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Persons infected with Severe Acute Respiratory Syndrome (SARS) SARS-CoV-2 vary in severity from being asymptomatic to having fever, cough, sore throat, general weakness and fatigue and muscular pain and in the most severe cases, severe pneumonia, acute respiratory distress syndrome and sepsis potentially leading to death. Predictive markers of clinical worsening after admission are lacking. COVID-19 immunopathogenesis and relevant therapeutic strategies are still under investigation.
Although viral shedding peaks during the first week of symptoms, reports show that clinical deterioration often coincides with the development of host antiviral immune responses. The inflammatory response to SARS-CoV-2 infection may underpin COVID-19 pathogenesis leading to aberrant and excessive immune responses that may enter the pulmonary circulation in large numbers and play an immune damaging role causing lung functional disability resulting in clinical worsening. Therapeutic strategies using corticosteroids or biotherapies targeting IL-6 may be valuable in some patients. Based on a better understanding of COVID-19 immunopathogenesis, the identification of predictive biomarkers early in the disease process would be of outstanding interest to tailor prompt therapeutic interventions.
On these bases, the present project aims to unravel, using innovative integrated multimodal immunological approaches, immunologic predictive markers by finely characterizing from their admission innate and adaptive immune responses in two well described cohorts of COVID-19 patients that are being collected in Toulouse (COVID-BioToul) and Bordeaux (COLCOV-19 BX).Those two biological cohorts are connected with two clinical cohorts in Toulouse and Bordeaux in order to have a very well defined population of COVID-19 patients and their clinical outcome. In both cohorts, investigators harvest and cryopreserve biological samples, including plasma and peripheral blood mononuclear cells (PBMCs), on admission and longitudinally from patients evolving or not toward severe forms of the disease in Bordeaux and Toulouse University Hospitals and will allow to investigate primary and secondary objectives. Moreover in the two centers, there are also two clinical outpatients cohorts of healthcare workers attending dedicated clinics in the frame of their surveillance medical program, which constitute groups of patients with benign forms of COVID-19.
The primary objective of IMMUNOMARK-COV is to define an applicable immune signature predicting clinical worsening on COVID-19 patient admission in order to help physicians to take informed therapeutic decisions able to modify early the course of the disease.
Secondary objectives are:
Identification of early predictive biomarkers of worsening of COVID-19 patients is of paramount importance. This goal is expected to be achieved through the fine analysis of circulating immune effectors, and their dynamics, in categories of patients with very different clinical outcomes.
To date, management of clinical worsening relies mainly on supportive care in ICU, leading to prolonged stay and saturation of facilities. Earlier therapeutic intervention based on identification of robust predictive biomarkers should:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| hospitalized patients | very well-defined population of COVID-19 patients with the following outcomes: Patients with severe disease requiring on admission ICU management for SARS, Non-severe hospitalized patients with secondary clinical worsening requiring ICU management, Non-severe hospitalized patients without clinical worsening requiring ICU management. |
| |
| healthcare workers | mildly symptomatic patients among healthcare workers attending outpatient dedicated clinics will be recruited |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Blood collection on admission and longitudinally | Biological | Samples already collected on admission (day 0) and longitudinally (day 4, 8 12 and in discharge) |
|
| Measure | Description | Time Frame |
|---|---|---|
| Immune signature on admission : phenotypic profile of blood T-cells | Immune signature will be compared between COVID-19 patients according to their clinical characteristics and outcome, together with SARS-CoV2 viral shedding (known for every patient in the cohort) on samples harvested on admission: a phenotypic profiling of blood T-cells by multicolor FACS analysis (using 30+ color panels analyzed by multiparametric flow cytometry) assessing T cell subsets (classical CD4 or CD8 T-cells as well as unconventional gdT-cells and regulatory T cells) through the expression of a wide range of surface and intracellular markers. | Day 0 |
| Immune signature on admission : inflammatory cytokines | Immune signature will be compared between COVID-19 patients according to their clinical characteristics and outcome, together with SARS-CoV2 viral shedding (known for every patient in the cohort) on samples harvested on admission: An analysis on plasma samples of concentration of a wide range of inflammatory cytokines such as IFNa, IFNb and IL-6. | Day 0 |
| Measure | Description | Time Frame |
|---|---|---|
| Dynamics of cellular immunity: CD4 and CD8 T cells | On samples harvested longitudinally from patients, analysis of the relative magnitude and dynamic and polyfunctional profile of SARS-CoV-2 specific CD8 and CD4 T cell responses by analyzing the capacity of T cells to produce simultaneously a variety of cytokines such as IFNa, IFNb and IL-6, will be performed. | Day 0, Day 4, Day 8, Day 12, Day 30 (or in discharge) |
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Inclusion Criteria:
For COVID-19 hospitalized patients
Exclusion Criteria:
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Patients hospitalized or healthy workers for COVID-19
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| Name | Affiliation | Role |
|---|---|---|
| Pierre DELOBEL, MD PhD | University Hospital, Toulouse | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University Hospital Bordeaux | Bordeau | 33000 | France | |||
| University Hospital Toulouse |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34051147 | Result | Kreutmair S, Unger S, Nunez NG, Ingelfinger F, Alberti C, De Feo D, Krishnarajah S, Kauffmann M, Friebel E, Babaei S, Gaborit B, Lutz M, Jurado NP, Malek NP, Goepel S, Rosenberger P, Haberle HA, Ayoub I, Al-Hajj S, Nilsson J, Claassen M, Liblau R, Martin-Blondel G, Bitzer M, Roquilly A, Becher B. Distinct immunological signatures discriminate severe COVID-19 from non-SARS-CoV-2-driven critical pneumonia. Immunity. 2021 Jul 13;54(7):1578-1593.e5. doi: 10.1016/j.immuni.2021.05.002. Epub 2021 May 9. |
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| ID | Term |
|---|---|
| D000086382 | COVID-19 |
| ID | Term |
|---|---|
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
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| Blood collection on their first consultation and 10 to 14 days later | Biological | Samples already collected on consultation (D0) and 14 days later |
|
| Dynamics of cellular immunity: gd T cells | On samples harvested longitudinally from patients, dynamics of gd T cells will be performed. | Day 0, Day 4, Day 8, Day 12, Day 30 (or in discharge) |
| Dynamics of cellular immunity: T cell transcriptomic analysis | On samples harvested longitudinally from patients, transcriptomic analysis of different types of T cells will be performed. | Day 0, Day 4, Day 8, Day 12, Day 30 (or in discharge) |
| Dynamics of cellular immunity: humoral immunity | On samples harvested longitudinally from patients, humoral immunity will be performed. | Day 0, Day 4, Day 8, Day 12, Day 30 (or in discharge) |
| Toulouse |
| 31059 |
| France |
| D014777 |
| Virus Diseases |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |