Maintenance of age in human neurons generated by microRNA-based neuronal conversion of fibroblasts
Christine J Huh,
Bo Zhang,
Matheus B Victor,
Sonika Dahiya,
Luis FZ Batista,
Steve Horvath,
Andrew S Yoo
Affiliations
Christine J Huh
Department of Developmental Biology, Washington University School of Medicine, St. Louis, United States; Program in Molecular and Cellular Biology, Washington University School of Medicine, St. Louis, United States
Bo Zhang
Department of Developmental Biology, Washington University School of Medicine, St. Louis, United States
Matheus B Victor
Department of Developmental Biology, Washington University School of Medicine, St. Louis, United States; Program in Neuroscience, Washington University School of Medicine, St. Louis, United States
Sonika Dahiya
Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, United States
Luis FZ Batista
Department of Developmental Biology, Washington University School of Medicine, St. Louis, United States; Department of Medicine, Washington University School of Medicine, St. Louis, United States
Steve Horvath
Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States; Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, United States
Aging is a major risk factor in many forms of late-onset neurodegenerative disorders. The ability to recapitulate age-related characteristics of human neurons in culture will offer unprecedented opportunities to study the biological processes underlying neuronal aging. Here, we show that using a recently demonstrated microRNA-based cellular reprogramming approach, human fibroblasts from postnatal to near centenarian donors can be efficiently converted into neurons that maintain multiple age-associated signatures. Application of an epigenetic biomarker of aging (referred to as epigenetic clock) to DNA methylation data revealed that the epigenetic ages of fibroblasts were highly correlated with corresponding age estimates of reprogrammed neurons. Transcriptome and microRNA profiles reveal genes differentially expressed between young and old neurons. Further analyses of oxidative stress, DNA damage and telomere length exhibit the retention of age-associated cellular properties in converted neurons from corresponding fibroblasts. Our results collectively demonstrate the maintenance of age after neuronal conversion.
