HYGIEIA: HYpothesizing the Genesis of Infectious Diseases and Epidemics through an Integrated Systems Biology Approach
More than two years on, the COVID-19 pandemic continues to wreak havoc around the world and has battle-tested the pandemic-situation responses of all major global governments. Two key areas of investigation that are still unclear are: the molecular mechanisms that lead to heterogenic patient outcome...
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Published in | Viruses Vol. 14; no. 7; p. 1373 |
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Main Authors | , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
MDPI AG
23.06.2022
MDPI |
Subjects | |
Online Access | Get full text |
ISSN | 1999-4915 1999-4915 |
DOI | 10.3390/v14071373 |
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Abstract | More than two years on, the COVID-19 pandemic continues to wreak havoc around the world and has battle-tested the pandemic-situation responses of all major global governments. Two key areas of investigation that are still unclear are: the molecular mechanisms that lead to heterogenic patient outcomes, and the causes of Post COVID condition (AKA Long-COVID). In this paper, we introduce the HYGIEIA project, designed to respond to the enormous challenges of the COVID-19 pandemic through a multi-omic approach supported by network medicine. It is hoped that in addition to investigating COVID-19, the logistics deployed within this project will be applicable to other infectious agents, pandemic-type situations, and also other complex, non-infectious diseases. Here, we first look at previous research into COVID-19 in the context of the proteome, metabolome, transcriptome, microbiome, host genome, and viral genome. We then discuss a proposed methodology for a large-scale multi-omic longitudinal study to investigate the aforementioned biological strata through high-throughput sequencing (HTS) and mass-spectrometry (MS) technologies. Lastly, we discuss how a network medicine approach can be used to analyze the data and make meaningful discoveries, with the final aim being the translation of these discoveries into the clinics to improve patient care. |
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AbstractList | More than two years on, the COVID-19 pandemic continues to wreak havoc around the world and has battle-tested the pandemic-situation responses of all major global governments. Two key areas of investigation that are still unclear are: the molecular mechanisms that lead to heterogenic patient outcomes, and the causes of Post COVID condition (AKA Long-COVID). In this paper, we introduce the HYGIEIA project, designed to respond to the enormous challenges of the COVID-19 pandemic through a multi-omic approach supported by network medicine. It is hoped that in addition to investigating COVID-19, the logistics deployed within this project will be applicable to other infectious agents, pandemic-type situations, and also other complex, non-infectious diseases. Here, we first look at previous research into COVID-19 in the context of the proteome, metabolome, transcriptome, microbiome, host genome, and viral genome. We then discuss a proposed methodology for a large-scale multi-omic longitudinal study to investigate the aforementioned biological strata through high-throughput sequencing (HTS) and mass-spectrometry (MS) technologies. Lastly, we discuss how a network medicine approach can be used to analyze the data and make meaningful discoveries, with the final aim being the translation of these discoveries into the clinics to improve patient care. More than two years on, the COVID-19 pandemic continues to wreak havoc around the world and has battle-tested the pandemic-situation responses of all major global governments. Two key areas of investigation that are still unclear are: the molecular mechanisms that lead to heterogenic patient outcomes, and the causes of Post COVID condition (AKA Long-COVID). In this paper, we introduce the HYGIEIA project, designed to respond to the enormous challenges of the COVID-19 pandemic through a multi-omic approach supported by network medicine. It is hoped that in addition to investigating COVID-19, the logistics deployed within this project will be applicable to other infectious agents, pandemic-type situations, and also other complex, non-infectious diseases. Here, we first look at previous research into COVID-19 in the context of the proteome, metabolome, transcriptome, microbiome, host genome, and viral genome. We then discuss a proposed methodology for a large-scale multi-omic longitudinal study to investigate the aforementioned biological strata through high-throughput sequencing (HTS) and mass-spectrometry (MS) technologies. Lastly, we discuss how a network medicine approach can be used to analyze the data and make meaningful discoveries, with the final aim being the translation of these discoveries into the clinics to improve patient care.More than two years on, the COVID-19 pandemic continues to wreak havoc around the world and has battle-tested the pandemic-situation responses of all major global governments. Two key areas of investigation that are still unclear are: the molecular mechanisms that lead to heterogenic patient outcomes, and the causes of Post COVID condition (AKA Long-COVID). In this paper, we introduce the HYGIEIA project, designed to respond to the enormous challenges of the COVID-19 pandemic through a multi-omic approach supported by network medicine. It is hoped that in addition to investigating COVID-19, the logistics deployed within this project will be applicable to other infectious agents, pandemic-type situations, and also other complex, non-infectious diseases. Here, we first look at previous research into COVID-19 in the context of the proteome, metabolome, transcriptome, microbiome, host genome, and viral genome. We then discuss a proposed methodology for a large-scale multi-omic longitudinal study to investigate the aforementioned biological strata through high-throughput sequencing (HTS) and mass-spectrometry (MS) technologies. Lastly, we discuss how a network medicine approach can be used to analyze the data and make meaningful discoveries, with the final aim being the translation of these discoveries into the clinics to improve patient care. |
Audience | Academic |
Author | Kabamba, Benoît Belkhir, Leïla Ward, Bradley Cani, Patrice D. Vertommen, Didier Elens, Laure de Greef, Julien Haufroid, Vincent Balligand, Jean-Luc Collet, Jean-François Jodogne, Sébastien Pyr dit Ruys, Sébastien Yombi, Jean Cyr Gatto, Laurent Dewulf, Joseph P. |
AuthorAffiliation | 5 WELBIO (Walloon Excellence in Life Sciences and Biotechnology), Metabolism and Nutrition Research Group, Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; patrice.cani@uclouvain.be 1 Integrated Pharmacometrics, Pharmacogenomics and Pharmacokinetics Group (PMGK), Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; bradley.ward@uclouvain.be (B.W.); sebastien.pyrditruys@uclouvain.be (S.P.d.R.) 3 Department of Internal Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; jean.yombi@uclouvain.be 8 Department of Biochemistry, de Duve Institute, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium 4 WELBIO (Walloon Excellence in Life Sciences and Biotechnology), Pole of Pharmacology and Therapeutics (FATH), Institut de Recherche Experimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouva |
AuthorAffiliation_xml | – name: 1 Integrated Pharmacometrics, Pharmacogenomics and Pharmacokinetics Group (PMGK), Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; bradley.ward@uclouvain.be (B.W.); sebastien.pyrditruys@uclouvain.be (S.P.d.R.) – name: 5 WELBIO (Walloon Excellence in Life Sciences and Biotechnology), Metabolism and Nutrition Research Group, Louvain Drug Research Institute (LDRI), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; patrice.cani@uclouvain.be – name: 7 Department of Laboratory Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; benoit.kabamba@saintluc.uclouvain.be – name: 10 Computer Science and Engineering Department (INGI), Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM), UCLouvain, Université Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium; sebastien.jodogne@uclouvain.be – name: 4 WELBIO (Walloon Excellence in Life Sciences and Biotechnology), Pole of Pharmacology and Therapeutics (FATH), Institut de Recherche Experimentale et Clinique (IREC), Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; jean-luc.balligand@uclouvain.be – name: 8 Department of Biochemistry, de Duve Institute, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium – name: 9 Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; laurent.gatto@uclouvain.be – name: 3 Department of Internal Medicine, Cliniques Universitaires Saint-Luc, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; jean.yombi@uclouvain.be – name: 6 WELBIO (Walloon Excellence in Life Sciences and Biotechnology), de Duve Institute, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; jean-francois.collet@uclouvain.be – name: 12 De Duve Institute, and MASSPROT Platform, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; didier.vertommen@uclouvain.be – name: 11 Pôle de Microbiologie, Institut de Recherche Expérimentale et Clinique, UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium – name: 2 Louvain Center for Toxicology and Applied Pharmacology (LTAP), Institut de Recherche Expérimentale et Clinique (IREC), UCLouvain, Université Catholique de Louvain, 1200 Brussels, Belgium; julien.degreef@saintluc.uclouvain.be (J.d.G.); joseph.dewulf@saintluc.uclouvain.be (J.P.D.); vincent.haufroid@saintluc.uclouvain.be (V.H.) |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35891354$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1016_j_arres_2025_100126 crossref_primary_10_1111_bph_17449 crossref_primary_10_3390_cells11213526 crossref_primary_10_1021_acs_jproteome_4c00104 |
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Keywords | COVID-19 proteomics metabolomics metagenomics network medicine transcriptomics genomics post COVID condition |
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