Language
English
Publication Date
6-1-2025
Journal
PNAS Nexus
DOI
10.1093/pnasnexus/pgaf177
PMID
40583914
PMCID
PMC12203532
PubMedCentral® Posted Date
6-3-2025
PubMedCentral® Full Text Version
Post-print
Abstract
DNA methylation is a crucial epigenetic marker used in various clocks to predict epigenetic age. However, many existing clocks fail to account for crucial information about CpG sites and their interrelationships, such as co-methylation patterns. We present a novel approach to represent methylation data as a graph, using methylation values and relevant information about CpG sites as nodes, and relationships like co-methylation, same gene, and same chromosome as edges. We then use a graph neural network (GNN) to predict age. Thus our model, GraphAge leverages both the structural and positional information for prediction as well as better interpretation. Although, we had to train in a constrained compute setting, GraphAge still showed competitive performance with a mean absolute error of 3.207 and a mean squared error of 25.277, substantially outperforming the existing models. Perhaps more importantly, we utilized GNN explainer for interpretation purposes and were able to unearth interesting insights (e.g. key CpG sites, pathways and their relationships through methylation regulated networks in the context of aging), which were not possible to "decode" without leveraging the unique capability of GraphAge to "encode" various structural relationships. GraphAge has the potential to consume and utilize all relevant information (if available) about an individual that relates to the complex process of aging. So, in that sense it is one of its kind and can be seen as the first benchmark for a multimodal model which can incorporate all these information in order to close the gap in our understanding of the true nature of aging.
Keywords
epigenetic age, DNA methylation, co-methylation, graph neural network (GNN), computational epigenetics
Published Open-Access
yes
Recommended Citation
Ahmed, Saleh Sakib; Shabab, Nahian; Samee, Abul Hassan; et al., "GraphAge: Unleashing the Power of Graph Neural Network to Decode Epigenetic Aging" (2025). Faculty, Staff and Students Publications. 6259.
https://digitalcommons.library.tmc.edu/baylor_docs/6259
Comments
This article has been corrected. See PNAS Nexus. 2025 Sep 17;4(9):pgaf294.