---
library_name: pyaging
tags:
- pyaging
- aging-clock
- biology
- dna-methylation
---

# zhangmortality

Ten-CpG whole-blood mortality risk score. Pyaging implements the paper supplement's continuous LASSO-weighted score exactly (the sum of ten raw beta values multiplied by their published coefficients). The same study also defines a separate simplified 0-10 aberrant-methylation count based on cohort-specific quartile cutoffs.

Model weights retain the original authors' terms; the pyaging software license does not relicense them.

| | |
|---|---|
| **Predicts** | mortality risk |
| **Species** | Homo sapiens |
| **Tissue** | whole blood |
| **Data type** | DNA methylation |
| **Model type** | weighted linear score |
| **Year** | 2017 |

## Use with pyaging

```python
import pyaging as pya

pya.pred.predict_age(adata, ["zhangmortality"])
```

Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).

## Citation

Zhang, Y., Wilson, R., Heiss, J. et al. DNA methylation signatures in peripheral blood strongly predict all-cause mortality. Nature Communications 8, 14617 (2017).

https://doi.org/10.1038/ncomms14617