One of the most profound advances in the last decade of biomedical research has been the development of human induced pluripotent stem cell (hiPSC) models for identification of disease mechanisms and drug discovery. Human iPSC technology has the capacity to revolutionize healthcare and the realization of personalized medicine, but differentiated tissues derived from stem cells come with major criticisms compared to native tissue, including variability in genetic backgrounds, a lack of functional maturity, and differences in epigenetic profiles. It is widely believed that increasing complexity will lead to improved clinical relevance, so methods are being developed that go from a single cell type to various levels of 2-D coculturing and 3-D organoids. As this inevitable trend continues, it will be essential to thoroughly understand the strengths and weaknesses of more complex models and to develop criteria for assessing biological relevance. We believe the payoff of robust, high-throughput, clinically meaningful human stem cell models could be the elimination of often inadequate animal models. To facilitate this transition, we will look at the challenges and strategies of complex model development through the lens of neurodegeneration to encapsulate where the disease-in-a-dish field currently is and where it needs to go to improve.

Neurodegenerative disease encompasses a broad range of conditions that primarily affect the human brain, resulting in progressive loss of function and eventual cell death. Diseases including amyotrophic sclerosis, Parkinson’s, Huntington’s, and Alzheimer’s (AD) share similar challenges for robust modeling as they are all complicated, with pathologies associated with age, intricate genetics, and environmental factors. Model organisms from yeast to rodents have made important contributions to improving our understanding of key mechanisms that lead to neurodegenerative conditions, yet these models have failed to develop any drugs that prevent the progression of neurodegeneration across a wide range of diseases, including AD, Parkinson’s disease, and Huntington’s disease. Why? In many cases, animal models fail to recapitulate the complexity of human neurological states. For example, most animal models do not exhibit the extensive neuronal loss characteristic of advanced AD pathology [Grow et al., 2016; Eaton and Wishart, 2017]. Furthermore, the ability of rodents to model the motor impairment and perturbed decision-making characteristic of many neurodegenerative disorders is questionable due to differences in neuronal network development and complexity, reduced white matter content, and reduced neuronal density in targeted regions such as the substantia nigra [Grow et al., 2016]. The complete absence of brain regions containing gyrencephalic cortex, separate caudate and putamen or subthalamic nuclei further confounds the use of rodents to study human neurodegeneration [Eaton and Wishart, 2017].

Human stem cell technology, and induced pluripotent stem cells (iPSC) in particular, has made it possible to study human neurodegeneration from a developmental perspective while investigating the genetic contribution using gene-editing strategies. Next-generation sequencing techniques have synergized with high-throughput assays to enable the evaluation and comparison of multiple patient-specific cell lines, ushering in the possibility of precision medicine. Along with their enormous potential, neurological iPSC models come with several shortcomings that need to be acknowledged and overcome. Specifically, efforts are being made to improve retention of epigenetic profiles, reduce variability, increase maturity, and build multi-cell type organoids that mimic native tissue. Here we review each of these issues and how they pertain to the widespread adoption of hiPSC-based platforms in modeling human neurodevelopment and degeneration (Fig. 1). In addition, we discuss possible solutions to unsolved challenges and offer a new perspective on where efforts should be focused to further advance our understanding of, and ability to combat, neurodegenerative decline. We will attempt to answer the following question: what are the barriers between the current state of hiPSC technology and the full adoption of body-on-a-chip models of neuronal tissue?

Human iPSC technology has unlocked new avenues of research in biomedical science. With the expression of just 4 factors, i.e., Oct4, Sox2, Klf4, and c-Myc, a terminally differentiated cell can be reverted into a pluripotent state [Takahashi and Yamanaka, 2006], making it possible to direct cells down almost any cell lineage. This groundbreaking discovery has been improved upon and alternative strategies have been developed [Mertens et al., 2016; Shahbazi et al., 2018], but the reprogramming process from somatic cell to iPSC remains inefficient [Zhou and Zeng, 2013; Schlaeger et al., 2015]. Part of this inefficiency is due to epigenetic barriers to this process that restrict the transition from terminally differentiated to pluripotent states [Ebrahimi, 2015]. Identification and utilization of novel methods which circumvent epigenetic barriers will be useful in improving reprogramming efforts and, ultimately, the robustness of human iPSC models. Overcoming these barriers and improving the precision of directed differentiations is an important problem to solve before stem cell transplant therapies can be adopted, as incompletely or inaccurately differentiated cells have the potential to create teratomas or other unpredictable effects [Hong et al., 2014].

Epigenetic modifications alter gene expression without changing the underlying DNA sequence. These epigenetic changes can be induced by many factors, including environment [Lopizzo et al., 2015; Holland et al., 2016], diet [Shimazu et al., 2013; Kong et al., 2017], exercise [Lavratti et al., 2017; Jessop and Toledo-Rodriguez, 2018], aging [Benayoun et al., 2015; Kubben and Misteli, 2017], disease [Christopher et al., 2017; Roubroeks et al., 2017], and cancer [Johnson et al., 2015; Toh et al., 2017]. Epigenetic regulation occurs through noncoding RNAs, direct chemical changes to DNA, or indirectly through DNA-associated proteins – all resulting in the suppression or enhancement of gene expression [Berger et al., 2009]. Multiple lines of evidence indicate the importance of epigenetic regulation in mediating reprogramming of somatic cells to iPSC. Specifically, large-scale shRNA screens have identified Trim28 [Miles et al., 2017], Setdb1 [Chen et al., 2013], and Rif1 [Li et al., 2017] as repressors of epigenetic modification that can serve as barriers to reprogramming efforts through silencing of endogenous retroviruses involved in establishing pluripotency [Ivanov et al., 2007; Matsui et al., 2010; Karimi et al., 2011; Maksakova et al., 2011; Friedli et al., 2014; Ohnuki et al., 2014]. Knockdown of Trim28 and Setdb1 in wild-type and immortalized mouse embryonic fibroblasts has been shown to substantially increase reprogramming efficiency via a decrease in methylation of histone 3 lysine 9 (H3K9me3), a heterochromatic associated histone mark linked to repression of lineage genes [Hawkins et al., 2010; Becker et al., 2016; Miles et al., 2017]. Knockdown of Rif1 similarly enhanced reprogramming efficiency. In addition to endogenous retroviruses repression regulators, histone-mediated chromatin structural states can also serve as a barrier to genetic reprogramming. MacroH2a isoforms have been shown to be incorporated into pluripotency genes to silence their activity and their removal may help facilitate reprogramming efforts [Gaspar-Maia et al., 2013].

Epigenetic silencing is especially important to consider when stem cells differentiate as the epigenetic switching of genes “on” or “off” is important in the regulation of cell fate [Ficz et al., 2011; Tao et al., 2018; Zhu et al., 2018]. This allows cells to develop distinct identities while maintaining a common genetic code. Reproducing gene-silencing patterns in vitro would be a powerful tool to recapitulate the in vivo niche to better study the normal function of individual cells and the development of disease states. An understanding of the epigenetic changes that neurons undergo during development is therefore beneficial when seeking to direct the differentiation of cells as close as possible to the desired cell type. To define the regulatory pathways that determine cell fate, Ziller et. al. [2015] tracked changes in DNA modification patterns, an “epigenetic footprint,” in human embryonic stem (ES) cells during neuronal differentiation. Analysis of global transcription in ES cells and 4 neural progenitor cell stages revealed the differential expression of 3,396 genes. DNA methylation data exhibited 2 overall patterns of epigenetic change in the transition from ES to a neural fate and beyond. The first pattern connected early neural fate decisions with the widespread loss of methylation and subsequent hypomethylation maintenance. The second pattern correlated later-stage cell fate decisions with a stage-specific DNA methylation loss and subsequent gain at the next stage. To identify the regulators of these patterns of epigenetic change, a computational model was developed to link epigenetic footprints to specific transcription factors. Analysis of the top-ranked transcription factors predicted to be activated during the cell state transition confirmed known regulators of neuronal development and differentiation, including PAX6, OTX2, FOXG1, and SOX proteins [Götz et al., 1998; Pevny et al., 1998; Martinez-Barbera et al., 2001; Hanashima et al., 2004] and neural induction pathways associated with inhibition of TGF-β and reduction in SMAD4 activity [Chambers et al., 2009]. Such data may provide researchers with a “roadmap” for guiding the correct development of iPSC neurons for downstream applications.

Despite enormous efforts to engineer functional cells from iPSC that match as closely as possible the primary cells they are designed to phenocopy, iPSC-derived neurons do not always match their primary counterparts. While the genotypes may be the same and cells may display the correct surface markers and similar electrophysiological properties, differences can exist in the epigenetic profile between the primary cell and the reprogrammed mimic, resulting in significant variances in gene expression. It is not yet known what impact these differences will have when using hiPSC-derived neurons as predictors of human neural responses to chemical or pathological challenges. In a study of iPSC-derived midbrain mesodiencephalic dopaminergic neurons, major differences were found between primary cells and iPSC-derived neurons in levels of DNA methylation [Roessler et al., 2014]. These differences in methylation changed the expression levels of genes involved in function, neurodevelopment, regulation of synaptic transmission, and cell communication. Not surprisingly, gene expression patterns in iPSC-derived neurons strongly correlated with those found in embryonic primary neurons rather than postnatal-stage primary neurons. The iPSC-derived dopaminergic neurons displayed these differences in gene expression despite typical mature morphology, expression of archetypal markers (microtubule-associated protein 2 and tyrosine hydroxylase), and robust electrophysiological recordings. These observations highlight the importance of taking into consideration not only functional and morphological characteristics but also epigenetic characteristics.

The fetal nature of iPSC-derived neurons presents a challenge when attempting to model advanced-age neurodegenerative disease [Studer et al., 2015], as results obtained in the context of late-onset degenerative disease may actually express biochemical markers more-closely associated with early-onset conditions. The epigenetic landscape is therefore important to consider when choosing a model system, particularly in studying human disease pathologies which occur at specific life stages. Transdifferentiation of aged cells may offer a suitable method to retain older epigenetic patterns when producing model neurons. Methods of direct conversion of fibroblasts into induced neurons have been developed in human models [Hu et al., 2015; Mertens et al., 2015]. 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]. However, transdifferentiation does have one significant drawback, since directly converted neurons are postmitotic and therefore cannot be expanded the way iPSCs can.

Other limitations to consider when recapitulating disease in hiPSC models are the side effects of cell expansion over time. For example, repeated passaging may pose a problem in modeling Rett syndrome, an X-linked neurodevelopmental disorder characterized by profound intellectual and motor disabilities caused by the loss of function in methyl-CpG-binding protein 2 [Ip et al., 2018]. Modeling this disorder in hiPSC is potentially problematic, as DNA methylation profiles, including those involved in X inactivation, may change during the repeated passaging of iPSCs [Bock et al., 2011; Nishino et al., 2011; Nazor et al., 2012]. Furthermore, analysis of low and high passage cultures of normal pluripotent populations has revealed the existence of hypermethylation events at CpG islands and silencing of genes, including TSPYL5. This tumor suppressor is downregulated in certain cancers, which could confound modeling of normal neurons [Weissbein et al., 2017]. The emergence of growth-promoting epigenetic alterations must therefore be carefully monitored, particularly when considering expanded, patient-derived cells for implant therapies.

In addition to improving hiPSC differentiation protocols, an understanding of how epigenetic misregulation causes disease may further our efforts to elucidate pathological mechanisms and treat complex neurological disorders using iPSC technology. In AD, misregulation occurs across all areas of epigenetic influence, including dysregulation in global methylation, altered expression of chromatin-associated proteins, and deregulation of noncoding RNA. Each aspect of misregulation is under intense scrutiny for potential therapeutic targets. Analysis of the epigenetic landscape in patients suffering from dementia has highlighted significant differences compared with age-matched controls, suggesting that alterations in DNA structure may play a central role in the progression of neurodegenerative conditions [Gräff et al., 2012]. In particular, global changes in hypo- and hypermethylation of CpG islands have been detected in dementia-associated brain regions. One study observed an approximately 20% decrease in DNA methylation markers 5-methylcytidine (5-mC) and 5-hydroxymethylcytidine (5-hmC) in hippocampal tissue from AD patients compared to nondemented, age-matched controls [Chouliaras et al., 2013]. Similar results were obtained from monozygotic twins discordant for AD [Chouliaras et al., 2013]. Identical DNA sequences producing discordant phenotypes with regard to dementia provide further evidence of the importance of noncoding genetic modification in neurodegeneration onset and progression. In another study of monozygotic twins discordant for AD, increased gene expression of sirtuin 1, an enzyme with a role in acetylation of DNA-associated proteins, as well as histone deacetylases (HDAC) HDAC2 and HDAC9, were observed in the AD-exhibiting twin [D’Addario et al., 2017]. In fact, expression of HDAC2, a known key player in functional plasticity in learning and memory, was previously shown to be upregulated in AD brains [Gräff et al., 2012] and current research is being focused on reducing HDAC protein expression as a target for the treatment of AD [Cuadrado-Tejedor et al., 2017; Yang et al., 2017; Volmar et al., 2018]. The role of noncoding RNA has been extensively reviewed elsewhere but includes influences on neuroinflammation, generation and clearance of amyloid-β (Aβ) and τ proteins, synaptic integrity and function, activity of mitochondria and endoplasmic reticulum, and the cell cycle [Maoz et al., 2017; Millan, 2017; Idda et al., 2018].

Not only is there evidence to suggest that epigenetic mechanisms contribute to AD pathology, but epigenetic mechanisms may also be responsible for exacerbating the damage caused by the disease and preventing endogenous processes that replace neuronal loss. Continual neurogenesis occurs in a healthy adult brain and helps maintain normal learning and memory through integration into the existing neuronal circuitry [Spalding et al., 2013; Ernst et al., 2014]. As discussed above, neurogenesis is mediated by epigenetic mechanisms that tightly control gene expression during cell fate decisions. Though controversial [Toda et al., 2018], these processes may be impaired in the AD brain [Boekhoorn et al., 2006; Li et al., 2008], and the loss of neurons without replacement would certainly accelerate disease progression. Conflicting results regarding the occurrence of neurogenesis in AD may be due to a lack of information regarding the occurrence of neurogenesis at specific disease stages or the variant nature of AD progression.

As our understanding of the epigenetic landscape and its role in neurodegenerative disease improves, our capacity to manipulate such changes to combat disease likewise increases. For example, high-throughput screening of neural progenitors has been used to identify compounds capable of reversing epigenetic silencing of the Fmr1 gene in fragile X syndrome. Mental retardation in fragile X is largely caused by epigenetic silencing of Fmr1 and these results offer hope that targeted reversal of these pathogenic epigenetic modifications may be possible in the near future [Kaufmann et al., 2015].

Research involving animal models relies heavily on inbred lines to ensure consistency both internally within a given study and externally between studies conducted at different sites. The use of animal lines with identical genetic backgrounds provides a degree of certainty that the differences observed have arisen from experimental manipulation rather than differential responses due to genetic variation. Clonal human iPSC lines also offer consistency of genotype. However, genetic variability across human populations means that substantial differences between lines exist, and the means to account for this heterogeneity when predicting patient responses to therapeutic interventions have yet to be established. Personalized medicine – the means to conduct studies on a patient’s own cells to determine the best possible therapeutic options for that individual – holds great potential to improve standards of care and reduce costs in the long run, but our current inability to fully exploit iPSCs for such applications further underscores the difficulty in using these cells to test basic biological hypotheses and address the pathophysiological variability across human populations.

In the past, issues have been raised regarding the persistence of cell-of-origin memory after a somatic cell type has undergone iPSC reprogramming [Bar-Nur et al., 2011]. However, long-term culture and serial reprogramming have proven efficacious in erasing such memory [Kim et al., 2010; Polo et al., 2010], as well as reducing differences between iPSC and ES cell lines [Chin et al., 2010] and eliminating genetic mosaicism [Hussein et al., 2011]. Worries about the incorporation of reprogramming factor genes into the iPSC genome, thereby potentially leading to alterations in the genotype, have also been raised. Fortunately, the generation of replication-defective persistent Sendai virus has enabled effective cellular reprogramming followed by erasure of the vector’s genomic RNA [Nishimura et al., 2011], reducing the risk of variability or spurious gene activation/inactivation in companion iPSC lines. Using such vectors, it has been shown that donor cell type contributes minimally to iPSC variability in terms of gene expression profiles and the epigenetic landscape [Kyttälä et al., 2016]. However, this same study, along with others [Rouhani et al., 2014], has highlighted that donor-related variability can influence expression of lineage-priming genes in iPSCs. This suggests that such cells exhibit a variable capacity to differentiate down specific lineages and that this is dictated, at least in part, by the donor genotype. Therefore, the ability to produce a fully differentiated, functional somatic cell from iPSC is determined not only by the efficiency of the differentiation method employed but also by the parent donor cell used to generate the iPSC line. This makes heterogeneity downstream of a given differentiation method likely when comparing multiple iPSC sources, which suggests that direct comparisons of a given cell type’s response to challenge across different genetic backgrounds may be problematic and strongly argues for using isogenic iPSC lines whenever possible.

Within one congenital disease, further variability exists in the number of causal genes and the range of pathogenic mutations in each gene known to produce symptoms. Even for relatively straightforward, monogenic disorders, different mutations cause variable pathological phenotypes depending on whether the location of the mutation is in the structural or regulatory portion of the gene. For example, Huntington’s disease is caused by the presence of a mutation for a long series of glutamine-encoding CAG repeats (> 36 repeats) in the Huntingtin (HTT) gene, and longer repeat sequences correlate with a younger age of disease onset [Andrew et al., 1993]. The length of CAG repeats in the HTT sequence of patient-derived iPSC has likewise been shown to produce line-specific phenotypes when these cells are differentiated into neurons [Berndt et al., 2011]. Such line-specific differences include changes in energy metabolism, cell-cell adhesion, stressor vulnerability, and cell survival, with longer CAG repeats producing poorer readouts for these metrics.

AD can be broadly broken down in to early onset (prior to age 65 years) and late onset (after age 65 years). Both early-onset AD and late-onset AD have a heritable component, with the majority of early-onset AD showing a strong family history [Bekris et al., 2010]. Autosomal dominant AD is almost exclusively early-onset AD and accounts for approximate 1% of all AD cases [Bekris et al., 2010]. This form of the disorder is due to more than 200 changes that have been reported in the genes encoding amyloid precursor protein (APP), presenilin (PSEN) 1, and PSEN 2 [Ryan and Rossor, 2010]. Although the pathogenic nature of these changes has not been confirmed in every instance, this heterogeneity underscores the significant variability in patients suffering from this debilitating condition. Even assuming that only a subset of these mutations are pathological, mutations in these genes account for a small percentage of AD in general, and the degree to which the study of these mutations can serve as a paradigm for late-onset sporadic AD, which has complex genetic and environmental components, is still uncertain. In terms of late-onset sporadic AD, the APOE gene has been most consistently associated with AD risk. In humans, there are 3 isoforms of APOE with polymorphisms encoding either cysteine or arginine at amino acid positions 112 and 158. The frequency of the APOE e4 allele, coding for arginine, is highly increased in patients with AD and the presence of the arginine amino acid affects the structure and lipid-binding abilities of the APOE protein [Bekris et al., 2010]. Recent work using isogenic cellular models of APOE derived from hiPSCs has yielded exciting data indicating that APOE e4 increases Aβ production and τ phosphorylation (the 2 main pathological hallmarks of AD) and also causes gene expression changes in brain inflammatory cells, suggesting that upregulation of an innate immune response in the brain can contribute to neurodegeneration [Lin et al., 2018; Wang et al., 2018a]. Importantly, these effects were seen exclusively in human cells, highlighting the differences between hiPSC and other commonly used nonhuman model systems. Despite this, comparing diseased cells with those from healthy controls can raise issues with baseline genetic variance between healthy and patient genotypes. The increasing availability of CRISPR/Cas9 and other gene-editing methods has made the generation of isogenic cell lines, where different variant lines are derived from the same genetic background, a critical component for investigating the potential pathogenic effects of a given variant. By correcting the mutation in a given line, or inducing a pathological mutation in an otherwise healthy line, researchers can study the effect of that mutation against controls without worrying about donor variance. However, off target effects of the editing process cannot be ruled out. In particular, activation of a DNA damage response via p53 activation has recently been reported to account for Cas9 toxicity in pluripotent stem cells [Ihry et al., 2018]. At this point, it is also unknown if off target effects have a significant impact on the eventual phenotype of differentiated cells. Efforts to improve the targeting efficiency of current gene-editing methods are an active area of current research [Miller et al., 2007; Sanjana et al., 2014; Tsai et al., 2014], but the genome-wide specificities of these techniques have yet to be fully defined. The importance of understanding the unexpected impact of gene editing on iPSC-derived somatic cell function within the scientific community is clear from the recent establishment of several initiatives, including the US NIH Somatic Cell Genome Editing (SCGE) program [National Institutes of Health, 2018], which is seeking to fund projects aimed at defining the risk of adverse biological consequences of current editing methods, including CRISPR/Cas9. Likewise, the European Academies Science Advisory Council published a report last year in which they emphasized the need for “intensive basic and clinical research” to better understand “the risks such as inaccurate editing and the potential benefit” of proposed genome modifications on human cells, for both clinical and nonclinical applications [European Academies’ Science Advisory Council, 2017]. Given the potential impact of such technologies for combatting genetic disorders, we can expect such research to proceed rapidly in the coming years, leading to a greater understanding of how such methods could impact the reliability of iPSC-based research.

Clonal variability represents one final source of potential variance in iPSC-based research. Investigations into mutational load in iPSC lines have demonstrated that there is a significant risk for iPSCs to exhibit new mutations as a result of reprogramming, but that new mutations vary in different iPSC clones [Gore et al., 2011]. The authors of this work admit the possibility that reprogramming itself is “mutagenic” but provide data arguing that selection during reprogramming, colony-picking, and subsequent culture may be contributing factors. As such, it is possible that if reprogramming efficiency is improved to the point where no colony picking or clonal expansion is required then the resulting iPSC may have a significantly reduced incidence of new mutations. Several studies have reported significant copy number alterations, including duplications and deletions, between iPSC and their donor cells [Laurent et al., 2011; Martins-Taylor et al., 2011; Kilpinen et al., 2017]. Most of these alterations appear to be iPSC clone specific, leading to genetic mosaicism in cultures established from nonclonal colonies [Kilpinen et al., 2017]. In fact, one study of 711 iPSC lines derived from 301 healthy individuals found that just 15% of the observed copy-number alterations were identified in all replicates [Kilpinen et al., 2017], highlighting the significant potential for genotype variability in different iPSC clones. Despite these findings, recent work has highlighted that the widespread use of more than one clone per individual can be detrimental to the robustness of the findings and that spurious differential expression is exacerbated by the inclusion of multiple iPSC clones for a given line [Germain and Testa, 2017]. As such, the authors recommend increasing the number of donor lines, rather than the number of clones, to improve assay sensitivity.

Additionally, the ability to detect genomic instability in stem cell populations is crucial to moving forward with in-patient therapeutic applications. In 2015, safety concerns prevented the progression of the first-in-human clinical trial of patient-derived stem cells [Chakradhar, 2016]. Patient fibroblasts were reprogrammed to retinal neurons and transplanted for the treatment of age-related macular degeneration. No genetic abnormalities were detected in the first patient’s cells. She was not given any immunosuppressants, and her worsening vision stabilized. However, the second patient’s screen for genetic abnormalities revealed mutations in 3 genes. One of the 3 genes is known as an oncogene in the Catalogue of Somatic Mutations in Cancer. Despite the fact that that these mutations were not shown to lead directly to adverse effects, the planned transplantation of an hiPSC-derived retinal pigment epithelium was cancelled, highlighting the need for a greater understanding of the risks posed by novel iPSC mutations.

Although considerable work has been done to characterize the level of genetic variability that exists in and between iPSC populations, no methods have yet been proposed to assess the experimental significance that such variability could impose on the study of neural development and pathology or on potential clinical outcomes of hiPSC-based therapeutics. Increasing the number of lines used within a given study and (possibly) the number of iPSC clones analyzed per line may help account for variability in differentiation efficiency. However, how many lines would be necessary to account for any observed variance has not been widely agreed upon and would likely vary depending on the specific requirements of the study in question. High-throughput screening modalities could offer the means to compare large iPSC libraries for a given effect or drug response. However, in certain cases with substantial patient variability, whether the number of lines necessary to enable extrapolation of conclusions that pertain to a meaningful subset of the human population would be practical for the majority of research laboratories is an open question.

Human iPSC should, in theory, mimic exactly the phenotype of ES cells [Robinton and Daley, 2012]. As such, differentiation methods developed to produce somatic cells from these sources should attempt to mirror the developmental signaling cascade known to regulate lineage specification during embryo patterning and differentiation. As our understanding of these pathways improves, our capacity to control iPSC differentiation likewise increases. For example, recent work studying the differentiation of skeletal muscle has led to the development of methods to produce functional muscle fibers from both healthy and dystrophic patient-derived iPSCs [Chal et al., 2015, 2016; Xi et al., 2017; Hicks et al., 2018]. Although neuronal and cardiac differentiation methods have been available for some time [Zhu et al., 2011; Selvaraj et al., 2012], our ability to produce skeletal muscle has lagged behind and it is only with improved understanding of the necessary developmental cues provided in utero that we have been able to further our capacity to produce such lineages from iPSC in vitro. Transcriptomic studies of primary and iPSC-derived cortical neurons have confirmed that iPSC-derived neurons are highly similar to primary cortical neurons at the level of single cells. However, some data suggests that current markers may not be able to disambiguate cortical layer identity in these cultures [Handel et al., 2016]. Therefore, our ability to produce mixed populations of cortical neurons from iPSCs is well established but our capacity to identify specific cortical subtypes requires further refinement.

Despite our ever-increasing ability to produce specific somatic cell types and subtypes, the vast majority of iPSC-directed differentiations produce populations that most closely resemble fetal or neonatal cells. In order to effectively model adult physiological responses to chemicals or adult onset diseases, there remains a need to devise practical methods to promote maturation of cells differentiated from iPSCs to the point where clinically-predictive data can be reliably obtained. During embryogenesis, the development of synaptically active, postmitotic neurons from early-stage neural precursors depends on a tightly regulated transcriptional cascade. The resulting morphological changes then enable the connectivity of the synaptic network necessary to facilitate sustained central nervous system function [Dodla et al., 2010; Kaur et al., 2014]. Similarly, the functional properties of emerging iPSC-based neuronal networks in vitro are highly changeable and subject to differentiation efficiency, cellular subtype specification, and maturation of the neurons, as guided by the input cues provided by researchers. Cultures derived from primary tissues have been shown to readily form functional networks in vitro [Biffi et al., 2013; Penn et al., 2016], and stem cell-based models have likewise been proven capable of exhibiting similar connectivity in culture [Ban et al., 2006]. However, the extent to which these networks are capable of modeling connectivity in the aged brain has yet to be fully characterized and it seems likely that in situ maturation of iPSC-derived neuronal populations would likely improve our ability to study age-associated neurodegeneration using such systems. The necessity to further mature iPSC-derived somatic cells has been widely discussed in the cardiac literature, to the point where several groups have detailed criteria that should be considered when gauging the maturation state of iPSC-derived cardiac populations to ensure their suitability for use in predictive preclinical assays [Lundy et al., 2013; Sheehy et al., 2014; Yang et al., 2014b; Kolanowski et al., 2017]. However, a comprehensive list of maturation criteria with which to assess neuronal development in vitro has been less forthcoming. The importance of developing mature neurons is clear, given the number of degenerative neurological conditions that are associated with advanced age [Deecke and Dal-Bianco, 1991], but what criteria should be used to assess iPSC-derived neuronal maturation? In Table 1 we provide a list of potential metrics and justification for gauging in vitro neuron maturity. Such a list could serve as the basis for more standardized assessment of neuronal maturity prior to use in downstream applications.

The defining properties of an electrically-active cell type are its ability to fire an action potential (AP) and respond correctly to neurotransmitter release. Functional output is thus the gold standard for assessing the health and maturity of neurons and can be measured via patch clamp electrophysiology [Franz et al., 2017], microelectrode array [Obien et al., 2014], or application of voltage-sensitive dyes [Mennerick et al., 2010]. Regardless of the AP properties of individual neurons, the predictive value of iPSC-based central nervous system models is predicated on the ability of the derived cells to recapitulate accurately the functional behaviors of primary neuronal networks through synaptic connectivity. Neurons derived from human iPSCs have been shown to fire AP in response to depolarizing current injections after just 3 weeks of differentiation [Prè et al., 2014]. However, the AP properties at this time point are relatively poor, but in the following weeks they undergo significant improvements characterized by increases in Na+ and K+ current amplitudes, AP amplitude, full width at half maximum of the AP spike, and AP threshold [Prè et al., 2014]. Resting membrane potential in these cells likewise decreased with time, illustrating an improved capacity for cells to regulate ion gradients across their membranes with increased time in culture.

Time has likewise proven to be a key regulator of network connectivity in iPSC neuronal models. Analysis of 1-year-old hiPSC-derived cerebral cortical neurons on microelectrode arrays has illustrated that synchronized burst firing (simultaneous AP bursts) behavior increased steadily from 16 to 30 weeks in culture and that the response to glutamatergic synaptic agonists and inhibitors was similarly time dependent [Odawara et al., 2016]. Also, spike frequency appeared to plateau after 23 weeks in culture, whereas synchronized burst activity steadily increased up to 30+ weeks. Given the differences in firing behavior and drug responses at different time points, these data highlight the need to establish suitable endpoints for pharmacological studies, as compound efficacy will likely vary with culture age. It also seems probable that rate of functional development in iPSC-derived neuronal populations will depend on donor genotype (as discussed above) so the need to establish functional criteria with which to normalize performance and establish experimental endpoints is high. Quantifying AP parameters, resting membrane potentials, spontaneous AP firing rates, burst fire activity, and network burst activity and establishing endpoints when these metrics reach a plateau seems logical. However, culture periods of 30+ weeks are likely impractical for a wide number of downstream assays.

Long-term culture coupled with functional analysis may also prove efficacious in the study of neurodegenerative disease. A recent study utilizing commercially sourced iPSC-derived cortical neurons investigated functional responses to acute supraphysiological doses of Aβ in comparison with low dose physiological concentrations of the protein [Berry et al., 2018]. The authors aimed to determine whether chronic exposure to Aβ at levels comparable to those observed in patients produced a different phenotype compared to the short-term high dose often used in vitro when studying AD. The results suggested that extended, low doses of Aβ produced mild functional impairment of the iPSC-derived neurons without the excessive levels of cell death seen with acute, high doses. Therefore, it is possible that a more measured and physiologic approach to the study of Aβ on neuronal function may enable assessment of early cognitive impairment instead of the catastrophic impact of supraphysiological doses applied in the short term. However, the degree to which the functional impairment observed mirrors the functional capacity of neurons in patients with mild cognitive impairment remains to be seen. In another example, researchers investigated the firing capabilities of motor neurons harboring TARDBP or C9ORF72 amyotrophic lateral sclerosis-causing mutations and showed time-dependent changes in firing capacity [Devlin et al., 2015]. Mutant cells were found to exhibit a progressive decreasing ability to fire chains of AP in response to depolarizing current injections between 4 and 10 weeks in vitro, suggesting that extended culture periods may be necessary to model functional decline in neurodegenerative disease.

In addition to functional performance, morphological characteristics should be considered when assessing neuronal development in vitro. Long-term culture has again shown significant increases in the soma size and primary dendrite widths of developing neurons [Odawara et al., 2014]. The density of synaptic junctions formed on cultured neurons also offers a strong indicator of the structural development of a given neuronal population as well as the degree of connectivity. Complex dendritic arborization and axonal distinction [Gouder et al., 2015; Kang et al., 2017] coupled with stable expression of pan-neuronal markers such as NeuN, MAP-2, and Tuj1 [Hu et al., 2010; Gunhanlar et al., 2018] should likewise be considered.

Despite the positive contribution of long-term culture, it may be impractical for many applications. In addition, it is not yet known whether neurons cultured in vitro for extended periods will ever reach the point of accurately recapitulating the environment of an aged and/or demented brain. It is clear that other methods to drive neuronal maturation in vitro are warranted. Topographic substrates mirroring the structural cues provided by the extracellular matrix have been shown to influence neuronal differentiation from iPSC, with specific topographies altering yes-associated protein expression and in turn affecting the neural differentiation capacity of cultured cells [Song et al., 2016]. Topographic surfaces have also been shown to enhance direct conversion of fibroblasts to neurons through modulation of histone modifications related to cytoskeletal organization [Yoo et al., 2015]. Such substrates enable control of neuritic outgrowth and polarity, which may also offer benefits when seeking to develop controlled neuronal networks [Ferrari et al., 2011]. Studies into other electrically active cell types, like cardiomyocytes, have demonstrated that topographic patterning can enhance physiological structure and function [Yang et al., 2014a; Carson et al., 2016] but whether or not such surfaces enhance network connectivity and functional performance in iPSC-based neuronal cultures remains to be seen. Highly conductive substrates have been shown to improve network activity in cultured neuronal populations [Lovat et al., 2005; Tang et al., 2013]. Although the exact mechanism behind this phenomenon has yet to be characterized, the collected data demonstrate the ability for such conductive surfaces to enhance functional parameters of neurons in vitro.

To model age-related disorders, researchers have shown that forced overexpression of progerin in iPSC-derived neurons can reestablish age-related markers lost during reprogramming and that the resulting cells exhibit degenerative changes in dendrite branching, protein folding, and oxidative stress [Miller et al., 2013]. Furthermore, such genetic manipulation in iPSCs derived from Parkinson’s disease patients produced neurons with condensed nuclei that express cleaved caspase-3. Progerin overexpression in these neurons exacerbated the loss of dendrite length when compared with non-Parkinson’s control cells. Alternatively, manipulation of telomerase expression in iPSC-derived neurons, through exposure to the telomerase inhibitor BIBR1532, reduced dendritic development and led to a reduction in the expression of tyrosine hydroxylase, the rate-limiting enzyme in the synthesis of dopamine, a phenotypic feature associated with Parkinson’s disease [Vera et al., 2016]. Such methods indicate that manipulation of genetic regulators of aging are a viable means of achieving an aged neuronal phenotype. However, direct reprogramming (transdifferentiation; discussed above) may offer an alternative method to achieve mature neurons without reliance on complex or protracted maturation protocols. Using transdifferentiated neurons, researchers have identified the nuclear pore-associated transport protein RanBP17 as a significant factor in cell aging, both in neurons and other cell types, and demonstrated that direct conversion of aged fibroblasts to neurons enabled retention of age-related nucleocytoplasmic defects associated with this protein [Mertens et al., 2015]. Direct conversion of fibroblasts derived from familial AD patients produced neurons with elevated levels of Aβ and phosphorylated τ compared with controls [Hu et al., 2015], indicating that induced neurons can also recapitulate AD phenotypes in cultured neurons.

As valuable as hiPSC-derived neurons are for studying specific cellular mechanisms, purified cultures of individual neuronal subtypes do not represent the in vivo niche and will never fully recapitulate the complexity of the human central nervous system. As such, their capacity to accurately model neuronal circuitry and degenerative behavior in disease states is limited. As our ability to generate mature subtype-specific neurons improves, our capacity to create more and more complex in vitro systems likewise increases. Such technological advances could enable more predictive study of human neurological and pathological phenomena, thereby enhancing the development of novel therapeutics and eventually removing ethically questionable and unreliable animal models all together. Here we describe recent efforts to create more complex multicell-type models incorporating hiPSC-derived neuronal elements and describe their uses in studying nervous system development and disease.

Use of multielectrode arrays has shown that the electrophysiological properties of hiPSC-derived neurons improve over time and that the level of spontaneous activity is increased through coculture with rodent astrocytes [Odawara et al., 2014]. Specifically, spontaneous firing rates in coculture on day 35 were twice the level reported in neuron-only controls, and mixed populations could be maintained for more than 120 days. More recently, coculture of hiPSC-derived cortical neurons with human astrocytes showed more frequent and synchronized spike trains as well as more dynamic changes in overall spike patterns compared with neuron-only controls [Kuijlaars et al., 2016; Kayama et al., 2018]. The occurrence of temporally coordinated spiking patterns may represent physiological signs of organized circuits within the cultured hiPSC-derived neuronal population, indicating the value of astrocytes on neuronal organization and function in vitro. In addition to improving baseline function, astrocytes have been shown to effectively rescue defects in neurogenesis of dopaminergic neurons exhibiting mitochondrial respiratory chain disruption [Du et al., 2018]. In this system, coculture of astrocytes with defective neurons restored mitochondrial functions, suggesting a significant role for astroglia in maintaining mitochondrial development and bioenergetics during neuronal differentiation. In an iPSC model of autism spectrum disorder, autism spectrum disorder-derived astrocytes were shown to interfere with normal neuronal development and researchers identified interleukin-6 secretion from these cells as a potential mechanism contributing to autism pathophysiology [Russo et al., 2018]. Models such as these highlight the potential for hiPSC-based coculture systems to investigate the synergistic effects in contributing to both normal functional development in neurons as well as disease onset and progression.

In addition to astrocytes, two other cell type models are being developed for the specific study of interplay between neurons and other central nervous system cell types. Activated hiPSC-derived microglia, cocultured with hiPSC-derived cortical neurons, have been shown to exhibit more physiologically correct behaviors than monoculture controls. These behaviors include the downregulation of pathogen response pathways and a more anti-inflammatory cytokine-based response [Haenseler et al., 2017]. Methods for producing myelinating oligodendrocytes from hiPSC are also available [Wang et al., 2013; Ehrlich et al., 2017]. Such cells have been shown to produce myelin basic protein that engages neurofilament-positive axons from both primary [Wang et al., 2013] and hiPSC-derived [Ehrlich et al., 2017] human neurons when maintained in coculture.

The interaction of neurons with peripheral tissue cell types is also being investigated using hiPSC-based models. Human iPSC-derived motor neurons have been cocultured with skeletal muscle from various human and nonhuman sources as a means to study neuromuscular junction formation and function [Demestre et al., 2015; Puttonen et al., 2015; Santhanam et al., 2018]. Such models can be used to test the efficacy of pharmacological agents as well as to model synaptic breakdown in cases of neuromuscular disorders, such as spinal muscular atrophy [Yoshida et al., 2015]. As our ability to promote skeletal muscle differentiation and maturation from hiPSC sources improves [Chal et al., 2015, 2016; Xi et al., 2017], we can expect further advances in modeling of neuromuscular development, function, and breakdown to occur. Production of hiPSC-derived Schwann cells has been published [Liu et al., 2012; Cai et al., 2017], but their capacity to myelinate human neurons has yet to be reported within in vitro cocultures, highlighting the difficulty in producing such responses in human systems and an important avenue for future study. Innervation of cardiac muscle with sympathetic neurons has been reported and the capacity for neuronal activation to regulate spontaneous beat behavior in hiPSC-derived cardiomyocytes has been demonstrated [Oh et al., 2016]. Reports such as these indicate the potential of hiPSC-derived in vitro coculture systems for studying the interactions between neurons and peripheral tissues. Given that the primary roles of these peripheral neuronal subtypes are to regulate the function of nonneuronal tissues, coculture platforms such as these represent necessary technologies to enable accurate assessment of neuronal function. Not only do such systems represent the means to assay novel drugs and therapeutics, but they also offer the possibility of modeling peripheral neurodegenerative disease states that could not be effectively studied in monocultures of hiPSC-derived neurons.

Movement toward more complex multiorgan models is hampered by the need to maintain optimal culture conditions for disparate cell types. The establishment of 3+ cell or tissue types within controlled in vitro platforms is relatively rare but it is an exciting area of current research due to their potential to model complex tissue-tissue interplay. The development of these so-called organs-on-chips is a rapidly evolving field within bioengineering and is reviewed in detail elsewhere [Huh et al., 2012; Wang et al., 2018b]. The capacity for such systems to model complex neurological function has yet to be demonstrated but remains a tantalizing prospect for future research as our ability to generate more complex models increases.

In addition to multicell type models, movement towards 3-D organoids represents an alternative method for increasing the complexity of hiPSC neuronal models as a means to better recapitulate neurological function in health and disease. Single cell RNA sequencing comparing human cerebral organoids derived from embryonic and hiPSC sources with fetal neocortex has shown that cells differentiated within organoid structures display genetic programs similar to those of the fetal cerebral cortex [Lancaster et al., 2013; Camp et al., 2015]. Specifically, researchers showed that more than 80% of genes implicated in neocortex development that are differentially expressed along the fetal cortex lineage have similar expression profiles in organoid and fetal cerebral cortex samples. This finding is of critical importance as it confirms the ability of such tissue constructs to mirror the development of the neocortex in humans and therefore its potential to act as a suitable surrogate for studying neurodevelopment. Furthermore, studies of layer specific midbrain markers in neuronal organoids has illustrated that such cells adopt a midbrain dopaminergic phenotype [Tieng et al., 2014; Jo et al., 2016] and express neuromelanin-like granules that are structurally similar to those isolated from human substantia nigra tissues – a feature absent from monolayer cultures and organoids produced from mouse cell sources [Jo et al., 2016]. When using hiPSCs derived from microcephaly patients, researchers found that cells within neuronal organoids exhibited premature neuronal differentiation and highlighted this defect as a potential pathological mechanism in this disease [Lancaster et al., 2013]. Additionally, brain region-specific organoids have been used to model exposure to the Zika virus [Qian et al., 2016]. Infection was shown to increase cell death and reduced proliferation, leading to a decreased neuronal cell layer volume resembling microcephaly. It is clear that advanced organoids have the capacity to obtain results not achievable in simpler 2-D systems and results described herein highlight the value of such culture models in elucidating disease-specific mechanisms.

In recent years, rapid progress has been made in the creation of in vitro systems for studying human neurodevelopment and degeneration. However, significant hurdles remain before the adoption of hiPSC-based systems can offer accurate modeling of human neural tissue. For the most part, both 2-D and 3-D models of the human cortex fail to recapitulate the layered structure of the native tissue. Establishment of such structures is likely to be necessary in order to model higher brain function, including mechanisms related to learning and memory, which may be required for accurate modeling of AD and associated dementias. The use of agarose-alginate gels to create layers of cortical neurons has been shown to offer a viable method for controlling the interaction of layered cortical neurons, although this method has yet to be employed in the maintenance of hiPSC-derived cells [Kunze et al., 2011]. More recently, Kim et al. [2017] used polydimethylsiloxane and collagen hydrogels to recreate the CA3-CA1 hippocampal neural circuit in a monolithic hydrogel and demonstrate functional connectivity between neuronal populations. This work was again achieved using primary rodent neurons and adoption of human cell sources with such bioengineering technologies represents a critical step towards better modeling of human nervous system function. Layered models of hiPSC-derived cortical neurons have been reportedly generated in 3-D using suspension culture and timed application of rostral neutralizing factors to promote the formation of polarized radial glia, intermediate progenitors, and organized, layer-specific cortical neurons [Mariani et al., 2012]. Similarly, Matrigel scaffolds coupled with a spinning bioreactor have been shown to yield cortical-like structures in which the cells were shown to closely follow the endogenous developmental program of the cerebral cortex [Lancaster and Knoblich, 2014]. As such models become more widespread, methods to overcome hypoxia-induced cell death in larger, more cell-dense platforms will become essential. Additionally, protocols for assessing function in these engineered tissues must be carefully considered. Analysis of slices of primary neural tissue are commonly used for electrophysiological assessment and similar methods may be applicable to engineered human tissues. Alternatively, optical mapping or insertion of electrode arrays could be employed to measure function in situ.

For the study of age-related neurodegenerative disease, it is necessary to understand the changes occurring between a healthy, mature neuron and an aged, dysfunctional neuron. Because the study of this phenomenon is challenging in vivo, a hurdle remains to create a comprehensive in vitro model of neurodegeneration that integrates the risks of cellular aging with the positive aspects of hiPSC technology. The work described above regarding the overexpression of progerin to exacerbate age-associated degenerative phenotypes is promising, but the need exists to identify additional molecular drivers of nonsyndromic aging that might predispose human neurons to age-related cellular dysfunction. In this regard, examination of epigenetic factors may represent a plausible target as epigenetic regulation is not only a defined “hallmark of aging” [López-Otín et al., 2013] but also plays a critical role in neuronal function and cognition. Importantly, HDAC inhibitors can ameliorate a broad range of neurodegenerative phenotypes [Hommet et al., 2007; Xuan et al., 2012; Falkenberg and Johnstone, 2014] and hiPSC-derived neurons are amenable to preclinical screening paradigms [Medda et al., 2016; Brownjohn et al., 2017].

The generation of more complex cortical models is likely to have a negative impact on throughput, cost, and potentially culture consistency. While this may be a minor concern to academic laboratories, such considerations may limit the applicability of novel culture platforms for use in preclinical therapeutic development. Consequentially, an issue worthy of discussion is exactly how much complexity is necessary to effectively model a given biological mechanism. It seems sensible that future screening modalities will offer a range of complexities for studying different aspects of neurodegenerative disease. Simple cell-based models can likely be relied on for investigation of basic cellular mechanisms. Multicell type, organized 3-D models may then be employed at later stages of therapy development to assay what impact modulation of these specific mechanisms within a given cell type has on overall function within engineered human neural tissues.

Although cocultures of hiPSC-derived neurons with microglia have been reported [Haenseler et al., 2017], their ability to faithfully recapitulate inflammatory responses within in vitro models has yet to be demonstrated. Neuroinflammation is a hallmark of AD and neurodegenerative diseases in general [Heneka et al., 2015; Walters et al., 2016]. As such, inclusion of inflammatory cell types may well be necessary to induce a clinically relevant phenotype within engineered, hiPSC-based neural tissues. How microglia might be effectively included is an issue that has not been adequately addressed in most in vitro AD research. In addition to microglia, circulating macrophages would be necessary to effectively model neuroinflammation, but methods to create a circulating cell component within neuronal models represents and added layer of complexity that may be difficult to overcome in a reliable, reproducible, and cost-effective manner. This point raises the more general issue of how closely hiPSC-derived neuronal models can mimic the clinical phenotype presented in patients suffering from neurodegenerative conditions. Certainly, hiPSC-derived neurons have be used in novel high-throughput screening efforts, making them potentially useful for rapid preclinical studies [Medda et al., 2016; Brownjohn et al., 2017]. In light of these studies, it remains unclear whether inclusion of all central nervous system cell types in physiologically representative ratios and organizations is necessary to produce data that is truly predictive. If not, can models incorporating single cell sources be used to provide insight into a wide number of patient mutations or are individual patient-based models necessary? Can such systems be realistically established on a timescale likely to be of benefit to patients?

The more widespread availability of CRISPR/Cas9 gene editing may offer a way to avoid reliance on patient-derived cells and instead lead to the establishment of a core group of mutant lines used to provide more general insight into disease etiology. Integration of CRISPR-edited lines along with isogenic controls into more complex models of the human cortex may allow targeted investigation of specific mutations and their impact on normal cortical function. Furthermore, such systems may represent useful testbeds for preclinical analysis of therapeutic efficacy and toxicity without reliance on the generation of individual patient specific lines for each separate study.

As discussed above, the epigenetic signature of reprogrammed cells may represent a significant road block to the accurate in vitro modeling of human neurodegeneration. Interestingly, hiPSC-based cerebral organoids have been compared to fetal tissue and the transcriptomic dynamics of the engineered tissues was shown to faithfully follow the gene expression trajectories of early-to-mid fetal human brains [Luo et al., 2016]. Demethylated regions identified during organoid development overlapped with fetal brain regulatory elements, suggesting that inclusion of hiPSC-derived neurons in more complex 3-D models may offer an alternative method to improve recapitulation of the epigenetic state of cultured cells. However, whether such techniques can be employed to recreate the transcriptomic and epigenetic signature of aged brains has yet to be demonstrated. Methods to recreate an aged neuronal phenotype must likely be considered in addition to the development of more complex cortical models to ensure both the input cell and the engineered niche offer accurate representations of the native tissue in healthy and neurodegenerative states.

Human iPSC technologies offer an unprecedented level of potential to model any cell type and, therefore, disease state. The use of advanced stem cell models combined with a thorough understanding of the model’s advantages and restrictions is likely the best choice moving forward, underscoring the need for productive scientific collaboration as the current limitations of this technology are significant but not insurmountable. Additionally, these limitations can also be applied as lessons for modeling other complex conditions, including cardiomyopathies and cancers. As our ability to generate more accurate, subtype-specific cells with correct transcriptomic and epigenomic signatures improves so will our capacity to effectively model disease toward the elucidation of pathological mechanisms and even the establishment of therapeutic applications for patient-derived hiPSCs. The concordant development of more complex and physiologically relevant models of neural tissue offers exciting prospects for our future ability to model neurological form and function.

The authors declare that they have no conflict of interests.

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