Neuroimaging endophenotypes in autism spectrum disorder

Pre-autism: Advancing early identification and intervention in autism

Autism spectrum disorder (ASD) is often diagnosed long after symptoms have become noticeable. This delay can make it difficult to provide early intervention, which can impact long-term outcomes. The concept of "pre-autism" highlights the phase before a formal diagnosis of ASD, providing an opportunity for earlier identification and intervention, which could be a turning point in ASD management. In a previous article, we explored different ways of diagnosing pre-autism, including historical records, physical markers, laboratory tests, and radiological evidence. This manuscript builds on that foundation by emphasizing the importance of early diagnosis and intervention in ASD. Recent research advancements have clarified that ASD presentations can be complex, and individualized support strategies are necessary. The significance of pre-autism lies in its potential to alter the trajectory of ASD through early detection and intervention despite challenges such as limited awareness and variability in symptom presentation. Biomarkers and diagnostic tools have shown promise as avenues for early detection, but it is essential to exercise caution and not rely too heavily on yet-to-be-established markers. Addressing these challenges requires a collaborative effort to increase awareness, improve access to diagnostic tools, and foster inclusive environments. Ultimately, this manuscript calls for ongoing research, advocacy, and resource allocation to enhance early detection and intervention efforts, ensuring optimal outcomes for individuals on the autism spectrum.

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.

Cortico-basal ganglia white matter microstructure is linked to restricted repetitive behavior in autism spectrum disorder

BACKGROUND

Restricted repetitive behavior (RRB) is one of two behavioral domains required for the diagnosis of autism spectrum disorder (ASD). Neuroimaging is widely used to study brain alterations associated with ASD and the domain of social and communication deficits, but there has been less work regarding brain alterations linked to RRB.

METHODS

We utilized neuroimaging data from the National Institute of Mental Health Data Archive to assess basal ganglia and cerebellum structure in a cohort of children and adolescents with ASD compared to typically developing (TD) controls. We evaluated regional gray matter volumes from T1-weighted anatomical scans and assessed diffusion-weighted scans to quantify white matter microstructure with free-water imaging. We also investigated the interaction of biological sex and ASD diagnosis on these measures, and their correlation with clinical scales of RRB.

RESULTS

Individuals with ASD had significantly lower free-water corrected fractional anisotropy (FAT) and higher free-water (FW) in cortico-basal ganglia white matter tracts. These microstructural differences did not interact with biological sex. Moreover, both FAT and FW in basal ganglia white matter tracts significantly correlated with measures of RRB. In contrast, we found no significant difference in basal ganglia or cerebellar gray matter volumes.

LIMITATIONS

The basal ganglia and cerebellar regions in this study were selected due to their hypothesized relevance to RRB. Differences between ASD and TD individuals that may occur outside the basal ganglia and cerebellum, and their potential relationship to RRB, were not evaluated.

CONCLUSIONS

These new findings demonstrate that cortico-basal ganglia white matter microstructure is altered in ASD and linked to RRB. FW in cortico-basal ganglia and intra-basal ganglia white matter was more sensitive to group differences in ASD, whereas cortico-basal ganglia FAT was more closely linked to RRB. In contrast, basal ganglia and cerebellar volumes did not differ in ASD. There was no interaction between ASD diagnosis and sex-related differences in brain structure. Future diffusion imaging investigations in ASD may benefit from free-water estimation and correction in order to better understand how white matter is affected in ASD, and how such measures are linked to RRB.

Early Diagnosis of Autism Spectrum Disorder: A Review and Analysis of the Risks and Benefits

Autism spectrum disorder (ASD) is a neurodevelopmental condition made up of enduring challenges in social communication and interaction and the presence of repetitive and restricted behavior patterns. Early diagnosis of autism is crucial for timely intervention and improved long-term outcomes. This review aims to explore some of its signs and symptoms, look into some diagnostic tools, and analyze the benefits and risks associated with an early diagnosis of autism. The symptoms of ASD vary from child to child, some of which are: avoidance of eye contact, lack of response to names, excessive fear, and lack of interactive and pretend play. Early identification of these symptoms by caregivers and healthcare providers facilitates the need for diagnosis and appropriate interventions. Some screening and diagnostic tools that have been found to help make the diagnosis are the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F), the Social Communication Questionnaire (SCQ), the Parents' Evaluation of Developmental Status (PEDS), and the Childhood Autism Rating Scale (CARS), amongst others. The benefits of early diagnosis include the opportunity for early intervention, which has been shown to enhance developmental outcomes and improve adaptive skills. Early identification allows for the implementation of specialized interventions tailored to the specific needs of individuals with autism, targeting social communication, language development, and behavioral challenges. Furthermore, early diagnosis enables families to access appropriate support services, educational resources, and community programs, facilitating better coping mechanisms, reducing parental stress, and increasing adult independence. However, early diagnosis of autism also entails certain risks. One significant concern is the potential for labeling and stigmatization, which can impact the child's self-esteem and social interactions. There is a risk of overdiagnosis or misdiagnosis, leading to unnecessary interventions and treatments. Additionally, the diagnostic process can be lengthy, complex, and emotionally challenging for families, requiring comprehensive assessments by multidisciplinary teams. This review highlights the importance of a balanced approach when considering the benefits and risks of early diagnosis. Early identification allows for timely interventions that significantly improve developmental outcomes and quality of life for individuals with autism. To mitigate the risks, it is crucial to ensure accurate and reliable diagnostic procedures, support families throughout the process, and promote societal awareness and acceptance. We also highlighted some future directions in the management of autism, including the use of biomarkers and the use of artificial intelligence and learning for diagnosing ASD.

Tubers Affecting the Fusiform Face Area Are Associated with Autism Diagnosis

OBJECTIVE

Tuberous sclerosis complex (TSC) is associated with focal brain "tubers" and a high incidence of autism spectrum disorder (ASD). The location of brain tubers associated with autism may provide insight into the neuroanatomical substrate of ASD symptoms.

METHODS

We delineated tuber locations for 115 TSC participants with ASD (n = 31) and without ASD (n = 84) from the Tuberous Sclerosis Complex Autism Center of Excellence Research Network. We tested for associations between ASD diagnosis and tuber burden within the whole brain, specific lobes, and at 8 regions of interest derived from the ASD neuroimaging literature, including the anterior cingulate, orbitofrontal and posterior parietal cortices, inferior frontal and fusiform gyri, superior temporal sulcus, amygdala, and supplemental motor area. Next, we performed an unbiased data-driven voxelwise lesion symptom mapping (VLSM) analysis. Finally, we calculated the risk of ASD associated with positive findings from the above analyses.

RESULTS

There were no significant ASD-related differences in tuber burden across the whole brain, within specific lobes, or within a priori regions derived from the ASD literature. However, using VLSM analysis, we found that tubers involving the right fusiform face area (FFA) were associated with a 3.7-fold increased risk of developing ASD.

INTERPRETATION

Although TSC is a rare cause of ASD, there is a strong association between tuber involvement of the right FFA and ASD diagnosis. This highlights a potentially causative mechanism for developing autism in TSC that may guide research into ASD symptoms more generally. ANN NEUROL 2023;93:577-590.

Molecular Abnormalities in BTBR Mice and Their Relevance to Schizophrenia and Autism Spectrum Disorders: An Overview of Transcriptomic and Proteomic Studies

Animal models of psychopathologies are of exceptional interest for neurobiologists because these models allow us to clarify molecular mechanisms underlying the pathologies. One such model is the inbred BTBR strain of mice, which is characterized by behavioral, neuroanatomical, and physiological hallmarks of schizophrenia (SCZ) and autism spectrum disorders (ASDs). Despite the active use of BTBR mice as a model object, the understanding of the molecular features of this strain that cause the observed behavioral phenotype remains insufficient. Here, we analyzed recently published data from independent transcriptomic and proteomic studies on hippocampal and corticostriatal samples from BTBR mice to search for the most consistent aberrations in gene or protein expression. Next, we compared reproducible molecular signatures of BTBR mice with data on postmortem samples from ASD and SCZ patients. Taken together, these data helped us to elucidate brain-region-specific molecular abnormalities in BTBR mice as well as their relevance to the anomalies seen in ASDs or SCZ in humans.

In-silico discovery of dual active molecule to restore synaptic wiring against autism spectrum disorder via HDAC2 and H3R inhibition

Metal-dependent histone deacetylases (HDACs) are essential epigenetic regulators; their molecular and pharmacological roles in medically critical diseases such as neuropsychiatric disorders, neurodegeneration, and cancer are being studied globally. HDAC2’s differential expression in the central nervous system makes it an appealing therapeutic target for chronic neurological diseases like autism spectrum disorder. In this study, we identified H3R inhibitor molecules that are computationally effective at binding to the HDAC2 metal-coordinated binding site. The study highlights the importance of pitolisant in screening the potential H3R inhibitors by using a hybrid workflow of ligand and receptor-based drug discovery. The screened lead compounds with PubChem SIDs 103179850, 103185945, and 103362074 show viable binding with HDAC2 in silico. The importance of ligand contacts with the Zn²⁺ ion in the HDAC2 catalytic site is also discussed and investigated for a significant role in enzyme inhibition. The proposed H3R inhibitors 103179850, 103185945, and 103362074 are estimated as dual-active molecules to block the HDAC2-mediated deacetylation of the EAAT2 gene (SLC1A2) and H3R-mediated synaptic transmission irregularity and are, therefore, open for experimental validation.

Using causal methods to map symptoms to brain circuits in neurodevelopment disorders: moving from identifying correlates to developing treatments

A wide variety of model systems and experimental techniques can provide insight into the structure and function of the human brain in typical development and in neurodevelopmental disorders. Unfortunately, this work, whether based on manipulation of animal models or observational and correlational methods in humans, has a high attrition rate in translating scientific discovery into practicable treatments and therapies for neurodevelopmental disorders.With new computational and neuromodulatory approaches to interrogating brain networks, opportunities exist for "bedside-to bedside-translation" with a potentially shorter path to therapeutic options. Specifically, methods like lesion network mapping can identify brain networks involved in the generation of complex symptomatology, both from acute onset lesion-related symptoms and from focal developmental anomalies. Traditional neuroimaging can examine the generalizability of these findings to idiopathic populations, while non-invasive neuromodulation techniques such as transcranial magnetic stimulation provide the ability to do targeted activation or inhibition of these specific brain regions and networks. In parallel, real-time functional MRI neurofeedback also allow for endogenous neuromodulation of specific targets that may be out of reach for transcranial exogenous methods.Discovery of novel neuroanatomical circuits for transdiagnostic symptoms and neuroimaging-based endophenotypes may now be feasible for neurodevelopmental disorders using data from cohorts with focal brain anomalies. These novel circuits, after validation in large-scale highly characterized research cohorts and tested prospectively using noninvasive neuromodulation and neurofeedback techniques, may represent a new pathway for symptom-based targeted therapy.

Cortical Thickness and Clinical Findings in Prescholar Children With Autism Spectrum Disorder

The term autism spectrum disorder (ASD) includes a wide variability of clinical presentation, and this clinical heterogeneity seems to reflect a still unclear multifactorial etiopathogenesis, encompassing different genetic risk factors and susceptibility to environmental factors. Several studies and many theories recognize as mechanisms of autism a disruption of brain development and maturation time course, suggesting the existence of common neurobiological substrates, such as defective synaptic structure and aberrant brain connectivity. Magnetic resonance imaging (MRI) plays an important role in both assessment of region-specific structural changes and quantification of specific alterations in gray or white matter, which could lead to the identification of an MRI biomarker. In this study, we performed measurement of cortical thickness in a selected well-known group of preschool ASD subjects with the aim of finding correlation between cortical metrics and clinical scores to understand the underlying mechanism of symptoms and to support early clinical diagnosis. Our results confirm that recent brain MRI techniques combined with clinical data can provide some useful information in defining the cerebral regions involved in ASD although large sample studies with homogeneous analytical and multisite approaches are needed.

Molecular Dysregulation in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) comprises a heterogeneous group of neurodevelopmental disorders with a strong heritable genetic component. At present, ASD is diagnosed solely by behavioral criteria. Advances in genomic analysis have contributed to numerous candidate genes for the risk of ASD, where rare mutations and s common variants contribute to its susceptibility. Moreover, studies show rare de novo variants, copy number variation and single nucleotide polymorphisms (SNPs) also impact neurodevelopment signaling. Exploration of rare and common variants involved in common dysregulated pathways can provide new diagnostic and therapeutic strategies for ASD. Contributions of current innovative molecular strategies to understand etiology of ASD will be explored which are focused on whole exome sequencing (WES), whole genome sequencing (WGS), microRNA, long non-coding RNAs and CRISPR/Cas9 models. Some promising areas of pharmacogenomic and endophenotype directed therapies as novel personalized treatment and prevention will be discussed.

The trend of association between autism traits in mothers and severity of autism symptomatology in children

Purpose

Autism spectrum disorders (ASD) are heterogeneous disorders, and heterogeneity lies both at genetic and phenotypic levels. To better understand the etiology and pathway that may contribute to autism symptomatology, it is important to study milder expressions of autism characteristics – autistic traits or milder expressions of autism phenotype, especially in intergenerational context. This study aims to see the trend of association, if any, between child autism symptom and mothers’ autism phenotype as well as mothers’ theory of mind and to see if mothers’ theory of mind was associated with their own autistic traits.

Design/methodology/approach

Data were collected from 96 mothers of children with varying symptom severity of autism (mild, moderate and severe) using Autism Spectrum Quotient and faux pas recognition test. Analysis of variance, trend analysis and t-test were done.

Findings

Results showed a linear trend of relationship between mothers’ autism phenotype and child symptom severity. However, the groups did not have significant differences in theory of mind. Only a few components of theory of mind were found to be associated with autistic traits. These findings question the prevailing idea that theory of mind can be a reliable endophenotype of autism.

Research limitations/implications

There has been a lack of research assessing the possible link between parents’ autism phenotype and symptom severity of ASD children. This study is a preliminary step towards that direction. This study indicates a probability of shared genetic liability between mothers and offspring, which would have important consequences for understanding the mechanisms that lead to autism.

Practical implications

This study offers implications for treatment planning of those with clinical ASD. An awareness of parental factors is critical for any holistic intervention plan when a family seeks treatment for their child. This study suggests that while individualising interventions, clinicians may consider possible presence of high levels of autistic traits and related cognitive features present in the probands’ parents.

Originality/value

There has been lack of research assessing the possible link between parents’ autism phenotype and symptom severity of ASD children. This study, even though preliminary, is a step towards that direction. This study suggests that autism traits might be influenced by common genetic variation and indicates a probability of shared genetic liability between mothers and offspring, which would have important consequences for understanding the mechanisms that lead to autism.

Brief Report: Neuroimaging Endophenotypes of Social Robotic Applications in Autism Spectrum Disorder

A plethora of neuroimaging studies have focused on the discovery of potential neuroendophenotypes useful to understand the etiopathogenesis of autism and predict treatment response. Social robotics has recently been proposed as an effective tool to strengthen the current treatments in children with autism. However, the high clinical heterogeneity characterizing this disorder might interfere with behavioral effects. Neuroimaging is set to overcome these limitations by capturing the level of heterogeneity. Here, we provide a preliminary evaluation of the neural basis of social robotics and how extracting neural hallmarks useful to design more effective behavioral applications. Despite the endophenotype-oriented neuroimaging research approach is in its relative infancy, this preliminary evidence encourages innovation to address its current limitations.

Changes in the development of subcortical structures in autism spectrum disorder

Many studies have reported abnormalities in the volume of subcortical structures in individuals with autism spectrum disorder (ASD), and many of these change with age. However, most studies that have investigated subcortical structures were cross-sectional and did not accurately segment the subcortical structures. In this study, we used volBrain, an automatic and reliable quantitative analysis tool, and a longitudinal design to examine developmental changes in the volume of subcortical structures in ASD, and quantified the relation between subcortical volume development and clinical correlates. Nineteen individuals with ASD (16 males; age: 12.53 ± 2.34 years at baseline; interval: 2.33 years) and 14 typically developing controls (TDC; 12 males; age: 13.50 ± 1.77 years at baseline; interval: 2.31 years) underwent T1-weighted MRI at two time points. Bilaterally, hippocampus volume increased from baseline to follow-up in both ASD and TDC, with no difference between groups. Left caudate and right thalamus volume decreased in ASD, but did not change in TDC. The decreases in left caudate and right thalamus volume were related to ASD social score. Right amygdala volume was larger in ASD than in TDC at baseline but not at follow-up. These results confirm previous cross-sectional findings regarding the development of subcortical structures in ASD. The association between developmental changes in left caudate and right thalamus volume and ASD social score offers an explanation for the social deficits in ASD. Results also captured the different abnormality of amygdala volume between childhood and late adolescence.

Quantitative Gait Analysis in Duplication 15q Syndrome and Nonsyndromic ASD

Motor impairments occur frequently in genetic syndromes highly penetrant for autism spectrum disorder (syndromic ASD) and in individuals with ASD without a genetic diagnosis (nonsyndromic ASD). In particular, abnormalities in gait in ASD have been linked to language delay, ASD severity, and likelihood of having a genetic disorder. Quantitative measures of motor function can improve our ability to evaluate motor differences in individuals with syndromic and nonsyndromic ASD with varying levels of intellectual disability and adaptive skills. To evaluate this methodology, we chose to use quantitative gait analysis to study duplication 15q syndrome (dup15q syndrome), a genetic disorder highly penetrant for motor delays, intellectual disability, and ASD. We evaluated quantitative gait variables in individuals with dup15q syndrome (n = 39) and nonsyndromic ASD (n = 21) and compared these data to a reference typically developing cohort. We found a gait pattern of slow pace, poor postural control, and large gait variability in dup15q syndrome. Our findings improve characterization of motor function in dup15q syndrome and nonsyndromic ASD. Quantitative gait analysis can be used as a translational method and can improve our identification of clinical endpoints to be used in treatment trials for these syndromes. Autism Res 2020, 13: 1102-1110. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Motor impairments, particularly abnormalities in walking, occur frequently in genetic syndromes highly penetrant for autism spectrum disorder (syndromic ASD). Here, using quantitative gait analysis, we find that individuals with duplication 15q syndrome have an atypical gait pattern that differentiates them from typically developing and nonsyndromic ASD individuals. Our findings improve motor characterization in dup15q syndrome and nonsyndromic ASD.

Identification, Evaluation, and Management of Children With Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder with reported prevalence in the United States of 1 in 59 children (approximately 1.7%). Core deficits are identified in 2 domains: social communication/interaction and restrictive, repetitive patterns of behavior. Children and youth with ASD have service needs in behavioral, educational, health, leisure, family support, and other areas. Standardized screening for ASD at 18 and 24 months of age with ongoing developmental surveillance continues to be recommended in primary care (although it may be performed in other settings), because ASD is common, can be diagnosed as young as 18 months of age, and has evidenced-based interventions that may improve function. More accurate and culturally sensitive screening approaches are needed. Primary care providers should be familiar with the diagnostic criteria for ASD, appropriate etiologic evaluation, and co-occurring medical and behavioral conditions (such as disorders of sleep and feeding, gastrointestinal tract symptoms, obesity, seizures, attention-deficit/hyperactivity disorder, anxiety, and wandering) that affect the child's function and quality of life. There is an increasing evidence base to support behavioral and other interventions to address specific skills and symptoms. Shared decision making calls for collaboration with families in evaluation and choice of interventions.  This single clinical report updates the 2007 American Academy of Pediatrics clinical reports on the evaluation and treatment of ASD in one publication with an online table of contents and section view available through the American Academy of Pediatrics Gateway to help the reader identify topic areas within the report.

Severe white matter damage in SHANK3 deficiency: a human and translational study

Objective

Heterozygous SHANK3 mutations or partial deletions of the long arm of chromosome 22, also known as Phelan–McDermid syndrome, result in a syndromic form of the autism spectrum as well as in global developmental delay, intellectual disability, and several neuropsychiatric comorbidities. The exact pathophysiological mechanisms underlying the disease are still far from being deciphered but studies of SHANK3 models have contributed to the understanding of how the loss of the synaptic protein SHANK3 affects neuronal function.

Methods and results

Diffusion tensor imaging‐based and automatic volumetric brain mapping were performed in 12 SHANK3‐deficient participants (mean age 19 ± 15 years) versus 14 age‐ and gender‐matched controls (mean age 29 ± 5 years). Using whole brain–based spatial statistics, we observed a highly significant pattern of white matter alterations in participants with SHANK3 mutations with focus on the long association fiber tracts, particularly the uncinate tract and the inferior fronto‐occipital fasciculus. In contrast, only subtle gray matter volumetric abnormalities were detectable. In a back‐translational approach, we observed similar white matter alterations in heterozygous isoform–specific Shank3 knockout (KO) mice. Here, in the baseline data sets, the comparison of Shank3 heterozygous KO vs wildtype showed significant fractional anisotropy reduction of the long fiber tract systems in the KO model. The multiparametric Magnetic Resonance Imaging (MRI) analysis by DTI and volumetry demonstrated a pathology pattern with severe white matter alterations and only subtle gray matter changes in the animal model.

Interpretation

In summary, these translational data provide strong evidence that the SHANK3‐deficiency–associated pathomechanism presents predominantly with a white matter disease. Further studies should concentrate on the role of SHANK3 during early axonal pathfinding/wiring and in myelin formation.

Association of genes with phenotype in autism spectrum disorder

Autism spectrum disorder (ASD) is a genetic heterogeneous neurodevelopmental disorder that is characterized by impairments in social interaction and speech development and is accompanied by stereotypical behaviors such as body rocking, hand flapping, spinning objects, sniffing and restricted behaviors. The considerable significance of the genetics associated with autism has led to the identification of many risk genes for ASD used for the probing of ASD specificity and shared cognitive features over the past few decades. Identification of ASD risk genes helps to unravel various genetic variants and signaling pathways which are involved in ASD. This review highlights the role of ASD risk genes in gene transcription and translation regulation processes, as well as neuronal activity modulation, synaptic plasticity, disrupted key biological signaling pathways, and the novel candidate genes that play a significant role in the pathophysiology of ASD. The current emphasis on autism spectrum disorders has generated new opportunities in the field of neuroscience, and further advancements in the identification of different biomarkers, risk genes, and genetic pathways can help in the early diagnosis and development of new clinical and pharmacological treatments for ASD.

The Use of Artificial Intelligence in Screening and Diagnosis of Autism Spectrum Disorder: A Literature Review

Objectives:

The detection of autism spectrum disorder (ASD) is based on behavioral observations. To build a more objective datadriven method for screening and diagnosing ASD, many studies have attempted to incorporate artificial intelligence (AI) technologies. Therefore, the purpose of this literature review is to summarize the studies that used AI in the assessment process and examine whether other behavioral data could potentially be used to distinguish ASD characteristics.

Methods:

Based on our search and exclusion criteria, we reviewed 13 studies.

Results:

To improve the accuracy of outcomes, AI algorithms have been used to identify items in assessment instruments that are most predictive of ASD. Creating a smaller subset and therefore reducing the lengthy evaluation process, studies have tested the efficiency of identifying individuals with ASD from those without. Other studies have examined the feasibility of using other behavioral observational features as potential supportive data.

Conclusion:

While previous studies have shown high accuracy, sensitivity, and specificity in classifying ASD and non-ASD individuals, there remain many challenges regarding feasibility in the real-world that need to be resolved before AI methods can be fully integrated into the healthcare system as clinical decision support systems.

Differences in Cortical Structure and Functional MRI Connectivity in High Functioning Autism

Autism spectrum disorders (ASD) represent a complex group of neurodevelopmental conditions characterized by deficits in communication and social behaviors. We examined the functional connectivity (FC) of the default mode network (DMN) and its relation to multimodal morphometry to investigate superregional, system-level alterations in a group of 22 adolescents and young adults with high-functioning autism compared to age-, and intelligence quotient-matched 29 healthy controls. The main findings were that ASD patients had gray matter (GM) reduction, decreased cortical thickness and larger cortical surface areas in several brain regions, including the cingulate, temporal lobes, and amygdala, as well as increased gyrification in regions associated with encoding visual memories and areas of the sensorimotor component of the DMN, more pronounced in the left hemisphere. Moreover, patients with ASD had decreased connectivity between the posterior cingulate cortex, and areas of the executive control component of the DMN and increased FC between the anteromedial prefrontal cortex and areas of the sensorimotor component of the DMN. Reduced cortical thickness in the right inferior frontal lobe correlated with higher social impairment according to the scores of the Autism Diagnostic Interview-Revised (ADI-R). Reduced cortical thickness in left frontal regions, as well as an increased cortical thickness in the right temporal pole and posterior cingulate, were associated with worse scores on the communication domain of the ADI-R. We found no association between scores on the restrictive and repetitive behaviors domain of ADI-R with structural measures or FC. The combination of these structural and connectivity abnormalities may help to explain some of the core behaviors in high-functioning ASD and need to be investigated further.

The neural circuitry of restricted repetitive behavior: Magnetic resonance imaging in neurodevelopmental disorders and animal models

Restricted, repetitive behaviors (RRBs) are patterns of behavior that exhibit little variation in form and have no obvious function. RRBs although transdiagonstic are a particularly prominent feature of certain neurodevelopmental disorders, yet relatively little is known about the neural circuitry of RRBs. Past work in this area has focused on isolated brain regions and neurotransmitter systems, but implementing a neural circuit approach has the potential to greatly improve understanding of RRBs. Magnetic resonance imaging (MRI) is well-suited to studying the structural and functional connectivity of the nervous system, and is a highly translational research tool. In this review, we synthesize MRI research from both neurodevelopmental disorders and relevant animal models that informs the neural circuitry of RRB. Together, these studies implicate distributed neural circuits between the cortex, basal ganglia, and cerebellum. Despite progress in neuroimaging of RRB, there are many opportunities for conceptual and methodological improvement. We conclude by suggesting future directions for MRI research in RRB, and how such studies can benefit from complementary approaches in neuroscience.

Mycobacterium avium subspecies paratuberculosis: A possible causative agent in human morbidity and risk to public health safety

Mycobacterium avium subspecies paratuberculosis is a bacterial parasite and the causative agent of paratuberculosis, a disease predominately found in cattle and sheep. Infection with this microorganism results in substantial farming economic losses and animal morbidity. The link between infection with this pathogen and human disease has been theorised for many years with Crohn's disease being one of many suspected resultant conditions. Mycobacterium avium may be spread from animal to human hosts by water and foodborne transmission routes, where the foodborne route of exposure represents a significant risk for susceptible populations, namely children and the immune-compromised. Following colonisation of the host, the parasitic organism evades the host immune system by use of molecular mimicry, displaying peptide sequences similar to that of the host cells causing a disruption of self-verses non self-recognition. Theoretically, this failure to recognise the invading organism as distinct from host cells may result in numerous autoimmune conditions. Here, the author presents current information assessing the link between numerous diseases states in humans such inflammatory bowel disease, Type 1 diabetes, rheumatoid arthritis, Hashimoto\'s thyroiditis, multiple sclerosis and autism following infection with Mycobacterium avium paratuberculosis. The possibility of zoonotic transmission of the organism and its significant risk to public health safety as a consequence is also discussed.

Motor development and delay: advances in assessment of motor skills in autism spectrum disorders

PURPOSE OF REVIEW

Motor impairments in neurodevelopmental disorders, specifically autism spectrum disorder (ASD), are prevalent and pervasive. Moreover, motor impairments may be the first sign of atypical development in ASD and likely contribute to abnormalities in social communication. However, measurement of motor function in ASD has lagged behind other behavioral phenotyping. Quantitative and neurodiagnostic measures of motor function can help identify specific motor impairments in ASD and the underlying neural mechanisms that might be implicated. These findings can serve as markers of early diagnosis, clinical stratification, and treatment targets.

RECENT FINDINGS

Here, we briefly review recent studies on the importance of motor function to other developmental domains in ASD. We then highlight studies that have applied quantitative and neurodiagnostic measures to better measure motor impairments in ASD and the neural mechanisms that may contribute to these abnormalities.

SUMMARY

Information from advanced quantitative and neurodiagnostic methods of motor function contribute to a better understanding of the specific and subtle motor impairments in ASD, and the relationship of motor function to language and social development. Greater utilization of these methods can assist with early diagnosis and development of targeted interventions. However, there remains a need to utilize these approaches in children with neurodevelopmental disorders across a developmental trajectory and with varying levels of cognitive function.

Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders

Recent years have witnessed the proliferation of neuroimaging studies of neurodevelopmental disorders (NDDs), particularly of children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Tourette's syndrome (TS). Neuroimaging offers immense potential in understanding the biology of these disorders, and how it relates to clinical symptoms. Neuroimaging techniques, in the long run, may help identify neurobiological markers to assist clinical diagnosis and treatment. However, methodological challenges have affected the progress of clinical neuroimaging. This paper reviews the methodological challenges involved in imaging children with NDDs. Specific topics include correcting for head motion, normalization using pediatric brain templates, accounting for psychotropic medication use, delineating complex developmental trajectories, and overcoming smaller sample sizes. The potential of neuroimaging-based biomarkers and the utility of implementing neuroimaging in a clinical setting are also discussed. Data-sharing approaches, technological advances, and an increase in the number of longitudinal, prospective studies are recommended as future directions. Significant advances have been made already, and future decades will continue to see innovative progress in neuroimaging research endeavors of NDDs.

Imaging genetics in autism spectrum disorders: Linking genetics and brain imaging in the pursuit of the underlying neurobiological mechanisms

Autism spectrum disorders (ASD) include a wide range of heterogeneous neurodevelopmental conditions that affect an individual in several aspects of social communication and behavior. Recent advances in molecular genetic technologies have dramatically increased our understanding of ASD etiology through the identification of several autism risk genes, most of which serve important functions in synaptic plasticity and protein synthesis. However, despite significant progress in this field of research, the characterization of the neurobiological mechanisms by which common genetic risk variants might operate to give rise to ASD symptomatology has proven to be far more difficult than expected. The imaging genetics approach holds great promise for advancing our understanding of ASD etiology by bridging the gap between genetic variations and their resultant biological effects on the brain. This paper provides a conceptual overview of the contribution of genetics in ASD and discusses key findings from the emerging field of imaging genetics.

Candidate Biomarkers in Children with Autism Spectrum Disorder: A Review of MRI Studies

Searching for effective biomarkers is one of the most challenging tasks in the research field of Autism Spectrum Disorder (ASD). Magnetic resonance imaging (MRI) provides a non-invasive and powerful tool for investigating changes in the structure, function, maturation, connectivity, and metabolism of the brain of children with ASD. Here, we review the more recent MRI studies in young children with ASD, aiming to provide candidate biomarkers for the diagnosis of childhood ASD. The review covers structural imaging methods, diffusion tensor imaging, resting-state functional MRI, and magnetic resonance spectroscopy. Future advances in neuroimaging techniques, as well as cross-disciplinary studies and large-scale collaborations will be needed for an integrated approach linking neuroimaging, genetics, and phenotypic data to allow the discovery of new, effective biomarkers.