Philip Shaw

Randomized controlled trials (RCTs) guide treatment decisions in youth with mental health disorders, yet concerns remain about their generalizability. Here we conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-compliant systematic review and meta-analysis (CRD42024629137) to assess the inclusivity and representativeness of RCTs on pharmacological and nutraceutical interventions in children and adolescents with Diagnostic and Statistical Manual of Mental Disorders and/or International Classification of Diseases-defined mental disorders. Random-effects meta-analyses were conducted by disorder, and temporal trends were assessed. Primary outcomes were the representativeness of RCTs with respect to sex (pooled proportion of female participants) and race/ethnicity (distribution of racial and ethnic groups); secondary outcomes included the exclusion of key clinical populations (for example, autistic individuals, those with intellectual disability and those with suicide risk). A total of 397 RCTs (46,989 participants; mean age 10.2 ± 3.1 years) were included, mostly targeting attention deficit hyperactivity disorder (34.5%) or autism spectrum disorder (29.7%). Female participants represented 28.3%. Only 53.7% of RCTs reported racial data; 75.0% were white, 10.1% Black, 6.2% Hispanic and 2.0% Asian. Autistic individuals and those with learning disabilities were excluded in 56.5% and 44.3% of trials, respectively; 76.0% of depression RCTs excluded participants at suicide risk. There is a persistent mismatch between the youth most affected by mental health disorders and those included in RCTs. Some vulnerable populations including people of colour, women and special populations seem to be under-represented, requiring more inclusive practice to support equitable and effective care.

Both brain and behavior undergo considerable changes during adolescence, a time synonymous with the emergence several psychiatric disorders, including mood and psychotic disorders. Multiple studies have explored the interaction between brain and behavior during childhood and adolescence, with both mixed and convergent findings between the studies. One challenge is that different longitudinal models can be applied to both the same or similar dataset and yet yield different results. Without knowing the ground truth, the best modeling approach to understanding the brain/behavior interplay during development remains unclear. Within this context, simulated datasets can provide a mechanism to test many different neurodevelopmental features, not only regarding the interplay between brain and behavior, but also how specific epidemiologic factors can influence study findings. Simulated datasets have the ‘ground truth’ relationships embedded within the models used to create these datasets. Thus, the goal of this study was to assess the epidemiologic and clinical characteristics of 15 large simulated longitudinal neuroimaging datasets, independently created from five research groups from three different continents. We found that while most of the neuroimaging and behavioral trajectories in the simulated datasets reflected growth patterns identified in the literature, there was also considerable variability between how the groups modeled the epidemiologic, clinical, and neurodevelopmental growth patterns. The conclusion is that while simulation studies are an underused strategy to test assumptions related to neurodevelopmental disorders, simulation studies require iterative approaches, testing simulated against real-world data and challenging the different assumptions associated with the neurodevelopmental models, until there is convergence between actual and simulated datasets.

Recent evidence suggests the brain’s major excitatory neurotransmitter, glutamate, plays a key role in attention-deficit/hyperactivity disorder (ADHD). Here we ask if glutamate also plays a role in the variable clinical courses of ADHD. While some children ‘grow out’ of ADHD by adolescence, others experience persistent symptoms into adulthood. Prior work implicates structural and functional differences in medial prefrontal cortex as pivotal in these different ADHD symptom courses, and we now ask if glutamate developmental change also contributes. Given the role of glutamate in neurotransmission, we also investigate potential impacts on the brain’s intrinsic connectivity. Using a glutamate-specific magnetic resonance spectroscopy sequence at 3 T, we analyzed 241 spectra on 161 participants, including 69 with persistent ADHD, 20 with remitting ADHD, and 72 never affected controls. Intrinsic functional connectivity was also assessed in a subset of 104 participants with 141 functional MRI scans. Using linear mixed models, we found an age-related increase in medial prefrontal glutamate in the persistent ADHD group which differed significantly from an age-related decrease among those who remitted and the never affected controls. Furthermore, altered prefrontal glutamate concentrations were associated with changes in intrinsic connectivity between the default mode network (which includes medial frontal cortex) and subcortical regions. These findings may indicate altered maturation of glutamate in the medial prefrontal cortex in youth with persistent ADHD.

Autism Spectrum Disorder (autism) and Attention Deficit/Hyperactivity Disorder (ADHD) often co-occur, although it remains unclear if these conditions share common neurobiological foundations or exhibit distinct alterations in resting-state brain connectivity. We conducted a cross-sectional mega-analytic comparison of functional connectivity patterns linked to autism and ADHD traits in children and adolescents (ages 6-19 years; n=10,168), with follow-up analyses considering autism (n=764 autistic; n=893 neurotypical) and ADHD diagnoses (n=2,026 ADHD; n=2,409 neurotypical). In total, 12,732 unique child and adolescent participants were included: 3,528 in both analyses, 6,640 in the trait analysis only, and 2,564 in the diagnostic analysis only. Autism traits and diagnosis were associated with reduced connectivity between the thalamus, putamen, salience/ventral attention, and frontoparietal networks, while ADHD traits showed the opposite pattern. Hyperconnectivity between the default mode and dorsal attention networks was observed in both autistic and ADHD groups relative to neurotypical individuals and associated with ADHD traits. Despite frequent co-occurrence, autism and ADHD traits exhibit distinct neural signatures, with small effect sizes indicating subtle associations.

One of the challenges in the field of neuroimaging is that we often lack knowledge about the underlying truth and whether our methods can detect developmental changes. To address this gap, five research groups around the globe created simulated datasets embedded with their assumptions of the interplay between brain development, cognition, and behavior. Each group independently created the datasets, unaware of the approaches and assumptions made by the other groups. Each group simulated three datasets with the same variables, each with 10,000 participants over 7 longitudinal waves, ranging from 7 to 20 years-of-age. The independently created datasets include demographic data, brain derived variables along with behavior and cognition variables. These datasets and code that were used to generate the datasets can be downloaded and used by the research community to apply different longitudinal models to determine the underlying patterns and assumptions where the ground truth is known.

While epigenetic modifications have been implicated in ADHD through studies of peripheral tissue, to date there has been no examination of the epigenome of the brain in the disorder. To address this gap, we mapped the methylome of the caudate nucleus and anterior cingulate cortex in post-mortem tissue from fifty-eight individuals with or without ADHD. While no single probe showed adjusted significance in differential methylation, several differentially methylated regions emerged. These regions implicated genes involved in developmental processes including neurogenesis and the differentiation of oligodendrocytes and glial cells. We demonstrate a significant association between differentially methylated genes in the caudate and genes implicated by GWAS not only in ADHD but also in autistic spectrum, obsessive compulsive and bipolar affective disorders through GWAS. Using transcriptomic data available on the same subjects, we found modest correlations between the methylation and expression of genes. In conclusion, this study of the cortico-striatal methylome points to gene and gene pathways involved in neurodevelopment, consistent with studies of common and rare genetic variation, as well as the post-mortem transcriptome in ADHD.