Neurodegeneration & AI

Our group focuses on understanding the molecular mechanisms of neurodegenerative diseases through advanced computational and bioinformatics approaches, with the ultimate goal of developing early diagnostic tools and biomarkers for improved patient care.
In our research, we investigate protein biomarkers in body fluids as crucial indicators for neurodegenerative diseases. We address the challenges of detecting these biomarkers in complex biological environments, with particular emphasis on protein conformational changes and accessibility in body fluids. Our work examines the interactions between biomarkers and antibodies, whilst seeking to understand proteoforms to improve detection methods.
Through computational methods, we explore two key aspects of neurodegenerative diseases. First, we analyse protein abundance changes by examining proteomic profiles and multi-omics data to identify disease signatures. Second, we conduct protein structure analysis, investigating structural changes with a focus on amyloid fibril formation and characteristics, protein aggregation propensity, and temperature-dependent protein denaturation.
Our team develops and utilises bioinformatics tools and data resources to support biofluid protein biomarker assay development, analyse complex multi-omics datasets, and predict protein properties related to neurodegenerative diseases. This research contributes to earlier and more accurate diagnosis of neurodegenerative diseases and subtypes, potentially enabling intervention before symptom onset. Our work is crucial for advancing precision medicine approaches and improving patient outcomes in conditions such as Alzheimer's disease and other forms of dementia.
Researchers
J. (Jan) van Eck
PhD Candidateprof. dr. S. (Sanne) Abeln
ProfessorD. (Dea) Gogishvili
Researcher
Publications
Gogishvili, D., Minois-Genin, E., Van Eck, J., & Abeln, S. (2024). PatchProt: hydrophobic patch prediction using protein foundation models. Bioinformatics Advances, 4(1), Article vbae154. https://doi.org/10.1093/bioadv/vbae154
https://research-portal.uu.nl/ws/files/244660726/vbae154.pdf
Waury, K., Gogishvili, D., Nieuwland, R., Chatterjee, M., Teunissen, C. E., & Abeln, S. (2023). Proteome encoded determinants of protein sorting into extracellular vesicles. (pp. 1-22). bioRxiv. https://doi.org/10.1101/2023.02.01.526570
Gils, J. H. M. V., Gogishvili, D., Eck, J. V., Bouwmeester, R., Dijk, E. V., & Abeln, S. (2022). How sticky are our proteins? Quantifying hydrophobicity of the human proteome. Bioinformatics Advances, 2(1). https://doi.org/10.1093/bioadv/vbac002
https://dspace.library.uu.nl/bitstream/handle/1874/434517/vbac002.pdf?sequence=1
- Gils, J. H. M. V., Dijk, E. V., Peduzzo, A., Hofmann, A., Vettore, N., Schützmann, M. P., Groth, G., Mouhib, H., Otzen, D. E., Buell, A. K., & Abeln, S. (2020). The hydrophobic effect characterises the thermodynamic signature of amyloid fibril growth. PLoS Computational Biology, 16(5). https://doi.org/10.1371/journal.pcbi.1007767
https://dspace.library.uu.nl/bitstream/handle/1874/434519/The_hydrophobic_effect_characterises_the_thermodynamic_signature_of_amyloid_fibril_growth.pdf?sequence=1