Characterization of inflammatory responses by host transcriptomics and coinfections by metagenomics in order to understand the excess mortality of patients with COVID-19 with ARDS in intensive care – COMETS

Pandemic SARS-CoV-2 (COVID-19) respiratory infection is responsible for more than 4,000 deaths, mainly (67%) secondary to acute respiratory distress syndromes (ARDS) (Yang 2020) . ARDS is usually associated with a mortality of around 40% (Gilbert 2018), but this rate reaches 61% in patients infected with SARS-CoV-2 (Yang 2020). Two endotypes have been described in patients with ARDS: one, hyper-inflammatory, associated with very high mortality (51%); the second, slightly inflammatory (immunoparalysis), associated with much lower mortality (19%) (Calfee 2014). In COVID-19 patients, distinct immune response profiles have also been observed. Some patients present deep lymphopenia and/or prolonged viral excretions associated with more frequent occurrence of co-infections (+ 29% of virus, + 23% of bacteria, + 10% of fungi) (Zhang 2020). The latter group may be at higher risk in terms of mortality. The intensity of the inflammatory response and / or microbial coinfections therefore appear as risk factors for severity and mortality in patients infected with SARS-CoV-2 which determine the course of the disease. To adapt early optimal therapeutic management to each forms of the disease, it is essential to be able to characterize these profiles on the microbiological and inflammatory level.
With a committed network of 6 intensive-care units across eastern and northern Ile-de-France, 180 patients with ARDS and infected with SARS-CoV-2 are being enrolled. For these patients, a nasopharyngeal swab is collected at inclusion; followed by a new nasopharyngeal swab and a deep respiratory sample once a week, until D28, for an exploration of co-infections and for monitoring the viral load of SARS-CoV-2. The rest of each of these samples are collected for the study. In parallel, the clinical data usually collected in the context of intensive care will be collected on a CRF. They will allow to calculate risk scores such as SOFA.
Clinical metagenomics is a technique that has the ability to explore the host's inflammatory response by transcriptomics and the co-infection(s) of all microorganisms. For this, an accredited method according to standard 15189 and used in diagnostic routine for the exploration of complex infections will be used (Rodriguez 2019). In practice, the samples will be pre-extracted (chemical, enzymatic and mechanical lysis) then extracted using QiaSymphony (Qiagen). The library will be prepared jointly by Nextera XT kit for DNA and Stranded TruSeq Total RNA (Illumina) then sequenced by NovaSeq (Illumina). The metagenomic and transcriptomic analysis will be performed by our MetaMIC software, supplemented with a specific module recently added for the analysis of SARS-CoV-2 genetic variability and its dynamics over time. Finally, an unsupervised data-mining analysis will be carried out to establish the presence of the "hyperinflammatory" and "immunoparalysis" groups, then allow the analysis of the determinants guiding their clustering. Each group will be analyzed according to its clinical, biological and virological data to determine specific prognostic markers.
The proposed project will therefore comprehensively assess the dynamics of SARS-CoV-2 infection, the inflammatory profile and the microbiological documentation of COVID-19 patients in ARDS by metagenomics / transcriptomics with the aim of detecting profiles of patients at higher risk, to understand the mechanisms of severe forms of the disease and to allow a more precise and earlier evaluation of the prognosis, as well as an adaptation of the management.