library_name: pyaging
tags:
- pyaging
- aging-clock
- biology
- clinical-biomarkers
phenoage
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.
Model weights retain the original authors' terms; the pyaging software license does not relicense them.
| Predicts | phenotypic age |
| Species | Homo sapiens |
| Tissue | blood |
| Data type | clinical biomarkers |
| Model type | penalized hazards regression with Gompertz calibration |
| Year | 2018 |
Use with pyaging
import pyaging as pya
pya.pred.predict_age(adata, ["phenoage"])
Browse every clock in the pyaging Clock Catalogue.
Citation
Levine, M. E., et al. "An epigenetic biomarker of aging for lifespan and healthspan." Aging 10.4 (2018): 573-591.