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Human Skin, Oral, and Gut Microbiomes Predict Chronological Age.
Huang, Shi; Haiminen, Niina; Carrieri, Anna-Paola; Hu, Rebecca; Jiang, Lingjing; Parida, Laxmi; Russell, Baylee; Allaband, Celeste; Zarrinpar, Amir; Vázquez-Baeza, Yoshiki; Belda-Ferre, Pedro; Zhou, Hongwei; Kim, Ho-Cheol; Swafford, Austin D; Knight, Rob; Xu, Zhenjiang Zech.
Afiliación
  • Huang S; Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, La Jolla, California, USA.
  • Haiminen N; UCSD Health Department of Pediatrics, University of California, San Diego, La Jolla, California, USA.
  • Carrieri AP; IBM T. J. Watson Research Center, Yorktown Heights, New York, USA.
  • Hu R; IBM Research UK, The Hartree Centre, Warrington, United Kingdom.
  • Jiang L; Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, La Jolla, California, USA.
  • Parida L; Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, La Jolla, California, USA.
  • Russell B; Division of Biostatistics, University of California, San Diego, La Jolla, California, USA.
  • Allaband C; IBM T. J. Watson Research Center, Yorktown Heights, New York, USA.
  • Zarrinpar A; UCSD Division of Gastroenterology, University of California, San Diego, La Jolla, California, USA.
  • Vázquez-Baeza Y; Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, California, USA.
  • Belda-Ferre P; UCSD Division of Gastroenterology, University of California, San Diego, La Jolla, California, USA.
  • Zhou H; VA San Diego Health Care, La Jolla, California, USA.
  • Kim HC; Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, La Jolla, California, USA.
  • Swafford AD; UCSD Health Department of Pediatrics, University of California, San Diego, La Jolla, California, USA.
  • Knight R; Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, La Jolla, California, USA.
  • Xu ZZ; UCSD Health Department of Pediatrics, University of California, San Diego, La Jolla, California, USA.
mSystems ; 5(1)2020 Feb 11.
Article en En | MEDLINE | ID: mdl-32047061
ABSTRACT
Human 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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: MSystems Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: MSystems Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos