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A Phenotyping Regimen for Genetically Modified Mice Used to Study Genes Implicated in Human Diseases of Aging
Published on: July 14, 2016
A manually curated gene-phenotype catalogue for progeroid syndromes and premature aging
1University of Ljubljana, Biotechnical Faculty, Department of Animal Science, 1230 Domžale, Slovenia.
Abstract:
Progeroid syndromes (PS) are a heterogeneous group of rare hereditary disorders with features resembling premature aging, thereby serving as valuable models for studying human aging biology. However, data on these syndromes remain fragmented across literature sources, with inconsistent terminology and classifications hindering systematic analyses. To address these challenges, we developed a curated catalogue integrating information from 84 publications and the Online Mendelian Inheritance in Man (OMIM) database. This resource consolidates data on 144 genes linked to 56 syndromes and their subtypes, comprising 160 distinct clinical entities, and their associated clinical manifestations categorized into 18 clinical feature groups. The compiled data were visualized and analyzed through a genome-phenome association network, offering new insights into the genetic and phenotypic heterogeneity of these disorders. The gene set was further analyzed through a protein-protein interaction (PPI) network and functional enrichment analysis, revealing a highly interconnected protein network with pronounced enrichment of genome maintenance pathways. Ten highly connected hub genes were prioritized in the PPI network based on degree centrality and further examined in the context of aging by cross-referencing with the Open Genes database, a curated resource of human genes associated with aging and longevity. A case study of the LMNA gene illustrated the pleiotropic impact of single-gene variants across multiple syndromes and related disorders beyond classical PS. Overall, this study provides a reference resource and framework to support future research into premature aging syndromes and their broader implications for understanding physiological aging.
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