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Article: Human skin, oral, and gut microbiomes predict chronological age

TitleHuman skin, oral, and gut microbiomes predict chronological age
Authors
Issue Date2020
Citation
mSystems, 2020, v. 5, n. 1, article no. e00630-19 How to Cite?
AbstractHuman gut microbiomes are known to change with age, yet the relative value of human microbiomes across the body as predictors of age, and prediction robustness across populations is unknown. In this study, we tested the ability of the oral, gut, and skin (hand and forehead) microbiomes to predict age in adults using random forest regression on data combined from multiple publicly available studies, evaluating the models in each cohort individually. Intriguingly, the skin microbiome provides the best prediction of age (mean ± standard deviation, 3.8 ± 0.45 years, versus 4.5 ± 0.14 years for the oral microbiome and 11.5 ± 0.12 years for the gut microbiome). This also agrees with forensic studies showing that the skin microbiome predicts postmortem interval better than microbiomes from other body sites. Age prediction models constructed from the hand microbiome generalized to the forehead and vice versa, across cohorts, and results from the gut microbiome generalized across multiple cohorts (United States, United Kingdom, and China). Interestingly, taxa enriched in young individuals (18 to 30 years) tend to be more abundant and more prevalent than taxa enriched in elderly individuals (>60 yrs), suggesting a model in which physiological aging occurs concomitantly with the loss of key taxa over a lifetime, enabling potential microbiome-targeted therapeutic strategies to prevent aging. IMPORTANCE Considerable evidence suggests that the gut microbiome changes with age or even accelerates aging in adults. Whether the age-related changes in the gut microbiome are more or less prominent than those for other body sites and whether predictions can be made about a person’s age from a microbiome sample remain unknown. We therefore combined several large studies from different countries to determine which body site’s microbiome could most accurately predict age. We found that the skin was the best, on average yielding predictions within 4 years of chronological age. This study sets the stage for future research on the role of the microbiome in accelerating or decelerating the aging process and in the susceptibility for age-related diseases.
Persistent Identifierhttp://hdl.handle.net/10722/311484
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHuang, Shi-
dc.contributor.authorHaiminen, Niina-
dc.contributor.authorCarrieri, Anna Paola-
dc.contributor.authorHu, Rebecca-
dc.contributor.authorJiang, Lingjing-
dc.contributor.authorParida, Laxmi-
dc.contributor.authorRussell, Baylee-
dc.contributor.authorAllaband, Celeste-
dc.contributor.authorZarrinpar, Amir-
dc.contributor.authorVázquez-Baeza, Yoshiki-
dc.contributor.authorBelda-Ferre, Pedro-
dc.contributor.authorZhou, Hongwei-
dc.contributor.authorKim, Ho Cheol-
dc.contributor.authorSwafford, Austin D.-
dc.contributor.authorKnight, Rob-
dc.contributor.authorXu, Zhenjiang Zech-
dc.date.accessioned2022-03-22T11:54:03Z-
dc.date.available2022-03-22T11:54:03Z-
dc.date.issued2020-
dc.identifier.citationmSystems, 2020, v. 5, n. 1, article no. e00630-19-
dc.identifier.urihttp://hdl.handle.net/10722/311484-
dc.description.abstractHuman gut microbiomes are known to change with age, yet the relative value of human microbiomes across the body as predictors of age, and prediction robustness across populations is unknown. In this study, we tested the ability of the oral, gut, and skin (hand and forehead) microbiomes to predict age in adults using random forest regression on data combined from multiple publicly available studies, evaluating the models in each cohort individually. Intriguingly, the skin microbiome provides the best prediction of age (mean ± standard deviation, 3.8 ± 0.45 years, versus 4.5 ± 0.14 years for the oral microbiome and 11.5 ± 0.12 years for the gut microbiome). This also agrees with forensic studies showing that the skin microbiome predicts postmortem interval better than microbiomes from other body sites. Age prediction models constructed from the hand microbiome generalized to the forehead and vice versa, across cohorts, and results from the gut microbiome generalized across multiple cohorts (United States, United Kingdom, and China). Interestingly, taxa enriched in young individuals (18 to 30 years) tend to be more abundant and more prevalent than taxa enriched in elderly individuals (>60 yrs), suggesting a model in which physiological aging occurs concomitantly with the loss of key taxa over a lifetime, enabling potential microbiome-targeted therapeutic strategies to prevent aging. IMPORTANCE Considerable evidence suggests that the gut microbiome changes with age or even accelerates aging in adults. Whether the age-related changes in the gut microbiome are more or less prominent than those for other body sites and whether predictions can be made about a person’s age from a microbiome sample remain unknown. We therefore combined several large studies from different countries to determine which body site’s microbiome could most accurately predict age. We found that the skin was the best, on average yielding predictions within 4 years of chronological age. This study sets the stage for future research on the role of the microbiome in accelerating or decelerating the aging process and in the susceptibility for age-related diseases.-
dc.languageeng-
dc.relation.ispartofmSystems-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleHuman skin, oral, and gut microbiomes predict chronological age-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1128/mSystems.00630-19-
dc.identifier.pmid32047061-
dc.identifier.pmcidPMC7018528-
dc.identifier.scopuseid_2-s2.0-85079233114-
dc.identifier.volume5-
dc.identifier.issue1-
dc.identifier.spagearticle no. e00630-19-
dc.identifier.epagearticle no. e00630-19-
dc.identifier.eissn2379-5077-
dc.identifier.isiWOS:000518855000017-

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