Biology subjects

Wolking, S.

Publications and source records attributed to Wolking, S..

4 recordsLinked to original sources

bioRxiv2025

Predicting Drug Response with Multi-Task Gradient-Boosted Trees in Epilepsy

MotivationDespite the availability of numerous anti-seizure medications (ASMs), drug resistance remains a major issue for people with epilepsy. The probability of achieving seizure freedom diminishes with each unsuccessful drug trial, and the impact of genetic and clinical markers on ASM response remains unclear. To address this issue, we used state-of-the-art machine learning (ML) methods to predict the response of people with epilepsy to individual ASMs based on their clinical and genomic information. ResultsTo overcome data sparsity for less common drugs, we implement a multi-task (MT) learning approach for gradient-boosted trees (GBTs), assuming that predicting responses to different ASMs involves similar tasks. This strategy allows models for less prevalent drugs to leverage the more abundant data available for other drugs during training. The proposed model outperforms individual and combined drug-response predictions for most drugs. Our findings identify key genomic and clinical features influencing drug response, enhancing understanding of individual drug responses in people with epilepsy, and aiding clinicians in making informed treatment decisions. Availability and ImplementationDue to privacy reasons data is not publically available. The code will be made available upon acceptance under https://github.com/pfeiferAI/MT-GBT

bioinformatics↗

bioRxiv2025

Modeling AP2M1 Developmental and Epileptic Encephalopathy in Drosophila

Genetic defects in AP2M1, which encodes the -subunit of the adaptor protein complex 2 (AP-2) essential for clathrin-mediated endocytosis (CME), cause a rare form of developmental and epileptic encephalopathy (DEE). In this study, we modeled AP2M1-DEE in Drosophila melanogaster to gain deeper insights into the underlying disease mechanisms. Pan-neuronal knock-down of the Drosophila AP2M1 ortholog, AP-2{micro}, resulted in a consistent heat-sensitive paralysis phenotype and altered morphology in class IV dendritic arborization (c4da) neurons. Unexpectedly, affected flies were resistant to antiseizure medications and exhibited increased resistance to electrically induced seizures. A CRISPR-engineered fly line carrying the recurrent human disease variant p.Arg170Trp displayed a milder seizure resistance phenotype. While these findings contrast with the human phenotype, they align with previous studies on other CME-related genes in Drosophila. Our results suggest that hyperexcitability and seizures in AP2M1-DEE may stem from broader defects in neuronal development rather than direct synaptic dysfunction.

neuroscience↗

bioRxiv2024

Comprehensive Analysis of Human Dendritic Spine Morphology and Density: Exploring Diversity of Human Dendritic Spines

Dendritic spines, small protrusions on neuronal dendrites, play a crucial role in brain function by changing shape and size in response to neural activity. So far, in depth analysis of dendritic spines in human brain tissue is lacking. This study presents a comprehensive analysis of human dendritic spine morphology and density using a unique dataset from human brain tissue from 27 patients (8 females, 19 males, aged 18-71) undergoing tumor or epilepsy surgery at three neurosurgery sites. We used acute slices and organotypic brain slice cultures to examine dendritic spines, classifying them into the three main morphological subtypes: Mushroom, Thin, and Stubby, via 3D reconstruction using ZEISS arivis Pro software. A deep learning model, trained on 39 diverse datasets, automated spine segmentation and 3D reconstruction, achieving a 74% F1-score and reducing processing time by over 50%. We show significant differences in spine density by sex, dendrite type, and tissue condition. Females had higher spine densities than males, and apical dendrites were denser in spines than basal ones. Acute tissue showed higher spine densities compared to cultured human brain tissue. With time in culture, Mushroom spines decreased, while Stubby and Thin spine percentages increased, particularly from 7-9 to 14 days in vitro, reflecting potential synaptic plasticity changes. Our study underscores the importance of using human brain tissue to understand unique synaptic properties and shows that integrating deep learning with traditional methods enables efficient large-scale analysis, revealing key insights into sex- and tissue-specific dendritic spine dynamics relevant to neurological diseases. New and NoteworthyThis study presents a dataset of nearly 4,000 morphologically reconstructed human dendritic spines across different ages, gender, and tissue conditions. The dataset was further used to evaluate a deep learning algorithm for three-dimensional spine reconstruction, offering a scalable method for semi-automated spine analysis across various tissues and microscopy setups. The findings enhance understanding of human neurology, indicating potential connections between spine morphology, brain function, and the mechanisms of neurological and psychiatric diseases.

neuroscience↗

bioRxiv2019

Polygenic risk scores of several subtypes of epilepsies in a founder population

ImportanceEpilepsy is defined as a group of neurological disorders characterized by epileptic seizures, brief episodes of symptoms that are caused by abnormal or excessive neuronal activity in the brain. Epilepsy affects around 3 percent of individuals. In the past 10 years, many groups have been working to better understand the complex genetic mechanisms underlying epilepsy. Together, they studied many different genetic mechanisms, but there is still a substantial missing heritability component in epilepsy genetics.\n\nObjectiveHere, we used polygenic risk scores (PRS) to quantify the cumulative effects of a number of variants, which may individually have a very small effect on susceptibility.\n\nDesignWe calculated PRS in 522 French-Canadian epilepsy patients divided into seven subtypes and French-Canadian controls.\n\nSettingAll study participants (cases and controls) were selected based on their French-Canadian ancestry.\n\nParticipantsThe epilepsy cohort was composed of families of at least three affected individuals with Idiopathic Generalized Epilepsy (IGE) or Non-acquired Focal Epilepsy (NAFE) previously collected and diagnosed by neurologists following the International League Against Epilepsy (ILAE) criteria.\n\nExposuresAll samples were processed on a common genotyping array.\n\nMain outcomes and ResultsWe show that the area under the curve (AUC) is almost always slightly greater than 0.5, especially in patients with IGE and subtypes. We also looked at the association of the PRS with the different phenotypes using a linear mixed effects model estimated by generalized estimating equation (GEE) with the pairwise identity-by-descent (IBD) matrix as a random effect. P-values of GEE were consistent with AUC calculations.\n\nConclusions and RelevanceGlobally, we support the notion that PRS and SNP-based heritability provide reliable measures to rightfully estimate the contribution of genetic factors to the pathophysiological mechanism of epilepsies, but further studies are needed on PRS before they can be used clinically.

genetics↗