Progeroid syndromes (PS) are a heterogeneous group of rare hereditary diseases with clinical features that resemble accelerated aging, and as such they serve as a useful model for understanding natural degenerative changes and the mechanisms of human aging. Although more than 100 such syndromes have been described to date, the information about them is scattered across various sources, making knowledge synthesis and systematic analysis difficult. The aim of this master’s thesis was to collect and systematically organize the dispersed data on PS and their associated genes and to deepen the understanding of this diverse group of disorders through integrative bioinformatic analysis of their genetic factors. By incorporating data from 84 publications and the OMIM database, we developed a comprehensive database named ProGenDB, which, with 144 genes and a total of 160 clinical PS entities, is, to our knowledge, the largest published collection of such disorders to date. We visualized the collected data in the form of a genome-phenome association network, offering a new perspective on the genetic and phenotypic heterogeneity of PS. The pathway enrichment analysis confirmed that PS genes are enriched in biological processes associated with natural aging, with DNA repair processes standing out in particular. The protein-protein interaction (PPI) network revealed a tight interconnection among the involved proteins, and the identified functional modules within this network enabled a systematic overview of the disrupted biological processes in PS. Centrality analyses within the PPI network highlighted key targets for further research. Furthermore, we identified 14 PS gene clusters in which the genes are arranged in close proximity on the genome, including two pairs of overlapping genes, and 48 PS genes located within fragile regions of the genome – known hotspots of genomic instability – thereby highlighting further regions of interest for future analysis. Overall, our study lays the foundation for future research in both the field of PS and physiological aging. Further refinement and expansion of the established database, as well as in-depth analyses of the highlighted genes and regions, represent key objectives for upcoming research efforts.
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