

Pathology foundation models provide reusable representations for computational pathology, but staining- and scanner-induced variation may compromise the robustness and reproducibility of embedding-based analyses across acquisition settings. Stain normalisation is widely used to mitigate such colour variation, yet whether it improves retrieval with modern self-supervised pathology encoders remains unclear. We test whether stain normalisation improves cross-scanner and cross-staining image retrieval using the PLISM whole-slide image subset, comprising 13 co-registered images of serial sections prepared under different staining conditions and digitised using seven scanners (91 whole-slide images). We sample 400 matched locations across the 91 images, yielding 36,400 tile instances. We compare two DINOv2-based encoders, Phikon-v2 (1,024-dimensional) and Midnight-12k (3,072-dimensional), with Reinhard and Macenko normalisation against an unnormalised baseline. Performance is measured using paired top-1 nearest-neighbour retrieval accuracy in two settings: cross-scanner retrieval of the same physical section digitised by different scanners, and cross-staining retrieval across co-registered images of serial sections, which differ in staining condition and may also contain section-level morphological variation. Neither normalisation method consistently improves top-1 retrieval relative to no normalisation, while Macenko reduces accuracy by up to 18.3 percentage points. An exploratory UMAP of unnormalised Midnight-12k slide-level mean embeddings showed partial overlap between scanner groups in a two-dimensional projection. These results challenge the routine use of stain normalisation in foundation-model retrieval pipelines and support validating preprocessing choices for each encoder and retrieval setting.

pathology↗

bioRxiv2015

Modulating pathological oscillations by rhythmic non-invasive brain stimulation – a therapeutic concept?

A large amount of studies of the last decades revealed an association between human behaviour and oscillatory activity in the human brain. Alike, abnormalities of oscillatory activity were related with pathological behaviour in many neuropsychiatric disorders, such as in Parkinsons disease (PD) or in schizophrenia (SCZ). As a therapeutic tool, non-invasive brain stimulation (NIBS) has demonstrated the potential to improve behavioural performance in patients suffering from neuropsychiatric disorders. Since evidence accumulates that NIBS might be able to modulate oscillatory activity and related behaviour in a scientific setting, this review focuses on discussing potential interventional strategies to target abnormalities in oscillatory activity in neuropsychiatric disorders. In particular, we will review oscillatory changes described in patients after stroke, with PD or suffering from SCZ. Potential ways of targeting interventionally the underlying pathological oscillations to improve related pathological behaviour will be further discussed.

Neuroscience↗

bioRxiv2017

Lewy pathology in Parkinson’s disease consists of a crowded organellar membranous medley

Parkinsons disease, the most common age-related movement disorder, is a progressive neurodegenerative disease with unclear etiology. Key neuropathological hallmarks are Lewy bodies and Lewy neurites, which are neuronal inclusions that are immunopositive for the protein -synuclein. In-depth ultrastructural analysis of this Lewy pathology is crucial to understanding pathogenesis and progression of the disease. Using correlative light and electron microscopy/tomography on brain tissue from five Parkinsons disease brain donors, we identified -synuclein immunopositive Lewy pathology and could show that the majority of these features including Lewy bodies and Lewy neurites primarily consists of a crowded membranous medley of vesicular structures and dysmorphic organelles. Only a small fraction of observed Lewy bodies contained predominant proteinaceous filaments, as previously described. The crowding of organellar components was confirmed by STED- based super-resolution microscopy, and high lipid content within the -synuclein immunopositive inclusions was corroborated by confocal imaging, CARS/FTIR imaging and lipidomics. Applying this correlative high-resolution imaging and biophysical approach, we discovered in the postmortem brain of Parkinsons patients a subcellular protein-lipid compartmentalization not previously described in Lewy pathology.

neuroscience↗