The neurobehavioral, environmental and genetic factors impacting ADHD.

National Human Genome Research Institute

Investigators

Linked publications, trials & patents

Abstract

This report details progress towards our overarching aim of understanding the interplay between behavioral, social, genetic and brain factors in development. Much of our research focuses on how attention deficit hyperactivity disorder (ADHD) may impact on brain development. In 2022-2023, we undertook two major project. In the first, our group has focused on integrating findings from our NHGRI-based cohort on how brain differences are tied to ADHD with data from other, similar childhood cohorts. A second strand of work over the past year sought to examine the many associations between ADHD and the brain that our group, and many others, have reported over the years. We asked: are these neural differences the cause of ADHD onset, or are they secondary to symptoms? And what is the direction of the relationship between brain and ADHD over time: do early childhood neural and cognitive features drive later ADHD symptoms, or are early symptoms the drivers of later neurocognitive anomalies? We addressed these questions by applying approaches such as Mendelian randomization and cross lag panel analysis. 1. Brain differences in ADHD across multiple cohorts. While my groups earlier work (2006 to 2016) examined neuroanatomic features, we now focus on the brains functional networks, defined by intrinsic, coordinated patterns of activation (the Blood Oxygenation Level Dependent signal) that emerge during a task-free period, as measured by functional MRI . We also use diffusion tensor imaging, to measure the microstructural properties of the structural connections, composed of white matter tracts, within and between these functional networks. We have employed a model of ADHD as the result of dysregulated connectivity between the task-oriented networks that support attention/cognitive control and the default-mode network that is prominent during task-free, introspective processing An analogy is that the online activity of the brain is repeatedly interrupted by the brain going offline, leading to attention lapses, mind wandering and impulsivity. The literature on cross-sectional studies has given mixed support for this model, likely as many studies had modest sample sizes, usually less than a hundred. To address this limitation, my group has obtained data on over 10,000 youth from multiple cohorts allowing us to detect the functional and structural connectivity anomalies tied to ADHD that are present across multiple, independent datasets. We thus were able to integrate data from our NHGRI-based cohort (of around 400 subjects) with data from multiple different sites. In brief, we found modest support for the model of ADHD as associated with altered interactions between brain networks. Specifically, we found support for the concept of ADHD as tied to atypical interactions between the default mode and task positive networks. ADHD traits ascertained by parental questionnaires were associated with less anti-correlation between the default mode and dorsal attention network (and between the default mode and ventral attention network. Similar effects emerged in case-control contrasts of youth with the diagnosis of ADHD compared to unaffected youth, one-to-one matched on age, sex, race/ethnicity and in-scanner motion. POur findings also held when examining only those with ADHD who were not taking medication, when cases and controls were matched one-to-one on comorbid symptoms of anxiety and depression. We are now extending this work to examine ADHD related alterations in functional connections between subcortical regions, specifically the basal ganglia and amygdala, and the cortex. We also examined structural connectivity changes seen in ADHD, using in vivo diffusion tensor imaging. Both trait measures of attention problems and the diagnosis of ADHD were associated with altered structural connectivity as measured by microstructure of the white matter tracts connecting key components of the brains attentional networks. The strongest associations with both ADHD traits and for the diagnosis of ADHD were for the left inferior longitudinal and uncinate fasciculi, with small effect sizes for trait associations and slightly larger effect sizes for case-control differences. These tracts form part the structural backbone of the ventral attention and default mode networks Our findings add to the emerging consensus that the cross-sectional neural changes detectable by current neuroimaging modalities in a complex phenotype such as ADHD are associated with small effect sizes, making large imaging sample sizes and replication paramount. Publications. PMC9751118 and PMID: 36609028. 2. Towards causal inferences. In our second project we leveraged available GWAS data and used two-sample bidirectional Mendelian randomization to parse possible causal associations between ADHD and neural This approach uses genetic variants as instrumental variables to assess potential causal relationships between an exposure (such as liability to ADHD) and an outcome (such as neural connectivity features). We found a causal effect on ADHD risk for SNPs associated with a functional network that connected posterior regions of the default mode, central executive and salience networks. Greater expression of this functional network was associated with a lower risk of ADHD and we found no evidence of horizontal pleiotropy and no outliers. This work suggests that functional connectivity between the default mode and some task-positive networks, previously merely associated with ADHD, may play a causal role in its onset. Bidirectional links emerged between ADHD and both major depression and autistic spectrum disorders. We have also started to parse the direction of the relationship over time between the brain and ADHD symptoms, using data from our deeply phenotyped NHGRI cohort, Specifically, on 167 youth, (each with two assessments a mean of 2.5 years apart, SD 1) we estimated functional connectivity as eigenvector centrality, a summary measure of the connectivity of each brain voxel with the remaining voxels of the brain. Using voxel-wise cross-lag panel modeling, we found that less connectivity at baseline within a region of the ventral attention network (the right inferior frontal gyrus) was associated with more symptoms of inattention at follow-up. By contrast, the cross-lag pathway from baseline inattention to later functional connectivity was not significant, In short, early neural connectivity anomalies had a cross-lagged relationship with symptoms, but not vice versa. We now extend this work by including more observations, multiple cohorts and refine our analytic approaches. Key publications. PMC9463186 and PMC9560913.