Aging | Aging the Brain: Multi-region Methylation Principal Component Based Clock in the Context of Alzheimer’s Disease

08-01-2022

“PCBrainAge may aid in future investigations linking heterogeneity in the aging process to AD [Alzheimer’s disease] risk and individual resilience.”

Listen to an audio version of this press release

BUFFALO, NY- August 1, 2022 – A new research paper was published in Aging (abbreviated as "Aging (Albany NY)" by Medline/PubMed and as "Aging-US" by Web of Science) on the cover of Volume 14, Issue 14, entitled, “Aging the brain: multi-region methylation principal component based clock in the context of Alzheimer’s disease.”

Alzheimer’s disease (AD) risk increases exponentially with age and is associated with multiple molecular hallmarks of aging, one of which is epigenetic alterations. Epigenetic age predictors based on 5’ cytosine methylation (DNAm), or epigenetic clocks, have previously suggested that epigenetic age acceleration may occur in AD brain tissue. 

“Epigenetic clocks are promising tools for the quantification of biological aging, yet we hypothesize that investigation of brain aging in AD will be assisted by the development of brain-specific epigenetic clocks.” 

In this new study, researchers Kyra L. Thrush, David A. Bennett, Christopher Gaiteri, Steve Horvath, Christopher H. van Dyck, Albert T. Higgins-Chen, and Morgan E. Levine, from Yale University, Rush University Medical Center, University of California Los Angeles, VA Connecticut Healthcare System, and Altos Labs, hypothesized that a brain age methylation-based predictor could be developed with meaningful disease associations and broad multi-brain-region utility.

“To test this, we used DNAm capture to generate a PC-based epigenetic predictor of brain aging which we show to: (1) strongly reflect AD neuropathology and cognitive decline, and (2) track age across multiple brain regions.”

The team generated a novel age predictor, termed PCBrainAge, that was trained solely in cortical samples. This predictor utilizes a combination of principal components analysis and regularized regression, which reduces technical noise and greatly improves test-retest reliability.

“To characterize the scope of PCBrainAge’s utility, we generated DNAm data from multiple brain regions in a sample from the Religious Orders Study and Rush Memory and Aging Project.”

PCBrainAge captures meaningful heterogeneity of aging: Its acceleration demonstrates stronger associations with clinical AD dementia, pathologic AD, and APOE ε4 carrier status compared to extant epigenetic age predictors. It further does so across multiple cortical and subcortical regions. 

“Overall, PCBrainAge’s increased reliability and specificity makes it a particularly promising tool for investigating heterogeneity in brain aging, as well as epigenetic alterations underlying AD risk and resilience.”

DOI: https://doi.org/10.18632/aging.204196 

Corresponding Author: Albert T. Higgins-Chen - Email: a.higginschen@yale.edu 

Keywords: epigenetic clocks, unsupervised machine learning, brain, Alzheimer's disease, age acceleration

Sign up for free Altmetric alerts about this article:  https://aging.altmetric.com/details/email_updates?id=10.18632%2Faging.204196

About Aging-US:

Aging publishes research papers in all fields of aging research including but not limited, aging from yeast to mammals, cellular senescence, age-related diseases such as cancer and Alzheimer’s diseases and their prevention and treatment, anti-aging strategies and drug development and especially the role of signal transduction pathways such as mTOR in aging and potential approaches to modulate these signaling pathways to extend lifespan. The journal aims to promote treatment of age-related diseases by slowing down aging, validation of anti-aging drugs by treating age-related diseases, prevention of cancer by inhibiting aging. Cancer and COVID-19 are age-related diseases.

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

Please visit our website at www.Aging-US.com and connect with us:

For media inquiries, please contact media@impactjournals.com.