BiT age: A transcriptome‐based aging clock near the theoretical limit of accuracy

Aging clocks dissociate biological from chronological age. The estimation of age is important for identifying gerontogenes and assessing environmental, nutritional, or therapeutic impacts on the aging process. Recently, methylation markers were shown to allow based age-dependent somatic epigenetic alterations. However, DNA absent in some species such as Caenorhabditis elegans it remains unclear whether how affect gene expression. transcriptomes have suffered considerable variation data relatively low accuracy. Here, we devised an approach that uses temporal scaling binarization C. define a set predicts with accuracy close theoretical limit. Our model accurately longevity effects diverse strains, treatments, conditions. involved genes support role specific transcription factors well innate immunity neuronal signaling regulation We show this binarized transcriptomic (BiT age) clock can also be applied human prediction high BiT could therefore find wide application genetic, interventions