Functional microbiome deficits associated with ageing: chronological age-threshold

Composition of the gut microbiota changes during ageing, but questions remain about whether age is also associated with deficits in microbiome function and whether these changes occur sharply or progressively. The ability to define these deficits in populations of different ages may help determine a chronological age threshold at which deficits occur and subsequently identify innovative dietary strategies for active and healthy ageing. Here, active gut microbiota and associated metabolic functions were evaluated using shotgun proteomics in three well‐defined age groups consisting of 30 healthy volunteers, namely, ten infants, ten adults and ten elderly individuals. Samples from each volunteer at intervals of up to 6 months (n = 83 samples) were used for validation. Ageing gradually increases the diversity of gut bacteria that actively synthesize proteins, that is by 1.4‐fold from infants to elderly individuals. An analysis of functional deficits consistently identifies a relationship between tryptophan and indole metabolism and ageing (p < 2.8e−8). Indeed, the synthesis of proteins involved in tryptophan and indole production and the faecal concentrations of these metabolites are directly correlated (r2 > .987) and progressively decrease with age (r2 > .948). An age threshold for a 50% decrease is observed ca. 11–31 years old, and a greater than 90% reduction is observed from the ages of 34–54 years. Based on recent investigations linking tryptophan with abundance of indole and other “healthy” longevity molecules and on the results from this small cohort study, dietary interventions aimed at manipulating tryptophan deficits since a relatively “young” age of 34 and, particularly, in the elderly are recommended.
S.R. was recipient of a postdoctoral “Sara Borrell” contract from the Instituto de Salud Carlos III. This work was funded by grants SAF2015‐65878‐R and RTI2018‐095166‐B‐I00 from the Ministry of Science, Innovation and Universities with the cofunds of the European Regional Development Fund (ERDF) and the Agencia Estatal de Investigación (AEI), grant PIE14/00045 from the Instituto de Salud Carlos III, grant AC17/00022 from the Instituto de Salud Carlos III and Fundación Agencia Española contra el Cáncer (AECC) within the ERA NET TRANSCAN‐2, grant 2017‐1485 from the AECC and grant Prometeo/2018/A/133 from the Generalitat Valenciana. M.F. acknowledges the support of BIO2017‐85522‐R, from the Ministry of Science, Innovation and Universities, with the cofunds of the ERDF and the Agencia Estatal de Investigación (AEI). The proteomic analysis was performed in the Proteomics Facility of The Spanish National Center for Biotechnology (CNB‐CSIC) that belongs to ProteoRed, PRB3‐ISCIII, supported by grant PT17/0019. The funding bodies did not have a role in the design or conduct of the study, the analysis and interpretation of the results, the writing of the report, or the decision to publish.