An Aging Clock Based on the Transcriptome Rather than Epigenome

Researchers here use the transcription levels of hundreds of proteins taken from published nematode study data sets to produce an accurate aging clock, akin to the epigenetic clocks that were the first age assessments of this nature. They then apply much the same process to human data. These clocks are of potential value because they may offer a way to dramatically speed up the process of assessing approaches to rejuvenation, but a great deal more work must be accomplished in order to achieve this goal. At present it is far from clear as to what exactly these metrics are measuring, under the hood. They must thus be calibrated for each and every new type of potential therapy, which rather defeats the point.

Aging clocks dissociate biological from chronological age. The estimation of biological age is important for identifying gerontogenes and assessing environmental, nutritional, or therapeutic impacts on the aging process. Recently, methylation markers were shown to allow estimation of biological age based on age-dependent somatic epigenetic alterations. However, DNA methylation is absent in some species such as Caenorhabditis elegans and it remains unclear whether and how the epigenetic clocks affect gene expression. Aging clocks based on transcriptomes have suffered from considerable variation in the data and relatively low accuracy.

Here, we devised an approach that uses temporal scaling and binarization of C. elegans transcriptomes to define a gene set that predicts biological age with an accuracy that is close to the theoretical limit. Our model accurately predicts the longevity effects of diverse strains, treatments, and conditions. The involved genes support a role of specific transcription factors as well as innate immunity and neuronal signaling in the regulation of the aging process. We show that this transcriptome clock can also be applied to human age prediction with high accuracy. This transcriptome aging clock could therefore find wide application in genetic, environmental, and therapeutic interventions in the aging process.