pcgrimagegdf15 / config.json
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{
"approved_by_author": "\u231b",
"citation": "Higgins-Chen, Albert T., et al. \"A computational solution for bolstering reliability of epigenetic clocks: implications for clinical trials and longitudinal tracking.\" Nature Aging 2 (2022): 644\u2013661.",
"citations": 546,
"citations_date": "2026-10-02",
"clock_name": "pcgrimagegdf15",
"data_type": "DNA methylation",
"doi": "https://doi.org/10.1038/s43587-022-00248-2",
"journal": "Nature Aging",
"last_author": "Morgan E. Levine",
"model_type": "PCA + elastic net regression",
"n_features": 78465,
"notes": "Standalone principal-component proxy trained to reproduce the original DNAm GDF15 score. Coefficients are composed exactly from the author PCA rotation and proxy regression. CpGs use the author GSE40279 reference. Sex (female=1, male=0) and chronological age must be supplied when selected by the original component regression; missing demographic inputs are rejected. Selected demographic inputs: age.",
"platform": [
"Illumina 450K"
],
"population": "adults",
"predicts": [
"GDF-15"
],
"reference_values": true,
"research_only": null,
"species": "Homo sapiens",
"tissue": [
"whole blood"
],
"training_target": [
"DNAm GDF15 output"
],
"unit": [
"picograms per milliliter"
],
"version": "0.5.4",
"year": 2022
}