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

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.