A 209‐Site DNA Methylation Predictor of Chronological Age Evaluated Under Empirical and Random Missingness

DNA methylation age prediction from incomplete profiles requires evaluation under empirical and random missingness. We evaluated whole-blood chronological-age prediction using 524 development and 132 held-out GSE40279 samples and an external GSE73103 cohort (n = 355). Feature-stability analysis across 750 prespecified perturbation conditions identified a 209-CpG primary panel and a 52-CpG stringent sensitivity subset. The primary predictor combined five-nearest-neighbor reconstruction (KNN5) with Ridge regression. In the internal holdout, intact-profile prediction achieved a mean absolute error of 4.24 years, a root-mean-square error (RMSE) of 5.38 years, and Pearson r = 0.934. Under masks derived from 42 empirical templates of formalin-fixed paraffin-embedded detection failure, KNN5 reduced RMSE by 0.365 years relative to development-set mean replacement (95% bootstrap interval for the difference, -0.546 to -0.205), with larger reductions at higher missingness burdens. The reconstruction advantage persisted in complementary development analyses after randomization preserving both sample-level and CpG-level failure counts. External predictions remained associated with chronological age (r = 0.835), despite age-dependent calibration bias. Mixture analyses showed that background accuracy was central to target recovery as mixture asymmetry increased. These findings support local reconstruction within a stability-selected CpG panel for chronological-age prediction under the evaluated empirical and random missingness conditions.

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Publication Details

Journal
Aging Cell
Published
2026-11-01
DOI
https://doi.org/10.1111/acel.70800
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
0.00

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article

A 209‐Site DNA Methylation Predictor of Chronological Age Evaluated Under Empirical and Random Missingness

Xiangteng Zhao, Biqing Huang, Shiwen Yu, Shushan Wei et al.
1 links
Aging Cell
Epigenetics and DNA Methylation
article

A 209‐Site DNA Methylation Predictor of Chronological Age Evaluated Under Empirical and Random Missingness

Xiangteng Zhao, Biqing Huang, Shiwen Yu, Shushan Wei, Yanhong Lu, Ruoqi Zhao, Tong Yu, Yeting Zeng, Zijie Wang
article en

Abstract

DNA methylation age prediction from incomplete profiles requires evaluation under empirical and random missingness. We evaluated whole-blood chronological-age prediction using 524 development and 132 held-out GSE40279 samples and an external GSE73103 cohort (n = 355). Feature-stability analysis across 750 prespecified perturbation conditions identified a 209-CpG primary panel and a 52-CpG stringent sensitivity subset. The primary predictor combined five-nearest-neighbor reconstruction (KNN5) with Ridge regression. In the internal holdout, intact-profile prediction achieved a mean absolute error of 4.24 years, a root-mean-square error (RMSE) of 5.38 years, and Pearson r = 0.934. Under masks derived from 42 empirical templates of formalin-fixed paraffin-embedded detection failure, KNN5 reduced RMSE by 0.365 years relative to development-set mean replacement (95% bootstrap interval for the difference, -0.546 to -0.205), with larger reductions at higher missingness burdens. The reconstruction advantage persisted in complementary development analyses after randomization preserving both sample-level and CpG-level failure counts. External predictions remained associated with chronological age (r = 0.835), despite age-dependent calibration bias. Mixture analyses showed that background accuracy was central to target recovery as mixture asymmetry increased. These findings support local reconstruction within a stability-selected CpG panel for chronological-age prediction under the evaluated empirical and random missingness conditions.

Aging CellVol. 25(11)
Fujian Medical University (CN), Fudan University (CN), First Affiliated Hospital of Fujian Medical University (CN), Zhongshan Hospital (CN), Fujian Provincial Hospital (CN), Fuzhou University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Fujian Province
Good health and well-being
Openalex Percentile: Top 22%
Epigenetics and DNA Methylation
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