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Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling
Recent studies have demonstrated a relevant role of the host genetics in the coronavirus disease 2019 (COVID-19) prognosis. Most of the 7000 rare diseases described to date have a genetic component, typically highly penetrant. However, this vast spectrum of genetic variability remains yet unexplored...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9239744/ https://www.ncbi.nlm.nih.gov/pubmed/35022696 http://dx.doi.org/10.1093/hmg/ddac007 |
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author | López-Sánchez, Macarena Loucera, Carlos Peña-Chilet, María Dopazo, Joaquín |
author_facet | López-Sánchez, Macarena Loucera, Carlos Peña-Chilet, María Dopazo, Joaquín |
author_sort | López-Sánchez, Macarena |
collection | PubMed |
description | Recent studies have demonstrated a relevant role of the host genetics in the coronavirus disease 2019 (COVID-19) prognosis. Most of the 7000 rare diseases described to date have a genetic component, typically highly penetrant. However, this vast spectrum of genetic variability remains yet unexplored with respect to possible interactions with COVID-19. Here, a mathematical mechanistic model of the COVID-19 molecular disease mechanism has been used to detect potential interactions between rare disease genes and the COVID-19 infection process and downstream consequences. Out of the 2518 disease genes analyzed, causative of 3854 rare diseases, a total of 254 genes have a direct effect on the COVID-19 molecular disease mechanism and 207 have an indirect effect revealed by a significant strong correlation. This remarkable potential of interaction occurs for >300 rare diseases. Mechanistic modeling of COVID-19 disease map has allowed a holistic systematic analysis of the potential interactions between the loss of function in known rare disease genes and the pathological consequences of COVID-19 infection. The results identify links between disease genes and COVID-19 hallmarks and demonstrate the usefulness of the proposed approach for future preventive measures in some rare diseases. |
format | Online Article Text |
id | pubmed-9239744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92397442022-06-29 Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling López-Sánchez, Macarena Loucera, Carlos Peña-Chilet, María Dopazo, Joaquín Hum Mol Genet Bioinformatics Article Recent studies have demonstrated a relevant role of the host genetics in the coronavirus disease 2019 (COVID-19) prognosis. Most of the 7000 rare diseases described to date have a genetic component, typically highly penetrant. However, this vast spectrum of genetic variability remains yet unexplored with respect to possible interactions with COVID-19. Here, a mathematical mechanistic model of the COVID-19 molecular disease mechanism has been used to detect potential interactions between rare disease genes and the COVID-19 infection process and downstream consequences. Out of the 2518 disease genes analyzed, causative of 3854 rare diseases, a total of 254 genes have a direct effect on the COVID-19 molecular disease mechanism and 207 have an indirect effect revealed by a significant strong correlation. This remarkable potential of interaction occurs for >300 rare diseases. Mechanistic modeling of COVID-19 disease map has allowed a holistic systematic analysis of the potential interactions between the loss of function in known rare disease genes and the pathological consequences of COVID-19 infection. The results identify links between disease genes and COVID-19 hallmarks and demonstrate the usefulness of the proposed approach for future preventive measures in some rare diseases. Oxford University Press 2022-01-12 /pmc/articles/PMC9239744/ /pubmed/35022696 http://dx.doi.org/10.1093/hmg/ddac007 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Bioinformatics Article López-Sánchez, Macarena Loucera, Carlos Peña-Chilet, María Dopazo, Joaquín Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling |
title | Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling |
title_full | Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling |
title_fullStr | Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling |
title_full_unstemmed | Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling |
title_short | Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling |
title_sort | discovering potential interactions between rare diseases and covid-19 by combining mechanistic models of viral infection with statistical modeling |
topic | Bioinformatics Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9239744/ https://www.ncbi.nlm.nih.gov/pubmed/35022696 http://dx.doi.org/10.1093/hmg/ddac007 |
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