Novel Epigenetic Clock for Fetal Brain Development Predicts Fetal Epigenetic Age for iPSCs and iPSC-Derived Neurons.

Abstract

Induced pluripotent stem cells (iPSCs) and their differentiated neurons (iPSC-neurons) are a widely used cellular model in the research of the central nervous system. However, it is unknown how well they capture age-associated processes, particularly given that pluripotent cells are only present during the early stages of mammalian development. Epigenetic clocks utilize coordinated age-associated changes in DNA methylation to make predictions that correlate strongly with chronological age, and is has been shown that the induction of pluripotency rejuvenates predicted epigenetic age. As existing clocks are not optimized for the study of brain development, to investigate more precisely the epigenetic age of iPSCs and iPSC-neurons, here, we establish the fetal brain clock (FBC), a bespoke epigenetic clock trained in prenatal neurodevelopmental samples. Our data show that the FBC outperforms other established epigenetic clocks in predicting the age of fetal brain samples. We then applied the FBC to DNA methylation data of cellular datasets that have profiled iPSCs and iPSC-derived neuronal precursor cells and neurons and find that these cell types are characterized by a fetal epigenetic age. Furthermore, while differentiation from iPSCs to neurons significantly increases the epigenetic age, iPSC-neurons are still predicted as having fetal epigenetic age. Together our findings reiterate the need for better understanding of the limitations of existing epigenetic clocks for answering biological research questions and highlight a potential limitation of iPSC-neurons as a cellular model for the research of age-related diseases as they might not fully recapitulate an aged phenotype.

Characterization of DNA Methylomic Signatures in Induced Pluripotent Stem Cells During Neuronal Differentiation

“…One concern when using iPSC-derived neurons to study diseases, particularly age-related neurodegenerative disorders, is the biological age of the neurons. To address this, we used two different epigenetic age calculators to calculate the epigenetic age of the samples, including the latest iteration of the Horvath age calculator ( Horvath et al, 2018 ) and a new fetal brain clock developed by Steg et al (2020) . The Horvath calculator predicted an increase in epigenetic age throughout differentiation and maturation, although these increases were not significant ( Figure 1A ).…”

“…(A) The estimated epigenetic age (Y-axis) of the four cellular stages (X-axis) increased throughout differentiation using the epigenetic age clock created by Horvath et al (2018) , although there were no significant differences between cellular stages. (B) The estimated epigenetic age of iPSCs and NPCs were significantly lower than the mature Days 37 and 58 neurons using the fetal brain epigenetic age clock created by Steg et al (2020) , but with no difference between iPSCs and NPCs or between Days 37 and 58 neurons. The age of each sample is given in days post-conception.…”

“…While the Horvath epigenetic age calculator has been shown to accurately predict the epigenetic age of brain samples ( Horvath et al, 2018 ), it has been reported to be inaccurate in juvenile samples, presumably because DNA methylation changes are more dynamic in children ( McEwen et al, 2019 ). For this reason, we also used the Steg fetal brain clock as this was trained using human fetal brain samples ( Steg et al, 2020 ). Both methods predicted that the iPSC-derived neurons are epigenetically immature, with the Steg fetal clock showing significant differences between cellular stages.…”

“…In this study, we used two epigenetic age calculators: first, the pan-tissue DNA methylation age estimator ( Horvath et al, 2018 ), which predicts chronological age based on the DNA methylation levels of 353 CpGs that were identified in human adult tissues, and second, a recently developed epigenetic clock using DNA methylation data from fetal brain tissue, based on 107 CpGs ( Steg et al, 2020 ). The coefficients and intercept for both the Horvath and Steg age calculators were downloaded and were applied using the agep function of the wateRmelon package ( Pidsley et al, 2013 ).…”