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Host factors in severe COVID-19: learning from extreme cases

English title Host factors in severe COVID-19: learning from extreme cases
Applicant Bochud Pierre-Yves
Number 196036
Funding scheme Special Call on Coronaviruses
Research institution Service des Maladies Infectieuses Département de Médecine Interne CHUV
Institution of higher education University of Lausanne - LA
Main discipline Clinical Immunology and Immunopathology
Start/End 01.06.2020 - 31.05.2022
Approved amount 298'440.00
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All Disciplines (3)

Discipline
Clinical Immunology and Immunopathology
Immunology, Immunopathology
Infectious Diseases

Keywords (5)

Genetics/genomics; Genetic association studies; Transcriptomics; COVID-19; Immunogenetics

Lay Summary (French)

Lead
Au début du mois de décembre 2019, des cas de pneumonie d’origine inconnue ont été décrits dans la ville de Wuhan (Chine). L'agent rapidement identifié est un nouveau virus à ARN nommé «severe acute respiratory syndrome » coronavirus 2 (SARS-CoV-2). En quelques mois, l’infection à SARS-CoV-2 (COVID-19) s’est rapidement répandue, en causant près de 300'000 décès dans le monde (mai 2020). Les études initiales suggèrent que 20% des patients infectés nécessitent une hospitalisation, et 5% une prise en charge en réanimation, avec une mortalité estimée à 1-3%. Bien que les mesures de confinement mises en place dans plusieurs pays (y compris en Suisse) aient permis d'atténuer la première vague d'infection sans que les Services de santé ne soient débordés, l’évolution de la pandémie en l’absence de traitement spécifique est actuellement très préoccupante.
Lay summary

Bien que les manifestations les plus sévères de COVID-19 soient liées à certains facteurs de risques tels que l’âge élevé et/ou la présence de comorbidités, on ignore pourquoi certains individus présentent une maladie relativement peu symptomatique alors que d’autres patients nécessitent un support ventilatoire prolongé. Il est urgent de mieux comprendre les facteurs qui conduisent à une infection sévère, afin de pouvoir diriger les ressources médicales vers les individus à risque.

Dans ce projet, nous posons l’hypothèse que des variations dans des gènes du système immunitaire de l’hôte (polymorphismes) pourraient expliquer, du moins en partie, des différences individuelles dans la susceptibilité à l’infection. Nous proposons de séquencer l'ADN de patients atteints de COVID-19 afin de déterminer s'il existe de variants associés à une présentation particulièrement sévère de la maladie. L'identification des ces variants permettrait d'identifier des individus particulièrement à risque qui pourraient bénéficier en premier lieu de mesures préventives (mesures de protection, vaccins, prophylaxies) dès que de telles mesures sont disponibles.

Nous posons également l'hypothèse que le profil d'expression des gènes dans le sang (transcriptome) chez les patients infectés pourrait différer, et permettre de prédire l'évolution de la maladie. L'identification de profils de patients sévères avant la survenue de complications grave permettrait de faciliter la prise en charge des patients

Direct link to Lay Summary Last update: 17.05.2020

Responsible applicant and co-applicants

Project partner

Associated projects

Number Title Start Funding scheme
165954 Immunogenetics of Viral Infections - Focus on human herpesviruses (HHVs) 01.06.2016 Project funding (special)

Abstract

The world is currently facing a pandemic due to a new Coronavirus (SARS-CoV-2) that emerged as cause of severe pneumonia in the city of Wuhan (China) in December 2019. Coronavirus 2019 disease (COVID-19) touched > 300'000 individuals and caused > 13’000 deaths worldwide as of March 21, 2020. While adverse COVID-19 outcome relies on age (e.g. >65 y. o.) and presence of comorbidities, severe forms of the disease are increasingly reported among young and previously healthy individuals. In the absence of specific antiviral drugs, the sudden influx of hundreds of patients requiring respiratory support represents a major threat to health care systems, forcing numerous countries to declare the state of emergency, with unprecedented measures to slow down the spread of the outbreak. In this application, we propose two strategies to identify patients at risk to develop severe COVID-19 at an early stage of infection.AIM 1. To identify host genetic variants associated with severe COVID-19We will perform whole genome sequencing (WGS) in ~100 patients* with an “extreme” presentation of COVID-19, defined by the need for mechanical ventilation in young patients with =1 comorbid condition (see details in M&M). Samples will be collected from an ongoing study in Lausanne (collection has already started and CRF is in place) and extended to additional hospitals/centres in Switzerland. Of note, DNA can be obtained from recovered patients after infection.Participants of the CoLaus study (middle-aged individuals from Lausanne) will be used as controls. SNP-array data is already available for this cohort and we also will perform whole-exome sequencing on 250 individuals. Moreover, individuals from the genome aggregation database (gnomAD) will be used as an additional control group with data from more than 125’000 individuals for exomes and 15’000 for genomes. This will allow for a 4-steps analysis strate-gy, including a genome-wide association study (GWAS) for common variants (SNPs), a GWAS for rare variants, a gene burden testing approach and a pathway burden testing approach.AIM 2. To identify early transcriptomic signatures associated with severe COVID-19We will perform whole blood RNA sequencing (RNAseq) in 50 patients with an “extreme” presentation of COVID-19, as defined above, and 50 patients hospitalized with a milder course of infection (no ICU). Sampling will be per-formed at hospital entry, at day 7-9 from symptoms onset and day 12-15 from symptoms onset (for patients with prolonged hospitalisation).Analysis will include the identification of sets of differentially expressed (DE) genes, gene set enrichment analysis (GSEA) to identify gene ontology terms and gene pathways showing significant up-regulation or down-regulation, digital cell quantification (DCQ) to identify differences in cell type abundance, and machine learning methods to iden-tify panel of genes whose abundance could be used to predict the disease outcome.Relevance. Given the increasing number of patients requiring respiratory support, it is urgent to identify high-risk individuals as soon as possible, as those may be benefit from prevention strategies (such as isolation, vaccination and prophylaxis). This is particularly relevant given the absence of knowledge on the level and duration of protective immunity after a first infection with SARS-CoV-2. This study will also provide new insights on the pathogenesis of COVID-19, including mechanisms leading to the excessive inflammatory responses in severe cases*Investigators are submitting another funding application (reallocation of another project interrupded due to the pandemic) to support logistics (study nurses etc). If accepted, may also contribute to increase the number of extreme cases up to 125-150.
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