Biology subjects

Scholl, M.

Publications and source records attributed to Scholl, M..

3 recordsLinked to original sources

bioRxiv2024

Chemical imaging signatures delineate heterogeneous amyloid plaque populations across the Alzheimers disease spectrum

Amyloid plaque deposition is recognized as the primary pathological hallmark of Alzheimers disease(AD) that precedes other pathological events and cognitive symptoms. Plaque pathology represents itself with an immense polymorphic variety comprising plaques with different stages of amyloid fibrillization ranging from diffuse to fibrillar, mature plaques. The association of polymorphic A{beta} plaque pathology with AD pathogenesis, clinical symptoms and disease progression remains unclear. Advanced chemical imaging tools, such as functional amyloid microscopy combined with MALDI mass spectrometry imaging (MSI), are now enhanced by deep learning algorithms. This integration allows for precise delineation of polymorphic plaque structures and detailed identification of their associated A{beta} compositions. We here set out to make use of these tools to interrogate heterogenic plaque types and their associated biochemical architecture. Our findings reveal distinct A{beta} signatures that differentiate diffuse plaques from fibrilized ones, with the latter showing substantially higher levels of A{beta}x-40. Notably, within the fibrilized category, we identified a distinct subtype known as coarse-grain plaques. Both in sAD and fAD brain tissue, coarse grain plaques contained more A{beta}x-40 and less A{beta}x-42 compared with cored plaques. The coarse grain plaques in both sAD and fAD also showed higher levels of neuritic content including paired helical filaments (PHF-1)/phosphorylated phospho Tau-immunopositive neurites. Finally, the A{beta} peptide content in coarse grain plaques resembled that of vascular A{beta} deposits (CAA) though with relatively higher levels of A{beta}1-42 and pyroglutamated A{beta}x-40 and A{beta}x-42 species in coarse grain plaques. This is the first of its kind study on spatial in situ biochemical characterization of different plaque morphotypes demonstrating the potential of the correlative imaging techniques used that further increase the understanding of heterogeneous AD pathology. Linking the biochemical characteristics of amyloid plaque polymorphisms with various AD etiologies and toxicity mechanisms is crucial. Understanding the connection between plaque structure and disease pathogenesis can enhance our insights. This knowledge is particularly valuable for developing and advancing novel, amyloid-targeting therapeutics.

neuroscience↗

bioRxiv2020

Bispecific tau antibodies with additional binding to C1q or alpha-synuclein

BackgroundAlzheimers disease (AD) and other tauopathies are neurodegenerative disorders characterized by cellular accumulation of aggregated tau protein. Tau pathology within these disorders is accompanied by chronic neuroinflammation, such as activation of the classical complement pathway by complement initiation factor C1q. Additionally, about half of the AD cases present with inclusions composed of aggregated alpha-synuclein called Lewy bodies. Lewy bodies in disorders such as Parkinsons disease and Lewy body dementia also frequently occur together with tau pathology. Immunotherapy is currently the most promising treatment strategy for tauopathies. However, the presence of multiple pathological processes within tauopathies makes it desirable to simultaneously target more than one disease pathway. MethodsHerein, we have developed three bispecific antibodies based on published antibody binding region sequences. One bispecific antibody binds to tau plus alpha-synuclein and two bispecific antibodies bind to tau plus C1q. ResultsThe affinity of the bispecific antibodies to their targets compared to their monospecific counterparts ranged from nearly identical to one order of magnitude lower. All bispecific antibodies retained binding to aggregated protein in patient-derived brain sections. The bispecific antibodies also retained their ability to inhibit aggregation of recombinant tau, regardless of whether the tau binding sites were in IgG or scFv format. Mono- and bispecific antibodies inhibited cellular seeding induced by AD-derived pathological tau with similar efficacy. Finally, both Tau-C1q bispecific antibodies completely inhibited the classical complement pathway. ConclusionBispecific antibodies that bind to multiple pathological targets may therefore present a promising approach to treat tauopathies and other neurodegenerative disorders.

neuroscience↗

bioRxiv2018

Data-driven approaches improve Tau-PET biomarkers in Alzheimer’s disease

Previous positron emission tomography (PET) studies have quantified filamentous tau pathology using regions-of-interest (ROIs) based on observations of the topographical distribution of neurofibrillary tangles in post-mortem tissue. However, such approaches may not take full advantage of information contained in neuroimaging data. The present study employs an unsupervised data-driven method to identify spatial patterns of tau-PET distribution, and to compare these patterns to previously published \"pathology-driven\" ROIs. Tau-PET patterns were identified from a discovery sample comprised of 123 normal controls and patients with mild cognitive impairment or Alzheimers disease (AD) dementia from the Swedish BioFINDER cohort, who underwent [18F]AV1451 PET scanning. Associations with cognition were tested in a separate sample of 90 individuals from ADNI. BioFINDER [18F]AV1451 images were entered into a robust voxelwise stable clustering algorithm, which resulted in five clusters. Mean [18F]AV1451 uptake in the data-driven clusters, and in 35 previously published pathology-driven ROIs, was extracted from ADNI [18F]AV1451 scans. We performed linear models comparing [18F]AV1451 signal across all 40 ROIs to several tests of global cognition, adjusting for age, sex and education. Two data-driven ROIs consistently demonstrated the strongest or near-strongest effect sizes across all cognitive tests. Inputting all regions plus demographics into a feature selection routine resulted in selection of two ROIs (one data-driven, one pathology-driven) and education, which together explained 28% of the variance of a global cognitive composite score. Our findings suggest that [18F]AV1451-PET data naturally clusters into spatial patterns that are biologically meaningful and that may offer advantages as clinical tools.

neuroscience↗