03044nas a2200385   4500008004100000022001400041245012200055210006900177260001600246300000700262490000700269520175100276653001502027653001102042653001302053653004202066653001102108653002302119653001802142100002802160700002302188700002602211700002402237700002602261700003202287700003302319700002802352700003002380700001802410700002102428700002002449700001902469700002502488856014502513       2025                        eng d  a1479-587600aA genomic strategy for precision medicine in rare diseases: integrating customized algorithms into clinical practice.0 agenomic strategy for precision medicine in rare diseases integra  c2025 Jan 20  a860 v233 a<p><b>BACKGROUND: </b>Despite the use of Next-Generation Sequencing (NGS) as the gold standard for the diagnosis of rare diseases, its clinical implementation has been challenging, limiting the cost-effectiveness of NGS and the understanding, control and safety essential for decision-making in clinical applications. Here, we describe a personalized NGS-based strategy integrating precision medicine into a public healthcare system and its implementation in the routine diagnosis process during a five-year pilot program.</p><p><b>METHODS: </b>Our approach involved customized probe designs, the generation of virtual panels and the development of a personalized medicine module (PMM) for variant prioritization. This strategy was applied to 6500 individuals including 6267 index patients and 233 NGS-based carrier screenings.</p><p><b>RESULTS: </b>Causative variants were identified in 2061 index patients (average 32.9%, ranging from 12 to 62% by condition). Also, 131 autosomal-recessive cases could be partially genetically diagnosed. These results led to over 5000 additional studies including carrier, prenatal and preimplantational tests or pharmacological and gene therapy treatments.</p><p><b>CONCLUSION: </b>This strategy has shown promising improvements in the diagnostic rate, facilitating timely diagnosis and gradually expanding our services portfolio for rare diseases. The steps taken towards the integration of clinical and genomic data are opening new possibilities for conducting both retrospective and prospective healthcare studies. Overall, this study represents a major milestone in the ongoing efforts to improve our understanding and clinical management of rare diseases, a crucial area of medical research and care.</p>10aAlgorithms10aFemale10aGenomics10aHigh-Throughput Nucleotide Sequencing10aHumans10aPrecision Medicine10arare diseases1 aMéndez-Vidal, Cristina1 aBravo-Gil, Nereida1 aPerez-Florido, Javier1 aMarcos-Luque, Irene1 aFernández, Raquel, M1 aFernandez-Rueda, Jose, Luis1 adel Pozo, María, González-1 aMartín-Sánchez, Marta1 aFernández-Suárez, Elena1 aMena, Marcela1 aCarmona, Rosario1 aDopazo, Joaquin1 aBorrego, Salud1 aAntiňolo, Guillermo  uhttps://www.clinbioinfosspa.es/content/genomic-strategy-precision-medicine-rare-diseases-integrating-customized-algorithms-clinical-practice03075nas a2200325   4500008004100000022001400041245009700055210006900152260000900221300001200230490000600242520201700248100001802265700001802283700001902301700002402320700002702344700003202371700002202403700001502425700002202440700002202462700002202484700002602506700002402532700002002556700002202576700002302598856012802621       2023                        eng d  a2673-764700aVisualization of automatically combined disease maps and pathway diagrams for rare diseases.0 aVisualization of automatically combined disease maps and pathway  c2023  a11015050 v33 a<p> Investigation of molecular mechanisms of human disorders, especially rare diseases, require exploration of various knowledge repositories for building precise hypotheses and complex data interpretation. Recently, increasingly more resources offer diagrammatic representation of such mechanisms, including disease-dedicated schematics in pathway databases and disease maps. However, collection of knowledge across them is challenging, especially for research projects with limited manpower.  In this article we present an automated workflow for construction of maps of molecular mechanisms for rare diseases. The workflow requires a standardized definition of a disease using Orphanet or HPO identifiers to collect relevant genes and variants, and to assemble a functional, visual repository of related mechanisms, including data overlays. The diagrams composing the final map are unified to a common systems biology format from CellDesigner SBML, GPML and SBML+layout+render. The constructed resource contains disease-relevant genes and variants as data overlays for immediate visual exploration, including embedded genetic variant browser and protein structure viewer.  We demonstrate the functionality of our workflow on two examples of rare diseases: Kawasaki disease and retinitis pigmentosa. Two maps are constructed based on their corresponding identifiers. Moreover, for the retinitis pigmentosa use-case, we include a list of differentially expressed genes to demonstrate how to tailor the workflow using omics datasets.  In summary, our work allows for an ad-hoc construction of molecular diagrams combined from different sources, preserving their layout and graphical style, but integrating them into a single resource. This allows to reduce time consuming tasks of prototyping of a molecular disease map, enabling visual exploration, hypothesis building, data visualization and further refinement. The code of the workflow is open and accessible at https://gitlab.lcsb.uni.lu/minerva/automap/.</p>1 aGawron, Piotr1 aHoksza, David1 aPiñero, Janet1 aPeña-Chilet, Maria1 aEsteban-Medina, Marina1 aFernandez-Rueda, Jose, Luis1 aColonna, Vincenza1 aSmula, Ewa1 aHeirendt, Laurent1 aAncien, François1 aGrouès, Valentin1 aSatagopam, Venkata, P1 aSchneider, Reinhard1 aDopazo, Joaquin1 aFurlong, Laura, I1 aOstaszewski, Marek  uhttps://www.clinbioinfosspa.es/content/visualization-automatically-combined-disease-maps-and-pathway-diagrams-rare-diseases