• Users Online: 48
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 

 Table of Contents  
Year : 2018  |  Volume : 3  |  Issue : 2  |  Page : 42-47

Modeling neurodegenerative diseases by human pluripotent stem cell-induced brain organoid

1 Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
2 Program in Biological Sciences in Dental Medicine, Harvard School of Dental Medicine, Boston, MA, USA
3 Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
4 Department of Wounds and Burns Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
5 ApreX, Inc., 120 Wyllis Ave, U216, Everett, MA, USA

Date of Submission15-Mar-2018
Date of Acceptance13-May-2018
Date of Web Publication27-Jun-2018

Correspondence Address:
Rui Sun
ApreX, Inc., 120 Wyllis Ave, U216, Everett, MA
Xu Luo
Department of Wounds and Burns Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ts.ts_4_18

Rights and Permissions

Neurodegenerative disease (ND) contains a range of conditions which are primarily characterized by progressive neuronal dysfunction and loss. ND is particularly difficult to cure, due to the vulnerability of the nervous system. Currently, few genes and pathways are found to be related to ND. However, no solitary mechanism appears to be primary in neurodegeneration, and these pathogenic mechanisms likely act synergistically through complex interactions to promote neurodegeneration. Moreover, the existing treatment is mainly focusing on alleviating the symptoms of the disease. Furthermore, recent studies reveal considerable overlaps of symptomatology and genetic risks across the disease subtypes by detailed studies at cellular, molecular and genetic level. To better understand the etiology and pathogenesis of ND, study of the abnormalities at patient level is most ideal. However, direct access to the brain tissues from healthy individuals and patients is very limited. Therefore, an alternative experimental model is required to study the mechanism of ND. The most commonly used models are animal models, including Caenorhabditis elegans, Drosophila, zebrafish, and genetically modified mice. However, animal models also have their limitations including partial recapitulation of the disease features and difficulties in modifying disease genes. The recent development in three-dimensional (3D) brain organoids might provide a better experimental model to study ND, because 3D brain organoid system carries great potential to expand the range of both physiological and pathological features that can be found during the development of disease, enabling higher order investigation of mechanism and functionality.

Keywords: Disease modeling, organoid, stem cell

How to cite this article:
Tian F, Hao J, Hu L, Luo X, Sun R. Modeling neurodegenerative diseases by human pluripotent stem cell-induced brain organoid. Transl Surg 2018;3:42-7

How to cite this URL:
Tian F, Hao J, Hu L, Luo X, Sun R. Modeling neurodegenerative diseases by human pluripotent stem cell-induced brain organoid. Transl Surg [serial online] 2018 [cited 2022 Jan 24];3:42-7. Available from: http://www.translsurg.com/text.asp?2018/3/2/42/235393

  Introduction Top

Current understanding of pathogenic mechanisms underlying neurodegenerative conditions

Neurodegenerative disease (ND) is particularly difficult to cure due to the vulnerability of the nervous system.[1] Neurodegeneration covers a wide spectrum of neurological disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), Huntington's disease (HD), progressive supranuclear palsy, multiple system atrophy, and spinal muscular atrophy, among others.[2],[3]

Common pathological features shared among the neurodegenerative disorders including neuronal cell death, gliosis, atrophy, and pathological protein inclusion bodies.[4] The previous study has found that HD is a genetic disorder caused by the cytosine-adenosine-guanine (CAG) repeat expansion in the huntington gene.[5] ALS, AD, and PD are more commonly sporadic in nature; however, specific gene mutations can cause autosomal dominant or autosomal recessive forms of these disorders, often starting earlier in life than sporadic forms of these illnesses.[6],[7]

In addition, genetic factors are recognized to play a role in the risk of ND. For instance, amyloid-beta precursor protein (APP), presenilin 1, and presenilin 2 have been reported to be associated with most autosomal dominant familial AD.[8] However, for most of the NDs, both the environmental and genetic differences may act as risk factors.[9] For instance, PD might be the result of a complicated interaction of genetic and environmental factors.[10] ALS, also known as Lou Gehrig's disease, is a progressive and fatal ND characterized by dysfunction and loss of motor neurons.[2],[11] ALS patients generally suffer from a gradually spreading paralysis and often die of terminal respiratory failure or pneumonia, within only 3–5 years of diagnosis.[11],[12] Although there is nearly no cure to ALS currently, an increasing number of mutated genes have been identified to be associated with both familial and sporadic ALS, and more computational approaches combined with genome-wide association studies seems to further spur this trend.[13] The identified mutations can be seen in genes involved in completely distinct pathways, including SOD1, TDP43, FUS, and C9ORF72.[14]

While the cause of each neurodegenerative disorder differs, they do share commonalities in cellular pathway and mechanism involved in neurodegeneration once the disease process has been initiated.[9],[15] For many neurodegenerative disorders, mechanisms leading to cell death include mitochondrial dysfunction, oxidative stress, loss of growth factors, proteasomal dysfunction, autophagic/lysosomal dysfunction, excitotoxicity, protein aggregation, prion-like spread, and neuroinflammation.[15],[16] However, no solitary mechanism appears to be primary in neurodegeneration, and these pathogenic mechanisms likely act synergistically through complex interactions to promote neurodegeneration.[16]

Current therapeutic agents designed to correct the biochemical or genetic defects are limited

Current treatment options are aiming at treating the symptoms of the disease. For several of the neurodegenerative disorders, these therapies can significantly improve patients' lifespan and life quality.[17] However, no current therapeutic intervention for any of the neurodegenerative disorders attenuate or stop neurodegeneration, and patients with ND progressively get worse. Ultimately, better understanding of the mechanisms underlying neurodegeneration should lead to better therapeutic options.

Therapeutic agents are mostly tested in animal models only; increasing need for experimental models in neurodegenerative diseases

NDs are characterized by progressive neuronal dysfunction and loss.[9] The classification of the disease is currently based on the clinical symptoms and aberrant protein modifications and accumulations.[5],[9],[18] However, there are considerable overlaps of symptomatology and genetic risks across the disease subtypes, indicating the interrelation of these disorders. As the phenotypes of NDs are studied in ever-greater detail at cellular, molecular, and genetic level, it becomes clear that an individual clinically defined disease shows great heterogeneity across each of the disease subtypes.[9],[19] Therefore, to better understand the etiology and pathogenesis of complex diseases such as ND, study of the abnormalities that affect the brains of patients with neurodegenerative symptoms at a higher level is increasingly needed.

The most ideal model to study ND pathology would be the human brain. However, direct access to the brain tissues of healthy individuals and patients is very limited. The availability of such brain samples are often restricted to some small specific regions, and most tissues are postmortem without neural activity.[20] Thus, far, conventional experimental animal models, including Caenorhabditis elegans, Drosophila, zebrafish, and genetically modified mice, are the most commonly used models to elucidate the role of mutant genes in the development and progress of the disease.[20],[21] However, the findings from those studies are limited and usually require further verification in humans.

ND is largely age-related disorders in humans. In nonhuman species, on the other hand, ND represents an extremely rare condition.[9],[22] However, aged mammals may develop neuropathological lesions such as β-amyloidosis or neurofibrillary tangles.[23],[24] For example, genetically modified animal models carrying the human genes, found to be mutated in familial cases of ND, were generated to study the mechanism of onset and progression of such pathologies (e.g., AD, PD, FTD, or ALS).[9]

Nevertheless, animal models also have their limitations. One of the major shortcomings of the available animal models is that they only partially recapitulate the complexity of the clinical features found in humans.[23] The most animals have inherent differences in the brain compared to human beings, such as the structure, function, and development of the brain.[22] Many NDs, including autism spectrum disorder (ASD), AD, and PD, are caused by a heterogeneous combination of variant alleles and have, therefore, proven difficult to recapitulate in animal models.[25] In addition, many genetic mutations or states are difficult to reproduce in animal models (i.e., large structural rearrangements, polygenic states that require multiple-targeted mutations).[2]

The studies on immunotherapy of AD are generally considered the epitome of the failure of animal studies in the generation of innovative treatments for human patients.[26] The immunotherapy against β-amyloid, which showed some success in APP-transgenic mice, was rapidly tested in humans but had to be discontinued due to the occurrence of meningoencephalitis in a subset of patients.[27] In addition, it could be argued that the animal model had predicted that the immunotherapy would reduce the amyloid burden in the brain parenchyma (also observed in humans); however, the inability of the model to indicate the risk of encephalopathy is questionable.

For instance, the recent announcement by Pfizer that it would shut down its entire research and development programs for AD and PD implies the desperate need of disease models to reliably recapitulate the phenotypes from patients.[28] The failure rate of AD-targeting agents from clinical trial is over 99%.[29] The intrinsic genetic distinction between human and lower animal models limits the interpretation of basic research results from these disease models especially in the investigation of β-amyloid.[30] In addition, the toxicity hypothesis of β-amyloid has always been controversial in the field.[30],[31] On the other hand, however, patient-derived stem cell models carrying AD-related mutations still could not reconstitute complex system level function such as immunity and circulation.[32]

The combination of these factors show that it is necessary to integrate current models with new in vitro systems. There is a need of using human cells as a source of disease modeling to fully recapitulate pathways found in human diseases and obtain reliable response to therapeutics.[33] The incorporation of patient-derived induced pluripotent stem cells (iPSCs), with distinct genetic composition and amenable to large-scale genetic modifications, provides a great resource for ND studies.

  Modeling the Brain from Human Pluripotent Stem Cells Top

Stem cells are characterized by two features: self-renewal and potency to differentiate into other functional cell types.[2] These properties render stem cell technology particularly useful for regenerative medicine. With the emerging technology of human embryonic stem cells (ESCs) and iPSCs, patient-specific stem cell models can now be well constructed to recapitulate the genetic and phenotypical properties of various human diseases.[2],[9] For instance, by introducing the pluripotent genes to the fibroblasts of ALS, carrying specific genetic mutations, we can readily generate a series of disease isogenic lines to study how different mutations contribute to the ALS phenotypes.[9]

With the development of genome editing technology, such as the Clustered Regularly Interspaced Short Palindromic Repeats system, the possibilities of in vitro disease modeling have also been expanded.[34] The reproduction or correction of the mutant allele at one or more loci in patient-derived cells could help in identifying the causal gene/genes among the broader pool of risk alleles. For instance, recent studies have demonstrated that in vitro and in vivo correction of the X-linked disease-causing mutation can rescue the phenotype of Duchenne muscular dystrophy.[35] The isogenic iPSC line created by highly specific targeting of disease-related mutations could also provide a perfect control to study ND mechanism in vitro[Figure 1].[35]
Figure 1: Application of patient-derived induced pluripotent stem cells in two-dimensional and three-dimensional models

Click here to view

However, the biggest challenge for iPSC-based disease modeling, NDs in particular, is to reliably reproduce authentic cell types and to reproducibly mimic the cell–cell interactions and circuit connectivity of the human nervous system. In addition, the generation of developmentally mature cell types can enable disease modeling to surpass the early embryonic stage, which is important for the onset of most NDs. Currently, it is challenging to associate specific in vitro models with a precise developmental stage due to their inherent disorganization and unsynchronized development. However,in vitro models normally reproduce stages of progenitor development, differentiation, neurogenesis, and apoptosis. In the field of NDs, it is necessary to develop robust methods for the recapitulation of more mature tissues to model later-stage pathological events such as neuronal dysfunction and death.

Modeling brain by human pluripotent stem cells in two-dimension and its application

Numerous protocols have been established in the field to direct the differentiation of human pluripotent stem cells (hPSCs) into neuronal cell subtypes.[36] Early in vitro models of neural development from hPSCs involved two-dimensional (2D) culture, making adherent cell systems.[36] For instance, the dual SMAD inhibition method can be used to derive ALS patient-specific motor neurons for disease modeling.[37],[38] The ectopic expression of neurogenin two in hPSCs also provide an accelerated generation of various types of neurons especially useful for the modeling of complex psychiatric diseases such as schizophrenia.[9],[39] In addition, patient-derived neurons can also be generated from direct reprogramming of patient-derived fibroblasts or other terminally differentiated neurons such as induced neuron or induced motor neuron.[36]

Before real-three-dimensional (3D) brain models were developed, this 2D differentiation or reprogramming models had open the avenue to understand the disease-causing mechanism with patient-derived neural cell types.[9] For instance, coculture of motor neurons, differentiated from hPSCs, with glial cell types carrying ALS-causing mutations have been used to successfully dissect the noncell autonomous effects of ALS.[40] Another promising example is the direct reprogramming of astrocytes to dopaminergic neurons, which has provided useful platform to not only investigate PD mechanism but also as well aid functional recovery of mouse models with PD.[41]

Nevertheless, the 2D cultures of hPSCs are conventionally cultured in dishes or flasks. However, in addition to nonspheroids structure, the 2D culture systems usually have low yield and are limited in scalability and reproducibility.[42]

Modeling brain in three-dimensional organoid and its application

In nonadherent culture dishes, pluripotent stem cells have the tendency to aggregate and form 3D spherical structures.[43],[44] In many cases, these self-assembled “cell aggregates” can specify and differentiate into subtypes of cells with organ-specific lineage.[43] Given the fact that they resemble organs regarding cell lineage while the morphology seems strikingly distinct, we normally term them as “organoids”.[43] These 3D brain organoids generated from human ESCs and iPSCs, appear to recapitulate the brain's 3D cytoarchitectural arrangement and provide new opportunities to explore disease pathogenesis in the human brain.

Perhaps, the most common method to generate hPSC-derived 3D brain organoids is serum-free floating culture of embryoid body (EB)-like aggregates.[45],[46],[47] By modifying different region-specific patterning factors, these aggregates can guide the progenitors to particular regional identities.[46] For instance, inhibition of Wnt and TGF-β could promote toward protracted cortical development, while modulation of FGF signaling can control the rostral-caudal polarity of cortical progenitors.[46],[48] The utilization of an extracellular scaffolding matrix method enables neuroepithelium buds to grow and extend and to form cerebral organoids with discrete brain regions including dorsal cortex, ventral forebrain, retina, hippocampus, choroid plexus, and midbrain–hindbrain boundary.[44] To reduce the cost and space of previous cerebral organoids method, Qian et al.[49] developed, a miniaturized spinning bioreactor and modified the EBs culture procedure, which also increased the reproducibility and generated different brain region-specific organoids, including forebrain, midbrain, and hypothalamic organoids. In addition, a novel organoid model called human cortical spheroids (hCSs), made of neurons from deep and superficial cortical layers, were developed and their transcriptional signatures mimic those found during in vivo fetal development.[46] Neurons in hCSs are surrounded by nonreactive astrocytes which facilitate the formation of functional synapses. All of these brain organoids provide various neuronal and glial cell types with 3D cytoarchitectural arrangement to facilitate the study of neural development and neural disease modeling.

hPSC-derived 3D brain organoids have been used to study different neurodevelopmental diseases, including Autosomal recessive primary microcephaly (MCPH), Zika virus infection, and ASD. 3D iPSC-derived brain organoids from patients with MCPH display smaller size, compared to controls, similar to brain size shrinkage seen in patients.[44] Further analysis shows that smaller organoid size is a consequence of impaired proliferation and expansion of the founder progenitor pool and simultaneous premature neuronal differentiation. However, mouse model could not recapitulate MCPH as it did not exhibit an obvious reduction of brain size.[50],[51] In addition to neurodevelopmental diseases, 3D brain organoids have also been used to model early-onset neurologic disease variants such as early-onset AD.[52] 3D brain organoids derived from early-onset familial AD (fAD) patients recapitulated AD phenotypes including β-amyloid aggregation, hyperphosphorylated Tau (pTau), and endosome abnormalities.[53] Furthermore, 3D brain organoids might be of use in facilitating drug screening in neurodegenerative disorders, as demonstrated by reduced amyloid and pTau pathologies in fAD organoids treated with β-and γ-secretase inhibitors.

  Conclusion Top

The promise and challenges of modeling neurodegenerative disease in three-dimensional

3D brain organoid system carries great potential to expand the range of both physiological and pathological features that can be found in the development of disease, enabling higher-order investigation of mechanism and functionality. It also holds great promise by generating broad cellular diversity, which may enable cell-cell interactions,[54] and may recapitulate distinct brain regions.[49]

Particularly, patient-derived iPSCs carrying specific disease mutations can be genetically corrected to generate isogenic line to dissect the mechanisms of the disease.[9] One study generated iPSCs from patients with major psychiatric disorders to uncover a disease-related mutant DISC1 and proved the cellular deficits using several gene-edited isogenic iPS cell lines.[55] Another study utilized patient-derived stem cell model to provide mechanistic insight into gene-environmental interaction in the pathogenesis of PD.[56] The application of high-throughput screening with stem cell models enable drug screening and may boost therapeutics.

However, it is unclear how far the cells and circuits present within the 3D organoids can develop in culture, because most organoid models have been cultured for a relatively short period and have mostly been used to study early developmental events. Many NDs, however, manifest defects in later developmental stages. The current organoid does not have vasculature, which might prevent the organoid from maturation. In addition, most NDs have been found to breakdown the blood-brain barrier, the recapitulation of vasculature can also broaden our understanding of the disease onset and progression of this condition.[57]

Modeling neuromuscular junction and the peripheral nervous system are also a challenge that remain to be elucidated to model the disease pathology and progression. A recent breakthrough on multitissue interaction platform to stimulate human organs and intertissue interactions among heart, liver, and lung might shed light on modeling multitissue interactions in brain system.[58]

Perspectives and closing remarks

The 3D in vitro models hold great potential to study the higher order brain functionality and development. The current self-patterning 3D organoid system can generate broad cellular diversity, which may enable cell–cell interactions. Cell-cell interactions are well-known for tissue maturation, such as neuron-glia interactions, can lead to myelination, synaptogenesis, and circuit maturation. Therefore, the organoid systems can expand the range of features that were established in 2D culture and further have a great potential in modeling complex neural disorders such as the NDs.

So far, the 3D organoid system has not been extensively applied to study ND because of the complexity of its phenotypes. Currently, the cellular composition and the diverse cell types present in the 3D system are still unclear. A comprehensive knowledge in cell type characterization is needed for the application of 3D organoid as a model system especially for NDs. In addition, whether cells and circuits in the 3D system can obtain structural and physiological features of the postnatal brain remains elusive. A major limitation of the current 3D organoid system is the lack of vasculature, which prevents longer culture of the organoid due to limited oxygen and nutrition supply at its center.

Although much remains to be done, it is likely that the use of 3D brain organoid and spheroid models to recapitulate neural diseases will increase in the next few years. Improved maturation and increased diversity will enable the understanding of previously inaccessible mechanisms and processes, which may underlie the pathology seen in patients. In addition, the advancement in protocols that enable spatial and temporal control of patterning factors might lead to more complicated cellular composition and successfully reproduce tissue architecture. Future models with large quantity productions can also incorporate gene edited cell lines or patient-derived iPSCs for high-throughput downstream analysis. With the advancement in technology and analysis methods, the 3D organoid models will generate an unprecedented wealth of data facilitating a closer investigation of neurobiological features underlying disease states and mechanisms of the etiology for NDs.

Financial support and sponsorship


Conflicts of interest

Rui Sun is a cofounder of Aprex, Inc., a start-up for 3D organoid modeling of cancer. The remaining authors declare no competing financial interests.

  References Top

He Z, Höke A. Evolutionary perspectives: Introduction to the special issue on Axon Regeneration Across Species. Exp Neurol 2017;287(Pt3):299.  Back to cited text no. 1
Sances S, Bruijn LI, Chandran S, Eggan K, Ho R, Klim JR, Livesey MR, Lowry E, Macklis JD, Rushton D, Sadegh C, Sareen D, Wichterle H, Zhang SC, Svendsen CN. Modeling ALS with motor neurons derived from human induced pluripotent stem cells. Nat Neurosci 2016;19 (4):542-53.  Back to cited text no. 2
Zhao L, Yuan Y, Li P, Pan J, Qin J, Liu Y, Zhang Y, Tian F, Yu B, Zhou S. miR-221-3p inhibits schwann cell myelination. Neuroscience 2018;379:239-45.  Back to cited text no. 3
Couratier P, Corcia P, Lautrette G, Nicol M, Marin B. ALS and frontotemporal dementia belong to a common disease spectrum. Rev Neurol (Paris) 2017;173 (5):273-9.  Back to cited text no. 4
Walker FO. Huntington's disease. Lancet 2007;369 (9557):218-28.  Back to cited text no. 5
Al-Chalabi A, Jones A, Troakes C, King A, Al-Sarraj S, van den Berg LH. The genetics and neuropathology of amyotrophic lateral sclerosis. Acta Neuropathol 2017;124 (3):339-52.  Back to cited text no. 6
Lesage S, Brice A. Parkinson's disease: From monogenic forms to genetic susceptibility factors. Hum Mol Genet 2009;18(R1):R48-59.  Back to cited text no. 7
Reiss AB, Arain HA, Stecker MM, Siegart NM, Kasselman LJ. Amyloid toxicity in Alzheimer's disease. Rev Neurosci 2018. pii: /j/revneuro.ahead-of-print/revneuro-2017-0063/revneuro-2017-0063.xml.  Back to cited text no. 8
Sandoe J, Eggan K. Opportunities and challenges of pluripotent stem cell neurodegenerative disease models. Nat Neurosci 2013;16 (7):780-9.  Back to cited text no. 9
Kalia LV, Lang AE. Parkinson's disease. Lancet 2015;386 (9996):896-912.  Back to cited text no. 10
Kanning KC, Kaplan A, Henderson CE. Motor neuron diversity in development and disease. Annu Rev Neurosci 2010;33:409-40.  Back to cited text no. 11
O'Brien MR, Whitehead B, Jack BA, Mitchell JD. From symptom onset to a diagnosis of amyotrophic lateral sclerosis/motor neuron disease (ALS/MND): Experiences of people with ALS/MND and family carers – A qualitative study. Amyotroph Lateral Scler 2011;12 (2):97-104.  Back to cited text no. 12
Renton AE, Traynor BJ. CRESTing the ALS mountain. Nat Neurosci 2013;16 (7):774-5.  Back to cited text no. 13
Renton AE, Chiò A, Traynor BJ. State of play in amyotrophic lateral sclerosis genetics. Nat Neurosci 2014;17 (1):17-23.  Back to cited text no. 14
Tian F, Yang W, Mordes DA, Wang JY, Salameh JS, Mok J, Chew J, Sharma A, Leno-Duran E, Suzuki-Uematsu S, Suzuki N, Han SS, Lu FK, Ji M, Zhang R, Liu Y, Strominger J, Shneider NA, Petrucelli L, Xie XS, Eggan K. Monitoring peripheral nerve degeneration in ALS by label-free stimulated Raman scattering imaging. Nat Commun 2016;7:13283.  Back to cited text no. 15
Tonoki A, Kuranaga E, Tomioka T, Hamazaki J, Murata S, Tanaka K, Miura M. Genetic evidence linking age-dependent attenuation of the 26S proteasome with the aging process. Mol Cell Biol 2009;29 (4):1095-106.  Back to cited text no. 16
Miller RG, Jackson CE, Kasarskis EJ, England JD, Forshew D, Johnston W, Kalra S, Katz JS, Mitsumoto H, Rosenfeld J, Shoesmith C, Strong MJ, Woolley SC; Quality Standards Subcommittee of the American Academy of Neurology. Practice parameter update: The care of the patient with amyotrophic lateral sclerosis: Multidisciplinary care, symptom management, and cognitive/behavioral impairment (an evidence-based review): Report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 2009;73 (15):1227-33.  Back to cited text no. 17
Heemels MT. Neurodegenerative diseases. Nature 2016;539 (7628):179.  Back to cited text no. 18
Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh PR; ReproGen Consortium; Psychiatric Genomics Consortium; Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3, Duncan L, Perry JR, Patterson N, Robinson EB, Daly MJ, Price AL, Neale BM. An atlas of genetic correlations across human diseases and traits. Nat Genet 2015;47 (11):1236-41.  Back to cited text no. 19
McCullumsmith RE, Hammond JH, Shan D, Meador-Woodruff JH. Postmortem brain: An underutilized substrate for studying severe mental illness. Neuropsychopharmacology 2015;40 (5):1307.  Back to cited text no. 20
Skaper SD. Transgenic animal models of neurodegenerative diseases. CNS Neurol Disord Drug Targets 2010;9 (4):384-5.  Back to cited text no. 21
Cooper JF, Van Raamsdonk JM. Modeling Parkinson's disease in C. elegans. J Parkinsons Dis 2018;8 (1):17-32.  Back to cited text no. 22
Martini AC, Forner S, Trujillo-Estrada L, Baglietto-Vargas D, LaFerla FM. Past to future: What animal models have taught us about Alzheimer's disease. J Alzheimers Dis 2018. [doi: 10.3233/JAD-179917].  Back to cited text no. 23
Jellinger KA, Attems J. Neuropathological approaches to cerebral aging and neuroplasticity. Dialogues Clin Neurosci 2013;15 (1):29-43.  Back to cited text no. 24
McCarroll SA, Hyman SE. Progress in the genetics of polygenic brain disorders: Significant new challenges for neurobiology. Neuron 2013;80 (3):578-87.  Back to cited text no. 25
Bales KR. The value and limitations of transgenic mouse models used in drug discovery for Alzheimer's disease: An update. Expert Opin Drug Discov 2012;7 (4):281-97.  Back to cited text no. 26
Potashkin JA, Blume SR, Runkle NK. Limitations of animal models of Parkinson's disease. Parkinsons Dis 2010;2011:658083.  Back to cited text no. 27
Stimulus package. Nat Med 2018;24 (3):247.  Back to cited text no. 28
Cummings J, Lee G, Mortsdorf T, Ritter A, Zhong K. Alzheimer's disease drug development pipeline: 2017. Alzheimers Dement (N Y) 2017;3 (3):367-84.  Back to cited text no. 29
Vargas LM, Cerpa W, Muñoz FJ, Zanlungo S, Alvarez AR. Amyloid-β oligomers synaptotoxicity: The emerging role of EphA4/c-Abl signaling in Alzheimer's disease. Biochim Biophys Acta 2018;1864(4 Pt A):1148-59.  Back to cited text no. 30
Chiang AC, Fowler SW, Savjani RR, Hilsenbeck SG, Wallace CE, Cirrito JR, Das P, Jankowsky JL. Combination anti-Abeta treatment maximizes cognitive recovery and rebalances mTOR signaling in APP mice. J Exp Med 2018;215 (5):1349-64.  Back to cited text no. 31
Fang Y, Gao T, Zhang B, Pu J. Recent advances: Decoding Alzheimer's disease with stem cells. Front Aging Neurosci 2018;10:77.  Back to cited text no. 32
Han SS, Williams LA, Eggan KC. Constructing and deconstructing stem cell models of neurological disease. Neuron 2011;70 (4):626-44.  Back to cited text no. 33
Komor AC, Badran AH, Liu DR. CRISPR-based technologies for the manipulation of eukaryotic genomes. Cell 2017;168 (1-2):20-36.  Back to cited text no. 34
Ben Jehuda R, Shemer Y, Binah O. Genome editing in induced pluripotent stem cells using CRISPR/Cas9. Stem Cell Rev 2018;14(3):323-36.  Back to cited text no. 35
Davis-Dusenbery BN, Williams LA, Klim JR, Eggan K. How to make spinal motor neurons. Development 2014;141 (3):491-501.  Back to cited text no. 36
Dimos JT, Rodolfa KT, Niakan KK, Weisenthal LM, Mitsumoto H, Chung W, Croft GF, Saphier G, Leibel R, Goland R, Wichterle H, Henderson CE, Eggan K. Induced pluripotent stem cells generated from patients with ALS can be differentiated into motor neurons. Science 2008;321 (5893):1218-21.  Back to cited text no. 37
Chambers SM, Fasano CA, Papapetrou EP, Tomishima M, Sadelain M, Studer L. Highly efficient neural conversion of human ES and iPS cells by dual inhibition of SMAD signaling. Nat Biotechnol 2009;27 (3):275-80.  Back to cited text no. 38
Zhang Y, Pak C, Han Y, Ahlenius H, Zhang Z, Chanda S, Marro S, Patzke C, Acuna C, Covy J, Xu W, Yang N, Danko T, Chen L, Wernig M, Südhof TC. Rapid single-step induction of functional neurons from human pluripotent stem cells. Neuron 2013;78 (5):785-98.  Back to cited text no. 39
de Boer AS, Koszka K, Kiskinis E, Suzuki N, Davis-Dusenbery BN, Eggan K. Genetic validation of a therapeutic target in a mouse model of ALS. Sci Transl Med 2014;6 (248):248ra104.  Back to cited text no. 40
Rivetti di Val Cervo P, Romanov RA, Spigolon G, Masini D, Martín-Montañez E, Toledo EM, La Manno G, Feyder M, Pifl C, Ng YH, Sánchez SP, Linnarsson S, Wernig M, Harkany T, Fisone G, Arenas E. Induction of functional dopamine neurons from human astrocytes in vitro and mouse astrocytes in a Parkinson's disease model. Nat Biotechnol 2017;35 (5):444-52.  Back to cited text no. 41
Serra M, Brito C, Correia C, Alves PM. Process engineering of human pluripotent stem cells for clinical application. Trends Biotechnol 2012;30 (6):350-9.  Back to cited text no. 42
Dutta D, Heo I, Clevers H. Disease modeling in stem cell-derived 3D organoid systems. Trends Mol Med 2017;23 (5):393-410.  Back to cited text no. 43
Lancaster MA, Renner M, Martin CA, Wenzel D, Bicknell LS, Hurles ME, Homfray T, Penninger JM, Jackson AP, Knoblich JA. Cerebral organoids model human brain development and microcephaly. Nature 2013;501 (7467):373-9.  Back to cited text no. 44
Watanabe K, Ueno M, Kamiya D, Nishiyama A, Matsumura M, Wataya T, Takahashi JB, Nishikawa S, Nishikawa S, Muguruma K, Sasai Y. A rock inhibitor permits survival of dissociated human embryonic stem cells. Nat Biotechnol 2007;25 (6):681-6.  Back to cited text no. 45
Lee CT, Bendriem RM, Wu WW, Shen RF. 3D brain Organoids derived from pluripotent stem cells: Promising experimental models for brain development and neurodegenerative disorders. J Biomed Sci 2017;24 (1):59.  Back to cited text no. 46
Clevers H. Modeling development and disease with organoids. Cell 2016;165 (7):1586-97.  Back to cited text no. 47
Kadoshima T, Sakaguchi H, Nakano T, Soen M, Ando S, Eiraku M, Sasai Y. Self-organization of axial polarity, inside-out layer pattern, and species-specific progenitor dynamics in human ES cell-derived neocortex. Proc Natl Acad Sci U S A 2013;110 (50):20284-9.  Back to cited text no. 48
Qian X, Nguyen HN, Song MM, Hadiono C, Ogden SC, Hammack C, Yao B, Hamersky GR, Jacob F, Zhong C, Yoon KJ, Jeang W, Lin L, Li Y, Thakor J, Berg DA, Zhang C, Kang E, Chickering M, Nauen D11, Ho CY, Wen Z, Christian KM, Shi PY, Maher BJ, Wu H, Jin P, Tang H, Song H, Ming GL. Brain-region-specific organoids using mini-bioreactors for modeling ZIKV exposure. Cell 2016;165 (5):1238-54.  Back to cited text no. 49
Barrera JA, Kao LR, Hammer RE, Seemann J, Fuchs JL, Megraw TL. CDK5RAP2 regulates centriole engagement and cohesion in mice. Dev Cell 2010;18 (6):913-26.  Back to cited text no. 50
Lizarraga SB, Margossian SP, Harris MH, Campagna DR, Han AP, Blevins S, Mudbhary R, Barker JE, Walsh CA, Fleming MD. Cdk5rap2 regulates centrosome function and chromosome segregation in neuronal progenitors. Development 2010;137 (11):1907-17.  Back to cited text no. 51
Campion D, Dumanchin C, Hannequin D, Dubois B, Belliard S, Puel M, Thomas-Anterion C, Michon A, Martin C, Charbonnier F, Raux G, Camuzat A, Penet C, Mesnage V, Martinez M, Clerget-Darpoux F, Brice A, Frebourg T. Early-onset autosomal dominant Alzheimer disease: Prevalence, genetic heterogeneity, and mutation spectrum. Am J Hum Genet 1999;65 (3):664-70.  Back to cited text no. 52
Raja WK, Mungenast AE, Lin YT, Ko T, Abdurrob F, Seo J, Tsai LH. Self-organizing 3D human neural tissue derived from induced pluripotent stem cells recapitulate Alzheimer's disease phenotypes. PLoS One 2016;11 (9):e0161969.  Back to cited text no. 53
Ilieva H, Polymenidou M, Cleveland DW. Non-cell autonomous toxicity in neurodegenerative disorders: ALS and beyond. J Cell Biol 2009;187 (6):761-72.  Back to cited text no. 54
Wen Z, Nguyen HN, Guo Z, Lalli MA, Wang X, Su Y, Kim NS, Yoon KJ, Shin J, Zhang C, Makri G, Nauen D, Yu H, Guzman E, Chiang CH, Yoritomo N, Kaibuchi K, Zou J, Christian KM, Cheng L, Ross CA, Margolis RL, Chen G, Kosik KS, Song H, Ming GL. Synaptic dysregulation in a human iPS cell model of mental disorders. Nature 2014;515 (7527):414-8.  Back to cited text no. 55
Ryan SD, Dolatabadi N, Chan SF, Zhang X, Akhtar MW, Parker J, Soldner F, Sunico CR, Nagar S, Talantova M, Lee B, Lopez K, Nutter A, Shan B, Molokanova E, Zhang Y, Han X, Nakamura T, Masliah E, Yates JR 3rd, Nakanishi N, Andreyev AY, Okamoto S, Jaenisch R, Ambasudhan R, Lipton SA. Isogenic human iPSC Parkinson's model shows nitrosative stress-induced dysfunction in MEF2-PGC1alpha transcription. Cell 2013;155 (6):1351-64.  Back to cited text no. 56
Sweeney MD, Sagare AP, Zlokovic BV. Blood-brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders. Nat Rev Neurol 2018;14 (3):133-50.  Back to cited text no. 57
Zhang YS, Aleman J, Shin SR, Kilic T, Kim D, Mousavi Shaegh SA, Massa S, Riahi R, Chae S, Hu N, Avci H, Zhang W, Silvestri A, Sanati Nezhad A, Manbohi A, De Ferrari F, Polini A, Calzone G, Shaikh N, Alerasool P, Budina E, Kang J, Bhise N, Ribas J Pourmand A, Skardal A, Shupe T, Bishop CE, Dokmeci MR, Atala A, Khademhosseini A. Multisensor-integrated organs-on-chips platform for automated and continual in situ monitoring of organoid behaviors. Proc Natl Acad Sci U S A 2017;114 (12):E2293-302.  Back to cited text no. 58


  [Figure 1]

This article has been cited by
1 The multifaceted roles of nucleophagy in cancer development and therapy
Lili Zhao,Wenxi Li,Xu Luo,Surui Sheng
Cell Biology International. 2020;
[Pubmed] | [DOI]
2 Modeling rare pediatric neurogenetic disorders with IPSCs
Jaemin Kim,David Nonis,Maria Gabriela Otero,Tyler Mark Pierson
AIMS Cell and Tissue Engineering. 2019; 3(1): 1
[Pubmed] | [DOI]


Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

  In this article
Modeling the Bra...
Article Figures

 Article Access Statistics
    PDF Downloaded455    
    Comments [Add]    
    Cited by others 2    

Recommend this journal