A Comparison of Structural Brain Imaging Findings in Autism Spectrum Disorder and Attention-Deficit Hyperactivity Disorder

Current Status and Future Directions in the Development of Digital Therapeutic Interventions for Neurodevelopmental Disorders

Innovations in digital technologies have emerged digital therapeutics (DTx) as a novel therapeutic intervention. DTx hold potential as novel theragnostics for disorders with broad diagnostic spectra, including neurodevelopmental diseases (NDDs). In this review, we highlight challenging factors in the successful development and deployment of DTx for NDDs with respect to patients, medical professionals, and manufacturers. We also discuss the implications of these factors and future directions for revitalizing DTx development for NDDs.

Understanding heterogeneity in psychiatric disorders: A method for identifying subtypes and parsing comorbidity

AIM

Most psychiatric and neurodevelopmental disorders are heterogeneous. Neural abnormalities in patients might differ in magnitude and kind, giving rise to distinct subtypes that can be partly overlapping (comorbidity). Identifying disorder-related individual differences is challenging due to the overwhelming presence of disorder-unrelated variation shared with healthy controls. Recently, Contrastive Variational Autoencoders (CVAEs) have been shown to separate disorder-related individual variation from disorder-unrelated variation. However, it is not known if CVAEs can also satisfy the other key desiderata for psychiatric research: capturing disease subtypes and disentangling comorbidity. In this paper, we compare CVAEs to other methods as a function of hyperparameters, such as model size and training data availability. We also introduce a new architecture for modeling comorbid disorders and test a novel training procedure for CVAEs that improves their reproducibility.

METHODS

We use synthetic neuroanatomical MRI data with known ground truth for shared and disorder-specific effects and study the performance of the CVAE and non-contrastive baseline models at detecting disorder-subtypes and disentangling comorbidity in brain images varying along shared and disorder-specific dimensions.

RESULTS

CVAE models consistently outperformed non-contrastive alternatives as measured by correlation with disorder-specific ground truth effects and accuracy of subtype discovery. The CVAE also successfully disentangled neuroanatomical loci of comorbid disorders, due to its novel architecture. Improved training procedure reduced variability in the results by up to 5.5×.

CONCLUSION

The results showcase how the CVAE can be used as an overall framework in precision psychiatry studies, enabling reliable detection of interpretable neuromarkers, discovering disorder subtypes and disentangling comorbidity.

Unraveling the causal pathways of maternal smoking and breastfeeding in the development of neuropsychiatric disorders: A Mendelian randomization perspective

BACKGROUND

Maternal smoking around birth (MSAB) and early-life breastfeeding (BAB) represent critical factors that may exert enduring effects on neuropsychiatric health. Although previous research has examined these exposures separately, the combined impact of both on disorders such as ADHD, ASD, BD, MDD, ANX, and SCZ remains unclear. This study aims to evaluate the causal relationships between MSAB and BAB and the risk of developing these neuropsychiatric disorders through Mendelian randomization (MR) analysis.

METHODS

A two-sample MR analysis was conducted to investigate the potential causal effects of MSAB and BAB on a range of neuropsychiatric disorders. Genetic variants associated with MSAB and BAB were obtained from genome-wide association studies (GWAS), while summary data for neuropsychiatric disorders were gathered from large GWAS consortia. The primary MR analysis was conducted using the inverse-variance weighted (IVW) method, with additional sensitivity analyses performed to confirm the robustness of the findings. A False Discovery Rate (FDR) correction was applied to control for the issue of multiple comparisons and reduce the risk of Type I errors.

RESULTS

The IVW analysis indicated that there were significant associations between MSAB and an increased risk of the following conditions: The IVW analysis indicated significant associations between MSAB and an increased risk of ADHD (odds ratio [OR] = 5.36, 95 % confidence interval [CI] = 2.58-7.63, p-value for false discovery rate [PFDR] = 0.004) and major depressive disorder (MDD) (OR = 1.92, 95 % CI = 1.29-2.88, PFDR = 0. Furthermore, significant associations were observed between MSAB and an increased risk of bipolar disorder (BD) (OR = 6.33, 95 % CI = 1.56-8.73, PFDR = 0.020), anxiety disorders (ANX) (OR = 1.03, 95 % CI = 1.00-1.05, PFDR = 0.039), and attention deficit hyperactivity disorder (ADHD) (OR = 5.36, 95 % CI = 2.58-7.63, PFDR = 0.004). No significant associations were identified between MSAB and Autism Spectrum Disorder (ASD) or Schizophrenia (SCZ). In contrast, the results indicated that BAB was associated with a protective effect against ADHD (OR = 0.17, 95 % CI = 0.04-0.63, PFDR = 0.025), MDD (OR = 0.26, 95 % CI = 0.12-0.58, PFDR = 0.006), and ANX (OR = 0.96, 95 % CI = 0.49-0.99, PFDR = 0.030). No significant effects of BAB were observed for ASD, BD, or SCZ.

CONCLUSIONS

This study shows that maternal smoking around the time of birth increases the risk of attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), bipolar disorder (BD), and anxiety disorders (ANX). In contrast, breastfeeding during infancy offers protective benefits against ADHD, MDD, and ANX. These findings underscore the vital importance of maternal health behaviours during the perinatal and infant feeding periods. They also highlight the need for targeted public health interventions aimed at reducing the risk of neuropsychiatric disorders.

Brain-Charting Autism and Attention-Deficit/Hyperactivity Disorder Reveals Distinct and Overlapping Neurobiology

BACKGROUND

Autism and attention-deficit/hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology that is still poorly understood. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together and sex differences are often overlooked. Population modeling, often referred to as normative modeling, provides a unified framework for studying age-specific and sex-specific divergences in brain development.

METHODS

Here, we used population modeling and a large, multisite neuroimaging dataset (N = 4255 after quality control) to characterize cortical anatomy associated with autism and ADHD, benchmarked against models of average brain development based on a sample of more than 75,000 individuals. We also examined sex and age differences and relationship with autistic traits and explored the co-occurrence of autism and ADHD.

RESULTS

We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume that was localized to the superior temporal cortex, whereas individuals with ADHD showed more global increases in cortical thickness but lower cortical volume and surface area across much of the cortex. The co-occurring autism+ADHD group showed a unique pattern of widespread increases in cortical thickness and certain decreases in surface area. We also found that sex modulated the neuroanatomy of autism but not ADHD, and there was an age-by-diagnosis interaction for ADHD only.

CONCLUSIONS

These results indicate distinct cortical differences in autism and ADHD that are differentially affected by age and sex as well as potentially unique patterns related to their co-occurrence.

Towards system redesign: An exploratory analysis of neurodivergent traits in a childhood population referred for autism assessment

BACKGROUND

Children's health services in many countries are moving from single condition diagnostic silo assessments to considering neurodevelopment in a more holistic sense. There has been increasing recognition of the importance of clinical overlap and co-occurrence of different neurotypes when assessing neurodivergent children. Using a cross-sectional service evaluation design, we investigated the overlap of neurodivergences in a cohort of children referred for autism assessment, focusing on motor, learning, and attention/activity level domains. We aimed to determine what proportion of children in a cohort referred for an autism assessment showed traits of additional neurodivergences, and what proportion were further investigated.

METHODS

We evaluated anonymised medical records of children aged between two and 17 years referred for autism assessment. We used validated questionnaires to assess for neurodivergent traits. A weighted scoring system was developed to determine traits in each neurodevelopmental domain and a score above the median was considered to indicate a neurodivergent trait. Evidence of further investigations were recorded. We then examined the relationships between autism traits and traits of additional neurodivergence.

RESULTS

114 participants were included for evaluation. 62.3% (n = 71) had completed questionnaires for analysis. Of these, 71.8% (n = 51) scored greater than the median for at least one additional neurotype, indicating the presence of other neurodivergent traits, and 88.7% (n = 64) attracted a diagnosis of autism. Only 26.3% of children with evidence of additional neurotypes were further investigated beyond their autism assessment.

CONCLUSIONS

Our results demonstrate the extensive overlap between additional neurodivergent traits in a population of children referred with suspected autism and show that only a small proportion were further investigated. The use of standardised questionnaires to uncover additional neurodivergences may have utility in improving the holistic nature of neurodevelopmental assessments.

Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology

Background

Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Normative modelling provides a unified framework for studying age-specific and sex-specific divergences in neurodivergent brain development.

Methods

Here we use normative modelling and a large, multi-site neuroimaging dataset to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of typical brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD).

Results

We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume localised to the superior temporal cortex, whereas individuals with ADHD showed more global effects of cortical thickness increases but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only.

Conclusions

These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.

The neuroanatomical substrates of autism and ADHD and their link to putative genomic underpinnings

BACKGROUND

Autism spectrum disorders (ASD) are neurodevelopmental conditions accompanied by differences in brain development. Neuroanatomical differences in autism are variable across individuals and likely underpin distinct clinical phenotypes. To parse heterogeneity, it is essential to establish how the neurobiology of ASD is modulated by differences associated with co-occurring conditions, such as attention-deficit/hyperactivity disorder (ADHD). This study aimed to (1) investigate between-group differences in autistic individuals with and without co-occurring ADHD, and to (2) link these variances to putative genomic underpinnings.

METHODS

We examined differences in cortical thickness (CT) and surface area (SA) and their genomic associations in a sample of 533 individuals from the Longitudinal European Autism Project. Using a general linear model including main effects of autism and ADHD, and an ASD-by-ADHD interaction, we examined to which degree ADHD modulates the autism-related neuroanatomy. Further, leveraging the spatial gene expression data of the Allen Human Brain Atlas, we identified genes whose spatial expression patterns resemble our neuroimaging findings.

RESULTS

In addition to significant main effects for ASD and ADHD in fronto-temporal, limbic, and occipital regions, we observed a significant ASD-by-ADHD interaction in the left precentral gyrus and the right frontal gyrus for measures of CT and SA, respectively. Moreover, individuals with ASD + ADHD differed in CT to those without. Both main effects and the interaction were enriched for ASD-but not for ADHD-related genes.

LIMITATIONS

Although we employed a multicenter design to overcome single-site recruitment limitations, our sample size of N = 25 individuals in the ADHD only group is relatively small compared to the other subgroups, which limits the generalizability of the results. Also, we assigned subjects into ADHD positive groupings according to the DSM-5 rating scale. While this is sufficient for obtaining a research diagnosis of ADHD, our approach did not take into account for how long the symptoms have been present, which is typically considered when assessing ADHD in the clinical setting.

CONCLUSION

Thus, our findings suggest that the neuroanatomy of ASD is significantly modulated by ADHD, and that autistic individuals with co-occurring ADHD may have specific neuroanatomical underpinnings potentially mediated by atypical gene expression.

EEG Correlates of Cognitive Functions in a Child with ASD and White Matter Signal Abnormalities: A Case Report with Two-and-a-Half-Year Follow-Up

This research aimed to examine the EEG correlates of different stimuli processing instances in a child with ASD and white matter signal abnormalities and to investigate their relationship to the results of behavioral tests. The prospective case study reports two and a half years of follow-up data from a child aged 38 to 66 months. Cognitive, speech-language, sensory, and EEG correlates of auditory-verbal and auditory-visual-verbal information processing were recorded during five test periods, and their mutual interrelation was analyzed. EEG findings revealed no functional theta frequency range redistribution in the frontal regions favoring the left hemisphere during speech processing. The results pointed to a positive linear trend in the relative theta frequency range and a negative linear trend in the relative alpha frequency range when listening to and watching the cartoon. There was a statistically significant correlation between EEG signals and behavioral test results. Based on the obtained results, it may be concluded that EEG signals and their association with the results of behavioral tests should be evaluated with certain restraints considering the characteristics of the stimuli during EEG recording.

Fronto-parietal white matter microstructure associated with working memory performance in children with ADHD

INTRODUCTION

Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder with many functional impairments thought to be underpinned by difficulties in executive function domains such as working memory. The superior longitudinal fasciculus (SLF) plays an integral role in the development of working memory in neurotypical children. Neuroimaging research suggests reduced white matter organization of the SLF may contribute to working memory difficulties commonly seen in ADHD. This study aimed to examine the relationship between white matter organization of the SLF and working memory in children with ADHD.

METHODS

We examined the association of tract volume and apparent fibre density (AFD) of the SLF with working memory in children with ADHD (n = 64) and controls (n = 58) aged 9-11years. Children completed a computerized spatial n-back task and underwent diffusion magnetic resonance imaging (dMRI). Constrained spherical deconvolution-based tractography was used to construct the three branches of the SLF bilaterally and examine volume and AFD of the SLF.

RESULTS

Regression analyses revealed children with ADHD exhibited poorer working memory, and lower volume and AFD of the left SLF-II compared to healthy controls. There was also an association between reaction time and variability (RT and RT-V) and the left SLF-II. Further analyses revealed volume of the left SLF-II mediated the relationship between ADHD and working memory performance (RT and RT-V).

DISCUSSION

These findings add to the current body of ADHD literature, revealing the potential role of frontoparietal white matter in working memory difficulties in ADHD.

Neurite orientation dispersion and density imaging of white matter microstructure in sensory processing dysfunction with versus without comorbid ADHD

Introduction

Sensory Processing Dysfunction (SPD) is common yet understudied, affecting up to one in six children with 40% experiencing co-occurring challenges with attention. The neural architecture of SPD with Attention Deficit and Hyperactivity Disorder (ADHD) (SPD+ADHD) versus SPD without ADHD (SPD-ADHD) has yet to be explored in diffusion tensor imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI) has yet to be examined.

Methods

The present study computed DTI and NODDI biophysical model parameter maps of one hundred children with SPD. Global, regional and voxel-level white matter tract measures were analyzed and compared between SPD+ADHD and SPD-ADHD groups.

Results

SPD+ADHD children had global WM Fractional Anisotropy (FA) and Neurite Density Index (NDI) that trended lower than SPD-ADHD children, primarily in boys only. Data-driven voxelwise and WM tract-based analysis revealed statistically significant decreases of NDI in boys with SPD+ADHD compared to those with SPD-ADHD, primarily in projection tracts of the internal capsule and commissural fibers of the splenium of the corpus callosum.

Conclusion

We conclude that WM microstructure is more delayed/disrupted in boys with SPD+ADHD compared to SPD-ADHD, with NODDI showing a larger effect than DTI. This may represent the combined WM pathology of SPD and ADHD, or it may result from a greater degree of SPD WM pathology causing the development of ADHD.

The shared white matter developmental trajectory anomalies of attention-deficit/hyperactivity disorder and autism spectrum disorders: A meta-analysis of diffusion tensor imaging studies

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) show common brain area abnormalities, which may contribute to the high shared co-occurrence symptoms and comorbidity of the two disorders. However, neuroanatomic anomalies in neurodevelopmental disorders may change over the course of development, and the developmental variation of these two disorders is unclear. Our study conducted a systematic literature search of PubMed, Web of Science, and EMBASE databases to identify disorder-shared abnormalities of white matter (WM) from childhood to adulthood in ADHD and ASD. 28 ADHD and 23 ASD datasets were included in this meta-analysis and were analysed by AES-SDM to detect differences in fractional anisotropy in patients compared to typically developing individuals. Our main findings reveal the variable WM developmental trajectories in ADHD and ASD respectively, and the two disorders showed overlapping corpus callosum tract abnormalities in their development from children to adults. Furthermore, the overlapping abnormalities of the corpus callosum tract increased with age, which may be related to their gradually increasing shared symptoms and comorbidity in these two disorders.

Accurate corresponding fiber tract segmentation via FiberGeoMap learner with application to autism

Fiber tract segmentation is a prerequisite for tract-based statistical analysis. Brain fiber streamlines obtained by diffusion magnetic resonance imaging and tractography technology are usually difficult to be leveraged directly, thus need to be segmented into fiber tracts. Previous research mainly consists of two steps: defining and computing the similarity features of fiber streamlines, then adopting machine learning algorithms for fiber clustering or classification. Defining the similarity feature is the basic premise and determines its potential reliability and application. In this study, we adopt geometric features for fiber tract segmentation and develop a novel descriptor (FiberGeoMap) for the corresponding representation, which can effectively depict fiber streamlines' shapes and positions. FiberGeoMap can differentiate fiber tracts within the same subject, meanwhile preserving the shape and position consistency across subjects, thus can identify common fiber tracts across brains. We also proposed a Transformer-based encoder network called FiberGeoMap Learner, to perform segmentation based on the geometric features. Experimental results showed that the proposed method can differentiate the 103 various fiber tracts, which outperformed the existing methods in both the number of categories and segmentation accuracy. Furthermore, the proposed method identified some fiber tracts that were statistically different on fractional anisotropy (FA), mean diffusion (MD), and fiber number ration in autism.

A fatal alliance: Glial connexins, myelin pathology and mental disorders

Mature oligodendrocytes are myelin forming glial cells which are responsible for myelination of neuronal axons in the white matter of the central nervous system. Myelin pathology is a major feature of severe neurological disorders. Oligodendrocyte-specific gene mutations and/or white matter alterations have also been addressed in a variety of mental disorders. Breakdown of myelin integrity and demyelination is associated with severe symptoms, including impairments in motor coordination, breathing, dysarthria, perception (vision and hearing), and cognition. Furthermore, there is evidence indicating that myelin sheath defects and white matter pathology contributes to the affective and cognitive symptoms of patients with mental disorders. Oligodendrocytes express the connexins GJC2; mCx47 [human (GJC2) and mouse (mCx47) connexin gene nomenclature according to Söhl and Willecke (2003)], GJB1; mCx32, and GJD1; mCx29 in both white and gray matter. Preclinical findings indicate that alterations in connexin expression in oligodendrocytes and astrocytes can induce myelin defects. GJC2; mCx47 is expressed at early embryonic stages in oligodendrocyte precursors cells which precedes central nervous system myelination. In adult humans and animals GJC2, respectively mCx47 expression is essential for oligodendrocyte function and ensures adequate myelination as well as myelin maintenance in the central nervous system. In the past decade, evidence has accumulated suggesting that mental disorders can be accompanied by changes in connexin expression, myelin sheath defects and corresponding white matter alterations. This dual pathology could compromise inter-neuronal information transfer, processing and communication and eventually contribute to behavioral, sensory-motor, affective and cognitive symptoms in patients with mental disorders. The induction of myelin repair and remyelination in the central nervous system of patients with mental disorders could help to restore normal neuronal information propagation and ameliorate behavioral and cognitive symptoms in individuals with mental disorders.

Distinct and shared white matter abnormalities when ADHD is comorbid with ASD: A preliminary diffusion tensor imaging study

Attention deficit/hyperactivity disorder (ADHD), a common neurodevelopmental disorder, is the most frequent comorbid condition seen in children with autism spectrum disorder (ASD). This high comorbidity between ADHD and ASD worsens symptom manifestations and complicates disease treatment and prognosis. It remains unclear whether individuals suffering with both ADHD and ASD, compared to individuals with ADHD only, share overlapping neural correlates associated with ADHD neuropathology, or exhibit a distinct neuropathological profile. Answering this question is critical to the understanding of treatment outcomes for the challenging comorbid ADHD symptoms. To identify the shared and the differentiated neural correlates of the comorbidity mechanisms of ADHD with ASD, we use diffusion tensor imaging (DTI) to characterize white-matter microstructure integrity in youth diagnosed with ADHD+ASD and youth with ADHD-only (excluding both the diagnosis and symptoms of ASD) compared with a healthy control group. Results show that the ADHD-only cohort exhibits impaired microstructural integrity (lower fractional anisotropy, FA) in the callosal-cingulum (CC-CG) tracts compared to the control cohort. The ADHD+ASD comorbid cohort shows impaired FA in an overlapping region within the CC-CG tracts and, additionally, shows impaired FA in the frontolimbic tracts including the uncinate fasciculus and anterior thalamic radiation. Across all participants, FA in the CC-CG showed a significantly negative relationship with the degree of ADHD symptom severity. Findings of this study suggest a specific role of CC-CG underlying ADHD neuropathology and symptom manifestations, and when comorbid with ASD a shared ADHD profile with a shift toward an anterior-brain, frontal impact. Results of this study may facilitate future targeted therapeutics and assist in diagnostic precision for individuals suffering with differing levels of comorbid ADHD with ASD, and ultimately contribute to improve prognostication and outcomes for these two highly prevalent and comorbid neurodevelopmental disorders.

Neurodevelopmental toxicity induced by airborne particulate matter

Airborne particulate matter (PM), the primary component associated with health risks in air pollution, can negatively impact human health. Studies have shown that PM can enter the brain by inhalation, but data on the exact quantity of particles that reach the brain are unknown. Particulate matter exposure can result in neurotoxicity. Exposure to PM poses a greater health risk to infants and children because their nervous systems are not fully developed. This review paper highlights the association between PM and neurodevelopmental toxicity (NDT). Exposure to PM can induce oxidative stress and inflammation, potentially resulting in blood-brain barrier damage and increased susceptibility to development of neurodevelopmental disorders (NDD), such as autism spectrum disorders and attention deficit disorders. In addition, human and animal exposure to PM can induce microglia activation and epigenetic alterations and alter the neurotransmitter levels, which may increase risks for development of NDD. However, the systematic comparisons of the effects of PM on NDD at different ages of exposure are deficient. The elucidation of PM exposure risks and NDT in children during the early developmental stages are of great importance. The synthesis of current research may help to identify markers and mechanisms of PM-induced neurodevelopmental toxicity, allowing for the development of strategies to prevent permanent damage of developing brain.

The long-range white matter microstructural alterations in drug-naive children with ADHD: A tract-based spatial statistics study

BACKGROUND

To investigate WM alterations, particularly the changes in long-range fibers, in drug-naive children with attention deficit hyperactivity disorder (ADHD), we conducted tract-based spatial statistics (TBSS) analysis on diffusion tensor imaging (DTI) data.

MATERIALS AND METHODS

In this study, 57 children with ADHD and 41 healthy controls (HCs) were enrolled. None of the enrolled ADHD children received any medication before data collection. WM changes were then correlated with clinical symptoms, including the hyperactivity index score and the impulsivity score.

RESULTS

ADHD children demonstrated decreased FA in the right forceps major, left inferior fronto-occipital fasciculus, and left genu Internal capsule. Moreover, higher RD was observed in the right forceps major, superior longitudinal fasciculus, and forceps major. The results of linear regression analysis including learning problem score, hyperactivity index score and impulsivity score showed that higher earning problem and hyperactivity/impulsivity symptom scores were negatively correlated with the mean FA value in the right forceps major, left IFOF and left genu Internal capsule.

CONCLUSION

Our results demonstrate that microstructural WM alterations and changes in the long-range WM connections are present in children with ADHD. We speculate that these changes may relate to the symptoms of hyperactivity and impulsivity.

Impact of brain overgrowth on sensorial learning processing during the first year of life

Macrocephaly is present in about 2–5% of the general population. It can be found as an isolated benign trait or as part of a syndromic condition. Brain overgrowth has been associated with neurodevelopmental disorders such as autism during the first year of life, however, evidence remains inconclusive. Furthermore, most of the studies have involved pathological or high-risk populations, but little is known about the effects of brain overgrowth on neurodevelopment in otherwise neurotypical infants. We investigated the impact of brain overgrowth on basic perceptual learning processes (repetition effects and change detection response) during the first year of life. We recorded high density electroencephalograms (EEG) in 116 full-term healthy infants aged between 3 and 11 months, 35 macrocephalic (14 girls) and 81 normocephalic (39 girls) classified according to the WHO head circumference norms. We used an adapted oddball paradigm, time-frequency analyses, and auditory event-related brain potentials (ERPs) to investigate differences between groups. We show that brain overgrowth has a significant impact on repetition effects and change detection response in the 10–20 Hz frequency band, and in N450 latency, suggesting that these correlates of sensorial learning processes are sensitive to brain overgrowth during the first year of life.

Deficits in attention, motor control and perception childhood to age 30 years: prospective case-control study of outcome predictors

OBJECTIVE

Investigate predictors of adverse outcome in children with and without attention-deficit/hyperactivity disorder (ADHD) combined with developmental coordination disorder (DCD) at 6 years of age.

DESIGN

Prospective population-based cohort study.

SETTING

Western Sweden.

PARTICIPANTS

From a screening-based population cohort of 589 individuals, 62 (11 female) diagnosed with ADHD+DCD at mean age 6.6 years, and a comparison group of 51 population-matched (10 female) children were followed prospectively.

OUTCOME MEASURES

Drawn from a clinical reassessment at age 9 years of 110 of the 113 individuals, neuropsychiatric symptoms, continuous performance test results and measures of motor function were used as predictors of outcome in linear regression models. Participants were followed in national registers up to 30-31 years of age for outcomes in adulthood. Predictors were regressed onto an adverse outcome score (range 0-7) comprising seven binary endpoints, and when applicable onto each continuous outcome separately (low educational attainment, low occupation level, psychiatric disorder, psychotropic medication prescription, sick pension, high dependence on social benefits and criminal conviction).

RESULTS

Of the 110 individuals, 3 had died. In univariable regression onto the adverse outcome score, the strongest predictors at age 9 years were symptoms of conduct disorder, oppositional defiant disorder, ADHD and motor dysfunction, with an R² around 25%, followed by autistic traits (R²=15%) and depressive symptoms (R²=8%). Combining these six strongest predictors in a multivariable model yielded an adjusted R²=38%. Subgroup analyses were similar, except for a strong association of autistic traits with the adverse outcome score in females (n=20, R²=50%).

CONCLUSION

Several neurodevelopmental symptoms, including ADHD severity at age 9 years, accounted for a considerable amount of the variance in terms of adulthood adverse outcome. Broad neurodevelopmental profiling irrespective of diagnostic thresholds should inform research and clinical practice. The study highlights the importance of considering associated comorbidities and problems in ADHD.

Identify aberrant white matter microstructure in ASD, ADHD and other neurodevelopmental disorders: A meta-analysis of diffusion tensor imaging studies

BACKGROUND

Neurodevelopmental disorders (NDDs) usually present overlapping symptoms. Abnormal white matter (WM) microstructure has been found in these disorders. Identification of common and unique neural abnormalities across NDDs could provide further insight into the underlying pathophysiological mechanisms.

METHODS

We performed a voxel-based meta-analysis of whole-brain diffusion tensor imaging (DTI) studies in autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) and other NDDs. A systematic literature search was conducted through March 2020 to identify studies that compared measures of WM microstructure between patients with NDDs and neurotypical controls. Peak voxel coordinates were meta-analyzed via anisotropic effect size-signed differential mapping (AES-SDM) as well as activation likelihood estimation (ALE).

RESULTS

Our final sample included a total of 4137 subjects from 66 studies across five NDDs. Fractional anisotropy (FA) reductions were found in the splenium of the CC in ADHD, and the genu and splenium of CC in ASD. And mean diffusivity (MD) increases were shown in posterior thalamic radiation in ASD. No consistent abnormalities were detected in specific learning disorder, motor disorder or communication disorder. Significant differences between child/adolescent and adult patients were found within the CC across NDDs, reflective of aberrant neurodevelopmental processes in NDDs.

CONCLUSIONS

The current study demonstrated atypical WM patterns in ASD, ADHD and other NDDs. Microstructural abnormalities in the splenium of the CC were possibly shared among ASD and ADHD.

Transdiagnostic symptom subtypes across autism spectrum disorders and attention deficit hyperactivity disorder: validated by measures of neurocognition and structural connectivity

BACKGROUNDS

Autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are neurodevelopmental disorders that exhibit within-disorder heterogeneity and cross-disorder phenotypic overlap, thus suggesting that the current disease categories may not fully represent the etiologic essence of the disorders, especially for highly comorbid neurodevelopmental disorders. In this study, we explored the subtypes of a combined sample of ASD and ADHD by integrating measurements of behavior, cognition and brain imaging.

METHODS

A total of 164 participants, including 65 with ASD, 47 with ADHD, and 52 controls, were recruited. Unsupervised machine learning with an agglomerative hierarchical clustering algorithm was used to identify transdiagnostic symptom clusters. Neurocognition and brain structural connectivity measurements were used to assess symptom clusters. Mediation analysis was used to explore the relationship between transdiagnostic symptoms, neurocognition and brain structural connectivity.

RESULTS

We identified three symptom clusters that did not fall within the diagnostic boundaries of DSM. External measurements from neurocognition and neuroimaging domains supported distinct profiles, including fine motor function, verbal fluency, and structural connectivity in the corpus callosum between these symptom clusters, highlighting possible biomarkers for ASD and ADHD. Additionally, fine motor function was shown to mediate the relationship between the corpus callosum and perseveration symptoms.

CONCLUSIONS

In this transdiagnostic study on ASD and ADHD, we identified three subtypes showing meaningful associations between symptoms, neurocognition and brain white matter structural connectivity. The fine motor function and structural connectivity of corpus callosum might be used as biomarkers for neurodevelopmental disorders with social skill symptoms. The results of this study highlighted the importance of precise phenotyping and further supported the effects of fine motor intervention on ASD and ADHD.

Affective Empathy, Theory of Mind and Social Functioning in Patients With Focal Epilepsy

OBJECTIVE

Social cognition comprises basic and more complex functions, such as theory of mind (ToM) and affective empathy. Although everyday social interactions may be impaired if such higher-order social cognitive functions are compromised, associations between social functioning and social cognition in people with focal epilepsy (PWFE) are still poorly understood. We used a novel, naturalistic approach to investigate ToM in PWFE by applying the Movie for the Assessment of Social Cognition (MASC). Furthermore, we studied affective empathy, the relationship between social cognitive parameters and measures of social functioning, as well as between epilepsy focus and ToM.

METHODS

Thirty patients with either temporal (TLE) or frontal lobe epilepsy (FLE) were compared to 29 healthy control subjects (HC). In addition to the MASC, we applied questionnaire measures assessing empathy and everyday social functioning.

RESULTS

PWFE, especially with FLE, performed significantly worse than HC on the MASC. Perceived social integration and social activities, but not affective empathy, were reduced in PWFE. Regression analyses revealed associations between perceived social integration, clinical group status, affective empathy and ToM.

CONCLUSION

PWFE displayed ToM deficits during a naturalistic task, whereas affective empathy was unimpaired. FLE may be associated with especially compromised ToM performance. Social cognition and social functioning appear to be interrelated in PWFE, whose self-perceived levels of social integration and social activities are lower than those of HC. More research into the association between social cognition and social functioning in PWFE is needed, in order to develop tailored intervention programs for these patients.

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.

Whole Brain White Matter Tract Deviation and Idiosyncrasy From Normative Development in Autism and ADHD and Unaffected Siblings Link With Dimensions of Psychopathology and Cognition

OBJECTIVE

The heterogeneity of autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) preclude definitive identification of neurobiomarkers and biological risks. High clinical overlap suggests multifaceted circuit-level alterations across diagnoses, which remains elusive. This study investigated whether individuals with ADHD or ASD and their unaffected siblings constitute a spectrum of neurodevelopmental conditions in terms of white matter etiology.

METHODS

Sex-specific white matter tract normative development was modeled from diffusion MRI of 626 typically developing control subjects (ages 5-40 years; 376 of them male). Individualized metrics estimating white matter tract deviation from the age norm were derived for 279 probands with ADHD, 175 probands with ASD, and their unaffected siblings (ADHD, N=121; ASD, N=72).

RESULTS

ASD and ADHD shared diffuse white matter tract deviations in the commissure and association tracts (rho=0.54; p<0.001), while prefrontal corpus callosum deviated more remarkably in ASD (effect size=-0.36; p<0.001). Highly correlated deviance patterns between probands and unaffected siblings were found in both ASD (rho=0.69; p<0.001) and ADHD (rho=0.51; p<0.001), but only unaffected sisters of ASD probands showed a potential endophenotype in long-range association fibers and projection fibers connecting prefrontal regions. ADHD and ASD shared significant white matter tract idiosyncrasy (rho=0.55; p<0.001), particularly in tracts connecting prefrontal regions, not identified in either sibling group. Canonical correlation analysis identified multiple dimensions of psychopathology/cognition across categorical entities; autistic, visual memory, intelligence/planning/inhibition, nonverbal-intelligence/attention, working memory/attention, and set-shifting/response-variability were associated with distinct sets of white matter tract deviations.

CONCLUSIONS

When conceptualizing neurodevelopmental disorders as white matter tract deviations from normative patterns, ASD and ADHD are more alike than different. The modest white matter tract alterations in siblings suggest potential endophenotypes in these at-risk populations. This study further delineates brain-driven dimensions of psychopathology/cognition, which may help clarify within-diagnosis heterogeneity and high between-diagnosis co-occurrence.

Sex-specific associations between subcortical morphometry in childhood and adult alcohol consumption: A 17-year follow-up study

Men and women tend to differ in the age of first alcohol consumption, transition into disordered drinking, and the prevalence of alcohol use disorder. Here, we use a unique longitudinal dataset to test for potentially predispositonal sex-biases in brain organization prior to initial alcohol exposure. Our study combines measures of subcortical morphometry gathered in alcohol naive individuals during childhood (mean age: 9.43 years, SD = 2.06) with self-report measures of alcohol use in the same individuals an average of 17 years later (N = 81, 46 males, 35 females). We observe that pediatric amygdala and hippocampus volume both show sex-biased relationships with adult drinking. Specifically, females show a stronger association between subcortical volumetric reductions in childhood and peak drinking in adulthood as compared to males. Detailed analysis of subcortical shape localizes these effects to the rostro-medial hippocampus and basolateral amygdala subnuclei. In contrast, we did not observe sex-specific associations between striatal anatomy and peak alcohol consumption. These results are consistent with a model in which organization of the amygdala and hippocampus in childhood is more relevant for subsequent patterns of peak alcohol use in females as compared to males. Differential neuroanatomical precursors of alcohol use in males and females could provide a potential developmental basis for well recognized sex-differences in alcohol use behaviors.. Thus, our findings not only indicate that brain correlates of human alcohol consumption are manifest long before alcohol initiation, but that some of these correlates are not equivalent between males and females.

The neuropathology of autism: A systematic review of post-mortem studies of autism and related disorders

Post-mortem studies allow for the direct investigation of brain tissue in those with autism and related disorders. Several review articles have focused on aspects of post-mortem abnormalities but none has brought together the entire post-mortem literature. Here, we systematically review the evidence from post-mortem studies of autism, and of related disorders that present with autistic features. The literature consists of a small body of studies with small sample sizes, but several remarkably consistent findings are evident. Cortical layering is largely undisturbed, but there are consistent reductions in minicolumn numbers and aberrant myelination. Transcriptomics repeatedly implicate abberant synaptic, metabolic, proliferation, apoptosis and immune pathways. Sufficient replicated evidence is available to implicate non-coding RNA, aberrant epigenetic profiles, GABAergic, glutamatergic and glial dysfunction in autism pathogenesis. Overall, the cerebellum and frontal cortex are most consistently implicated, sometimes revealing distinct region-specific alterations. The literature on related disorders such as Rett syndrome, Fragile X and copy number variations (CNVs) predisposing to autism is particularly small and inconclusive. Larger studies, matched for gender, developmental stage, co-morbidities and drug treatment are required.

Metal and essential element concentrations during pregnancy and associations with autism spectrum disorder and attention-deficit/hyperactivity disorder in children

BACKGROUND

Prenatal exposure to toxic metals or variations in maternal levels of essential elements during pregnancy may be a risk factor for neurodevelopmental disorders such as attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) in offspring.

OBJECTIVES

We investigated whether maternal levels of toxic metals and essential elements measured in mid-pregnancy, individually and as mixtures, were associated with childhood diagnosis of ADHD or ASD.

METHODS

This study is based on the Norwegian Mother, Father and Child Cohort Study and included 705 ADHD cases, 397 ASD cases and 1034 controls. Cases were identified through linkage with the Norwegian Patient Registry. Maternal concentrations of 11 metals/elements were measured in blood at week 17 of gestation; cadmium; cesium; cobalt; copper; lead; magnesium; manganese; selenium; zinc; total arsenic; and total mercury. Multivariable adjusted logistic regression models were used to examine associations between quartile levels of individual metals/elements and outcomes. We also investigated non-linear associations using restricted cubic spline models. The joint effects of the metal/element mixture on ASD and ADHD diagnoses were estimated using a quantile-based g-computation approach.

RESULTS

For ASD, we identified positive associations (increased risks) in the second quartile of arsenic [OR = 1.77 (CI: 1.26, 2.49)] and the fourth quartiles of cadmium and manganese [OR = 1.57 (CI: 1.07 2.31); OR = 1.84 (CI: 1.30, 2.59)], respectively. In addition, there were negative associations between cesium, copper, mercury, and zinc and ASD. For ADHD, we found increased risk in the fourth quartiles of cadmium and magnesium [OR = 1.59 (CI: 1.15, 2.18); [OR = 1.42 (CI: 1.06, 1.91)]. There were also some negative associations, among others with mercury. In addition, we identified non-linear associations between ASD and arsenic, mercury, magnesium, and lead, and between ADHD and arsenic, copper, manganese, and mercury. There were no significant findings in the mixture approach analyses.

CONCLUSION

Results from the present study show several associations between levels of metals and elements during gestation and ASD and ADHD in children. The most notable ones involved arsenic, cadmium, copper, mercury, manganese, magnesium, and lead. Our results suggest that even population levels of these compounds may have negative impacts on neurodevelopment. As we observed mainly similarities among the metals' and elements' impact on ASD and ADHD, it could be that the two disorders share some neurochemical and neurodevelopmental pathways. The results warrant further investigation and replication, as well as studies of combined effects of metals/elements and mechanistic underpinnings.

The Association Between Autism Symptoms and Child Functioning in a Sample With ADHD Recruited From the Community

Objective: Although autism spectrum disorder (ASD) symptoms are associated with poorer functioning in children with attention-deficit/hyperactivity disorder (ADHD), it is unclear which ASD symptom domains are most impairing. This study investigated whether specific ASD symptom domains were associated with child functioning in children with ADHD. Method: Parents of 164 children with ADHD completed a diagnostic interview to assess ADHD and comorbidities. Parents reported on ASD symptoms (Social Communication Questionnaire) and child quality of life (Pediatric Quality of Life Inventory 4.0). Parents and teachers completed the Strengths and Difficulties Questionnaire (emotional, conduct, and peer problems). Results: Repetitive and stereotyped behaviors were independently associated with emotional (p = .02) and conduct (p = .03) problems, and poorer quality of life (p = .004). Reciprocal social interaction deficits were independently associated with peer problems (p = .03). Conclusion: Reciprocal social interaction deficits and repetitive and stereotyped behaviors are important areas that should be focused on in ADHD assessment and treatment.

A Review of the Default Mode Network in Autism Spectrum Disorders and Attention Deficit Hyperactivity Disorder

Functional magnetic resonance imaging (fMRI) has been widely used to examine the relationships between brain function and phenotypic features in neurodevelopmental disorders. Techniques such as resting-state functional connectivity (FC) have enabled the identification of the primary networks of the brain. One fMRI network, in particular, the default mode network (DMN), has been implicated in social-cognitive deficits in autism spectrum disorders (ASD) and attentional deficits in attention deficit hyperactivity disorder (ADHD). Given the significant clinical and genetic overlap between ASD and ADHD, surprisingly, no reviews have compared the clinical, developmental, and genetic correlates of DMN in ASD and ADHD and here we address this knowledge gap. We find that, compared with matched controls, ASD studies show a mixed pattern of both stronger and weaker FC in the DMN and ADHD studies mostly show stronger FC. Factors such as age, intelligence quotient, medication status, and heredity affect DMN FC in both ASD and ADHD. We also note that most DMN studies make ASD versus ADHD group comparisons and fail to consider ASD+ADHD comorbidity. We conclude, by identifying areas for improvement and by discussing the importance of using transdiagnostic approaches such as the Research Domain Criteria (RDoC) to fully account for the phenotypic and genotypic heterogeneity and overlap of ASD and ADHD.

Reduced fine motor competence in children with ADHD is associated with atypical microstructural organization within the superior longitudinal fasciculus

Recent work in healthy adults suggests that white matter organization within the superior longitudinal fasciculus (SLF) may, at least partly, explain individual differences in fine motor skills. The SLF is also often implicated in the neurobiology underlying attention deficit hyperactivity disorder (ADHD) as part of the attention network connecting frontal and parietal regions. While ADHD is primarily characterized by inattention, impulsivity and/or hyperactivity, atypical fine motor control is a common comorbid feature. This study aimed to investigate the association between reduced fine motor skills in ADHD and microstructural properties within the SLF. Participants were 55 right-handed children with ADHD and 61 controls aged 9-11 years. Fine motor control was assessed using the Grooved Pegboard task. Children underwent high angular resolution diffusion MRI. Following pre-processing, constrained spherical deconvolution tractography was performed to delineate the three SLF branches bilaterally. Children with ADHD showed significantly poorer fine motor performance relative to controls in the non-dominant hand, indicated by significantly slower left handed Grooved Pegboard task performance. This slower response time for the non-dominant (left) hand was significantly associated with reduced apparent fibre density within the right SLF I, and reduced right SLF I, II and III volume. This finding was independent of spatial attention performance. These data support previous reports indicating that children with ADHD have poorer fine motor performance than controls in their non-dominant hand, and indicates that the neurobiological basis for impaired fine motor control may involve white matter properties within the contralateral SLF. This suggests that white matter properties in fronto-parietal areas may have broader implications than attention.

Actionable and incidental neuroradiological findings in twins with neurodevelopmental disorders

While previous research has investigated neuroradiological findings in autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD), the entire range of neurodevelopmental disorders (NDDs) has not yet been well-studied using magnetic resonance imaging (MRI). Considering the overlap among NDDs and simultaneous development of the brain and face, guided by molecular signaling, we examined the relationship of actionable and incidental (non-actionable) MRI findings and NDD diagnoses together with facial morphological variants and genetic copy number variants (CNVs). A cross-sectional study was conducted with a twin cohort 8–36 years of age (57% monozygotic, 40% dizygotic), including 372 subjects (46% with NDDs; 47% female) imaged by MRI, 280 with data for facial morphological variants, and 183 for CNVs. Fifty-one percent of participants had MRI findings. Males had a statistically significantly higher percentage of MRI findings (57.7%) compared with females (43.8%, p = 0.03). Twin zygosity was not statistically significantly correlated with incidence or severity of specific MRI findings. No statistically significant association was found between MRI findings and any NDD diagnosis or facial morphological variants; however, MRI findings were statistically significantly associated with the number of CNVs (OR 1.20, 95% CI 1.00–1.44, p = 0.05, adjusted OR for sex 1.24, 95% CI 1.03–1.50, p = 0.02). When combining the presence of MRI findings, facial morphological variants, and CNVs, statistically significant relationships were found with ASD and ADHD diagnoses (p = 0.0006 and p = 0.002, respectively). The results of this study demonstrate that the ability to identify NDDs from combined radiology, morphology, and CNV assessments may be possible. Additionally, twins do not appear to be at increased risk for neuroradiological variants.

Comprehensive Profiling of Gene Expression in the Cerebral Cortex and Striatum of BTBRTF/ArtRbrc Mice Compared to C57BL/6J Mice

Mouse line BTBR T+ Iptr3^tf/J (hereafter referred as to BTBR/J) is a mouse strain that shows lower sociability compared to the C57BL/6J mouse strain (B6) and thus is often utilized as a model for autism spectrum disorder (ASD). In this study, we utilized another subline, BTBRTF/ArtRbrc (hereafter referred as to BTBR/R), and analyzed the associated brain transcriptome compared to B6 mice using microarray analysis, quantitative RT-PCR analysis, various bioinformatics analyses, and in situ hybridization. We focused on the cerebral cortex and the striatum, both of which are thought to be brain circuits associated with ASD symptoms. The transcriptome profiling identified 1,280 differentially expressed genes (DEGs; 974 downregulated and 306 upregulated genes, including 498 non-coding RNAs [ncRNAs]) in BTBR/R mice compared to B6 mice. Among these DEGs, 53 genes were consistent with ASD-related genes already established. Gene Ontology (GO) enrichment analysis highlighted 78 annotations (GO terms) including DNA/chromatin regulation, transcriptional/translational regulation, intercellular signaling, metabolism, immune signaling, and neurotransmitter/synaptic transmission-related terms. RNA interaction analysis revealed novel RNA–RNA networks, including 227 ASD-related genes. Weighted correlation network analysis highlighted 10 enriched modules including DNA/chromatin regulation, neurotransmitter/synaptic transmission, and transcriptional/translational regulation. Finally, the behavioral analyses showed that, compared to B6 mice, BTBR/R mice have mild but significant deficits in social novelty recognition and repetitive behavior. In addition, the BTBR/R data were comprehensively compared with those reported in the previous studies of human subjects with ASD as well as ASD animal models, including BTBR/J mice. Our results allow us to propose potentially important genes, ncRNAs, and RNA interactions. Analysis of the altered brain transcriptome data of the BTBR/R and BTBR/J sublines can contribute to the understanding of the genetic underpinnings of autism susceptibility.

Clinical Subtypes in Children with Attention-Deficit Hyperactivity Disorder According to Their Child Behavior Checklist Profile

This study sought to identify subgroups of attention-deficit hyperactivity disorder (ADHD) defined by specific patterns of emotional and behavioral symptoms according to the parent-rated Child Behavior Checklist (CBCL). Our clinical sample comprised 314 children (aged 4 to 15 years) diagnosed with ADHD according to the DSM-5. In addition, comorbid psychiatric disorders, general functioning, and medication status were assessed. Cluster analysis was performed on the CBCL syndrome subscales and yielded a solution with four distinct subgroups. The "High internalizing/externalizing" group displayed an overlap between internalizing and externalizing problems in the CBCL profile. In addition, the "High internalizing/externalizing" group revealed a high rate of comorbid autism spectrum disorder and elevated autistic traits. The "Inattention and internalizing" group revealed a high rate of the predominantly inattentive presentation according to ADHD specifier from the DSM-5. The "Aggression and externalizing" group revealed a high rate of comorbid oppositional defiant disorder and conduct disorder. The "Less psychopathology" group scored low on all syndrome scales. Children with ADHD were subdivided into four distinct subgroups characterized by psychopathological patterns, with and without internalizing and externalizing problems. The overlap between internalizing and externalizing problems may be mediated with emotional dysregulation and associated neurobiological bases.

Cross-Disorder Analysis of Brain Structural Abnormalities in Six Major Psychiatric Disorders: A Secondary Analysis of Mega- and Meta-analytical Findings From the ENIGMA Consortium

BACKGROUND

Neuroimaging studies have consistently reported similar brain structural abnormalities across different psychiatric disorders. Yet, the extent and regional distribution of shared morphometric abnormalities between disorders remains unknown.

METHODS

Here, we conducted a cross-disorder analysis of brain structural abnormalities in 6 psychiatric disorders based on effect size estimates for cortical thickness and subcortical volume differences between healthy control subjects and psychiatric patients from 11 mega- and meta-analyses from the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta Analysis) consortium. Correlational and exploratory factor analyses were used to quantify the relative overlap in brain structural effect sizes between disorders and to identify brain regions with disorder-specific abnormalities.

RESULTS

Brain structural abnormalities in major depressive disorder, bipolar disorder, schizophrenia, and obsessive-compulsive disorder were highly correlated (r = .443 to r = .782), and one shared latent underlying factor explained between 42.3% and 88.7% of the brain structural variance of each disorder. The observed shared morphometric signature of these disorders showed little similarity with brain structural patterns related to physiological aging. In contrast, patterns of brain structural abnormalities independent of all other disorders were observed in both attention-deficit/hyperactivity disorder and autism spectrum disorder. Brain regions showing high proportions of independent variance were identified for each disorder to locate disorder-specific morphometric abnormalities.

CONCLUSIONS

Taken together, these results offer novel insights into transdiagnostic as well as disorder-specific brain structural abnormalities across 6 major psychiatric disorders. Limitations comprise the uncertain contribution of risk factors, comorbidities, and medication effects to the observed pattern of results that should be clarified by future research.

White matter alterations in autism spectrum disorder and attention-deficit/hyperactivity disorder in relation to sensory profile

Background

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have high rates of co-occurrence and share atypical behavioral characteristics, including sensory symptoms. The present diffusion tensor imaging (DTI) study was conducted to examine whether and how white matter alterations are observed in adult populations with developmental disorders (DD) and to determine how brain–sensory relationships are either shared between or distinct to ASD and ADHD.

Methods

We collected DTI data from adult population with DD (a primary diagnosis of ASD: n = 105, ADHD: n = 55) as well as age- and sex-matched typically developing (TD) participants (n = 58). Voxel-wise fractional anisotropy (FA), mean diffusivity, axial diffusivity, and radial diffusivity (RD) were analyzed using tract-based spatial statistics. The severities of sensory symptoms were assessed using the Adolescent/Adult Sensory Profile (AASP).

Results

Categorical analyses identified voxel clusters showing significant effects of DD on FA and RD in the posterior portion of the corpus callosum and its extension in the right hemisphere. Furthermore, regression analyses using the AASP scores revealed that slopes in relationships of FA or RD with the degree of sensory symptoms were parallel between the two DDs in large parts of the affected corpus callosum regions. A small but significant cluster did exist showing difference in association between an AASP subscale score and RD across ASD and ADHD.

Limitations

Wide age range of the participants may be oversimplified.

Conclusions

These results indicate that white matter alteration and their relationships to sensory symptoms are largely shared between ASD and ADHD, with localized abnormalities showing significant between-diagnosis differences within DD.

Associations Between Limbic System White Matter Structure and Socio-Emotional Functioning in Children with ADHD + ASD

Children with attention deficit/hyperactivity disorder (ADHD) combined with autism spectrum disorder (ASD) symptoms (ADHD + ASD) have poorer social and emotional functioning than those with ADHD alone. However, no studies have specifically examined the associations between ASD symptoms, measures of social and emotional functioning and limbic system white matter microstructure. Tractography on the cingulum, uncinate fasciculus and fornix were performed for 151 children with (N = 78) and without (N = 73) ADHD. Participants in the ADHD group who scored 11 or above on the Social Communication Questionnaire were classified as the ADHD + ASD group (N = 16). Significant differences in mean cingulum FA were present between the control group and the ADHD (all) group, however, no significant differences were seen between the ADHD and ADHD + ASD groups. Despite this, significant associations were seen between mean FA of the left cingulum and emotional problems for the ADHD + ASD group. Results give greater insights into the specific biological basis of emotional problems in the ADHD + ASD group, indicating that the cingulum may play a role.

The role of cerebellum in the child neuropsychological functioning

This chapter proposes a review of neuropsychologic and behavior findings in pediatric pathologies of the cerebellum, including cerebellar malformations, pediatric ataxias, cerebellar tumors, and other acquired cerebellar injuries during childhood. The chapter also contains reviews of the cerebellar mutism/posterior fossa syndrome, reported cognitive associations with the development of the cerebellum in typically developing children and subjects born preterm, and the role of the cerebellum in neurodevelopmental disorders such as autism spectrum disorders and developmental dyslexia. Cognitive findings in pediatric cerebellar disorders are considered in the context of known cerebellocerebral connections, internal cellular organization of the cerebellum, the idea of a universal cerebellar transform and computational internal models, and the role of the cerebellum in specific cognitive and motor functions, such as working memory, language, timing, or control of eye movements. The chapter closes with a discussion of the strengths and weaknesses of the cognitive affective syndrome as it has been described in children and some conclusions and perspectives.

Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups

OBJECTIVE

Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data.

METHODS

Structural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures).

RESULTS

No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood.

CONCLUSIONS

The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

Data-Driven Diagnostics and the Potential of Mobile Artificial Intelligence for Digital Therapeutic Phenotyping in Computational Psychiatry

Data science and digital technologies have the potential to transform diagnostic classification. Digital technologies enable the collection of big data, and advances in machine learning and artificial intelligence enable scalable, rapid, and automated classification of medical conditions. In this review, we summarize and categorize various data-driven methods for diagnostic classification. In particular, we focus on autism as an example of a challenging disorder due to its highly heterogeneous nature. We begin by describing the frontier of data science methods for the neuropsychiatry of autism. We discuss early signs of autism as defined by existing pen-and-paper-based diagnostic instruments and describe data-driven feature selection techniques for determining the behaviors that are most salient for distinguishing children with autism from neurologically typical children. We then describe data-driven detection techniques, particularly computer vision and eye tracking, that provide a means of quantifying behavioral differences between cases and controls. We also describe methods of preserving the privacy of collected videos and prior efforts of incorporating humans in the diagnostic loop. Finally, we summarize existing digital therapeutic interventions that allow for data capture and longitudinal outcome tracking as the diagnosis moves along a positive trajectory. Digital phenotyping of autism is paving the way for quantitative psychiatry more broadly and will set the stage for more scalable, accessible, and precise diagnostic techniques in the field.

Clinical versus automated assessments of morphological variants in twins with and without neurodevelopmental disorders

Physical examinations are recommended as part of a comprehensive evaluation for individuals with neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder. These examinations should include assessment for morphological variants. Previous studies have shown an increase in morphological variants in individuals with NDDs, particularly ASD, and that these variants may be present in greater amounts in individuals with genetic alterations. Unfortunately, assessment for morphological variants can be subjective and time-consuming, and require a high degree of clinical expertise. Therefore, objective, automated methods of morphological assessment are desirable. This study compared the use of Face2Gene, an automated tool to explore facial morphological variants, to clinical consensus assessment, using a cohort of N = 290 twins enriched for NDDs (n = 135 with NDD diagnoses). Agreement between automated and clinical assessments were satisfactory to complete (78.3-100%). In our twin sample, individuals with NDDs did not have greater numbers of facial morphological variants when compared to those with typical development, nor when controlling for shared genetic and environmental factors within twin pairs. Common facial morphological variants in those with and without NDDs were similar and included thick upper lip vermilion, abnormality of the nasal tip, long face, and upslanted palpebral fissure. We conclude that although facial morphological variants can be assessed reliably in NDDs with automated tools like Face2Gene, clinical utility is limited when just exploring the facial region. Therefore, currently, automated assessments may best complement, rather than replace, in-person clinical assessments.

Gait control in children with attention-deficit/hyperactivity disorder

The current profile of gait control in children with ADHD is incomplete and predominately based on children walking forward at a self-selected pace. There are no studies of potential gait deficits in this clinical population when walking in different directions in combination with varying rates of stepping that are freely selected and entrained to an external stimulus. The purpose of the current study was to address this lack of information by assessing gait of children aged 7-17 years with (n = 17) and without (n = 26) ADHD. Participants walked forward and backward along an electronically instrumented carpet at a self-selected stepping rate and in synchrony to a metronome that dictated an increased and decreased stepping rate. Using repeated measures analysis of covariance (ANCOVA) to assess spatiotemporal gait parameters, results showed that children with ADHD exhibited a significantly exaggerated, toes 'turned out,' foot position for all walking conditions compared to typically developing children. When walking backward, children with ADHD produced an increased step width, higher stepping cadence, and increased velocity. Additionally, coefficient of variation ratios indicated that children with ADHD produced greater variability of velocity, cadence, and step time for all walking conditions, and greater variability for stride length when walking at an increased stepping rate. Results were interpreted in terms of clinical significance and practical ramifications that inform rehabilitation specialists in designing therapies that ameliorate the reported gait deficits.

Deviation from normative brain development is associated with symptom severity in autism spectrum disorder

Background

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition. The degree to which the brain development in ASD deviates from typical brain development, and how this deviation relates to observed behavioral outcomes at the individual level are not well-studied. We hypothesize that the degree of deviation from typical brain development of an individual with ASD would relate to observed symptom severity.

Methods

The developmental changes in anatomical (cortical thickness, surface area, and volume) and diffusion metrics (fractional anisotropy and apparent diffusion coefficient) were compared between a sample of ASD (n = 247) and typically developing children (TDC) (n = 220) aged 6-25. Machine learning was used to predict age (brain age) from these metrics in the TDC sample, to define a normative model of brain development. This model was then used to compute brain age in the ASD sample. The difference between chronological age and brain age was considered a developmental deviation index (DDI), which was then correlated with ASD symptom severity.

Results

Machine learning model trained on all five metrics accurately predicted age in the TDC (r = 0.88) and the ASD (r = 0.85) samples, with dominant contributions to the model from the diffusion metrics. Within the ASD group, the DDI derived from fractional anisotropy was correlated with ASD symptom severity (r = - 0.2), such that individuals with the most advanced brain age showing the lowest severity, and individuals with the most delayed brain age showing the highest severity.

Limitations

This work investigated only linear relationships between five specific brain metrics and only one measure of ASD symptom severity in a limited age range. Reported effect sizes are moderate. Further work is needed to investigate developmental differences in other age ranges, other aspects of behavior, other neurobiological measures, and in an independent sample before results can be clinically applicable.

Conclusions

Findings demonstrate that the degree of deviation from typical brain development relates to ASD symptom severity, partially accounting for the observed heterogeneity in ASD. Our approach enables characterization of each individual with reference to normative brain development and identification of distinct developmental subtypes, facilitating a better understanding of developmental heterogeneity in ASD.

Structural brain abnormalities in children and adolescents with comorbid autism spectrum disorder and attention-deficit/hyperactivity disorder

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) share high rates of comorbidity, with the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition now acknowledging the comorbid diagnosis of ASD and ADHD. Although structural abnormalities in the prefrontal cortex, cerebellum, and basal ganglia occur in both ASD and ADHD, no structural studies have focused exclusively on patients with comorbid ASD and ADHD. We thus aimed to clarify the structural features and developmental changes in patients with comorbid ASD and ADHD in a relatively large sample from two sites. Ninety-two patients were age-matched to 141 typically developing (TD) controls (age range: 5-16 years) and assessed for volumetric characteristics using structural magnetic resonance imaging (i.e. surface-based morphometry). While there were no significant differences in prefrontal cortex, cerebellum, and basal ganglia volumes, patients with ASD and ADHD exhibited significantly lower left postcentral gyrus volumes than TD controls. We observed significantly lower postcentral gyrus volumes exclusively in children and preadolescents, and not in adolescents. Our findings suggest that abnormal somatosensory, attributed to delayed maturation of the left postcentral gyrus, leads to the core symptoms experienced by patients with comorbid ASD and ADHD.

Examining overlap and homogeneity in ASD, ADHD, and OCD: a data-driven, diagnosis-agnostic approach

The validity of diagnostic labels of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive compulsive disorder (OCD) is an open question given the mounting evidence that these categories may not correspond to conditions with distinct etiologies, biologies, or phenotypes. The objective of this study was to determine the agreement between existing diagnostic labels and groups discovered based on a data-driven, diagnosis-agnostic approach integrating cortical neuroanatomy and core-domain phenotype features. A machine learning pipeline, called bagged-multiview clustering, was designed to discover homogeneous subgroups by integrating cortical thickness data and measures of core-domain phenotypic features of ASD, ADHD, and OCD. This study was conducted using data from the Province of Ontario Neurodevelopmental Disorders (POND) Network, a multi-center study in Ontario, Canada. Participants (n = 226) included children between the ages of 6 and 18 with a diagnosis of ASD (n = 112, median [IQR] age = 11.7[4.8], 21% female), ADHD (n = 58, median [IQR] age = 10.2[3.3], 14% female), or OCD (n = 34, median [IQR] age = 12.1[4.2], 38% female), as well as typically developing controls (n = 22, median [IQR] age = 11.0[3.8], 55% female). The diagnosis-agnostic groups were significantly different than each other in phenotypic characteristics (SCQ: χ²(9) = 111.21, p < 0.0001; SWAN: χ²(9) = 142.44, p < 0.0001) as well as cortical thickness in 75 regions of the brain. The analyses revealed disagreement between existing diagnostic labels and the diagnosis-agnostic homogeneous groups (normalized mutual information < 0.20). Our results did not support the validity of existing diagnostic labels of ASD, ADHD, and OCD as distinct entities with respect to phenotype and cortical morphology.

Effects of prenatal exposure to particulate matter air pollution on corpus callosum and behavioral problems in children

OBJECTIVE

Air pollution (AP) may affect neurodevelopment, but studies about the effects of AP on the growing human brain are still scarce. We aimed to investigate the effects of prenatal exposure to AP on lateral ventricles (LV) and corpus callosum (CC) volumes in children and to determine whether the induced brain changes are associated with behavioral problems.

METHODS

Among the children recruited through a set of representative schools of the city of Barcelona, (Spain) in the Brain Development and Air Pollution Ultrafine Particles in School Children (BREATHE) study, 186 typically developing participants aged 8-12 years underwent brain MRI on the same 1.5 T MR unit over a 1.5-year period (October 2012-April 2014). Brain volumes were derived from structural MRI scans using automated tissue segmentation. Behavioral problems were assessed using the Strengths and Difficulties Questionnaire (SDQ) and the criteria of the Attention Deficit Hyperactivity Disorder DSM-IV list. Prenatal fine particle (PM_2.5) levels were retrospectively estimated at the mothers' residential addresses during pregnancy with land use regression (LUR) models. To determine whether brain structures might be affected by prenatal PM_2.5 exposure, linear regression models were run and adjusted for age, sex, intracranial volume (ICV), maternal education, home socioeconomic vulnerability index, birthweight and mothers' smoking status during pregnancy. To test for associations between brain changes and behavioral outcomes, negative binomial regressions were performed and adjusted for age, sex, ICV.

RESULTS

Prenatal PM_2.5 levels ranged from 11.8 to 39.5 μg/m³ during the third trimester of pregnancy. An interquartile range increase in PM_2.5 level (7 μg/m³) was significantly linked to a decrease in the body CC volume (mm³) (β = -53.7, 95%CI [-92.0, -15.5] corresponding to a 5% decrease of the mean body CC volume) independently of ICV, age, sex, maternal education, socioeconomic vulnerability index at home, birthweight and mothers' smoking status during the third trimester of pregnancy. A 50 mm³ decrease in the body CC was associated with a significant higher hyperactivity subscore (Rate Ratio (RR) = 1.09, 95%CI [1.01, 1.17) independently of age, sex and ICV. The statistical significance of these results did not survive to False Discovery Rate correction for multiple comparisons.

CONCLUSIONS

Prenatal exposure to PM_2.5 may be associated with CC volume decrease in children. The consequences might be an increase in behavioral problems.

Childhood sleep disturbances and white matter microstructure in preadolescence

BACKGROUND

Sleep problems occur in up to 30% of children and have been associated with adverse developmental outcomes. However, due to a lack of longitudinal neuroimaging studies, the neurobiological changes that may underlie some of these associations have remained unclear. This study explored the association between sleep problems during childhood and white matter (WM) microstructure in preadolescence.

METHODS

Children from the population-based birth cohort, the Generation R Study, who had repeatedly assessed sleep problems between 1.5 and 10 years of age and a MRI scan at age 10 (N = 2,449), were included. Mothers reported on their child's sleep problems using the Child Behavior Checklist (CBCL 1.5-5) when children were 1.5, 3, and 6 years of age. At age 2, mothers completed very similar questions. At age 10, both children and their mothers reported on sleep problems. We used whole-brain and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) values obtained through diffusion tensor imaging as measures of WM microstructure.

RESULTS

Childhood sleep problems at 1.5, 2, and 6 years of age were associated with less WM microstructural integrity (approximately 0.05 SD lower global FA score per 1-SD sleep problems). In repeated-measures analyses, children with more sleep problems (per 1-SD) at baseline had lower FA values at age 10 in particular in the corticospinal tract (-0.12 SD, 95% CI:-0.20;-0.05), the uncinate fasciculus (-0.12 SD, 95% CI:-0.19;-0.05), and the forceps major (-0.11 SD, 95% CI:-0.18;-0.03), although effect estimates across the tracts did not differ substantially.

CONCLUSIONS

Childhood sleep disturbances are associated with less WM microstructural integrity in preadolescence. Our results show that early neurodevelopment may be a period of particular vulnerability to sleep problems. This study cannot demonstrate causality but suggests that preventive interventions addressing sleep problems should be further explored to test whether they impact adverse neurodevelopment.

Systematic Review: Overlap Between Eating, Autism Spectrum, and Attention-Deficit/Hyperactivity Disorder

Background: Links between eating disorders (EDs) [e.g., anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED)] and the major neurodevelopmental disorders of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have been repeatedly highlighted. In both ASD and ADHD, these links range from an elevated risk for EDs to common symptomatic overlaps and etiological commonalities with EDs. Methods: We performed a systematic literature search (through July 2019) with Medline via Ovid for epidemiological data on EDs (AN, BN, and BED) in combination with both ASD and ADHD. Results: The reviewed studies showed that, on average, 4.7% of patients with certain ED diagnoses (AN, BN, or BED) received an ASD diagnosis. Reliable data on the prevalence of EDs in ASD samples are still scarce. Comorbid ASD is most commonly diagnosed in patients with AN. The prevalence of ADHD in EDs ranged between 1.6% and 18%. Comorbid ADHD was more often reported in the AN-binge eating/purging subtype and BN than in the AN restrictive subtype. The prevalence of EDs in ADHD ranged between no association and a lifetime prevalence of 21.8% of developing an ED in women with ADHD. Conclusions: Studies on the prevalence rates of EDs in ADHD and ASD and vice versa are heterogeneous, but they indicate frequent association. While there is growing evidence of clinical overlaps between the three disorders, it remains difficult to determine whether overlapping characteristics (e.g., social withdrawal) are due to common comorbidities (e.g., depression) or are instead primarily associated with EDs and neurodevelopmental disorders. Furthermore, prospective studies are required to better understand how these disorders are related and whether ADHD and ASD could be either specific or nonspecific predisposing factors for the development of EDs.

The Functional Brain Organization of an Individual Allows Prediction of Measures of Social Abilities Transdiagnostically in Autism and Attention-Deficit/Hyperactivity Disorder

BACKGROUND

Autism spectrum disorder and attention-deficit/hyperactivity disorder (ADHD) are associated with complex changes as revealed by functional magnetic resonance imaging. To date, neuroimaging-based models are not able to characterize individuals with sufficient sensitivity and specificity. Further, although evidence shows that ADHD traits occur in individuals with autism spectrum disorder, and autism spectrum disorder traits in individuals with ADHD, the neurofunctional basis of the overlap is undefined.

METHODS

Using individuals from the Autism Brain Imaging Data Exchange and ADHD-200, we apply a data-driven, subject-level approach, connectome-based predictive modeling, to resting-state functional magnetic resonance imaging data to identify brain-behavior associations that are predictive of symptom severity. We examine cross-diagnostic commonalities and differences.

RESULTS

Using leave-one-subject-out and split-half analyses, we define networks that predict Social Responsiveness Scale, Autism Diagnostic Observation Schedule, and ADHD Rating Scale scores and confirm that these networks generalize to novel subjects. Networks share minimal overlap of edges (<2%) but some common regions of high hubness (Brodmann areas 10, 11, and 21, cerebellum, and thalamus). Further, predicted Social Responsiveness Scale scores for individuals with ADHD are linked to ADHD symptoms, supporting the hypothesis that brain organization relevant to autism spectrum disorder severity shares a component associated with attention in ADHD. Predictive connections and high-hubness regions are found within a wide range of brain areas and across conventional networks.

CONCLUSIONS

An individual's functional connectivity profile contains information that supports dimensional, nonbinary classification in autism spectrum disorder and ADHD. Furthermore, we can determine disorder-specific and shared neurofunctional pathology using our method.