config.json

{
 "approved_by_author": "\u231b",
 "citation": [
  "Rozenblit, M., et al. Evidence of accelerated epigenetic aging of breast tissues in patients with breast cancer is driven by CpGs associated with polycomb-related genes. Clinical Epigenetics 14, 30 (2022).",
  "Levine, M. E., et al. \"An epigenetic biomarker of aging for lifespan and healthspan.\" Aging 10.4 (2018): 573-591."
 ],
 "citations": 23,
 "citations_date": "2026-10-02",
 "clock_name": "dnamphenoageprc",
 "data_type": "DNA methylation",
 "doi": "https://doi.org/10.1186/s13148-022-01249-z",
 "journal": "Clinical Epigenetics",
 "last_author": "Morgan Levine",
 "model_type": "weighted linear score",
 "n_features": 55,
 "notes": "Original Levine-lab polycomb-related PhenoAge contribution using 55 CpGs. Coefficients retain their original values; the 60.664 PhenoAge intercept is excluded from both partitions, so these scores are not standalone calibrated ages. The two contributions plus the original intercept reconstruct DNAmPhenoAge. Follows author imputation=FALSE: absent CpGs and supplied NA values contribute zero. The parent DNAmPhenoAge coefficients were fitted on InCHIANTI 450K whole-blood data; the selected sites also occur on 27K and EPIC arrays.",
 "platform": [
  "Illumina 450K"
 ],
 "population": "adults",
 "predicts": [
  "polycomb-related PhenoAge contribution"
 ],
 "preprocess": "missing_beta_zero_contribution",
 "research_only": null,
 "species": "Homo sapiens",
 "tissue": [
  "whole blood"
 ],
 "training_target": [
  "phenotypic age"
 ],
 "unit": [
  "years"
 ],
 "version": "0.5.7",
 "year": 2022
}