{
 "approved_by_author": "\u231b",
 "citation": "Higgins-Chen, Albert T., et al. \"A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking.\" Nature Aging 2 (2022): 644\u2013661.",
 "citations": 546,
 "citations_date": "2026-10-02",
 "clock_name": "pcdnamtl",
 "data_type": "DNA methylation",
 "doi": "https://doi.org/10.1038/s43587-022-00248-2",
 "journal": "Nature Aging",
 "last_author": "Morgan E. Levine",
 "model_type": "PCA + elastic net regression",
 "n_features": 78464,
 "notes": "Principal-component proxy trained to reproduce the original DNAmTL clock output; the returned score remains in kilobases. Figure-level base-pair deviations are a separate analysis-scale conversion.",
 "platform": [
  "Illumina 450K"
 ],
 "population": "adults",
 "predicts": [
  "leukocyte telomere length"
 ],
 "reference_values": true,
 "research_only": null,
 "species": "Homo sapiens",
 "tissue": [
  "whole blood"
 ],
 "training_target": [
  "DNAmTL output"
 ],
 "unit": [
  "kilobases"
 ],
 "version": "0.5.7",
 "year": 2022
}