| { |
| "approved_by_author": "\u231b", |
| "citation": "Levine, M. E., et al. \"An epigenetic biomarker of aging for lifespan and healthspan.\" Aging 10.4 (2018): 573-591.", |
| "citations": 3848, |
| "citations_date": "2026-10-02", |
| "clock_name": "phenoage", |
| "data_type": "clinical biomarkers", |
| "doi": "https://doi.org/10.18632/aging.101414", |
| "journal": "Aging", |
| "last_author": "Steve Horvath", |
| "model_type": "penalized hazards regression with Gompertz calibration", |
| "n_features": 10, |
| "notes": "Clinical Phenotypic Age combines chronological age with nine blood biomarkers and expresses modeled mortality risk as an equivalent age in years. Supply raw C-reactive protein in mg/dL; pyaging applies its natural logarithm, flooring values at 0.01 mg/dL. Before 0.5.0, callers supplied log_crp instead. Starting in pyaging 0.5.7, Gompertz gamma is 0.0076927 as specified in the original supplementary methods; earlier versions incorrectly used the Cox selection penalty 0.0192, inflating finite estimates by approximately 9.619365 years for otherwise identical inputs. This correction applies to clinical phenoage, not the separately fitted DNA-methylation clocks. Use pyaging >=0.5.7 with this artifact because the formula is implemented in the package class.", |
| "platform": [ |
| "clinical laboratory assays" |
| ], |
| "population": "adults", |
| "postprocess": "mortality_to_phenoage", |
| "predicts": [ |
| "phenotypic age" |
| ], |
| "preprocess": "natural_log_crp", |
| "research_only": null, |
| "species": "Homo sapiens", |
| "tissue": [ |
| "blood" |
| ], |
| "training_target": [ |
| "mortality" |
| ], |
| "unit": [ |
| "years" |
| ], |
| "version": "0.5.7", |
| "year": 2018 |
| } |
