Investigating the feasibility of 18F‐flortaucipir PET imaging in the antemortem diagnosis of primary age‐related tauopathy (PART): An observational imaging‐pathological study
AbstractINTRODUCTIONPrimary age‐related tauopathy (PART) is characterized by neurofibrillary tangles and minimal β‐amyloid deposition, diagnosed postmortem. This study investigates 18F‐flortaucipir (FTP) PET imaging for antemortem PART diagnosis.METHODSWe analyzed FTP PET scans from 50 autopsy‐confirmed PART and 13 control subjects. Temporal lobe uptake was assessed both qualitatively and quantitatively. Demographic and clinicopathological characteristics and voxel‐level uptake using SPM12 were compared between FTP‐positive and FTP‐negative cases. Intra‐reader reproducibility was evaluated with Krippendorff's alpha.RESULTSMinimal/mild and moderate FTP uptake was seen in 32% of PART cases and 62% of controls, primarily in the left inferior temporal lobe. No demographic or clinicopathological differences were found between FTP‐positive and FTP‐negative cases. High intra‐reader reproducibility (α = 0.83) was noted.DISCUSSIONFTP PET imaging did not show a specific uptake pattern for PART diagnosis, indicating that in vivo PART identification using FTP PET is challenging. Similar uptake in controls suggests non‐specific uptake in PART.Highlights 18F‐flortaucipir (FTP) PET scans were analyzed for diagnosing PART antemortem. 32% of PART cases had minimal/mild FTP uptake in the left inferior temporal lobe. Similar to PART FTP uptake was found in 62% of control subjects. No specific uptake pattern was found, challenging in vivo PART diagnosis.
Comparative Study of GPT-4Vision and Convolutional Neural Networks in Histopathological Image Analysis
American Journal of Clinical Pathology | October 15, 2024 | Volume: 162 | Issue: Supplement_1 | Pages: S137-S138
Abstract Introduction/Objective Recent advancements in artificial intelligence (AI), particularly with Large Language Models like ChatGPT-4Vision (GPT-4V), have expanded the potential for automated interpretation of medical images. This study evaluates the diagnostic accuracy of GPT-4V in histopathological analysis of neurodegenerative diseases and compares its performance with traditional Convolutional Neural Networks (CNNs). Methods/Case Report We utilized 1515 histopathological images, including hematoxylin and eosin (H&E) staining and tau immunohistochemistry, from patients with various neurodegenerative diseases, such as Alzheimer’s disease, progressive supranuclear palsy, and corticobasal degeneration. GPT-4V’s performance was assessed through multi- step prompts to assess how textual context influences the image interpretation. In the quantitative analysis, the diagnostic accuracy of GPT-4V and the CNN-based model YOLOv8 was assessed for classifying three tau lesions—astrocytic plaques, neuritic plaques, and tufted astrocytes. The analysis used both zero-shot and few-shot learning methods, where GPT-4V and YOLOv8 were evaluated on their ability to distinguish these lesions using ten hold-out test images and 490 training images per lesion. Results (if a Case Study enter NA) GPT-4V accurately recognized Lewy bodies in all cases, but it showed limited accuracy in identifying neurofibrillary tangles (20%) and Pick bodies (0%) on H&E slides. Notably, GPT-4V often suggested Alzheimer’s disease as a potential diagnosis, relying more on contextual clues, such as the prevalence of certain diseases, rather than direct image analysis. In the tau immunohistochemical analysis, GPT-4V’s diagnoses were strongly influenced by additional information about staining and brain region. However, few-shot learning markedly improved GPT-4V’s diagnostic capabilities from 40% accuracy with zero-shot learning to 90% with few-shot learning, reaching best accuracy with 20-shot learning. This performance compared favorably against YOLOv8, which also achieved 90% accuracy but required 100-shot learning. Conclusion While GPT-4V faces challenges in independently interpreting histopathological images, few-shot learning significantly improves its accuracy. This approach is particularly promising for neuropathology, where acquiring extensive labeled datasets is challenging. The findings highlight the need for ongoing refinement of AI applications in pathology, emphasizing balanced integration of textual and visual data to optimize diagnostic efficacy and reliability.
Amyloid PET detects the deposition of brain Aβ earlier than CSF fluid biomarkers
AbstractINTRODUCTIONUnderstanding the relationship between amyloid beta (Aβ) positron emission tomography (PET) and Aβ cerebrospinal fluid (CSF) biomarkers will define their potential utility in Aβ treatment. Few population‐based or neuropathologic comparisons have been reported.METHODSParticipants 50+ years with Aβ PET and Aβ CSF biomarkers (phosphorylated tau [p‐tau]181/Aβ42, n = 505, and Aβ42/40, n = 54) were included from the Mayo Clinic Study on Aging. From these participants, an autopsy subgroup was identified (n = 47). The relationships of Aβ PET and Aβ CSF biomarkers were assessed cross‐sectionally in all participants and longitudinally in autopsy data.RESULTSCross‐sectionally, more participants were Aβ PET+ versus Aβ CSF− than Aβ PET− versus Aβ CSF+ with an incremental effect when using Aβ PET regions selected for early Aβ deposition. The sensitivity for the first detection of Thal phase ≥ 1 in longitudinal data was higher for Aβ PET (89%) than p‐tau181/Aβ42 (64%).DISCUSSIONAβ PET can detect earlier cortical Aβ deposition than Aβ CSF biomarkers. Aβ PET+ versus Aβ CSF− findings are several‐fold greater using regional Aβ PET analyses and in peri‐threshold‐standardized uptake value ratio participants.Highlights Amyloid beta (Aβ) positron emission tomography (PET) has greater sensitivity for Aβ deposition than Aβ cerebrospinal fluid (CSF) in early Aβ development. A population‐based sample of participants (n = 505) with PET and CSF tests was used. Cortical regions showing early Aβ on Aβ PET were also used in these analyses. Neuropathology was used to validate detection of Aβ by Aβ PET and Aβ CSF biomarkers.
Primary Progressive Aphasia Lacking Core Features of Nonfluent and Semantic Variants
Neurology | October 8, 2024 | Volume: 103 | Issue: 9 | Pages: No page available
Mutations in the PINK1 and PRKN genes are the most frequent genetic cause of early-onset Parkinson disease. The pathogenic p.R275W substitution in PRKN is the most frequent substitution observed in patients, and thus far has been characterized mostly through overexpression models that suggest a possible gain of toxic misfunction. However, its effects under endogenous conditions are largely unknown. We used patient fibroblasts, isogenic neurons, and post-mortem human brain samples from carriers with and without PRKN p.R275W to assess functional impact. Immunoblot analysis and immunofluorescence were used to study mitophagy activation, and mitophagy execution was analyzed by flow cytometry of the reporter mitoKeima. The functional analysis was accompanied by structural investigation of PRKN p.R275W. We observed lower PRKN protein in fibroblasts with compound heterozygous p.R275W mutations. Isogenic neurons showed an allele-dose dependent decrease in PRKN protein. Lower PRKN protein levels were accompanied by diminished phosphorylated ubiquitin and decreased MFN2 modification. Mitochondrial degradation was also allele-dose dependently impaired. Consistently, PRKN protein levels were drastically reduced in human brain samples from p.R275W carriers. Finally, structural simulations showed significant changes in the closed form of PRKN p.R275W. Our data suggest that under endogenous conditions the p.R275W mutation results in a loss-of-function by destabilizing PRKN.
Modeling Lewy body disease with
SNCA
triplication iPSC-derived cortical organoids and identifying therapeutic drugs
Science Advances | September 11, 2024 | Volume: 10 | Issue: 37 | Pages: No page available
Aggregated α-synuclein (α-SYN) proteins, encoded by the SNCA gene, are hallmarks of Lewy body disease (LBD), affecting multiple brain regions. However, the specific mechanisms underlying α-SYN pathology in cortical neurons, crucial for LBD-associated dementia, remain unclear. Here, we recapitulated α-SYN pathologies in human induced pluripotent stem cells (iPSCs)–derived cortical organoids generated from patients with LBD with SNCA gene triplication. Single-cell RNA sequencing, combined with functional and molecular validation, identified synaptic and mitochondrial dysfunction in excitatory neurons exhibiting high expression of the SNCA gene, aligning with observations in the cortex of autopsy-confirmed LBD human brains. Furthermore, we screened 1280 Food and Drug Administration–approved drugs and identified four candidates (entacapone, tolcapone, phenazopyridine hydrochloride, and zalcitabine) that inhibited α-SYN seeding activity in real-time quaking-induced conversion assays with human brains, reduced α-SYN aggregation, and alleviated mitochondrial dysfunction in SNCA triplication organoids and excitatory neurons. Our findings establish human cortical LBD models and suggest potential therapeutic drugs targeting α-SYN aggregation for LBD.
Bridging the gap: Multi‐omics profiling of brain tissue in Alzheimer's disease and older controls in multi‐ethnic populations
Abstract INTRODUCTION Multi‐omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked Black Americans (BA) and Latin Americans (LA), who are disproportionately affected by AD. METHODS To bridge this gap, Accelerating Medicines Partnership in Alzheimer's Disease (AMP‐AD) expanded brain multi‐omics profiling to multi‐ethnic donors. RESULTS We generated multi‐omics data and curated and harmonized phenotypic data from BA ( n = 306), LA ( n = 326), or BA and LA ( n = 4) brain donors plus non‐Hispanic White ( n = 252) and other ( n = 20) ethnic groups, to establish a foundational dataset enriched for BA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSION The inclusion of traditionally underrepresented groups in multi‐omics studies is essential to discovering the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD. Highlights Accelerating Medicines Partnership in Alzheimer's Disease Diversity Initiative led brain tissue profiling in multi‐ethnic populations. Brain multi‐omics data is generated from Black American, Latin American, and non‐Hispanic White donors. RNA, whole genome sequencing and tandem mass tag proteomicsis completed and shared. Multiple brain regions including caudate, temporal and dorsolateral prefrontal cortex were profiled.
Chromogranin A Deficiency Attenuates Tauopathy by Altering Epinephrine–Alpha-Adrenergic Receptor Signaling
No container title available | August 9, 2024 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Metabolic disorders such as insulin resistance and hypertension are potential risk factors for aging and neurodegenerative diseases. These conditions are reversed in Chromogranin A knockout (CgA-KO) mice. This study investigates the role of CgA in Alzheimer’s disease (AD) and corticobasal degeneration (CBD). CgA ablation in tauopathy mice (hTau) (CgA-KO/hTau) exhibited reduced tau aggregation, spreading, extended lifespan, and improved cognitive function. Transcriptomic and metabolite analysis of mouse cortices revealed altered alpha1-adrenergic receptors (Adra1) and high epinephrine (EPI) levels in hTau mice compared to WT mice, mirroring observations in AD and CBD patients. CgA-KO/hTau mice exhibited a reversal of EPI levels in the cortex and the expression of Adra1, nearly returning them to WT levels. Treatment of hippocampal slices with EPI or Adra1 agonist intensified, while an Adra1 antagonist inhibited tau hyperphosphorylation and aggregation. These findings highlight the interplay between the EPI-Adra signaling system and CgA in tauopathy.
Clinicopathologic and Neuroimaging Correlations of Nonverbal Oral Apraxia in Patients With Neurodegenerative Disease
Neurology | July 30, 2024 | Volume: 103 | Issue: 4 | Pages: No page available