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

Cortical scaling of the neonatal brain in typical and altered development

Theoretically derived scaling laws capture the nonlinear relationships between rapidly expanding brain volume and cortical gyrification across mammalian species and in adult humans. However, the preservation of these laws has not been comprehensively assessed in typical or pathological brain development. Here, we assessed the scaling laws governing cortical thickness (CT), surface area (SA), and cortical folding in the neonatal brain. We also assessed multivariate morphological terms that capture brain size, shape, and folding processes. The sample consisted of 345 typically developing infants, 73 preterm infants, and 107 infants with congenital heart disease (CHD) who underwent brain MRI. Our results show that typically developing neonates and those with CHD follow the cortical folding scaling law obtained from mammalian brains, children, and adults which captures the relationship between exposed SA, total SA, and CT. Cortical folding scaling was not affected by gestational age at birth, postmenstrual age at scan, sex, or multiple birth in these populations. CHD was characterized by a unique reduction in the multivariate morphological term capturing size, suggesting that CHD affects cortical growth overall but not cortical folding processes. In contrast, preterm birth was characterized by altered cortical folding scaling and altered shape, suggesting that the developmentally programmed processes of cortical folding are disrupted in this population. The degree of altered shape was associated with cognitive abilities in early childhood in preterm infants.

ENIGMA-Meditation: Worldwide Consortium for Neuroscientific Investigations of Meditation Practices

Meditation is a family of ancient and contemporary contemplative mind-body practices that can modulate psychological processes, awareness, and mental states. Over the last 40 years, clinical science has manualized meditation practices and designed various meditation interventions that have shown therapeutic efficacy for disorders including depression, pain, addiction, and anxiety. Over the past decade, neuroimaging has been used to examine the neuroscientific basis of meditation practices, effects, states, and outcomes for clinical and nonclinical populations. However, the generalizability and replicability of current neuroscientific models of meditation have not yet been established, because they are largely based on small datasets entrenched with heterogeneity along several domains of meditation (e.g., practice types, meditation experience, clinical disorder targeted), experimental design, and neuroimaging methods (e.g., preprocessing, analysis, task-based, resting-state, structural magnetic resonance imaging). These limitations have precluded a nuanced and rigorous neuroscientific phenotyping of meditation practices and their potential benefits. Here, we present ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis)-Meditation, the first worldwide collaborative consortium for neuroscientific investigations of meditation practices. ENIGMA-Meditation will enable systematic meta- and mega-analyses of globally distributed neuroimaging datasets of meditation using shared, standardized neuroimaging methods and tools to improve statistical power and generalizability. Through this powerful collaborative framework, existing neuroscientific accounts of meditation practices can be extended to generate novel and rigorous neuroscientific insights that account for multidomain heterogeneity. ENIGMA-Meditation will inform neuroscientific mechanisms that underlie therapeutic action of meditation practices on psychological and cognitive attributes, thereby advancing the field of meditation and contemplative neuroscience.

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.

Increasing Health Literacy on ADHD: A Cross-Disciplinary Integrative Review Examining the Impact of ADHD on Brain Maturation, Composition and Function and Cognitive Processes Across the Life Course

There is a significant need to improve ADHD health literacy. This cross-disciplinary integrative review was conducted to synthesise the evidence on the impact ADHD has on brain maturation, composition and function as well as cognitive processes, across the life course. Although results are highly heterogenous, ADHD appears to be associated with (1) a significant delay in cortical maturation and differences in neuroanatomy that do not appear to fully resolve in adulthood, (2) atypical brain function, and (3) atypical cognitive processes. The cognitive processes implicated include working memory, inhibitory control, cognitive flexibility, alerting attention, reward processing, long-term memory, reaction time, time perception and estimation, planning, and complex decision making/problem-solving. We aim to use this data to develop a 'framework/checklist" that parents, adults and clinicians can use to identify the possible mechanisms that may be contributing to an individual with ADHD's challenges. This information can also be used to inform the content of ADHD education programs to ensure participants receive empirically-determine information from high quality review studies and meta-analysis that accurately reflects the rigor and limitations of study findings.

Research progress of tDCS in the treatment of ADHD

TDCS is one of the most widely used non-invasive neuromodulation techniques, which changes the excitability of local cortical tissue by applying weak continuous direct current to the scalp, effectively improves the attention and concentration of ADHD children, and improves the impulse disorder of patients, but related research is still in its infancy. Based on a review of a large number of existing literatures and an analysis of the pathogenesis and principle of ADHD, this paper summarized the research on tDCS in the treatment of ADHD in recent years from the aspects of treatment mechanism, safety and stimulation parameters, and simply compared the application of tDCS with other non-traumatic neuromodulation techniques in the treatment of ADHD. The future development direction of this technology is further discussed.

Multimodal imaging of the amygdala in non-clinical subjects with high vs. low autistic-like social skills traits

Recent clinical and theoretical frameworks suggest that social skills and theory of mind impairments characteristic of autism spectrum disorder (ASD) are distributed in the general population on a continuum between healthy individuals and patients. The present multimodal study aimed at investigating the amygdala's function, perfusion, and volume in 56 non-clinical subjects from the general population with high (n = 28 High-SOC) or low (n = 28 Low-SOC) autistic-like social skills traits. Participants underwent magnetic resonance imaging to evaluate the amygdala's functional connectivity at rest, blood perfusion by means of arterial spin labelling, its activation during a face evaluation task and lastly grey matter volumes. The High-SOC group was characterised by higher blood perfusion in both amygdalae, lower volume of the left amygdala and higher activations of the right amygdala during processing of human faces with fearful value. Resting state analyses did not reveal any significant difference between the two groups. Overall, our results highlight the presence of overlapping morpho-functional alterations of the amygdala between healthy individuals and ASD patients confirming the importance of the amygdala in this disorder and in social and emotional processing. Our findings may help disentangle the neurobiological facets of ASD elucidating aetiology and the relationship between clinical symptomatology and neurobiology.

Neuroglia in autism spectrum disorders

Autism spectrum disorder (ASD) is characterized by difficulties in social interaction, communication, and repetitive behavior, typically diagnosed during early childhood and attributed to altered neuronal network connectivity. Several genetic and environmental risk factors contribute to ASD, including pre- or early life immune activation, which can trigger microglial and astroglial reactivity, impacting early neurodevelopment. In ASD, astrocytes show altered glutamate metabolism, directly influencing neuronal network activity, while microglia display impaired synaptic pruning, an essential developmental process for the refinement of neuronal connections. Additionally, reduced myelination in specific cortical and subcortical regions may affect brain connectivity in ASD, with white matter integrity correlating with the severity of the disorder, suggesting an important role for oligodendrocytes and myelin in ASD. This chapter provides an overview of current literature on the role of neuroglia cells in ASD, with a focus on immune activation, glutamate signaling, synaptic pruning, and myelination.

Neuroimaging Insights into Brain Mechanisms of Early-onset Restrictive Eating Disorders

Background

Early-onset restrictive eating disorders (rEO-ED) encompass a heterogeneous group of conditions, including early-onset anorexia nervosa (EO-AN) and avoidant restrictive food intake disorders (ARFID). Almost nothing is known about the consequences of rEO-ED on brain development.

Methods

We performed the largest comparison of MRI-derived brain features in children and early adolescents (<13 years) with EO-AN (n=124), ARFID (n=50), and typically developing individuals (TD, n=112).

Results

Despite similar body mass index (BMI) distributions, EO-AN and ARFID showed divergent structural patterns, suggesting independent brain mechanisms. Half the regional brain measures were correlated with BMI in EO-AN and none in ARFID, indicating a partial mediation of EO-AN signal by BMI. EO-AN was associated with a widespread pattern of thinner cortex, while underweight ARFID patients exhibited smaller surface area and subcortical volumes than TD.

Conclusion

Future studies will be required to partition the contribution of low BMI vs. ED mechanisms in neurodevelopmental disorders.

Molecular signatures of cortical expansion in the human foetal brain

The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. Recent studies have revealed a remarkable molecular diversity across the prenatal cortex but little is known about how this diversity translates into the differential rates of cortical expansion observed during gestation. We present a digital resource, μBrain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal brain. Using μBrain, we evaluate the molecular signatures of preferentially-expanded cortical regions, quantified in utero using magnetic resonance imaging. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of neocortical expansion during gestation. We identify genes, upregulated from mid-gestation, that are highly expressed in rapidly expanding neocortex and implicated in genetic disorders with cognitive sequelae. The μBrain atlas provides a tool to comprehensively map early brain development across domains, model systems and resolution scales.

Structural Brain Correlates of Anxiety During Development

Anxiety and related disorders are prevalent across the lifespan, often have their onset during youth, and are associated with notable levels of impairment and burden across multiple domains. Elucidating the associations between differential patterns of neurodevelopment and anxiety in youth is a promising approach for developing deeper insights regarding the neurobiological etiologies and maintenance factors associated with anxiety and related disorders. A growing body of literature has yielded evidence of associations between patterns of brain structure (i.e., volume, cortical thickness, and cortical surface area) and anxiety. Here, we present a review and synthesis of the existing body of literature surrounding neurostructural correlates of anxiety in youth spanning multiple anxiety presentations and three neurostructural modalities. We reveal substantially more research focusing on brain volume than cortical thickness or surface area and a greater number of studies examining anxiety broadly defined, obsessive-compulsive disorder, or posttraumatic stress disorder. There is also evidence of considerable variability in the brain regions implicated and the direction of associations across studies. Finally, we discuss the gaps and limitations in this body of work, which suggest avenues for future directions.

Exploring the most discriminative brain structural abnormalities in ASD with multi-stage progressive feature refinement approach

Objective

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by increasing prevalence, diverse impairments, and unclear origins and mechanisms. To gain a better grasp of the origins of ASD, it is essential to identify the most distinctive structural brain abnormalities in individuals with ASD.

Methods

A Multi-Stage Progressive Feature Refinement Approach was employed to identify the most pivotal structural magnetic resonance imaging (MRI) features that distinguish individuals with ASD from typically developing (TD) individuals. The study included 175 individuals with ASD and 69 TD individuals, all aged between 7 and 18 years, matched in terms of age and gender. Both cortical and subcortical features were integrated, with a particular focus on hippocampal subfields.

Results

Out of 317 features, 9 had the most significant impact on distinguishing ASD from TD individuals. These structural features, which include a specific hippocampal subfield, are closely related to the brain areas associated with the reward system.

Conclusion

Structural irregularities in the reward system may play a crucial role in the pathophysiology of ASD, and specific hippocampal subfields may also contribute uniquely, warranting further investigation.

Superior temporal sulcus folding, functional network connectivity, and autistic-like traits in a non-clinical population

BACKGROUND

Autistic-like traits (ALT) are prevalent across the general population and might be linked to some facets of a broader autism spectrum disorder (ASD) phenotype. Recent studies suggest an association of these traits with both genetic and brain structural markers in non-autistic individuals, showing similar spatial location of findings observed in ASD and thus suggesting a potential neurobiological continuum.

METHODS

In this study, we first tested an association of ALTs (assessed with the AQ questionnaire) with cortical complexity, a cortical surface marker of early neurodevelopment, and then the association with disrupted functional connectivity. We analysed structural T1-weighted and resting-state functional MRI scans in 250 psychiatrically healthy individuals without a history of early developmental disorders, in a first step using the CAT12 toolbox for cortical complexity analysis and in a second step we used regional cortical complexity findings to apply the CONN toolbox for seed-based functional connectivity analysis.

RESULTS

Our findings show a significant negative correlation of both AQ total and AQ attention switching subscores with left superior temporal sulcus (STS) cortical folding complexity, with the former being significantly correlated with STS to left lateral occipital cortex connectivity, while the latter showed significant positive correlation of STS to left inferior/middle frontal gyrus connectivity (n = 233; all p < 0.05, FWE cluster-level corrected). Additional analyses also revealed a significant correlation of AQ attention to detail subscores with STS to left lateral occipital cortex connectivity.

LIMITATIONS

Phenotyping might affect association results (e.g. choice of inventories); in addition, our study was limited to subclinical expressions of autistic-like traits.

CONCLUSIONS

Our findings provide further evidence for biological correlates of ALT even in the absence of clinical ASD, while establishing a link between structural variation of early developmental origin and functional connectivity.

Where do neurodevelopmental conditions fit in transdiagnostic psychiatric frameworks? Incorporating a new neurodevelopmental spectrum

Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.

Influences of RASopathies on Neuroanatomical Variation in Children

BACKGROUND

RASopathies are a group of disorders characterized by pathogenic mutations in the Ras/mitogen-activated protein kinase (Ras/MAPK) signaling pathway. Distinct pathogenic variants in genes encoding proteins in the Ras/MAPK pathway cause Noonan syndrome (NS) and neurofibromatosis type 1 (NF1), which are associated with increased risk for autism spectrum disorder and attention-deficit/hyperactivity disorder.

METHODS

This study examined the effect of RASopathies (NS and NF1) on human neuroanatomy, specifically on surface area (SA), cortical thickness (CT), and subcortical volumes. Using vertex-based analysis for cortical measures and Desikan region of interest parcellation for subcortical volumes, we compared structural T1-weighted images of children with RASopathies (n = 91, mean age = 8.81 years, SD = 2.12) to those of sex- and age-matched typically developing children (n = 74, mean age = 9.07 years, SD = 1.77).

RESULTS

Compared with typically developing children, RASopathies had convergent effects on SA and CT, exhibiting increased SA in the precentral gyrus, decreased SA in occipital regions, and thinner CT in the precentral gyrus. RASopathies exhibited divergent effects on subcortical volumes, with syndrome-specific influences from NS and NF1. Overall, children with NS showed decreased volumes in striatal and thalamic structures, and children with NF1 displayed increased volumes in the hippocampus, amygdala, and thalamus.

CONCLUSIONS

Our study reveals the converging and diverging neuroanatomical effects of RASopathies on human neurodevelopment. The convergence of cortical effects on SA and CT indicates a shared influence of Ras/MAPK hyperactivation on the human brain. Therefore, considering these measures as objective outcome indicators for targeted treatments is imperative.

Gray matter asymmetry alterations in children and adolescents with comorbid autism spectrum disorder and attention-deficit/hyperactivity disorder

Despite the high coexistence of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) (ASD + ADHD), the underlying neurobiological basis of this disorder remains unclear. Altered brain structural asymmetries have been verified in ASD and ADHD, respectively, making brain asymmetry a candidate for characterizing this coexisting disorder. Here, we measured the gray matter (GM) volume asymmetry in ASD + ADHD versus ASD without ADHD (ASD-only), ADHD without ASD (ADHD-only), and typically developing controls (TDc). High-resolution T1-weighted data from 48 ASD + ADHD, 63 ASD-only, 32 ADHD-only, and 211 matched TDc were included in our study. We also assessed brain-behavior relationships and the effects of age on GM asymmetry. We found that there were both shared and disorder-specific GM volume asymmetry alterations in ASD + ADHD, ASD-only, and ADHD-only compared with TDc. This finding demonstrates that ASD + ADHD is neither an endophenocopy nor an additive pathology of ASD and ADHD, but an entirely different neuroanatomical pathology. In addition, ASD + ADHD displayed altered GM volume asymmetries in the prefrontal regions responsible for executive function and theory of mind compared with ASD-only. We also found significant effects of age on GM asymmetry. The present study may provide structural insights into the neural basis of ASD + ADHD.

Neural correlates of inattention in adults with ADHD

In the last two decades, numerous magnetic resonance imaging (MRI) studies have examined differences in cortical structure between individuals with Attention-Deficit/Hyperactivity Disorder (ADHD) and healthy controls. These studies primarily emphasized alterations in gray matter volume (GMV) and cortical thickness (CT). Still, the scientific literature is notably scarce in regard to investigating associations of cortical structure with ADHD psychopathology, specifically inattention within adults with ADHD. The present study aimed to elucidate neurobiological underpinnings of inattention beyond GMV and CT by including cortical gyrification, sulcal depth, and fractal dimension. Building upon the Comparison of Methylphenidate and Psychotherapy in Adult ADHD Study (COMPAS), cortical structure parameters were investigated using 141 T1-weighted anatomical scans of adult patients with ADHD. All brain structural analyses were performed using the threshold-free cluster enhancement (TFCE) approach and the Computational Anatomy Toolbox (CAT12) integrated into the Statistical Parametric Mapping Software (Matlab Version R2021a). Results revealed significant correlations of inattention in multiple brain regions. Cortical gyrification was negatively correlated, whereas cortical thickness and fractal dimension were positively associated with inattention. The clusters showed widespread distribution across the cerebral cortex, with both hemispheres affected. The cortical regions most prominently affected included the precuneus, para-, pre-, and postcentral gyri, superior parietal lobe, and posterior cingulate cortex. This study highlights the importance of cortical alterations in attentional processes in adults with ADHD. Further research in this area is warranted to elucidate intricacies of inattention in adults with ADHD to potentially enhance diagnostic accuracy and inform personalized treatment strategies.

Chronic Low-Grade Inflammation and Brain Structure in the Middle-Aged and Elderly Adults

Low-grade inflammation (LGI) mainly acted as the mediator of the association of obesity and inflammatory diet with numerous chronic diseases, including neuropsychiatric diseases. However, the evidence about the effect of LGI on brain structure is limited but important, especially in the context of accelerating aging. This study was then designed to close the gap, and we leveraged a total of 37,699 participants from the UK Biobank and utilized inflammation score (INFLA-score) to measure LGI. We built the longitudinal relationships of INFLA-score with brain imaging phenotypes using multiple linear regression models. We further analyzed the interactive effects of specific covariates. The results showed high level inflammation reduced the volumes of the subcortex and cortex, especially the globus pallidus (β [95% confidence interval] = -0.062 [-0.083, -0.041]), thalamus (-0.053 [-0.073, -0.033]), insula (-0.052 [-0.072, -0.032]), superior temporal gyrus (-0.049 [-0.069, -0.028]), lateral orbitofrontal cortex (-0.047 [-0.068, -0.027]), and others. Most significant effects were observed among urban residents. Furthermore, males and individuals with physical frailty were susceptive to the associations. The study provided potential insights into pathological changes during disease progression and might aid in the development of preventive and control targets in an age-friendly city to promote great health and well-being for sustainable development goals.

Genetic influences on brain and cognitive health and their interactions with cardiovascular conditions and depression

Approximately 40% of dementia cases could be prevented or delayed by modifiable risk factors related to lifestyle and environment. These risk factors, such as depression and vascular disease, do not affect all individuals in the same way, likely due to inter-individual differences in genetics. However, the precise nature of how genetic risk profiles interact with modifiable risk factors to affect brain health is poorly understood. Here we combine multiple data resources, including genotyping and postmortem gene expression, to map the genetic landscape of brain structure and identify 367 loci associated with cortical thickness and 13 loci associated with white matter hyperintensities (P < 5×10-8), with several loci also showing a significant association with cognitive function. We show that among 220 unique genetic loci associated with cortical thickness in our genome-wide association studies (GWAS), 95 also showed evidence of interaction with depression or cardiovascular conditions. Polygenic risk scores based on our GWAS of inferior frontal thickness also interacted with hypertension in predicting executive function in the Canadian Longitudinal Study on Aging. These findings advance our understanding of the genetic underpinning of brain structure and show that genetic risk for brain and cognitive health is in part moderated by treatable mid-life factors.

Prevalence of comorbidity of autism and ADHD and associated characteristics in school population: EPINED study

Autism and attention deficit hyperactivity disorder (ADHD) comorbidity in the school population have been understudied. This study estimates its prevalence considering both parents' and teachers' reports and clinical diagnosis. Sociodemographic, clinical, and cognitive data were compared by diagnostic groups: autism, ADHD, autism and ADHD, subthreshold autism spectrum disorder (ASD), subthreshold ADHD, and children without neurodevelopmental conditions. Following a two-phase design, 3727 parents and teachers (1802 preschoolers, 1925 school-age children) participated in the first phase. Subsequently, 781 participants underwent individual assessment for DSM-5 diagnoses. The estimated prevalence of the comorbid diagnosis was 0.51% (0.28%-0.74%), with significant sex differences (0.16% girls, 0.89% boys). The cooccurrence of symptoms of autism and ADHD reported by parents or teachers was 3.2% and 2.6%, respectively. ADHD comorbidity was observed in 32.8% of autistic children and 31.4% of those with subthreshold ASD. ASD comorbidity was observed in 9.8% of children with ADHD and 5.7% of those with subthreshold ADHD. Comorbidity was reported by at least one informant in 95% of children. Only 15.8% of children with autism and ADHD had been previously diagnosed with both conditions. Early detection and accurate comorbidity diagnosis are crucial to address the clinical and socio-educational needs of these children.

Alterations in cortical thickness and volumes of subcortical structures in pediatric patients with complete spinal cord injury

AIMS

To study the changes in cortical thickness and subcortical gray matter structures in children with complete spinal cord injury (CSCI), reveal the possible causes of dysfunction beyond sensory motor dysfunction after CSCI, and provide a possible neural basis for corresponding functional intervention training.

METHODS

Thirty-seven pediatric CSCI patients and 34 age-, gender-matched healthy children as healthy controls (HCs) were recruited. The 3D high-resolution T1-weighted structural images of all subjects were obtained using a 3.0 Tesla MRI system. Statistical differences between pediatric CSCI patients and HCs in cortical thickness and volumes of subcortical gray matter structures were evaluated. Then, correlation analyses were performed to analyze the correlation between the imaging indicators and clinical characteristics.

RESULTS

Compared with HCs, pediatric CSCI patients showed decreased cortical thickness in the right precentral gyrus, superior temporal gyrus, and posterior segment of the lateral sulcus, while increased cortical thickness in the right lingual gyrus and inferior occipital gyrus. The volume of the right thalamus in pediatric CSCI patients was significantly smaller than that in HCs. No significant correlation was found between the imaging indicators and the injury duration, sensory scores, and motor scores of pediatric CSCI patients.

CONCLUSIONS

These findings demonstrated that the brain structural reorganizations of pediatric CSCI occurred not only in sensory motor areas but also in cognitive and visual related brain regions, which may suggest that the visual processing, cognitive abnormalities, and related early intervention therapy also deserve greater attention beyond sensory motor rehabilitation training in pediatric CSCI patients.

The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

Potential Neuroprotective Effect of Melatonin in the Hippocampus of Male BTBR Mice

Autism spectrum disorder (ASD) is a neurodevelopmental disorder identified by impairments in common social interactions and repetitive behaviors. In ASD patients, substantial morphological alterations have been observed in the hippocampus, which represents an important region for the development of social skills. Melatonin, commonly found in many foods and plants, is also produced by the pineal gland. This indolamine, known to regulate the circadian rhythm, shows antioxidant and anti-inflammatory properties. We therefore hypothesized that melatonin may reduce oxidative stress and inflammation in the hippocampus of ASD patients. We explored our hypothesis using the BTBR mouse, a well-regarded murine transgenic model for ASD. Immediately after weaning, male BTBR and C57BL/6 mice underwent an 8-week treatment with melatonin or vehicle. Later, through immunohistochemistry and the immunoblotting analysis of the hippocampus, we evaluated the overall expression and cellular localization of Nrf2 and SOD1, two enzymes involved in the oxidative stress response. Similarly, we evaluated NLRP3 and NFkB, two mediators of inflammation, and GAD67, an enzyme responsible for the synthesis of GABA. Ultimately, we addressed melatonin's potential to regulate iron metabolism through a DAB-enhanced Perls reaction assay. Results showed melatonin's potential for modulating the analyzed markers in BTBR mice, suggesting a potential neuroprotective effect in ASD patients.

Cortical grey matter volume differences in children with developmental coordination disorder compared to typically developing children

Introduction

The cause of Developmental Coordination Disorder (DCD) is unknown, but neuroimaging evidence suggests that DCD may be related to altered brain development. Children with DCD show less structural and functional connectivity compared to typically developing (TD) children, but few studies have examined cortical volume in children with DCD. The purpose of this study was to investigate cortical grey matter volume using voxel-based morphometry (VBM) in children with DCD compared to TD children.

Methods

This cross-sectional study was part of a larger randomized-controlled trial (ClinicalTrials.gov ID: NCT02597751) that involved various MRI scans of children with/without DCD. This paper focuses on the anatomical scans, performing VBM of cortical grey matter volume in 30 children with DCD and 12 TD children. Preprocessing and VBM data analysis were conducted using the Computational Anatomy Tool Box-12 and a study-specific brain template. Differences between DCD and TD groups were assessed using a one-way ANOVA, controlling for total intracranial volume. Regression analyses examined if motor and/or attentional difficulties predicted grey matter volume. We used threshold-free cluster enhancement (5,000 permutations) and set an alpha level of 0.05. Due to the small sample size, we did not correct for multiple comparisons.

Results

Compared to the TD group, children with DCD had significantly greater grey matter in the left superior frontal gyrus. Lower motor scores (meaning greater impairment) were related to greater grey matter volume in left superior frontal gyrus, frontal pole, and right middle frontal gyrus. Greater grey matter volume was also significantly correlated with higher scores on the Conners 3 ADHD Index in the left superior frontal gyrus, superior parietal lobe, and precuneus. These results indicate that greater grey matter volume in these regions is associated with poorer motor and attentional skills.

Discussion

Greater grey matter volume in the left superior frontal gyrus in children with DCD may be a result of delayed or absent healthy cortical thinning, potentially due to altered synaptic pruning as seen in other neurodevelopmental disorders. These findings provide further support for the hypothesis that DCD is related to altered brain development.

Improvement of attention deficit disorder symptoms after treatment of obstructive sleep apnea in an adult: a case report and mini review

Sparse literature exists on the effects of obstructive sleep apnea (OSA) treatment on symptoms of attention deficit hyperactivity disorder (ADHD) in adults. This article aims to bring to the fore the relationship between ADHD and OSA in adults and the implications of the treatment of OSA on the symptoms of ADHD. A case of an adult who was previously diagnosed with attention deficit disorder in childhood with symptom improvement following OSA treatment is reported. Considering the complex relationship between ADHD and sleep problems, the recommendation to screen for OSA and other sleep problems among persons being assessed for ADHD should be upheld. This article advocates for more research on the effect of the treatment of OSA on ADHD symptoms.

CITATION

Awadalla TO, Igwe O, Okeafor CU, Attarian HP. Improvement of attention deficit disorder symptoms after treatment of obstructive sleep apnea in an adult: a case report and mini review. J Clin Sleep Med. 2024;20(5):825-827.

Effects of gene dosage and development on subcortical nuclei volumes in individuals with 22q11.2 copy number variations

The 22q11.2 locus contains genes critical for brain development. Reciprocal Copy Number Variations (CNVs) at this locus impact risk for neurodevelopmental and psychiatric disorders. Both 22q11.2 deletions (22qDel) and duplications (22qDup) are associated with autism, but 22qDel uniquely elevates schizophrenia risk. Understanding brain phenotypes associated with these highly penetrant CNVs can provide insights into genetic pathways underlying neuropsychiatric disorders. Human neuroimaging and animal models indicate subcortical brain alterations in 22qDel, yet little is known about developmental differences across specific nuclei between reciprocal 22q11.2 CNV carriers and typically developing (TD) controls. We conducted a longitudinal MRI study in a total of 385 scans from 22qDel (n = 96, scans = 191, 53.1% female), 22qDup (n = 37, scans = 64, 45.9% female), and TD controls (n = 80, scans = 130, 51.2% female), across a wide age range (5.5-49.5 years). Volumes of the thalamus, hippocampus, amygdala, and anatomical subregions were estimated using FreeSurfer, and the linear effects of 22q11.2 gene dosage and non-linear effects of age were characterized with generalized additive mixed models (GAMMs). Positive gene dosage effects (volume increasing with copy number) were observed for total intracranial and whole hippocampus volumes, but not whole thalamus or amygdala volumes. Several amygdala subregions exhibited similar positive effects, with bi-directional effects found across thalamic nuclei. Distinct age-related trajectories were observed across the three groups. Notably, both 22qDel and 22qDup carriers exhibited flattened development of hippocampal CA2/3 subfields relative to TD controls. This study provides novel insights into the impact of 22q11.2 CNVs on subcortical brain structures and their developmental trajectories.

Systematic review and meta-analysis: multimodal functional and anatomical neural alterations in autism spectrum disorder

BACKGROUND

This meta-analysis aimed to explore the most robust findings across numerous existing resting-state functional imaging and voxel-based morphometry (VBM) studies on the functional and structural brain alterations in individuals with autism spectrum disorder (ASD).

METHODS

A whole-brain voxel-wise meta-analysis was conducted to compare the differences in the intrinsic functional activity and gray matter volume (GMV) between individuals with ASD and typically developing individuals (TDs) using Seed-based d Mapping software.

RESULTS

A total of 23 functional imaging studies (786 ASD, 710 TDs) and 52 VBM studies (1728 ASD, 1747 TDs) were included. Compared with TDs, individuals with ASD displayed resting-state functional decreases in the left insula (extending to left superior temporal gyrus [STG]), bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), left angular gyrus and right inferior temporal gyrus, as well as increases in the right supplementary motor area and precuneus. For VBM meta-analysis, individuals with ASD displayed decreased GMV in the ACC/mPFC and left cerebellum, and increased GMV in the left middle temporal gyrus (extending to the left insula and STG), bilateral olfactory cortex, and right precentral gyrus. Further, individuals with ASD displayed decreased resting-state functional activity and increased GMV in the left insula after overlapping the functional and structural differences.

CONCLUSIONS

The present multimodal meta-analysis demonstrated that ASD exhibited similar alterations in both function and structure of the insula and ACC/mPFC, and functional or structural alterations in the default mode network (DMN), primary motor and sensory regions. These findings contribute to further understanding of the pathophysiology of ASD.

Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study

Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion magnetic resonance imaging [MRI]). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N = 34,029) and ABCD Study (N = 8607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI in a genome-wide association study (GWAS) with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition.

Common and distinct cortical thickness alterations in youth with autism spectrum disorder and attention-deficit/hyperactivity disorder

BACKGROUND

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders with overlapping behavioral features and genetic etiology. While brain cortical thickness (CTh) alterations have been reported in ASD and ADHD separately, the degree to which ASD and ADHD are associated with common and distinct patterns of CTh changes is unclear.

METHODS

We searched PubMed, Web of Science, Embase, and Science Direct from inception to 8 December 2023 and included studies of cortical thickness comparing youth (age less than 18) with ASD or ADHD with typically developing controls (TDC). We conducted a comparative meta-analysis of vertex-based studies to identify common and distinct CTh alterations in ASD and ADHD.

RESULTS

Twelve ASD datasets involving 458 individuals with ASD and 10 ADHD datasets involving 383 individuals with ADHD were included in the analysis. Compared to TDC, ASD showed increased CTh in bilateral superior frontal gyrus, left middle temporal gyrus, and right superior parietal lobule (SPL) and decreased CTh in right temporoparietal junction (TPJ). ADHD showed decreased CTh in bilateral precentral gyri, right postcentral gyrus, and right TPJ relative to TDC. Conjunction analysis showed both disorders shared reduced TPJ CTh located in default mode network (DMN). Comparative analyses indicated ASD had greater CTh in right SPL and TPJ located in dorsal attention network and thinner CTh in right TPJ located in ventral attention network than ADHD.

CONCLUSIONS

These results suggest shared thinner TPJ located in DMN is an overlapping neurobiological feature of ASD and ADHD. This alteration together with SPL alterations might be related to altered biological motion processing in ASD, while abnormalities in sensorimotor systems may contribute to behavioral control problems in ADHD. The disorder-specific thinner TPJ located in disparate attention networks provides novel insight into distinct symptoms of attentional deficits associated with the two neurodevelopmental disorders.

TRIAL REGISTRATION

PROSPERO CRD42022370620. Registered on November 9, 2022.

Adolescent to young adult longitudinal development of subcortical volumes in two European sites with four waves

Adolescent subcortical structural brain development might underlie psychopathological symptoms, which often emerge in adolescence. At the same time, sex differences exist in psychopathology, which might be mirrored in underlying sex differences in structural development. However, previous studies showed inconsistencies in subcortical trajectories and potential sex differences. Therefore, we aimed to investigate the subcortical structural trajectories and their sex differences across adolescence using for the first time a single cohort design, the same quality control procedure, software, and a general additive mixed modeling approach. We investigated two large European sites from ages 14 to 24 with 503 participants and 1408 total scans from France and Germany as part of the IMAGEN project including four waves of data acquisition. We found significantly larger volumes in males versus females in both sites and across all seven subcortical regions. Sex differences in age-related trajectories were observed across all regions in both sites. Our findings provide further evidence of sex differences in longitudinal adolescent brain development of subcortical regions and thus might eventually support the relationship of underlying brain development and different adolescent psychopathology in boys and girls.

Molecular signatures of cortical expansion in the human fetal brain

The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. A growing catalogue of cells in the prenatal brain has revealed remarkable molecular diversity across cortical areas.1,2 Despite this, little is known about how this translates into the patterns of differential cortical expansion observed in humans during the latter stages of gestation. Here we present a new resource, μBrain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal developing brain. Built using generative artificial intelligence, μBrain is a three-dimensional cellular-resolution digital atlas combining publicly-available serial sections of the postmortem human brain at 21 weeks gestation3 with bulk tissue microarray data, sampled across 29 cortical regions and 5 transient tissue zones.4 Using μBrain, we evaluate the molecular signatures of preferentially-expanded cortical regions during human gestation, quantified in utero using magnetic resonance imaging (MRI). We find that differences in the rates of expansion across cortical areas during gestation respect anatomical and evolutionary boundaries between cortical types5 and are founded upon extended periods of upper-layer cortical neuron migration that continue beyond mid-gestation. We identify a set of genes that are upregulated from mid-gestation and highly expressed in rapidly expanding neocortex, which are implicated in genetic disorders with cognitive sequelae. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of expansion across the neocortical sheet during the prenatal epoch. The μBrain atlas is available from: https://garedaba.github.io/micro-brain/ and provides a new tool to comprehensively map early brain development across domains, model systems and resolution scales.

Cortical thickness abnormalities in autism spectrum disorder

The pathological mechanism of autism spectrum disorder (ASD) remains unclear. Nowadays, surface-based morphometry (SBM) based on structural magnetic resonance imaging (sMRI) techniques have reported cortical thickness (CT) variations in ASD. However, the findings were inconsistent and heterogeneous. This current meta-analysis conducted a whole-brain vertex-wise coordinate-based meta-analysis (CBMA) on CT studies to explore the most noticeable and robust CT changes in ASD individuals by applying the seed-based d mapping (SDM) program. A total of 26 investigations comprised 27 datasets were included, containing 1,635 subjects with ASD and 1470 HC, along with 94 coordinates. Individuals with ASD exhibited significantly altered CT in several regions compared to HC, including four clusters with thicker CT in the right superior temporal gyrus (STG.R), the left middle temporal gyrus (MTG.L), the left anterior cingulate/paracingulate gyri, the right superior frontal gyrus (SFG.R, medial orbital parts), as well as three clusters with cortical thinning including the left parahippocampal gyrus (PHG.L), the right precentral gyrus (PCG.R) and the left middle frontal gyrus (MFG.L). Adults with ASD only demonstrated CT thinning in the right parahippocampal gyrus (PHG.R), revealed by subgroup meta-analyses. Meta-regression analyses found that CT in STG.R was positively correlated with age. Meanwhile, CT in MFG.L and PHG.L had negative correlations with the age of ASD individuals. These results suggested a complicated and atypical cortical development trajectory in ASD, and would provide a deeper understanding of the neural mechanism underlying the cortical morphology in ASD.

Large-Scale Neuroimaging of Mental Illness

Neuroimaging has provided important insights into the brain variations related to mental illness. Inconsistencies in prior studies, however, call for methods that lead to more replicable and generalizable brain markers that can reliably predict illness severity, treatment course, and prognosis. A paradigm shift is underway with large-scale international research teams actively pooling data and resources to drive consensus findings and test emerging methods aimed at achieving the goals of precision psychiatry. In parallel with large-scale psychiatric genomics studies, international consortia combining neuroimaging data are mapping the transdiagnostic brain signatures of mental illness on an unprecedented scale. This chapter discusses the major challenges, recent findings, and a roadmap for developing better neuroimaging-based tools and markers for mental illness.

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.

Decoding anxiety-impulsivity subtypes in preadolescent internalising disorders: findings from the Adolescent Brain Cognitive Development study

BACKGROUND

Internalising disorders are highly prevalent emotional dysregulations during preadolescence but clinical decision-making is hampered by high heterogeneity. During this period impulsivity represents a major risk factor for psychopathological trajectories and may act on this heterogeneity given the controversial anxiety-impulsivity relationships. However, how impulsivity contributes to the heterogeneous symptomatology, neurobiology, neurocognition and clinical trajectories in preadolescent internalising disorders remains unclear.

AIMS

The aim was to determine impulsivity-dependent subtypes in preadolescent internalising disorders that demonstrate distinct anxiety-impulsivity relationships, neurobiological, genetic, cognitive and clinical trajectory signatures.

METHOD

We applied a data-driven strategy to determine impulsivity-related subtypes in 2430 preadolescents with internalising disorders from the Adolescent Brain Cognitive Development study. Cross-sectional and longitudinal analyses were employed to examine subtype-specific signatures of the anxiety-impulsivity relationship, brain morphology, cognition and clinical trajectory from age 10 to 12 years.

RESULTS

We identified two distinct subtypes of patients who internalise with comparably high anxiety yet distinguishable levels of impulsivity, i.e. enhanced (subtype 1) or decreased (subtype 2) compared with control participants. The two subtypes exhibited opposing anxiety-impulsivity relationships: higher anxiety at baseline was associated with higher lack of perseverance in subtype 1 but lower sensation seeking in subtype 2 at baseline/follow-up. Subtype 1 demonstrated thicker prefrontal and temporal cortices, and genes enriched in immune-related diseases and glutamatergic and GABAergic neurons. Subtype 1 exhibited cognitive deficits and a detrimental trajectory characterised by increasing emotional/behavioural dysregulations and suicide risks during follow-up.

CONCLUSIONS

Our results indicate impulsivity-dependent subtypes in preadolescent internalising disorders and unify past controversies about the anxiety-impulsivity interaction. Clinically, individuals with a high-impulsivity subtype exhibit a detrimental trajectory, thus early interventions are warranted.

Cerebral cortical structural alteration patterns across four major psychiatric disorders in 5549 individuals

According to the operational diagnostic criteria, psychiatric disorders such as schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and autism spectrum disorder (ASD) are classified based on symptoms. While its cluster of symptoms defines each of these psychiatric disorders, there is also an overlap in symptoms between the disorders. We hypothesized that there are also similarities and differences in cortical structural neuroimaging features among these psychiatric disorders. T1-weighted magnetic resonance imaging scans were performed for 5,549 subjects recruited from 14 sites. Effect sizes were determined using a linear regression model within each protocol, and these effect sizes were meta-analyzed. The similarity of the differences in cortical thickness and surface area of each disorder group was calculated using cosine similarity, which was calculated from the effect sizes of each cortical regions. The thinnest cortex was found in SZ, followed by BD and MDD. The cosine similarity values between disorders were 0.943 for SZ and BD, 0.959 for SZ and MDD, and 0.943 for BD and MDD, which indicated that a common pattern of cortical thickness alterations was found among SZ, BD, and MDD. Additionally, a generally smaller cortical surface area was found in SZ and MDD than in BD, and the effect was larger in SZ. The cosine similarity values between disorders were 0.945 for SZ and MDD, 0.867 for SZ and ASD, and 0.811 for MDD and ASD, which indicated a common pattern of cortical surface area alterations among SZ, MDD, and ASD. Patterns of alterations in cortical thickness and surface area were revealed in the four major psychiatric disorders. To our knowledge, this is the first report of a cross-disorder analysis conducted on four major psychiatric disorders. Cross-disorder brain imaging research can help to advance our understanding of the pathogenesis of psychiatric disorders and common symptoms.

Effects of Gene Dosage and Development on Subcortical Nuclei Volumes in Individuals with 22q11.2 Copy Number Variations

The 22q11.2 locus contains genes critical for brain development. Reciprocal Copy Number Variations (CNVs) at this locus impact risk for neurodevelopmental and psychiatric disorders. Both 22q11.2 deletions (22qDel) and duplications (22qDup) are associated with autism, but 22qDel uniquely elevates schizophrenia risk. Understanding brain phenotypes associated with these highly penetrant CNVs can provide insights into genetic pathways underlying neuropsychiatric disorders. Human neuroimaging and animal models indicate subcortical brain alterations in 22qDel, yet little is known about developmental differences across specific nuclei between reciprocal 22q11.2 CNV carriers and typically developing (TD) controls. We conducted a longitudinal MRI study in 22qDel (n=96, 53.1% female), 22qDup (n=37, 45.9% female), and TD controls (n=80, 51.2% female), across a wide age range (5.5-49.5 years). Volumes of the thalamus, hippocampus, amygdala, and anatomical subregions were estimated using FreeSurfer, and the effect of 22q11.2 gene dosage was examined using linear mixed models. Age-related changes were characterized with general additive mixed models (GAMMs). Positive gene dosage effects (22qDel < TD < 22qDup) were observed for total intracranial and whole hippocampus volumes, but not whole thalamus or amygdala volumes. Several amygdala subregions exhibited similar positive effects, with bi-directional effects found across thalamic nuclei. Distinct age-related trajectories were observed across the three groups. Notably, both 22qDel and 22qDup carriers exhibited flattened development of hippocampal CA2/3 subfields relative to TD controls. This study provides novel insights into the impact of 22q11.2 CNVs on subcortical brain structures and their developmental trajectories.

Associations among prenatal exposure to gestational diabetes mellitus, brain structure, and child adiposity markers

OBJECTIVE

The aim of this study was to investigate the mediating role of child brain structure in the relationship between prenatal gestational diabetes mellitus (GDM) exposure and child adiposity.

METHODS

This was a cross-sectional study of 9- to 10-year-old participants and siblings across the US. Data were obtained from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study®. Brain structure was evaluated by magnetic resonance imaging. GDM exposure was self-reported, and discordance for GDM exposure within biological siblings was identified. Mixed effects and mediation models were used to examine associations among prenatal GDM exposure, brain structure, and adiposity markers with sociodemographic covariates.

RESULTS

The sample included 8521 children (7% GDM-exposed), among whom there were 28 sibling pairs discordant for GDM exposure. Across the entire study sample, prenatal exposure to GDM was associated with lower global and regional cortical gray matter volume (GMV) in the bilateral rostral middle frontal gyrus and superior temporal gyrus. GDM-exposed siblings also demonstrated lower global cortical GMV than unexposed siblings. Global cortical GMV partially mediated the associations between prenatal GDM exposure and child adiposity markers.

CONCLUSIONS

The results identify brain markers of prenatal GDM exposure and suggest that low cortical GMV may explain increased obesity risk for offspring prenatally exposed to GDM.

Predicting mild cognitive impairments from cognitively normal brains using a novel brain age estimation model based on structural magnetic resonance imaging

Brain age prediction is a practical method used to quantify brain aging and detect neurodegenerative diseases such as Alzheimer's disease (AD). However, very few studies have considered brain age prediction as a biomarker for the conversion of cognitively normal (CN) to mild cognitive impairment (MCI). In this study, we developed a novel brain age prediction model using brain volume and cortical thickness features. We calculated an acceleration of brain age (ABA) derived from the suggested model to estimate different diagnostic groups (CN, MCI, and AD) and to classify CN to MCI and MCI to AD conversion groups. We observed a strong association between ABA and the 3 diagnostic groups. Additionally, the classification models for CN to MCI conversion and MCI to AD conversion exhibited acceptable and robust performances, with area under the curve values of 0.66 and 0.76, respectively. We believe that our proposed model provides a reliable estimate of brain age for elderly individuals and can identify those at risk of progressing from CN to MCI. This model has great potential to reveal a diagnosis associated with a change in cognitive decline.

Inferring the genetic relationship between brain imaging-derived phenotypes and risk of complex diseases by Mendelian randomization and genome-wide colocalization

Observational studies consistently disclose brain imaging-derived phenotypes (IDPs) as critical markers for early diagnosis of both brain disorders and cardiovascular diseases. However, it remains unclear about the shared genetic landscape between brain IDPs and the risk of brain disorders and cardiovascular diseases, restricting the applications of potential diagnostic techniques through brain IDPs. Here, we reported genetic correlations and putative causal relationships between 921 brain IDPs, 20 brain disorders and six cardiovascular diseases by leveraging their large-scale genome-wide association study (GWAS) summary statistics. Applications of Mendelian randomization (MR) identified significant putative causal effects of multiple region-specific brain IDPs in relation to the increased risks for amyotrophic lateral sclerosis (ALS), major depressive disorder (MDD), autism spectrum disorder (ASD) and schizophrenia (SCZ). We also found brain IDPs specifically from temporal lobe as a putatively causal consequence of hypertension. The genome-wide colocalization analysis identified three genomic regions in which MDD, ASD and SCZ colocalized with the brain IDPs, and two novel SNPs to be associated with ASD, SCZ, and multiple brain IDPs. Furthermore, we identified a list of candidate genes involved in the shared genetics underlying pairs of brain IDPs and MDD, ASD, SCZ, ALS and hypertension. Our results provide novel insights into the genetic relationships between brain disorders and cardiovascular diseases and brain IDP, which may server as clues for using brain IDPs to predict risks of diseases.

Common and disorder-specific cortical thickness alterations in internalizing, externalizing and thought disorders during early adolescence: an Adolescent Brain and Cognitive Development study

BACKGROUND

A growing body of neuroimaging studies has reported common neural abnormalities among mental disorders in adults. However, it is unclear whether the distinct disorder-specific mechanisms operate during adolescence despite the overlap among disorders.

METHODS

We studied a large cohort of more than 11 000 preadolescent (age 9-10 yr) children from the Adolescent Brain and Cognitive Development cohort. We adopted a regrouping approach to compare cortical thickness (CT) alterations and longitudinal changes between healthy controls (n = 4041) and externalizing (n = 1182), internalizing (n = 1959) and thought disorder (n = 347) groups. Genome-wide association study (GWAS) was performed on regional CT across 4468 unrelated European youth.

RESULTS

Youth with externalizing or internalizing disorders exhibited increased regional CT compared with controls. Externalizing (p = 8 × 10-4, Cohen d = 0.10) and internalizing disorders (p = 2 × 10-3, Cohen d = 0.08) shared thicker CT in the left pars opercularis. The somatosensory and the primary auditory cortex were uniquely affected in externalizing disorders, whereas the primary motor cortex and higher-order visual association areas were uniquely affected in internalizing disorders. Only youth with externalizing disorders showed decelerated cortical thinning from age 10-12 years. The GWAS found 59 genome-wide significant associated genetic variants across these regions. Cortical thickness in common regions was associated with glutamatergic neurons, while internalizing-specific regional CT was associated with astrocytes, oligodendrocyte progenitor cells and GABAergic neurons.

LIMITATIONS

The sample size of the GWAS was relatively small.

CONCLUSION

Our study provides strong evidence for the presence of specificity in CT, developmental trajectories and underlying genetic underpinnings among externalizing and internalizing disorders during early adolescence. Our results support the neurobiological validity of the regrouping approach that could supplement the use of a dimensional approach in future clinical practice.

Subcortical Brain Alterations in Carriers of Genomic Copy Number Variants

OBJECTIVE

Copy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disorders (NPDs), including autism (ASD) and schizophrenia. Little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, the authors investigated gross volume, vertex-level thickness, and surface maps of subcortical structures in 11 CNVs and six NPDs.

METHODS

Subcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (CNVs at 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2; age range, 6-80 years; 340 males) and 782 control subjects (age range, 6-80 years; 387 males) as well as ENIGMA summary statistics for ASD, schizophrenia, attention deficit hyperactivity disorder, obsessive-compulsive disorder, bipolar disorder, and major depression.

RESULTS

All CNVs showed alterations in at least one subcortical measure. Each structure was affected by at least two CNVs, and the hippocampus and amygdala were affected by five. Shape analyses detected subregional alterations that were averaged out in volume analyses. A common latent dimension was identified, characterized by opposing effects on the hippocampus/amygdala and putamen/pallidum, across CNVs and across NPDs. Effect sizes of CNVs on subcortical volume, thickness, and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and schizophrenia.

CONCLUSIONS

The findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions, as well distinct effects, with some CNVs clustering with adult-onset conditions and others with ASD. These findings provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD and why a single CNV increases the risk for a diverse set of NPDs.

Association between overt aggression and anhedonia in patients with major depressive disorder during the acute phase

OBJECTIVE

To explore the factors influencing anhedonia at baseline and use them as confounding factors. To further investigate the correlation between overt aggression and anhedonia during the acute phase of major depressive disorder.

METHODS

In this eight-week prospective study, 384 major depressive disorder patients were recruited from the outpatient section of Shanghai Mental Health Center from May 1, 2017, to October 30, 2018. Standard treatments were performed with escitalopram or venlafaxine for participants. Depressive symptoms, overt aggression, and anhedonia were assessed using the 17-item Hamilton Rating Scale for Depression, Modified Overt Aggression Scale, and Snaith-Hamilton Pleasure Scale at baseline, and in the 4th and 8th weeks.

RESULTS

Obsessive-compulsive symptoms and the duration of untreated psychosis were positively associated with aggression (P < 0.05). Patients with aggressive behaviour had worse cognitive impairment and severe anhedonia of pleasurable sensory experiences (P < 0.05). For anhedonia, being female (tau_b = -0.23, P = 0.012) was a protective factor, while number of recurrent, melancholic features, current obsessions, previous combination drug therapies, depressive symptoms, and aggressive behaviour were risk factors (P < 0.05). Social anhedonia related to interests/pastimes, and pleasurable sensory experiences were more severe in major depressive disorder patients with aggressive behaviour in the acute phase (P < 0.05).

CONCLUSIONS

Anhedonia persisted in major depressive disorder patients with aggressive behaviour after standardized treatment during the acute phase. Being female protected the pleasures from social interaction and sensory experience. However, the number of depressive episodes, melancholic features, current obsessive symptoms, previous combination drug therapies, depressive symptoms, and aggressive behaviour was positively associated with anhedonia.

Neurogenetic mechanisms of risk for ADHD: Examining associations of polygenic scores and brain volumes in a population cohort

BACKGROUND

ADHD polygenic scores (PGSs) have been previously shown to predict ADHD outcomes in several studies. However, ADHD PGSs are typically correlated with ADHD but not necessarily reflective of causal mechanisms. More research is needed to elucidate the neurobiological mechanisms underlying ADHD. We leveraged functional annotation information into an ADHD PGS to (1) improve the prediction performance over a non-annotated ADHD PGS and (2) test whether volumetric variation in brain regions putatively associated with ADHD mediate the association between PGSs and ADHD outcomes.

METHODS

Data were from the Philadelphia Neurodevelopmental Cohort (N = 555). Multiple mediation models were tested to examine the indirect effects of two ADHD PGSs-one using a traditional computation involving clumping and thresholding and another using a functionally annotated approach (i.e., AnnoPred)-on ADHD inattention (IA) and hyperactivity-impulsivity (HI) symptoms, via gray matter volumes in the cingulate gyrus, angular gyrus, caudate, dorsolateral prefrontal cortex (DLPFC), and inferior temporal lobe.

RESULTS

A direct effect was detected between the AnnoPred ADHD PGS and IA symptoms in adolescents. No indirect effects via brain volumes were detected for either IA or HI symptoms. However, both ADHD PGSs were negatively associated with the DLPFC.

CONCLUSIONS

The AnnoPred ADHD PGS was a more developmentally specific predictor of adolescent IA symptoms compared to the traditional ADHD PGS. However, brain volumes did not mediate the effects of either a traditional or AnnoPred ADHD PGS on ADHD symptoms, suggesting that we may still be underpowered in clarifying brain-based biomarkers for ADHD using genetic measures.

A prospective investigation of impacts of comorbid attention deficit hyperactivity disorder (ADHD) on clinical features and long-term treatment response in adult patients with obsessive-compulsive disorder (OCD)

BACKGROUND

A close association between obsessive-compulsive disorder (OCD) and attention-deficit/hyperactivity disorder (ADHD) in children and adolescents has been investigated in previous studies. However, few studies examined the relationship between lifetime comorbidity of ADHD and OCD in adults. Therefore, we sought to investigate the clinical and psychopathological features related to comorbid ADHD in Japanese adult patients with OCD.

METHODS

We assessed lifetime comorbidity of ADHD in 93 adult Japanese patients with OCD. Additionally, we used the Japanese version of Conners' Adult ADHD Rating Scales to assess the characteristics and severity of ADHD in each participant. According to the results, we excluded OCD patients that did not have ADHD but who exhibited elevated levels of ADHD traits. We compared OCD patients with ADHD (ADHD+ group) and those without ADHD or its trait (ADHD- group) in terms of background profiles and clinical features, such as OCD symptomatology and psychometric test results. Additionally, the 6-month treatment outcome was compared prospectively between groups.

RESULTS

Of the 93 OCD participants, the prevalence of lifetime comorbidity of ADHD was estimated as 16.1%. Compared with the ADHD- group, participants in the ADHD+ group had an earlier age of onset of OCD, higher frequencies of hoarding symptoms, higher levels of depressive and anxiety symptoms and lower quality of life, more elevated levels of impulsivity, and higher rates of substance or behavioral addiction and major depression. Finally, the mean improvement rate on the Yale-Brown Obsessive Compulsive Scale after 6 months of standardized OCD treatment in the ADHD+ group (16.1%) was significantly lower than that in the ADHD- group (44.6%).

CONCLUSION

The lifetime comorbidity of ADHD is likely to exert a significant effect on clinical features and treatment outcome in adult patients with OCD. It is important to consider that underlying ADHD pathology may function as a facilitator for increased severity of global clinical features and treatment refractory conditions in OCD patients. Further studies are required to examine treatment strategies for such patients.

Feeding practice during infancy is associated with attention-deficit/hyperactivity disorder and autism spectrum disorder: a population-based study in South Korea

Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are representative neurodevelopmental disorders. Using a nationwide database, we aimed to investigate whether feeding practices in infancy (breastfeeding and the timing of supplementary food introduction) could impact ADHD or ASD development. We evaluated 1,173,448 children aged 4-6 months who were included in the National Screening Program for Infants and Children (NHSPIC) between 2008 and 2014. We observed individuals until 6-7 years of age. Data on feeding type (milk feeding: exclusive breastfeeding [EBF], partial breastfeeding [PBF], exclusive formula feeding [EFF] at 4-6 months of age; supplementary food introduction: < 6 or > 6 months of age) were obtained from the NHSPIC, and diagnoses were based on the International Classification of Diseases, Tenth Revision. In a generalized linear model, children who received EBF had significantly lower incidence of both ADHD (odds ratio [OR]: 0.77, 95% confidence interval [CI]: 0.72-0.82) and ASD (OR: 0.64, 95% CI: 0.60-0.67) than that of children who received EFF. PBF also had a significant protective effect on both ADHD (0.91; 0.85-0.98), and ASD (0.89; 0.83-0.95). The timing of supplementary food introduction was not associated with either ADHD or ASD, although there was an increased risk of ASD in the EFF infants who had supplementary food introduced at > 6 months of age.  Conclusion: Our study strengthens and supports the beneficial effect of breastfeeding on neurodevelopmental disorders in children. Breastfeeding should be encouraged and recommended to promote desirable neurodevelopmental outcomes. What is Known: • Breastfeeding is beneficial for the overall health of children, including neurodevelopmental outcomes and cognitive functions. What is New: • Breastfeeding, especially exclusive breastfeeding, was protective against neurodevelopmental disorders. • The effect of the timing of supplementary food introduction was limited.

Country-level gender inequality is associated with structural differences in the brains of women and men

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women's brains and provide initial evidence for neuroscience-informed policies for gender equality.

Parsing the heterogeneity of brain-symptom associations in autism spectrum disorder via random forest with homogeneous canonical correlation

BACKGROUND

Autism spectrum disorder (ASD) is a highly heterogeneous developmental disorder, but the neuroimaging substrates of its heterogeneity remain unknown. The difficulty lies mainly on the significant individual variability in the brain-symptom association.

METHODS

T1-weighted magnetic resonance imaging data from the Autism Brain Imaging Database Exchange (ABIDE) (N_TDC = 1146) were used to generate a normative model to map brain structure deviations of cases (N_ASD = 571). Voxel-based morphometry (VBM) was used to compute gray matter volume (GMV). Singular Value Decomposition (SVD) was employed to perform dimensionality reduction. A tree-based algorithm was proposed to identify the ASD subtypes according to the pattern of brain-symptom association as assessed by a homogeneous canonical correlation.

RESULTS

We identified 4 ASD subtypes with distinct association patterns between residual volumes and a social symptom score. More severe the social symptom was associated with greater GMVs in both the frontoparietal regions for the subtype1 (r = 0.29-0.44) and the ventral visual pathway for the subtype3 (r = 0.19-0.23), but lower GMVs in both the right anterior cingulate cortex for the subtype4 (r = -0.25) and a few subcortical regions for the subtype2 (r = -0.31-0.20). The subtyping significantly improved the classification accuracy between cases and controls from 0.64 to 0.75 (p < 0.05, permutation test), which was also better than the accuracy of 0.68 achieved by the k-means-based subtyping (p < 0.01).

LIMITATIONS

Sample size limited the study due to the missing data.

CONCLUSIONS

These findings suggest that the heterogeneity of ASD might reflect changes in different subsystems of the social brain, especially including social attention, motivation, perceiving and evaluation.

Systematic comparisons of different quality control approaches applied to three large pediatric neuroimaging datasets

INTRODUCTION

Poor quality T1-weighted brain scans systematically affect the calculation of brain measures. Removing the influence of such scans requires identifying and excluding scans with noise and artefacts through a quality control (QC) procedure. While QC is critical for brain imaging analyses, it is not yet clear whether different QC approaches lead to the exclusion of the same participants. Further, the removal of poor-quality scans may unintentionally introduce a sampling bias by excluding the subset of participants who are younger and/or feature greater clinical impairment. This study had two aims: 1) examine whether different QC approaches applied to T1-weighted scans would exclude the same participants, and 2) examine how exclusion of poor-quality scans impacts specific demographic, clinical and brain measure characteristics between excluded and included participants in three large pediatric neuroimaging samples.

METHODS

We used T1-weighted, resting-state fMRI, demographic and clinical data from the Province of Ontario Neurodevelopmental Disorders network (Aim 1: n=553, Aim 2: n=465), the Healthy Brain Network (Aim 1: n=1051, Aim 2: n=558), and the Philadelphia Neurodevelopmental Cohort (Aim 1: n=1087; Aim 2: n=619). Four different QC approaches were applied to T1-weighted MRI (visual QC, metric QC, automated QC, fMRI-derived QC). We used tetrachoric correlation and inter-rater reliability analyses to examine whether different QC approaches excluded the same participants. We examined differences in age, mental health symptoms, everyday/adaptive functioning, IQ and structural MRI-derived brain indices between participants that were included versus excluded following each QC approach.

RESULTS

Dataset-specific findings revealed mixed results with respect to overlap of QC exclusion. However, in POND and HBN, we found a moderate level of overlap between visual and automated QC approaches (r_tet=0.52-0.59). Implementation of QC excluded younger participants, and tended to exclude those with lower IQ, and lower everyday/adaptive functioning scores across several approaches in a dataset-specific manner. Across nearly all datasets and QC approaches examined, excluded participants had lower estimates of cortical thickness and subcortical volume, but this effect did not differ by QC approach.

CONCLUSION

The results of this study provide insight into the influence of QC decisions on structural pediatric imaging analyses. While different QC approaches exclude different subsets of participants, the variation of influence of different QC approaches on clinical and brain metrics is minimal in large datasets. Overall, implementation of QC tends to exclude participants who are younger, and those who have more cognitive and functional impairment. Given that automated QC is standardized and can reduce between-study differences, the results of this study support the potential to use automated QC for large pediatric neuroimaging datasets.