Epigenetic clocks in preterm neonates: Bridging developmental biology and precision neonatal research (Review)

The abrupt disruption of intrauterine epigenetic programming caused by preterm birth exposes the developing neonate to the physiological stressors of the neonatal intensive care unit (NICU). Birth weight and gestational age are the two main factors used in current clinical risk stratification. The biological heterogeneity and differing developmental outcomes observed among infants with identical clinical profiles, however, are not taken into consideration by these traditional parameters. DNA methylation‑based epigenetic clocks estimate tissue‑ and model‑specific age and may support research into developmental timing and associations with NICU exposures, including inflammation, hyperoxia and pain. The present review summarizes the principal epigenetic clocks relevant to preterm neonates, critically examines their tissue specificity, performance and validation, and discusses methodological, ethical and translational priorities. Neonatal clocks estimate developmental timing rather than cellular senescence; developmental velocity requires longitudinal measurements. The confounding effects of postnatal clinical interventions and tissue‑specific cellular heterogeneity render the interpretation of these metrics difficult. In the present review, neonatal epigenetic clocks should be used as research tools to improve neonatal phenotyping, rather than as predictive diagnostic biomarkers at the bedside. Establishing standardized, tissue‑specific bioinformatic pipelines, integrating multi‑omics data and validating models across various populations are all necessary to translate these tools into clinical practice. High assay costs, lengthy turnaround times, a lack of organized parental counseling frameworks, and unresolved data governance and ownership protocols are additional obstacles to clinical implementation. Neonatal epigenetic clocks ultimately provide a research framework for future precision neonatology by illuminating how early‑life biological programming influences long‑term health trajectories.