| { |
| "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": "pcgrimagepackyrs", |
| "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": 78466, |
| "notes": "Standalone principal-component proxy trained to reproduce the original DNAm smoking pack-years score. Coefficients are composed exactly from the author PCA rotation and proxy regression. CpGs use the author GSE40279 reference. Sex (female=1, male=0) and chronological age must be supplied when selected by the original component regression; missing demographic inputs are rejected. Selected demographic inputs: female, age.", |
| "platform": [ |
| "Illumina 450K" |
| ], |
| "population": "adults", |
| "predicts": [ |
| "smoking exposure" |
| ], |
| "reference_values": true, |
| "research_only": null, |
| "species": "Homo sapiens", |
| "tissue": [ |
| "whole blood" |
| ], |
| "training_target": [ |
| "DNAm smoking pack-years output" |
| ], |
| "unit": [ |
| "pack-years" |
| ], |
| "version": "0.5.4", |
| "year": 2022 |
| } |
