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Integrative analysis of multi-omics longitudinal data to identify effective strategies for the prediction and treatment of COVID-19

Projectomschrijving

Een deel van de COVID-19-patiënten ontwikkelt zeer ernstige ademhalingssymptomen, terwijl anderen milde griepachtige symptomen ervaren. Hoewel het duidelijk is dat genetische en niet-genetische factoren van invloed zijn op de ernst van het ziekteverloop zijn de onderliggende moleculaire mechanismen onbekend. Daardoor kan op dit moment het ziekteverloop voor een individu niet voorspeld worden.

Onderzoek en verwachte uitkomsten

Dit project beoogt door gebruik te maken van langdurende metingen van multi-omics-data meer inzicht in de ziekte te krijgen en het verloop te voorspellen. Met als uiteindelijke doel om tot een behandelstrategie voor individuele patiënten te komen.

Producten

Titel: Dysregulated Innate and Adaptive Immune Responses Discriminate Disease Severity in COVID-19
Magazine: The Journal of Infectious Diseases
Link: https://academic.oup.com/jid/article/223/8/1322/6125806
Titel: Dexamethasone attenuates interferon-related cytokine hyperresponsiveness in COVID-19 patients
Magazine: Frontiers in Immunology
Link: https://www.frontiersin.org/articles/10.3389/fimmu.2023.1233318/full
Titel: Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes
Magazine: Respiratory Medicine
Link: https://www.sciencedirect.com/science/article/pii/S0954611123002196

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Samenvatting van de aanvraag

The ongoing pandemic with the new SARS-CoV2 virus shows the desperate and urgent need for better strategies to predict and treat Coronavirus disease 2019 (COVID-19). A subset of COVID-19 patients develop very severe respiratory symptoms, whereas others experience mild flu-like symptoms. Although it is evident that the host genetic and non-genetic factors, in interaction with new SARS-CoV2 virus, can determine variability in COVID-19 outcome, the underlying molecular mechanisms of patient-specific (COVID-19) outcome are unknown. We have recently observed a striking time-dependent variability in immune response among COVID-19 patients, where 50% of the ICU patients showed immune response patterns similar to non-ICU patients. This suggests that instead of single layers of omics data measured cross-sectionally, we need longitudinal measurements of multi-omics data to predict severity and to obtain biological/molecular explanations to the clinical variability. To determine how individual variation in molecular response (e.g. circulatory proteins and metabolites) affect COVID-19 severity and outcome we will use a unique and a largest cohort to date of COVID-19 patients in the Netherlands to profile longitudinal multi-omics data. We will then characterize: 1) the role of plasma metabolites, inflammatory markers and circulatory proteome variability in explaining COVID-19 outcome; 2) pinpoint causal molecular networks using dynamic changes in host multi-omics data; and 3) provide the genetic support for multi-omics variability that determine COVID-19 outcome in prospective independent cohorts. By conducting systematic longitudinal systems biology analyses, we will be able to establish causal relationships between omics-networks and COVID-19 clinical phenotypes. This will increase our understanding of the pathogenesis of COVID-19 and help to sub-group patients based on their response pattern so that treatment strategies can be adapted to individual patient categories.

Onderwerpen

Kenmerken

Projectnummer:
10430012010002
Looptijd: 100%
Looptijd: 100 %
2020
2023
Onderdeel van programma:
Gerelateerde subsidieronde:
Projectleider en penvoerder:
dr. V.K. Kumar
Verantwoordelijke organisatie:
Radboud Universitair Medisch Centrum