Lee · Aging 2019 · cross-sectional biomarker derivation and validation study · n=1,102 (training set; test set n not specified)

Placental epigenetic clocks: estimating gestational age using placental DNA methylation levels.

Cited 172 times in the scientific literature.

Level 4 - case-series / case-control

Cross-sectional biomarker derivation and validation study using human placental tissue samples

PubMed 31235674 · doi:10.18632/aging.102049 · record verified 2026-08-29

What was done

The authors developed and validated epigenetic clocks specifically for placental tissue to estimate gestational age (GA) using placental DNA methylation (DNAm) data. Using a training dataset of 1,102 DNAm arrays, they constructed three models: a robust placental clock (RPC) unaffected by common pregnancy complications, a control placental clock (CPC) derived from uncomplicated pregnancies, and a refined RPC for uncomplicated term pregnancies. They also tested whether clocks trained on cord blood or other tissues could accurately estimate GA in placental tissue.

What was found

The robust placental clock predicted GA with a correlation of r > 0.95 and a median absolute error of less than one week in test data. Non-placental epigenetic clocks (such as cord blood clocks) failed to accurately estimate GA in placental samples. Specific quantitative performance figures for the CPC and refined RPC were not reported in the abstract.

Why it matters

Because pan-tissue and blood-based epigenetic clocks do not transfer well to placenta, these placental-specific clocks provide an accurate method for tracking fetal gestational age and studying developmental biology.

Limits

The abstract does not state the sample size, demographic profile, or clinical composition of the test dataset. Direct numeric accuracy metrics are omitted for two of the three models (CPC and refined RPC).

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