Insights for disease modeling from single-cell transcriptomics of iPSC-derived Ngn2-induced neurons and astrocytes across differentiation time and co-culture.

BACKGROUND: Trans-differentiation of human-induced pluripotent stem cells into neurons via Ngn2-induction (hiPSC-N) has become an efficient system to quickly generate neurons a likely significant advance for disease modeling and in vitro assay development. Recent single-cell interrogation of Ngn2-induced neurons, however, has revealed some similarities to unexpected neuronal lineages. Similarly, a straightforward method to generate hiPSC-derived astrocytes (hiPSC-A) for the study of neuropsychiatric disorders has also been described. RESULTS: Here, we examine the homogeneity and similarity of hiPSC-N and hiPSC-A to their in vivo counterparts, the impact of different lengths of time post Ngn2 induction on hiPSC-N (15 or 21 days), and the impact of hiPSC-N/hiPSC-A co-culture. Leveraging the wealth of existing public single-cell RNA-seq (scRNA-seq) data in Ngn2-induced neurons and in vivo data from the developing brain, we provide perspectives on the lineage origins and maturation of hiPSC-N and hiPSC-A. While induction protocols in different labs produce consistent cell type profiles, both hiPSC-N and hiPSC-A show significant heterogeneity and similarity to multiple in vivo cell fates, and both more precisely approximate their in vivo counterparts when co-cultured. Gene expression data from the hiPSC-N show enrichment of genes linked to schizophrenia (SZ) and autism spectrum disorders (ASD) as has been previously shown for neural stem cells and neurons. These overrepresentations of disease genes are strongest in our system at early times (day 15) in Ngn2-induction/maturation of neurons, when we also observe the greatest similarity to early in vivo excitatory neurons. We have assembled this new scRNA-seq data along with the public data explored here as an integrated biologist-friendly web-resource for researchers seeking to understand this system more deeply: https://nemoanalytics.org/p?l=DasEtAlNGN2&g=NES . CONCLUSIONS: While overall we support the use of the investigated cellular models for the study of neuropsychiatric disease, we also identify important limitations. We hope that this work will contribute to understanding and optimizing cellular modeling for complex brain disorders.

Molecular signatures associated with cognitive deficits in schizophrenia: a study of biopsied olfactory neural epithelium.

Cognitive impairment is a key feature of schizophrenia (SZ) and determines functional outcome. Nonetheless, molecular signatures in neuronal tissues that associate with deficits are not well understood. We conducted nasal biopsy to obtain olfactory epithelium from patients with SZ and control subjects. The neural layers from the biopsied epithelium were enriched by laser-captured microdissection. We then performed an unbiased microarray expression study and implemented a systematic neuropsychological assessment on the same participants. The differentially regulated genes in SZ were further filtered based on correlation with neuropsychological traits. This strategy identified the SMAD 5 gene, and real-time quantitative PCR analysis also supports downregulation of the SMAD pathway in SZ. The SMAD pathway has been important in multiple tissues, including the role for neurodevelopment and bone formation. Here the involvement of the pathway in adult brain function is suggested. This exploratory study establishes a strategy to better identify neuronal molecular signatures that are potentially associated with mental illness and cognitive deficits. We propose that the SMAD pathway may be a novel target in addressing cognitive deficit of SZ in future studies.

Acetaldehyde-induced changes in monoamine and amino acid extracellular microdialysate content of the nucleus accumbens.

The effect of an acute intraperitoneal (i.p.) injection of acetaldehyde, 20 mg/kg or 100 mg/kg, on the microdialysate content of both amino acids and monoamines was studies in the nucleus accumbens (NA) by a microdialysis technique. Acetaldehyde, ACH, which was detectable at levels of 50-130 mumol/g brain tissue 10 min after injection, evoked a significant decrease in the extracellular microdialysis dopamine content, which was sustained for the period of the study, i.e. 120 min. Homovanillic acid, HVA, decreased significantly when the lower dose of ACH was administered while dihydrophenylacetic acid, DOPAC, showed no significant change with either dose of ACH during the period of the study. Serotonin levels decreased significantly after both doses of acetaldehyde, with significant increases of its major metabolite, hydroxyindolacetic acid, 5-HIAA, with the higher acetaldehyde dose. Taurine increased significantly, only during the first twenty minutes, after both doses of acetaldehyde, although neither of the excitatory amino acids assayed, glutamate and aspartate, nor the inhibitory amino acid, GABA, showed any significant changes. Acetaldehyde clearly evokes significant perturbation in the monoamine content of the NA, such changes being the converse to those reported for monoamines after ethanol administration, which might indicate a negative reinforcement effect.

Excessive sugar intake alters binding to dopamine and mu-opioid receptors in the brain.

Palatable food stimulates neural systems implicated in drug dependence; thus sugar might have effects like a drug of abuse. Rats were given 25% glucose solution with chow for 12 h followed by 12 h of food deprivation each day. They doubled their glucose intake in 10 days and developed a pattern of excessive intake in the first hour of daily access. After 30 days, receptor binding was compared to chow-fed controls. Dopamine D-1 receptor binding increased significantly in the accumbens core and shell. In contrast, D-2 binding decreased in the dorsal striatum. Binding to dopamine transporter increased in the midbrain. Opioid mu-1 receptor binding increased significantly in the cingulate cortex, hippocampus, locus coeruleus and accumbens shell. Thus, intermittent, excessive sugar intake sensitized D-1 and mu-1 receptors much like some drugs of abuse.

Unique pharmacological actions of atypical neuroleptic quetiapine: possible role in cell cycle/fate control.

Quetiapine is an atypical neuroleptic with a pharmacological profile distinct from classic neuroleptics that function primarily via blockade of dopamine D2 receptors. In the United States, quetiapine is currently approved for treating patients with schizophrenia, major depression and bipolar I disorder. Despite its widespread use, its cellular effects remain elusive. To address possible mechanisms, we chronically treated mice with quetiapine, haloperidol or vehicle and examined quetiapine-specific gene expression change in the frontal cortex. Through microarray analysis, we observed that several groups of genes were differentially expressed upon exposure to quetiapine compared with haloperidol or vehicle; among them, Cdkn1a, the gene encoding p21, exhibited the greatest fold change relative to haloperidol. The quetiapine-induced downregulation of p21/Cdkn1a was confirmed by real-time polymerase chain reaction and in situ hybridization. Consistent with single gene-level analyses, functional group analyses also indicated that gene sets associated with cell cycle/fate were differentially regulated in the quetiapine-treated group. In cortical cell cultures treated with quetiapine, p21/Cdkn1a was significantly downregulated in oligodendrocyte precursor cells and neurons, but not in astrocytes. We propose that cell cycle-associated intervention by quetiapine in the frontal cortex may underlie a unique efficacy of quetiapine compared with typical neuroleptics.

High throughput analysis of gene expression in the human brain.

The human brain is thought to have the greatest complexity of gene expression of any region of the body, reflecting the diverse functions of neurons and glia. Studies of gene expression in the human brain may yield fundamental information about the phenotype of brain cells in different stages of development, in different brain regions, and in different physiological and pathological states. As the human genome project nears completion, several technological advances allow the analysis of thousands of expressed genes in a small brain sample. This review describes available sources of human brain material, and several high throughput techniques used to measure the expression of thousands of genes. These techniques include expressed sequence tag (EST) sequencing of cDNA libraries; differential display; subtractive hybridization; serial analysis of gene expression (SAGE); and the emerging technology of high density DNA microarrays. Measurement of gene expression with microarrays and other technologies has potential applications in the study of human brain diseases, including cognitive disorders for which animal models are typically not available. Gene expression measurements may be used to identify genes that are abnormally regulated as a secondary consequence of a disease state, or to identify the response of brain cells to pharmacological treatments.

Gene expression profiling in postmortem Rett Syndrome brain: differential gene expression and patient classification.

The identification of mutations in the transcriptional repressor methyl-CpG-binding protein 2 (MECP2) gene in Rett Syndrome (RTT) suggests that an inappropriate release of transcriptional silencing may give rise to RTT neuropathology. Despite this progress, the molecular basis of RTT neuropathogenesis remains unclear. Using multiple cDNA microarray technologies, subtractive hybridization, and conventional biochemistry, we generated comprehensive gene expression profiles of postmortem brain tissue from RTT patients and matched controls. Many glial transcripts involved in known neuropathological mechanisms were found to have increased expression in RTT brain, while decreases were observed in the expression of multiple neuron-specific mRNAs. Dramatic and consistent decreases in transcripts encoding presynaptic markers indicated a specific deficit in presynaptic development. Employing multiple clustering algorithms, it was possible to accurately segregate RTT from control brain tissue samples based solely on gene expression profile. Although previously achieved in cancers, our results constitute the first report of human disease classification using gene expression profiling in a complex tissue source such as brain.