#36 · Epigenomics

Aging clocks now span transcriptomic damage, CpG-TF links, and trajectory artifacts

The dominant thread is molecular age estimation, with each item addressing how aging is quantified and interpreted. The tDamAge preprint quantifies transcriptomic damage, defined as aberrant transcript structures from RNA-seq, and uses a machine-learning clock to frame it as a causal measure of aging and rejuvenation; this transcript-structure readout is the new element. The published TFMethyl Clock links epigenetic clock CpGs to transcription factor binding sites and predicts chronological age with competitive accuracy, offering an interpretable route to the same question. A separate preprint reports that LOESS and DE-SWAN can generate artifactual nonlinear waves of molecular aging through simulation and reanalysis, challenging discrete aging-crest claims. Together these items place model interpretability and the validity of trajectory fitting alongside predictive accuracy.