Deep learning based joint fusion approach to exploit anatomical and functional brain information in autism spectrum disorders.

BACKGROUND: The integration of the information encoded in multiparametric MRI images can enhance the performance of machine-learning classifiers. In this study, we investigate whether the combination of structural and functional MRI might improve the performances of a deep learning (DL) model trained to discriminate subjects with Autism Spectrum Disorders (ASD) with respect to typically developing controls (TD). MATERIAL AND METHODS: We analyzed both structural and functional MRI brain scans publicly available within the ABIDE I and II data collections. We considered 1383 male subjects with age between 5 and 40 years, including 680 subjects with ASD and 703 TD from 35 different acquisition sites. We extracted morphometric and functional brain features from MRI scans with the Freesurfer and the CPAC analysis packages, respectively. Then, due to the multisite nature of the dataset, we implemented a data harmonization protocol. The ASD vs. TD classification was carried out with a multiple-input DL model, consisting in a neural network which generates a fixed-length feature representation of the data of each modality (FR-NN), and a Dense Neural Network for classification (C-NN). Specifically, we implemented a joint fusion approach to multiple source data integration. The main advantage of the latter is that the loss is propagated back to the FR-NN during the training, thus creating informative feature representations for each data modality. Then, a C-NN, with a number of layers and neurons per layer to be optimized during the model training, performs the ASD-TD discrimination. The performance was evaluated by computing the Area under the Receiver Operating Characteristic curve within a nested 10-fold cross-validation. The brain features that drive the DL classification were identified by the SHAP explainability framework. RESULTS: The AUC values of 0.66±0.05 and of 0.76±0.04 were obtained in the ASD vs. TD discrimination when only structural or functional features are considered, respectively. The joint fusion approach led to an AUC of 0.78±0.04. The set of structural and functional connectivity features identified as the most important for the two-class discrimination supports the idea that brain changes tend to occur in individuals with ASD in regions belonging to the Default Mode Network and to the Social Brain. CONCLUSIONS: Our results demonstrate that the multimodal joint fusion approach outperforms the classification results obtained with data acquired by a single MRI modality as it efficiently exploits the complementarity of structural and functional brain information.

Children with Autism Spectrum Disorder and Abnormalities of Clinical EEG: A Qualitative Review.

Over the last decade, the comorbidity between Autism Spectrum Disorder (ASD) and epilepsy has been widely demonstrated, and many hypotheses regarding the common neurobiological bases of these disorders have been put forward. A variable, but significant, prevalence of abnormalities on electroencephalogram (EEG) has been documented in non-epileptic children with ASD; therefore, several scientific studies have recently tried to demonstrate the role of these abnormalities as a possible biomarker of altered neural connectivity in ASD individuals. This narrative review intends to summarize the main findings of the recent scientific literature regarding abnormalities detected with standard EEG in children/adolescents with idiopathic ASD. Research using three different databases (PubMed, Scopus and Google Scholar) was conducted, resulting in the selection of 10 original articles. Despite an important lack of studies on preschoolers and a deep heterogeneity in results, some authors speculated on a possible association between EEG abnormalities and ASD characteristics, in particular, the severity of symptoms. Although this correlation needs to be more strongly elucidated, these findings may encourage future studies aimed at demonstrating the role of electrical brain abnormalities as an early biomarker of neural circuit alterations in ASD, highlighting the potential diagnostic, prognostic and therapeutic value of EEG in this field.

Expression of miRNAs in Pre-Schoolers with Autism Spectrum Disorders Compared with Typically Developing Peers and Its Effects after Probiotic Supplementation.

Alteration of the microbiota-gut-brain axis has been recently recognized as a possible contributor to the physiopathology of autism spectrum disorder (ASD). In this context, microRNA (miRNAs) dysfunction, implicated both in several neuropathological conditions including ASD and in different gastrointestinal disorders (GIDs), could represent an important modulating factor. In this contextual framework, we studied the transcriptional profile of specific circulating miRNAs associated with both ASD (miR-197-5p, miR-424-5p, miR-500a-5p, miR-664a-5p) and GID (miR-21-5p, miR-320a-5p, miR-31-5p, miR-223-5p) in a group of pre-schoolers with ASD and in typically developing (TD) peers. In the ASD group, we also assessed the same miRNAs after a 6-month supplementation with probiotics and their correlation with plasma levels of zonulin and lactoferrin. At baseline, the expression of miRNAs involved in ASD were significantly reduced in ASD pre-schoolers vs. TD controls. Regarding the miRNAs involved in GID, the expression levels of miR-320-5p, miR-31-5p, and miR-223-5p were significantly higher in ASD than in TD subjects, whereas miR-21-5p showed significantly reduced expression in the ASD group vs. TD group. Supplementation with probiotics did not significantly change the expression of miRNAs in the ASD population. We found a significative negative correlation between zonulin and miR-197-5p and miR-21-5p at baseline, as well as between lactoferrin and miR-223-5p after 6 months of probiotic supplementation. Our study confirms the presence of an altered profile of the miRNAs investigated in ASD versus TD peers that was not modified by supplementation with probiotics.

Sex/Gender Differences in the Language Profiles of Italian Children with Autism Spectrum Disorder: A Retrospective Study.

Sex/gender (S/G) differences in ASD language profiles have been poorly investigated. The present study aims to explore whether male (M) and female (F) children with ASD and with normal non-verbal cognitive abilities differ in their linguistic profiles. A sample of 76 Italian children with ASD (range: 4.9-8 years), including 50 Ms and 26 Fs, was retrospectively recruited. Language profiles were analyzed using standardized tests for the evaluation of receptive and expressive vocabulary as well as grammar. Grammatical comprehension was the most impaired domain compared to the other language measures in both M and F children. Comparing language profiles between S/G, Fs showed significantly better scores than Ms in grammatical production (p = 0.002), and Ms showed better active negative sentence comprehension (p = 0.035). Moreover, comparing the language profiles between Ms and Fs with a receptive disorder, Fs had significantly worse grammatical comprehension and better grammatical production than Ms. Even among children without a receptive disorder, Fs had significantly higher grammatical production scores. The S/G differences in language profile, particularly better expressive language in Fs than Ms, can partially contribute to the delayed ASD diagnosis or underdiagnosis of Fs without intellectual disability. Finally, the results document the importance of accurately investigating both expressive and receptive abilities in children with ASD.

DNA Methylation Biomarkers for Young Children with Idiopathic Autism Spectrum Disorder: A Systematic Review.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition, the underlying pathological mechanisms of which are not yet completely understood. Although several genetic and genomic alterations have been linked to ASD, for the majority of ASD patients, the cause remains unknown, and the condition likely arises due to complex interactions between low-risk genes and environmental factors. There is increasing evidence that epigenetic mechanisms that are highly sensitive to environmental factors and influence gene function without altering the DNA sequence, particularly aberrant DNA methylation, are involved in ASD pathogenesis. This systematic review aimed to update the clinical application of DNA methylation investigations in children with idiopathic ASD, investigating its potential application in clinical settings. To this end, a literature search was performed on different scientific databases using a combination of terms related to the association between peripheral DNA methylation and young children with idiopathic ASD; this search led to the identification of 18 articles. In the selected studies, DNA methylation is investigated in peripheral blood or saliva samples, at both gene-specific and genome-wide levels. The results obtained suggest that peripheral DNA methylation could represent a promising methodology in ASD biomarker research, although further studies are needed to develop DNA-methylation-based clinical applications.

A Potential Biomarker of Brain Activity in Autism Spectrum Disorders: A Pilot fNIRS Study in Female Preschoolers.

Autism spectrum disorder (ASD) refers to a neurodevelopmental condition whose detection still remains challenging in young females due to the heterogeneity of the behavioral phenotype and the capacity of camouflage. The availability of quantitative biomarkers to assess brain function may support in the assessment of ASD. Functional Near-infrared Spectroscopy (fNIRS) is a non-invasive and flexible tool that quantifies cortical hemodynamic responses (HDR) that can be easily employed to describe brain activity. Since the study of the visual phenotype is a paradigmatic model to evaluate cerebral processing in many neurodevelopmental conditions, we hypothesized that visually-evoked HDR (vHDR) might represent a potential biomarker in ASD females. We performed a case-control study comparing vHDR in a cohort of high-functioning preschooler females with ASD (fASD) and sex/age matched peers. We demonstrated the feasibility of visual fNIRS measurements in fASD, and the possibility to discriminate between fASD and typical subjects using different signal features, such as the amplitude and lateralization of vHDR. Moreover, the level of response lateralization was correlated to the severity of autistic traits. These results corroborate the cruciality of sensory symptoms in ASD, paving the way for the validation of the fNIRS analytical tool for diagnosis and treatment outcome monitoring in the ASD population.

Impact of sleep disorders on behavioral issues in preschoolers with autism spectrum disorder.

Background: Sleep disorders are one of the most common problems in children with Autism Spectrum Disorder (ASD). However, they often tend to be underdiagnosed and incorrectly treated in clinical practice. This study aims to identify sleep disorders in preschool children with ASD and to explore their relationship with the core symptoms of autism, the child's developmental and cognitive level as well as the psychiatric comorbidities. Methods: We recruited 163 preschool children with a diagnosis of ASD. The Children's Sleep Habits Questionnaire (CSHQ) assessed sleep conditions. Multiple standardized tests were used to evaluate intellectual abilities, the presence of repetitive behaviors (through the Repetitive Behavior Scale-Revised), as well as the emotional-behavioral problems and the psychiatric comorbidities (through the Child Behavior Checklist -CBCL 11/2-5). Results: The results showed that poor disorders had consistently higher scores in all areas assessed by the CSHQ and on the CBCL across all domains. The correlational analysis showed that severe sleep disorders were associated with higher scores in internalizing, externalizing, and total problems at the CBCL syndromic scales, and in all DSM-oriented CBCL subscales. Moreover, we found that the association between sleep disorders and restricted and repetitive behaviors (RRBs) is explained by the anxiety-related symptoms. Conclusion: Based on these findings, the study recommends that screening for sleep problems followed by early intervention should constitute a routine part of clinical practice for children with ASD.

Sex/gender differences in children with autism spectrum disorder: A brief overview on epidemiology, symptom profile, and neuroanatomy.

Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental conditions whose shared core features are impairments in social interaction and communication as well as restricted patterns of behavior, interests, and activities. The significant and consistent male preponderance in ASD prevalence has historically affected the scientific knowledge of autism in females as regards, inter alia, the clinical presentation, the genetic architecture, and the structural brain underpinnings. Indeed, females with ASD are under-investigated as samples recruited for clinical research typically reflect the strong male bias of the disorder. In the last years, the study of the various aspects of sex/gender (s/g) differences in ASD is gaining increased clinical and research interest resulting in a growing number of investigations on this topic. Here, I review and discuss evidence emerged from epidemiological, clinical, and neuroimaging studies in the last decade focusing on s/g differences in children with ASD. These studies are the prerequisites for the development of assessment and treatment practices which take into consideration s/g differences in ASD. Ultimately, a better understanding of s/g differences aims at improving healthcare for both ASD males and females.

A randomized controlled trial into the effects of probiotics on electroencephalography in preschoolers with autism.

LAY ABSTRACT: This study investigates the effects of a probiotic on preschoolers' brain electrical activity with autism spectrum disorder. Autism is a disorder with an increasing prevalence characterized by an enormous individual, family, and social cost. Although the etiology of autism spectrum disorder is unknown, an interaction between genetic and environmental factors is implicated, converging in altered brain synaptogenesis and, therefore, connectivity. Besides deepening the knowledge on the resting brain electrical activity that characterizes this disorder, this study allows analyzing the positive central effects of a 6-month therapy with a probiotic through a randomized, double-blind placebo-controlled study and the correlations between electroencephalography activity and biochemical and clinical parameters. In subjects treated with probiotics, we observed a decrease of power in frontopolar regions in beta and gamma bands, and increased coherence in the same bands together with a shift in frontal asymmetry, which suggests a modification toward a typical brain activity. Electroencephalography measures were significantly correlated with clinical and biochemical measures. These findings support the importance of further investigations on probiotics' benefits in autism spectrum disorder to better elucidate mechanistic links between probiotics supplementation and changes in brain activity.

High-Risk Siblings without Autism: Insights from a Clinical and Eye-Tracking Study.

Joint attention (JA)-the human ability to coordinate our attention with that of other people-is impaired in the early stage of Autism Spectrum Disorder (ASD). However, little is known about the JA skills in the younger siblings of children with ASD who do not develop ASD at 36 months of age [high-risk (HR)-noASD]. In order to advance our understanding of this topic, a prospective multicenter observational study was conducted with three groups of toddlers (age range: 18-33 months): 17 with ASD, 19 with HR-noASD and 16 with typical development (TD). All subjects underwent a comprehensive clinical assessment and an eye-tracking experiment with pre-recorded stimuli in which the visual patterns during two tasks eliciting initiating joint attention (IJA) were measured. Specifically, fixations, transitions and alternating gaze were analyzed. Clinical evaluation revealed that HR-noASD subjects had lower non-verbal cognitive skills than TD children, while similar levels of restricted and repetitive behaviors and better social communication skills were detected in comparison with ASD children. Eye-tracking paradigms indicated that HR-noASD toddlers had visual patterns resembling TD in terms of target-object-to-face gaze alternations, while their looking behaviors were similar to ASD toddlers regarding not-target-object-to-face gaze alternations. This study indicated that high-risk, unaffected siblings displayed a shared profile of IJA-eye-tracking measures with both ASD patients and TD controls, providing new insights into the characterization of social attention in this group of toddlers.

Artificial neural networks reveal sex differences in gene methylation, and connections between maternal risk factors and symptom severity in autism spectrum disorder.

Aim and methods: Artificial neural networks were used to unravel connections among blood gene methylation levels, sex, maternal risk factors and symptom severity evaluated using the Autism Diagnostic Observation Schedule 2 (ADOS-2) score in 58 children with autism spectrum disorder (ASD). Results: Methylation levels of MECP2, HTR1A and OXTR genes were connected to females, and those of EN2, BCL2 and RELN genes to males. High gestational weight gain, lack of folic acid supplements, advanced maternal age, preterm birth, low birthweight and living in rural context were the best predictors of a high ADOS-2 score. Conclusion: Artificial neural networks revealed links among ASD maternal risk factors, symptom severity, gene methylation levels and sex differences in methylation that warrant further investigation in ASD.

Vitamin D Status in Children with Autism Spectrum Disorders: Determinants and Effects of the Response to Probiotic Supplementation.

A relationship between the presence of clinical symptoms and gastrointestinal (GI) disturbances associated with nutritional deficiencies, including vitamin D (25(OH)D) deficiency, has been observed in autism spectrum disorder (ASD). The aim was to evaluate 25(OH)D levels according to the annual rhythm cycle, gender, the severity of autism, nutritional or clinical status, inflammatory and metabolic biomarkers, GI symptoms, and the clinical response to probiotic/placebo supplementation in preschooler children with ASD. Eighty-one ASD preschoolers (67 males) were assessed with standardized tools for ASD severity (ADOS score) and GI symptoms (by GI-Index at six-items and at nine-items, the latter defined as the Total GI-Index). The 25(OH)D levels were compared among different ASD subgroups according to metabolic and inflammatory biomarkers (leptin, insulin, resistin, PAI-1, MCP-1, TNF-alfa, and IL-6), gender, and the presence or absence of: (i) GI symptoms, (ii) the response to probiotic supplementation (the improvement of GI symptomatology), (iii) the response to probiotic supplementation (improvement of ASD severity). Only 25% of the ASD children presented an adequate 25(OH)D status (≥30 ng/mL according to the Endocrine Society guidelines). All the 25(OH)D levels falling in the severe deficiency range (<10 ng/mL) were observed in the male subgroup. A significant inverse correlation between 25(OH)D and leptin was observed (R = −0.24, p = 0.037). An inverse correlation was found between 25(OH)D levels and the GI Index 6-Items and Total GI-Index (R = −0.25, p = 0.026; −0.27, = 0.009) and a direct relationship with the probiotic response (R = 0.4, p = 0.05). The monitoring of 25(OH)D levels and the co-administration of 25(OH)D and probiotic supplementation could be considered in ASD from early ages.

Multi-site harmonization of MRI data uncovers machine-learning discrimination capability in barely separable populations: An example from the ABIDE dataset.

Machine Learning (ML) techniques have been widely used in Neuroimaging studies of Autism Spectrum Disorders (ASD) both to identify possible brain alterations related to this condition and to evaluate the predictive power of brain imaging modalities. The collection and public sharing of large imaging samples has favored an even greater diffusion of the use of ML-based analyses. However, multi-center data collections may suffer the batch effect, which, especially in case of Magnetic Resonance Imaging (MRI) studies, should be curated to avoid confounding effects for ML classifiers and masking biases. This is particularly important in the study of barely separable populations according to MRI data, such as subjects with ASD compared to controls with typical development (TD). Here, we show how the implementation of a harmo- nization protocol on brain structural features unlocks the case-control ML separation capability in the analysis of a multi-center MRI dataset. This effect is demonstrated on the ABIDE data collection, involving subjects encompassing a wide age range. After data harmonization, the overall ASD vs. TD discrimination capability by a Random Forest (RF) classifier improves from a very low performance (AUC = 0.58 ± 0.04) to a still low, but reasonably significant AUC = 0.67 ± 0.03. The performances of the RF classifier have been evaluated also in the age-specific subgroups of children, adolescents and adults, obtaining AUC = 0.62 ± 0.02, AUC = 0.65 ± 0.03 and AUC = 0.69 ± 0.06, respectively. Specific and consistent patterns of anatomical differences related to the ASD condition have been identified for the three different age subgroups.

Virtual Ontogeny of Cortical Growth Preceding Mental Illness.

BACKGROUND: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. METHODS: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. RESULTS: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. CONCLUSIONS: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.

Looking for "fNIRS Signature" in Autism Spectrum: A Systematic Review Starting From Preschoolers.

Accumulating evidence suggests that functional Near-Infrared Spectroscopy (fNIRS) can provide an essential bridge between our current understanding of neural circuit organization and cortical activity in the developing brain. Indeed, fNIRS allows studying brain functions through the measurement of neurovascular coupling that links neural activity to subsequent changes in cerebral blood flow and hemoglobin oxygenation levels. While the literature offers a multitude of fNIRS applications to typical development, only recently this tool has been extended to the study of neurodevelopmental disorders (NDDs). The exponential rise of scientific publications on this topic during the last years reflects the interest to identify a "fNIRS signature" as a biomarker of high translational value to support both early clinical diagnosis and treatment outcome. The purpose of this systematic review is to describe the updating clinical applications of fNIRS in NDDs, with a specific focus on preschool population. Starting from this rationale, a systematic search was conducted for relevant studies in different scientific databases (Pubmed, Scopus, and Web of Science) resulting in 13 published articles. In these studies, fNIRS was applied in individuals with Autism Spectrum Disorder (ASD) or infants at high risk of developing ASD. Both functional connectivity in resting-state conditions and task-evoked brain activation using multiple experimental paradigms were used in the selected investigations, suggesting that fNIRS might be considered a promising method for identifying early quantitative biomarkers in the autism field.

Interventions on Microbiota: Where Do We Stand on a Gut-Brain Link in Autism? A Systematic Review.

The alteration of the microbiota-gut-brain axis has been recently recognized as a critical modulator of neuropsychiatric health and a possible factor in the etiopathogenesis of autism spectrum disorders (ASD). This systematic review offers practitioners an overview of the potential therapeutic options to modify dysbiosis, GI symptoms, and ASD severity by modulating the microbiota-gut-brain axis in ASD, taking into consideration limits and benefits from current findings. Comprehensive searches of PubMed, Scopus, the Web of Science Core Collection, and EMBASE were performed from 2000 to 2021, crossing terms referred to ASD and treatments acting on the microbiota-gut-brain axis. A total of 1769 publications were identified, of which 19 articles met the inclusion criteria. Data were extracted independently by two reviewers using a preconstructed form. Despite the encouraging findings, considering the variability of the treatments, the samples size, the duration of treatment, and the tools used to evaluate the outcome of the examined trials, these results are still partial. They do not allow to establish a conclusive beneficial effect of probiotics and other interventions on the symptoms of ASD. In particular, the optimal species, subspecies, and dosages have yet to be identified. Considering the heterogeneity of ASD, double-blind, randomized, controlled trials and treatment tailored to ASD characteristics and host-microbiota are recommended.

Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium.

Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium's ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.

Correlation among maternal risk factors, gene methylation and disease severity in females with autism spectrum disorder.

Aim: To detect early-life environmental factors leading to DNA methylation changes of autism spectrum disorder (ASD)-related genes in young ASD females and reveal epigenetic biomarkers of disease severity. Materials & methods: We investigated blood methylation levels of MECP2, OXTR, BDNF, RELN, BCL2, EN2 and HTR1A genes in 42 ASD females. Results: Maternal gestational weight gain correlated with BDNF methylation levels (Bonferroni-corrected p = 0.034), and lack of folic acid supplementation at periconception resulted in higher disease severity in the ASD children (Bonferroni-corrected p = 0.048). RELN methylation levels were inversely correlated with disease severity (Bonferroni corrected p = 0.042). Conclusion: The present study revealed gene-environment interactions and potential epigenetic biomarkers of disease severity in ASD females.

Early-life maternal factors can leave marks on the DNA of the developing fetus, including changes in DNA methylation that regulate gene expression levels. These marks can pose an increased risk for several diseases, such as autism spectrum disorder (ASD) and other developmental disorders. In the present study, we searched for links between early-life maternal factors and the methylation levels of ASD-related genes in blood DNA samples of young ASD diagnosed females. We found that high maternal gestational weight gain resulted in increased methylation levels of the BDNF gene, one of the most important genes for brain development. Moreover, lack of maternal folic acid supplementation and low RELN methylation levels resulted in higher disease severity in ASD females.

Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure.

Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.