Coronavirus Studied by Metagenomics in ARDS COVID-19 Patients

COVID-19 Clinical Trial

— COMETS  

Official title:

Characterization and Prognostic Impact of Inflammatory Responses by Host Transcriptomics and Co-infection by Metagenomics in Patients With ARDS COVID-19 in Intensive Care

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT04516486
• Other study ID #: APHP200418
• Status: Active, not recruiting
• Start date: March 9, 2020
• Est. completion date: December 31, 2020

Study information

• Verified date: June 2020
• Source: Assistance Publique - Hôpitaux de Paris
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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). ARDS is usually associated with a mortality of around 40%, but this rate reaches 61% in patients infected with SARS-CoV-2. 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%). 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). 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.

Description:

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. 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.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 180
• Est. completion date: December 31, 2020
• Est. primary completion date: May 24, 2020
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Patient admitted to intensive care for ARDS (Berlin definition) documented at SARS-CoV-2

• Major patient (age = 18 years)

• Collection of the non-opposition of the patient or his support person, family member or close friend (newsletter)

Exclusion Criteria:

• Minor patient

• Refusal to participate in the study

• Patient protected by law

• Prisoner

Related Conditions & MeSH terms

• Acute Lung Injury
• COVID-19
• Respiratory Distress Syndrome, Adult
• Respiratory Distress Syndrome, Newborn

Intervention

Other:
• retrospective metagenomics on clinical samples collected during hospitalization
Massive sequencing of respiratory samples (restrospective)

Locations

Country	Name	City	State
France	CHU Henri Mondor	Créteil

Sponsors (1)

Lead Sponsor	Collaborator
Assistance Publique - Hôpitaux de Paris

Country where clinical trial is conducted

France, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Identify two endotypes (hyper-inflammatory and co-infections) and quantify their prognostic value in terms of short-term mortality (Day 28) in patients treated for ARDS infected with SARS-Cov2.	Unsupervised Transcriptomic analysis to explore the presence of 2 different groups of patients in the cohort.	Day 0 to Day 28 (longitudinal study)
Secondary	Nature of viral, bacterial and fungal co-infections in the different clusters identified	Shotgun Metagenomics analysis of respiratory samples to explore viruses, bacteria, fungi, parasites in relation with severity of the disease	Day 0 to Day 28
Secondary	Comparison of SARS CoV-2 viral replication dynamics in the different clusters identified	Quantification based on metagenomics through time	Day 0 to Day 28
Secondary	4. Characterization of the viral genetic determinants selected over time in the different clusters identified	Viral genomic comparison and machine learning to assess the role of the mutations (quasispecies) in the severity of the disease	Day 0 to Day 28