Patient-Derived Induced Pluripotent Stem Cells (iPSCs) and Cerebral Organoids for Drug Screening and Development in Autism Spectrum Disorder: Opportunities and Challenges

Nitric oxide and peroxynitrite as new biomarkers for early diagnosis of autism

Autism spectrum disorder, or autism, is a neurodevelopmental disorder of the developing child's brain with a genetic causality. It can be diagnosed at about three years after birth when it begins to present itself via a range of neuropsychiatric symptoms. Nitric oxide is a crucial small molecule of life synthesized within cells of our body systems, including cells of our brain. Peroxynitrite is the product of reaction between superoxide anion and nitric oxide. It normally isomerizes into harmless nitrates or nitrites. However, when excessive superoxide anion is present, the cellular concentration of peroxynitrite can increase to a toxic level. Autism has been suggested to cause oxidative damage to brain cells. Until now, it is impossible to sample tissue from a live brain. Instead, stem cells can be derived (from an autism patient's somatic cells) which can then be differentiated and chemically directed to grow into miniature 3-dimensional tissue masses resembling specific brain regions (e.g., the cortex) called brain organoids. This review discusses utilizing nitric oxide and peroxynitrite as biomarkers and comparing their relative concentrations in stem cells and stem cell derived brain organoids of healthy and autistic individuals to develop a bioanalytical process for early diagnosis of autism.

Advances in the Differentiation of hiPSCs into Cerebellar Neuronal Cells

The cerebellum has historically been primarily associated with the regulation of precise motor functions. However, recent findings suggest that it also plays a pivotal role in the development of advanced cognitive functions, including learning, memory, and emotion regulation. Pathological changes in the cerebellum, whether congenital hereditary or acquired degenerative, can result in a diverse spectrum of disorders, ranging from genetic spinocerebellar ataxias to psychiatric conditions such as autism, and schizophrenia. While studies in animal models have significantly contributed to our understanding of the genetic networks governing cerebellar development, it is important to note that the human cerebellum follows a protracted developmental timeline compared to the neocortex. Consequently, employing animal models to uncover human-specific molecular events in cerebellar development presents significant challenges. The emergence of human induced pluripotent stem cells (hiPSCs) has provided an invaluable tool for creating human-based culture systems, enabling the modeling and analysis of cerebellar physiology and pathology. hiPSCs and their differentiated progenies can be derived from patients with specific disorders or carrying distinct genetic variants. Importantly, they preserve the unique genetic signatures of the individuals from whom they originate, allowing for the elucidation of human-specific molecular and cellular processes involved in cerebellar development and related disorders. This review focuses on the technical advancements in the utilization of hiPSCs for the generation of both 2D cerebellar neuronal cells and 3D cerebellar organoids.

The Promise and Potential of Brain Organoids

Brain organoids are 3D in vitro culture systems derived from human pluripotent stem cells that self-organize to model features of the (developing) human brain. This review examines the techniques behind organoid generation, their current and potential applications, and future directions for the field. Brain organoids possess complex architecture containing various neural cell types, synapses, and myelination. They have been utilized for toxicology testing, disease modeling, infection studies, personalized medicine, and gene-environment interaction studies. An emerging concept termed Organoid Intelligence (OI) combines organoids with artificial intelligence systems to generate learning and memory, with the goals of modeling cognition and enabling biological computing applications. Brain organoids allow neuroscience studies not previously achievable with traditional techniques, and have the potential to transform disease modeling, drug development, and the understanding of human brain development and disorders. The aspirational vision of OI parallels the origins of artificial intelligence, and efforts are underway to map a roadmap toward its realization. In summary, brain organoids constitute a disruptive technology that is rapidly advancing and gaining traction across multiple disciplines.

Electrophysiological insights with brain organoid models: a brief review

Brain organoid is a three-dimensional (3D) tissue derived from stem cells such as induced pluripotent stem cells (iPSCs) embryonic stem cells (ESCs) that reflect real human brain structure. It replicates the complexity and development of the human brain, enabling studies of the human brain in vitro. With emerging technologies, its application is various, including disease modeling and drug screening. A variety of experimental methods have been used to study structural and molecular characteristics of brain organoids. However, electrophysiological analysis is necessary to understand their functional characteristics and complexity. Although electrophysiological approaches have rapidly advanced for monolayered cells, there are some limitations in studying electrophysiological and neural network characteristics due to the lack of 3D characteristics. Herein, electrophysiological measurement and analytical methods related to neural complexity and 3D characteristics of brain organoids are reviewed. Overall, electrophysiological understanding of brain organoids allows us to overcome limitations of monolayer in vitro cell culture models, providing deep insights into the neural network complex of the real human brain and new ways of disease modeling. [BMB Reports 2024; 57(7): 311-317].

Mesenchymal Stem Cells and Purinergic Signaling in Autism Spectrum Disorder: Bridging the Gap between Cell-Based Strategies and Neuro-Immune Modulation

The prevalence of autism spectrum disorder (ASD) is still increasing, which means that this neurodevelopmental lifelong pathology requires special scientific attention and efforts focused on developing novel therapeutic approaches. It has become increasingly evident that neuroinflammation and dysregulation of neuro-immune cross-talk are specific hallmarks of ASD, offering the possibility to treat these disorders by factors modulating neuro-immunological interactions. Mesenchymal stem cell-based therapy has already been postulated as one of the therapeutic approaches for ASD; however, less is known about the molecular mechanisms of stem cell influence. One of the possibilities, although still underestimated, is the paracrine purinergic activity of MSCs, by which stem cells ameliorate inflammatory reactions. Modulation of adenosine signaling may help restore neurotransmitter balance, reduce neuroinflammation, and improve overall brain function in individuals with ASD. In our review article, we present a novel insight into purinergic signaling, including but not limited to the adenosinergic pathway and its role in neuroinflammation and neuro-immune cross-talk modulation. We anticipate that by achieving a greater understanding of the purinergic signaling contribution to ASD and related disorders, novel therapeutic strategies may be devised for patients with autism in the near future.

Induced Pluripotent Stem Cells and Organoids in Advancing Neuropathology Research and Therapies

This review delves into the groundbreaking impact of induced pluripotent stem cells (iPSCs) and three-dimensional organoid models in propelling forward neuropathology research. With a focus on neurodegenerative diseases, neuromotor disorders, and related conditions, iPSCs provide a platform for personalized disease modeling, holding significant potential for regenerative therapy and drug discovery. The adaptability of iPSCs, along with associated methodologies, enables the generation of various types of neural cell differentiations and their integration into three-dimensional organoid models, effectively replicating complex tissue structures in vitro. Key advancements in organoid and iPSC generation protocols, alongside the careful selection of donor cell types, are emphasized as critical steps in harnessing these technologies to mitigate tumorigenic risks and other hurdles. Encouragingly, iPSCs show promising outcomes in regenerative therapies, as evidenced by their successful application in animal models.

Application Prospect of Induced Pluripotent Stem Cells in Organoids and Cell Therapy

Since its inception, induced pluripotent stem cell (iPSC) technology has been hailed as a powerful tool for comprehending disease etiology and advancing drug screening across various domains. While earlier iPSC-based disease modeling and drug assessment primarily operated at the cellular level, recent years have witnessed a significant shift towards organoid-based investigations. Organoids derived from iPSCs offer distinct advantages, particularly in enabling the observation of disease progression and drug metabolism in an in vivo-like environment, surpassing the capabilities of iPSC-derived cells. Furthermore, iPSC-based cell therapy has emerged as a focal point of clinical interest. In this review, we provide an extensive overview of non-integrative reprogramming methods that have evolved since the inception of iPSC technology. We also deliver a comprehensive examination of iPSC-derived organoids, spanning the realms of the nervous system, cardiovascular system, and oncology, as well as systematically elucidate recent advancements in iPSC-related cell therapies.

Brain organoids: A revolutionary tool for modeling neurological disorders and development of therapeutics

Brain organoids are self-organized, three-dimensional (3D) aggregates derived from pluripotent stem cells that have cell types and cellular architectures resembling those of the developing human brain. The current understanding of human brain developmental processes and neurological disorders has advanced significantly with the introduction of this in vitro model. Brain organoids serve as a translational link between two-dimensional (2D) cultures and in vivo models which imitate the neural tube formation at the early and late stages and the differentiation of neuroepithelium with whole-brain regionalization. In addition, the generation of region-specific brain organoids made it possible to investigate the pathogenic and etiological aspects of acquired and inherited brain disease along with drug discovery and drug toxicity testing. In this review article, we first summarize an overview of the existing methods and platforms used for generating brain organoids and their limitations and then discuss the recent advancement in brain organoid technology. In addition, we discuss how brain organoids have been used to model aspects of neurodevelopmental and neurodegenerative diseases, including autism spectrum disorder (ASD), Rett syndrome, Zika virus-related microcephaly, Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD).

Retracing our steps: A review on autism research in children, its limitation and impending pharmacological interventions

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by three core impairments: impaired communication, impaired reciprocal social interaction, and restricted, repetitive, and stereotypical behavior patterns. Spectrum refers to the heterogeneity of presentation, severity of symptoms, and medical comorbidities associated with ASD. Among the most common underlying medical conditions are attention-deficit/hyperactivity disorder (ADHD), anxiety, depression, epilepsy, digestive disorders, metabolic disorders, and immune disorders. At present, in the absence of an objective and accurate diagnosis of ASD, such as a blood test, pharmacological management remains a challenge. There are no approved medications to treat the core symptoms of the disorder and behavioral interventions are typically used as first line treatment. Additionally, psychotropic drugs with different mechanisms of action have been approved to reduce associated symptoms and comorbidities, including aripiprazole, risperidone, and haloperidol for irritability and aggression, methylphenidate, atomoxetine, clonidine, and guanfacine for ADHD, and melatonin for sleep disturbances. The purpose of this review is to emphasize that it is imperative to develop objective, personalized diagnostic kits in order to tailor and individualize treatment strategies, as well as to describe the current pharmacological management options available in clinical practice and new prospects that may be helpful in managing ASD's core symptoms.

Opportunities and limitations for studying neuropsychiatric disorders using patient-derived induced pluripotent stem cells

Neuropsychiatric disorders affect a large proportion of the global population and there is an urgent need to understand the pathogenesis and to develop novel and improved treatments of these devastating disorders. However, the diverse symptomatology combined with complex polygenic etiology, and the limited access to disorder-relevant cell types in human brains represent a major obstacle for mechanistic disease research. Conventional animal models, such as rodents, are limited by inherent species differences in brain development, architecture, and function. Advances in human induced pluripotent stem cells (hiPSCs) technologies have provided platforms for new discoveries in neuropsychiatric disorders. First, hiPSC-based disease models enable unprecedented investigation of psychiatric disorders at the molecular, cellular, and structural levels. Second, hiPSCs derived from patients with known genetics, symptoms, and drug response profiles offer an opportunity to recapitulate pathogenesis in relevant cell types and provide novel approaches for understanding disease mechanisms and for developing effective treatments. Third, genome-editing technologies have extended the potential of hiPSCs for generating models to elucidate the genetic basis of rare monogenetic and complex polygenic psychiatric disorders and to establish the causality between genotype and phenotype. Here we review opportunities and limitations for studying psychiatric disorders using various hiPSC-derived model systems.

Autism Spectrum Disorder: Neurodevelopmental Risk Factors, Biological Mechanism, and Precision Therapy

Autism spectrum disorder (ASD) is a heterogeneous, behaviorally defined neurodevelopmental disorder. Over the past two decades, the prevalence of autism spectrum disorders has progressively increased, however, no clear diagnostic markers and specifically targeted medications for autism have emerged. As a result, neurobehavioral abnormalities, neurobiological alterations in ASD, and the development of novel ASD pharmacological therapy necessitate multidisciplinary collaboration. In this review, we discuss the development of multiple animal models of ASD to contribute to the disease mechanisms of ASD, as well as new studies from multiple disciplines to assess the behavioral pathology of ASD. In addition, we summarize and highlight the mechanistic advances regarding gene transcription, RNA and non-coding RNA translation, abnormal synaptic signaling pathways, epigenetic post-translational modifications, brain-gut axis, immune inflammation and neural loop abnormalities in autism to provide a theoretical basis for the next step of precision therapy. Furthermore, we review existing autism therapy tactics and limits and present challenges and opportunities for translating multidisciplinary knowledge of ASD into clinical practice.

An insight into the iPSCs-derived two-dimensional culture and three-dimensional organoid models for neurodegenerative disorders

The use of induced pluripotent stem cells (iPSCs) is a promising approach when used as models to study neurodegenerative disorders (NDDs) in vitro. iPSCs have been used in in vitro two-dimensional cultures; however, these two-dimensional cultures do not mimic the physiological three-dimensional cellular environment. The use of iPSCs-derived three-dimensional organoids has risen as a powerful alternative to using animal models to study NDDs. These iPSCs-derived three-dimensional organoids can resemble the complexity of the tissue of interest, making it an approachable, cost-effective technique, to study NDDs in an ethical manner. Furthermore, the use of iPSCs-derived organoids will be an important tool to develop new therapeutics and pharmaceutics to treat NDDs. Herein, we will highlight how iPSCs-derived two-dimensional cultures and three-dimensional organoids have been used to study NDDs, as well as the advantages and disadvantages of both techniques.

Bringing machine learning to research on intellectual and developmental disabilities: taking inspiration from neurological diseases

Intellectual and Developmental Disabilities (IDDs), such as Down syndrome, Fragile X syndrome, Rett syndrome, and autism spectrum disorder, usually manifest at birth or early childhood. IDDs are characterized by significant impairment in intellectual and adaptive functioning, and both genetic and environmental factors underpin IDD biology. Molecular and genetic stratification of IDDs remain challenging mainly due to overlapping factors and comorbidity. Advances in high throughput sequencing, imaging, and tools to record behavioral data at scale have greatly enhanced our understanding of the molecular, cellular, structural, and environmental basis of some IDDs. Fueled by the "big data" revolution, artificial intelligence (AI) and machine learning (ML) technologies have brought a whole new paradigm shift in computational biology. Evidently, the ML-driven approach to clinical diagnoses has the potential to augment classical methods that use symptoms and external observations, hoping to push the personalized treatment plan forward. Therefore, integrative analyses and applications of ML technology have a direct bearing on discoveries in IDDs. The application of ML to IDDs can potentially improve screening and early diagnosis, advance our understanding of the complexity of comorbidity, and accelerate the identification of biomarkers for clinical research and drug development. For more than five decades, the IDDRC network has supported a nexus of investigators at centers across the USA, all striving to understand the interplay between various factors underlying IDDs. In this review, we introduced fast-increasing multi-modal data types, highlighted example studies that employed ML technologies to illuminate factors and biological mechanisms underlying IDDs, as well as recent advances in ML technologies and their applications to IDDs and other neurological diseases. We discussed various molecular, clinical, and environmental data collection modes, including genetic, imaging, phenotypical, and behavioral data types, along with multiple repositories that store and share such data. Furthermore, we outlined some fundamental concepts of machine learning algorithms and presented our opinion on specific gaps that will need to be filled to accomplish, for example, reliable implementation of ML-based diagnosis technology in IDD clinics. We anticipate that this review will guide researchers to formulate AI and ML-based approaches to investigate IDDs and related conditions.

Engineering Organoids for in vitro Modeling of Phenylketonuria

Phenylketonuria is a recessive genetic disorder of amino-acid metabolism, where impaired phenylalanine hydroxylase function leads to the accumulation of neurotoxic phenylalanine levels in the brain. Severe cognitive and neuronal impairment are observed in untreated/late-diagnosed patients, and even early treated ones are not safe from life-long sequelae. Despite the wealth of knowledge acquired from available disease models, the chronic effect of Phenylketonuria in the brain is still poorly understood and the consequences to the aging brain remain an open question. Thus, there is the need for better predictive models, able to recapitulate specific mechanisms of this disease. Human induced pluripotent stem cells (hiPSCs), with their ability to differentiate and self-organize in multiple tissues, might provide a new exciting in vitro platform to model specific PKU-derived neuronal impairment. In this review, we gather what is known about the impact of phenylalanine in the brain of patients and highlight where hiPSC-derived organoids could contribute to the understanding of this disease.

Microglia-like Cells Promote Neuronal Functions in Cerebral Organoids

Human cerebral organoids, derived from induced pluripotent stem cells, offer a unique in vitro research window to the development of the cerebral cortex. However, a key player in the developing brain, the microglia, do not natively emerge in cerebral organoids. Here we show that erythromyeloid progenitors (EMPs), differentiated from induced pluripotent stem cells, migrate to cerebral organoids, and mature into microglia-like cells and interact with synaptic material. Patch-clamp electrophysiological recordings show that the microglia-like population supported the emergence of more mature and diversified neuronal phenotypes displaying repetitive firing of action potentials, low-threshold spikes and synaptic activity, while multielectrode array recordings revealed spontaneous bursting activity and increased power of gamma-band oscillations upon pharmacological challenge with NMDA. To conclude, microglia-like cells within the organoids promote neuronal and network maturation and recapitulate some aspects of microglia-neuron co-development in vivo, indicating that cerebral organoids could be a useful biorealistic human in vitro platform for studying microglia-neuron interactions.

Modeling schizophrenia with iPS cell technology and disease mouse models

Induced pluripotent stem cell (iPSC) technology, which enables the direct analysis of neuronal cells with the same genetic background as patients, has recently garnered significant attention in schizophrenia research. This technology is important because it enables a comprehensive interpretation using mice and human clinical research and cross-species verification. Here I review recent advances in modeling schizophrenia using iPSC technology, alongside the utility of disease mouse models.