The Binarized Transcriptomic Aging Clock

In this study, we build such a transcriptomic aging clock that predicts the biological age of C. elegans based on high-throughput gene expression data to an unprecedented accuracy. We combine a temporal rescaling approach, to make samples of diverse lifespans comparable, with a novel binarization approach, which overcomes current limitations in the prediction of the biological age. Moreover, we show that the model accurately predicts the effects of several lifespan-affecting factors such as insulin-like signaling, a dysregulated miRNA regulation, the effect of an epigenetic mark, translational efficiency, dietary restriction, heat stress, pathogen exposure, the diet-, and dosage-dependent effects of drugs. This combination of rescaling and binarization of gene expression data therefore allows for the first time to build an accurate aging clock that predicts the biological age regardless of the genotype or treatment. Lastly, we show how our binarized transcriptomic aging (BiT age) clock model has the potential to improve the prediction of the transcriptomic age of humans and might therefore be universally applicable to assess biological age.
Source: Fight Aging! - Category: Research Authors: Tags: Medicine, Biotech, Research Source Type: blogs