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

# intrinclock

Multi-tissue chronological-age clock designed by excluding CpGs associated with CD8+ T-cell differentiation, then fitting two sequential elastic-net models so predictions remain stable across immune-cell composition. The article reports 381 CpGs; the official lambda.min model and this implementation both use the same 380 non-zero CpG inputs.

| | |
|---|---|
| **Predicts** | chronological age |
| **Species** | Homo sapiens |
| **Tissue** | multi-tissue |
| **Data type** | DNA methylation |
| **Model type** | two-stage elastic net regression |
| **Year** | 2024 |

## Use with pyaging

```python
import pyaging as pya

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

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

## Citation

Tomusiak, A., et al. “Development of an epigenetic clock resistant to changes in immune cell composition.” Communications Biology 7, 934 (2024).

https://doi.org/10.1038/s42003-024-06609-4