Temporal proteomic profiling of postnatal human cortical development

Differential effects of moderate chronic ethanol consumption on neurobehavior, white matter glial protein expression, and mTOR pathway signaling with adolescent brain maturation

Background: Adolescent brains are highly vulnerable to heavy alcohol exposure. Increased understanding of how alcohol adversely impacts brain maturation may improve treatment outcomes.Objectives: This study characterizes short-term versus long-term effects of ethanol feeding on behavior, frontal lobe glial proteins, and mTOR signaling.Methods: Adolescent rats (8/group) were fed liquid diets containing 26% or 0% ethanol for 2 or 9 weeks, then subjected to novel object recognition (NOR) and open field (OF) tests. Frontal lobes were used for molecular assays.Results: Significant ethanol effects on OF performance occurred in the 2-week model (p < .0001). Further shifts in OF and NOR performance were unrelated to ethanol exposure in the 9-week models (p < .05 to p < .0001). Ethanol inhibited MAG1 (p < .01) and MBP (p < .0001) after 2 but not 9 weeks. However, both control and ethanol 9-week models had significantly reduced MAG1 (p < .001-0.0001), MBP (p < .0001), PDGFRA (p < .05-0.01), and PLP (p < .001-0.0001) relative to the 2-week models. GFAP was the only glial protein significantly inhibited by ethanol in both 2- (p < .01) and 9-week (p < .05) models. Concerning the mTOR pathway, ethanol reduced IRS-1 (p < .05) and globally inhibited mTOR (p < .01 or p < .001) in the 9- but not the 2-week model.Conclusions: Short-term versus long-term ethanol exposures differentially alter neurobehavioral function, glial protein expression, and signaling through IRS-1 and mTOR, which have known roles in myelination during adolescence. These findings suggest that strategies to prevent chronic alcohol-related brain pathology should consider the increased maturation-related vulnerability of adolescent brains.

Genome-wide transcriptome profiling and development of age prediction models in the human brain

Aging-related transcriptome changes in various regions of the healthy human brain have been explored in previous works, however, a study to develop prediction models for age based on the expression levels of specific panels of transcripts is lacking. Moreover, studies that have assessed sexually dimorphic gene activities in the aging brain have reported discrepant results, suggesting that additional studies would be advantageous. The prefrontal cortex (PFC) region was previously shown to have a particularly large number of significant transcriptome alterations during healthy aging in a study that compared different regions in the human brain. We harmonized neuropathologically normal PFC transcriptome datasets obtained from the Gene Expression Omnibus (GEO) repository, ranging in age from 21 to 105 years, and found a large number of differentially regulated transcripts in the old and elderly, compared to young samples overall, and compared female and male-specific expression alterations. We assessed the genes that were associated with age by employing ontology, pathway, and network analyses. Furthermore, we applied various established (least absolute shrinkage and selection operator (Lasso) and Elastic Net (EN)) and recent (eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM)) machine learning algorithms to develop accurate prediction models for chronological age and validated them. Studies to further validate these models in other large populations and molecular studies to elucidate the potential mechanisms by which the transcripts identified may be related to aging phenotypes would be advantageous.

NeuroTri2-VISDOT: An open-access tool to harness the power of second trimester human single cell data to inform models of Mendelian neurodevelopmental disorders

Whole exome and genome sequencing, coupled with refined bioinformatic pipelines, have enabled improved diagnostic yields for individuals with Mendelian conditions and have led to the rapid identification of novel syndromes. For many Mendelian neurodevelopmental disorders (NDDs), there is a lack of pre-existing model systems for mechanistic work. Thus, it is critical for translational researchers to have an accessible phenotype- and genotype-informed approach for model system selection. Single-cell RNA sequencing data can be informative in such an approach, as it can indicate which cell types express a gene of interest at the highest levels across time. For Mendelian NDDs, such data for the developing human brain is especially useful. A valuable single-cell RNA sequencing dataset of the second trimester developing human brain was produced by Bhaduri et al in 2021, but access to these data can be limited by computing power and the learning curve of single-cell data analysis. To reduce these barriers for translational research on Mendelian NDDs, we have built the web-based tool, Neurodevelopment in Trimester 2 - VIsualization of Single cell Data Online Tool (NeuroTri2-VISDOT), for exploring this single-cell dataset, and we have employed it in several different settings to demonstrate its utility for the translational research community.

Proteome Profiling of Rat Brain Cortical Changes during Early Postnatal Brain Development

Label-free quantitation (LFQ) was applied to proteome profiling of rat brain cortical development during the early postnatal period. Male and female rat brain extracts were prepared using a convenient, detergent-free sample preparation technique at postnatal days (PND) 2, 8, 15, and 22. The PND protein ratios were calculated using Proteome Discoverer, and the PND protein change profiles were constructed separately for male and female animals for key presynaptic, postsynaptic, and adhesion brain proteins. The profiles were compared to the analogous profiles assembled from the published mouse and rat cortex proteomic data, including the fractionated-synaptosome data. The PND protein-change trendlines, Pearson correlation coefficient (PCC), and linear regression analysis of the statistically significant PND protein changes were used in the comparative analysis of the datasets. The analysis identified similarities and differences between the datasets. Importantly, there were significant similarities in the comparison of the rat cortex PND (current work) vs mouse (previously published) PND profiles, although in general, a lower abundance of synaptic proteins in mice than in rats was found. The male and female rat cortex PND profiles were expectedly almost identical (98-99% correlation by PCC), which also substantiated this LFQ nanoflow liquid chromatography-high-resolution mass spectrometry approach.

Moving CNS axon growth and regeneration research into human model systems

Axon regeneration is limited in the adult mammalian central nervous system (CNS) due to both intrinsic and extrinsic factors. Rodent studies have shown that developmental age can drive differences in intrinsic axon growth ability, such that embryonic rodent CNS neurons extend long axons while postnatal and adult CNS neurons do not. In recent decades, scientists have identified several intrinsic developmental regulators in rodents that modulate growth. However, whether this developmentally programmed decline in CNS axon growth is conserved in humans is not yet known. Until recently, there have been limited human neuronal model systems, and even fewer age-specific human models. Human in vitro models range from pluripotent stem cell-derived neurons to directly reprogrammed (transdifferentiated) neurons derived from human somatic cells. In this review, we discuss the advantages and disadvantages of each system, and how studying axon growth in human neurons can provide species-specific knowledge in the field of CNS axon regeneration with the goal of bridging basic science studies to clinical trials. Additionally, with the increased availability and quality of 'omics datasets of human cortical tissue across development and lifespan, scientists can mine these datasets for developmentally regulated pathways and genes. As there has been little research performed in human neurons to study modulators of axon growth, here we provide a summary of approaches to begin to shift the field of CNS axon growth and regeneration into human model systems to uncover novel drivers of axon growth.

Inter-Regional Proteomic Profiling of the Human Brain Using an Optimized Protein Extraction Method from Formalin-Fixed Tissue to Identify Signaling Pathways

Proteomics offers vast potential for studying the molecular regulation of the human brain. Formalin fixation is a common method for preserving human tissue; however, it presents challenges for proteomic analysis. In this study, we compared the efficiency of two different protein-extraction buffers on three post-mortem, formalin-fixed human brains. Equal amounts of extracted proteins were subjected to in-gel tryptic digestion and LC-MS/MS. Protein, peptide sequence, and peptide group identifications; protein abundance; and gene ontology pathways were analyzed. Protein extraction was superior using lysis buffer containing tris(hydroxymethyl)aminomethane hydrochloride, sodium dodecyl sulfate, sodium deoxycholate, and Triton X-100 (TrisHCl, SDS, SDC, Triton X-100), which was then used for inter-regional analysis. Pre-frontal, motor, temporal, and occipital cortex tissues were analyzed by label free quantification (LFQ) proteomics, Ingenuity Pathway Analysis and PANTHERdb. Inter-regional analysis revealed differential enrichment of proteins. We found similarly activated cellular signaling pathways in different brain regions, suggesting commonalities in the molecular regulation of neuroanatomically-linked brain functions. Overall, we developed an optimized, robust, and efficient method for protein extraction from formalin-fixed human brain tissue for in-depth LFQ proteomics. We also demonstrate herein that this method is suitable for rapid and routine analysis to uncover molecular signaling pathways in the human brain.

Altered transcriptome-proteome coupling indicates aberrant proteostasis in Parkinson's disease

Aberrant proteostasis is thought to be implicated in Parkinson's disease (PD), but patient-derived evidence is scant. We hypothesized that impaired proteostasis is reflected as altered transcriptome-proteome correlation in the PD brain. We integrated transcriptomic and proteomic data from prefrontal cortex of PD patients and young and aged controls to assess RNA-protein correlations across samples. The aged brain showed a genome-wide decrease in mRNA-protein correlation. Genes encoding synaptic vesicle proteins showed negative correlations, likely reflecting spatial separation of mRNA and protein into soma and synapses. PD showed a broader transcriptome-proteome decoupling, consistent with a proteome-wide decline in proteostasis. Genes showing negative correlation in PD were enriched for proteasome subunits, indicating accentuated spatial separation of transcript and protein in PD neurons. In addition, PD showed positive correlations for mitochondrial respiratory chain genes, suggesting a tighter regulation in the face of mitochondrial dysfunction. Our results support the hypothesis that aberrant proteasomal function is implicated in PD pathogenesis.

Dendritic Spines: Synaptogenesis and Synaptic Pruning for the Developmental Organization of Brain Circuits

Synaptic overproduction and elimination is a regular developmental event in the mammalian brain. In the cerebral cortex, synaptic overproduction is almost exclusively correlated with glutamatergic synapses located on dendritic spines. Therefore, analysis of changes in spine density on different parts of the dendritic tree in identified classes of principal neurons could provide insight into developmental reorganization of specific microcircuits.The activity-dependent stabilization and selective elimination of the initially overproduced synapses is a major mechanism for generating diversity of neural connections beyond their genetic determination. The largest number of overproduced synapses was found in the monkey and human cerebral cortex. The highest (exceeding adult values by two- to threefold) and most protracted overproduction (up to third decade of life) was described for associative layer IIIC pyramidal neurons in the human dorsolateral prefrontal cortex.Therefore, the highest proportion and extraordinarily extended phase of synaptic spine overproduction is a hallmark of neural circuitry in human higher-order associative areas. This indicates that microcircuits processing the most complex human cognitive functions have the highest level of developmental plasticity. This finding is the backbone for understanding the effect of environmental impact on the development of the most complex, human-specific cognitive and emotional capacities, and on the late onset of human-specific neuropsychiatric disorders, such as autism and schizophrenia.

Modelling the Human Blood-Brain Barrier in Huntington Disease

While blood–brain barrier (BBB) dysfunction has been described in neurological disorders, including Huntington’s disease (HD), it is not known if endothelial cells themselves are functionally compromised when promoting BBB dysfunction. Furthermore, the underlying mechanisms of BBB dysfunction remain elusive given the limitations with mouse models and post mortem tissue to identify primary deficits. We established models of BBB and undertook a transcriptome and functional analysis of human induced pluripotent stem cell (iPSC)-derived brain-like microvascular endothelial cells (iBMEC) from HD patients or unaffected controls. We demonstrated that HD-iBMECs have abnormalities in barrier properties, as well as in specific BBB functions such as receptor-mediated transcytosis.

The HSP40 chaperone Ydj1 drives amyloid beta 42 toxicity

Amyloid beta 42 (Abeta42) is the principal trigger of neurodegeneration during Alzheimer's disease (AD). However, the etiology of its noxious cellular effects remains elusive. In a combinatory genetic and proteomic approach using a yeast model to study aspects of intracellular Abeta42 toxicity, we here identify the HSP40 family member Ydj1, the yeast orthologue of human DnaJA1, as a crucial factor in Abeta42-mediated cell death. We demonstrate that Ydj1/DnaJA1 physically interacts with Abeta42 (in yeast and mouse), stabilizes Abeta42 oligomers, and mediates their translocation to mitochondria. Consequently, deletion of YDJ1 strongly reduces co-purification of Abeta42 with mitochondria and prevents Abeta42-induced mitochondria-dependent cell death. Consistently, purified DnaJ chaperone delays Abeta42 fibrillization in vitro, and heterologous expression of human DnaJA1 induces formation of Abeta42 oligomers and their deleterious translocation to mitochondria in vivo. Finally, downregulation of the Ydj1 fly homologue, Droj2, improves stress resistance, mitochondrial morphology, and memory performance in a Drosophila melanogaster AD model. These data reveal an unexpected and detrimental role for specific HSP40s in promoting hallmarks of Abeta42 toxicity.

STAT3 is a biologically relevant therapeutic target in H3K27M-mutant diffuse midline glioma

Background

H3K27M-mutant diffuse midline glioma (DMG) is a lethal brain tumor that usually occurs in children. Despite advances in our understanding of its underlying biology, efficacious therapies are severely lacking.

Methods

We screened a library of drugs either FDA-approved or in clinical trial using a library of patient-derived H3K27M-mutant DMG cell lines with cell viability as the outcome. Results were validated for clinical relevance and mechanistic importance using patient specimens from biopsy and autopsy, patient-derived cell lines, inhibition by gene knockdown and small molecule inhibitors, and patient-derived xenografts.

Results

Kinase inhibitors were highly toxic to H3K27M-mutant DMG cells. Within this class, STAT3 inhibitors demonstrated robust cytotoxic activity in vitro. Mechanistic analyses revealed one form of activated STAT3, phospho-tyrosine- 705 STAT3 (pSTAT3), was selectively upregulated in H3K27M-mutant cell lines and clinical specimens. STAT3 inhibition by CRISPR/Cas9 knockout, shRNA or small molecule inhibition reduced cell viability in vitro, and partially restored expression of the polycomb repressive mark H3K27me3, which is classically lost in H3K27M-mutant DMG. Putative STAT3-regulated genes were enriched in an H3K27M-knockout DMG cell line, indicating relative gain of STAT3 signaling in K27M-mutant cells. Treatment of patient-derived intracranial xenografts with WP1066, a STAT3 pathway inhibitor currently in clinical use for pediatric brain tumors, resulted in stasis of tumor growth, and increased overall survival. Finally, pSTAT3(Y705) was detected in circulating plasma extracellular vesicles of patients with H3K27M-mutant DMG.

Conclusions

STAT3 is a biologically relevant therapeutic target in H3K27M-mutant DMG. STAT3 inhibition should be considered in future clinical trials.

Filamin A increases aggressiveness of human neuroblastomas

Background

The actin-binding protein filamin A (FLNA) regulates oncogenic signal transduction important for tumor growth, but the role of FLNA in the progression of neuroblastoma (NB) has not been explored.

Methods

We analyzed FLNA mRNA expression in the R2 NB-database and FLNA protein expression in human NB tumors. We then silenced FLNA expression in human SKNBE2 and IMR32 NB cells by lentiviral vector encoding shRNA FLNA and assayed the cells for proliferation, migration, colony, spheroid formation, and apoptosis. SKNBE2 xenografts expressing or lacking FLNA in BALB/c nude mice were analyzed by both routine histopathology and immunohistochemistry.

Results

We observed shorter patient survival with higher expression of FLNA mRNA than patients with lower FLNA mRNA expression, and high-risk NB tumors expressed higher FLNA levels. SKNBE2 cells expressing higher FLNA levels proliferated more than IMR32 cells expressing lower FLNA levels. NB cell lines transfected with siRNA FLNA proliferated and migrated less, expressed lower levels of phosphorylated AKT and ERK1/2, formed smaller colonies and spheroids, as well as increased apoptosis. After inoculation of SKNBE2 cells infected with lentivirus expressing shRNA FLNA, size of NB tumors and number of proliferating cells were decreased. Furthermore, we identified STAT3 as an interacting partner of FLNA. Silencing FLNA mRNA reduced levels of phosphorylated STAT3 and MYCN, and induced expression NF-κB, cleaved caspase 3, and p53.

Conclusion

Inhibition of FLNA impaired NB cell signaling and function and reduced NB tumor size in vivo, suggesting that drugs targeting either FLNA or its interaction with STAT3 may be useful in the treatment of NB.

A Practical Guide to Sparse k-Means Clustering for Studying Molecular Development of the Human Brain

Studying the molecular development of the human brain presents unique challenges for selecting a data analysis approach. The rare and valuable nature of human postmortem brain tissue, especially for developmental studies, means the sample sizes are small (n), but the use of high throughput genomic and proteomic methods measure the expression levels for hundreds or thousands of variables [e.g., genes or proteins (p)] for each sample. This leads to a data structure that is high dimensional (p ≫ n) and introduces the curse of dimensionality, which poses a challenge for traditional statistical approaches. In contrast, high dimensional analyses, especially cluster analyses developed for sparse data, have worked well for analyzing genomic datasets where p ≫ n. Here we explore applying a lasso-based clustering method developed for high dimensional genomic data with small sample sizes. Using protein and gene data from the developing human visual cortex, we compared clustering methods. We identified an application of sparse k-means clustering [robust sparse k-means clustering (RSKC)] that partitioned samples into age-related clusters that reflect lifespan stages from birth to aging. RSKC adaptively selects a subset of the genes or proteins contributing to partitioning samples into age-related clusters that progress across the lifespan. This approach addresses a problem in current studies that could not identify multiple postnatal clusters. Moreover, clusters encompassed a range of ages like a series of overlapping waves illustrating that chronological- and brain-age have a complex relationship. In addition, a recently developed workflow to create plasticity phenotypes (Balsor et al., 2020) was applied to the clusters and revealed neurobiologically relevant features that identified how the human visual cortex changes across the lifespan. These methods can help address the growing demand for multimodal integration, from molecular machinery to brain imaging signals, to understand the human brain’s development.

MicroRNAs in the Onset of Schizophrenia

Mounting evidence implicates microRNAs (miRNAs) in the pathology of schizophrenia. These small noncoding RNAs bind to mRNAs containing complementary sequences and promote their degradation and/or inhibit protein synthesis. A single miRNA may have hundreds of targets, and miRNA targets are overrepresented among schizophrenia-risk genes. Although schizophrenia is a neurodevelopmental disorder, symptoms usually do not appear until adolescence, and most patients do not receive a schizophrenia diagnosis until late adolescence or early adulthood. However, few studies have examined miRNAs during this critical period. First, we examine evidence that the miRNA pathway is dynamic throughout adolescence and adulthood and that miRNAs regulate processes critical to late neurodevelopment that are aberrant in patients with schizophrenia. Next, we examine evidence implicating miRNAs in the conversion to psychosis, including a schizophrenia-associated single nucleotide polymorphism in MIR137HG that is among the strongest known predictors of age of onset in patients with schizophrenia. Finally, we examine how hemizygosity for DGCR8, which encodes an obligate component of the complex that synthesizes miRNA precursors, may contribute to the onset of psychosis in patients with 22q11.2 microdeletions and how animal models of this disorder can help us understand the many roles of miRNAs in the onset of schizophrenia.

Bioinformatic Analysis of Temporal and Spatial Proteome Alternations During Infections

Microbial pathogens have evolved numerous mechanisms to hijack host's systems, thus causing disease. This is mediated by alterations in the combined host-pathogen proteome in time and space. Mass spectrometry-based proteomics approaches have been developed and tailored to map disease progression. The result is complex multidimensional data that pose numerous analytic challenges for downstream interpretation. However, a systematic review of approaches for the downstream analysis of such data has been lacking in the field. In this review, we detail the steps of a typical temporal and spatial analysis, including data pre-processing steps (i.e., quality control, data normalization, the imputation of missing values, and dimensionality reduction), different statistical and machine learning approaches, validation, interpretation, and the extraction of biological information from mass spectrometry data. We also discuss current best practices for these steps based on a collection of independent studies to guide users in selecting the most suitable strategies for their dataset and analysis objectives. Moreover, we also compiled the list of commonly used R software packages for each step of the analysis. These could be easily integrated into one's analysis pipeline. Furthermore, we guide readers through various analysis steps by applying these workflows to mock and host-pathogen interaction data from public datasets. The workflows presented in this review will serve as an introduction for data analysis novices, while also helping established users update their data analysis pipelines. We conclude the review by discussing future directions and developments in temporal and spatial proteomics and data analysis approaches. Data analysis codes, prepared for this review are available from https://github.com/BabuLab-UofR/TempSpac, where guidelines and sample datasets are also offered for testing purposes.

Age-dependent and region-specific alteration of parvalbumin neurons, perineuronal nets and microglia in the mouse prefrontal cortex and hippocampus following obesogenic diet consumption

Emergent evidence demonstrates that excessive consumption of high fat and high sugar (HFHS) diets has negative consequences on hippocampal and prefrontal cortex (PFC) function. Moreover, the delayed maturation of the PFC including the late development of parvalbumin-expressing (PV) interneurons and perineuronal nets (PNNs) may promote vulnerability to HFHS diet-induced nutritional stress. However, the young brain may have some resistance to diet-induced neuroinflammation. Thus, we examined the impact of a HFHS diet commencing either in adolescence or adulthood in male mice. PV interneurons, PNNs and microglia were assessed using immunohistochemistry. We observed greater numbers of PV neurons and PNNs in the hippocampus and the prelimbic and infralimbic PFC in adult mice in comparison to our younger cohort. Mice that consumed HFHS diet as adults had reduced numbers of hippocampal PV neurons and PNNs, which correlated with adiposity. However, we saw no effects of diet on PV and PNNs in the PFC. HFHS diet increased microgliosis in the adult cohort, and morphological changes to microglia were observed in the PFC and hippocampus of the adolescent cohort, with a shift to activated microglia phenotypes. Taken together, these findings demonstrate different regional and age-specific effects of obesogenic diets on PV neurons, PNNs and microglia.

Genetic origins of suicidality? A synopsis of genes in suicidal behaviours, with regard to evidence diversity, disorder specificity and neurodevelopmental brain transcriptomics

With regard to suicidal behavior (SB) genetics, many novel genes have been implicated over the years, in particular by a variety of hypothesis-free genomic methods (e.g. GWAS and exome sequencing). In addition, many novel SB gene findings appear enigmatic in their biological relevance and have weak statistical support, e.g. lack direct replications. Adding to this is the comorbidity between psychiatric disorders and SB. Here we provide a synopsis of SB genes, by prioritization of 106 (out of ~2500) genes based on their highest level of evidence diversity across mainly five genetic evidence types (candidate/GWAS SNP, CNV, linkage and whole exome sequencing), supplemented by three functional categories. This is a representative set of both old and new SB gene candidates, implicated by all kinds of evidence. Furthermore, we define a subset of 40 SB "specific" genes, which are not found among ~3900 genes implicated in other neuropsychiatric disorders, e.g. Autism spectrum disorders (ASD) or Schizophrenia. Biological research of suicidality contains a major developmental focus, e.g. with regard to the gene-environment interactions and epigenetic effects during childhood. Less is known about early (fetal) development and SB genes. Inspired by huge efforts to understand the role early (fetal) neurodevelopment in e.g. ASD by using brain transcriptomic data, we here also characterize the 106 SB genes. We find interesting spatiotemporal expression differences and similarities between SB specific and non-specific genes during brain neurodevelopment. These aspects are of interest to investigate further, to better understand and counteract the genetic origins suicidality.

The Protracted Maturation of Associative Layer IIIC Pyramidal Neurons in the Human Prefrontal Cortex During Childhood: A Major Role in Cognitive Development and Selective Alteration in Autism

The human specific cognitive shift starts around the age of 2 years with the onset of self-awareness, and continues with extraordinary increase in cognitive capacities during early childhood. Diffuse changes in functional connectivity in children aged 2-6 years indicate an increase in the capacity of cortical network. Interestingly, structural network complexity does not increase during this time and, thus, it is likely to be induced by selective maturation of a specific neuronal subclass. Here, we provide an overview of a subclass of cortico-cortical neurons, the associative layer IIIC pyramids of the human prefrontal cortex. Their local axonal collaterals are in control of the prefrontal cortico-cortical output, while their long projections modulate inter-areal processing. In this way, layer IIIC pyramids are the major integrative element of cortical processing, and changes in their connectivity patterns will affect global cortical functioning. Layer IIIC neurons have a unique pattern of dendritic maturation. In contrast to other classes of principal neurons, they undergo an additional phase of extensive dendritic growth during early childhood, and show characteristic molecular changes. Taken together, circuits associated with layer IIIC neurons have the most protracted period of developmental plasticity. This unique feature is advanced but also provides a window of opportunity for pathological events to disrupt normal formation of cognitive circuits involving layer IIIC neurons. In this manuscript, we discuss how disrupted dendritic and axonal maturation of layer IIIC neurons may lead into global cortical disconnectivity, affecting development of complex communication and social abilities. We also propose a model that developmentally dictated incorporation of layer IIIC neurons into maturing cortico-cortical circuits between 2 to 6 years will reveal a previous (perinatal) lesion affecting other classes of principal neurons. This "disclosure" of pre-existing functionally silent lesions of other neuronal classes induced by development of layer IIIC associative neurons, or their direct alteration, could be found in different forms of autism spectrum disorders. Understanding the gene-environment interaction in shaping cognitive microcircuitries may be fundamental for developing rehabilitation and prevention strategies in autism spectrum and other cognitive disorders.