Abstract
Atypical parkinsonism (AP) is a group of complex neurodegenerative disorders with marked clinical and pathophysiological heterogeneity. The use of systems biology tools may contribute to the characterization of hub-bottleneck genes, and the identification of its biological pathways to broaden the understanding of the bases of these disorders. A systematic search was performed on the DisGeNET database, which integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. The tools STRING 11.0 and Cytoscape 3.8.2 were used for analysis of protein-protein interaction (PPI) network. The PPI network topography analyses were performed using the CytoHubba 0.1 plugin for Cytoscape. The hub and bottleneck genes were inserted into 4 different sets on the InteractiveVenn. Additional functional enrichment analyses were performed to identify Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and gene ontology for a described set of genes. The systematic search in the DisGeNET database identified 485 genes involved with Atypical Parkinsonism. Superimposing these genes, we detected a total of 31 hub-bottleneck genes. Moreover, our functional enrichment analyses demonstrated the involvement of these hub-bottleneck genes in 3 major KEGG pathways. We identified 31 highly interconnected hub-bottleneck genes through a systems biology approach, which may play a key role in the pathogenesis of atypical parkinsonism. The functional enrichment analyses showed that these genes are involved in several biological processes and pathways, such as the glial cell development, glial cell activation and cognition, pathways were related to Alzheimer disease and Parkinson disease. As a hypothesis, we highlight as possible key genes for AP the MAPT (microtubule associated protein tau), APOE (apolipoprotein E), SNCA (synuclein alpha) and APP (amyloid beta precursor protein) genes.
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Data availability
The datasets generated analysed during the current study are available in the repository, DisGeNET database v.7,0 https://www.disgenet.org.
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Acknowledgements
We would like to thank Research Incentive Fund – Hospital de Clınicas de Porto Alegre (FIPE – HCPA), CAPES (Coordination for the Improvement of Higher Education Personnel) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for financial support and Programa de Pós- Graduação em Genética e Biologia Molecular at Universidade Federal do Rio Grande do Sul, Brazil.
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This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Research Incentive Fund – Hospital de Clínicas de Porto Alegre (FIPE – HCPA).
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Amanda Pasqualotto, Marian Siebert, Felipe Mateus Pellenz, Vinicius da Silva, Artur Francisco Schumacher-Schuh and Ida Vanessa Doederlein Schwartz. The first draft of the manuscript was written by Amanda Pasqualotto and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Supplementary Material 1: Table S1.
All genes recovered from the DisGeNET database associated with AP
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Pasqualotto, A., da Silva, V., Pellenz, F. et al. Identification of metabolic pathways and key genes associated with atypical parkinsonism using a systems biology approach. Metab Brain Dis 39, 577–587 (2024). https://doi.org/10.1007/s11011-024-01342-7
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DOI: https://doi.org/10.1007/s11011-024-01342-7