CDiP technology for reverse engineering of sporadic Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disease that causes cognitive impairment for which neither treatable nor preventable approaches have been confirmed. Although genetic factors are considered to contribute to sporadic AD, for the majority of AD patients, the exact causes of AD aren't fully understood. For AD genetics, we developed cellular dissection of polygenicity (CDiP) technology to identify the smallest unit of AD, i.e., genetic factors at a cellular level. By CDiP, we found potential therapeutic targets, a rare variant for disease stratification, and polygenes to predict real-world AD by using the real-world data of AD cohort studies (Alzheimer's Disease Neuroimaging Initiative: ADNI and Japanese Alzheimer's Disease Neuroimaging Initiative: J-ADNI). In this review, we describe the components and results of CDiP in AD, induced pluripotent stem cell (iPSC) cohort, a cell genome-wide association study (cell GWAS), and machine learning. And finally, we discuss the future perspectives of CDiP technology for reverse engineering of sporadic AD toward AD eradication.

Prediction Model of Amyotrophic Lateral Sclerosis by Deep Learning with Patient Induced Pluripotent Stem Cells.

In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence-based prediction model of ALS using induced pluripotent stem cells (iPSCs). Images of spinal motor neurons derived from healthy control subject and ALS patient iPSCs were analyzed by a convolutional neural network, and the algorithm achieved an area under the curve of 0.97 for classifying healthy control and ALS. This prediction model by deep learning algorithm with iPSC technology could support the diagnosis and may provide proactive treatment of ALS through future prospective research. ANN NEUROL 2021;89:1226-1233.

Temporal relation between neural activity and neurite pruning on a numerical model and a microchannel device with micro electrode array.

Synapse elimination and neurite pruning are essential processes for the formation of neuronal circuits. These regressive events depend on neural activity and occur in the early postnatal days known as the critical period, but what makes this temporal specificity is not well understood. One possibility is that the neural activities during the developmentally regulated shift of action of GABA inhibitory transmission lead to the critical period. Moreover, it has been reported that the shifting action of the inhibitory transmission on immature neurons overlaps with synapse elimination and neurite pruning and that increased inhibitory transmission by drug treatment could induce temporal shift of the critical period. However, the relationship among these phenomena remains unclear because it is difficult to experimentally show how the developmental shift of inhibitory transmission influences neural activities and whether the activities promote synapse elimination and neurite pruning. In this study, we modeled synapse elimination in neuronal circuits using the modified Izhikevich's model with functional shifting of GABAergic transmission. The simulation results show that synaptic pruning within a specified period like the critical period is spontaneously generated as a function of the developmentally shifting inhibitory transmission and that the specific firing rate and increasing synchronization of neural circuits are seen at the initial stage of the critical period. This temporal relationship was experimentally supported by an in vitro primary culture of rat cortical neurons in a microchannel on a multi-electrode array (MEA). The firing rate decreased remarkably between the 18-25 days in vitro (DIV), and following these changes in the firing rate, the neurite density was slightly reduced. Our simulation and experimental results suggest that decreasing neural activity due to developing inhibitory synaptic transmission could induce synapse elimination and neurite pruning at particular time such as the critical period. Additionally, these findings indicate that we can estimate the maturity level of inhibitory transmission and the critical period by measuring the firing rate and the degree of synchronization in engineered neural networks.

Mutant α-synuclein causes death of human cortical neurons via ERK1/2 and JNK activation.

Synucleinopathies refer to a group of disorders characterized by SNCA/α-synuclein (α-Syn)-containing cytoplasmic inclusions and neuronal cell loss in the nervous system including the cortex, a common feature being cognitive impairment. Still, the molecular pathogenesis of cognitive decline remains poorly understood, hampering the development of effective treatments. Here, we generated induced pluripotent stem cells (iPSCs) derived from familial Parkinson's disease (PD) patients carrying SNCA A53T mutation, differentiating them into cortical neurons by a direct conversion method. Patient iPSCs-derived cortical neurons harboring mutant α-Syn exhibited increased α-Syn-positive aggregates, shorter neurites, and time-dependent vulnerability. Furthermore, RNA-sequencing analysis, followed by biochemical validation, identified the activation of the ERK1/2 and JNK cascades in cortical neurons with SNCA A53T mutation. This result was consistent with a reverted phenotype of neuronal death in cortical neurons when treated with ERK1/2 and JNK inhibitors, respectively. Our findings emphasize the role of ERK1/2 and JNK cascades in the vulnerability of cortical neurons in synucleinopathies, and they could pave the way toward therapeutic advancements for synucleinopathies.

Few-shot prediction of amyloid ß accumulation from mainly unpaired data on biomarker candidates.

The pair-wise observation of the input and target values obtained from the same sample is mandatory in any prediction problem. In the biomarker discovery of Alzheimer's disease (AD), however, obtaining such paired data is laborious and often avoided. Accumulation of amyloid-beta (Aß) in the brain precedes neurodegeneration in AD, and the quantitative accumulation level may reflect disease progression in the very early phase. Nevertheless, the direct observation of Aß is rarely paired with the observation of other biomarker candidates. To this end, we established a method that quantitatively predicts Aß accumulation from biomarker candidates by integrating the mostly unpaired observations via a few-shot learning approach. When applied to 5xFAD mouse behavioral data, the proposed method predicted the accumulation level that conformed to the observed amount of Aß in the samples with paired data. The results suggest that the proposed model can contribute to discovering Aß predictability-based biomarkers.

One-step induction of photoreceptor-like cells from human iPSCs by delivering transcription factors.

Retinal dystrophies (RDs) lead to irreversible vision impairment with no radical treatment. Although photoreceptor cells (PRCs) differentiated from human induced pluripotent stem cells (iPSCs) are essential for the study of RDs as a scalable source, current differentiation methods for PRCs require multiple steps. To address these issues, we developed a method to generate PRCs from human iPSCs by introducing the transcription factors, CRX and NEUROD1. This approach enabled us to generate induced photoreceptor-like cells (iPRCs) expressing PRC markers. Single-cell RNA sequencing revealed the transcriptome of iPRCs in which the genes associated with phototransduction were expressed. Generated iPRCs exhibited their functional properties in calcium imaging. Furthermore, light-induced damage on iPRCs was inhibited by an antioxidant compound. This simple approach would facilitate the availability of materials for PRC-related research and provide a useful application for disease modeling and drug discovery.

Dissection of the polygenic architecture of neuronal Aß production using a large sample of individual iPSC lines derived from Alzheimer's disease patients.

Genome-wide association studies have demonstrated that polygenic risks shape Alzheimer's disease (AD). To elucidate the polygenic architecture of AD phenotypes at a cellular level, we established induced pluripotent stem cells from 102 patients with AD, differentiated them into cortical neurons and conducted a genome-wide analysis of the neuronal production of amyloid ß (Aß). Using such a cellular dissection of polygenicity (CDiP) approach, we identified 24 significant genome-wide loci associated with alterations in Aß production, including some loci not previously associated with AD, and confirmed the influence of some of the corresponding genes on Aß levels by the use of small interfering RNA. CDiP genotype sets improved the predictions of amyloid positivity in the brains and cerebrospinal fluid of patients in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Secondary analyses of exome sequencing data from the Japanese ADNI and the ADNI cohorts focused on the 24 CDiP-derived loci associated with alterations in Aß led to the identification of rare AD variants in KCNMA1.

Human induced pluripotent stem cells generated from a patient with idiopathic basal ganglia calcification.

Idiopathic basal ganglia calcification (IBGC) is a rare neurodegenerative disease, characterized by abnormal calcium deposits in basal ganglia of the brain. The affected individuals exhibit movement disorders, and progressive deterioration of cognitive and psychiatric ability. The genetic cause of the disease is mutation in one of several different genes, SLC20A2, PDGFB, PDGFRB, XPR1 or MYORG, which inheritably or sporadically occurs. Here we generated an induced pluripotent stem cell (iPSC) line from an IBGC patient, which is likely be a powerful tool for revealing the pathomechanisms and exploring potential therapeutic candidates of IBGC.

Induction of inverted morphology in brain organoids by vertical-mixing bioreactors.

Organoid technology provides an opportunity to generate brain-like structures by recapitulating developmental steps in the manner of self-organization. Here we examined the vertical-mixing effect on brain organoid structures using bioreactors and established inverted brain organoids. The organoids generated by vertical mixing showed neurons that migrated from the outer periphery to the inner core of organoids, in contrast to orbital mixing. Computational analysis of flow dynamics clarified that, by comparison with orbital mixing, vertical mixing maintained the high turbulent energy around organoids, and continuously kept inter-organoid distances by dispersing and adding uniform rheological force on organoids. To uncover the mechanisms of the inverted structure, we investigated the direction of primary cilia, a cellular mechanosensor. Primary cilia of neural progenitors by vertical mixing were aligned in a multidirectional manner, and those by orbital mixing in a bidirectional manner. Single-cell RNA sequencing revealed that neurons of inverted brain organoids presented a GABAergic character of the ventral forebrain. These results suggest that controlling fluid dynamics by biomechanical engineering can direct stem cell differentiation of brain organoids, and that inverted brain organoids will be applicable for studying human brain development and disorders in the future.

Establishment of induced pluripotent stem cells from schizophrenia discordant fraternal twins.

Schizophrenia (SCZ) is one of the major psychiatric disorders. The genetic factor is certainly influential in the onset of the disease but is not decisive. There is no identified molecular/cellular marker of the disease, and the pathomechanism is still unknown. In this study, we generated human induced pluripotent stem cells (iPSCs) derived from SCZ-discordant fraternal twins, and they could contribute to elucidation of the pathomechanism of SCZ.

Generation of a human induced pluripotent stem cell line, BRCi009-A, derived from a patient with glycogen storage disease type 1a.

Glycogen storage disease type 1a (GSD1a) is an autosomal recessive disorder caused by mutations of the glucose-6-phosphatase (G6PC) gene. Mutations of the G6PC gene lead to excessive accumulation of glycogen in the liver, kidney, and intestinal mucosa due to the deficiency of microsomal glucose-6-phosphatase. Human induced pluripotent stem cells (iPSCs) enable the production of patient-derived hepatocytes in culture and are therefore a promising tool for modeling GSD1a. Here, we report the establishment of human iPSCs from a GSD1a patient carrying a G6PC mutation (c.648G > T; p.Leu216 = ).

Development of neural population activity toward self-organized criticality.

Self-organized criticality (SoC), a spontaneous dynamic state established and maintained in networks of moderate complexity, is a universal characteristic of neural systems. Such systems produce cascades of spontaneous activity that are typically characterized by power-law distributions and rich, stable spatiotemporal patterns (i.e., neuronal avalanches). Since the dynamics of the critical state confer advantages in information processing within neuronal networks, it is of great interest to determine how criticality emerges during development. One possible mechanism is developmental, and includes axonal elongation during synaptogenesis and subsequent synaptic pruning in combination with the maturation of GABAergic inhibition (i.e., the integration then fragmentation process). Because experimental evidence for this mechanism remains inconclusive, we studied the developmental variation of neuronal avalanches in dissociated cortical neurons using high-density complementary metal-oxide semiconductor (CMOS) microelectrode arrays (MEAs). The spontaneous activities of nine cultures were monitored using CMOS MEAs from 4 to 30days in vitro (DIV) at single-cell spatial resolution. While cells were immature, cultures demonstrated random-like patterns of activity and an exponential avalanche size distribution; this distribution was followed by a bimodal distribution, and finally a power-law-like distribution. The bimodal distribution was associated with a large-scale avalanche with a homogeneous spatiotemporal pattern, while the subsequent power-law distribution was associated with diverse patterns. These results suggest that the SoC emerges through a two-step process: the integration process accompanying the characteristic large-scale avalanche and the fragmentation process associated with diverse middle-size avalanches.

State-Dependent Propagation of Neuronal Sub-Population in Spontaneous Synchronized Bursts.

Repeating stable spatiotemporal patterns emerge in synchronized spontaneous activity in neuronal networks. The repertoire of such patterns can serve as memory, or a reservoir of information, in a neuronal network; moreover, the variety of patterns may represent the network memory capacity. However, a neuronal substrate for producing a repertoire of patterns in synchronization remains elusive. We herein hypothesize that state-dependent propagation of a neuronal sub-population is the key mechanism. By combining high-resolution measurement with a 4096-channel complementary metal-oxide semiconductor (CMOS) microelectrode array (MEA) and dimensionality reduction with non-negative matrix factorization (NMF), we investigated synchronized bursts of dissociated rat cortical neurons at approximately 3 weeks in vitro. We found that bursts had a repertoire of repeating spatiotemporal patterns, and different patterns shared a partially similar sequence of sub-population, supporting the idea of sequential structure of neuronal sub-populations during synchronized activity. We additionally found that similar spatiotemporal patterns tended to appear successively and periodically, suggesting a state-dependent fluctuation of propagation, which has been overlooked in existing literature. Thus, such a state-dependent property within the sequential sub-population structure is a plausible neural substrate for performing a repertoire of stable patterns during synchronized activity.