Anselm-Franz-von-Bentzel-Weg 3, 55128 Mainz
The Big Picture of Neurodegeneration
Neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases (NDDs) for many years, thus we gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on these three omics-layers. Our meta-study reveals highly significant processes in the identified set of 139 genes, common to all analyzed NDDs and might therefore contribute to the development of pharmaceutical measures against neurodegeneration in general.
These results marked the starting point of further research, again conducted in a team-effort with Susanne Klingenberg, to now find hallmarks emerging across four omics-layers in these four neurodegenerative diseases. We updated our genomic database and expanded our analysis to methylomic data. As we did not focus on the overlap common to all four diseases but to all significantly emerging genes we chose a network-based community detection approach to grasp the underlying subprocesses and hallmarks of neurodegeneration.
However, in addition to studying neurodegenerative diseases in a broad sense using publicly available datasets, I am also joining the analysis of experimental work on Alzheimer’s Diseases and multiple sclerosis, e.g. in RG Stroh. In addition to ongoing research, one paper on the detection of altered network dynamics in AD mouse models and its restoration using the drug Acitretin has been published here.
As the accumulation of large amounts of data for comprehensive analyses relies heavily on standardized protocols and efficient analyses, I further worked on the development of analysis tools and helped proposing some general experimental guidelines to enable further acceleration and standardization of experiments and subsequent computational steps. The tools that I developed can be found on my github page (https://github.com/NiRuff/IntelliPy & https://github.com/NiRuff/ViNe-Seg ). The former, IntelliPy has been published here.
The analysis of calcium imaging data in RG Stroh led to the development of some analytical procedures that led to the ViNe-Seg tool, that is currently still under development but also to the publication of some experimental guidelines in a book chapter.
Currently I am working on some extensions of my old projects but also on the following:
- Establishment and analyses of long-term observation systems in stressed mice
- Analysis of proteomic and methylomic alterations in aging individuals
- Prediction of stressor response score based on proteomic data in humans
- Backhaus, H., Ruffini, N., Wierczeiko, A., Stroh, A. (2023). An All-Optical Physiology Pipeline Toward Highly Specific and Artifact-Free Circuit Mapping. In: Papagiakoumou, E. (eds) All-Optical Methods to Study Neuronal Function. Neuromethods, vol 191. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2764-8_5
- Ruffini N, Klingenberg S, Heese R, Schweiger S, Gerber S. The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach. Front Aging Neurosci. 2022 Jun 27;14:866886. doi: 10.3389/fnagi.2022.866886. PMID: 35832065; PMCID: PMC9271745
- Ruffini N, Müller M, Schmitt U, Gerber S. IntelliPy: A GUI for analyzing IntelliCage data. Bioinformatics. 2021 Oct 2;37(21):3972–3. doi: 10.1093/bioinformatics/btab682. Epub ahead of print. PMID: 34601559; PMCID: PMC8570781.
- Rosales Jubal E, Schwalm M, Dos Santos Guilherme M, Schuck F, Reinhardt S, Tose A, Barger Z, Roesler MK, Ruffini N, Wierczeiko A, Schmeisser MJ, Schmitt U, Endres K, Stroh A. Acitretin reverses early functional network degradation in a mouse model of familial Alzheimer's disease. Sci Rep. 2021 Mar 23;11(1):6649. doi: 10.1038/s41598-021-85912-0. PMID: 33758244; PMCID: PMC7988040.
- Nicolas Ruffini, Susanne Klingenberg, Susann Schweiger and Susanne Gerber. Common Factors in Neurodegeneration: A Meta-Study revealing Shared Patterns on a Multi-Omics Scale, Cells 9(12), 2642, https://doi.org/10.3390/cells9122642, (2020).