Trajectory Inference of Human Aging from Cross-Sectional DNA Methylation Data
DNA methylation (DNAm) serves as one of the most robust molecular biomarkers of biological aging. While conventional epigenetic clocks accurately predict chronological age from high-dimensional CpG profiles, they treat aging as a static regression task, meaning they can only output a single score rather than simulating how an entire profile continuously changes over time. To reconstruct these continuous dynamics, we frame lifelong human epigenetic aging as a trajectory inference problem across discrete age snapshots derived from widely available cross-sectional data. We introduce a two-stage computational pipeline: first, an age-regularized Variational Autoencoder (VAE) maps high-dimensio...
| Authors | Chandan Gupta, Syed Haider, Pietro Liò |
|---|---|
| Primary category | q-bio.QM |
| Published | 4 July 2026 |
| Last updated at source | 4 July 2026 |
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