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

TL;DR

This study finds that aging affects DNA methylation differently in men and women, revealing new biomarkers for cancer and inflammation.

Contribution

The study introduces SNITCH, a framework to detect nonlinear, sex-specific DNA methylation aging patterns.

Findings

Nonlinear methylation trajectories are linked to developmental transcription factors with oncogenic roles.

A female-specific cluster is associated with cancer and inflammation in an independent cohort.

Sex-specific aging patterns are consistent across multiple cohorts and independent of immune cell composition.

Abstract

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 nonlinear transitions and sex-specific trajectories.

We develop SNITCH, a computational framework to detect complex nonlinear methylation trajectories and disentangle shared from sex-divergent patterns. Applied to the array-derived whole-blood methylomes from 252 females and 246 males (ages 19–90 years), SNITCH reveals convergent and divergent epigenetic aging pathways independent of immune cell composition. Nonlinear trajectories are enriched for developmental transcription factor motifs, including NF1/CTF and REST, with known oncogenic roles. Importantly, a female-specific nonlinear cluster is prospectively associated with cancer onset and systemic inflammation in an independent cohort, nominating clinically relevant biomarkers. We replicate the analysis in an additional cohort and highlight consistent nonlinear trajectories.

Our results uncover sex-specific, nonlinear aging programs that capture the dynamics of epigenetic change beyond linear models. These findings provide potential candidate biomarkers for early disease risk and advance understanding of how aging trajectories diverge between sexes.

The online version contains supplementary material available at 10.1186/s13059-026-03952-z.

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