Cerebral organoids derived from patients with Alzheimer's disease with PSEN1/2 mutations have defective tissue patterning and altered development

Engineering organoids as cerebral disease models

Cerebral organoids pioneered in replicating complex brain tissue architectures in vitro, offering a vast potential for human disease modeling. They enable the in vitro study of human physiological and pathophysiological mechanisms of various neurological diseases and disorders. The trajectory of technological advancements in brain organoid generation and engineering over the past decade indicates that the technology might, in the future, mature into indispensable solutions at the horizon of personalized and regenerative medicine. In this review, we highlight recent advances in the engineering of brain organoids as disease models and discuss some of the challenges and opportunities for future research in this rapidly evolving field.

Understanding monocyte-driven neuroinflammation in Alzheimer's disease using human brain organoid microphysiological systems

Increasing evidence suggests that Alzheimer's disease (AD) pathogenesis strongly correlates with neuroinflammation. Peripheral monocytes are crucial components of the human immune system that may play a role in neuroinflammation, but their contribution to AD pathogenesis is largely understudied partially due to the lack of appropriate human models. Here, we present human cortical organoid microphysiological systems (hCO-MPSs) for modeling dynamic AD neuroinflammation mediated by monocytes. By incorporating 3D printed devices into an existing cortical organoid protocol, 96 hCO-MPSs can be established with significantly reduced necrosis and hypoxia as well as enhanced viability within a commonly used 96 well plate, and each hCO-MPS consists of a doughnut-shaped hCO and a 3D printed device per well. Using this approach, monocytes from AD patients exhibit higher infiltration, decreased amyloid-beta (Aβ) clearance, and stronger inflammatory responses compared to monocytes from age-matched control donors. Moreover, pro-inflammatory effects such as elevated astrocyte activation and neuronal apoptosis were observed to be induced by AD monocytes. Furthermore, the significant increase in the expression of IL1B and CCL3, both at the transcriptional and protein levels, indicated the pivotal role of these cytokine and chemokine in monocyte-mediated AD neuroinflammation. Our findings provide insight for understanding monocytes' role in AD pathogenesis, and the user-friendly MPS models we present are compatible with existing laboratory settings, highlighting their potential for modeling neuroinflammation and developing new therapeutics for various neuroinflammatory diseases.

An integrated transcriptomic cell atlas of human neural organoids

Human neural organoids, generated from pluripotent stem cells in vitro, are useful tools to study human brain development, evolution and disease. However, it is unclear which parts of the human brain are covered by existing protocols, and it has been difficult to quantitatively assess organoid variation and fidelity. Here we integrate 36 single-cell transcriptomic datasets spanning 26 protocols into one integrated human neural organoid cell atlas totalling more than 1.7 million cells1-26. Mapping to developing human brain references27-30 shows primary cell types and states that have been generated in vitro, and estimates transcriptomic similarity between primary and organoid counterparts across protocols. We provide a programmatic interface to browse the atlas and query new datasets, and showcase the power of the atlas to annotate organoid cell types and evaluate new organoid protocols. Finally, we show that the atlas can be used as a diverse control cohort to annotate and compare organoid models of neural disease, identifying genes and pathways that may underlie pathological mechanisms with the neural models. The human neural organoid cell atlas will be useful to assess organoid fidelity, characterize perturbed and diseased states and facilitate protocol development.

Alzheimer's disease induced neurons bearing PSEN1 mutations exhibit reduced excitability

Alzheimer's disease (AD) is a devastating neurodegenerative condition that affects memory and cognition, characterized by neuronal loss and currently lacking a cure. Mutations in PSEN1 (Presenilin 1) are among the most common causes of early-onset familial AD (fAD). While changes in neuronal excitability are believed to be early indicators of AD progression, the link between PSEN1 mutations and neuronal excitability remains to be fully elucidated. This study examined iPSC-derived neurons (iNs) from fAD patients with PSEN1 mutations S290C or A246E, alongside CRISPR-corrected isogenic cell lines, to investigate early changes in excitability. Electrophysiological profiling revealed reduced excitability in both PSEN1 mutant iNs compared to their isogenic controls. Neurons bearing S290C and A246E mutations exhibited divergent passive membrane properties compared to isogenic controls, suggesting distinct effects of PSEN1 mutations on neuronal excitability. Additionally, both PSEN1 backgrounds exhibited higher current density of voltage-gated potassium (Kv) channels relative to their isogenic iNs, while displaying comparable voltage-gated sodium (Nav) channel current density. This suggests that the Nav/Kv imbalance contributes to impaired neuronal firing in fAD iNs. Deciphering these early cellular and molecular changes in AD is crucial for understanding disease pathogenesis.

Functional Neural Networks in Human Brain Organoids

Human brain organoids are 3-dimensional brain-like tissues derived from human pluripotent stem cells and hold promising potential for modeling neurological, psychiatric, and developmental disorders. While the molecular and cellular aspects of human brain organoids have been intensively studied, their functional properties such as organoid neural networks (ONNs) are largely understudied. Here, we summarize recent research advances in understanding, characterization, and application of functional ONNs in human brain organoids. We first discuss the formation of ONNs and follow up with characterization strategies including microelectrode array (MEA) technology and calcium imaging. Moreover, we highlight recent studies utilizing ONNs to investigate neurological diseases such as Rett syndrome and Alzheimer's disease. Finally, we provide our perspectives on the future challenges and opportunities for using ONNs in basic research and translational applications.

Experimental Cell Models for Investigating Neurodegenerative Diseases

Experimental models play a pivotal role in biomedical research, facilitating the understanding of disease mechanisms and the development of novel therapeutics. This is particularly true for neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and motor neuron disease, which present complex challenges for research and therapy development. In this work, we review the recent literature about experimental models and motor neuron disease. We identified three main categories of models that are highly studied by scientists. In fact, experimental models for investigating these diseases encompass a variety of approaches, including modeling the patient's cell culture, patient-derived induced pluripotent stem cells, and organoids. Each model offers unique advantages and limitations, providing researchers with a range of tools to address complex biological questions. Here, we discuss the characteristics, applications, and recent advancements in terms of each model system, highlighting their contributions to advancing biomedical knowledge and translational research.

Strategies for modeling aging and age-related diseases

The ability to reprogram patient-derived-somatic cells to IPSCs (Induced Pluripotent Stem Cells) has led to a better understanding of aging and age-related diseases like Parkinson's, and Alzheimer's. The established patient-derived disease models mimic disease pathology and can be used to design drugs for aging and age-related diseases. However, the age and genetic mutations of the donor cells, the employed reprogramming, and the differentiation protocol might often pose challenges in establishing an appropriate disease model. In this review, we will focus on the various strategies for the successful reprogramming and differentiation of patient-derived cells to disease models for aging and age-related diseases, emphasizing the accuracy in the recapitulation of disease pathology and ways to overcome the limitations of its potential application in cell replacement therapy and drug development.

Integration of single-cell sequencing with machine learning and Mendelian randomization analysis identifies the NAP1L1 gene as a predictive biomarker for Alzheimer's disease

Background

The most effective approach to managing Alzheimer's disease (AD) lies in identifying reliable biomarkers for AD to forecast the disease in advance, followed by timely early intervention for patients.

Methods

Transcriptomic data on peripheral blood mononuclear cells (PBMCs) from patients with AD and the control group were collected, and preliminary data processing was completed using standardized analytical methods. PBMCs were initially segmented into distinct subpopulations, and the divisions were progressively refined until the most significantly altered cell populations were identified. A combination of high-dimensional weighted gene co-expression analysis (hdWGCNA), cellular communication, pseudotime analysis, and single-cell regulatory network inference and clustering (SCENIC) analysis was used to conduct single-cell transcriptomics analysis and identify key gene modules from them. Genes were screened using machine learning (ML) in the key gene modules, and internal and external dataset validations were performed using multiple ML methods to test predictive performance. Finally, bidirectional Mendelian randomization (MR) analysis, regional linkage analysis, and the Steiger test were employed to analyze the key gene.

Result

A significant decrease in non-classical monocytes was detected in PMBC of AD patients. Subsequent analyses revealed the inherent connection of non-classical monocytes to AD, and the NAP1L1 gene identified within its gene module appeared to exhibit some association with AD as well.

Conclusion

The NAP1L1 gene is a potential predictive biomarker for AD.

Tackling neurodegeneration in vitro with omics: a path towards new targets and drugs

Drug discovery is a generally inefficient and capital-intensive process. For neurodegenerative diseases (NDDs), the development of novel therapeutics is particularly urgent considering the long list of late-stage drug candidate failures. Although our knowledge on the pathogenic mechanisms driving neurodegeneration is growing, additional efforts are required to achieve a better and ultimately complete understanding of the pathophysiological underpinnings of NDDs. Beyond the etiology of NDDs being heterogeneous and multifactorial, this process is further complicated by the fact that current experimental models only partially recapitulate the major phenotypes observed in humans. In such a scenario, multi-omic approaches have the potential to accelerate the identification of new or repurposed drugs against a multitude of the underlying mechanisms driving NDDs. One major advantage for the implementation of multi-omic approaches in the drug discovery process is that these overarching tools are able to disentangle disease states and model perturbations through the comprehensive characterization of distinct molecular layers (i.e., genome, transcriptome, proteome) up to a single-cell resolution. Because of recent advances increasing their affordability and scalability, the use of omics technologies to drive drug discovery is nascent, but rapidly expanding in the neuroscience field. Combined with increasingly advanced in vitro models, which particularly benefited from the introduction of human iPSCs, multi-omics are shaping a new paradigm in drug discovery for NDDs, from disease characterization to therapeutics prediction and experimental screening. In this review, we discuss examples, main advantages and open challenges in the use of multi-omic approaches for the in vitro discovery of targets and therapies against NDDs.

Generation of Alzheimer's Disease Model Derived from Induced Pluripotent Stem Cells with APP Gene Mutation

Alzheimer's disease (AD), the most common cause of dementia, is characterized by disruptions in memory, cognition, and personality, significantly impacting morbidity and mortality rates among older adults. However, the exact pathophysiological mechanism of AD remains unknown, and effective treatment options for AD are still lacking. Human induced pluripotent stem cells (iPSC) are emerging as promising platforms for disease research, offering the ability to model the genetic mutations associated with various conditions. Patient-derived iPSCs are useful for modeling neurodegenerative and neurodevelopmental disorders. In this study, we generated AD iPSCs from peripheral blood mononuclear cells obtained from a 65-year-old patient with AD carrying the E682K mutation in the gene encoding the amyloid precursor protein. Cerebral organoids derived from AD iPSCs recapitulated the AD phenotype, exhibiting significantly increased levels of tau protein. Our analysis revealed that an iPSC disease model of AD is a valuable assessment tool for pathophysiological research and drug screening.

Simple modeling of familial Alzheimer's disease using human pluripotent stem cell-derived cerebral organoid technology

BACKGROUND

Cerebral organoids (COs) are the most advanced in vitro models that resemble the human brain. The use of COs as a model for Alzheimer's disease (AD), as well as other brain diseases, has recently gained attention. This study aimed to develop a human AD CO model using normal human pluripotent stem cells (hPSCs) that recapitulates the pathological phenotypes of AD and to determine the usefulness of this model for drug screening.

METHODS

We established AD hPSC lines from normal hPSCs by introducing genes that harbor familial AD mutations, and the COs were generated using these hPSC lines. The pathological features of AD, including extensive amyloid-β (Aβ) accumulation, tauopathy, and neurodegeneration, were analyzed using enzyme-linked immunosorbent assay, Amylo-Glo staining, thioflavin-S staining, immunohistochemistry, Bielschowsky's staining, and western blot analysis.

RESULTS

The AD COs exhibited extensive Aβ accumulation. The levels of paired helical filament tau and neurofibrillary tangle-like silver deposits were highly increased in the AD COs. The number of cells immunoreactive for cleaved caspase-3 was significantly increased in the AD COs. In addition, treatment of AD COs with BACE1 inhibitor IV, a β-secretase inhibitor, and compound E, a γ-secretase inhibitor, significantly attenuated the AD pathological features.

CONCLUSION

Our model effectively recapitulates AD pathology. Hence, it is a valuable platform for understanding the mechanisms underlying AD pathogenesis and can be used to test the efficacy of anti-AD drugs.

METTL3-dependent m6A modification of PSEN1 mRNA regulates craniofacial development through the Wnt/β-catenin signaling pathway

Craniofacial malformations, often associated with syndromes, are prevalent birth defects. Emerging evidence underscores the importance of m6A modifications in various bioprocesses such as stem cell differentiation, tissue development, and tumorigenesis. Here, in vivo, experiments with zebrafish models revealed that mettl3-knockdown embryos at 144 h postfertilization exhibited aberrant craniofacial features, including altered mouth opening, jaw dimensions, ethmoid plate, tooth formation and hypoactive behavior. Similarly, low METTL3 expression inhibited the proliferation and migration of BMSCs, HEPM cells, and DPSCs. Loss of METTL3 led to reduced mRNA m6A methylation and PSEN1 expression, impacting craniofacial phenotypes. Co-injection of mettl3 or psen1 mRNA rescued the level of Sox10 fusion protein, promoted voluntary movement, and mitigated abnormal craniofacial phenotypes induced by mettl3 knockdown in zebrafish. Mechanistically, YTHDF1 enhanced the mRNA stability of m6A-modified PSEN1, while decreased METTL3-mediated m6A methylation hindered β-catenin binding to PSEN1, suppressing Wnt/β-catenin signaling. Pharmacological activation of the Wnt/β-catenin pathway partially alleviated the phenotypes of mettl3 morphant and reversed the decreases in cell proliferation and migration induced by METTL3 silencing. This study elucidates the pivotal role of METTL3 in craniofacial development via the METTL3/YTHDF1/PSEN1/β-catenin signaling axis.