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library_name: pyaging
tags:
- pyaging
- aging-clock
- biology
- dna-methylation
---
# depressionbarbu
Blood methylation risk score for major depressive disorder, fitted with LASSO in 1,223 cases and 1,824 controls. The training outcome was MDD status residualized for age, sex and ten genetic principal components. The paper used dasen-normalized M-values, with training methylation additionally adjusted for relatedness, blood-cell composition and processing batch. The packaged linear model does not perform those input transformations or adjustments; raw beta values are not the published training input. Its output is a unitless score, not a depression probability or a classifier of prevalent versus incident disease.
Model weights retain the original authors' terms; the pyaging software license does not relicense them.
| | |
|---|---|
| **Predicts** | major depressive disorder |
| **Species** | Homo sapiens |
| **Tissue** | whole blood |
| **Data type** | DNA methylation |
| **Model type** | LASSO regression |
| **Year** | 2021 |
## Use with pyaging
```python
import pyaging as pya
pya.pred.predict_age(adata, ["depressionbarbu"])
```
Browse every clock in the [pyaging Clock Catalogue](https://pyaging.readthedocs.io).
## Citation
Barbu, Miruna C., et al. "Epigenetic prediction of major depressive disorder." Molecular Psychiatry 26.9 (2021): 5112-5123.
https://doi.org/10.1038/s41380-020-0808-3
|