Autism spectrum disorders: developmental disconnection syndromes

BDNF and GSK-3beta expression changes underlie the beneficial effects of crocin on behavioral alterations in a rat model of autism induced by prenatal valproic acid administration

Autism spectrum disorder (ASD) is a serious neurodevelopmental disorder characterized by impairments in social interaction, language, and communication and induction of stereotypic behavior. In rodents, prenatal administration of valproic acid (often on 12.5 gestational days) is used for the induction of an ASD-like model. In the present study, we aimed to assess the potential therapeutic effects of crocin (a major component of Saffron, a neuroprotective and anti-inflammatory agent) on behavioral dysfunctions with respect to the level of brain-derived neurotrophic factor (BDNF) and glycogen synthase kinase-3 beta (GSK-3beta) in the medial prefrontal cortex. Valproic acid was intraperitoneally injected at the dose of 600 mg/kg on 12.5 gestational days. BDNF and GSK-3beta expression levels were also measured using real-time PCR. Locomotion, anxiety-like behavior, grooming, and sniffing were also measured in the open-field test. The results showed that prenatal valproic acid administration induced hyperactivity, anxiety-like behavior, increased grooming and sniffing (stereotyped behavior), decreased BDNF levels, and increased GSK-3beta levels in the medial prefrontal cortex. However, crocin dose-dependently restored the effects of prenatal valproic acid administration on behavioral functions and gene expressions. In conclusion, we suggested that BDNF and GSK-3beta expression changes in the medial prefrontal cortex may underlie the pathophysiology of ASD. The therapeutic effects of crocin may be also related to counteracting BDNF and GSK-3beta expression changes induced by prenatal valproic acid.

A computational cognitive neuroscience approach for characterizing individual differences in autism: Introduction to Special Issue

Traditional psychological research has often treated inter-subject variability as statistical noise (even, nuisance variance), focusing instead on averages rather than individual differences. This approach has limited our understanding of the substantial heterogeneity observed in neuropsychiatric disorders, particularly autism spectrum disorder (ASD). In this introduction to a special issue on this theme, we discuss recent advances in cognitive computational neuroscience that can lead to a more systematic notion of core symptom dimensions that differentiate between ASD subtypes. These advances include large participant databases and data-sharing initiatives to increase sample sizes of autistic individuals across a wider range of cultural and socioeconomic backgrounds. Our perspective helps to build bridges between autism symptomatology and individual differences in autistic traits in the non-autistic population and introduces finer-grained dynamic methods to capture behavioral dynamics at the individual level. We specifically focus on how cognitive computational models have emerged as powerful tools to better characterize autistic traits in the general population and autistic population, particularly with respect to social decision-making. We finally outline how we can combine and harness these recent advances, on the one hand, big data initiatives, and on the other hand, cognitive computational models, to achieve a more systematic and nuanced understanding of autism that can lead to improved diagnostic accuracy and personalized interventions.

Relationships and representations of brain structures, connectivity, dynamics and functions

The review explores the complex interplay between brain structures and their associated functions, presenting a diversity of hierarchical models that enhances our understanding of these relationships. Central to this approach are structure-function flow diagrams, which offer a visual representation of how specific neuroanatomical structures are linked to their functional roles. These diagrams are instrumental in mapping the intricate connections between different brain regions, providing a clearer understanding of how functions emerge from the underlying neural architecture. The study details innovative attempts to develop new functional hierarchies that integrate structural and functional data. These efforts leverage recent advancements in neuroimaging techniques such as fMRI, EEG, MEG, and PET, as well as computational models that simulate neural dynamics. By combining these approaches, the study seeks to create a more refined and dynamic hierarchy that can accommodate the brain's complexity, including its capacity for plasticity and adaptation. A significant focus is placed on the overlap of structures and functions within the brain. The manuscript acknowledges that many brain regions are multifunctional, contributing to different cognitive and behavioral processes depending on the context. This overlap highlights the need for a flexible, non-linear hierarchy that can capture the brain's intricate functional landscape. Moreover, the study examines the interdependence of these functions, emphasizing how the loss or impairment of one function can impact others. Another crucial aspect discussed is the brain's ability to compensate for functional deficits following neurological diseases or injuries. The investigation explores how the brain reorganizes itself, often through the recruitment of alternative neural pathways or the enhancement of existing ones, to maintain functionality despite structural damage. This compensatory mechanism underscores the brain's remarkable plasticity, demonstrating its ability to adapt and reconfigure itself in response to injury, thereby ensuring the continuation of essential functions. In conclusion, the study presents a system of brain functions that integrates structural, functional, and dynamic perspectives. It offers a robust framework for understanding how the brain's complex network of structures supports a wide range of cognitive and behavioral functions, with significant implications for both basic neuroscience and clinical applications.

Impaired emotion recognition in Cntnap2-deficient mice is associated with hyper-synchronous prefrontal cortex neuronal activity

Individuals diagnosed with autism spectrum disorder (ASD) show difficulty in recognizing emotions in others, a process termed emotion recognition. While human fMRI studies linked multiple brain areas to emotion recognition, the specific mechanisms underlying impaired emotion recognition in ASD are not clear. Here, we employed an emotional state preference (ESP) task to show that Cntnap2-knockout (KO) mice, an established ASD model, do not distinguish between conspecifics according to their emotional state. We assessed brain-wide local-field potential (LFP) signals during various social behavior tasks and found that Cntnap2-KO mice exhibited higher LFP theta and gamma rhythmicity than did C57BL/6J mice, even at rest. Specifically, Cntnap2-KO mice showed increased theta coherence, especially between the prelimbic cortex (PrL) and the hypothalamic paraventricular nucleus, during social behavior. Moreover, we observed significantly increased Granger causality of theta rhythmicity between these two brain areas, across several types of social behavior tasks. Finally, optogenetic stimulation of PrL pyramidal neurons in C57BL/6J mice impaired their social discrimination abilities, including in ESP. Together, these results suggest that increased rhythmicity of PrL pyramidal neuronal activity and its hyper-synchronization with specific brain regions are involved in the impaired emotion recognition exhibited by Cntnap2-KO mice.

Insights on the Shared Genetic Landscape of Neurodevelopmental and Movement Disorders

PURPOSE OF REVIEW

Large-scale studies using hypothesis-free exome sequencing have revealed the strong heritability of neurodevelopmental disorders (NDDs) and their molecular overlap with later-onset, progressive, movement disorders phenotypes. In this review, we focus on the shared genetic landscape of NDDs and movement disorders.

RECENT FINDINGS

Cumulative research has shown that up to 30% of cases labelled as "cerebral palsy" have a monogenic etiology. Causal pathogenic variants are particularly enriched in genes previously associated with adult-onset progressive movement disorders, such as spastic paraplegias, dystonias, and cerebellar ataxias. Biological pathways that have emerged as common culprits are transcriptional regulation, neuritogenesis, and synaptic function. Defects in the same genes can cause neurological dysfunction both during early development and later in life. We highlight the implications of the increasing number of NDD gene etiologies for genetic testing in movement disorders. Finally, we discuss gaps and opportunities in the translation of this knowledge to the bedside.

Synaptic-dependent developmental dysconnectivity in 22q11.2 deletion syndrome

Chromosome 22q11.2 deletion increases the risk of neuropsychiatric disorders like autism and schizophrenia. Disruption of large-scale functional connectivity in 22q11 deletion syndrome (22q11DS) has been widely reported, but the biological factors driving these changes remain unclear. We used a cross-species design to uncover the developmental trajectory and neural underpinnings of brain dysconnectivity in 22q11DS. In LgDel mice, a model for 22q11DS, we found age-specific patterns of brain dysconnectivity, with widespread fMRI hyperconnectivity in juvenile mice reconfiguring to hippocampal hypoconnectivity over puberty. These changes correlated with developmental alterations in dendritic spine density, and both were transiently normalized by GSK3β inhibition, suggesting a synaptic origin for this phenomenon. Notably, analogous pubertal hyperconnectivity-to-hypoconnectivity reconfiguration occurs in human 22q11DS, affecting cortical regions enriched for GSK3β-associated synaptic genes and autism-relevant transcripts. This dysconnectivity also predicts age-dependent social alterations in 22q11DS individuals. These results suggest that synaptic mechanisms underlie developmental brain dysconnectivity in 22q11DS.

Valproic acid levels in neurodevelopmental disorders: correlation with CYP and SULT genes using LC-MS/MS

BACKGROUND

Valproic acid (VPA) is one of the most widely prescribed antiepileptic drugs worldwide, which is used to treat migraines, bipolar disorder, and anxiety. However, VPA is associated with a wide range of side effects. This study evaluates therapeutic drug monitoring (TDM) in individuals with neurodevelopmental disorders. It explores the correlation between valproic acid (VPA) plasma levels and genetic polymorphisms in cytochrome P450 (CYP) enzymes and cytosolic sulfotransferase (SULT) genes.

METHODS

A simple and accurate LC-MS/MS method was developed, validated, and applied in the TDM of 14 individuals on VPA therapy. Plasma VPA levels were measured, and genotyped genes SULT1A1, CYP2D64, CYP2D610, CYP3A5, and CYP2C19*2. Statistical analyses were conducted using SPSS.

RESULTS

Of the fourteen participants, two had toxic plasma VPA levels (≥ 100 µg/mL), one had a sub-therapeutic level (< 50 µg/mL), and eleven were within or slightly above the therapeutic range (50-100 µg/mL). No significant correlation was observed between VPA plasma concentrations and genotypes of SULT1A1 (p = 0.522), CYP2C192 (p = 0.288), CYP2D64 (p = 0.895), or CYP2D6*10 (p = 0.067). While no direct associations were found, genotype-guided drug therapy remains a promising strategy for optimizing drug efficacy and minimizing toxicity.

CONCLUSIONS

This study highlights the complexity of valproic acid (VPA) therapy in individuals with neurodevelopmental disorders and the limited influence of common genetic polymorphisms in CYP and SULT genes on VPA plasma levels. While therapeutic drug monitoring (TDM) remains an invaluable tool for optimizing VPA therapy, the lack of significant correlations between genetic variants and VPA concentrations suggests that routine pharmacogenetic testing for these specific variants may not be warranted in clinical practice. However, the observed toxic and sub-therapeutic VPA levels emphasize the importance of regular TDM to mitigate risks associated with overdose or insufficient dosing.

Canalization of circuit assembly by δ-protocadherins in the zebrafish optic tectum

Neurons are precisely and reproducibly assembled into complex networks during development. How genes collaborate to guide this assembly remains an enduring mystery. In humans, large numbers of genes have been implicated in neurodevelopmental disorders that are characterized by variable and overlapping phenotypes. The complexity of the brain, the large number of genes involved and the heterogeneity of the disorders makes understanding the relationships between genes, development and neural function challenging. Waddington suggested the concept of canalization to describe the role of genes in shaping developmental trajectories that lead to precise outcomes1. Here, we show that members of the δ-protocadherin family of homophilic adhesion molecules, Protocadherin-19 and Protocadherin-17, contribute to developmental canalization of visual circuit assembly in the zebrafish. We provided oriented visual stimuli to zebrafish larvae and performed in vivo 2-photon calcium imaging in the optic tectum. The latent dynamics resulting from the population activity were confined to a conserved manifold. Among different wild type larvae, these dynamics were remarkably similar, allowing quantitative comparisons within and among genotypes. In both Protocadherin-19 and Protocadherin-17 mutants, the latent dynamics diverged from wild type. Importantly, these deviations could be averaged away, suggesting that the loss of these adhesion molecules leads to stochastic phenotypic variability and introduced disruptions of circuit organization that varied among individual mutants. These results provide a specific, quantitative example of canalization in the development of a vertebrate neural circuit, and suggest a framework for understanding the observed variability in complex brain disorders.

The striatal matrix compartment is expanded in autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is the second-most common neurodevelopmental disorder in childhood. This complex developmental disorder manifests with restricted interests, repetitive behaviors, and difficulties in communication and social awareness. The inherited and acquired causes of ASD impact many and diverse brain regions, challenging efforts to identify a shared neuroanatomical substrate for this range of symptoms. The striatum and its connections are among the most implicated sites of abnormal structure and/or function in ASD. Striatal projection neurons develop in segregated tissue compartments, the matrix and striosome, that are histochemically, pharmacologically, and functionally distinct. Immunohistochemical assessment of ASD and animal models of autism described abnormal matrix:striosome volume ratios, with an possible shift from striosome to matrix volume. Shifting the matrix:striosome ratio could result from expansion in matrix, reduction in striosome, spatial redistribution of the compartments, or a combination of these changes. Each type of ratio-shifting abnormality may predispose to ASD but yield different combinations of ASD features.

METHODS

We developed a cohort of 426 children and adults (213 matched ASD-control pairs) and performed connectivity-based parcellation (diffusion tractography) of the striatum. This identified voxels with matrix-like and striosome-like patterns of structural connectivity.

RESULTS

Matrix-like volume was increased in ASD, with no evident change in the volume or organization of the striosome-like compartment. The inter-compartment volume difference (matrix minus striosome) within each individual was 31% larger in ASD. Matrix-like volume was increased in both caudate and putamen, and in somatotopic zones throughout the rostral-caudal extent of the striatum. Subjects with moderate elevations in ADOS (Autism Diagnostic Observation Schedule) scores had increased matrix-like volume, but those with highly elevated ADOS scores had 3.7-fold larger increases in matrix-like volume.

CONCLUSIONS

Matrix and striosome are embedded in distinct structural and functional networks, suggesting that compartment-selective injury or maldevelopment may mediate specific and distinct clinical features. Previously, assessing the striatal compartments in humans required post mortem tissue. Striatal parcellation provides a means to assess neuropsychiatric diseases for compartment-specific abnormalities. While this ASD cohort had increased matrix-like volume, other mechanisms that shift the matrix:striosome ratio may also increase the chance of developing the diverse social, sensory, and motor phenotypes of ASD.

Differential links in 16p11.2 deletion carriers reveal aberrant connections between large-scale networks

Qualitatively different topographical patterns of connections are thought to underlie individual differences in thought and behavior, particularly at heteromodal association areas. As such, we hypothesized that connections unique to 16p11.2 deletion carriers compared to controls, rather than hyper- or hypo-connectivity, would serve as a better model to explain the cognitive and behavioral changes observed in individuals carrying this autism-risk copy number variation. Using a spatially-unbiased, data-driven approach we found that differential links clustered non-uniformly across the cortex-particularly at the superior temporal gyrus and sulcus, posterior insula, cingulate sulcus, and inferior parietal lobule bilaterally. At these hotspots, altered local connectivity that spanned across the borders of cortical large-scale networks coincided with aberrant distant interconnectivity between large-scale networks. This was most evident between the auditory and the dorsomedial default (DNb) networks-such that greater between-network interconnectivity was associated with greater communication and social impairment. Entangled connectivity between large-scale networks may preclude each network from having the necessary fidelity to operate properly, particularly when the 2 networks have opposing organization principles-namely, local specialization (segregation) versus global coherency (integration).

Gangliosides and Cholesterol: Dual Regulators of Neuronal Membrane Framework in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation. Diagnosing ASD is complex, and the criteria for diagnosis, as well as the term ASD, have changed during the last decades. Diagnosis is made based on observation and accomplishment of specific diagnostic criteria, while a particular biomarker of ASD does not yet exist. However, studies universally report a disequilibrium in membrane lipid content, pointing to a unique neurolipid signature of ASD. This review sheds light on the possible role of cholesterol and gangliosides, complex membrane glycosphingolipids, in the development of ASD. In addition to maintaining membrane integrity, neuronal signaling, and synaptic plasticity, these lipids play a role in neurotransmitter release and calcium signaling. Evidence linking ASD to lipidome changes includes low cholesterol levels, unusual ganglioside levels, and unique metabolic profiles. ASD symptoms may be mitigated with therapeutic interventions targeting the lipid composition of membranes. However, restoring membrane equilibrium in the central nervous system remains a challenge. This review underscores the need for comprehensive research into lipid metabolism to uncover practical insights into ASD etiology and treatment as lipidomics emerges as a major area in ASD research.

Robust Autism Spectrum Disorder-Related Spatial Covariance Gray Matter Pattern Revealed With a Large-Scale Multi-Center Dataset

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder and its underlying neuroanatomical mechanisms still remain unclear. The scaled subprofile model of principal component analysis (SSM-PCA) is a data-driven multivariate technique for capturing stable disease-related spatial covariance pattern. Here, SSM-PCA is innovatively applied to obtain robust ASD-related gray matter volume pattern associated with clinical symptoms. We utilized T1-weighted structural MRI images (sMRI) of 576 subjects (288 ASDs and 288 typically developing (TD) controls) aged 7-29 years from the Autism Brain Imaging Data Exchange II (ABIDE II) dataset. These images were analyzed with SSM-PCA to identify the ASD-related spatial covariance pattern. Subsequently, we investigated the relationship between the pattern and clinical symptoms and verified its robustness. Then, the applicability of the pattern under different age stages were further explored. The results revealed that the ASD-related pattern primarily involves the thalamus, putamen, parahippocampus, orbitofrontal cortex, and cerebellum. The expression of this pattern correlated with Social Response Scale and Social Communication Questionnaire scores. Moreover, the ASD-related pattern was robust for the ABIDE I dataset. Regarding the applicability of the pattern for different age stages, the effect sizes of its expression in ASD were medium in the children and adults, while small in adolescents. This study identified a robust ASD-related pattern based on gray matter volume that is associated with social deficits. Our findings provide new insights into the neuroanatomical mechanisms of ASD and may facilitate its future intervention.

Genetic machinery which accompanies metaplasticity operates differentially in experimental model of autism

The present study investigated metaplasticity-related mRNA expressions in valproic acid (VPA)-rats, focusing on the PI3K/AKT pathway. Wistar dams were treated with a single intraperitoneal injection of 600 mg/kg VPA or saline on embryonic day E12.5 or an equal volume of saline solution. Three behavioral tests were conducted on these males' offspring: grid-walking test, negative geotaxis test, and three-chamber social interaction test. Metaplasticity was induced in 60-day-old male progeny by giving high-frequency stimulation for 5 minutes following low-frequency stimulation to the perforant pathway. For the baseline stimulation protocol (n = 6), stimulation was delivered to the dentate gyrus at the previously determined stimulation intensity (0.33 Hz 0.175 msec 30 s) for 75 min. The percent change of slope of field excitatory postsynaptic potential (fEPSP) and amplitude of population spike were calculated 55-60 min after induction protocol. The mRNA levels of PI3K, PTEN, AKT, GSK-3β, and MAPT were measured in the hippocampus by using quantitative rt-PCR. We found that offspring of VPA-treated rats showed significantly impaired sensorimotor coordination, decreased sociability, impaired preference for social novelty, and reduced input-output curve of fEPSP slope, compared to control animals. Despite a similar metaplastic response, mRNA levels of genes of interest were similar but considerably down-regulated after induction in offspring of VPA-treated dams. Our study provides evidence that the induced expression of autism-related genes has evolved to enable an adaptation mechanism during metaplastic control of long-term potentiation.

The pediatric psychopharmacology of autism spectrum disorder: A systematic review - Part II: The future

Part I of this systematic review summarized the state-of-the-art of pediatric psychopharmacology for Autism Spectrum Disorder (ASD), a severe and lifelong neurodevelopmental disorder. The purpose of this Part II follow-up article is to provide a systematic overview of the experimental psychopharmacology of ASD. To this aim, we have first identified in the Clinicaltrials.gov website all the 157 pharmacological and nutraceutical compounds which have been experimentally tested in children and adolescents with ASD using the randomized placebo-controlled trial (RCT) design. After excluding 24 drugs already presented in Part I, a systematic review spanning each of the remaining 133 compounds was registered on Prospero (ID: CRD42023476555), performed on PubMed (August 8, 2024), and completed with EBSCO, PsycINFO (psychology and psychiatry literature) and the Cochrane Database of Systematic reviews, yielding a total of 115 published RCTs, including 57 trials for 23 pharmacological compounds and 48 trials for 17 nutraceuticals/supplements. Melatonin and oxytocin were not included, because recent systematic reviews have been already published for both these compounds. RCTs of drugs with the strongest foundation in preclinical research, namely arbaclofen, balovaptan and bumetanide have all failed to reach their primary end-points, although efforts to target specific patient subgroups do warrant further investigation. For the vast majority of compounds, including cannabidiol, vasopressin, and probiotics, insufficient evidence of efficacy and safety is available. However, a small subset of compounds, including N-acetylcysteine, folinic acid, l-carnitine, coenzyme Q10, sulforaphane, and metformin may already be considered, with due caution, for clinical use, because there is promising evidence of efficacy and a high safety profile. For several other compounds, such as secretin, efficacy can be confidently excluded, and/or the data discourage undertaking new RCTs. Part I and Part II summarize "drug-based" information, which will be ultimately merged to provide clinicians with a "symptom-based" consensus statement in a conclusive Part III, with the overarching aim to foster evidence-based clinical practices and to organize new strategies for future clinical trials.

Molecular architecture of the altered cortical complexity in autism

Autism spectrum disorder (ASD) is characterized by difficulties in social interaction, communication challenges, and repetitive behaviors. Despite extensive research, the molecular mechanisms underlying these neurodevelopmental abnormalities remain elusive. We integrated microscale brain gene expression data with macroscale MRI data from 1829 participants, including individuals with ASD and typically developing controls, from the autism brain imaging data exchange I and II. Using fractal dimension as an index for quantifying cortical complexity, we identified significant regional alterations in ASD, within the left temporoparietal, left peripheral visual, right central visual, left somatomotor (including the insula), and left ventral attention networks. Partial least squares regression analysis revealed gene sets associated with these cortical complexity changes, enriched for biological functions related to synaptic transmission, synaptic plasticity, mitochondrial dysfunction, and chromatin organization. Cell-specific analyses, protein-protein interaction network analysis and gene temporal expression profiling further elucidated the dynamic molecular landscape associated with these alterations. These findings indicate that ASD-related alterations in cortical complexity are closely linked to specific genetic pathways. The combined analysis of neuroimaging and transcriptomic data enhances our understanding of how genetic factors contribute to brain structural changes in ASD.

Subregion-specific thalamocortical functional connectivity, executive function, and social behavior in children with autism spectrum disorders

The thalamus has extensive cortical connections and is an integrative hub for cognitive functions governing social behavior. This study examined (1) associations between thalamocortical resting-state functional connectivity (RSFC) and social behavior in children and (2) how various executive function (EF) subdomains mediate the association between thalamocortical RSFC and social behavior. Children from the autism brain imaging data exchange (ABIDE) initiative with neuroimaging, behavioral, and demographic data were included in our study (age < 14, ASD; n = 207, typically developing; n = 259). Thalamocortical RSFC was examined for associations with social communication and interaction (SCI) scores (SRS; social responsiveness scale) using Spearman's rank-order correlation, first in ASD children and then in typically developing children. This was followed by a more granular analysis at the thalamic subregion level. We then examined the mediating roles of eight EF subdomains in ASD children (n = 139). Right thalamus-default mode network (DMN) RSFC was significantly associated with SCI scores in ASD children (ρ = 0.23, pFDR = 0.012), primarily driven by the medial (ρ = 0.22, pFDR = 0.013), ventral (ρ = 0.17, pFDR = 0.036), and intralaminar (ρ = 0.17, pFDR = 0.036) thalamic subregions. Cognitive flexibility (ACME = 0.13, punc = 0.016) and emotional control (ACME = 0.08, punc = 0.020) significantly mediated the association between right thalamus-DMN RSFC and SCI scores. This study provided novel insights into the association between thalamocortical RSFC and social behavior in ASD children at the thalamic subregion level, providing higher levels of precision in brain-behavior mapping. Cognitive flexibility and emotion regulation were highlighted as potential targets to ameliorate the downstream effects of altered thalamocortical connectivity to improve social outcomes in ASD children.

The Medial Prefrontal Cortex-Basolateral Amygdala Circuit Mediates Anxiety in Shank3 InsG3680 Knock-in Mice

Anxiety disorder is a major symptom of autism spectrum disorder (ASD) with a comorbidity rate of ~40%. However, the neural mechanisms of the emergence of anxiety in ASD remain unclear. In our study, we found that hyperactivity of basolateral amygdala (BLA) pyramidal neurons (PNs) in Shank3 InsG3680 knock-in (InsG3680+/+) mice is involved in the development of anxiety. Electrophysiological results also showed increased excitatory input and decreased inhibitory input in BLA PNs. Chemogenetic inhibition of the excitability of PNs in the BLA rescued the anxiety phenotype of InsG3680+/+ mice. Further study found that the diminished control of the BLA by medial prefrontal cortex (mPFC) and optogenetic activation of the mPFC-BLA pathway also had a rescue effect, which increased the feedforward inhibition of the BLA. Taken together, our results suggest that hyperactivity of the BLA and alteration of the mPFC-BLA circuitry are involved in anxiety in InsG3680+/+ mice.

Patterns of Brain Maturation in Autism and Their Molecular Associations

Importance

In the neurotypical brain, regions develop in coordinated patterns, providing a fundamental scaffold for brain function and behavior. Whether altered patterns contribute to clinical profiles in neurodevelopmental conditions, including autism, remains unclear.

Objectives

To examine if, in autism, brain regions develop differently in relation to each other and how these differences are associated with molecular/genomic mechanisms and symptomatology.

Design, Setting, and Participants

This study was an analysis of one the largest deep-phenotyped, case-control, longitudinal (2 assessments separated by approximately 12-24 months) structural magnetic resonance imaging and cognitive-behavioral autism datasets (EU-AIMS Longitudinal European Autism Project [LEAP]; study dates, February 2014-November 2017) and an out-of-sample validation in the Brain Development Imaging Study (BrainMapASD) independent cohort. Analyses were performed during the 2022 to 2023 period. This multicenter study included autistic and neurotypical children, adolescents, and adults. Autistic participants were included if they had an existing autism diagnosis (DSM-IV/International Statistical Classification of Diseases and Related Health Problems, Tenth Revision or DSM-5 criteria). Autistic participants with co-occurring psychiatric conditions (except psychosis/bipolar disorder) and those taking regular medications were included.

Exposures

Neuroanatomy of neurotypical and autistic participants.

Main Outcomes and Measures

Intraindividual changes in surface area and cortical thickness over time, analyzed via surface-based morphometrics.

Results

A total of 386 individuals in the LEAP cohort (6-31 years at first visit; 214 autistic individuals, mean [SD] age, 17.3 [5.4] years; 154 male [72.0%] and 172 neurotypical individuals, mean [SD] age, 16.35 [5.7] years; 108 male [62.8%]) and 146 individuals in the BrainMapASD cohort (11-18 years at first visit; 49 autistic individuals, mean [SD] age, 14.31 [2.4] years; 42 male [85.7%] and 97 neurotypical individuals, mean [SD] age, 14.10 [2.5] years; 58 male [59.8%]). Maturational between-group differences in cortical thickness and surface area were established that were mostly driven by sensorimotor regions (eg, across features, absolute loadings for early visual cortex ranged from 0.07 to 0.11, whereas absolute loadings for dorsolateral prefrontal cortex ranged from 0.005 to 0.06). Neurodevelopmental differences were transcriptomically enriched for genes expressed in several cell types and during various neurodevelopmental stages, and autism candidate genes (eg, downregulated genes in autism, including those regulating synaptic transmission; enrichment odds ratio =3.7; P =2.6 × -10). A more neurotypical, less autismlike maturational profile was associated with fewer social difficulties and more typical sensory processing (false discovery rate P <.05; Pearson r ≥0.17). Results were replicated in the independently collected BrainMapASD cohort.

Conclusions and Relevance

Results of this case-control study suggest that the coordinated development of brain regions was altered in autism, involved a complex interplay of temporally sensitive molecular mechanisms, and may be associated with both lower-order (eg, sensory) and higher-order (eg, social) clinical features of autism. Thus, examining maturational patterns may provide an analytic framework to study the neurobiological origins of clinical profiles in neurodevelopmental/mental health conditions.

Resting-State Functional Connectivity of the Amygdala in Autism: A Preregistered Large-Scale Study

OBJECTIVE

Three leading neurobiological hypotheses about autism spectrum disorder (ASD) propose underconnectivity between brain regions, atypical function of the amygdala, and generally higher variability between individuals with ASD than between neurotypical individuals. Past work has often failed to generalize, because of small sample sizes, unquantified data quality, and analytic flexibility. This study addressed these limitations while testing the above three hypotheses, applied to amygdala functional connectivity.

METHODS

In a comprehensive preregistered study, the three hypotheses were tested in a subset (N=488 after exclusions; N=212 with ASD) of the Autism Brain Imaging Data Exchange data sets. The authors analyzed resting-state functional connectivity (FC) from functional MRI data from two anatomically defined amygdala subdivisions, in three hypotheses with respect to magnitude, pattern similarity, and variability, across different anatomical scales ranging from whole brain to specific regions and networks.

RESULTS

A Bayesian approach to hypothesis evaluation produced inconsistent evidence in ASD for atypical amygdala FC magnitude, strong evidence that the multivariate pattern of FC was typical, and no consistent evidence of increased interindividual variability in FC. The results strongly depended on analytic choices, including preprocessing pipeline for the neuroimaging data, anatomical specificity, and subject exclusions.

CONCLUSIONS

A preregistered set of analyses found no reliable evidence for atypical functional connectivity of the amygdala in autism, contrary to leading hypotheses. Future studies should test an expanded set of hypotheses across multiple processing pipelines, collect deeper data per individual, and include a greater diversity of participants to ensure robust generalizability of findings on amygdala FC in ASD.

Dynamic functional connections analysis with spectral learning for brain disorder detection

Dynamic functional connections (dFCs), can reveal neural activities, which provides an insightful way of mining the temporal patterns within the human brain and further detecting brain disorders. However, most existing studies focus on the dFCs estimation to identify brain disorders by shallow temporal features and methods, which cannot capture the inherent temporal patterns of dFCs effectively. To address this problem, this study proposes a novel method, named dynamic functional connections analysis with spectral learning (dCSL), to explore inherently temporal patterns of dFCs and further detect the brain disorders. Concretely, dCSL includes two components, dFCs estimation module and dFCs analysis module. In the former, dFCs are estimated via the sliding window technique. In the latter, the spectral kernel mapping is first constructed by combining the Fourier transform with the non-stationary kernel. Subsequently, the spectral kernel mapping is stacked into a deep kernel network to explore higher-order temporal patterns of dFCs through spectral learning. The proposed dCSL, sharing the benefits of deep architecture and non-stationary kernel, can not only calculate the long-range relationship but also explore the higher-order temporal patterns of dFCs. To evaluate the proposed method, a set of brain disorder classification tasks are conducted on several public datasets. As a result, the proposed dCSL achieves 5% accuracy improvement compared with the widely used approaches for analyzing sequence data, 1.3% accuracy improvement compared with the state-of-the-art methods for dFCs. In addition, the discriminative brain regions are explored in the ASD detection task. The findings in this study are consistent with the clinical performance in ASD.

Continuous exercise training rescues hippocampal long-term potentiation in the VPA rat model of Autism: Uncovering sex-specific effects

Long-term potentiation (LTP) impairment has been reported in many studies of autistic models. The aim of the present study was to investigate the effects of interval training (IT) and continuous training (CT) exercises on LTP in the hippocampal dentate gyrus (DG) neurons of valproic acid (VPA) rat model of autism. To induce an autism-like model, pregnant rats were injected 500 mg/kg NaVPA (intraperitoneal) on the embryonic day 12.5. IT and CT aerobic exercises started on postnatal day 56 in the offspring. Four weeks after IT and/or CT exercises, the offspring were urethane-anesthetized and placed into a stereotaxic apparatus for surgery, electrode implantation, and field potential recording. In the DG region, excitatory post synaptic potentials (EPSP) slope and population spike (PS) amplitude were measured. Sex differences in LTP were evident for control rats but not for VPA-exposed offspring. LTP was significantly smaller in VPA-exposed male offspring compared with control male rats. In contrast to males, there was no difference between VPA-exposed female offspring and control female rats. Interestingly, we observed a sex difference in the response to exercise between VPA-exposed male and female offspring. CT exercise training (but not IT) increased LTP in VPA-exposed male offspring. Both IT and CT exercise trainings had no effect on intact LTP in VPA-exposed female offspring. Our work suggests that there may be differences in the benefits of exercise interventions based on sex, and CT exercise training could be more beneficial for LTP improvements.

Contactin-4 suppresses antitumor T cell responses by engaging amyloid precursor protein

Immune checkpoint inhibitors have substantial advanced tumor treatment, but their limited benefits and strong responses in only a subset of patients remain challenging. In this study, we explored the immunomodulatory function of contactin-4 (CNTN4). CNTN4 was highly expressed in tumor tissues, and expression impaired the antitumor function of T cells. CNTN4 bound to amyloid precursor protein (APP) on T cells, which attenuated conjugation between cancer cells and T cells, and diminished T cell receptor signaling cascades. We developed an anti-CNTN4 antibody (GENA-104A16) and an anti-APP antibody (5A7) that blocked the binding between CNTN4 and APP. Administration of either GENA-104A16 or 5A7 promoted antitumor T cell responses in a syngeneic mouse model and increased tumor-infiltrating lymphocytes in vivo. Furthermore, elevated CNTN4 levels were associated with poor prognosis and negatively correlated with various cytotoxic immune-related markers. These results suggest that CNTN4-APP is an inhibitory checkpoint in T cells and represents a promising therapeutic strategy for cancer immunotherapy.

Knockdown of the Non-canonical Wnt Gene Prickle2 Leads to Cerebellar Purkinje Cell Abnormalities While Cerebellar-Mediated Behaviors Remain Intact

Autism spectrum disorders (ASD) involve brain wide abnormalities that contribute to a constellation of symptoms including behavioral inflexibility, cognitive dysfunction, learning impairments, altered social interactions, and perceptive time difficulties. Although a single genetic variation does not cause ASD, genetic variations such as one involving a non-canonical Wnt signaling gene, Prickle2, has been found in individuals with ASD. Previous work looking into phenotypes of Prickle2 knock-out (Prickle2-/-) and heterozygous mice (Prickle2-/+) suggest patterns of behavior similar to individuals with ASD including altered social interaction and behavioral inflexibility. Growing evidence implicates the cerebellum in ASD. As Prickle2 is expressed in the cerebellum, this animal model presents a unique opportunity to investigate the cerebellar contribution to autism-like phenotypes. Here, we explore cerebellar structural and physiological abnormalities in animals with Prickle2 knockdown using immunohistochemistry, whole-cell patch clamp electrophysiology, and several cerebellar-associated motor and timing tasks, including interval timing and eyeblink conditioning. Histologically, Prickle2-/- mice have significantly more empty spaces or gaps between Purkinje cells in the posterior lobules and a decreased propensity for Purkinje cells to fire action potentials. These structural cerebellar abnormalities did not impair cerebellar-associated behaviors as eyeblink conditioning and interval timing remained intact. Therefore, although Prickle-/- mice show classic phenotypes of ASD, they do not recapitulate the involvement of the adult cerebellum and may not represent the pathophysiological heterogeneity of the disorder.

Biomarkers of preschool children with autism spectrum disorder: quantitative analysis of whole-brain tissue component volumes, intelligence scores, ADOS-CSS, and ages of first-word production and walking onset

BACKGROUND

Preschooling is a critical time for intervention in children with autism spectrum disorder (ASD); thus, we analyzed brain tissue component volumes (BTCVs) and clinical indicators in preschool children with ASD to identify new biomarkers for early screening.

METHODS

Eighty preschool children (3-6 years) with ASD were retrospectively included. The whole-brain myelin content (MyC), white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), and non-WM/GM/MyC/CSF brain component volumes were obtained using synthetic magnetic resonance imaging (SyMRI). Clinical data, such as intelligence scores, autism diagnostic observation schedule-calibrated severity scores, age at first production of single words (AFSW), age at first production of phrases (AFP), and age at walking onset (AWO), were also collected. The correlation between the BTCV and clinical data was evaluated, and the effect of BTCVs on clinical data was assessed by a regression model.

RESULTS

WM and GM volumes were positively correlated with intelligence scores (both P < 0.001), but WM and GM did not affect intelligence scores (P = 0.116, P = 0.290). AWO was positively correlated with AFSW and AFP (both P < 0.001). The multivariate linear regression analysis revealed that MyC, AFSW, AFP, and AWO were significantly different (P = 0.005, P < 0.001, P < 0.001).

CONCLUSIONS

This study revealed positive correlations between WM and GM volumes and intelligence scores. Whole-brain MyC affected AFSW, AFP, and AWO in preschool children with ASD. Noninvasive quantification of BTCVs via SyMRI revealed a new visualizable and quantifiable biomarker (abnormal MyC) for early ASD screening in preschool children.

Local and long-range input balance: A framework for investigating frontal cognitive circuit maturation in health and disease

Frontal cortical circuits undergo prolonged maturation across childhood and adolescence; however, it remains unknown what specific changes are occurring at the circuit level to establish adult cognitive function. With the recent advent of circuit dissection techniques, it is now feasible to examine circuit-specific changes in connectivity, activity, and function in animal models. Here, we propose that the balance of local and long-range inputs onto frontal cognitive circuits is an understudied metric of circuit maturation. This review highlights research on a frontal-sensory attention circuit that undergoes refinement of local/long-range connectivity, regulated by circuit activity and neuromodulatory signaling, and evaluates how this process may occur generally in the frontal cortex to support adult cognitive behavior. Notably, this balance can be bidirectionally disrupted through various mechanisms relevant to psychiatric disorders. Pharmacological or environmental interventions to normalize or reset the local and long-range balance could hold great therapeutic promise to prevent or rescue cognitive deficits.

Altered white matter connectivity of ventral language networks in autism spectrum disorder: An automated fiber quantification analysis with multi-site datasets

Comprehension and pragmatic deficits are prevalent in autism spectrum disorder (ASD) and are potentially linked to altered connectivity in the ventral language networks. However, previous magnetic resonance imaging studies have not sufficiently explored the microstructural abnormalities in the ventral fiber tracts underlying comprehension dysfunction in ASD. Additionally, the precise locations of white matter (WM) changes in the long tracts of patients with ASD remain poorly understood. In the current study, we applied the automated fiber-tract quantification (AFQ) method to investigate the fine-grained WM properties of the ventral language pathway and their relationships with comprehension and symptom manifestation in ASD. The analysis included diffusion/T1 weighted imaging data of 83 individuals with ASD and 83 age-matched typically developing (TD) controls. Case-control comparisons were performed on the diffusion metrics of the ventral tracts at both the global and point-wise levels. We also explored correlations between diffusion metrics, comprehension performance, and ASD traits, and conducted subgroup analyses based on age range to examine developmental moderating effects. Individuals with ASD exhibited remarkable hypoconnectivity in the ventral tracts, particularly in the temporal portions of the left inferior longitudinal fasciculus (ILF) and the inferior fronto-occipital fasciculus (IFOF). These WM abnormalities were associated with poor comprehension and more severe ASD symptoms. Furthermore, WM alterations in the ventral tract and their correlation with comprehension dysfunction were more prominent in younger children with ASD than in adolescents. These findings indicate that WM disruptions in the temporal portions of the left ILF/IFOF are most notable in ASD, potentially constituting the core neurological underpinnings of comprehension and communication deficits in autism. Moreover, impaired WM connectivity and comprehension ability in patients with ASD appear to improve with age.

Sensory processing associated with subcategories of restricted and repetitive behaviors in Japanese children and adolescents with autism spectrum disorder

Background

Restricted and repetitive behavior (RRB) is a core symptom of autism spectrum disorder (ASD). The structure of RRB subcategories and their relationship with atypical sensory processing in Japan are not well understood. This study examined subcategories of the RRB in Japanese children with ASD and explored their relationship with sensory processing.

Methods

A total of 103 children and adolescents with ASD participated in this study, with more than 70% having a co-occurring intellectual disability. First, exploratory factor analysis of the RRB items of the Social Responsiveness Scale second edition (SRS-2) was conducted to identify RRB subcategories. Second, Spearman correlation and multiple regression analysis were run to examine relationships between the RRB subcategories of SRS-2 and subsections of the Short Sensory Profile.

Results

Exploratory factor analysis indicated a two factors solution; repetitive sensory and motor behavior and insistence on sameness. Multiple regression analysis suggested that Movement Sensitivity and Auditory Filtering were associated with insistence on sameness. Furthermore, Underresponsive/Seeks Sensation, Visual/Auditory Sensitivity, and diagnosis of intellectual disabilities were associated with repetitive sensory and motor behavior.

Conclusions

Findings indicate that RRB subcategories are differently related to sensory processing patterns in children with ASD. These results suggested that RRB subcategories are beneficial to consider the relationship between RRB and sensory processing.

Deep brain stimulation of the Tbr1-deficient mouse model of autism spectrum disorder at the basolateral amygdala alters amygdalar connectivity, whole-brain synchronization, and social behaviors

Autism spectrum disorders (ASDs) are considered neural dysconnectivity syndromes. To better understand ASD and uncover potential treatments, it is imperative to know and dissect the connectivity deficits under conditions of autism. Here, we apply a whole-brain immunostaining and quantification platform to demonstrate impaired structural and functional connectivity and aberrant whole-brain synchronization in a Tbr1+/- autism mouse model. We express a channelrhodopsin variant oChIEF fused with Citrine at the basolateral amygdala (BLA) to outline the axonal projections of BLA neurons. By activating the BLA under blue light theta-burst stimulation (TBS), we then evaluate the effect of BLA activation on C-FOS expression at a whole brain level to represent neural activity. We show that Tbr1 haploinsufficiency almost completely disrupts contralateral BLA axonal projections and results in mistargeting in both ipsilateral and contralateral hemispheres, thereby globally altering BLA functional connectivity. Based on correlated C-FOS expression among brain regions, we further show that Tbr1 deficiency severely disrupts whole-brain synchronization in the absence of salient stimulation. Tbr1+/- and wild-type (WT) mice exhibit opposing responses to TBS-induced amygdalar activation, reducing synchronization in WT mice but enhancing it in Tbr1+/- mice. Whole-brain modular organization and intermodule connectivity are also affected by Tbr1 deficiency and amygdalar activation. Following BLA activation by TBS, the synchronizations of the whole brain and the default mode network, a specific subnetwork highly relevant to ASD, are enhanced in Tbr1+/- mice, implying a potential ameliorating effect of amygdalar stimulation on brain function. Indeed, TBS-mediated BLA activation increases nose-to-nose social interactions of Tbr1+/- mice, strengthening evidence for the role of amygdalar connectivity in social behaviors. Our high-resolution analytical platform reveals the inter- and intrahemispheric connectopathies arising from ASD. Our study emphasizes the defective synchronization at a whole-brain scale caused by Tbr1 deficiency and implies a potential beneficial effect of deep brain stimulation at the amygdala for TBR1-linked autism.

Identifying Diagnostic Biomarkers for Autism Spectrum Disorder From Higher-order Interactions Using the PED Algorithm

In the field of neuroimaging, more studies of abnormalities in brain regions of the autism spectrum disorder (ASD) usually focused on two brain regions connected, and less on abnormalities of higher-order interactions of brain regions. To explore the complex relationships of brain regions, we used the partial entropy decomposition (PED) algorithm to capture higher-order interactions by computing the higher-order dependencies of all three brain regions (triads). We proposed a method for examining the effect of individual brain regions on triads based on the PED and surrogate tests. The key triads were discovered by analyzing the effects. Further, the hypergraph modularity maximization algorithm revealed the higher-order brain structures, of which the link between right thalamus and left thalamus in ASD was more loose compared with the typical control (TC). Redundant key triad (left cerebellum crus 1 and left precuneus and right inferior occipital gyrus) exhibited a discernible attenuation in interaction in ASD, while the synergistic key triad (right cerebellum crus 1 and left postcentral gyrus and left lingual gyrus) indicated a notable decline. The results of classification model further confirmed the potential of the key triads as diagnostic biomarkers.

Towards understanding sex differences in autism spectrum disorders

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by social deficits, repetitive behaviours and lack of empathy. Its significant genetic heritability and potential comorbidities often lead to diagnostic and therapeutic challenges. This review addresses the biological basis of ASD, focusing on the sex differences in gene expression and hormonal influences. ASD is more commonly diagnosed in males at a ratio of 4:1, indicating a potential oversight in female-specific ASD research and a risk of underdiagnosis in females. We consider how ASD manifests differently across sexes by exploring differential gene expression in female and male brains and consider how variations in steroid hormones influence ASD characteristics. Synaptic function, including excitation/inhibition ratio imbalance, is influenced by gene mutations and this is explored as a key factor in the cognitive and behavioural manifestations of ASD. We also discuss the role of micro RNAs (miRNAs) and highlight a novel mutation in miRNA-873, which affects a suite of key synaptic genes, neurexin, neuroligin, SHANK and post-synaptic density proteins, implicated in the pathology of ASD. Our review suggests that genetic predisposition, sex differences in brain gene expression, and hormonal factors significantly contribute to the presentation, identification and severity of ASD, necessitating sex-specific considerations in diagnosis and treatments. These findings advocate for personalized interventions to improve the outcomes for individuals with ASD.

Effects of (S)-3,4-DCPG, an mGlu8 receptor agonist, on hippocampal long-term potentiation at perforant pathway-dentate gyrus synapses in prenatal valproic acid-induced rat model of autism

Autism spectrum disorder (ASD) is a pervasive neurodevelopmental condition characterized by social interaction deficits, communication impairments, repetitive behaviors, and sensory sensitivities. While the etiology of ASD is multifaceted, abnormalities in glutamatergic neurotransmission and synaptic plasticity have been implicated. This study investigated the role of metabotropic glutamate receptor 8 (mGlu8) in modulating long-term potentiation (LTP) in a rat model of ASD induced by prenatal valproic acid (VPA) exposure. To induce an animal model with autism-like characteristics, pregnant rats received an intraperitoneal injection of 500 mg/kg of sodium valproate (NaVPA) on embryonic day 12.5. High-frequency stimulation was applied to the perforant path-dentate gyrus (PP-DG) synapse to induce LTP, while the mGlu8 receptor agonist (S)-3,4-dicarboxyphenylglycine (DCPG) was administered into the DG. The results revealed that VPA-exposed rats exhibited reduced LTP compared to controls. DCPG had contrasting effects, inhibiting LTP in controls and enhancing it in VPA-exposed rats. Moreover, reduced social novelty preference index (SNPI) in VPA-exposed rats was reversed by intra-DG administration of S-3,4-DCPG. In conclusion, our study advances our understanding of the complex relationship between glutamatergic neurotransmission, synaptic plasticity, and VPA-induced autism model. The findings suggest that mGlu8 receptor dysfunction plays a role in the impaired synaptic plasticity seen in ASD.

Altered projection-specific synaptic remodeling and its modification by oxytocin in an idiopathic autism marmoset model

Alterations in the experience-dependent and autonomous elaboration of neural circuits are assumed to underlie autism spectrum disorder (ASD), though it is unclear what synaptic traits are responsible. Here, utilizing a valproic acid-induced ASD marmoset model, which shares common molecular features with idiopathic ASD, we investigate changes in the structural dynamics of tuft dendrites of upper-layer pyramidal neurons and adjacent axons in the dorsomedial prefrontal cortex through two-photon microscopy. In model marmosets, dendritic spine turnover is upregulated, and spines are generated in clusters and survived more often than in control marmosets. Presynaptic boutons in local axons, but not in commissural long-range axons, demonstrate hyperdynamic turnover in model marmosets, suggesting alterations in projection-specific plasticity. Intriguingly, nasal oxytocin administration attenuates clustered spine emergence in model marmosets. Enhanced clustered spine generation, possibly unique to certain presynaptic partners, may be associated with ASD and be a potential therapeutic target.

Molecular cascades and cell type-specific signatures in ASD revealed by single-cell genomics

Genomic profiling in postmortem brain from autistic individuals has consistently revealed convergent molecular changes. What drives these changes and how they relate to genetic susceptibility in this complex condition are not well understood. We performed deep single-nucleus RNA sequencing (snRNA-seq) to examine cell composition and transcriptomics, identifying dysregulation of cell type-specific gene regulatory networks (GRNs) in autism spectrum disorder (ASD), which we corroborated using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) and spatial transcriptomics. Transcriptomic changes were primarily cell type specific, involving multiple cell types, most prominently interhemispheric and callosal-projecting neurons, interneurons within superficial laminae, and distinct glial reactive states involving oligodendrocytes, microglia, and astrocytes. Autism-associated GRN drivers and their targets were enriched in rare and common genetic risk variants, connecting autism genetic susceptibility and cellular and circuit alterations in the human brain.

Functional connectivity in autism spectrum disorder evaluated using rs-fMRI and DKI

We evaluated functional connectivity (FC) in patients with adult autism spectrum disorder (ASD) using resting-state functional MRI (rs-fMRI) and diffusion kurtosis imaging (DKI). We acquired rs-fMRI data from 33 individuals with ASD and 33 healthy controls (HC) and DKI data from 18 individuals with ASD and 17 HC. ASD showed attenuated FC between the right frontal pole (FP) and the bilateral temporal fusiform cortex (TFusC) and enhanced FC between the right thalamus and the bilateral inferior division of lateral occipital cortex, and between the cerebellar vermis and the right occipital fusiform gyrus (OFusG) and the right lingual gyrus, compared with HC. ASD demonstrated increased axial kurtosis (AK) and mean kurtosis (MK) in white matter (WM) tracts, including the right anterior corona radiata (ACR), forceps minor (FM), and right superior longitudinal fasciculus (SLF). In ASD, there was also a significant negative correlation between MK and FC between the cerebellar vermis and the right OFusG in the corpus callosum, FM, right SLF and right ACR. Increased DKI metrics might represent neuroinflammation, increased complexity, or disrupted WM tissue integrity that alters long-distance connectivity. Nonetheless, protective or compensating adaptations of inflammation might lead to more abundant glial cells and cytokine activation effectively alleviating the degeneration of neurons, resulting in increased complexity. FC abnormality in ASD observed in rs-fMRI may be attributed to microstructural alterations of the commissural and long-range association tracts in WM as indicated by DKI.

Bridging Genetic Insights with Neuroimaging in Autism Spectrum Disorder-A Systematic Review

Autism Spectrum Disorder (ASD) is an early onset neurodevelopmental disorder characterized by impaired social interaction and communication, and repetitive patterns of behavior. Family studies show that ASD is highly heritable, and hundreds of genes have previously been implicated in the disorder; however, the etiology is still not fully clear. Brain imaging and electroencephalography (EEG) are key techniques that study alterations in brain structure and function. Combined with genetic analysis, these techniques have the potential to help in the clarification of the neurobiological mechanisms contributing to ASD and help in defining novel therapeutic targets. To further understand what is known today regarding the impact of genetic variants in the brain alterations observed in individuals with ASD, a systematic review was carried out using Pubmed and EBSCO databases and following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This review shows that specific genetic variants and altered patterns of gene expression in individuals with ASD may have an effect on brain circuits associated with face processing and social cognition, and contribute to excitation-inhibition imbalances and to anomalies in brain volumes.

Salience network connectivity is altered in 6-week-old infants at heightened likelihood for developing autism

Converging evidence implicates disrupted brain connectivity in autism spectrum disorder (ASD); however, the mechanisms linking altered connectivity early in development to the emergence of ASD symptomatology remain poorly understood. Here we examined whether atypicalities in the Salience Network - an early-emerging neural network involved in orienting attention to the most salient aspects of one's internal and external environment - may predict the development of ASD symptoms such as reduced social attention and atypical sensory processing. Six-week-old infants at high likelihood of developing ASD based on family history exhibited stronger Salience Network connectivity with sensorimotor regions; infants at typical likelihood of developing ASD demonstrated stronger Salience Network connectivity with prefrontal regions involved in social attention. Infants with higher connectivity with sensorimotor regions had lower connectivity with prefrontal regions, suggesting a direct tradeoff between attention to basic sensory versus socially-relevant information. Early alterations in Salience Network connectivity predicted subsequent ASD symptomatology, providing a plausible mechanistic account for the unfolding of atypical developmental trajectories associated with vulnerability to ASD.

Synaptic-dependent developmental dysconnectivity in 22q11.2 deletion syndrome

Chromosome 22q11.2 deletion is among the strongest known genetic risk factors for neuropsychiatric disorders, including autism and schizophrenia. Brain imaging studies have reported disrupted large-scale functional connectivity in people with 22q11 deletion syndrome (22q11DS). However, the significance and biological determinants of these functional alterations remain unclear. Here, we use a cross-species design to investigate the developmental trajectory and neural underpinnings of brain dysconnectivity in 22q11DS. We find that LgDel mice, an established mouse model of 22q11DS, exhibit age-specific patterns of functional MRI (fMRI) dysconnectivity, with widespread fMRI hyper-connectivity in juvenile mice reverting to focal hippocampal hypoconnectivity over puberty. These fMRI connectivity alterations are mirrored by co-occurring developmental alterations in dendritic spine density, and are both transiently normalized by developmental GSK3β inhibition, suggesting a synaptic origin for this phenomenon. Notably, analogous hyper- to hypoconnectivity reconfiguration occurs also in human 22q11DS, where it affects hippocampal and cortical regions spatially enriched for synaptic genes that interact with GSK3β, and autism-relevant transcripts. Functional dysconnectivity in somatomotor components of this network is predictive of age-dependent social alterations in 22q11.2 deletion carriers. Taken together, these findings suggest that synaptic-related mechanisms underlie developmentally mediated functional dysconnectivity in 22q11DS.

Clinical correlates of diagnostic certainty in children and youths with Autistic Disorder

BACKGROUND

Clinicians diagnosing autism rely on diagnostic criteria and instruments in combination with an implicit knowledge based on clinical expertise of the specific signs and presentations associated with the condition. This implicit knowledge influences how diagnostic criteria are interpreted, but it cannot be directly observed. Instead, insight into clinicians' understanding of autism can be gained by investigating their diagnostic certainty. Modest correlations between the certainty of an autism diagnosis and symptom load have been previously reported. Here, we investigated the associations of diagnostic certainty with specific items of the ADOS as well as other clinical features including head circumference.

METHODS

Phenotypic data from the Simons Simplex Collection was used to investigate clinical correlates of diagnostic certainty in individuals diagnosed with Autistic Disorder (n = 1511, age 4 to 18 years). Participants were stratified by the ADOS module used to evaluate them. We investigated how diagnostic certainty was associated with total ADOS scores, age, and ADOS module. We calculated the odds-ratios of being diagnosed with the highest possible certainty given the presence or absence of different signs during the ADOS evaluation. Associations between diagnostic certainty and other cognitive and clinical variables were also assessed.

RESULTS

In each ADOS module, some items showed a larger association with diagnostic certainty than others. Head circumference was significantly higher for individuals with the highest certainty rating across all three ADOS modules. In turn, head circumference was positively correlated with some of the ADOS items that were associated with diagnostic certainty, and was negatively correlated with verbal/nonverbal IQ ratio among those assessed with ADOS module 2.

LIMITATIONS

The investigated cohort was heterogeneous, e.g. in terms of age, IQ, language level, and total ADOS score, which could impede the identification of associations that only exist in a subgroup of the population. The variability of the certainty ratings in the sample was low, limiting the power to identify potential associations with other variables. Additionally, the scoring of diagnostic certainty may vary between clinicians.

CONCLUSION

Some ADOS items may better capture the signs that are most associated with clinicians' implicit knowledge of Autistic Disorder. If replicated in future studies, new diagnostic instruments with differentiated weighting of signs may be needed to better reflect this, possibly resulting in better specificity in standardized assessments.

Annual Research Review: Early intervention viewed through the lens of developmental neuroscience

The overarching goal of this paper is to examine the efficacy of early intervention when viewed through the lens of developmental neuroscience. We begin by briefly summarizing neural development from conception through the first few postnatal years. We emphasize the role of experience during the postnatal period, and consistent with decades of research on critical periods, we argue that experience can represent both a period of opportunity and a period of vulnerability. Because plasticity is at the heart of early intervention, we next turn our attention to the efficacy of early intervention drawing from two distinct literatures: early intervention services for children growing up in disadvantaged environments, and children at elevated likelihood of developing a neurodevelopmental delay or disorder. In the case of the former, we single out interventions that target caregiving and in the case of the latter, we highlight recent work on autism. A consistent theme throughout our review is a discussion of how early intervention is embedded in the developing brain. We conclude our article by discussing the implications our review has for policy, and we then offer recommendations for future research.

Mitochondria at the Nanoscale: Physics Meets Biology-What Does It Mean for Medicine?

Mitochondria are commonly perceived as "cellular power plants". Intriguingly, power conversion is not their only function. In the first part of this paper, we review the role of mitochondria in the evolution of eukaryotic organisms and in the regulation of the human body, specifically focusing on cancer and autism in relation to mitochondrial dysfunction. In the second part, we overview our previous works, revealing the physical principles of operation for proton-pumping complexes in the inner mitochondrial membrane. Our proposed simple models reveal the physical mechanisms of energy exchange. They can be further expanded to answer open questions about mitochondrial functions and the medical treatment of diseases associated with mitochondrial disorders.

Abnormal functional connectivity of the reward network is associated with social communication impairments in autism spectrum disorder: A large-scale multi-site resting-state fMRI study

BACKGROUND

The social motivation hypothesis proposes that the social deficits of autism spectrum disorder (ASD) are related to reward system dysfunction. However, functional connectivity (FC) patterns of the reward network in ASD have not been systematically explored yet.

METHODS

The reward network was defined as eight regions of interest (ROIs) per hemisphere, including the nucleus accumbens (NAc), caudate, putamen, anterior cingulate cortex (ACC), ventromedial prefrontal cortex (vmPFC), orbitofrontal cortex (OFC), amygdala, and insula. We computed both the ROI-wise resting-state FC and seed-based whole-brain FC in 298 ASD participants and 348 typically developing (TD) controls from the Autism Brain Imaging Data Exchange I dataset. Two-sample t-tests were applied to obtain the aberrant FCs. Then, the association between aberrant FCs and clinical symptoms was assessed with Pearson's correlation or Spearman's correlation. In addition, Neurosynth Image Decoder was used to generate word clouds verifying the cognitive functions of the aberrant pathways. Furthermore, a three-way multivariate analysis of variance (MANOVA) was conducted to examine the effects of gender, subtype and age on the atypical FCs.

RESULTS

For the within network analysis, the left ACC showed weaker FCs with both the right amygdala and left NAc in ASD compared with TD, which were negatively correlated with the Autism Diagnostic Observation Schedule (ADOS) total scores and Social Responsiveness Scale (SRS) total scores respectively. For the whole-brain analysis, weaker FC (i.e., FC between the left vmPFC and left calcarine gyrus, and between the right vmPFC and left precuneus) accompanied by stronger FC (i.e., FC between the left caudate and right insula) were exhibited in ASD relative to TD, which were positively associated with the SRS motivation scores. Additionally, we detected the main effect of age on FC between the left vmPFC and left calcarine gyrus, of subtype on FC between the right vmPFC and left precuneus, of age and age-by-gender interaction on FC between the left caudate and right insula.

CONCLUSIONS

Our findings highlight the crucial role of abnormal FC patterns of the reward network in the core social deficits of ASD, which have the potential to reveal new biomarkers for ASD.

Identification of novel NRF2-dependent genes as regulators of lead and arsenic toxicity in neural progenitor cells

Lead (Pb) and arsenic (As) are prevalent metal contaminants in the environment. Exposures to these metals are associated with impaired neuronal functions and adverse effects on neurodevelopment in children. However, the molecular mechanisms by which Pb and As impair neuronal functions remain poorly understood. Here, we identified F2RL2, TRIM16L, and PANX2 as novel targets of Nuclear factor erythroid 2-related factor 2 (NRF2)-the master transcriptional factor for the oxidative stress response-that are commonly upregulated with both Pb and As in human neural progenitor cells (NPCs). Using a ChIP (Chromatin immunoprecipitation)-qPCR assay, we showed that NRF2 directly binds to the promoter region of F2RL2, TRIM16L, and PANX2 to regulate expression of these genes. We demonstrated that F2RL2, PANX2, and TRIM16L have differential effects on cell death, proliferation, and differentiation of NPCs in both the presence and absence of metal exposures, highlighting their roles in regulating NPC function. Furthermore, the analyses of the transcriptomic data on NPCs derived from autism spectrum disorder (ASD) patients revealed that dysregulation of F2RL2, TRIM16L, and PANX2 was associated with ASD genetic backgrounds and ASD risk genes. Our findings revealed that Pb and As induce a shared NRF2-dependent transcriptional response in NPCs and identified novel genes regulating NPC function. While further in vivo studies are warranted, this study provides a novel mechanism linking metal exposures to NPC function and identifies potential genes of interest in the context of neurodevelopment.

The Mef2c Gene Dose-Dependently Controls Hippocampal Neurogenesis and the Expression of Autism-Like Behaviors

Mutations in the activity-dependent transcription factor MEF2C have been associated with several neuropsychiatric disorders. Among these, autism spectrum disorder (ASD)-related behavioral deficits are manifested. Multiple animal models that harbor mutations in Mef2c have provided compelling evidence that Mef2c is indeed an ASD gene. However, studies in mice with germline or global brain knock-out of Mef2c are limited in their ability to identify the precise neural substrates and cell types that are required for the expression of Mef2c-mediated ASD behaviors. Given the role of hippocampal neurogenesis in cognitive and social behaviors, in this study we aimed to investigate the role of Mef2c in the structure and function of newly generated dentate granule cells (DGCs) in the postnatal hippocampus and to determine whether disrupted Mef2c function is responsible for manifesting ASD behaviors. Overexpression of Mef2c (Mef2cOE ) arrested the transition of neurogenesis at progenitor stages, as indicated by sustained expression of Sox2+ in Mef2cOE DGCs. Conditional knock-out of Mef2c (Mef2ccko ) allowed neuronal commitment of Mef2ccko cells; however, Mef2ccko impaired not only dendritic arborization and spine formation but also synaptic transmission onto Mef2ccko DGCs. Moreover, the abnormal structure and function of Mef2ccko DGCs led to deficits in social interaction and social novelty recognition, which are key characteristics of ASD behaviors. Thus, our study revealed a dose-dependent requirement of Mef2c in the control of distinct steps of neurogenesis, as well as a critical cell-autonomous function of Mef2c in newborn DGCs in the expression of proper social behavior in both sexes.

iPSC-derived models of PACS1 syndrome reveal transcriptional and functional deficits in neuron activity

PACS1 syndrome is a neurodevelopmental disorder characterized by intellectual disability and distinct craniofacial abnormalities resulting from a de novo p.R203W variant in phosphofurin acidic cluster sorting protein 1 (PACS1). PACS1 is known to have functions in the endosomal pathway and nucleus, but how the p.R203W variant affects developing neurons is not fully understood. Here we differentiated stem cells towards neuronal models including cortical organoids to investigate the impact of the PACS1 syndrome-causing variant on neurodevelopment. While few deleterious effects were detected in PACS1(+/R203W) neural precursors, mature PACS1(+/R203W) glutamatergic neurons exhibited impaired expression of genes involved in synaptic signaling processes. Subsequent characterization of neural activity using calcium imaging and multielectrode arrays revealed the p.R203W PACS1 variant leads to a prolonged neuronal network burst duration mediated by an increased interspike interval. These findings demonstrate the impact of the PACS1 p.R203W variant on developing human neural tissue and uncover putative electrophysiological underpinnings of disease.

A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders

Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.

Synchronized LFP rhythmicity in the social brain reflects the context of social encounters

Mammalian social behavior is highly context-sensitive. Yet, little is known about the mechanisms that modulate social behavior according to its context. Recent studies have revealed a network of mostly limbic brain regions which regulates social behavior. We hypothesize that coherent theta and gamma rhythms reflect the organization of this network into functional sub-networks in a context-dependent manner. To test this concept, we simultaneously record local field potential (LFP) from multiple social brain regions in adult male mice performing three social discrimination tasks. While LFP rhythmicity across all tasks is dominated by a global internal state, the pattern of theta coherence between the various regions reflect the behavioral task more than other variables. Moreover, Granger causality analysis implicate the ventral dentate gyrus as a main player in coordinating the context-specific rhythmic activity. Thus, our results suggest that the pattern of coordinated rhythmic activity within the network reflects the subject's social context.

Delineating a Pathway for the Discovery of Functional Connectome Biomarkers of Autism

The promise of individually tailored care for autism has driven efforts to establish biomarkers. This chapter appraises the state of precision-medicine research focused on biomarkers based on the functional brain connectome. This work is grounded on abundant evidence supporting the brain dysconnection model of autism and the advantages of resting-state functional MRI (R-fMRI) for studying the brain in vivo. After considering biomarker requirements of consistency and clinical relevance, we provide a scoping review of R-fMRI studies of individual prediction in autism. In the past 10 years, responding to the availability of open data through the Autism Brain Imaging Data Exchange, machine learning studies have surged. Nearly all have focused on diagnostic label classification. These efforts have shown that autism prediction is feasible using functional connectome markers, with accuracy reported well above chance. In parallel, emerging approaches more directly addressing autism heterogeneity are paving the way for much-needed biomarkers of longitudinal outcome and treatment response. We conclude with key challenges to be addressed by the next generation of studies.

Identification and reduction of retained primitive reflexes by sensory stimulation in autism spectrum disorder: effects on qEEG networks and cognitive functions

Several authors have reported finding retained primitive reflexes (RPRs) in individuals with autism spectrum disorders (ASD). This case report describes the reduction of RPRs and changes in cognitive function after transcutaneous electrical nerve stimulation (TENS) of muscle. Three individuals were examined in a study at the Institute for Neurology and Neurosurgery in Havana, Cuba. Two child neurologists, not involved in the study, conducted clinical examinations on each participant and diagnosed each with ASD based on DSM-V criteria and the Autism Diagnostic Interview-Revised (an autism evaluation tool). Each child with ASD possessed a triad of impairments in three domains: social interaction, communication, and repetitive behaviour. Individuals were evaluated by quantitative electroencephalographic measures and tested by standardised cognitive function tests before and after 12 weeks of intervention. These interventions were associated with reduced ASD symptoms in the three domains, significant changes in qEEG network connectivity and significantly improved performance on standardised cognitive tests.