A metabolic signature predicts biological age in mice

2014-08-29

A metabolic signature predicts biological age in mice
metabolism

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Abstract
Our understanding of the mechanisms by which aging is produced is still very limited. Here, we have determined the sera metabolite profile of 117 wild-type mice of different genetic backgrounds ranging from 8 to 129 weeks of age. This has allowed us to define a robust metabolomic signature and a derived metabolomic score that reliably/accurately predicts the age of wild-type mice. In the case of telomerase-deficient mice, which have a shortened lifespan, their metabolomic score predicts older ages than expected. Conversely, in the case of mice that overexpress telomerase, their metabolic score corresponded to younger ages than expected. Importantly, telomerase reactivation late in life by using a TERT-based gene therapy recently described by us significantly reverted the metabolic profile of old mice to that of younger mice, further confirming an anti-aging role for telomerase. Thus, the metabolomic signature associated with natural mouse aging accurately predicts aging produced by telomere shortening, suggesting that natural mouse aging is in part produced by presence of short telomeres. These results indicate that the metabolomic signature is associated with the biological age rather than with the chronological age. This constitutes one of the first aging-associated metabolomic signatures in a mammalian organism.

Some Notes
de?ne a robust metabolomic signature and a
derived metabolomic score that reliably/accurately predicts the
age of wild-type mice
recently described by us signi?cantly reverted the metabolic
pro?le of old mice to that of younger mice
The age biomarkers identi?ed here include lipids and other small
molecules such as creatine, methionine, and uric acid. Whether these
biomarkers play a role in aging or are due to secondary phenomena will
require further investigation
strong evidence that
telomere loss signi?cantly contributes to natural mouse aging.
estimate the impact of
genetic modi?cations or treatments on mouse aging.