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- Title
Prediction of biological age and evaluation of genome-wide dynamic methylomic changes throughout human aging.
- Authors
Roudbar, Mahmoud Amiri; Mousavi, Seyedeh Fatemeh; Ardestani, Siavash Salek; Lopes, Fernando Brito; Momen, Mehdi; Gianola, Daniel; Khatib, Hasan
- Abstract
The use of DNA methylation signatures to predict chronological age and aging rate is of interest in many fields, including disease prevention and treatment, forensics, and anti-aging medicine. Although a large number of methylation markers are significantly associated with age, most age-prediction methods use a few markers selected based on either previously published studies or datasets containing methylation information. Here, we implemented reproducing kernel Hilbert spaces (RKHS) regression and a ridge regression model in a Bayesian framework that utilized phenotypic and methylation profiles simultaneously to predict chronological age. We used over 450,000 CpG sites from the whole blood of a large cohort of 4409 human individuals with a range of 10-101 years of age. Models were fitted using adjusted and un-adjusted methylation measurements for cell heterogeneity. Un-adjusted methylation scores delivered a significantly higher prediction accuracy than adjusted methylation data, with a correlation between age and predicted age of 0.98 and a root mean square error (RMSE) of 3.54 years in un-adjusted data, and 0.90 (correlation) and 7.16 (RMSE) years in adjusted data. Reducing the number of predictors (CpG sites) through subset selection improved predictive power with a correlation of 0.98 and an RMSE of 2.98 years in the RKHS model. We found distinct global methylation patterns, with a significant increase in the proportion of methylated cytosines in CpG islands and a decreased proportion in other CpG types, including CpG shore, shelf, and open sea (P<5e-06). Epigenetic drift seemed to be a widespread phenomenon as more than 97% of the age-associated methylation sites had heteroscedasticity. Apparent methylomic aging rate (AMAR) had a sex-specific pattern, with an increase in AMAR in females with age related to males.
- Subjects
STANDARD deviations; AGE; AGING; DNA methylation; HILBERT space; SUBSET selection
- Publication
G3: Genes | Genomes | Genetics, 2021, Vol 11, Issue 7, p1
- ISSN
2160-1836
- Publication type
Article
- DOI
10.1093/g3journal/jkab112