Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: López-Sánchez, Macarena, Loucera, Carlos, Peña-Chilet, María, Dopazo, Joaquín
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
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
_version_ 1784737370377027584
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
work_keys_str_mv AT lopezsanchezmacarena discoveringpotentialinteractionsbetweenrarediseasesandcovid19bycombiningmechanisticmodelsofviralinfectionwithstatisticalmodeling
AT louceracarlos discoveringpotentialinteractionsbetweenrarediseasesandcovid19bycombiningmechanisticmodelsofviralinfectionwithstatisticalmodeling
AT penachiletmaria discoveringpotentialinteractionsbetweenrarediseasesandcovid19bycombiningmechanisticmodelsofviralinfectionwithstatisticalmodeling
AT dopazojoaquin discoveringpotentialinteractionsbetweenrarediseasesandcovid19bycombiningmechanisticmodelsofviralinfectionwithstatisticalmodeling