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Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions
According to databases such as OMIM, Humsavar, Clinvar and Monarch, 1494 human enzymes are presently associated to 2539 genetic diseases, 75% of which are rare (with an Orphanet code). The Mondo ontology initiative allows a standardization of the disease name into specific codes, making it possible...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605996/ https://www.ncbi.nlm.nih.gov/pubmed/36289281 http://dx.doi.org/10.1038/s41598-022-22818-5 |
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author | Savojardo, Castrense Baldazzi, Davide Babbi, Giulia Martelli, Pier Luigi Casadio, Rita |
author_facet | Savojardo, Castrense Baldazzi, Davide Babbi, Giulia Martelli, Pier Luigi Casadio, Rita |
author_sort | Savojardo, Castrense |
collection | PubMed |
description | According to databases such as OMIM, Humsavar, Clinvar and Monarch, 1494 human enzymes are presently associated to 2539 genetic diseases, 75% of which are rare (with an Orphanet code). The Mondo ontology initiative allows a standardization of the disease name into specific codes, making it possible a computational association between genes, variants, diseases, and their effects on biological processes. Here, we tackle the problem of which biological processes enzymes can affect when the protein variant is disease-associated. We adopt Reactome to describe human biological processes, and by mapping disease-associated enzymes in the Reactome pathways, we establish a Reactome-disease association. This allows a novel categorization of human monogenic and polygenic diseases based on Reactome pathways and reactions. Our analysis aims at dissecting the complexity of the human genetic disease universe, highlighting all the possible links within diseases and Reactome pathways. The novel mapping helps understanding the biochemical/molecular biology of the disease and allows a direct glimpse on the present knowledge of other molecules involved. This is useful for a complete overview of the disease molecular mechanism/s and for planning future investigations. Data are collected in DAR, a database that is free for search and available at https://dar.biocomp.unibo.it. |
format | Online Article Text |
id | pubmed-9605996 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96059962022-10-28 Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions Savojardo, Castrense Baldazzi, Davide Babbi, Giulia Martelli, Pier Luigi Casadio, Rita Sci Rep Article According to databases such as OMIM, Humsavar, Clinvar and Monarch, 1494 human enzymes are presently associated to 2539 genetic diseases, 75% of which are rare (with an Orphanet code). The Mondo ontology initiative allows a standardization of the disease name into specific codes, making it possible a computational association between genes, variants, diseases, and their effects on biological processes. Here, we tackle the problem of which biological processes enzymes can affect when the protein variant is disease-associated. We adopt Reactome to describe human biological processes, and by mapping disease-associated enzymes in the Reactome pathways, we establish a Reactome-disease association. This allows a novel categorization of human monogenic and polygenic diseases based on Reactome pathways and reactions. Our analysis aims at dissecting the complexity of the human genetic disease universe, highlighting all the possible links within diseases and Reactome pathways. The novel mapping helps understanding the biochemical/molecular biology of the disease and allows a direct glimpse on the present knowledge of other molecules involved. This is useful for a complete overview of the disease molecular mechanism/s and for planning future investigations. Data are collected in DAR, a database that is free for search and available at https://dar.biocomp.unibo.it. Nature Publishing Group UK 2022-10-26 /pmc/articles/PMC9605996/ /pubmed/36289281 http://dx.doi.org/10.1038/s41598-022-22818-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Savojardo, Castrense Baldazzi, Davide Babbi, Giulia Martelli, Pier Luigi Casadio, Rita Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions |
title | Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions |
title_full | Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions |
title_fullStr | Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions |
title_full_unstemmed | Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions |
title_short | Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions |
title_sort | mapping human disease-associated enzymes into reactome allows characterization of disease groups and their interactions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605996/ https://www.ncbi.nlm.nih.gov/pubmed/36289281 http://dx.doi.org/10.1038/s41598-022-22818-5 |
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