Neuroanatomical differences in toddler boys with fragile x syndrome and idiopathic autism

Oligodendroglia and myelin pathology in fragile X syndrome

Studies of the pathophysiology of fragile X syndrome (FXS) have predominantly focused on synaptic and neuronal disruptions in the disease. However, emerging studies highlight the consistency of white matter abnormalities in the disorder. Recent investigations using animal models of FXS have suggested a role for the fragile X translational regulator 1 protein (FMRP) in the development and function of oligodendrocytes, the myelinating cells of the central nervous system. These studies are starting to uncover FMRP's involvement in the regulation of myelin-related genes, such as myelin basic protein, and its influence on the maturation and functionality of oligodendrocyte precursor cells and oligodendrocytes. Here, we consider evidence of white matter abnormalities in FXS, review our current understanding of FMRP's role in oligodendrocyte development and function, and highlight gaps in our knowledge of the pathogenic mechanisms that may contribute to white matter abnormalities in FXS. Addressing these gaps may help identify new therapeutic strategies aimed at enhancing outcomes for individuals affected by FXS.

Association of Intrinsic Functional Brain Network and Longitudinal Development of Cognitive Behavioral Symptoms in Young Girls With Fragile X Syndrome

BACKGROUND

Fragile X syndrome (FXS) is an X chromosome-linked genetic disorder characterized by increased risk for behavioral, social, and neurocognitive deficits. Because males express a more severe phenotype than females, research has focused largely on identifying neural abnormalities in all-male or both-sex populations with FXS. Therefore, very little is known about the neural alterations that contribute to cognitive behavioral symptoms in females with FXS. This cross-sectional study aimed to elucidate the large-scale resting-state brain networks associated with the multidomain cognitive behavioral phenotype in girls with FXS.

METHODS

We recruited 38 girls with full-mutation FXS (11.58 ± 3.15 years) and 32 girls without FXS (11.66 ± 2.27 years). Both groups were matched on age, verbal IQ, and multidomain cognitive behavioral symptoms. Resting-state functional magnetic resonance imaging data were collected.

RESULTS

Compared with the control group, girls with FXS showed significantly greater resting-state functional connectivity of the default mode network, lower nodal strength at the right middle temporal gyrus, stronger nodal strength at the left caudate, and higher global efficiency of the default mode network. These aberrant brain network characteristics map directly onto the cognitive behavioral symptoms commonly observed in girls with FXS. An exploratory analysis suggested that brain network patterns at a prior time point (time 1) were predictive of the longitudinal development of participants' multidomain cognitive behavioral symptoms.

CONCLUSIONS

These findings represent the first examination of large-scale brain network alterations in a large sample of girls with FXS, expanding our knowledge of potential neural mechanisms underlying the development of cognitive behavioral symptoms in girls with FXS.

Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry

BACKGROUND

The development of machine learning models for aiding in the diagnosis of mental disorder is recognized as a significant breakthrough in the field of psychiatry. However, clinical practice of such models remains a challenge, with poor generalizability being a major limitation.

METHODS

Here, we conducted a pre-registered meta-research assessment on neuroimaging-based models in the psychiatric literature, quantitatively examining global and regional sampling issues over recent decades, from a view that has been relatively underexplored. A total of 476 studies (n = 118,137) were included in the current assessment. Based on these findings, we built a comprehensive 5-star rating system to quantitatively evaluate the quality of existing machine learning models for psychiatric diagnoses.

RESULTS

A global sampling inequality in these models was revealed quantitatively (sampling Gini coefficient (G) = 0.81, p < .01), varying across different countries (regions) (e.g., China, G = 0.47; the USA, G = 0.58; Germany, G = 0.78; the UK, G = 0.87). Furthermore, the severity of this sampling inequality was significantly predicted by national economic levels (β =  - 2.75, p < .001, R²_adj = 0.40; r =  - .84, 95% CI: - .41 to - .97), and was plausibly predictable for model performance, with higher sampling inequality for reporting higher classification accuracy. Further analyses showed that lack of independent testing (84.24% of models, 95% CI: 81.0-87.5%), improper cross-validation (51.68% of models, 95% CI: 47.2-56.2%), and poor technical transparency (87.8% of models, 95% CI: 84.9-90.8%)/availability (80.88% of models, 95% CI: 77.3-84.4%) are prevailing in current diagnostic classifiers despite improvements over time. Relating to these observations, model performances were found decreased in studies with independent cross-country sampling validations (all p < .001, BF₁₀ > 15). In light of this, we proposed a purpose-built quantitative assessment checklist, which demonstrated that the overall ratings of these models increased by publication year but were negatively associated with model performance.

CONCLUSIONS

Together, improving sampling economic equality and hence the quality of machine learning models may be a crucial facet to plausibly translating neuroimaging-based diagnostic classifiers into clinical practice.

Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review

IMPORTANCE

Neuroimaging-based artificial intelligence (AI) diagnostic models have proliferated in psychiatry. However, their clinical applicability and reporting quality (ie, feasibility) for clinical practice have not been systematically evaluated.

OBJECTIVE

To systematically assess the risk of bias (ROB) and reporting quality of neuroimaging-based AI models for psychiatric diagnosis.

EVIDENCE REVIEW

PubMed was searched for peer-reviewed, full-length articles published between January 1, 1990, and March 16, 2022. Studies aimed at developing or validating neuroimaging-based AI models for clinical diagnosis of psychiatric disorders were included. Reference lists were further searched for suitable original studies. Data extraction followed the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. A closed-loop cross-sequential design was used for quality control. The PROBAST (Prediction Model Risk of Bias Assessment Tool) and modified CLEAR (Checklist for Evaluation of Image-Based Artificial Intelligence Reports) benchmarks were used to systematically evaluate ROB and reporting quality.

FINDINGS

A total of 517 studies presenting 555 AI models were included and evaluated. Of these models, 461 (83.1%; 95% CI, 80.0%-86.2%) were rated as having a high overall ROB based on the PROBAST. The ROB was particular high in the analysis domain, including inadequate sample size (398 of 555 models [71.7%; 95% CI, 68.0%-75.6%]), poor model performance examination (with 100% of models lacking calibration examination), and lack of handling data complexity (550 of 555 models [99.1%; 95% CI, 98.3%-99.9%]). None of the AI models was perceived to be applicable to clinical practices. Overall reporting completeness (ie, number of reported items/number of total items) for the AI models was 61.2% (95% CI, 60.6%-61.8%), and the completeness was poorest for the technical assessment domain with 39.9% (95% CI, 38.8%-41.1%).

CONCLUSIONS AND RELEVANCE

This systematic review found that the clinical applicability and feasibility of neuroimaging-based AI models for psychiatric diagnosis were challenged by a high ROB and poor reporting quality. Particularly in the analysis domain, ROB in AI diagnostic models should be addressed before clinical application.

Cortical Source Analysis of the Face Sensitive N290 ERP Component in Infants at High Risk for Autism

Appropriate head models for cortical source analysis were investigated and applied to source analyses examining the neural bases of the face-sensitive N290 event-related potential (ERP) component in infants at high risk for autism spectrum disorder (ASD). This included infant siblings of children with ASD (ASIBs) and infants with fragile X syndrome (FXS). First, alternative head models for use with ASIBs and FXS were investigated. Head models created from the infant's own MRI were examined in relation to five head models based on average MRI templates. The results of the head model comparison identified group-specific (i.e., ASIB or FXS) head models created from a large collection of structural MRIs as the best substitution for the head model created from the participant's own structural MRI. Second, the cortical source analysis was completed on N290 data collected from a previous study to investigate brain areas associated with face sensitive ERP responses. Participants' own MRIs were used for head models when available, and the group-specific head model was used when the participants' own MRIs were not available. The results provide evidence for unique patterns of neural activation during face processing across infants at high and low risk for ASD and across etiologically distinct high-risk groups. All infants demonstrated greater activation to faces than toys in brain areas most associated with specialized face processing. Infants with FXS displayed higher levels of activation to faces across all areas analyzed, while ASIBs show more muted levels of activation. Overall, the results of the current study demonstrate the importance of group-specific head models for accurate cortical source analysis in infants at high risk for ASD. This also allows for further research on early distinctions in brain function based on risk status.

Abnormal Brain Oscillations in Developmental Disorders: Application of Resting State EEG and MEG in Autism Spectrum Disorder and Fragile X Syndrome

Autism Spectrum Disorder (ASD) and Fragile X Syndrome (FXS) are neurodevelopmental disorders with similar clinical and behavior symptoms and partially overlapping and yet distinct neurobiological origins. It is therefore important to distinguish these disorders from each other as well as from typical development. Examining disruptions in functional connectivity often characteristic of neurodevelopment disorders may be one approach to doing so. This review focuses on EEG and MEG studies of resting state in ASD and FXS, a neuroimaging paradigm frequently used with difficult-to-test populations. It compares the brain regions and frequency bands that appear to be impacted, either in power or connectivity, in each disorder; as well as how these abnormalities may result in the observed symptoms. It argues that the findings in these studies are inconsistent and do not fit neatly into existing models of ASD and FXS, then highlights the gaps in the literature and recommends future avenues of inquiry.

The role of the host microbiome in autism and neurodegenerative disorders and effect of epigenetic procedures in the brain functions

Autism Spectrum Disorder (ASD) is a severe neurological/neurodegenerative syndrome that results in cognitive and communication disorders. The degree of dysbiosis is related to the severity of ASD signs. The gut is conferred with a variety of sensory receptors that cooperate with effector systems including the endocrine, nervous and gut immune systems of the intestine. Gut dysbiosis causes amplified inflammation, the launch of the HPA axis, changed levels of neurotransmitters and bacterial metabolites; these may donate to abnormal signaling throughout the Vagus nerve in ASD. Decreased integrity of the gastrointestinal barrier led to extreme leakage of substances as of the intestine in early life and inflammation followed by disruption of BBB integrity maybe increase the risk of ASD. Microbiota, by controlling the barrier permeability, regulate the quantity and types of bioactive materials that are transferred from the intestine to the brain. Exposure to metabolites and microbial products regulate significant procedures in the CNS, including glial cell role, myelination, synaptic pruning, and play a role in neurobehavioral, neurodegenerative, psychiatric, and metabolic syndrome.

Functional and Neuropathological Evidence for a Role of the Brainstem in Autism

The brainstem includes many nuclei and fiber tracts that mediate a wide range of functions. Data from two parallel approaches to the study of autistic spectrum disorder (ASD) implicate many brainstem structures. The first approach is to identify the functions affected in ASD and then trace the neural systems mediating those functions. While not included as core symptoms, three areas of function are frequently impaired in ASD: (1) Motor control both of the limbs and body and the control of eye movements; (2) Sensory information processing in vestibular and auditory systems; (3) Control of affect. There are critical brainstem nuclei mediating each of those functions. There are many nuclei critical for eye movement control including the superior colliculus. Vestibular information is first processed in the four nuclei of the vestibular nuclear complex. Auditory information is relayed to the dorsal and ventral cochlear nuclei and subsequently processed in multiple other brainstem nuclei. Critical structures in affect regulation are the brainstem sources of serotonin and norepinephrine, the raphe nuclei and the locus ceruleus. The second approach is the analysis of abnormalities from direct study of ASD brains. The structure most commonly identified as abnormal in neuropathological studies is the cerebellum. It is classically a major component of the motor system, critical for coordination. It has also been implicated in cognitive and language functions, among the core symptoms of ASD. This structure works very closely with the cerebral cortex; the cortex and the cerebellum show parallel enlargement over evolution. The cerebellum receives input from cortex via relays in the pontine nuclei. In addition, climbing fiber input to cerebellum comes from the inferior olive of the medulla. Mossy fiber input comes from the arcuate nucleus of the medulla as well as the pontine nuclei. The cerebellum projects to several brainstem nuclei including the vestibular nuclear complex and the red nucleus. There are thus multiple brainstem nuclei distributed at all levels of the brainstem, medulla, pons, and midbrain, that participate in functions affected in ASD. There is direct evidence that the cerebellum may be abnormal in ASD. The evidence strongly indicates that analysis of these structures could add to our understanding of the neural basis of ASD.

Neuroanatomical Profile of Young Females with Fragile X Syndrome: A Voxel-Based Morphometry Analysis

Fragile X syndrome is a genetic condition associated with alterations in brain and subsequent cognitive development. However, due to a milder phenotype relative to males, females with fragile X syndrome are underrepresented in research studies. In the current study, we investigate neuroanatomical differences in young females (age range: 6.03-16.32 years) with fragile X syndrome (N = 46) as compared to age-, sex-, and verbal abilities-matched participants (comparison group; N = 35). Between-group analyses of whole-brain and regional brain volumes were assessed using voxel-based morphometry. Results demonstrate significantly larger total gray and white matter volumes in girls with fragile X syndrome compared to a matched comparison group (Ps < 0.001). In addition, the fragile X group showed significantly larger gray matter volume in a bilateral parieto-occipital cluster and a right parieto-occipital cluster (Ps < 0.001). Conversely, the fragile X group showed significantly smaller gray matter volume in the bilateral gyrus rectus (P < 0.03). Associations between these regional brain volumes and key socio-emotional variables provide insight into gene-brain-behavior relationships underlying the fragile X syndrome phenotype in females. These findings represent the first characterization of a neuroanatomical phenotype in a large sample of girls with fragile X syndrome and expand our knowledge about potential neurodevelopmental mechanisms underlying cognitive-behavioral outcomes in this condition.

Automatic classification of autism spectrum disorder in children using cortical thickness and support vector machine

OBJECTIVE

Autism spectrum disorder (ASD) is a neurodevelopmental condition with a heterogeneous phenotype. The role of biomarkers in ASD diagnosis has been highlighted; cortical thickness has proved to be involved in the etiopathogenesis of ASD core symptoms. We apply support vector machine, a supervised machine learning method, in order to identify specific cortical thickness alterations in ASD subjects.

METHODS

A sample of 76 subjects (9.5 ± 3.4 years old) has been selected, 40 diagnosed with ASD and 36 typically developed subjects. All children underwent a magnetic resonance imaging (MRI) examination; T1-MPRAGE sequences were analyzed to extract features for the characterization and parcellation of regions of interests (ROI); average cortical thickness (CT) has been measured for each ROI. For the classification process, the extracted features were used as input for a classifier to identify ASD subjects through a "learning by example" procedure; the features with best performance was then selected by "greedy forward-feature selection." Finally, this model underwent a leave-one-out cross-validation approach.

RESULTS

From the training set of 68 ROIs, five ROIs reached accuracies of over 70%. After this phase, we used a recursive feature selection process in order to identify the eight features with the best accuracy (84.2%). CT resulted higher in ASD compared to controls in all the ROIs identified at the end of the process.

CONCLUSION

We found increased CT in various brain regions in ASD subjects, confirming their role in the pathogenesis of this condition. Considering the brain development curve during ages, these changes in CT may normalize during development. Further validation on a larger sample is required.

Neural correlates of cognitive control deficits in children with reading disorder

Reading disorder (RD) is characterized by deficient phonological processing, but children with RD also have cognitive control deficits, the neural correlates of which are not fully understood. We used fMRI to assess neural activity during the resolution of cognitive conflict on the Simon Spatial Incompatibility task and patterns of resting-state functional connectivity (RSFC) from task control (TC) regions in 7-12-year-old children with RD compared to their typically developing (TD) peers. Relative to TD children (n = 17), those with RD (n = 16) over-engaged a right superior/medial frontal cluster during the resolution of conflict (p = .05). Relative to TD children (n = 18), those with RD (n = 17) also showed reduced RSFC (voxel-wise p < .001; cluster-size p < .05, FDR corrected) from cingulo-opercular seeds to left hemisphere fronto-parietal and temporo-parietal reading-related regions, perhaps reflecting reduced organization of TC circuits and reduced integration with reading-related regions. Children with RD additionally showed reduced RSFC between fronto-parietal and default mode network regions. Follow-up analyses in a subset of children with both useable task and resting state data (RD = 13; TD = 17) revealed that greater conflict-related activation of the right frontal Simon task ROI associated with better word-reading, perhaps suggesting a compensatory role for this over-engagement. Connectivity from fronto-parietal seeds significantly associated with Simon task performance and word-reading accuracy in RD children. These findings suggest that altered functioning and connectivity of control circuits may contribute to cognitive control deficits in children with RD. Future studies should assess the utility of adding cognitive control training to reading remediation programs.

The role of monoamine oxidase enzymes in the pathophysiology of neurological disorders

Monoamine oxidase enzymes are responsible for the degredation of serotonin, dopamine, and norepinephrine in the central neurvous system. Although it has been nearly 100 years since they were first described, we are still learning about their role in the healthy brain and how they are altered in various disease states. The present review provides a survey of our current understanding of monoamine oxidases, with a focus on their contributions to neuropsychiatric, neurodevelopmental, and neurodegenerative disease. Important species differences in monoamine oxidase function and development in the brain are highlighted. Sex-specific monoamine oxidase regulatory mechanisms and their implications for various neurological disorders are also discussed. While our understanding of these critical enzymes has expanded over the last century, gaps exist in our understanding of sex and species differences and the roles monoamine oxidases may play in conditions often comorbid with neurological disorders.

Distinct patterns of repetition suppression in Fragile X syndrome, down syndrome, tuberous sclerosis complex and mutations in SYNGAP1

Sensory processing is the gateway to information processing and more complex processes such as learning. Alterations in sensory processing is a common phenotype of many genetic syndromes associated with intellectual disability (ID). It is currently unknown whether sensory processing alterations converge or diverge on brain responses between syndromes. Here, we compare for the first time four genetic conditions with ID using the same basic sensory learning paradigm. One hundred and five participants, aged between 3 and 30 years old, composing four clinical ID groups and one control group, were recruited: Fragile X syndrome (FXS; n = 14), tuberous sclerosis complex (TSC; n = 9), Down syndrome (DS; n = 19), SYNGAP1 mutations (n = 8) and Neurotypical controls (NT; n = 55)). All groups included female and male participants. Brain responses were recorded using electroencephalography (EEG) during an audio-visual task that involved three repetitions of the pronunciation of the phoneme /a/. Event Related Potentials (ERP) were used to: 1) compare peak-to-peak amplitudes between groups, 2) evaluate the presence of repetition suppression within each group and 3) compare the relative repetition suppression between groups. Our results revealed larger overall amplitudes in FXS. A repetition suppression (RS) pattern was found in the NT group, FXS and DS, suggesting spared repetition suppression in a multimodal task in these two ID syndromes. Interestingly, FXS presented a stronger RS on one peak-to-peak value in comparison with the NT. The results of our study reveal the distinctiveness of ERP and RS brain responses in ID syndromes. Further studies should be conducted to understand the molecular mechanisms involved in these patterns of responses.

White matter as a monitoring biomarker for neurodevelopmental disorder intervention studies

BACKGROUND

Early intervention is a valuable tool to support the development of toddlers with neurodevelopmental disorders. With recent research advances in early identification that allow for pre-symptomatic detection of autism in infancy, scientists are looking forward to intervention during infancy. These advances may be supported by the identification of biologically based treatment and outcome measures that are sensitive and dimensional. The purpose of this review is to evaluate white matter neurodevelopment as a monitoring biomarker for early treatment of neurodevelopmental disorders. Fragile X syndrome (FXS) and autism spectrum disorder (ASD) as used as exemplars. White matter has unique neurobiology, including a prolonged period of dynamic development. This developmental pattern may make white matter especially responsive to treatment. White matter develops aberrantly in children with ASD and FXS. Histologic studies in rodents have provided targets for FXS pharmacological intervention. However, pharmaceutical clinical trials in humans failed to garner positive clinical results. In this article, we argue that the use of neurobiological monitoring biomarkers may overcome some of these limitations, as they are objective, not susceptible to placebo effects, and are dimensional in nature.

SHORT CONCLUSION

As the field moves towards earlier detection and early intervention for neurodevelopmental disorders, we encourage scientists to consider the advantages of using neurobiological features as monitoring biomarkers.

Development of White Matter Circuitry in Infants With Fragile X Syndrome

IMPORTANCE

Fragile X syndrome (FXS) is a genetic neurodevelopmental disorder and the most common inherited cause of intellectual disability in males. However, there are no published data on brain development in children with FXS during infancy.

OBJECTIVE

To characterize the development of white matter at ages 6, 12, and 24 months in infants with FXS compared with that of typically developing controls.

DESIGN, SETTING, AND PARTICIPANTS

Longitudinal behavioral and brain imaging data were collected at 1 or more time points from 27 infants with FXS and 73 typically developing controls between August 1, 2008, and June 14, 2016, at 2 academic medical centers. Infants in the control group had no first- or second-degree relatives with intellectual or psychiatric disorders, including FXS and autism spectrum disorder.

MAIN OUTCOMES AND MEASURES

Nineteen major white matter pathways were defined in common atlas space based on anatomically informed methods. Diffusion parameters, including fractional anisotropy, were compared between groups using linear mixed effects modeling. Fiber pathways showing group differences were subsequently examined in association with direct measures of verbal and nonverbal development.

RESULTS

There were significant differences in the development of 12 of 19 fiber tracts between the 27 infants with FXS (22 boys and 5 girls) and the 73 infants in the control group (46 boys and 27 girls), with lower fractional anisotropy in bilateral subcortical-frontal, occipital-temporal, temporal-frontal, and cerebellar-thalamic pathways, as well as 4 of 6 subdivisions of the corpus callosum. For all 12 of these pathways, there were significant main effects between groups but not for the interaction of age × group, indicating that lower fractional anisotropy was present and stable from age 6 months in infants with FXS. Lower fractional anisotropy values in the uncinate fasciculi were correlated with lower nonverbal developmental quotient in the FXS group (left uncinate, F = 10.06; false discovery rate-corrected P = .03; right uncinate, F = 21.8; P = .004).

CONCLUSIONS AND RELEVANCE

The results substantiate in human infants the essential role of fragile X gene expression in the early development of white matter. The findings also suggest that the neurodevelopmental effects of FXS are well established at 6 months of age.

The journey to autism: Insights from neuroimaging studies of infants and toddlers

By definition, autism spectrum disorder (ASD) is a neurodevelopmental disorder that emerges during early childhood. It is during this time that infants and toddlers transition from appearing typical across multiple domains to exhibiting the behavioral phenotype of ASD. Neuroimaging studies focused on this period of development have provided crucial knowledge pertaining to this process, including possible mechanisms underlying pathogenesis of the disorder and offering the possibility of prodromal or presymptomatic prediction of risk. In this paper, we review findings from structural and functional brain imaging studies of ASD focused on the first years of life and discuss implications for next steps in research and clinical applications.

Longitudinal identification of clinically distinct neurophenotypes in young children with fragile X syndrome

Fragile X syndrome (FXS), due to mutations of the FMR1 gene, is the most common known inherited cause of developmental disability. The cognitive, behavioral, and neurological phenotypes observed in affected individuals can vary considerably, making it difficult to predict outcomes and determine the need for interventions. We sought to examine early structural brain growth as a potential marker for identification of clinically meaningful subgroups. Participants included 42 very young boys with FXS who completed a T1-weighted anatomical MRI and cognitive/behavioral assessment at two longitudinal time points, with mean ages of 2.89 y and 4.91 y. Topological data analysis (TDA), an unsupervised approach to multivariate pattern analysis, was applied to the longitudinal anatomical data to identify coherent but heretofore unknown subgroups. TDA revealed two large subgroups within the study population based solely on longitudinal MRI data. Post hoc comparisons of cognition, adaptive functioning, and autism severity scores between these groups demonstrated that one group was consistently higher functioning on all measures at both time points, with pronounced and significant unidirectional differences (P < 0.05 for time point 1 and/or time point 2 for each measure). These results support the existence of two longitudinally defined, neuroanatomically distinct, and clinically relevant phenotypes among boys with FXS. If confirmed by additional analyses, such information may be used to predict outcomes and guide design of targeted therapies. Furthermore, TDA of longitudinal anatomical MRI data may represent a useful method for reliably and objectively defining subtypes within other neuropsychiatric disorders.

Imaging genetics in neurodevelopmental psychopathology

Neurodevelopmental disorders are defined by highly heritable problems during development and brain growth. Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASDs), and intellectual disability (ID) are frequent neurodevelopmental disorders, with common comorbidity among them. Imaging genetics studies on the role of disease-linked genetic variants on brain structure and function have been performed to unravel the etiology of these disorders. Here, we reviewed imaging genetics literature on these disorders attempting to understand the mechanisms of individual disorders and their clinical overlap. For ADHD and ASD, we selected replicated candidate genes implicated through common genetic variants. For ID, which is mainly caused by rare variants, we included genes for relatively frequent forms of ID occurring comorbid with ADHD or ASD. We reviewed case-control studies and studies of risk variants in healthy individuals. Imaging genetics studies for ADHD were retrieved for SLC6A3/DAT1, DRD2, DRD4, NOS1, and SLC6A4/5HTT. For ASD, studies on CNTNAP2, MET, OXTR, and SLC6A4/5HTT were found. For ID, we reviewed the genes FMR1, TSC1 and TSC2, NF1, and MECP2. Alterations in brain volume, activity, and connectivity were observed. Several findings were consistent across studies, implicating, for example, SLC6A4/5HTT in brain activation and functional connectivity related to emotion regulation. However, many studies had small sample sizes, and hypothesis-based, brain region-specific studies were common. Results from available studies confirm that imaging genetics can provide insight into the link between genes, disease-related behavior, and the brain. However, the field is still in its early stages, and conclusions about shared mechanisms cannot yet be drawn.

Effects of a social stimulus on gene expression in a mouse model of fragile X syndrome

BACKGROUND

People with fragile X syndrome (FXS) often have deficits in social behavior, and a substantial portion meet criteria for autism spectrum disorder. Though the genetic cause of FXS is known to be due to the silencing of FMR1, and the Fmr1 null mouse model representing this lesion has been extensively studied, the contributions of this gene and its protein product, FMRP, to social behavior are not well understood.

METHODS

Fmr1 null mice and wildtype littermates were exposed to a social or non-social stimulus. In one experiment, subjects were assessed for expression of the inducible transcription factor c-Fos in response to the stimulus, to detect brain regions with social-specific activity. In a separate experiment, tissue was taken from those brain regions showing differential activity, and RNA sequencing was performed.

RESULTS

Immunohistochemistry revealed a significantly greater number of c-Fos-positive cells in the lateral amygdala and medial amygdala in the brains of mice exposed to a social stimulus, compared to a non-social stimulus. In the prelimbic cortex, there was no significant effect of social stimulus; although the number of c-Fos-positive cells was lower in the social condition compared to the non-social condition, and negatively correlated with c-Fos in the amygdala. RNA sequencing revealed differentially expressed genes enriched for molecules known to interact with FMRP and also for autism-related genes identified in the Simons Foundation Autism Research Initiative gene database. Ingenuity Pathway Analysis detected enrichment of differentially expressed genes in networks and pathways related to neuronal development, intracellular signaling, and inflammatory response.

CONCLUSIONS

Using the Fmr1 null mouse model of fragile X syndrome, we have identified brain regions, gene networks, and molecular pathways responsive to a social stimulus. These findings, and future experiments following up on the role of specific gene networks, may shed light on the neural mechanisms underlying dysregulated social behaviors in fragile X syndrome and more broadly.

Neural correlates of face processing in etiologically-distinct 12-month-old infants at high-risk of autism spectrum disorder

Neural correlates of face processing were examined in 12-month-olds at high-risk for autism spectrum disorder (ASD), including 21 siblings of children with ASD (ASIBs) and 15 infants with fragile X syndrome (FXS), as well as 21 low-risk (LR) controls. Event-related potentials were recorded to familiar and novel face and toy stimuli. All infants demonstrated greater N290 amplitude to faces than toys. At the Nc component, LR infants showed greater amplitude to novel stimuli than to their mother’s face and own toy, whereas infants with FXS showed the opposite pattern of responses and ASIBs did not differentiate based on familiarity. These results reflect developing face specialization across high- and low-risk infants and reveal neural patterns that distinguish between groups at high-risk for ASD.

Anomalous gray matter patterns in specific reading comprehension deficit are independent of dyslexia

Specific reading comprehension deficit (SRCD) affects up to 10 % of all children. SRCD is distinct from dyslexia (DYS) in that individuals with SRCD show poor comprehension despite adequate decoding skills. Despite its prevalence and considerable behavioral research, there is not yet a unified cognitive profile of SRCD. While its neuroanatomical basis is unknown, SRCD could be anomalous in regions subserving their commonly reported cognitive weaknesses in semantic processing or executive function. Here we investigated, for the first time, patterns of gray matter volume difference in SRCD as compared to DYS and typical developing (TD) adolescent readers (N = 41). A linear support vector machine algorithm was applied to whole brain gray matter volumes generated through voxel-based morphometry. As expected, DYS differed significantly from TD in a pattern that included features from left fusiform and supramarginal gyri (DYS vs. TD: 80.0 %, p < 0.01). SRCD was well differentiated not only from TD (92.5 %, p < 0.001) but also from DYS (88.0 %, p < 0.001). Of particular interest were findings of reduced gray matter volume in right frontal areas that were also supported by univariate analysis. These areas are thought to subserve executive processes relevant for reading, such as monitoring and manipulating mental representations. Thus, preliminary analyses suggest that SRCD readers possess a distinct neural profile compared to both TD and DYS readers and that these differences might be linked to domain-general abilities. This work provides a foundation for further investigation into variants of reading disability beyond DYS.

Moving Toward Integrative, Multidimensional Research in Modern Psychiatry: Lessons Learned From Fragile X Syndrome

The field of psychiatry is approaching a major inflection point. The basic science behind cognition, emotion, behavior, and social processes has been advancing rapidly in the past 20 years. However, clinical research supporting the classification system in psychiatry has not kept up with these scientific advances. To begin organizing the basic science of psychiatry in a comprehensive manner, we begin by selecting fragile X syndrome, a neurogenetic disease with cognitive-behavioral manifestations, to illustrate key concepts in an integrative, multidimensional model. Specifically, we describe key genetic and molecular mechanisms (e.g., gamma-aminobutyric acidergic dysfunction and metabotropic glutamate receptor 5-associated long-term depression) relevant to the pathophysiology of fragile X syndrome as well as neural correlates of cognitive-behavioral symptoms. We then describe what we have learned from fragile X syndrome that may be applicable to other psychiatric disorders. We conclude this review by discussing current and future opportunities in diagnosing and treating psychiatric diseases.

The neuroanatomy of autism spectrum disorder: An overview of structural neuroimaging findings and their translatability to the clinical setting

Autism spectrum disorder is a complex neurodevelopmental disorder, which is accompanied by differences in brain anatomy, functioning and brain connectivity. Due to its neurodevelopmental character, and the large phenotypic heterogeneity among individuals on the autism spectrum, the neurobiology of autism spectrum disorder is inherently difficult to describe. Nevertheless, significant progress has been made in characterizing the neuroanatomical underpinnings of autism spectrum disorder across the human life span, and in identifying the molecular pathways that may be affected in autism spectrum disorder. Moreover, novel methodological frameworks for analyzing neuroimaging data are emerging that make it possible to characterize the neuroanatomy of autism spectrum disorder on the case level, and to stratify individuals based on their individual phenotypic make up. While these approaches are increasingly more often employed in the research setting, their applicability in the clinical setting remains a vision for the future. The aim of the current review is to (1) provide a general overview of recent structural neuroimaging findings examining the neuroanatomy of autism spectrum disorder across the human life span, and in males and females with the condition, (2) highlight potential neuroimaging (bio)markers that may in the future be used for the stratification of autism spectrum disorder individuals into biologically homogeneous subgroups and (3) inform treatment and intervention strategies.

Female-Specific Intergenerational Transmission Patterns of the Human Corticolimbic Circuitry

Parents have large genetic and environmental influences on offspring's cognition, behavior, and brain. These intergenerational effects are observed in mood disorders, with particularly robust association in depression between mothers and daughters. No studies have thus far examined the neural bases of these intergenerational effects in humans. Corticolimbic circuitry is known to be highly relevant in a wide range of processes, including mood regulation and depression. These findings suggest that corticolimbic circuitry may also show matrilineal transmission patterns. Therefore, we examined human parent-offspring association in this neurocircuitry and investigated the degree of association in gray matter volume between parent and offspring. We used voxelwise correlation analysis in a total of 35 healthy families, consisting of parents and their biological offspring. We found positive associations of regional gray matter volume in the corticolimbic circuit, including the amygdala, hippocampus, anterior cingulate cortex, and ventromedial prefrontal cortex between biological mothers and daughters. This association was significantly greater than mother-son, father-daughter, and father-son associations. The current study suggests that the corticolimbic circuitry, which has been implicated in mood regulation, shows a matrilineal-specific transmission patterns. Our preliminary findings are consistent with what has been found behaviorally in depression and may have clinical implications for disorders known to have dysfunction in mood regulation such as depression. Studies such as ours will likely bridge animal work examining gene expression in the brains and clinical symptom-based observations and provide promising ways to investigate intergenerational transmission patterns in the human brain.

SIGNIFICANCE STATEMENT

Parents have large genetic and environmental influences on the offspring, known as intergenerational effects. Specifically, depression has been shown to exhibit strong matrilineal transmission patterns. Although intergenerational transmission patterns in the human brain are virtually unknown, this would suggest that the corticolimbic circuitry relevant to a wide range of processes including mood regulation may also show matrilineal transmission patterns. Therefore, we examined the degree of association in corticolimbic gray matter volume (GMV) between parent and offspring in 35 healthy families. We found that positive correlations in maternal corticolimbic GMV with daughters were significantly greater than other parent-offspring dyads. Our findings provide new insight into the potential neuroanatomical basis of circuit-based female-specific intergenerational transmission patterns in depression.

HPA axis function predicts development of working memory in boys with FXS

The present study examines verbal working memory over time in boys with fragile X syndrome (FXS) compared to nonverbal mental-age (NVMA) matched, typically developing (TD) boys. Concomitantly, the relationship between cortisol-a physiological marker for stress-and verbal working memory performance over time is examined to understand the role of physiological mechanisms in cognitive development in FXS. Participants were assessed between one and three times over a 2-year time frame using two verbal working memory tests that differ in complexity: memory for words and auditory working memory with salivary cortisol collected at the beginning and end of each assessment. Multilevel modeling results indicate specific deficits over time on the memory for words task in boys with FXS compared to TD controls that is exacerbated by elevated baseline cortisol. Similar increasing rates of growth over time were observed for boys with FXS and TD controls on the more complex auditory working memory task, but only boys with FXS displayed an association of increased baseline cortisol and lower performance. This study highlights the benefit of investigations of how dynamic biological and cognitive factors interact and influence cognitive development over time.

Symptoms of Autism in Males with Fragile X Syndrome: A Comparison to Nonsyndromic ASD Using Current ADI-R Scores

Symptoms of autism are frequent in males with fragile X syndrome (FXS), but it is not clear whether symptom profiles differ from those of nonsyndromic ASD. Using individual item scores from the Autism Diagnostic Inventory-Revised, we examined which current symptoms of autism differed in boys with FXS relative to same-aged boys diagnosed with nonsyndromic ASD. In addition, different subsamples of participants were matched on autism diagnostic status and severity of autism symptoms. Between-group comparisons revealed that boys with FXS showed significantly less impairment in Social Smiling than did age-, diagnostic-, and severity-matched boys with nonsyndromic ASD. Severity-matched boys with FXS showed more impairment in complex mannerisms than did boys with nonsyndromic ASD. Behavioral differences between FXS and nonsyndromic ASD may be of theoretical importance in understanding the causes and correlates of ASD in FXS and in developing and implementing appropriate treatments.

The effect of gender on the neuroanatomy of children with autism spectrum disorders: a support vector machine case-control study

Background

Genetic, hormonal, and environmental factors contribute since infancy to sexual dimorphism in regional brain structures of subjects with typical development. However, the neuroanatomical differences between male and female children with autism spectrum disorders (ASD) are an intriguing and still poorly investigated issue. This study aims to evaluate whether the brain of young children with ASD exhibits sex-related structural differences and if a correlation exists between clinical ASD features and neuroanatomical underpinnings.

Methods

A total of 152 structural MRI scans were analysed. Specifically, 76 young children with ASD (38 males and 38 females; 2–7 years of age; mean = 53 months, standard deviation = 17 months) were evaluated employing a support vector machine (SVM)-based analysis of the grey matter (GM). Group comparisons consisted of 76 age-, gender- and non-verbal-intelligence quotient-matched children with typical development or idiopathic developmental delay without autism.

Results

For both genders combined, SVM showed a significantly increased GM volume in young children with ASD with respect to control subjects, predominantly in the bilateral superior frontal gyrus (Brodmann area –BA– 10), bilateral precuneus (BA 31), bilateral superior temporal gyrus (BA 20/22), whereas less GM in patients with ASD was found in right inferior temporal gyrus (BA 37). For the within gender comparisons (i.e., females with ASD vs. controls and males with ASD vs. controls), two overlapping regions in bilateral precuneus (BA 31) and left superior frontal gyrus (BA 9/10) were detected. Sex-by-group analyses revealed in males with ASD compared to matched controls two male-specific regions of increased GM volume (left middle occipital gyrus—BA 19—and right superior temporal gyrus—BA 22). Comparisons in females with and without ASD demonstrated increased GM volumes predominantly in the bilateral frontal regions. Additional regions of significantly increased GM volume in the right anterior cingulate cortex (BA 32) and right cerebellum were typical only of females with ASD.

Conclusions

Despite the specific behavioural correlates of sex-dimorphism in ASD, brain morphology as yet remains unclear and requires future dedicated investigations. This study provides evidence of structural brain gender differences in young children with ASD that possibly contribute to the different phenotypic disease manifestations in males and females.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-015-0067-3) contains supplementary material, which is available to authorized users.

Structural-functional connectivity deficits of neocortical circuits in the Fmr1 (-/y) mouse model of autism

Fragile X syndrome (FXS), the most common inherited form of intellectual disability disorder and a frequent cause of autism spectrum disorder (ASD), is characterized by a high prevalence of sensory symptoms. Perturbations in the anatomical connectivity of neocortical circuits resulting in their functional defects have been hypothesized to contribute to the underlying etiology of these disorders. We tested this idea by probing alterations in the functional and structural connectivity of both local and long-ranging neocortical circuits in the Fmr1 (-/y) mouse model of FXS. To achieve this, we combined in vivo ultrahigh-field diffusion tensor magnetic resonance imaging (MRI), functional MRI, and viral tracing approaches in adult mice. Our results show an anatomical hyperconnectivity phenotype for the primary visual cortex (V1), but a disproportional low connectivity of V1 with other neocortical regions. These structural data are supported by defects in the structural integrity of the subcortical white matter in the anterior and posterior forebrain. These anatomical alterations might contribute to the observed functional decoupling across neocortical regions. We therefore identify FXS as a "connectopathy," providing a translational model for understanding sensory processing defects and functional decoupling of neocortical areas in FXS and ASD.

Developmental changes in cognitive and behavioural functioning of adolescents with fragile-X syndrome

BACKGROUND

Individuals with fragile-X syndrome exhibit developmental delay, hyperexcitation and social anxiety; they also show lack of attention and hyperactivity. Few studies have investigated whether levels of functioning change with increasing age. Here, we explored developmental changes across adolescence in the cognitive and behavioural profile of individuals with fragile-X syndrome. To this scope, we assessed intellectual functioning, adaptive behaviour, autistic symptomatology, behavioural problems (e.g. hyperactivity/lack of attention) and strengths (prosocial behaviours).

METHOD

Thirty-six participants underwent standardised outcome measures (i.e. the Wechsler Intelligence Scales-Revised, the Childhood Autism Rating Scale, the Vineland Adaptive Behavior Scales, and the Strengths and Difficulty Questionnaire) in three time points (Time 1: 9-11; Time 2: 11-13, and Time 3: 13-15 years).

RESULTS

Verbal IQ improved across time, whereas Nonverbal IQ declined and Full Scale IQ was quite unchanged. Autism ratings decreased; communication and social aspects of adaptive behaviour also enhanced. Finally, elevated levels of hyperactivity/lack of attention at Time 1 significantly improved across the three time points, whereas emotional symptoms, behavioural difficulties, problems with peers and prosocial behaviours remained stable over time.

CONCLUSION

These findings revealed specific developmental changes in cognitive and behavioural functioning of individuals with fragile-X syndrome, likely related to a progressive maturation of brain systems devoted to attentional control.

Emotion potentiated startle in fragile X syndrome

Social avoidance and anxiety are prevalent in fragile X syndrome (FXS) and are potentially mediated by the amygdala, a brain region critical for social behavior. Unfortunately, functional brain resonance imaging investigation of the amygdala in FXS is limited by the difficulties experienced by intellectually impaired and anxious participants. We investigated the relationship between social avoidance and emotion-potentiated startle, a probe of amygdala activation, in children and adolescents with FXS, developmental disability without FXS (DD), and typical development. Individuals with FXS or DD demonstrated significantly reduced potentiation to fearful faces than a typically developing control group (p < .05). However, among individuals with FXS, social avoidance correlated positively with fearful-face potentiation (p < .05). This suggests that general intellectual disability blunts amygdalar response, but differential amygdala responsiveness to social stimuli contributes to phenotypic variability among individuals with FXS.

Neuroimaging in autism spectrum disorder: brain structure and function across the lifespan

Over the past decade, in-vivo MRI studies have provided many invaluable insights into the neural substrates underlying autism spectrum disorder (ASD), which is now known to be associated with neurodevelopmental variations in brain anatomy, functioning, and connectivity. These systems-level features of ASD pathology seem to develop differentially across the human lifespan so that the cortical abnormalities that occur in children with ASD differ from those noted at other stages of life. Thus, investigation of the brain in ASD poses particular methodological challenges, which must be addressed to enable the comparison of results across studies. Novel analytical approaches are also being developed to facilitate the translation of findings from the research to the clinical setting. In the future, the insights provided by human neuroimaging studies could contribute to biomarker development for ASD and other neurodevelopmental disorders, and to new approaches to diagnosis and treatment.

Autism Spectrum Disorder (ASD) and Fragile X Syndrome (FXS): Two Overlapping Disorders Reviewed through Electroencephalography-What Can be Interpreted from the Available Information?

Autism Spectrum Disorder (ASD) and Fragile X syndrome (FXS) are neurodevelopmental disorders with different but potentially related neurobiological underpinnings, which exhibit significant overlap in their behavioural symptoms. FXS is a neurogenetic disorder of known cause whereas ASD is a complex genetic disorder, with both rare and common genetic risk factors and likely genetic and environmental interaction effects. A comparison of the phenotypic presentation of the two disorders may highlight those symptoms that are more likely to be under direct genetic control, for example in FXS as opposed to shared symptoms that are likely to be under the control of multiple mechanisms. This review is focused on the application and analysis of electroencephalography data (EEG) in ASD and FXS. Specifically, Event Related Potentials (ERP) and resting state studies (rEEG) studies investigating ASD and FXS cohorts are compared. This review explores the electrophysiological similarities and differences between the two disorders in addition to the potentially associated neurobiological mechanisms at play. A series of pertinent research questions which are suggested in the literature are also posed within the review.

Unusual developmental pattern of brain lateralization in young boys with autism spectrum disorder: Power analysis with child-sized magnetoencephalography

AIMS

Autism spectrum disorder (ASD) is often described as comprising an unusual brain growth pattern and aberrant brain lateralization. Although it is important to study the pathophysiology of the developing ASD cortex, examples of physiological brain lateralization in young children with ASD have yet to be well examined.

METHODS

Thirty-eight boys with ASD (aged 3-7 years) and 38 typically developing (TD) boys (aged 3-8 years) concentrated on video programs and their brain activities were measured non-invasively. We employed a customized child-sized magnetoencephalography system in which the sensors were located as close to the brain as possible for optimal recording in young children. To produce a credible laterality index of the brain oscillations, we defined two clusters of sensors corresponding to the right and left hemispheres. We focused on the laterality index ([left - right]/[left+right]) of the relative power band in seven frequency bands.

RESULTS

The TD group displayed significantly rightward lateralized brain oscillations in the theta-1 frequency bands compared to the ASD group.

CONCLUSIONS

This is the first study to demonstrate unusual brain lateralization of brain oscillations measured by magnetoencephalography in young children with ASD.

Annual research review: Rare genotypes and childhood psychopathology--uncovering diverse developmental mechanisms of ADHD risk

BACKGROUND

Through the increased availability and sophistication of genetic testing, it is now possible to identify causal diagnoses in a growing proportion of children with neurodevelopmental disorders. In addition to developmental delay and intellectual disability, many genetic disorders are associated with high risks of psychopathology, which curtail the wellbeing of affected individuals and their families. Beyond the identification of significant clinical needs, understanding the diverse pathways from rare genetic mutations to cognitive dysfunction and emotional-behavioural disturbance has theoretical and practical utility.

METHODS

We overview (based on a strategic search of the literature) the state-of-the-art on causal mechanisms leading to one of the most common childhood behavioural diagnoses - attention deficit hyperactivity disorder (ADHD) - in the context of specific genetic disorders. We focus on new insights emerging from the mapping of causal pathways from identified genetic differences to neuronal biology, brain abnormalities, cognitive processing differences and ultimately behavioural symptoms of ADHD.

FINDINGS

First, ADHD research in the context of rare genotypes highlights the complexity of multilevel mechanisms contributing to psychopathology risk. Second, comparisons between genetic disorders associated with similar psychopathology risks can elucidate convergent or distinct mechanisms at each level of analysis, which may inform therapeutic interventions and prognosis. Third, genetic disorders provide an unparalleled opportunity to observe dynamic developmental interactions between neurocognitive risk and behavioural symptoms. Fourth, variation in expression of psychopathology risk within each genetic disorder points to putative moderating and protective factors within the genome and the environment.

CONCLUSION

A common imperative emerging within psychopathology research is the need to investigate mechanistically how developmental trajectories converge or diverge between and within genotype-defined groups. Crucially, as genetic predispositions modify interaction dynamics from the outset, longitudinal research is required to understand the multi-level developmental processes that mediate symptom evolution.

Deletion of Fmr1 alters function and synaptic inputs in the auditory brainstem

Fragile X Syndrome (FXS), a neurodevelopmental disorder, is the most prevalent single-gene cause of autism spectrum disorder. Autism has been associated with impaired auditory processing, abnormalities in the auditory brainstem response (ABR), and reduced cell number and size in the auditory brainstem nuclei. FXS is characterized by elevated cortical responses to sound stimuli, with some evidence for aberrant ABRs. Here, we assessed ABRs and auditory brainstem anatomy in Fmr1^-/- mice, an animal model of FXS. We found that Fmr1^-/- mice showed elevated response thresholds to both click and tone stimuli. Amplitudes of ABR responses were reduced in Fmr1^-/- mice for early peaks of the ABR. The growth of the peak I response with sound intensity was less steep in mutants that in wild type mice. In contrast, amplitudes and response growth in peaks IV and V did not differ between these groups. We did not observe differences in peak latencies or in interpeak latencies. Cell size was reduced in Fmr1^-/- mice in the ventral cochlear nucleus (VCN) and in the medial nucleus of the trapezoid body (MNTB). We quantified levels of inhibitory and excitatory synaptic inputs in these nuclei using markers for presynaptic proteins. We measured VGAT and VGLUT immunolabeling in VCN, MNTB, and the lateral superior olive (LSO). VGAT expression in MNTB was significantly greater in the Fmr1^-/- mouse than in wild type mice. Together, these observations demonstrate that FXS affects peripheral and central aspects of hearing and alters the balance of excitation and inhibition in the auditory brainstem.

A review of feature reduction techniques in neuroimaging

Machine learning techniques are increasingly being used in making relevant predictions and inferences on individual subjects neuroimaging scan data. Previous studies have mostly focused on categorical discrimination of patients and matched healthy controls and more recently, on prediction of individual continuous variables such as clinical scores or age. However, these studies are greatly hampered by the large number of predictor variables (voxels) and low observations (subjects) also known as the curse-of-dimensionality or small-n-large-p problem. As a result, feature reduction techniques such as feature subset selection and dimensionality reduction are used to remove redundant predictor variables and experimental noise, a process which mitigates the curse-of-dimensionality and small-n-large-p effects. Feature reduction is an essential step before training a machine learning model to avoid overfitting and therefore improving model prediction accuracy and generalization ability. In this review, we discuss feature reduction techniques used with machine learning in neuroimaging studies.

The fragile X syndrome-autism comorbidity: what do we really know?

Autism spectrum disorder (ASD) is a common comorbid condition in people with fragile X syndrome (FXS). It has been assumed that ASD symptoms reflect the same underlying psychological and neurobiological impairments in both FXS and non-syndromic ASD, which has led to the claim that targeted pharmaceutical treatments that are efficacious for core symptoms of FXS are likely to be beneficial for non-syndromic ASD as well. In contrast, we present evidence from a variety of sources suggesting that there are important differences in ASD symptoms, behavioral and psychiatric correlates, and developmental trajectories between individuals with comorbid FXS and ASD and those with non-syndromic ASD. We also present evidence suggesting that social impairments may not distinguish individuals with FXS with and without ASD. Finally, we present data that demonstrate that the neurobiological substrates of the behavioral impairments, including those reflecting core ASD symptoms, are different in FXS and non-syndromic ASD. Together, these data suggest that there are clinically important differences between FXS and non-syndromic ASD that are masked by reliance on the categorical diagnosis of ASD. We argue for use of a symptom-based approach in future research, including studies designed to evaluate treatment efficacy.

Mapping genetically controlled neural circuits of social behavior and visuo-motor integration by a preliminary examination of atypical deletions with Williams syndrome

In this study of eight rare atypical deletion cases with Williams-Beuren syndrome (WS; also known as 7q11.23 deletion syndrome) consisting of three different patterns of deletions, compared to typical WS and typically developing (TD) individuals, we show preliminary evidence of dissociable genetic contributions to brain structure and human cognition. Univariate and multivariate pattern classification results of morphometric brain patterns complemented by behavior implicate a possible role for the chromosomal region that includes: 1) GTF2I/GTF2IRD1 in visuo-spatial/motor integration, intraparietal as well as overall gray matter structures, 2) the region spanning ABHD11 through RFC2 including LIMK1, in social cognition, in particular approachability, as well as orbitofrontal, amygdala and fusiform anatomy, and 3) the regions including STX1A, and/or CYLN2 in overall white matter structure. This knowledge contributes to our understanding of the role of genetics on human brain structure, cognition and pathophysiology of altered cognition in WS. The current study builds on ongoing research designed to characterize the impact of multiple genes, gene-gene interactions and changes in gene expression on the human brain.

Neurodevelopmental disorders in children born to mothers with systemic lupus erythematosus

Children born to women with systemic lupus erythematosus seem to have a potentially increased risk of neurodevelopmental disorders compared to children born to healthy women. Recent experimental data suggest in utero exposure to maternal antibodies and cytokines as important risk factors for neurodevelopmental disorders. Interestingly, women with systemic lupus erythematosus display high levels of autoantibodies and cytokines, which have been shown, in animal models, to alter fetal brain development and induce behavioral anomalies in offspring. Furthermore, subjects with systemic lupus erythematosus and neurodevelopmental disorders share a common genetic predisposition, which could impair the fetal immune response to in utero immunologic insults. Moreover, systemic lupus erythematosus pregnancies are at increased risk of adverse obstetrical outcomes and medication exposures, which have been implicated as potential risk factors for neurodevelopmental disorders. In this article, we review the current state of knowledge on neurodevelopmental disorders and their potential determinants in systemic lupus erythematosus offspring.

Typical and atypical brain development: a review of neuroimaging studies

In the course of development, the brain undergoes a remarkable process of restructuring as it adapts to the environment and becomes more efficient in processing information. A variety of brain imaging methods can be used to probe how anatomy, connectivity, and function change in the developing brain. Here we review recent discoveries regarding these brain changes in both typically developing individuals and individuals with neurodevelopmental disorders. We begin with typical development, summarizing research on changes in regional brain volume and tissue density, cortical thickness, white matter integrity, and functional connectivity. Space limits preclude the coverage of all neurodevelopmental disorders; instead, we cover a representative selection of studies examining neural correlates of autism, attention deficit/hyperactivity disorder, Fragile X, 22q11.2 deletion syndrome, Williams syndrome, Down syndrome, and Turner syndrome. Where possible, we focus on studies that identify an age by diagnosis interaction, suggesting an altered developmental trajectory. The studies we review generally cover the developmental period from infancy to early adulthood. Great progress has been made over the last 20 years in mapping how the brain matures with MR technology. With ever-improving technology, we expect this progress to accelerate, offering a deeper understanding of brain development, and more effective interventions for neurodevelopmental disorders.

Autism traits in children and adolescents with Cornelia de Lange syndrome

Cornelia de Lange syndrome (CdLS) is a cohesinopathy causing delayed growth and limb deficits. Individuals with CdLS have mild to profound intellectual disability and autistic features. This study characterizes the behavioral phenotype of children with CdLS, focusing on autistic features, maladaptive behaviors, and impact of age. Children with CdLS (5-18 years) were administered normed instruments to characterize autism features (Childhood Autism Rating Scale, CARS), maladaptive behaviors (Aberrant Behavior Checklist), and adaptive skills (Vineland Adaptive Behaviors Scales). CdLS features and severity were rated with Diagnostic Criteria for CdLS. Forty-one children with CdLS (23 females, 18 males) were classified as having "no autism" (n = 7; 17.1%), "mild autism" (n = 17; 41.4%), and "severe autism" (n = 17; 41.4%), using CARS scores. Characteristic items were abnormal emotional response, stereotypies, odd object use, rigidity, lack of verbal communication, and low intellectual functioning. Verbal communication deficits and repetitive behaviors were higher compared to sensory, social cognition, and behavior abnormalities (P ≤ 0.0001). Maladaptive behaviors associated with autism traits were stereotypies (P = 0.003), hyperactivity (P = 0.01), and lethargy (P = 0.03). Activities of daily living were significantly affected; socialization adaptive skills were a relative strength. However, with advancing age, both socialization (P < 0.0001) and communication (P = 0.001) domains declined significantly. CdLS is characterized by autistic features, notably excessive repetitive behaviors and expressive language deficits. While other adaptive skills are impacted, socialization adaptive skills are less affected. Advancing age can worsen communication and socialization deficits relative to neurotypical peers.

Topological methods reveal high and low functioning neuro-phenotypes within fragile X syndrome

Fragile X syndrome (FXS), due to mutations of the FMR1 gene, is the most common known inherited cause of developmental disability as well as the most common single-gene risk factor for autism. Our goal was to examine variation in brain structure in FXS with topological data analysis (TDA), and to assess how such variation is associated with measures of IQ and autism-related behaviors. To this end, we analyzed imaging and behavioral data from young boys (n = 52; aged 1.57-4.15 years) diagnosed with FXS. Application of topological methods to structural MRI data revealed two large subgroups within the study population. Comparison of these subgroups showed significant between-subgroup neuroanatomical differences similar to those previously reported to distinguish children with FXS from typically developing controls (e.g., enlarged caudate). In addition to neuroanatomy, the groups showed significant differences in IQ and autism severity scores. These results suggest that despite arising from a single gene mutation, FXS may encompass two biologically, and clinically separable phenotypes. In addition, these findings underscore the potential of TDA as a powerful tool in the search for biological phenotypes of neuropsychiatric disorders.

Testing for association of the monoamine oxidase A promoter polymorphism with brain structure volumes in both autism and the fragile X syndrome

BACKGROUND

Autism and the fragile X syndrome (FXS) are related to each other genetically and symptomatically. A cardinal biological feature of both disorders is abnormalities of cerebral cortical brain volumes. We have previously shown that the monoamine oxidase A (MAOA) promoter polymorphism is associated with cerebral cortical volumes in children with autism, and we now sought to determine whether the association was also present in children with FXS.

METHODS

Participants included 47 2-year-old Caucasian boys with FXS, some of whom also had autism, as well as 34 2-year-old boys with idiopathic autism analyzed in a previous study. The MAOA promoter polymorphism was genotyped and tested for relationships with gray and white matter volumes of the cerebral cortical lobes and cerebro-spinal fluid volume of the lateral ventricles.

RESULTS

MAOA genotype effects in FXS children were the same as those previously observed in idiopathic autism: the low activity MAOA promoter polymorphism allele was associated with increased gray and white matter volumes in all cerebral lobes. The effect was most pronounced in frontal lobe gray matter and all three white matter regions: frontal gray, F = 4.39, P = 0.04; frontal white, F = 5.71, P = 0.02; temporal white, F = 4.73, P = 0.04; parieto-occipital white, F = 5.00, P = 0.03. Analysis of combined FXS and idiopathic autism samples produced P values for these regions <0.01 and effect sizes of approximately 0.10.

CONCLUSIONS

The MAOA promoter polymorphism is similarly associated with brain structure volumes in both idiopathic autism and FXS. These data illuminate a number of important aspects of autism and FXS heritability: a genetic effect on a core biological trait of illness, the specificity/generalizability of the genetic effect, and the utility of examining individual genetic effects on the background of a single gene disorder such as FXS.

Neurobiological abnormalities in the first few years of life in individuals later diagnosed with autism spectrum disorder: a review of recent data

Background. Despite the widely-held understanding that the biological changes that lead to autism usually occur during prenatal life, there has been relatively little research into the functional development of the brain during early infancy in individuals later diagnosed with autism spectrum disorder (ASD). Objective. This review explores the studies over the last three years which have investigated differences in various brain regions in individuals with ASD or who later go on to receive a diagnosis of ASD. Methods. We used PRISMA guidelines and selected published articles reporting any neurological abnormalities in very early childhood in individuals with or later diagnosed with ASD. Results. Various brain regions are discussed including the amygdala, cerebellum, frontal cortex, and lateralised abnormalities of the temporal cortex during language processing. This review discusses studies investigating head circumference, electrophysiological markers, and interhemispheric synchronisation. All of the recent findings from the beginning of 2009 across these different aspects of defining neurological abnormalities are discussed in light of earlier findings. Conclusions. The studies across these different areas reveal the existence of atypicalities in the first year of life, well before ASD is reliably diagnosed. Cross-disciplinary approaches are essential to elucidate the pathophysiological sequence of events that lead to ASD.

Identifying large-scale brain networks in fragile X syndrome

IMPORTANCE

Fragile X syndrome (FXS) is an X-linked neurogenetic disorder characterized by a cognitive and behavioral phenotype resembling features of autism spectrum disorder. Until now, research has focused largely on identifying regional differences in brain structure and function between individuals with FXS and various control groups. Very little is known about the large-scale brain networks that may underlie the cognitive and behavioral symptoms of FXS.

OBJECTIVE

To identify large-scale, resting-state networks in FXS that differ from control individuals matched on age, IQ, and severity of behavioral and cognitive symptoms.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional, in vivo neuroimaging study conducted in an academic medical center. Participants (aged 10-23 years) included 17 males and females with FXS and 16 males and females serving as controls.

MAIN OUTCOMES AND MEASURES

Univariate voxel-based morphometric analyses, fractional amplitude of low-frequency fluctuations (fALFF) analysis, and group-independent component analysis with dual regression.

RESULTS

Patients with FXS showed decreased functional connectivity in the salience, precuneus, left executive control, language, and visuospatial networks compared with controls. Decreased fALFF in the bilateral insular, precuneus, and anterior cingulate cortices also was found in patients with FXS compared with control participants. Furthermore, fALFF in the left insular cortex was significantly positively correlated with IQ in patients with FXS. Decreased gray matter density, resting-state connectivity, and fALFF converged in the left insular cortex in patients with FXS.

CONCLUSIONS AND RELEVANCE

Fragile X syndrome results in widespread reductions in functional connectivity across multiple cognitive and affective brain networks. Converging structural and functional abnormalities in the left insular cortex, a region also implicated in individuals diagnosed with autism spectrum disorder, suggests that insula integrity and connectivity may be compromised in FXS. This method could prove useful in establishing an imaging biomarker for FXS.