Introduction: 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. Methods: 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. Results: 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. Discussion: 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/.

Computational Medicine Platform Fundacion Progreso y Salud Sevilla Spain

Department of Experimental and Health Sciences Pompeu Fabra University Barcelona Spain

Department of Genetics Genomics and Informatics College of Medicine University of Tennessee Health Science Center Memphis TN United States

Faculty of Mathematics and Physics Charles University Prague Czechia

Institute of Genetics and Biophysics National Research Council of Italy Naples Rome

Luxembourg Centre for Systems Biomedicine University of Luxembourg Luxembourg Luxembourg

MedBioinformatics Solutions SL Barcelona Spain

Research Programme on Biomedical Informatics Barcelona Spain

Spanish Network of Research in Rare Diseases Sevilla Spain

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Adams N. A., Awadein A., Toma H. S. (2007). The retinal ciliopathies. Ophthalmic Genet. 28, 113–125. 10.1080/13816810701537424 PubMed DOI

Ayuso C., Millan J. M. (2010). Retinitis pigmentosa and allied conditions today: A paradigm of translational research. Genome Med. 2, 34. 10.1186/gm155 PubMed DOI PMC

Balci H., Siper M. C., Saleh N., Safarli I., Roy L., Kilicarslan M., et al. (2021). Newt: A comprehensive web-based tool for viewing, constructing and analyzing biological maps. Bioinformatics 37, 1475–1477. 10.1093/bioinformatics/btaa850 PubMed DOI

Bales K. L., Gross A. K. (2016). Aberrant protein trafficking in retinal degenerations: The initial phase of retinal remodeling. Exp. Eye Res. 150, 71–80. 10.1016/j.exer.2015.11.007 PubMed DOI PMC

Bijnens J., Missiaen L., Bultynck G., Parys J. B. (2018). A critical appraisal of the role of intracellular Ca2+-signaling pathways in Kawasaki disease. Cell Calcium 71, 95–103. 10.1016/j.ceca.2018.01.002 PubMed DOI

Bukulmez H. (2021). Current understanding of multisystem inflammatory syndrome (MIS-C) following COVID-19 and its distinction from Kawasaki disease. Curr. Rheumatol. Rep. 23, 58. 10.1007/s11926-021-01028-4 PubMed DOI PMC

Carvalho-Silva D., Pierleoni A., Pignatelli M., Ong C., Fumis L., Karamanis N., et al. (2019). Open targets platform: New developments and updates two years on. Nucleic Acids Res. 47, D1056–D1065. 10.1093/nar/gky1133 PubMed DOI PMC

Chakraborty D., Strayve D. G., Makia M. S., Conley S. M., Kakahel M., Al-Ubaidi M. R., et al. (2020). Novel molecular mechanisms for Prph2-associated pattern dystrophy. FASEB J. Off. Publ. Fed. Am. Soc. Exp. Biol. 34, 1211–1230. 10.1096/fj.201901888r PubMed DOI PMC

Côté R., Reisinger F., Martens L., Barsnes H., Vizcaino J. A., Hermjakob H. (2010). The Ontology Lookup service: Bigger and better. Nucleic Acids Res. 38, W155–W160. 10.1093/nar/gkq331 PubMed DOI PMC

Csardi G., Nepusz T. (2006). The igraph software package for complex network research. InterJournal Complex Syst. 1695, 1–9.

Cunningham F., Allen J. E., Allen J., Alvarez-Jarreta J., Amode M. R., Im A., et al. (2022). Ensembl 2022. Nucleic Acids Res. 50, D988–D995. 10.1093/nar/gkab1049 PubMed DOI PMC

D’Alessandro E., Kawasaki A., Eandi C. M. (2022). Pathogenesis of vascular retinal manifestations in COVID-19 patients: A review. Biomedicines 10, 2710. 10.3390/biomedicines10112710 PubMed DOI PMC

Davis S., Geoquery P. S. M. (2007). GEOquery: A bridge between the gene expression Omnibus (GEO) and BioConductor. Bioinformatics 23, 1846–1847. 10.1093/bioinformatics/btm254 PubMed DOI

Ferrari S., Di Iorio E., Barbaro V., Ponzin D., Sorrentino F. S., Parmeggiani F. (2011). Retinitis pigmentosa: Genes and disease mechanisms. Curr. Genomics 12, 238–249. 10.2174/138920211795860107 PubMed DOI PMC

Frontiers (2021). Pre-mRNA processing factors and retinitis pigmentosa: RNA splicing and beyond. https://www.frontiersin.org/articles/10.3389/fcell.2021.700276/full. PubMed DOI PMC

Fu Z., Sun Y., Cakir B., Tomita Y., Huang S., Wang Z., et al. (2020). Targeting neurovascular interaction in retinal disorders. Int. J. Mol. Sci. 21, 1503 10.3390/ijms21041503 PubMed DOI PMC

Fujita K. A., Ostaszewski M., Matsuoka Y., Ghosh S., Glaab E., Trefois C., et al. (2014). Integrating pathways of Parkinson’s disease in a molecular interaction map. Mol. Neurobiol. 49, 88–102. 10.1007/s12035-013-8489-4 PubMed DOI PMC

Gawron P., Ostaszewski M., Satagopam V., Gebel S., Mazein A., Kuzma M., et al. (2016). MINERVA-a platform for visualization and curation of molecular interaction networks. NPJ Syst. Biol. Appl. 2, 16020. 10.1038/npjsba.2016.20 PubMed DOI PMC

Gawron P., Smula E., Schneider R., Ostaszewski M. (2023). Exploration and comparison of molecular mechanisms across diseases using MINERVA Net. Protein Sci. 32, e4565. 10.1002/pro.4565 PubMed DOI PMC

Gillespie M., Jassal B., Stephan R., Milacic M., Rothfels K., Senff-Ribeiro A., et al. (2022). The reactome pathway knowledgebase 2022. Nucleic Acids Res. 50, D687–D692. 10.1093/nar/gkab1028 PubMed DOI PMC

Giryes S., McGonagle D. (2023). Immune and non-immune mechanisms that determine vasculitis and coronary artery aneurysm topography in Kawasaki disease and MIS-C. Autoimmun. Rev. 22, 103240. 10.1016/j.autrev.2022.103240 PubMed DOI

Hoksza D., Gawron P., Ostaszewski M., Hausenauer J., Schneider R. (2019). Closing the gap between formats for storing layout information in systems biology. Brief. Bioinform 21. 10.1093/bib/bbz067 PubMed DOI PMC

Hoksza D., Gawron P., Ostaszewski M., Schneider R. (2018). MolArt: A molecular structure annotation and visualization tool. Bioinforma. Oxf Engl. 34, 4127–4128. 10.1093/bioinformatics/bty489 PubMed DOI PMC

Hoksza D., Gawron P., Ostaszewski M., Smula E., Schneider R. (2019). MINERVA API and plugins: Opening molecular network analysis and visualization to the community. Bioinforma. Oxf Engl. 35, 4496–4498. 10.1093/bioinformatics/btz286 PubMed DOI PMC

Ichhpujani P., Parmar U. P. S., Duggal S., Kumar S. (2022). COVID-19 vaccine-associated ocular adverse effects: An overview. Vaccines 10, 1879. 10.3390/vaccines10111879 PubMed DOI PMC

Kitano H., Funahashi A., Matsuoka Y., Oda K. (2005). Using process diagrams for the graphical representation of biological networks. Nat. Biotechnol. 23, 961–966. 10.1038/nbt1111 PubMed DOI

Köhler S., Gargano M., Matentzoglu N., Carmody L. C., Lewis-Smith D., Vasilevsky N. A., et al. (2021). The human phenotype Ontology in 2021. Nucleic Acids Res. 49, D1207–D1217. 10.1093/nar/gkaa1043 PubMed DOI PMC

Kuleshov M. V., Jones M. R., Rouillard A. D., Fernandez N. F., Duan Q., Wang Z., et al. (2016). Enrichr: A comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44, W90–W97. 10.1093/nar/gkw377 PubMed DOI PMC

Kumrah R., Vignesh P., Rawat A., Singh S. (2020). Immunogenetics of Kawasaki disease. Clin. Rev. Allergy Immunol. 59, 122–139. 10.1007/s12016-020-08783-9 PubMed DOI

Landrum M. J., Lee J. M., Benson M., Brown G. R., Chao C., Chitipiralla S., et al. (2018). ClinVar: Improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 46, D1062–D1067. 10.1093/nar/gkx1153 PubMed DOI PMC

Lei W.-T., Hsu C.-W., Chen P.-C., Tseng P., Kuo H.-C., Guo M. M.-H., et al. (2021). Increased risk of asthma and allergic rhinitis in patients with a past history of Kawasaki disease: A systematic review and meta-analyses. Front. Pediatr. 9, 746856. 10.3389/fped.2021.746856 PubMed DOI PMC

Liu T., Salguero P., Petek M., Martinez-Mira C., Balzano-Nogueira L., Ramšak Ž., et al. (2022). PaintOmics 4: New tools for the integrative analysis of multi-omics datasets supported by multiple pathway databases. Nucleic Acids Res. gkac352 50, W551–W559. 10.1093/nar/gkac352 PubMed DOI PMC

Liu X., Xu K., Tao X., Yin R., Ren G., Yu M., et al. (2022). ExpressVis: A biologist-oriented interactive web server for exploring multi-omics data. Nucleic Acids Res. gkac399 50, W312–W321. 10.1093/nar/gkac399 PubMed DOI PMC

Malone J., Holloway E., Adamusiak T., Kapushesky M., Zheng J., Kolesnikov N., et al. (2010). Modeling sample variables with an experimental factor Ontology. Bioinforma. Oxf Engl. 26, 1112–1118. 10.1093/bioinformatics/btq099 PubMed DOI PMC

Mannu G. S. (2014). Retinal phototransduction. Retin. Phototransduction. Neurosci. 19, 275–280. PubMed PMC

Martens M., Ammar A., Riutta A., Waagmeester A., Slenter D. N., Hanspers K., et al. (2021). WikiPathways: Connecting communities. Nucleic Acids Res. 49, D613–D621. 10.1093/nar/gkaa1024 PubMed DOI PMC

Mazein A., Ivanova O., Balaur I., Ostaszewski M., Berzhitskaya V., Serebriyskaya T., et al. (2021). AsthmaMap: An interactive knowledge repository for mechanisms of asthma. J. Allergy Clin. Immunol. 147, 853–856. 10.1016/j.jaci.2020.11.032 PubMed DOI

Mazein A., Ostaszewski M., Kuperstein I., Watterson S., Le Novère N., Lefaudeux D., et al. (2018). Systems medicine disease maps: Community-driven comprehensive representation of disease mechanisms. NPJ Syst. Biol. Appl. 4, 21. 10.1038/s41540-018-0059-y PubMed DOI PMC

McLaren W., Gil L., Hunt S. E., Riat H. S., Ritchie G. R. S., Thormann A., et al. (2016). The Ensembl variant effect predictor. Genome Biol. 17, 122. 10.1186/s13059-016-0974-4 PubMed DOI PMC

Orpha (1997). Orphanet: An online database of rare diseases and orphan drugs copyright INSERM. Available at http://www.orpha.net .

Ortega J. T., Jastrzebska B. (2021). Neuroinflammation as a therapeutic target in retinitis pigmentosa and quercetin as its potential modulator. Pharmaceutics 13, 1935. 10.3390/pharmaceutics13111935 PubMed DOI PMC

Ostaszewski M., Niarakis A., Mazein A., Kuperstein I., Phair R., Orta-Resendiz A., et al. (2021). COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms. Mol. Syst. Biol. 17, e10387. 10.15252/msb.202110387 PubMed DOI PMC

Piñero J., Ramírez-Anguita J. M., Saüch-Pitarch J., Ronzano F., Centeno E., Sanz F., et al. (2020). The DisGeNET knowledge platform for disease genomics: 2019 update. Nucleic Acids Res. 48, D845–D855. 10.1093/nar/gkz1021 PubMed DOI PMC

Makino N., Kuwabara M., Matsubara Y., Kosami K., Sasahara T., et al. (2022). Incidence of Kawasaki disease before and after the COVID-19 pandemic in Japan: Results of the 26th nationwide survey, 2019 to 2020. JAMA Pediatr. 176, 1217. 10.1001/jamapediatrics.2022.3756 PubMed DOI PMC

Robinson M. D., McCarthy D. J., Smyth G. K. (2010). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140. 10.1093/bioinformatics/btp616 PubMed DOI PMC

Rodchenkov I., Babur O., Luna A., Aksoy B. A., Wong J. V., Fong D., et al. (2019). Pathway commons 2019 update: Integration, analysis and exploration of pathway data. Nucleic Acids Res. gkz946 48, D489–D497. 10.1093/nar/gkz946 PubMed DOI PMC

Rodrigues A., Slembrouck-Brec A., Nanteau C., Terray A., Tymoshenko Y., Zagar Y., et al. (2022). Modeling PRPF31 retinitis pigmentosa using retinal pigment epithelium and organoids combined with gene augmentation rescue. Npj Regen. Med. 7, 39. 10.1038/s41536-022-00235-6 PubMed DOI PMC

Saito K., Gotoh N., Kang I., Shimada T., Usui T., Terao C. (2021). A case of retinitis pigmentosa homozygous for a rare CNGA1 causal variant. Sci. Rep. 11, 4681. 10.1038/s41598-021-84098-9 PubMed DOI PMC

Sakurai Y. (2019). Autoimmune aspects of Kawasaki disease. J. Investig. Allergol. Clin. Immunol. 29, 251–261. 10.18176/jiaci.0300 PubMed DOI

Singh V., Kalliolias G. D., Ostaszewski M., Veyssiere M., Pilalis E., Gawron P., et al. (2020). RA-Map: Building a state-of-the-art interactive knowledge base for rheumatoid arthritis. Database J. Biol. Databases Curation 2020, baaa017. 10.1093/database/baaa017 PubMed DOI PMC

Szklarczyk D., Gable A. L., Lyon D., Junge A., Wyder S., Huerta-Cepas J., et al. (2019). STRING v11: Protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47, D607–D613. 10.1093/nar/gky1131 PubMed DOI PMC

Türei D., Korcsmáros T., Saez-Rodriguez J. (2016). OmniPath: Guidelines and gateway for literature-curated signaling pathway resources. Nat. Methods 13, 966–967. 10.1038/nmeth.4077 PubMed DOI

Vanderkam D., Aksoy B. A., Hodes I., Perrone J., Hammerbacher J. (2016). pileup.js: a JavaScript library for interactive and in-browser visualization of genomic data. Bioinforma. Oxf Engl. 32, 2378–2379. 10.1093/bioinformatics/btw167 PubMed DOI PMC

Yang J., Dong C., Duan H., Shu Q., Li H. (2021). RDmap: A map for exploring rare diseases. Orphanet J. Rare Dis. 16, 101. 10.1186/s13023-021-01741-4 PubMed DOI PMC