| library_name: pyaging | |
| tags: | |
| - pyaging | |
| - aging-clock | |
| - biology | |
| - dna-methylation | |
| # cvdwesterman | |
| Whole-blood DNA-methylation score for cardiovascular risk. The paper's final cross-study learner stacks cohort-specific elastic-net Cox models; the packaged pyaging implementation is a 235-CpG linear score followed by a sigmoid. | |
| Model weights retain the original authors' terms; the pyaging software license does not relicense them. | |
| | | | | |
| |---|---| | |
| | **Predicts** | cardiovascular disease risk | | |
| | **Species** | Homo sapiens | | |
| | **Tissue** | whole blood | | |
| | **Data type** | DNA methylation | | |
| | **Model type** | elastic net Cox ensemble | | |
| | **Year** | 2020 | | |
| ## Use with pyaging | |
| ```python | |
| import pyaging as pya | |
| pya.pred.predict_age(adata, ["cvdwesterman"]) | |
| ``` | |
| Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io). | |
| ## Citation | |
| Westerman, K. et al. Epigenomic assessment of cardiovascular disease risk and interactions with traditional risk metrics. Journal of the American Heart Association 9, e015299 (2020). | |
| https://doi.org/10.1161/jaha.119.015299 | |