German Cancer Research Center (DKFZ), Research Division Microbiome and Cancer, Heidelberg, Germany.
Vale do Rio dos Sinos University (UNISINOS), Sao Leopoldo, Brazil.
Clin Infect Dis. 2022 Aug 24;75(1):e1063-e1071. doi: 10.1093/cid/ciab902.
At the entry site of respiratory virus infections, the oropharyngeal microbiome has been proposed as a major hub integrating viral and host immune signals. Early studies suggested that infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are associated with changes of the upper and lower airway microbiome, and that specific microbial signatures may predict coronavirus disease 2019 (COVID-19) illness. However, the results are not conclusive, as critical illness can drastically alter a patient's microbiome through multiple confounders.
To study oropharyngeal microbiome profiles in SARS-CoV-2 infection, clinical confounders, and prediction models in COVID-19, we performed a multicenter, cross-sectional clinical study analyzing oropharyngeal microbial metagenomes in healthy adults, patients with non-SARS-CoV-2 infections, or with mild, moderate, and severe COVID-19 (n = 322 participants).
In contrast to mild infections, patients admitted to a hospital with moderate or severe COVID-19 showed dysbiotic microbial configurations, which were significantly pronounced in patients treated with broad-spectrum antibiotics, receiving invasive mechanical ventilation, or when sampling was performed during prolonged hospitalization. In contrast, specimens collected early after admission allowed us to segregate microbiome features predictive of hospital COVID-19 mortality utilizing machine learning models. Taxonomic signatures were found to perform better than models utilizing clinical variables with Neisseria and Haemophilus species abundances as most important features.
In addition to the infection per se, several factors shape the oropharyngeal microbiome of severely affected COVID-19 patients and deserve consideration in the interpretation of the role of the microbiome in severe COVID-19. Nevertheless, we were able to extract microbial features that can help to predict clinical outcomes.
呼吸道病毒感染的入口部位，口咽微生物组被认为是整合病毒和宿主免疫信号的主要枢纽。早期研究表明，严重急性呼吸综合征冠状病毒 2（SARS-CoV-2）感染与上、下呼吸道微生物组的变化有关，特定的微生物特征可能预测 2019 年冠状病毒病（COVID-19）。然而，结果并不确定，因为严重疾病可能通过多种混杂因素剧烈改变患者的微生物组。
为了研究 SARS-CoV-2 感染、COVID-19 中的临床混杂因素和预测模型中的口咽微生物组谱，我们进行了一项多中心、横断面临床研究，分析了健康成年人、非 SARS-CoV-2 感染患者以及轻度、中度和重度 COVID-19 患者的口咽微生物宏基因组（n=322 名参与者）。
与轻度感染相比，因中度或重度 COVID-19 住院的患者表现出微生物群落失调的特征，而在接受广谱抗生素治疗、接受有创机械通气或在住院时间延长时采样的患者中，这种失调特征更为显著。相比之下，在入院后早期采集的标本允许我们利用机器学习模型将具有预测医院 COVID-19 死亡率的微生物组特征进行分类。分类学特征的表现优于利用临床变量的模型，其中奈瑟菌属和嗜血杆菌属的丰度是最重要的特征。
除感染本身外，还有几个因素影响严重 COVID-19 患者的口咽微生物组，在解释微生物组在严重 COVID-19 中的作用时需要考虑这些因素。尽管如此，我们还是能够提取出有助于预测临床结果的微生物特征。
