Characterizing the relationship between telomere length and DNA methylation age in induced pluripotent stem cells during neuronal differentiation

Abstract

AbstractBackgroundInduced pluripotent stem cells (iPSCs) and their resultant neurons are popular models for studying diseases of aging, such as Alzheimer’s disease (AD). One hallmark of aging is the decreasing length of telomeres, the repetitive, protective DNA sequences at the end of each chromosome. We have previously demonstrated that whilst epigenetic age does increase with differentiation, iPSC‐derived neurons still have a fetal DNA methylation profile. It has also been shown by others that telomere length in iPSC‐derived neurons is shorter than the that of the stem cells from which they are derived. However, to our knowledge no one has looked at both epigenetic age and telomere length in the same samples. Therefore, we have collected DNA from different stages of the differentiation of iPSCs into neurons in order to look at the relationship between epigenetic age and telomere length.MethodHuman fibroblast cells were reprogrammed using lentiviral transfection. The resulting iPSC colonies were expanded, differentiated and collected at four different time points: day0 (iPSCs), day16 (neuronal progenitor cells), day37 and day58 (mature neurons). DNA methylation was assessed using the Illumina EPIC array and epigenetic age was derived using both the Horvath skin and blood clock and the Steg fetal brain clock. Absolute telomere length was determined using quantitative real‐time PCR.ResultThis study has identified the telomere dynamics of iPSCs as they undergo differentiation into cortical neurons. Not only this, but by also calculating the epigenetic age in the same samples we have been able to look at the relationship between telomere length and epigenetic age using two differentiation DNA methylation age calculators.ConclusionWe have outlined the relationship between telomere length and DNA methylation age of iPSCs as they differentiate into cortical neurons. This information is important to consider when using iPSCs to model age‐related diseases such as AD.