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Ingrassia L, Boluda S, Potier MC, Haïk S, Jimenez G, Kar A, Racoceanu D, Delatour B, Stimmer L. Automated deep learning segmentation of neuritic plaques and neurofibrillary tangles in Alzheimer disease brain sections using a proprietary software. J Neuropathol Exp Neurol 2024; 83:752-762. [PMID: 38812098 PMCID: PMC11333827 DOI: 10.1093/jnen/nlae048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024] Open
Abstract
Neuropathological diagnosis of Alzheimer disease (AD) relies on semiquantitative analysis of phosphorylated tau-positive neurofibrillary tangles (NFTs) and neuritic plaques (NPs), without consideration of lesion heterogeneity in individual cases. We developed a deep learning workflow for automated annotation and segmentation of NPs and NFTs from AT8-immunostained whole slide images (WSIs) of AD brain sections. Fifteen WSIs of frontal cortex from 4 biobanks with varying tissue quality, staining intensity, and scanning formats were analyzed. We established an artificial intelligence (AI)-driven iterative procedure to improve the generation of expert-validated annotation datasets for NPs and NFTs thereby increasing annotation quality by >50%. This strategy yielded an expert-validated annotation database with 5013 NPs and 5143 NFTs. We next trained two U-Net convolutional neural networks for detection and segmentation of NPs or NFTs, achieving high accuracy and consistency (mean Dice similarity coefficient: NPs, 0.77; NFTs, 0.81). The workflow showed high generalization performance across different cases. This study serves as a proof-of-concept for the utilization of proprietary image analysis software (Visiopharm) in the automated deep learning segmentation of NPs and NFTs, demonstrating that AI can significantly improve the annotation quality of complex neuropathological features and enable the creation of highly precise models for identifying these markers in AD brain sections.
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Affiliation(s)
- Lea Ingrassia
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Susana Boluda
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
- Department of Neuropathology Raymond Escourolle, AP-HP, Pitié-Salpêtrière University Hospital, Paris, France
| | - Marie-Claude Potier
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Stéphane Haïk
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
- AP-HP, Cellule Nationale de Référence des MCJ, Salpêtrière Hospital, Paris, France
| | - Gabriel Jimenez
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Anuradha Kar
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Daniel Racoceanu
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Benoît Delatour
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Lev Stimmer
- Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Sorbonne Université, Hôpital de la Pitié-Salpêtrière, Paris, France
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Punzi M, Sestieri C, Picerni E, Chiarelli AM, Padulo C, Delli Pizzi A, Tullo MG, Tosoni A, Granzotto A, Della Penna S, Onofrj M, Ferretti A, Delli Pizzi S, Sensi SL. Atrophy of hippocampal subfields and amygdala nuclei in subjects with mild cognitive impairment progressing to Alzheimer's disease. Heliyon 2024; 10:e27429. [PMID: 38509925 PMCID: PMC10951508 DOI: 10.1016/j.heliyon.2024.e27429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 02/27/2024] [Accepted: 02/28/2024] [Indexed: 03/22/2024] Open
Abstract
The hippocampus and amygdala are the first brain regions to show early signs of Alzheimer's Disease (AD) pathology. AD is preceded by a prodromal stage known as Mild Cognitive Impairment (MCI), a crucial crossroad in the clinical progression of the disease. The topographical development of AD has been the subject of extended investigation. However, it is still largely unknown how the transition from MCI to AD affects specific hippocampal and amygdala subregions. The present study is set to answer that question. We analyzed data from 223 subjects: 75 healthy controls, 52 individuals with MCI, and 96 AD patients obtained from the ADNI. The MCI group was further divided into two subgroups depending on whether individuals in the 48 months following the diagnosis either remained stable (N = 21) or progressed to AD (N = 31). A MANCOVA test evaluated group differences in the volume of distinct amygdala and hippocampal subregions obtained from magnetic resonance images. Subsequently, a stepwise linear discriminant analysis (LDA) determined which combination of magnetic resonance imaging parameters was most effective in predicting the conversion from MCI to AD. The predictive performance was assessed through a Receiver Operating Characteristic analysis. AD patients displayed widespread subregional atrophy. MCI individuals who progressed to AD showed selective atrophy of the hippocampal subiculum and tail compared to stable MCI individuals, who were undistinguishable from healthy controls. Converter MCI showed atrophy of the amygdala's accessory basal, central, and cortical nuclei. The LDA identified the hippocampal subiculum and the amygdala's lateral and accessory basal nuclei as significant predictors of MCI conversion to AD. The analysis returned a sensitivity value of 0.78 and a specificity value of 0.62. These findings highlight the importance of targeted assessments of distinct amygdala and hippocampus subregions to help dissect the clinical and pathophysiological development of the MCI to AD transition.
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Affiliation(s)
- Miriam Punzi
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- Molecular Neurology Unit, Center for Advanced Studies and Technology (CAST), University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Carlo Sestieri
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- Institute for Advanced Biomedical Technologies (ITAB), “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Eleonora Picerni
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Antonio Maria Chiarelli
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Caterina Padulo
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- Department of Humanities, University of Naples Federico II, Naples, 80133, Italy
| | - Andrea Delli Pizzi
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Maria Giulia Tullo
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Annalisa Tosoni
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Alberto Granzotto
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- Molecular Neurology Unit, Center for Advanced Studies and Technology (CAST), University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Stefania Della Penna
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- Institute for Advanced Biomedical Technologies (ITAB), “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Marco Onofrj
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Antonio Ferretti
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- Institute for Advanced Biomedical Technologies (ITAB), “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- UdA-TechLab, Research Center, University “G. D’Annunzio” of Chieti-Pescara, 66100, Chieti, Italy
| | - Stefano Delli Pizzi
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- Institute for Advanced Biomedical Technologies (ITAB), “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- Molecular Neurology Unit, Center for Advanced Studies and Technology (CAST), University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
| | - Stefano L. Sensi
- Department of Neuroscience, Imaging, and Clinical Sciences, University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- Institute for Advanced Biomedical Technologies (ITAB), “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
- Molecular Neurology Unit, Center for Advanced Studies and Technology (CAST), University “G. D'Annunzio of Chieti-Pescara”, Chieti, 66100, Italy
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Ortega-Cruz D, Bress KS, Gazula H, Rabano A, Iglesias JE, Strange BA. Three-dimensional histology reveals dissociable human hippocampal long axis gradients of Alzheimer's pathology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.05.570038. [PMID: 38105985 PMCID: PMC10723286 DOI: 10.1101/2023.12.05.570038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
INTRODUCTION Three-dimensional (3D) histology analyses are essential to overcome sampling variability and understand pathological differences beyond the dissection axis. We present Path2MR, the first pipeline allowing 3D reconstruction of sparse human histology without an MRI reference. We implemented Path2MR with post-mortem hippocampal sections to explore pathology gradients in Alzheimer's Disease. METHODS Blockface photographs of brain hemisphere slices are used for 3D reconstruction, from which an MRI-like image is generated using machine learning. Histology sections are aligned to the reconstructed hemisphere and subsequently to an atlas in standard space. RESULTS Path2MR successfully registered histological sections to their anatomical position along the hippocampal longitudinal axis. Combined with histopathology quantification, we found an expected peak of tau pathology at the anterior end of the hippocampus, while amyloid-β displayed a quadratic anterior-posterior distribution. CONCLUSION Path2MR, which enables 3D histology using any brain bank dataset, revealed significant differences along the hippocampus between tau and amyloid-β.
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Affiliation(s)
- Diana Ortega-Cruz
- Laboratory for Clinical Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, IdISSC, 28223, Madrid, Spain
- Alzheimer's Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, 28031, Madrid, Spain
| | - Kimberly S Bress
- Alzheimer's Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, 28031, Madrid, Spain
- Current address: Vanderbilt University School of Medicine, 37232, Nashville, TN, USA
| | - Harshvardhan Gazula
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, 02129, Boston, MA, USA
| | - Alberto Rabano
- Alzheimer's Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, 28031, Madrid, Spain
| | - Juan Eugenio Iglesias
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, 02129, Boston, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 02139, Boston, MA, USA
- Centre for Medical Image Computing, University College London, WC1V 6LJ, London, United Kingdom
| | - Bryan A Strange
- Laboratory for Clinical Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, IdISSC, 28223, Madrid, Spain
- Alzheimer's Disease Research Unit, CIEN Foundation, Queen Sofia Foundation Alzheimer Center, 28031, Madrid, Spain
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Farrell K, Iida MA, Cherry JD, Casella A, Stein TD, Bieniek KF, Walker JM, Richardson TE, White CL, Alvarez VE, Huber BR, Dickson DW, Insausti R, Dams-O'Connor K, McKee AC, Crary JF. Differential Vulnerability of Hippocampal Subfields in Primary Age-Related Tauopathy and Chronic Traumatic Encephalopathy. J Neuropathol Exp Neurol 2022; 81:781-789. [PMID: 36004533 PMCID: PMC9487677 DOI: 10.1093/jnen/nlac066] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Chronic traumatic encephalopathy (CTE) is a tauopathy associated with repetitive mild head impacts characterized by perivascular hyperphosphorylated tau (p-tau) in neurofibrillary tangles (NFTs) and neurites in the depths of the neocortical sulci. In moderate to advanced CTE, NFTs accumulate in the hippocampus, potentially overlapping neuroanatomically with primary age-related tauopathy (PART), an age-related tauopathy characterized by Alzheimer disease-like tau pathology in the hippocampus devoid of amyloid plaques. We measured p-tau burden using positive-pixel counts on immunohistochemically stained and neuroanatomically segmented hippocampal tissue. Subjects with CTE had a higher total p-tau burden than PART subjects in all sectors (p = 0.005). Within groups, PART had significantly higher total p-tau burden in CA1/subiculum compared to CA3 (p = 0.02) and CA4 (p = 0.01) and total p-tau burden in CA2 trended higher than CA4 (p = 0.06). In CTE, total p-tau burden in CA1/subiculum was significantly higher than in the dentate gyrus; and CA2 also trended higher than dentate gyrus (p = 0.01, p = 0.06). When controlling for p-tau burden across the entire hippocampus, CA3 and CA4 had significantly higher p-tau burden in CTE than PART (p < 0.0001). These data demonstrate differences in hippocampal p-tau burden and regional distribution in CTE compared to PART that might be helpful in differential diagnosis and reveal insights into disease pathogenesis.
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Affiliation(s)
- Kurt Farrell
- Departments of Pathology, Artificial Intelligence & Human Health, Nash Family Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Megan A Iida
- Departments of Pathology, Artificial Intelligence & Human Health, Nash Family Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Jonathan D Cherry
- Department of Pathology, Alzheimer's Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Veterans Affairs Medical Center, Bedford, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Alicia Casella
- Departments of Pathology, Artificial Intelligence & Human Health, Nash Family Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Thor D Stein
- Department of Pathology, Alzheimer's Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Veterans Affairs Medical Center, Bedford, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Kevin F Bieniek
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, Texas, USA
- Department of Pathology, University of Texas Health Science Center, San Antonio, Texas, USA
| | - Jamie M Walker
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, Texas, USA
- Department of Pathology, University of Texas Health Science Center, San Antonio, Texas, USA
| | - Timothy E Richardson
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, Texas, USA
- Department of Pathology, University of Texas Health Science Center, San Antonio, Texas, USA
| | - Charles L White
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Victor E Alvarez
- Department of Pathology, Alzheimer's Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Veterans Affairs Medical Center, Bedford, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Bertrand R Huber
- Department of Pathology, Alzheimer's Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Veterans Affairs Medical Center, Bedford, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Dennis W Dickson
- Departments of Pathology and Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Ricardo Insausti
- Human Neuroanatomy Laboratory, School of Medicine, University of Castilla-La Mancha, Albacete, Spain
| | - Kristen Dams-O'Connor
- Department of Rehabilitation and Human Performance, Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ann C McKee
- Department of Pathology, Alzheimer's Disease and CTE Center, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Veterans Affairs Medical Center, Bedford, Massachusetts, USA
- VA Boston Healthcare System, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA
| | - John F Crary
- Departments of Pathology, Artificial Intelligence & Human Health, Nash Family Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Španić E, Langer Horvat L, Ilić K, Hof PR, Šimić G. NLRP1 Inflammasome Activation in the Hippocampal Formation in Alzheimer's Disease: Correlation with Neuropathological Changes and Unbiasedly Estimated Neuronal Loss. Cells 2022; 11:2223. [PMID: 35883667 PMCID: PMC9324749 DOI: 10.3390/cells11142223] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/12/2022] [Accepted: 07/16/2022] [Indexed: 02/04/2023] Open
Abstract
Neuroinflammation is one of the core pathological features of Alzheimer's disease (AD) as both amyloid β (Aβ) and tau monomers and oligomers can trigger the long-term pro-inflammatory phenotype of microglial cells with consequent overactivation of the inflammasomes. To investigate the NLRP1 inflammasome activation in AD, we analyzed the expression of NLRP1, ASC, cleaved gasdermin (cGSDMD), and active caspase-6 (CASP-6) proteins in each hippocampal subdivision (hilar part of CA3, CA2/3, CA1, subiculum) of postmortem tissue of 9 cognitively healthy controls (HC) and 11 AD patients whose disease duration varied from 3 to 7 years after the clinical diagnosis. The total number of neurons, along with the total number of neurofibrillary tangles (NFTs), were estimated in Nissl- and adjacent modified Bielschowsky-stained sections, respectively, using the optical disector method. The same 9 HC and 11 AD cases were additionally semiquantitatively analyzed for expression of IBA1, HLA-DR, and CD68 microglial markers. Our results show that the expression of NLRP1, ASC, and CASP-6 is present in a significantly greater number of hippocampal formation neurons in AD brains compared to controls, suggesting that the NLRP1 inflammasome is more active in the AD brain. None of the investigated inflammasome and microglial markers were found to correlate with the age of the subjects or the duration of AD. However, besides positive correlations with microglial IBA1 expression in the subiculum and with microglial CD68 expression in the CA1 field and subiculum in the AD group, the overall NLRP1 expression in the hippocampal formation was positively correlated with the number of NFTs, thus providing a causal link between neuroinflammation and neurofibrillary degeneration. The accumulation of AT8-immunoreactive phosphorylated tau proteins that we observed at nuclear pores of large pyramidal neurons of the Ammon's horn further supports their role in the extent of neuronal dysfunction and degeneration in AD. This is important because unlike fibrillar amyloid-β deposits that are not related to dementia severity, total NFTs and neuron numbers in the hippocampal formation, especially in the CA1 field, are the best correlates of cognitive deterioration in both human brain aging and AD. Our findings also support the notion that the CA2 field vulnerability is strongly linked to specific susceptibilities to different tauopathies, including primary age-related tauopathy. Altogether, these findings contrast with reports of nonsignificant microglial activation in aged nonhuman primates and indicate that susceptibility to inflammasome activation may render the human brain comparatively more vulnerable to neurodegenerative changes and AD. In conclusion, our results confirm a key role of NLRP1 inflammasome in AD pathogenesis and suggest NLRP1 as a potential diagnostic marker and therapeutic target to slow or prevent AD progression.
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Affiliation(s)
- Ena Španić
- Department of Neuroscience, Croatian Institute for Brain Research, University of Zagreb School of Medicine, Šalata 12, 10000 Zagreb, Croatia; (E.Š.); (L.L.H.); (K.I.)
| | - Lea Langer Horvat
- Department of Neuroscience, Croatian Institute for Brain Research, University of Zagreb School of Medicine, Šalata 12, 10000 Zagreb, Croatia; (E.Š.); (L.L.H.); (K.I.)
| | - Katarina Ilić
- Department of Neuroscience, Croatian Institute for Brain Research, University of Zagreb School of Medicine, Šalata 12, 10000 Zagreb, Croatia; (E.Š.); (L.L.H.); (K.I.)
- BRAIN Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London WC2R 2LS, UK
| | - Patrick R. Hof
- Nash Family Department of Neuroscience, Friedman Brain Institute, and Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Goran Šimić
- Department of Neuroscience, Croatian Institute for Brain Research, University of Zagreb School of Medicine, Šalata 12, 10000 Zagreb, Croatia; (E.Š.); (L.L.H.); (K.I.)
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Wang X, Zhang L, Lu H, Wu J, Liang H, Sun B, Zhu K. Expression Pattern of p62 in Primary Age-Related Tauopathy: Staging of p62 in PART. Front Aging Neurosci 2022; 14:793353. [PMID: 35547629 PMCID: PMC9084313 DOI: 10.3389/fnagi.2022.793353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 02/28/2022] [Indexed: 11/25/2022] Open
Abstract
The present study analyzed the distribution pattern of p62 immunoreactivity in brains of primary age-related tauopathy (PART) and Braak NFT matched pre-AD and Alzheimer’s disease (AD) patients using immunohistochemistry in combination with semi-quantitative evaluation. In PART and AD brains, p62 was found positive in seven regions, including the neocortex, thalamus, basal ganglia, hippocampus, brainstem, cerebellar dentate nucleus, and the cervical spinal cord. There was a positive correlation between the Braak NFT stage and the distribution of p62 expression. Six stages of expression of p62 were proposed from the present study. Expression of p62 in the hippocampus of PART and AD was classified stage I, the brainstem stage II, the thalamus stage I _I _I, the basal ganglia stage IV, the neocortex stage V, the cerebellum and the cervical spinal cord stage VI. The hippocampus was the site initially affected by p62, especially the CA1 and the subiculum. They might be the earliest accumulation site of p62.
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Affiliation(s)
- Xin Wang
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, China
| | - Lei Zhang
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Lu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China
| | - Juanli Wu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China
| | - Huazheng Liang
- Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People’s Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Bing Sun
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China
| | - Keqing Zhu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, China
- Department of Pathology, Zhejiang University School of Medicine, Hangzhou, China
- *Correspondence: Keqing Zhu,
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Jellinger KA. Recent update on the heterogeneity of the Alzheimer’s disease spectrum. J Neural Transm (Vienna) 2021; 129:1-24. [DOI: 10.1007/s00702-021-02449-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 11/25/2021] [Indexed: 02/03/2023]
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8
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Koga S, Ghayal NB, Dickson DW. Deep Learning-Based Image Classification in Differentiating Tufted Astrocytes, Astrocytic Plaques, and Neuritic Plaques. J Neuropathol Exp Neurol 2021; 80:306-312. [PMID: 33570124 DOI: 10.1093/jnen/nlab005] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
This study aimed to develop a deep learning-based image classification model that can differentiate tufted astrocytes (TA), astrocytic plaques (AP), and neuritic plaques (NP) based on images of tissue sections stained with phospho-tau immunohistochemistry. Phospho-tau-immunostained slides from the motor cortex were scanned at 20× magnification. An automated deep learning platform, Google AutoML, was used to create a model for distinguishing TA in progressive supranuclear palsy (PSP) from AP in corticobasal degeneration (CBD) and NP in Alzheimer disease (AD). A total of 1500 images of representative tau lesions were captured from 35 PSP, 27 CBD, and 33 AD patients. Of those, 1332 images were used for training, and 168 images for cross-validation. We tested the model using 100 additional test images taken from 20 patients of each disease. In cross-validation, precision and recall for each individual lesion type were 100% and 98.0% for TA, 98.5% and 98.5% for AP, and 98.0% and 100% for NP, respectively. In a test set, all images of TA and NP were correctly predicted. Only eleven images of AP were predicted to be TA or NP. Our data indicate the potential usefulness of deep learning-based image classification methods to assist in differential diagnosis of tauopathies.
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Affiliation(s)
- Shunsuke Koga
- From the Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Nikhil B Ghayal
- From the Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Dennis W Dickson
- From the Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
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Bauer S, Jin W, Zhang F, Linhardt RJ. The Application of Seaweed Polysaccharides and Their Derived Products with Potential for the Treatment of Alzheimer's Disease. Mar Drugs 2021; 19:89. [PMID: 33557077 PMCID: PMC7913876 DOI: 10.3390/md19020089] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 01/30/2021] [Accepted: 02/02/2021] [Indexed: 12/12/2022] Open
Abstract
Neurodegenerative diseases are among the most widespread diseases affecting humans, and the number of patients is only rising. Seaweed polysaccharide extracts show significant neuroprotective and reparative activities. Seaweed polysaccharides might provide the next big breakthrough in neurodegenerative disease treatment. This paper reviews the applications of seaweed polysaccharides as potential treatments of neurodegenerative diseases. The particular focus is on fucoidan, ulvan, and their derivatives as potential agents to treat Alzheimer's disease. This review provides a critical update on the progress in this important research area.
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Affiliation(s)
- Sarah Bauer
- Center for Biotechnology and Interdisciplinary Studies, Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Weihua Jin
- Center for Biotechnology and Interdisciplinary Studies, Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
- College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou 310014, China
| | - Fuming Zhang
- Center for Biotechnology and Interdisciplinary Studies, Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Robert J Linhardt
- Center for Biotechnology and Interdisciplinary Studies, Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
- Center for Biotechnology and Interdisciplinary Studies, Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
- Center for Biotechnology and Interdisciplinary Studies, Departments of Biological Science, Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
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Jellinger KA. Neuropathological assessment of the Alzheimer spectrum. J Neural Transm (Vienna) 2020; 127:1229-1256. [PMID: 32740684 DOI: 10.1007/s00702-020-02232-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 07/14/2020] [Indexed: 12/12/2022]
Abstract
Alzheimer disease (AD), the most common form of dementia globally, classically defined a clinicopathological entity, is a heterogenous disorder with various pathobiological subtypes, currently referred to as Alzheimer continuum. Its morphological hallmarks are extracellular parenchymal β-amyloid (amyloid plaques) and intraneuronal (tau aggregates forming neurofibrillary tangles) lesions accompanied by synaptic loss and vascular amyloid deposits, that are essential for the pathological diagnosis of AD. In addition to "classical" AD, several subtypes with characteristic regional patterns of tau pathology have been described that show distinct clinical features, differences in age, sex distribution, biomarker levels, and patterns of key network destructions responsible for cognitive decline. AD is a mixed proteinopathy (amyloid and tau), frequently associated with other age-related co-pathologies, such as cerebrovascular lesions, Lewy and TDP-43 pathologies, hippocampal sclerosis, or argyrophilic grain disease. These and other co-pathologies essentially influence the clinical picture of AD and may accelerate disease progression. The purpose of this review is to provide a critical overview of AD pathology, its defining pathological substrates, and the heterogeneity among the Alzheimer spectrum entities that may provide a broader diagnostic coverage of this devastating disorder as a basis for implementing precision medicine approaches and for ultimate development of successful disease-modifying drugs for AD.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, 1150, Vienna, Austria.
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