Discovering potential interactions between rare diseases and COVID-19 by combining mechanistic models of viral infection with statistical modeling

Author:

López-Sánchez Macarena12,Loucera Carlos12ORCID,Peña-Chilet María123,Dopazo Joaquín1234ORCID

Affiliation:

1. Clinical Bioinformatics Area, Fundación Progreso y Salud (FPS), CDCA, Hospital Virgen del Rocio , Sevilla 41013, Spain

2. Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio , Sevilla 41013, Spain

3. Bioinformatics in Rare Diseases (BiER), Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocío , Sevilla 41013, Spain

4. FPS/ELIXIR-es, Hospital Virgen del Rocío , Sevilla 42013, Spain

Abstract

Abstract 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.

Funder

Spanish Ministry of Science and Innovation

Centro de Investigación Biomédica En Red de Enfermedades Raras-Instituto de Salud Carlos III

Instituto de Salud Carlos III

European Regional Development Fund

Fundación Banco Bilbao Vizcaya Argentaria

H2020 Programme of the European Union

Marie Curie Innovative Training Network ‘Machine Learning Frontiers in Precision Medicine’

Consejería de Salud y Familias de la Junta de Andalucía

Consejería de Salud y Familia

Junta de Andalucía

European Social Fund

Publisher

Oxford University Press (OUP)

Subject

Genetics (clinical),Genetics,Molecular Biology,General Medicine

Reference77 articles.

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