Biology subjects

van Swieten, J.

Publications and source records attributed to van Swieten, J..

5 recordsLinked to original sources

bioRxiv2024

Allosteric modulation of protein kinase A in individuals affected by NLPD-PKA , a neurodegenerative disease in which the RIβ-L50R variant is expressed

Protein kinase A (PKA) is a crucial signaling enzyme in neurons, with its dysregulation being implicated in neurodegenerative diseases. Assembly of the PKA holoenzyme, comprising a dimer of heterodimers of regulatory (R) and catalytic (C) subunits, ensures allosteric regulation and functional specificity. Recently, we defined the RI{beta}-L50R variant as a causative mutation that triggers protein aggregation in a rare neurodegenerative disease. However, the mechanism underlying uncontrolled PKA allosteric regulation and its connection to the functional outcomes leading to clinical symptoms remain elusive. In this study, we established an in vitro model using patient-derived cells for a personalized approach and employed direct measurements of purified proteins to investigate disease mechanisms in a controlled environment. Structural analysis and circular dichroism spectroscopy revealed that cellular proteins aggregation resulted from misfolded RI{beta}-subunits, preventing holoenzyme assembly and anchoring through A Kinase Anchoring Proteins (AKAPs). While maintaining high affinity to the C subunit, the resulting RI{beta}-L50R:C heterodimer exhibits reduced cooperativity, requiring lower cAMP concentrations for dissociation. Consequently, there was an increased translocation of C-subunit into the nucleus, impacting gene expression. We successfully controlled C subunit translocation by introducing a mutation that decreased RI{beta}:C dissociation in response to elevated cAMP levels. This research thus sets the stage for developing therapeutic strategies that modulate PKA assembly and allostery, thus exerting control over the unique molecular signatures identified in the disease-associated transcriptome profile.

cell biology↗

bioRxiv2024

Neuronal downregulation of PLCG2 impairs synaptic function and elicits Alzheimer disease hallmarks

We developed a high content screening to investigate how Alzheimer disease (AD) genetic risk factors may affect synaptic mechanisms in rat primary neuronal cultures. Out of the target genes identified, we found that Plcg2 downregulation in mouse dentate gyrus neurons consistently disrupted dendritic morphology and synaptic function. In human neuronal cultures (hNCs), PLCG2 downregulation also impaired synaptic function and increased A{beta} levels and Tau phosphorylation. Very rare PLCG2 loss-of-function (LoF) variants were associated with a 10-fold increased AD risk. PLCG2 LoF carriers exhibit low mRNA/protein PLCG2/PLC{gamma}2 levels and the R953* LoF mutation compromised synaptic function and increased AD hallmarks in hNCs. Single nuclei RNAseq analyses confirmed that the downregulation of PLCG2 impacted pathways related to synaptic and neuronal functions, potentially through neurexin in neurons. In conclusion, PLC{gamma}2 downregulation could increase AD risk by impairing synaptic functions and increasing the A{beta} levels and Tau phosphorylation in neurons.

neuroscience↗

bioRxiv2021

Age-dependent formation of TMEM106B amyloid filaments in human brain

Many age-dependent neurodegenerative diseases, like Alzheimers and Parkinsons, are characterised by abundant inclusions of amyloid filaments. Filamentous inclusions of the proteins tau, amyloid-{beta} (A{beta}), -synuclein and TDP-43 are the most common. Here, we used electron cryo-microscopy (cryo-EM) structure determination to show that residues 120-254 of the lysosomal type II transmembrane protein 106B (TMEM106B) also form amyloid filaments in the human brain. We solved cryo-EM structures of TMEM106B filaments from the brains of 22 individuals with neurodegenerative conditions, including sporadic and inherited tauopathies, A{beta}-amyloidoses, synucleinopathies and TDP-43opathies, as well as from the brains of two neurologically normal individuals. We observed three different TMEM106B folds, with no clear relationship between folds and diseases. The presence of TMEM106B filaments correlated with that of a 29 kDa sarkosyl-insoluble fragment of the protein on Western blots. The presence of TMEM106B filaments in the brains of older, but not younger, neurologically normal individuals indicates that they form in an age-dependent manner.

neuroscience↗

bioRxiv2019

Data-driven algorithm for the diagnosis of behavioral variant frontotemporal dementia

INTRODUCTIONBrain structural imaging is paramount for the diagnosis of behavioral variant of frontotemporal dementia (bvFTD), but it has low sensitivity leading to erroneous or late diagnosis. METHODSA total of 515 subjects from two different bvFTD databases (training and validation cohorts) were included to perform voxel-wise deformation-based morphometry analysis to identify regions with significant differences between bvFTD and controls. A random forest classifier was used to individually predict bvFTD from morphometric differences in isolation and together with bedside cognitive scores. RESULTSAverage ten-fold cross-validation accuracy was 89% (82% sensitivity, 93% specificity) using only MRI and 94% (89% sensitivity, 98% specificity) with the addition of semantic fluency. In a separate validation cohort of genetically confirmed bvFTD, accuracy was 88% (81% sensitivity, 92% specificity) with MRI and 91% (79% sensitivity, 96% specificity) with added cognitive scores. DISCUSSIONThe random forest classifier developed can accurately predict bvFTD at the individual subject level.

neuroscience↗

bioRxiv2017

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we present a new machine learning technique - Subtype and Stage Inference (SuStaIn) - able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available crosssectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal new subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes, and characterises within-group heterogeneity for the first time. In Alzheimers disease, SuStaIn uncovers three subtypes, uniquely revealing their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p=7.18x10--4) or temporal stage (p=3.96x10-5). SuStaIn thus offers new promise for enabling disease subtype discovery and precision medicine.

neuroscience↗