bioRxivGenomicsPreprint
Methylation Clocks Do Not Predict Age or Alzheimer's Disease Risk Across Genetically Admixed Individuals
Sebastián Cruz-GonzáleziD, Ogechukwu Okpala, Esther Gu, Lissette Gomez, Makaela MewsiD, Jeffery M. VanceiD, Michael L. CuccaroiD, Mario Cornejo‐OlivasiD, Briseida E. Feliciano‐AstacioiD, Goldie S. ByrdiD, Jonathan L. HainesiD, Margaret Ann Pericak‐VanceiD, Anthony J. GriswoldiD, William S. BushiD, John A. CapraiD
Abstract
Epigenetic aging clocks based on DNA methylation patterns across the genome have emerged as a potential biomarker for risk of age-related diseases, like Alzheimers disease (AD), and environmental and social stressors. However, methylation clocks have not been comprehensively validated in genetically diverse individuals. Here we evaluate a set of first-, second-, and third-generation methylation clocks in 621 AD patients and matched controls from African American, Hispanic, and White cohorts. The clocks are less accurate at predicting age in genetically admixed cohorts compared to the White cohort, especially for those with substantial African ancestry. This decreased accuracy holds in >2,500 individuals of European and African ancestry from three additional datasets. The clocks also fail to consistently identify age acceleration in admixed AD cases compared to controls. To explore potential causes for the lack of generalization of the clocks, we intersected clock CpGs with methylation, germline genetic variants, and methylation QTL (meQTL) data from global populations. We find differential methylation between African and European ancestry individuals is common for clock CpGs. Genetic variants rarely disrupt clock CpGs between populations, but a substantial fraction of clock CpGs have meQTL with significantly higher frequencies in African genetic ancestries. Our results demonstrate that methylation clocks often fail to predict age and AD risk when applied across populations and suggest avenues for improving their portability by considering differences in genetic and epigenetic patterns across human populations.
- Citations
- 9
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- DNA methylation age acceleration and risk factors for Alzheimer’s disease
Daniel L. McCartney, Anna J. Stevenson, … Riccardo Emilio Marioni·Alzheimer s & Dementia Diagnosis Assessment & Disease MonitoringPeer-reviewed·Jan 1, 2018
- Properties of the epigenetic clock and age acceleration
Louis Y. El Khoury, T.J. Gorrie-Stone, … Leonard C. Schalkwyk·bioRxiv·Jul 6, 2018
- Recalibrating the Epigenetic Clock: Implications for Assessing Biological Age in the Human Cortex
Gemma L. Shireby, Jonathan P. Davies, … Jonathan S. Mill·BrainPeer-reviewed·Sep 15, 2020
- Biological Age and Age Acceleration Predict Alzheimer's Disease Plasma Biomarker Levels
Jaclyn M. Eissman, Yiyi Ma, … Badri Narayan Vardarajan·medRxiv·May 22, 2025
- Accurate age prediction from blood using of small set of DNA methylation sites and a cohort-based machine learning algorithm
Miri Varshavsky, Gil Harari, … Tommy Kaplan·Cell Reports MethodsPeer-reviewed·Aug 28, 2023
- The relationship between ageing and changes in the human blood and brain methylomes
Patrick Bryant, Arne Elofsson·NAR Genomics and BioinformaticsPeer-reviewed·Jan 13, 2022