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X-linked hypophosphatemia (XLH) is a rare hereditary disorder characterized by PHEX gene mutations, elevated FGF23 levels, and impaired bone mineralization. Burosumab, a monoclonal antibody targeting FGF23, has demonstrated clinical efficacy; however, the immunological dynamics during treatment remain unexplored. This study employed longitudinal single-cell RNA sequencing (scRNA-seq) to characterize peripheral blood immune cell alterations across multiple treatment stages in pediatric XLH. We performed scRNA-seq on peripheral blood mononuclear cells from pediatric patients with XLH at five time points spanning pretreatment and burosumab therapy phases, along with healthy pediatric controls. A total of 93,112 cells were analyzed using comprehensive bioinformatic pipelines, including unsupervised clustering, pseudotime trajectory analysis, temporal gene expression profiling, and cell-cell communication inference. Eleven major immune cell populations were identified, with notable dynamic alterations in T cells and natural killer (NK) cell subtypes across treatment stages. The cellular proportion of T helper 2 (Th2) cells and regulatory T (Treg) cells were elevated before treatment and normalized during therapy, whereas T helper 17 (Th17) cells exhibited reciprocal patterns. Genes upregulated in Treg cells during early treatment were enriched in osteoclast differentiation pathway. Natural killer subtype 2 cells showed enrichment in osteoclast differentiation and interleukin-12 response pathways. Cell-cell communication analysis identified dynamic interactions among Th2 cells, Th17 cells, Treg cells, and NK cell subtypes mediated by KLRB1-CLEC2D and SELL-SELPLG ligand-receptor pairs. This longitudinal transcriptomic study provides the first comprehensive characterization of peripheral immune dynamics during burosumab therapy in XLH, offering new insights into the immunological mechanisms underlying treatment response.
Pubmed ID: 42389507
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A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)
View all literature mentionsOpen-source software for network visualization and analysis helping data analysts to intuitively reveal patterns and trends, highlight outliers and tells stories with their data. It uses a 3D render engine to display large graphs in real-time and to speed up the exploration. Gephi combines built-in functionalities and flexible architecture to: explore, analyze, spatialize, filter, cluterize, manipulate and export all types of networks. Gephi runs on Windows, Linux and Mac OS X. Gephi is based on a visualize-and-manipulate paradigm which allow any user to discover networks and data properties. Moreover, it is designed to follow the chain of a case study, from data file to nice printable maps. It is open-source and free (GNU General Public License). Applications: * Exploratory Data Analysis: intuition-oriented analysis by networks manipulations in real time. * Link Analysis: revealing the underlying structures of associations between objects, in particular in scale-free networks. * Social Network Analysis: easy creation of social data connectors to map community organizations and small-world networks. * Biological Network analysis: representing patterns of biological data. * Poster creation: scientific work promotion with hi-quality printable maps. Gephi 0.7 architecture is modular and therefore allows developers to add and extend functionalities with ease. New features like Metrics, Layout, Filters, Data sources and more can be easily packaged in plugins and shared. The built-in Plugins Center automatically gets the list of plugins available from the Gephi Plugin portal and takes care of all software updates. Download, comment, and rate plugins provided by community members and third-party companies, or post your own contributions!
View all literature mentionsDatabase of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations and are derived from four sources: Genomic Context, High-throughput experiments, (Conserved) Coexpression, and previous knowledge. STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable. The database currently covers 5''214''234 proteins from 1133 organisms. (2013)
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