Host-microbiome associations in saliva predict COVID-19 severity.
Hend AlqaderiKhaled AltabtbaeiJosh L EspinozaSaadoun Bin HasanMohammad AlghounaimAbdullah AlawadyAbdullah AltabtabaeSarah AlJamaanSriraman DevarajanTahreer AlShammariMohammed Ben EidMichele MatsuokaHyesun JangChristopher L DupontMarcelo O FreirePublished in: PNAS nexus (2024)
Established evidence indicates that oral microbiota plays a crucial role in modulating host immune responses to viral infection. Following severe acute respiratory syndrome coronavirus 2, there are coordinated microbiome and inflammatory responses within the mucosal and systemic compartments that are unknown. The specific roles the oral microbiota and inflammatory cytokines play in the pathogenesis of coronavirus disease 2019 (COVID-19) are yet to be explored. Here, we evaluated the relationships between the salivary microbiome and host parameters in different groups of COVID-19 severity based on their oxygen requirement. Saliva and blood samples ( n = 80) were collected from COVID-19 and from noninfected individuals. We characterized the oral microbiomes using 16S ribosomal RNA gene sequencing and evaluated saliva and serum cytokines and chemokines using multiplex analysis. Alpha diversity of the salivary microbial community was negatively associated with COVID-19 severity, while diversity increased with health. Integrated cytokine evaluations of saliva and serum showed that the oral host response was distinct from the systemic response. The hierarchical classification of COVID-19 status and respiratory severity using multiple modalities separately (i.e. microbiome, salivary cytokines, and systemic cytokines) and simultaneously (i.e. multimodal perturbation analyses) revealed that the microbiome perturbation analysis was the most informative for predicting COVID-19 status and severity, followed by the multimodal. Our findings suggest that oral microbiome and salivary cytokines may be predictive of COVID-19 status and severity, whereas atypical local mucosal immune suppression and systemic hyperinflammation provide new cues to understand the pathogenesis in immunologically compromised populations.
Keyphrases
- coronavirus disease
- sars cov
- respiratory syndrome coronavirus
- microbial community
- immune response
- public health
- machine learning
- high throughput
- climate change
- single cell
- deep learning
- social media
- toll like receptor
- genome wide
- chronic pain
- copy number
- nucleic acid
- drug induced
- inflammatory response
- respiratory tract