Sex-specific non-linear DNA methylation aging trajectories reveal biomarkers of cancer risk and inflammation

Background: Aging is a multi-modal process, leaving distinct molecular signatures across the epigenome. DNA methylation is among the most robust biomarkers of biological aging, yet most studies assume linear age relationships and analyze mixed-sex cohorts, overlooking known sex differences. Such approaches risk obscuring critical non-linear transitions and sex-specific trajectories. Results: We developed SNITCH, a computational framework to detect complex non-linear methylation trajectories and disentangle shared from sex-divergent patterns. Applied to deconvoluted whole-blood methylomes from 252 females and 246 males (ages 19–90 years), SNITCH revealed convergent and divergent epigenetic aging pathways independent of immune cell composition. Non-linear trajectories were enriched for developmental transcription factor motifs, including NF1/CTF and REST, with known oncogenic roles. Importantly, a female-specific non-linear cluster was prospectively associated with cancer onset and systemic inflammation in an independent cohort, nominating clinically relevant biomarkers. Conclusion: Our results uncover sex-specific, non-linear aging programs that capture the dynamics of epigenetic change beyond linear models. These findings provide candidate biomarkers for early disease risk and advance understanding of how aging trajectories diverge between sexes, with potential applications across multi-omic studies of aging.