Biology subjects

Weintraub, D.

Publications and source records attributed to Weintraub, D..

5 recordsLinked to original sources

bioRxiv2026

Microglial reactivity in the hippocampal CA2 is associated with advanced neuronal α-synulceinopathy

Lewy body diseases are thought to evolve by the spread of intraneuronal -synuclein pathology. However, staging models of -synuclein pathology in the human brain seldom evaluate regions with direct synaptic connectivity to model microglial processes in disease. Here, we address this gap by testing the hypothesis that, within the well-defined synaptic connectivity of the intrahippocampal circuit, neuronal -synuclein pathology is associated with microglial reactivity. We selected a cohort of autopsy-confirmed Lewy body disease patients with hippocampal neuronal -synuclein pathology and minimal age-related co-pathologies (n=62) and as a control for other intraneuronal hippocampal pathology, we used a cohort of cognitively healthy patients with focal hippocampal tau accumulation with minimal amyloid plaques, termed primary age-related tauopathy (n=12). We immunostained consecutive hippocampal sections for -synuclein pathology and established markers of microglial reactivity, Iba1, HLA-DR, and CD68. With validated digital histology methods, we measured percent area occupied in 6 hippocampal subfields to compare the percent area occupied within subfields between patient cohorts, correlate the percent area occupied within and between subfields, and use linear-mixed effects models to compare the percent area occupied across subfields while co-varying for demographics. We also constructed two groups of either low-level hippocampal -synuclein pathology restricted to the cornu ammonis 2-3 subfields (Focal Subtype) or widespread -synuclein pathology within additional subfields (Widespread Subtype) to model hypothesized -synuclein pathological spread within the intrahippocampal circuit. Lewy body disease patients exhibited increased HLA-DR and CD68 in most hippocampal subfields compared with primary age-related tauopathy. In Lewy body disease patients, staining for all microglial markers was highest in the cornu ammonis field 2. Neuronal -synuclein pathology in the cornu ammonis field 2 consistently correlated with only HLA-DR and CD68 but not Iba1. Patients classified as the Widespread Subtype had worse cognitive impairment and increased HLA-DR and CD68 within the cornu ammonis field 2. Furthermore, HLA-DR and CD68 in the cornu ammonis field 2 correlated with distal neuronal -synuclein pathology only in subfields with retrograde connectivity. We found increased hippocampal microglial abnormalities in Lewy body disease patients compared with cognitively normal controls with primary age-related tauopathy, suggesting a relatively specific microglial/inflammatory response to neuronal -synuclein pathology. Our data is consistent with predominantly retrograde transmission of neuronal -synuclein pathology across hippocampal subfields, where the focal microglial response in the cornu ammonis field 2 may influence clinical outcomes and -synuclein pathological spread. These data suggest that microglial processes can help refine Lewy body disease histopathological staging.

neuroscience↗

bioRxiv2024

α-Synuclein Conformations in Plasma Distinguish Parkinson's Disease from Dementia with Lewy Bodies

AbstractSpread and aggregation of misfolded -synuclein (aSyn) within the brain is the pathologic hallmark of Lewy body diseases (LBD), including Parkinsons disease (PD) and dementia with Lewy bodies (DLB). While evidence exists for multiple aSyn protein conformations, often termed "strains" for their distinct biological properties, it is unclear whether PD and DLB result from aSyn strain differences, and biomarkers that differentiate PD and DLB are lacking. Moreover, while pathological forms of aSyn have been detected outside the brain (e.g., in skin, gut, blood), the functional significance of these peripheral aSyn species is unclear. Here, we developed assays using monoclonal antibodies selective for two different aSyn species generated in vitro - termed Strain A and Strain B - and used them to evaluate human brain tissue, cerebrospinal fluid (CSF), and plasma, through immunohistochemistry, enzyme-linked immunoassay, and immunoblotting. Surprisingly, we found that plasma aSyn species detected by these antibodies differentiated individuals with PD vs. DLB in a discovery cohort (UPenn, n=235, AUC 0.83) and a multi-site replication cohort (Parkinsons Disease Biomarker Program, or PDBP, n=200, AUC 0.72). aSyn plasma species detected by the Strain A antibody also predicted rate of cognitive decline in PD. We found no evidence for aSyn strains in CSF, and ability to template aSyn fibrillization differed for species isolated from plasma vs. brain, and in PD vs. DLB. Taken together, our findings suggest that aSyn conformational differences may impact clinical presentation and cortical spread of pathological aSyn. Moreover, the enrichment of these aSyn strains in plasma implicates a non-central nervous system source.

neuroscience↗

bioRxiv2021

3D Convolutional Neural Networks for Classification of Alzheimer's and Parkinson's Disease with T1-Weighted Brain MRI

Parkinsons disease (PD) and Alzheimers disease (AD) are progressive neurodegenerative disorders that affect millions of people worldwide. In this work, we propose a deep learning approach to classify these diseases based on 3D T1-weighted brain MRI. We analyzed several datasets including the Parkinsons Progression Markers Initiative (PPMI), an independent dataset from the University of Pennsylvania School of Medicine (UPenn), the Alzheimers Disease Neuroimaging Initiative (ADNI), and the Open Access Series of Imaging Studies (OASIS) dataset. The UPenn and OASIS datasets were used as independent test sets to evaluate the model performance during inference. We also implemented a random forest classifier as a baseline model by extracting key radiomics features from the same T1-weighted MRI scans. The proposed 3D convolutional neural network (CNN) model was trained from scratch for the classification tasks. For AD classification, the 3D CNN model achieved an ROC-AUC of 0.878 on the ADNI test set and an average ROC-AUC of 0.789 on the OASIS dataset. For PD classification, the proposed 3D CNN model achieved an ROC-AUC of 0.667 on the PPMI test set and an average ROC-AUC of 0.743 on the UPenn dataset. Model performance was largely maintained when using only 25% of the training dataset. The 3D CNN outperformed the random forest classifier for both the PD and AD tasks. The 3D CNN also generalized better on unseen MRI data from different imaging centers. These approaches show promise for screening of PD and AD patients using only T1-weighted brain MRI, which is relatively widely available. This model with additional validation could also be used to help differentiate between challenging cases of AD and PD when they present with similarly subtle motor and non-motor symptoms.

bioinformatics↗

bioRxiv2019

Cross-Sectional and Longitudinal Validation of Serum Neurofilament Light Chain (NfL) as a Biomarker of Parkinson’s Disease Progression

ObjectiveTo assess neurofilament light chain (NfL), as a biomarker for Parkinsons disease (PD). MethodsWe quantified NfL in (1) longitudinal CSF samples from PD, other cognate/neurodegenerative disorders (OND), and healthy controls (HC); (2) a cross-sectional cohort with paired CSF and serum samples from participants with PD, OND, and HC, and (3) a large longitudinal validation cohort with serum samples from PD, OND, HC, prodromal conditions, and mutation carriers. ResultsIn the longitudinal discovery cohort (1) NfL in CSF was highest in OND and higher in PD vs. HC across all visits (p<0.05) but did not change longitudinally. In the cross-sectional cohort (2) paired CSF and serum NfL samples were highly correlated (Spearmans rank [Formula]; p<10^-6). In the large validation cohort (3) mean baseline serum NfL was higher in PD (13{+/-}7.2pg/ml) vs. HC (12{+/-}6.7pg/ml; p=0.0336) and was highest in OND (18{+/-}7pg/ml; p=0.0351). Serum NfL increased longitudinally in PD vs. HC (p<0.01). Longitudinal motor scores were positively longitudinally associated with NfL, whereas some cognitive scores showed a negative longitudinal association with NfL. ConclusionsNfL levels in serum samples are increased in PD vs. HC, increase significantly over time, and correlate with clinical measures of PD severity. Although the specificity of NfL in PD is low and more specific biomarkers are needed, serum NfL is the first blood-based biomarker candidate that could support disease stratification (PD vs. OND), track clinical progression, and possibly assess responsiveness to neuroprotective treatments. NfL as a biomarker of response to neuroprotective interventions remains to be determined. Funding sources for studyPPMI is sponsored by the Michael J. Fox Foundation for Parkinsons Research (MJFF) and is co-funded by MJFF, Abbvie, Avid Radiopharmaceuticals, Biogen Idec, Bristol-Myers Squibb, Covance, Eli Lilly & Co., F. Hoffman-La Roche, Ltd., GE Healthcare, Genentech, GlaxoSmithKline, Lundbeck, Merck, MesoScale, Piramal, Pfizer and UCB. The funders had no role in the design and conduct of the study, in the collection, management, analysis, and interpretation of the data, in the preparation, review, or approval of the manuscript or in the decision to submit the manuscript for publication. Financial Disclosure/Conflict of Interest concerning the research related to the manuscriptBrit Mollenhauer, Douglas Galasko, Tatiana Foroud, Lana M. Chahine, Christopher S. Coffey, Andrew B. Singleton, Tanya Simuni, Daniel Weintraub, John Seibyl, Arthur W. Toga, and Caroline M. Tanner received funding from The Michael J. Fox Foundation for Parkinsons Research. Mohammed Dakna, Tzu-Ying Liu, Henrik Zetterberg, Sebastian Schade, Roland G. Gera, Wenting Wang, Feng Gao, Niels Kruse, Mark Frasier, Jesse M. Cedarbaum, Samantha J. Hutten, Claudia Trenkwalder, and Danielle Graham report no disclosures.

neuroscience↗

bioRxiv2019

Genome-wide association study of Parkinson's disease progression biomarkers in 12 longitudinal patients' cohorts

BackgroundSeveral reports have identified different patterns of Parkinsons disease progression in individuals carrying missense variants in the GBA or LRRK2 genes. The overall contribution of genetic factors to the severity and progression of Parkinsons disease, however, has not been well studied. ObjectivesTo test the association between genetic variants and the clinical features and progression of Parkinsons disease on a genome-wide scale. MethodsWe accumulated individual data from 12 longitudinal cohorts in a total of 4,093 patients with 25,254 observations over a median of 3.81 years. Genome-wide associations were evaluated for 25 cross-sectional and longitudinal phenotypes. Specific variants of interest, including 90 recently-identified disease risk variants, were also investigated for the associations with these phenotypes. ResultsTwo variants were genome-wide significant. Rs382940(T>A), within the intron of SLC44A1, was associated with reaching Hoehn and Yahr stage 3 or higher faster (HR 2.04 [1.58, 2.62], P-value = 3.46E-8). Rs61863020(G>A), an intergenic variant and eQTL for ADRA2A, was associated with a lower prevalence of insomnia at baseline (OR 0.63 [0,52, 0.75], P-value = 4.74E-8). In the targeted analysis, we found nine associations between known Parkinsons risk variants and more severe motor/cognitive symptoms. Also, we replicated previous reports of GBA coding variants (rs2230288: p.E365K, rs75548401: p.T408M) being associated with greater motor and cognitive decline over time, and APOE E4 tagging variant (rs429358) being associated with greater cognitive deficits in patients. ConclusionsWe identified novel genetic factors associated with heterogeneity of progression in Parkinsons disease. The results provide new insights into the pathogenesis of Parkinsons disease as well as patient stratification for clinical trials.

genetics↗