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.

Castrense Savojardo, D.B. (2022). Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions. SCIENTIFIC REPORTS, 12, 1-10 [10.1038/s41598-022-22818-5].

Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions

Castrense Savojardo
Primo
;
Davide Baldazzi;Giulia Babbi;Pier Luigi Martelli
Penultimo
;
Rita Casadio
Ultimo
2022

Abstract

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.
2022
Castrense Savojardo, D.B. (2022). Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions. SCIENTIFIC REPORTS, 12, 1-10 [10.1038/s41598-022-22818-5].
Castrense Savojardo, Davide Baldazzi, Giulia Babbi, Pier Luigi Martelli, Rita Casadio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/903045
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