Biology subjects

Knab, F.

Publications and source records attributed to Knab, F..

5 recordsLinked to original sources

bioRxiv2025

The Parkinsons disease associated Leucine-rich repeat kinase 2 affects expression of Transferrin receptor 1 and phosphorylation of key signaling proteins in human iPSC-derived dopaminergic neurons

Several variants in the Leucine-rich repeat kinase 2 (LRRK2) gene account for familiar and sporadic late-onset Parkinsons disease (PD). LRRK2 is a large, multifunctional kinase involved in different intracellular pathways crucial for homeostasis and cell survival. One of the poorly understood mechanisms of Parkinsonism is the iron accumulation in Substantia nigra pars compacta (SNc). Transferrin receptor 1 (TfR) plays a significant role for iron uptake into the cell. Here, we investigated the expression of TfR in human induced pluripotent stem cell (iPSC)-derived dopaminergic neurons (hDANs) generated from PD patients carrying the LRRK2 p.G2019S form and found dysregulated TfR levels. In addition, we found gene status depending variations of LRRK2 expression in differentiated hDANs, while neuronal progenitor cells (NPCs) did not display these changes. This suggests an unknown regulatory mechanism of LRRK2 expression during dopaminergic differentiation. Further investigations showed dysregulated phosphorylation of the PD-associated GSK-3{beta} und the key signaling factor Akt.

neuroscience↗

bioRxiv2025

Cellular and Extracellular microRNA Dysregulation in LRRK2-Linked Parkinson's Disease

Background and objectiveThe discovery of cell-free micro-RNAs in body fluids has made them a promising biomarker target in the field of neurodegenerative diseases. Although they have been reported to be differentially expressed in biofluids and tissues from sporadic Parkinsons disease patients, it remains unclear whether similar observations can be made in patients with genetic forms of the disease and if miRNA profiles reflect mutation-specific pathogenic pathways. Since induced pluripotent stem cell-derived neurons represent a widely used research model for both sporadic and familial Parkinsons disease, we sought to assess the usability of this model for the identification of differentially expressed cell-free micro-RNAs in the context of the Parkinsons disease-related LRRK2 G2019S mutation in a proof-of-concept study. Materials and methodsWe isolated extracellular vesicles carrying cell-free RNA from patient-derived induced pluripotent stem cells carrying the LRRK2 G2019S mutation and their gene-corrected isogenic controls. After the generation of small-RNA libraries and differential expression analysis, we quantified expression levels of fourteen micro-RNAs in an independent batch of cell-free and cellular RNA via RT-qPCR. Finally, we quantified pRab10 levels as a proxy of LRRK2 activity and correlated observable changes to the miRNA expression levels. ResultsWe successfully isolated extracellular vesicles from induced pluripotent stem cell-derived human dopaminergic neurons. We detected over 2000 different micro-RNAs of which 56 were differentially expressed. Dysregulation of four micro-RNAs was confirmed in an independent batch of cell-free RNA. We discovered a high correlation between changes in the cell-free and cellular micro-RNAomes. Finally, we showed poor correlation between LRRK2 expression or activity and miRNA expression levels. ConclusionsOur results suggest that patients carrying the LRRK2 G2019S mutation display alterations in cellular and cell-free micro-RNA expression levels. Notably, the miRNA changes observed in this study did not follow a linear relationship with LRRK2 expression levels or kinase activity. Validation in larger cohorts will be necessary.

neuroscience↗

bioRxiv2024

The Cellular and Extra-Cellular Proteomic Signature of Human Dopaminergic Neurons Carrying the LRRK2 G2019S Mutation

Extracellular vesicles are easily accessible in various biofluids and allow the assessment of disease-related changes of the proteome. This has made them a promising target for biomarker studies, especially in the field of neurodegeneration where access to diseased tissue is very limited. Genetic variants in the LRRK2 gene have been linked to both familial and sporadic forms of Parkinsons disease. With LRRK2 inhibitors entering clinical trials, there is an unmet need for biomarkers that reflect LRRK2-specific pathology and target engagement. In this study, we used induced pluripotent stem cells derived from a patient with Parkinsons disease carrying the LRRK2 G2019S mutation and an isogenic gene corrected control to generate human dopaminergic neurons. We isolated extracellular vesicles and neuronal cell lysates and characterized their proteomic signature using data-independent acquisition proteomics. We performed differential expression analysis and identified 595 significantly differentially regulated proteins in extracellular vesicles and 3205 in cell lysates. Next, we performed gene ontology enrichment analyses on the dysregulated proteins and found close association to biological processes relevant in neurodegeneration and Parkinsons disease. Finally, we focused on proteins that were dysregulated in both the extracellular and cellular proteomes and provide a list of ten promising biomarker candidates that are functionally relevant in neurodegeneration and linked to LRRK2 associated pathology. Among those was the sonic hedgehog signaling molecule, a protein that has tightly been linked to LRRK2-related disruption of cilia function. In conclusion, we characterized the cellular and extracellular proteome of dopaminergic neurons carrying the LRRK2 G2019S mutation and propose an experimentally based list of promising biomarker candidates for future studies.

neuroscience↗

bioRxiv2023

Using Extracellular miRNA Signatures to Identify Patients with LRRK2-Related Parkinson's Disease

BackgroundMutations in the Leucine Rich Repeat Kinase 2 gene are highly relevant in both sporadic and familial cases of Parkinsons disease. Specific therapies are entering clinical trials but patient stratification remains challenging. Dysregulated microRNA expression levels have been proposed as biomarker candidates in sporadic Parkinsons disease. ObjectiveIn this proof-of concept study we evaluate the potential of extracellular miRNA signatures to identify LRRK2-driven molecular patterns in Parkinsons disease. MethodsWe measured expression levels of 91 miRNAs via RT-qPCR in ten individuals with sporadic Parkinsons disease, ten LRRK2 mutation carriers and eleven healthy controls using both plasma and cerebrospinal fluid. We compared miRNA signatures using heatmaps and t-tests. Next, we applied group sorting algorithms and tested sensitivity and specificity of their group predictions. ResultsmiR-29c-3p was differentially expressed between LRRK2 mutation carriers and sporadic cases, with miR-425-5p trending towards significance. Individuals clustered in principal component analysis along mutation status. Group affiliation was predicted with high accuracy in the prediction models (sensitivity up to 89%, specificity up to 70%). miRs-128-3p, 29c-3p, 223-3p and 424-5p were identified as promising discriminators among all analyses. ConclusionsLRRK2 mutation status impacts the extracellular miRNA signature measured in plasma and separates mutation carriers from sporadic Parkinsons disease patients. Monitoring LRRK2 miRNA signatures could be an interesting approach to test drug efficacy of LRRK2-targeting therapies. In light of small sample size, the suggested approach needs to be validated in larger cohorts.

neuroscience↗

bioRxiv2022

Prediction of Stroke Outcome in Mice Based on Non-Invasive MRI and Behavioral Testing

BackgroundPrediction of post-stroke outcome using the degree of subacute deficit or magnetic resonance imaging is well studied in humans. While mice are frequently used animals in preclinical stroke research, systematic analysis of outcome predictors is lacking. MethodsWe introduced heterogeneity into our study to broaden the applicability of our prediction tools. We analyzed the effect of 30, 45 and 60 minutes of arterial occlusion on the variance of stroke volumes. Next, we built a heterogeneous cohort of 215 mice using data from 15 studies that included 45 minutes of middle cerebral artery occlusion and various genotypes. Motor function was measured using the staircase test of skilled reaching. Phases of subacute and residual deficit were defined. Magnetic resonance images of stroke lesions were co-registered on the Allen Mouse Brain Atlas to characterize stroke topology. Different random forest prediction models that either used motor-functional deficit or imaging parameters were generated for the subacute and residual deficits. ResultsVariance of stroke volumes was increased by 45 minutes of arterial occlusion compared to 60 minutes and including various genotypes. We detected both a subacute and residual motor-functional deficit after stroke and different recovery trajectories. In mice with small cortical lesions, lesion volume was the best predictor of the subacute deficit. The residual deficit was most accurately predicted by the degree of the subacute deficit. When using imaging parameters for the prediction of the residual deficit, including information about the lesion topology increased prediction accuracy. A subset of anatomical regions within the ischemic lesion had particular impact on the prediction of long-term outcome. ConclusionsWe developed and validated a robust tool for the prediction of functional outcome after stroke in mice using a large heterogeneous cohort. Study design and imaging limitations are discussed. In the future, using outcome prediction can improve the design of preclinical studies and guide intervention decisions.

neuroscience↗