Data integration and trans-Omics analysis for reconstructing relevant pathways and networks underlying neurodegenerative diseases
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Abstract
Neurodegenerative diseases are characterized by the progressive decline of neuronal and glial structures and functions, affecting both the central and peripheral nervous system. This deterioration results in impaired cognitive and/or motor abilities. Despite their significant impact on patients’ and caregivers’ quality of life as well as on public health costs, and despite a great number of ongoing investigations, no effective treatment has been found, due to the complex nature of these disorders. As complex diseases arise from a combination of genetic, environmental, and life-style factors, addressing them requires comprehensive identification and quantification of components encompassing gene, transcript and protein-level information to uncover the interconnected pathways, circuits, and networks involved. Advances in high-throughput technologies and bioinformatics, coupled with powerful computational and statistical modeling tools, enable the characterization of DNA sequences, transcripts, proteins, lipids, metabolites, and other biomolecules as entities on their specific omics-level, facilitating a broader understanding of disease mechanisms. The objective of this thesis was to study neurodegenerative diseases using a multi-omics approach. To achieve this goal, four of the most prevalent neurodegenerative diseases were selected for analysis and
comparison across four different omics levels. This approach aimed to uncover common mechanisms as well as distinct patterns among the diseases or omics levels, hopefully providing insights into the etiology and pathogenesis of these debilitating conditions. The diseases included the most prominent proteinopathies Alzheimer’s Disease, Parkinson’s Disease, Amyotrophic Lateral Sclerosis, and Huntington’s Disease. The omics levels examined were the Genome, the Transcriptome, the Proteome and DNA-Methylation (Epigenetics). Common features and mechanisms of neurodegeneration, such as protein misfolding and aggregation, chronic inflammation, mitochondrial dysfunctions, impaired Ca2+ homeostasis, a deregulated autophagy and apoptosis, and adequate stress response could be confirmed for all four diseases. But also differences could be distinguished in a very promising field, the circadian rhythm, which we found to be disrupted
in a disease-specific manner in all four diseases. These disruptions originate from a deregulated sleep pattern and a deregulated metabolism, which are both strongly prevalent in industrialized countries, leading to the very symptoms of neurodegeneration. In a case study focussing on deregulated circadian rhythm genes our work shows how to proceed with the provided data. The results of this case study are pointing to the importance on restoring healthy sleep patterns in order to prevent or at least prolong early disease stages. Future work could be done in the same way for detecting disease-specific differences in the main metabolic pathways, the AMPK- and the mTOR pathways.