The relevance of the human oral microbiome to our understanding of human health has grown in recent years as microbiome studies continue to develop. Given the links of the oral cavity with the digestive, respiratory and circulatory systems, the composition of the oral microbiome is relevant beyond just oral health, impacting systemic processes across the body. However, we still have a very limited understanding about intrinsic and extrinsic factors that shape the composition of the healthy oral microbiome. ...
The relevance of the human oral microbiome to our understanding of human health has grown in recent years as microbiome studies continue to develop. Given the links of the oral cavity with the digestive, respiratory and circulatory systems, the composition of the oral microbiome is relevant beyond just oral health, impacting systemic processes across the body. However, we still have a very limited understanding about intrinsic and extrinsic factors that shape the composition of the healthy oral microbiome. Here, we followed a citizen-science approach to assess the relative impact on the oral microbiome of selected biological, social, and lifestyle factors in 1648 Spanish individuals. We found that the oral microbiome changes across age, with middle ages showing a more homogeneous composition, and older ages showing more diverse microbiomes with increased representation of typically low abundance taxa. By measuring differences within and between groups of individuals sharing a given parameter, we were able to assess the relative impact of different factors in driving specific microbial compositions. Chronic health disorders present in the analyzed population were the most impactful factors, followed by smoking and the presence of yeasts in the oral cavity. Finally, we corroborate findings in the literature that relatives tend to have more similar oral microbiomes, and show for the first time a similar effect for classmates. Multiple intrinsic and extrinsic factors jointly shape the oral microbiome. Comparative analysis of metabarcoding data from a large sample set allows us to disentangle the individual effects.
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