Biology subjects

Winkelmann, J.

Publications and source records attributed to Winkelmann, J..

6 recordsLinked to original sources

bioRxiv2025

Alpha-Synuclein co-pathology in Alzheimer's Disease drives tau accumulation

The molecular basis for accelerated cognitive decline seen in Alzheimers Disease (AD) cases presenting with cortical alpha-Synuclein (-Syn) co-pathology is not well understood. We show that such co-pathology brains express higher levels of microtubule-associated protein tau and that increasing -Syn expression is sufficient to drive tau accumulation. Our results reveal a hitherto unknown link between the pathogenesis of AD and Parkinsons Disease whereby tau and -Syn synergistically drive dementia-related pathology.

neuroscience↗

bioRxiv2024

Can we predict sleep health based on brain features? A large-scale machine learning study

BackgroundsSeveral correlational or group comparison evidence highlighted robust associations between sleep health and macro-scale brain organization. However, inter-individual variability is critical in such interplay. Therefore, in this study, we aimed to investigate the role of brain imaging features in predicting diverse sleep health-related characteristics at the individual subject level using the Machine Learning (ML) approach. MethodsA sample of 28,088 participants from the UK Biobank was employed to calculate 4677 structural and functional neuroimaging markers. Then, we employed them to predict self-reported insomnia symptoms, sleep duration, easiness of getting up in the morning, chronotype, daily nap, daytime sleepiness, and snoring. To assess the predictability of brain features, we built seven different linear and nonlinear ML models for each sleep health-related characteristic. ResultsWe performed extensive ML analyses that involved more than 19 years of compute time. We observed relatively low performance in predicting all sleep health-related characteristics from brain images (e.g., balanced accuracy ranging between 0.50-0.59). Across all models, the best performance achieved was 0.59, using a linear ML model to predict the ease of getting up in the morning. In fact, a similar performance was achieved with models trained solely on age and sex, indicating that these demographic factors might be the ones driving the predictions. ConclusionsThe low capability of multimodal neuroimaging markers in predicting sleep health-related characteristics, even under extensive ML optimization in a large population sample, suggests a complex relationship between sleep health and brain organization.

neuroscience↗

bioRxiv2023

Spatial enhancer activation determines inhibitory neuron identity

The mammalian telencephalon contains a tremendous diversity of GABAergic projection neuron and interneuron types, that originate in a germinal zone of the embryonic basal ganglia. How genetic information in this transient structure is transformed into different cell types is not yet fully understood. Using a combination of in vivo CRISPR perturbation, lineage tracing, and ChIP-seq in mice, we found that the transcription factor MEIS2 favors the development of projection neurons through genomic binding sites in regulatory enhancers of projection neuron specific genes. MEIS2 requires the presence of the homeodomain transcription factor DLX5 to direct its functional activity towards these sites. In interneuron precursors, the activation of projection neuron specific enhancers by MEIS2 and DLX5 is repressed by the transcription factor LHX6. When MEIS2 carries a mutation associated with intellectual disability in humans, it is less effective at activating enhancers involved in projection neuron development. This suggests that GABAergic differentiation may be impaired in patients carrying this mutation. Our research supports a model ("Differential Binding ) where the spatial specific composition of transcription factors at cis-regulatory elements determines differential gene expression and cell fate decisions in the ganglionic eminence.

developmental biology↗

bioRxiv2021

Intronic elements associated with insomnia and restless legs syndrome exhibit cell type-specific epigenetic features contributing to MEIS1 regulation

A highly evolutionarily conserved MEIS1 intronic region is strongly associated with restless legs syndrome (RLS) and insomnia. To understand its regulatory function, we dissected the region by analyzing chromatin accessibility, enhancer-promoter contacts, DNA methylation, and eQTLs in different human neural cell types and tissues. We observed specific activity with respect to cell type and developmental maturation, indicating a prominent role for distinct highly conserved intronic elements in forebrain inhibitory neuron differentiation. Two elements were hypomethylated in neural cells with higher MEIS1 expression, suggesting a role of enhancer demethylation in gene regulation. MEIS1 eQTLs showed a striking modular chromosomal distribution, with forebrain eQTLs clustering in intron 8/9. CRISPR interference targeting of individual elements in this region attenuated MEIS1 expression, revealing a complex regulatory interplay of distinct elements. In summary, we found that MEIS1 regulation is organized in a modular pattern. Disease-associated intronic regulatory elements control MEIS1 expression with cell type and maturation stage specificity, particularly in the inhibitory neuron lineage. The precise spatiotemporal activity of these elements likely contributes to the pathogenesis of insomnia and RLS.

genetics↗

bioRxiv2021

Collagen VI regulates motor circuit plasticity and motor performance by cannabinoid modulation

Collagen VI is a key component of muscle basement membranes, and genetic variants can cause monogenic muscular dystrophies. Conversely, human genetic studies recently implicated collagen VI in central nervous system function, with variants causing the movement disorder dystonia. To elucidate the neurophysiological role of collagen VI, we generated mice with a truncation of the dystonia-related collagen 3 (VI) (COL6A3) C-terminal domain (CTD). These Col6a3CTT mice showed a recessive dystonia-like phenotype. We found that COL6A3 interacts with the cannabinoid receptor 1 (CB1R) complex in a CTD-dependent manner. Col6a3CTT mice have impaired homeostasis of excitatory input to the basal pontine nuclei (BPN), a motor control hub with dense COL6A3 expression, consistent with deficient endocannabinoid signaling. Aberrant synaptic input in the BPN was normalized by a CB1R agonist, and motor performance in Col6a3CTT mice was improved by CB1R agonist treatment. Our findings identify a readily therapeutically addressable synaptic mechanism for motor control. SIGNIFICANCE STATEMENTDystonia is a movement disorder characterized by involuntary movements. We previously identified genetic variants affecting a specific domain of the COL6A3 protein as a cause of dystonia. Here, we we created mice lacking the affected domain and observed an analogous movement disorder. Using a protein interaction screen, we found that the affected COL6A3 domain mediates an interaction with the cannabinoid receptor CB1R. Concordantly, our COL6A3-deficient mice showed a deficit in synaptic plasticity linked to a deficit in cannabinoid signaling. Pharmacological cannabinoid augmentation rescued the motor impairment of the mice. Thus, cannabinoid augmentation could be a promising avenue for treating dystonia, and we have identified a possible molecular mechanism mediating this.

neuroscience↗

bioRxiv2018

Spectral Contrast Optical Coherence Tomography Angiography Enables Single-Scan Vessel Imaging

Optical coherence tomography angiography relies on motion for contrast and requires at least two data acquisitions per pointwise scanning location. We present a method termed spectral contrast optical coherence tomography angiography using visible light that relies on the spectral signatures of blood for angiography from a single scan using endogenous contrast. We demonstrate the molecular sensitivity of this method, which enables lymphatic vessel, blood, and tissue discrimination.

biophysics↗