organagemortalityolink3000thyroid

Thyroid OrganAge mortality model for Olink Explore 3072, using author-recommended fold 1. Input columns are the original case-sensitive protein symbols and values are Olink NPX, already normalized. No additional centering or cohort scaling is applied. Absent proteins contribute zero; NaNs in supplied proteins propagate, matching the original Example_Script.R scoring expressions. For other assays, prepare and rescale protein values according to the author guidance before prediction. Output is relative natural-log mortality hazard, not age in years. Models labelled Female and Male contain protein features; neither requires a sex covariate. Academic/non-commercial research use only; commercial use requires a separate license from the authors.

Model weights retain the original authors' terms; the pyaging software license does not relicense them. See the original author license. These weights are restricted to research use under the authors' terms.

Predicts	mortality risk
Species	Homo sapiens
Tissue	blood
Data type	proteomics
Model type	elastic net Cox regression
Year	2025

Use with pyaging

import pyaging as pya

pya.pred.predict_age(adata, ["organagemortalityolink3000thyroid"])

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Citation

Goeminne, L. J. E., et al. "Plasma protein-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems." Cell Metabolism 37, 205–222.e6 (2025).

https://doi.org/10.1016/j.cmet.2024.10.005