Maintenance of age in human neurons generated by microRNA-based neuronal conversion of fibroblasts
Open accessAbstract
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.
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Direct cellular reprogramming retains age-related signatures stored in pre-reprogrammed non-neural somatic cells such as fibroblasts, including the epigenetic age, telomere length, and gene expression changes.
“Direct cellular reprogramming retains age-related signatures stored in pre-reprogrammed non-neural somatic cells such as fibroblasts, including the epigenetic age, telomere length, and gene expression changes (22, 23).”
From Modeling late-onset Alzheimer’s disease neuropathology via direct neuronal reprogramming (2024) · cites this paper as [22]
Fibroblast-derived iNs preserve substantial signatures of human aging, including transcriptomic, nuclear pore, mitochondrial, epigenetic, and other aspects of aging.
“Fibroblast-derived iNs preserve substantial signatures of human aging, including transcriptomic, nuclear pore, mitochondrial, epigenetic, and other aspects of aging (Herdy et al., 2019; Huh et al., 2016; Kim et al., 2018; Mertens et al., 2015a; Traxler et al., 2019).”
From Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients (2021) · cites this paper as Huh et al., 2016
Pluripotent stem cells and their derivatives reflect pre-natal DNA methylation ages.
“Clearly, iN DNAm ages reflect the adult and old chronological ages of their donors, whereas pluripotent stem cells and their derivatives reflect pre-natal DNAm ages (Figure 7H; Huh et al., 2016; Kim et al., 2014; Lo Sardo et al., 2017).”
From Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients (2021) · cites this paper as Huh et al., 2016
iN DNA methylation ages reflect the adult and old chronological ages of their donors.
“Clearly, iN DNAm ages reflect the adult and old chronological ages of their donors, whereas pluripotent stem cells and their derivatives reflect pre-natal DNAm ages (Figure 7H; Huh et al., 2016; Kim et al., 2014; Lo Sardo et al., 2017).”
From Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients (2021) · cites this paper as Huh et al., 2016
AD iNs do not display signs of accelerated epigenetic aging over control iNs.
“AD iNs did not display signs of accelerated epigenetic aging over control iNs (Figures 7I and 7J; Figure S6; Horvath, 2013; Huh et al., 2016).”
From Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients (2021) · cites this paper as Huh et al., 2016
Cellular aging features and adult-like neuronal identity of iNs are likely critical for the emergence of such phenotypes in sporadic AD neurons.
“Cellular aging features (Huh et al., 2016; Mertens et al., 2015a, 2018; Tang et al., 2017; Victor et al., 2014) and adult-like neuronal identity of iNs (Luo et al., 2019) are likely critical for the emergence of such phenotypes in sporadic AD neurons, because erasure of aging signatures and re-gaining of fetal identity represents a potent rescue in this study (Miller et al., 2013; Ocampo et al., 2”
From Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients (2021) · cites this paper as Huh et al., 2016
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“1Department of Developmental Biology, Washington University School of Medicine, St. Louis, United States; 2Program in Molecular and Cellular Biology, Washington University School of Medicine, St. Louis, United States; 3Program in Neuroscience, Washington University School of Medicine, St. Louis, United States; 4Depart…”
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Horvath, S., Erhart, W., Brosch, M., Ammerpohl, O., Schönfels, W. V., Ahrens, M., Heits, N., Bell, J. T., Tsai, P.-C., Spector, T. D., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1412759111 · Cited by 760 · cited 1× · see citing works
“The utility of the epigenetic clock method has been demonstrated in applications surrounding cognitive function (Levine et al., 2015), obesity (Horvath et al., 2014), Down syndrome (Horvath et al., 2015b), HIV infection (Horvath and Levine, 2015), and Parkinson’s disease (Horvath and Ritz, 2015).”
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“generated by microRNA-based neuronal conversion of fibroblasts”
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ResultAccelerated epigenetic aging in Down syndrome
Horvath, S., Garagnani, P., Bacalini, M. G., Pirazzini, C., Salvioli, S., Gentilini, D., Blasio, A. M. D., Giuliani, C., Tung, S., Vinters, H. V., et al. (2015) · Aging Cell · doi:10.1111/acel.12325 · Cited by 488 · see citing works
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“The utility of the epigenetic clock method has been demonstrated in applications surrounding cognitive function (Levine et al., 2015), obesity (Horvath et al., 2014), Down syndrome (Horvath et al., 2015b), HIV infection (Horvath and Levine, 2015), and Parkinson’s disease (Horvath and Ritz, 2015).”
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“cesses including inflammation, senescence, metabolism and telomerase activity (Kondo et al., 2016; Qin et al., 2012; Fang et al., 2010).”
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Horvath, S., Pirazzini, C., Bacalini, M. G., Gentilini, D., Di Blasio, A. M., Delledonne, M., Mari, D., Arosio, B., Monti, D., Passarino, G., et al. (2015) · Aging · doi:10.18632/aging.100861 · Cited by 316 · see citing works
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MicroRNAs as Mediators of the Ageing Process
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BackgroundMicroRNA-based conversion of human fibroblasts into striatal medium spiny neurons
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“…in age from 3 days to 96-year old were transduced with a lentiviral preparation of the Doxycline-inducible synthetic cluster of miR-9/9* and miR-124 (miR-9/9*-124), alongside transcription factors CTIP2, DLX1, DLX2, and MYT1L as previously described (Richner et al., 2015; Victor et al., 2014).”
BackgroundMethodInfluentialTomlinson, R. L., Abreu, E. B., Ziegler, T. D., Ly, H., Counter, C. M., Terns, R. M., & Terns, M. P. (2008) · Molecular Biology of the Cell · doi:10.1091/mbc.e08-02-0184 · Cited by 71 · cited 1× · see citing works
“The data were normalized using the ’Noob’ normalization method (Triche et al., 2013).”
Back and forth in time: Directing age in iPSC-derived lineages
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“Recently, experimental manipulations to accelerate aging in iPSC-derived cells have been explored, for instance, by overexpressing progerin, a mutant form of lamin A observed in progeria syndrome, to force the detection of agerelated pathophysiology of neurodegenerative disease (Arbab et al., 2014; Cornacchia and Stud…”
BackgroundSenescence: the good the bad and the dysfunctional
Pazolli, E., & Stewart, S. A. (2008) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2007.12.002 · Cited by 50 · cited 1× · see citing works
“…population doubling level (PDL) to elimi- nate any confounding variability introduced by sequential passaging (Campisi and d’Adda di Fagagna, 2007; Pazolli and Stewart, 2008), then subsequently transduced with miR-9/9*-124 with CTIP2, DLX1/2, and MYT1L (CDM) following our established protocol…”
MethodWhen rejuvenation is a problem: challenges of modeling late-onset neurodegenerative disease
Vera, E., & Studer, L. (2015) · Development · doi:10.1242/dev.120667 · Cited by 43 · cited 4× · see citing works
“…we previously described a reprogramming paradigm using neuronal microRNAs (miRNAs), miR-9/9* and miR-124 (miR-9/9*-124), that exert reprogramming activities to directly convert human fibroblasts to specific mature neuronal subtypes (Richner et al., 2015; Victor et al., 2014; Yoo et al., 2011).”
BackgroundMethodInfluentialKondo, H., Kim, H. W., Wang, L., Okada, M., Paul, C., Millard, R. W., & Wang, Y. (2015) · Aging Cell · doi:10.1111/acel.12411 · Cited by 39 · cited 1× · see citing works
“While the exact role of these microRNAs in aging is unknown, miR-10a and miR-497 have been previously implicated in aging-associated cellular pro- cesses including inflammation, senescence, metabolism and telomerase activity (Kondo et al., 2016; Qin et al., 2012; Fang et al., 2010).”
BackgroundTranslational gene mapping of cognitive decline
Wilmot, B., McWeeney, S. K., Nixon, R. R., Montine, T. J., Laut, J., Harrington, C. A., Kaye, J. A., & Kramer, P. L. (2006) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2006.11.008 · Cited by 35 · cited 1× · see citing works
“…we previously described a reprogramming paradigm using neuronal microRNAs (miRNAs), miR-9/9* and miR-124 (miR-9/9*-124), that exert reprogramming activities to directly convert human fibroblasts to specific mature neuronal subtypes (Richner et al., 2015; Victor et al., 2014; Yoo et al., 2011).”
BackgroundModeling motor neuron disease: the matter of time
Arbab, M., Baars, S., & Geijsen, N. (2014) · Trends in Neurosciences · doi:10.1016/j.tins.2014.07.008 · Cited by 33 · cited 2× · see citing works
“Recently, experimental manipulations to accelerate aging in iPSC-derived cells have been explored, for instance, by overexpressing progerin, a mutant form of lamin A observed in progeria syndrome, to force the detection of agerelated pathophysiology of neurodegenerative disease (Arbab et al., 2014; Cornacchia and Stud…”
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DNA methylation-based biomarkers and the epigenetic clock theory of ageing
Horvath, S., & Raj, K. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0004-3 · Cited by 3,095 · see citing works
The ageing epigenome and its rejuvenation
Zhang, W., Qu, J. T., Liu, G., & Belmonte, J. C. I. (2020) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0204-5 · Cited by 472 · see citing works
Modeling Alzheimer’s disease with iPSC-derived brain cells
Penney, J., Ralvenius, W. T., & Tsai, L.-H. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0468-3 · Cited by 471 · see citing works
Building Models of Brain Disorders with Three-Dimensional Organoids
Amin, N. D., & Paşca, S. P. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.007 · Cited by 312 · see citing works
Chen, X., & Mobley, W. C. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00659 · Cited by 291 · see citing works
Mertens, J., Reid, D. A., Lau, S., Kim, Y., & Gage, F. H. (2018) · Annual Review of Genetics · doi:10.1146/annurev-genet-120417-031534 · Cited by 252 · see citing works
“➌ Additionally, DNA lesions can accumulate via errors in transcription or in the removal of epigenetic methylation markers, and persistent lesions fundamentally alter metabolism due to bioenergetic stress; ➍ this leads to changes at the mitochondrial level, which in turn increase the amount of reactive oxygen species…”
BackgroundResultInfluentialVictor, M. B., Richner, M., Olsen, H. E., Lee, S. W., Monteys, A. M., Ma, C., Huh, C. J., Zhang, B., Davidson, B. L., Yang, X. W., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0075-7 · Cited by 246 · see citing works
Age-dependent instability of mature neuronal fate in induced neurons from Alzheimer’s patients
Mertens, J., Herdy, J. R., Traxler, L., Schafer, S. T., Schlachetzki, J. C. M., Böhnke, L., Reid, D. A., Lee, H., Zangwill, D., Fernandes, D. P., et al. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2021.04.004 · Cited by 240 · see citing works
Self-citationHerdy, J. R., Traxler, L., Agarwal, R. K., Karbacher, L., Schlachetzki, J. C. M., Boehnke, L., Zangwill, D., Galasko, D., Glass, C. K., Mertens, J., et al. (2022) · Cell Stem Cell · doi:10.1016/j.stem.2022.11.010 · Cited by 208 · see citing works
Simpson, D. J., & Chandra, T. (2021) · Aging Cell · doi:10.1111/acel.13452 · Cited by 182 · see citing works
Traxler, L., Herdy, J. R., Stefanoni, D., Eichhorner, S., Pelucchi, S., Szücs, A., Santagostino, A., Kim, Y., Agarwal, R. K., Schlachetzki, J. C. M., et al. (2022) · Cell Metabolism · doi:10.1016/j.cmet.2022.07.014 · Cited by 179 · see citing works
“, 2018) and observed increased DNA damage repair in old and AD iNs (Huh et al., 2016; Mertens et al., 2021), AD iNs showed a higher demand for NAD that was”
BackgroundTang, Y., Liu, M.-L., Zang, T., & Zhang, C.-L. (2017) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2017.00359 · Cited by 151 · see citing works
“Our results on spinal cord FibiMNs are in general agreement with previous studies showing that aging features are retained in directly reprogrammed brain neurons (Mertens et al., 2015; Huh et al., 2016).”
ResultAbernathy, D. G., Kim, W. K., McCoy, M. J., Lake, A. M., Ouwenga, R., Lee, S. W., Xing, X., Li, D., Lee, H. J., Heuckeroth, R. O., et al. (2017) · Cell Stem Cell · doi:10.1016/j.stem.2017.08.002 · Cited by 145 · see citing works
“These direct conversion modalities may prove to be invaluable in the study of late-onset neurodegenerative diseases because the original age of human fibroblasts is maintained in converted neurons (Huh et al., 2016; Mertens et al., 2015) in contrast to the cellular rejuvenation observed in induced pluripotent stem cel…”
BackgroundSelf-citationDirect neuronal reprogramming: Fast forward from new concepts toward therapeutic approaches
Bocchi, R., Masserdotti, G., & Götz, M. (2021) · Neuron · doi:10.1016/j.neuron.2021.11.023 · Cited by 128 · see citing works
“Direct neuronal reprogramming of human cells maintains many hallmarks of aging, such as epigenetic marks, nuclear lamina, and mitochondrial dysfunction (Horvath, 2013; Huh et al., 2016; Kim et al., 2018; Mertens et al., 2015).”
Advancing models of neural development with biomaterials
Roth, J. G., Huang, M. S., Li, T. L., Feig, V. R., Jiang, Y., Cui, B., Greely, H. T., Bao, Z., Pașca, S. P., & Heilshorn, S. C. (2021) · Nature reviews. Neuroscience · doi:10.1038/s41583-021-00496-y · Cited by 120 · see citing works
A comprehensive resource for induced pluripotent stem cells from patients with primary tauopathies
Karch, C. M., Kao, A. W., Karydas, A., Onanuga, K., Martinez, R., Argouarch, A., Wang, C., Huang, C., Sohn, P. D., Bowles, K. R., et al. (2019) · Stem Cell Reports · doi:10.1016/j.stemcr.2019.09.006 · Cited by 119 · see citing works
“In contrast, fibroblasts directly reprogrammed into neurons retain their aging characteristics such as DNA methylation (Huh et al., 2016; Maherali et al., 2007; Mertens et al., 2015).”
BackgroundKim, Y., Zheng, X., Ansari, Z., Bunnell, M. C., Herdy, J. R., Traxler, L., Lee, H., Paquola, A. C. M., Blithikioti, C., Ku, M., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.04.105 · Cited by 117 · see citing works
“study of age-related neurodegenerative diseases (Huh et al., 2016; Mertens et al., 2015; Tang et al., 2017).”
BackgroundInfluentialDrouin‐Ouellet, J., Lau, S., Brattås, P. L., Ottosson, D. R., Pircs, K., Grassi, D. A., Collins, L., Vuono, R., Sjöland, A. A., Westergren‐Thorsson, G., et al. (2017) · EMBO Molecular Medicine · doi:10.15252/emmm.201607471 · Cited by 105 · see citing works
“In addition, recent studies have also demonstrated that the resulting iNs, unlike iPSCs, maintain the aging signature of the donor, making iNs ideal candidates for modeling neuronal pathology in late-onset diseases (Mertens et al , 2015; Huh et al , 2016).”
Barák, M., Fedorová, V., Pospíšilová, V., Raška, J., Vochyánová, S., Sedmík, J., Hříbková, H., Klímová, H., Váňová, T., & Bohačiaková, D. (2022) · Stem Cell Reviews and Reports · doi:10.1007/s12015-021-10254-3 · Cited by 100 · see citing works
“Importantly, avoiding the iPSCs stage, transdifferentiated iNs were shown to conserve the agerelated epigenetic landscape and other cellular properties from the cell of origin [138, 140].”
BackgroundOh, Y. M., Lee, S. W., Kim, W. K., Chen, S., Church, V. A., Cates, K., Li, T., Zhang, B., Dolle, R. E., Dahiya, S., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01185-4 · Cited by 100 · see citing works
Self-citationLeigh Syndrome: A Tale of Two Genomes
Bakare, A. B., Lesnefsky, E. J., & Iyer, S. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.693734 · Cited by 101 · see citing works
Traumatic Stress and Accelerated Cellular Aging: From Epigenetics to Cardiometabolic Disease
Wolf, E. J., & Morrison, F. G. (2017) · Current Psychiatry Reports · doi:10.1007/s11920-017-0823-5 · Cited by 95 · see citing works
Proteostasis and lysosomal repair deficits in transdifferentiated neurons of Alzheimer’s disease
Chou, C.-C., Vest, R., Prado, M. A., Wilson-Grady, J., Paulo, J. A., Shibuya, Y., Moran-Losada, P., Lee, T.-T., Luo, J., Gygi, S. P., et al. (2025) · Nature Cell Biology · doi:10.1038/s41556-025-01623-y · Cited by 94 · see citing works
Huntington’s Disease Pathogenesis Is Modified In Vivo by Alfy/Wdfy3 and Selective Macroautophagy
Fox, L. M., Kim, K., Johnson, C. W., Chen, S., Croce, K. R., Victor, M. B., Eenjes, E., Bosco, J. R., Randolph, L. K., Dragatsis, I., et al. (2020) · Neuron · doi:10.1016/j.neuron.2019.12.003 · Cited by 76 · see citing works
“Recently, an HD patient fibroblast model from which medium spiny neurons (MSNs) are generated through direct neuronal conversion (Huh et al., 2016; Mertens et al., 2015) was shown to demonstrate an aggregation phenotype of endogenous mHtt, in the absence of extreme polyQ expansions that are rarely observed in the pati…”
BackgroundModeling late-onset Alzheimer’s disease neuropathology via direct neuronal reprogramming
Sun, Z., Kwon, J.-S., Ren, Y., Chen, S., Walker, C. K., Lu, X., Cates, K., Karahan, H., Sviben, S., Fitzpatrick, J. A. J., et al. (2024) · Science · doi:10.1126/science.adl2992 · Cited by 77 · see citing works
“These results underscore the potential of 3D neuronal reprogramming to model age-dependent A β deposition in LOAD neurons.”
Long Non-Coding RNAs in Neuronal Aging
Fernandes, D. P., Bitar, M., Jacobs, F. M. J., & Barry, G. (2018) · Non-Coding RNA · doi:10.3390/ncrna4020012 · Cited by 75 · see citing works
“Upregulated in the hippocampus of old mice [167]; downregulated in old induced striatal medium spiny neurons [168].”
Lee, S. W., Oh, Y. M., Lu, Y.-L., Kim, W. K., & Yoo, A. S. J. (2018) · Developmental Cell · doi:10.1016/j.devcel.2018.06.007 · Cited by 73 · see citing works
The Link Between Epigenetic Clocks for Aging and Senescence
Wagner, W. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00303 · Cited by 69 · see citing works
“Additional commonalities of senescence and aging include alteration of cellular morphology, metabolic changes, loss of differentiation potential, activation of the p53/p21CIP1 and p16INK4A/pRb signaling pathways, increased senescenceassociated β-galactosidase activity (SA-β-gal), formation of senescence-associated het…”
BackgroundDeconstructing Stepwise Fate Conversion of Human Fibroblasts to Neurons by MicroRNAs
Cates, K., McCoy, M. J., Kwon, J.-S., Liu, Y., Abernathy, D. G., Zhang, B., Liu, S., Gontarz, P., Kim, W. K., Chen, S., et al. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2020.08.015 · Cited by 67 · see citing works
Self-citationCapano, L. S., Sato, C., Ficulle, E., Yu, A., Horie, K., Kwon, J.-S., Burbach, K. F., Barthélemy, N. R., Fox, S. G., Karch, C. M., et al. (2022) · Cell Stem Cell · doi:10.1016/j.stem.2022.04.018 · Cited by 65 · see citing works
Self-citationHerdy, J., Schafer, S., Kim, Y., Ansari, Z., Zangwill, D., Ku, M., Paquola, A., Lee, H., Mertens, J., & Gage, F. H. (2019) · eLife · doi:10.7554/elife.41356 · Cited by 64 · see citing works
Mechanisms, pathways and strategies for rejuvenation through epigenetic reprogramming
Cipriano, A., Moqri, M., Maybury‐Lewis, S. Y., Rogers-Hammond, R., de Jong, T. A., Parker, A., Rasouli, S., Schöler, H. R., Sinclair, D. A., & Sebastiano, V. (2023) · Nature Aging · doi:10.1038/s43587-023-00539-2 · Cited by 65 · see citing works
Gatto, N., Dos Santos Souza, C., Shaw, A. C., Bell, S. M., Myszczynska, M. A., Powers, S., Meyer, K., Castelli, L. M., Karyka, E., Mortiboys, H., et al. (2021) · Aging Cell · doi:10.1111/acel.13281 · Cited by 58 · see citing works
“…recent studies have shown that neurons directly reprogrammed from fibroblasts without the use of pluripotency factors retain ageing signatures compared to induced pluripotent stem cells (iPSC)-derived neurons (Huh et al., 2016; Mertens et al., 2015; Tang et al., 2017; Victor et al., 2018).”
BackgroundSheng, C., Jungverdorben, J., Wiethoff, H., Lin, Q., Flitsch, L. J., Eckert, D., Hebisch, M., Fischer, J., Kesavan, J., Weykopf, B., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06398-5 · Cited by 58 · see citing works
Direct Neuronal Reprogramming: Bridging the Gap Between Basic Science and Clinical Application
Vasan, L., Park, E., David, L. A., Fleming, T., & Schuurmans, C. J. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.681087 · Cited by 60 · see citing works
“…cells DMEM/F12 BDNF, GDNF, heparin, IGF1, RA, SHH, N2 cAMP, purmorphamine Li et al., 2008 Human adipose tissue derived stem cells DMEM FGF2 Forskolin Jang et al., 2010 #71 Human mesenchymal stem cells NSA- basal medium Br-cAMP, dorsomorphin, RG108, rolipram TSA Funk and Alexanian, 2013 Human…”
BackgroundTranscriptional dynamics of murine motor neuron maturation in vivo and in vitro
Patel, T., Hammelman, J., Aziz, S., Jang, S., Closser, M., Michaels, T. L., Blum, J. A., Gifford, D. K., & Wichterle, H. (2022) · Nature Communications · doi:10.1038/s41467-022-33022-4 · Cited by 56 · see citing works
Next‐generation disease modeling with direct conversion: a new path to old neurons
Traxler, L., Edenhofer, F., & Mertens, J. (2019) · FEBS Letters · doi:10.1002/1873-3468.13678 · Cited by 55 · see citing works
Dissecting Alzheimer's disease pathogenesis in human 2D and 3D models
Cenini, G., Hebisch, M., Iefremova, V., Flitsch, L. J., Breitkreuz, Y., Tanzi, R. E., Kim, D. Y., Peitz, M., & Brüstle, O. (2020) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2020.103568 · Cited by 56 · see citing works
hiPSCs for predictive modelling of neurodegenerative diseases: dreaming the possible
Cervo, P. R. D. V., Besusso, D., Conforti, P., & Cattaneo, E. F. (2021) · Nature Reviews Neurology · doi:10.1038/s41582-021-00465-0 · Cited by 56 · see citing works
Transcription Factor-Based Fate Specification and Forward Programming for Neural Regeneration
Flitsch, L. J., Laupman, K. E., & Brüstle, O. (2020) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2020.00121 · Cited by 54 · see citing works
Drouin‐Ouellet, J., Pircs, K., Barker, R. A., Jakobsson, J., & Parmar, M. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00530 · Cited by 54 · see citing works
“Moreover, they show that the aging signature is maintained through their microRNA expression profile and increased oxidative stress levels (Huh et al., 2016).”
BackgroundInfluentialPircs, K., Drouin‐Ouellet, J., Horváth, V., Gil, J., Rezeli, M., Garza, R., Grassi, D. A., Sharma, Y., St‐Amour, I., Harris, K. L., et al. (2021) · Brain · doi:10.1093/brain/awab473 · Cited by 53 · see citing works
Cellular reprogramming as a tool to model human aging in a dish
Pitrez, P. R., Monteiro, L. M., Borgogno, O., Nissan, X., Mertens, J., & Ferreira, L. (2024) · Nature Communications · doi:10.1038/s41467-024-46004-5 · Cited by 49 · see citing works
Berry, B. J., Smith, A. S. T., Young, J. E., & Mack, D. L. (2018) · Cells Tissues Organs · doi:10.1159/000493018 · Cited by 47 · see citing works
“Such methods of direct conversion have been shown to maintain multiple epigenetic age-associated signatures when converted from fibroblast to neuron [Huh et al., 2016].”
MethodTargeting Adult Neurogenesis to Optimize Hippocampal Circuits in Aging
McAvoy, K. M., & Sahay, A. (2017) · Neurotherapeutics · doi:10.1007/s13311-017-0539-6 · Cited by 44 · see citing works
“The generation of human hippocampal neurons through direct reprogramming of fibroblasts, or directed differentiation of induced pluripotent stem cells, holds promise to delineate the neurobiological changes in aging at a cellular level [224, 225].”
BackgroundGómez-Verján, J. C., Vázquez-Martínez, E. R., Rivero-Segura, N. A., & Medina-Campos, R. H. (2018) · Human Genetics · doi:10.1007/s00439-018-1955-3 · Cited by 45 · see citing works
Human in vitro models for understanding mechanisms of autism spectrum disorder
Gordon, A., & Geschwind, D. H. (2020) · Molecular Autism · doi:10.1186/s13229-020-00332-7 · Cited by 43 · see citing works
“These iNs retain many of the epigenetic marks of the source tissue [44, 45] which can capture the epigenetic signature of aging.”
BackgroundMethodDrouin‐Ouellet, J., Legault, E. M., Nilsson, F., Pircs, K., Bouquety, J., Petit, F., Shrigley, S., Birtele, M., Pereira, M., Storm, P., et al. (2022) · Stem Cell Reports · doi:10.1016/j.stemcr.2022.08.010 · Cited by 47 · see citing works
“Stem Cell Repor This is an open access article under the C chondrial defects (Huh et al., 2016; Kim et al., 2018; Mertens et al., 2015, 2021; Tang et al., 2017).”
BackgroundYang, G., & Shcheglovitov, A. (2019) · Developmental Dynamics · doi:10.1002/dvdy.100 · Cited by 44 · see citing works
“Importantly, neurons produced from fibroblasts maintain age-related epigenetic marks, which makes them particularly suited for modeling later-onset neurodegenerative disorders.(104,105) In general, TF-based reprogramming of stem cells involves two simple steps: first, infection of stem cells with a combination of TFs…”
BackgroundMechanistic Insights Into MicroRNA-Induced Neuronal Reprogramming of Human Adult Fibroblasts
Lu, Y.-L., & Yoo, A. S. J. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00522 · Cited by 41 · see citing works
“, 2013), thereby retaining the age signatures of starting fibroblasts including the epigenetic clock (Horvath, 2013), ageassociated changes in transcriptome and microRNAs, reactive oxygen species (ROS) levels, DNA damage and telomere lengths (Mertens et al., 2015; Huh et al., 2016; Tang et al., 2017).”
BackgroundStem Cell Therapies in Alzheimer’s Disease: Applications for Disease Modeling
Si, Z., & Wang, X. (2021) · Journal of Pharmacology and Experimental Therapeutics · doi:10.1124/jpet.120.000324 · Cited by 41 · see citing works
“The “bioreactors” used in culture may also improve the health of the cells (Marion et al., 2009; Corti et al., 2012; Baxter et al., 2015; Huh et al., 2016; Mertens et al., 2018).”
BackgroundChanoumidou, K., Hernández-Rodríguez, B., Windener, F., Thomas, C., Stehling, M., Mozafari, S., Albrecht, S., Ottoboni, L., Antel, J., Kim, K.-P., et al. (2021) · Stem Cell Reports · doi:10.1016/j.stemcr.2021.03.001 · Cited by 39 · see citing works
“, 2008), directly converted cells maintainmany features of aging (Huh et al., 2016;Mertens et al., 2015).”
BackgroundHuman fibroblast and stem cell resource from the Dominantly Inherited Alzheimer Network
the Dominantly Inherited Alzheimer Network (DIAN), Karch, C. M. M., Hernández, D., Wang, J., Marsh, J. A., Hewitt, A. W., Hsu, S., Norton, J. B., Levitch, D., Donahue, T. A., et al. (2018) · Alzheimer s Research & Therapy · doi:10.1186/s13195-018-0400-0 · Cited by 37 · see citing works
The application of in vitro ‐derived human neurons in neurodegenerative disease modeling
D’Souza, G. X., Rose, S. E., Knupp, A., Nicholson, D. A., Keene, C. D., & Young, J. E. (2020) · Journal of Neuroscience Research · doi:10.1002/jnr.24615 · Cited by 35 · see citing works
“Indeed, several studies have shown that iNs appear to retain transcriptomic and epigenetic characteristics similar to the aged donor somatic cells (Huh et al., 2016; Mertens et al., 2015).”
BackgroundTelomere shortening induces aging-associated phenotypes in hiPSC-derived neurons and astrocytes
Harley, J., Santosa, M. M., Ng, C. Y., Grinchuk, O. V., Hor, J., Liang, Y., Lim, V. J. W., Tee, W., Ong, D. S. T., & Ng, S. (2023) · Biogerontology · doi:10.1007/s10522-023-10076-5 · Cited by 35 · see citing works
“Fibroblast-derived iNs preserve features of human aging including transcriptomic, epigenetic, mitochondrial and nuclear pore changes (Herdy et al. 2019; Huh et al. 2016; Kim et al. 2018; Mertens et al. 2015).”
BackgroundGhaffari, L., Starr, A., Nelson, A. T., & Sattler, R. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00056 · Cited by 34 · see citing works
“also showed that direct conversion using this protocol preserves age-related epigenetic and cellular signatures from the donor, similar to established transcription factor-only methods (Huh et al., 2016).”
BackgroundResultInfluentialAversano, S., Caiazza, C., & Caiazzo, M. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.1069482 · Cited by 33 · see citing works
Nwanaji‐Enwerem, J. C., Weisskopf, M. G., & Baccarelli, A. (2018) · Ageing Research Reviews · doi:10.1016/j.arr.2018.04.005 · Cited by 29 · see citing works
Precision Medicine in Rare Diseases
Villalón-García, I., Álvarez-Córdoba, M., Suarez-Rivero, J. M., Povea-Cabello, S., Talaverón-Rey, M., Suárez-Carrillo, A., Munuera-Cabeza, M., & Sánchez-Alcázar, J. A. (2020) · Diseases · doi:10.3390/diseases8040042 · Cited by 33 · see citing works
“In addition, iNs, unlike iPSCs, maintain the ageing [30] and the epigenetic marks of the donor [31,32], making them excellent candidates for modelling neuronal pathophysiology in age-related disorders.”
BackgroundRose, S. E., Frankowski, H., Knupp, A., Berry, B. J., Martinez, R. A., Dinh, S. Q., Bruner, L. T., Willis, S. L., Crane, P. K., Larson, E. B., et al. (2018) · Journal of Neuropathology & Experimental Neurology · doi:10.1093/jnen/nly013 · Cited by 29 · see citing works
“Finally, because reprogramming of somatic cells to hiPSCs erases epigenetic marks (12) we tested whether leptomeningeal cells are a viable starting cell source for direct neuron conversion.”
BackgroundInduced pluripotent stem cell‐based modeling of mutant LRRK 2‐associated Parkinson's disease
Weykopf, B., Haupt, S., Jungverdorben, J., Flitsch, L. J., Hebisch, M., Liu, G., Suzuki, K., Belmonte, J. C. I., Peitz, M., Blaess, S., et al. (2019) · European Journal of Neuroscience · doi:10.1111/ejn.14345 · Cited by 29 · see citing works
“Besides transcriptomic signatures, iN preserve the donor cell's age‐associated epigenetic memory and other aging hallmarks such as shortened telomere lengths, elevated ROS levels and accumulated DNA damage (Huh et al., 2016).”
BackgroundMicroRNA Roles in Cell Reprogramming Mechanisms
Pascale, E., Caiazza, C., Paladino, M., Parisi, S., Passaro, F., & Caiazzo, M. (2022) · Cells · doi:10.3390/cells11060940 · Cited by 30 · see citing works
Sato, M., Takizawa, H., Nakamura, A., Turner, B. J., Shabanpoor, F., & Aoki, Y. (2019) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2019.00297 · Cited by 29 · see citing works
The Importance of Non-neuronal Cell Types in hiPSC-Based Disease Modeling and Drug Screening
Gonzalez, D. M., Gregory, J. K., & Brennand, K. (2017) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2017.00117 · Cited by 26 · see citing works
“…is an essential part of the cellular reprogramming process; while important epigenetic markers associated with complex genetic diseases may be lost during hiPSC reprogramming, this does not seem to occur to the same extent during neuronal induction (Huh et al., 2016; Mertens et al., 2016).”
BackgroundSimple Generation of a High Yield Culture of Induced Neurons from Human Adult Skin Fibroblasts
Shrigley, S., Pircs, K., Barker, R. A., Parmar, M., & Drouin‐Ouellet, J. (2018) · Journal of Visualized Experiments · doi:10.3791/56904 · Cited by 26 · see citing works
Impact of traumatic brain injury on amyotrophic lateral sclerosis: from bedside to bench
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“Recent developments in direct neuronal transdifferentiation from adult somatic cell types appear to preserve aspects of cellular age (Abernathy et al. 2017; Huh et al. 2016; Victor et al. 2018; Yoo et al. 2011) and may facilitate the development of more accurate in vitro models of TBI pathogenesis.”
BackgroundCell reprogramming: Therapeutic potential and the promise of rejuvenation for the aging brain
López-León, M., Outeiro, T. F., & Goya, R. G. (2017) · Ageing Research Reviews · doi:10.1016/j.arr.2017.09.002 · Cited by 25 · see citing works
“Using a miRNAbased cellular reprogramming approach, human fibroblasts obtained from donors ranging from neonates to near centenarians could be efficiently converted into neurons that retain multiple age-associated signatures (Huh et al., 2016).”
Aging-relevant human basal forebrain cholinergic neurons as a cell model for Alzheimer’s disease
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“…whether it would be feasible to reduce the RCAN1 adult fibroblasts to neurons has been shown to propagate chronological age-related characteristics such as epigenetic cellular age stored in starting fibroblasts, thereby generating neurons that mimic the epigenetic age of fibroblast donors 6 .”
InfluentialGeneration of Human Neurons by microRNA-Mediated Direct Conversion of Dermal Fibroblasts
Church, V. A., Cates, K. L., Capano, L. S., Aryal, S., Kim, W. K., & Yoo, A. S. J. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-1084-8_6 · Cited by 24 · see citing works
Screening Platforms for Genetic Epilepsies—Zebrafish, iPSC-Derived Neurons, and Organoids
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Neuroprotective Effects of Cryptotanshinone in a Direct Reprogramming Model of Parkinson’s Disease
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The iNs and Outs of Direct Reprogramming to Induced Neurons
Carter, J. L., Halmai, J., & Fink, K. (2020) · Frontiers in Genome Editing · doi:10.3389/fgeed.2020.00007 · Cited by 19 · see citing works
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“…the differentiation process [103]; and 6) reprogramming into iPSCs can reset cellular age of lineage-speci fi c derived cells, such as neurons [104], and/or induces mitochondrial rejuvenation [105], thereby no longer exhibiting the original pathophysiological characteristics of a PMD.…”
BackgroundMcCaughey‐Chapman, A., & Connor, B. (2023) · Journal of Neuroscience Research · doi:10.1002/jnr.25173 · Cited by 21 · see citing works
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“It is hypothesized that the conservation of epigenetic markers may be achieved through direct reprogramming strategies [43] if donor-specific epigenetic profiles, such as with aging [44, 45], are of interest.”
BackgroundPrecision medicine in pantothenate kinase-associated neurodegeneration
Álvarez-Córdoba, M., Paz, M. V., Villalón-García, I., Povea-Cabello, S., Suarez-Rivero, J. M., Talaverón-Rey, M., Abril-Jaramillo, J., Vintimilla-Tosi, A. B., & Sánchez-Alcázar, J. A. (2019) · Neural Regeneration Research · doi:10.4103/1673-5374.251203 · Cited by 21 · see citing works
“In addition, iNs, unlike iPSCs, maintain the ageing (Mertens et al., 2015) and the epigenetic marks of the donor (Horvath, 2013; Huh et al., 2016), making them excellent candidates for modelling neuronal pathophysiology in age-related disorders.”
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Human neurons to model aging: A dish best served old
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“A recent study found that the epigenetic age (or more precisely termed ‘DNA methylation (DNAm) age’), a distinctive pattern of DNA methylation marks from which a donor’s age can be predicted, was the same between iNs and their parental fibroblast [30].”
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“While reprogramming of fibroblasts into hiPSCs erases age-related epigenetic marks and gene expression profiles, these can be at least partially maintained by inducing patient somatic cells directly into neurons (Mertens et al., 2015; Huh et al., 2016).”
BackgroundDirect Conversion of Human Fibroblasts to Induced Neurons
Zhou-Yang, L., Eichhorner, S., Karbacher, L., Böhnke, L., Traxler, L., & Mertens, J. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1601-7_6 · Cited by 17 · see citing works
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“The lack of cellular rejuvenation, shorter reprogramming durations and reduced labor required for iN generation are attractive for disease modeling.(14,15) However, iNs do not follow successive stages of neurodevelopment.”
BackgroundSchlachetzki, J. C. M., Toda, T., & Mertens, J. (2020) · Experimental Gerontology · doi:10.1016/j.exger.2020.110876 · Cited by 18 · see citing works
“Unlike iPSC-derived neurons, iNs show mature neuronal 5-hmC methylation and show transcriptomic aging signatures and preservation of their donors’ DNAm clock ages (Table 1)(Herdy et al., 2019; Huh et al., 2016).”
BackgroundCell reprogramming: methods, mechanisms and applications
Zhu, F., & Nie, G. (2025) · Cell Regeneration · doi:10.1186/s13619-025-00229-x · Cited by 24 · see citing works
“…(MET) (Li et al. 2010; Samavarchi-Tehrani et al. 2010), (4) a metabolic remodeling from oxidative phosphorylation to glyco-lysis-based metabolism (Zhang et al. 2016; Zhu et al. 2024), (5) the activation of early pluripotency-associ-ated genes (such as alkaline phosphatase and SSEA-1 in mouse;…”
Kajtez, J., Nilsson, F., Laurin, K., Bruzelius, A., Cepeda-Prado, E., Birtele, M., Barker, R. A., Herborg, F., Ottosson, D. R., Storm, P., et al. (2025) · Science Advances · doi:10.1126/sciadv.adq7855 · Cited by 16 · see citing works
“Besides being an invaluable tool to create patient and disease-specific neurons for modeling of age-associated neurological disorders ( 11 – 15 ), direct reprogramming offers a promising nonpluripotent cell source for personalized transplantation-based therapies for neurodegenerative diseases.”
Wheeler, H. B., Madrigal, A. A., & Chaim, I. A. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2317860121 · Cited by 17 · see citing works
“Excitingly, a recent technological advancement that can help overcome this limitation is the direct differentia - tion of fibroblasts to desired neuronal populations (143, 144).”
A cellular identity crisis? Plasticity changes during aging and rejuvenationPreprint
Gorelov, R. A., & Hochedlinger, K. (2024) · Genes & Development · doi:10.1101/gad.351728.124 · Cited by 18 · see citing works
“2; Horvath 2013; Huh et al. 2016; Sheng et al. 2018).”
Szabo, L., Lejri, I., Grimm, A., & Eckert, A. (2024) · Antioxidants · doi:10.3390/antiox13121482 · Cited by 17 · see citing works
“Specifically, common findings in humans, animals, and reprogrammed neurons have demonstrated an age-related decrease in the antioxidative defense system [42,54,55] together with heightened ROS levels [56,57], leading to an augmentation in oxidative stress [58,59].”
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Neurodegeneration in a dish: advancing human stem-cell-based models of Alzheimer’s disease
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Habekost, M., Qvist, P., Denham, M., Holm, I. E., & Jørgensen, A. L. (2021) · Molecular Neurobiology · doi:10.1007/s12035-020-02258-w · Cited by 14 · see citing works
“In contrast, direct conversion of fibroblasts into induced neurons (iNs) circumvents the pluripotent intermediate state, and it has been demonstrated that iNs retain the transcriptomic and epigenetic age of the starting cells [29, 35].”
BackgroundDirect Reprogramming of Somatic Cells to Neurons: Pros and Cons of Chemical Approach
Mollinari, C., & Merlo, D. (2021) · Neurochemical Research · doi:10.1007/s11064-021-03282-5 · Cited by 15 · see citing works
Human iPSC-Derived Neurons as A Platform for Deciphering the Mechanisms behind Brain Aging
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“Moreover, in iMSNs, the length of telomeres is unaltered, and it corresponds to the telomere length of the starting fibroblasts, which is related to the donor’s age [4].”
BackgroundInfluentialGenetic and Epigenetic Interplay Define Disease Onset and Severity in Repeat Diseases
Barbé, L., & Finkbeiner, S. M. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.750629 · Cited by 14 · see citing works
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BackgroundAdvances in mt-tRNA Mutation-Caused Mitochondrial Disease Modeling: Patients’ Brain in a Dish
Povea-Cabello, S., Paz, M. V., Suarez-Rivero, J. M., Álvarez-Córdoba, M., Villalón-García, I., Talaverón-Rey, M., Suárez-Carrillo, A., Munuera-Cabeza, M., & Sánchez-Alcázar, J. A. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2020.610764 · Cited by 14 · see citing works
Applications of Functional Genomics for Drug Discovery
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Research models to study lewy body dementia
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“Direct neuronal reprogramming, by which a neuron is formed via direct conversion from a somatic cell without going through a pluripotent intermediate stage, allows the possibility to generate patient-derived neurons that maintain the aging and epigenetic signatures of the donor [128, 129].”
Stem Cell Models for Context-Specific Modeling in Psychiatric Disorders
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Transcriptomic reprogramming for neuronal age reversal
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- Authors
- Huh, C. J., Zhang, B., Victor, M. B., Dahiya, S., Batista, L. F., Horvath, S., & Yoo, A. S.
- Affiliations
- Washington University in St. Louis (US)
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, United States
- University of California, Los Angeles (US)
- Corresponding author
- Yoo, Andrew S
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2016-09-20
- Volume
- 5
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC5067114
- OpenAlex
- W2521543069
- Cited by
- 213
- References
- 57
- Citations by year
- 2026: 16 · 2025: 18 · 2024: 23 · 2023: 22 · 2022: 17 · 2021: 33 · 2020: 29 · 2019: 17 · 2018: 26 · 2017: 11
- FWCI
- 9.35
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Commons@Becker (Washington University School of Medicine) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institute on Drug Abuse (R25 DA027995)
- National Institutes of Health (K99/R00, 4R00HL114732-03, 1U34AG051425-01, 5R01, AG042511-02, DP2NS083372-01)
- Washington University in St. Louis (DDRCC, NIDDK P30 DK052574)
- Ellison Medical Foundation (AG-NS-0878-12)
- Cure Alzheimer's Fund
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Pluripotent Stem Cells Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Keywords
- neuronal aging, fibroblast-to-neuron conversion, epigenetic clocks, DNA methylation, age-related gene expression, oxidative stress, DNA damage, telomere length, neurodegenerative diseases, human neurons
- MeSH terms
- Aging, Cytological Techniques, DNA Damage, Fibroblasts, Humans, Neurons, Telomere, Oxidative Stress, Gene Expression Profiling, MicroRNAs, Epigenesis, Genetic, Cell Transdifferentiation
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