Role of the Microbiota in the Evolution of the SARS-CoV-2 Disease,COVID-19, in Hospitalized Patients (MicrobioCOVID)
Role of the Microbiota in the Evolution of the SARS-CoV-2 Disease in Hospitalized Patients
Patients hospitalized for COVID-19 may need intensive care (e.g. mechanical ventilation) during hospitalization. Some risk factors are already known but better targeting of such patients is still needed, at least because existing risk factors are not strong enough to provide an accurate prediction. Care organization would benefit for such a predictive tool.
Oropharyngeal and gut microbiota could potentially fill a significant gap in predictive performances. The investigators therefore propose to sample 200 patients (oropharyngeal and rectal swab) admitted in infectious disease department at Bichat Hospital and at high risk of needing intensive care during hospitalization. The investigators plan to perform metagenomic sequencing and bioinformatic analysis of these samples to characterize the diversity of bacterial species present in the oropharynx and the gut and to identify new factors associated with the need for intensive care. Aside metagenomic analyses, The investigators will perform semi-quantitative cultures of the oropharyngeal and gut microbiota to identify and quantify pathogens in order to predict the risk of bacterial infections in COVD-19 patients.
For patients transferred in intensive care unit, The investigators will to perform another series of samples to better characterize the evolution of microbiota during mechanical ventilation and identify factors associated with the risk of developing a ventilator-associated pneumonia.
Microbiota data will be considered together with the host genotype, the viral sequence and a deep immunological profiling to identify the main determinants of the evolution toward severity of COVID-19.
研究概览
地位
条件
详细说明
Patients hospitalized for COVID-19 may need intensive care (e.g. mechanical ventilation) during hospitalization. Some risk factors are already known (e.g. sex, comorbidities, initial clinical presentation inflammatory cytokines), but better targeting of such patients is still needed, at least because existing risk factors are not strong enough to provide an accurate prediction. Care organization would benefit for such a predictive tool.
Oropharyngeal and gut microbiota could fill a significant gap in predictive performances. The investigators therefore propose to take advantage of the French-COVID cohort and sample 200 patients (oropharyngeal and rectal swab) admitted in infectious disease department at Bichat Hospital and at high risk of needing intensive care during hospitalization. The investigators plan to perform metagenomic sequencing and bioinformatic analysis of these samples to characterize the diversity of bacterial species present in the oropharynx and the gut and to identify new factors associated with the need for intensive care. Aside metagenomic analyses, The investigators will perform semi-quantitative cultures of the oropharyngeal and gut microbiota to identify and quantify pathogens in order to predict the risk of bacterial infections in COVD-19 patients.
The genetic determinants of the host (the patient) could also be predictive of the severity of the disease and so does the immunological response to the COVID-19. Likewise, it has been suggested that certain mutations (notably the D614G mutation) of the viral sequence could be associated with the infectivity of the virus.
In addition to the direct role of the microbiota in the course of infection, the immune characteristics specific to the host, by themselves or in interaction with the microbiota, could play an important role in the progression of the disease.
This project focuses on the clinical characterization of COVID-19 and its evolution, as well as disease management.
The research focuses on 4 main areas:
- Characterization of the oropharyngeal and intestinal microbiota of patients with COVID-19
- Characteristics of the host (genotype)
- Immune characteristics of the host
- Characteristics of the SARS-CoV-2 viral genome
For patients transferred in intensive care unit, The investigators will to perform another series of samples to better characterize the evolution of microbiota during mechanical ventilation and identify factors associated with the risk of developing a ventilator-associated pneumonia.
研究类型
注册 (预期的)
联系人和位置
学习联系方式
- 姓名:Etienne Ruppé
- 电话号码:33 1 40 25 80 00
- 邮箱:etienne.ruppe@aphp.fr
研究联系人备份
- 姓名:Xavier Lescure
- 电话号码:33 1 40 25 80 00
- 邮箱:xavier.lescure@aphp.fr
学习地点
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Paris、法国
- 招聘中
- LESCURE
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接触:
- xavier lescure
- 邮箱:xavier.lescure@aphp.fr
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参与标准
资格标准
适合学习的年龄
接受健康志愿者
有资格学习的性别
取样方法
研究人群
描述
Inclusion Criteria:
- Adult patient with documented SARS-CoV-2 infection requiring hospitalization.
Exclusion Criteria:
- Lack of consent
- Patients hospitalized in an intensive care unit
- Patient under guardianship or curatorship
学习计划
研究是如何设计的?
设计细节
队列和干预
团体/队列 |
干预/治疗 |
---|---|
Patients hospitalized for COVID-19
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analysis of oropharyngeal and intestinal microbiota
analysis of a part of host genotype
analysis of host immune factors
analysis of viral sequence
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研究衡量的是什么?
主要结果指标
结果测量 |
措施说明 |
大体时间 |
---|---|---|
Identify risk factors associated with severe forms of COVID-19 requiring transfer to ICU
大体时间:day 14
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The main endpoint is the indication of worsening of the general condition requiring transfer to ICU
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day 14
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次要结果测量
结果测量 |
措施说明 |
大体时间 |
---|---|---|
Link between the composition of the gut microbiota and admission to intensive care
大体时间:3 months
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Composition of the gut microbiota on admission to intensive care to predict the outcome of severe COVID-19 in patients transferred to the ICU (subgroup analysis)
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3 months
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Predictive performance of semi-quantitative culture and rapid metagenomic evaluation
大体时间:3 months
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Predictive performance of semi-quantitative culture and rapid metagenomic evaluation of the oropharyngeal microbiota to predict the occurrence of VAP in patients admitted to an ICU and mechanically ventilated (subgroup analysis).
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3 months
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合作者和调查者
研究记录日期
研究主要日期
学习开始 (实际的)
初级完成 (实际的)
研究完成 (预期的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
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