Post by Nadica (She/Her) on Aug 19, 2024 2:05:34 GMT
Adult outpatients with long COVID infected with SARS-CoV-2 Omicron variant. Part 1: Oral microbiota alterations - Published Aug 13, 2024
Abstract
Background:
Many individuals experience long COVID after SARS-CoV-2 infection. As microbiota can influence health, it may change with COVID-19. This study investigated differences in oral microbiota between COVID-19 patients with and without long COVID.
Methods:
Based on a prospective follow-up investigation, this nested case-control study evaluated the differences in oral microbiota in individuals with and without long COVID (Symptomatic and Asymptomatic groups), which were assessed by 16S rRNA sequencing on tongue coating samples. A predictive model was established using machine learning based on specific differential microbial communities.
Results:
One-hundred-and-eight patients were included (n=54 Symptomatic group). The Symptomatic group had higher Alpha diversity indices (observed_otus, Chao1, Shannon, and Simpson indices), differences in microbial composition (Beta diversity), and microbial dysbiosis with increased diversity and relative abundance of pathogenic bacteria. Marker bacteria (c__Campylobacterota, o__Coriobacteriales, o__Pseudomonadales, and o__Campylobacterales) were associated with long COVID by linear discriminant analysis effect size and receiver operating characteristic curves (AUC 0.821).
Conclusion:
There were distinct variations in oral microbiota between COVID-19 patients with and without long COVID. Changes in oral microbiota may indicate long COVID.
Abstract
Background:
Many individuals experience long COVID after SARS-CoV-2 infection. As microbiota can influence health, it may change with COVID-19. This study investigated differences in oral microbiota between COVID-19 patients with and without long COVID.
Methods:
Based on a prospective follow-up investigation, this nested case-control study evaluated the differences in oral microbiota in individuals with and without long COVID (Symptomatic and Asymptomatic groups), which were assessed by 16S rRNA sequencing on tongue coating samples. A predictive model was established using machine learning based on specific differential microbial communities.
Results:
One-hundred-and-eight patients were included (n=54 Symptomatic group). The Symptomatic group had higher Alpha diversity indices (observed_otus, Chao1, Shannon, and Simpson indices), differences in microbial composition (Beta diversity), and microbial dysbiosis with increased diversity and relative abundance of pathogenic bacteria. Marker bacteria (c__Campylobacterota, o__Coriobacteriales, o__Pseudomonadales, and o__Campylobacterales) were associated with long COVID by linear discriminant analysis effect size and receiver operating characteristic curves (AUC 0.821).
Conclusion:
There were distinct variations in oral microbiota between COVID-19 patients with and without long COVID. Changes in oral microbiota may indicate long COVID.