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The identification of distinct ADHD etiology in youths with TBI provides neurobiological insight into the clinical heterogeneity in the disorder. Results indicate that genetic predisposition to ADHD does not increase the risk for ADHD symptoms associated with TBI. ADHD symptoms associated with TBI may be a result of a mechanical insult rather than neurodevelopmental factors.

The brain-derived neurotrophic factor (BDNF) is critical for brain development, and the functional BDNF Val66Met polymorphism is implicated in risk for mood disorders. The objective of this study was to determine how the Val66Met polymorphism influences amygdala-cortical connectivity during neurodevelopment and assess the relevance for mood disorders. Age- and sex-specific effects of the BDNF Val66Met polymorphism on amygdala-cortical connectivity were assessed by examining covariance of amygdala volumes with thickness throughout the cortex in a sample of Caucasian youths ages 8-22 that were part of the Philadelphia Neurodevelopmental Cohort (n = 339). Follow-up analyses assessed corresponding BDNF genotype effects on resting-state functional connectivity (n = 186) and the association between BDNF genotype and major depressive disorder (MDD) (n = 2749). In adolescents, amygdala-cortical covariance was significantly stronger in Met allele carriers compared with Val/Val homozygotes in amygdala-cortical networks implicated in depression; these differences were driven by females. In follow-up analyses, the Met allele was also associated with stronger resting-state functional connectivity in adolescents and increased likelihood of MDD in adolescent females. The BDNF Val66Met polymorphism may confer risk for mood disorders in females through effects on amygdala-cortical connectivity during adolescence, coinciding with a period in the lifespan when onset of depression often occurs, more commonly in females.

Progressive cortical volumetric loss following moderate-severe traumatic brain injury (TBI) has been observed; however, regionally specific changes in the structural determinants of cortical volume, namely, cortical thickness (CT) and cortical surface area (CSA), are unknown and may inform the patterns and neural substrates of neurodegeneration and plasticity following injury. We aimed to (a) assess differences in CT and CSA between TBI participants and controls in the early chronic stage postinjury, (b) describe longitudinal changes in cortical morphometry following TBI, and (c) examine how regional changes in CT and CSA are associated. We acquired magnetic resonance images for 67 participants with TBI at up to 4 time-points spanning 5 months to 7 years post-injury, and 18 controls at 2 time-points. In the early chronic stage, TBI participants displayed thinner cortices than controls, predominantly in frontal regions, but no CSA differences. Throughout the chronic period, TBI participants showed widespread CT reductions in posterior cingulate/precuneus regions and moderate CT increase in frontal regions. Additionally, CSA showed a significant decrease in the orbitofrontal cortex and circumscribed increase in posterior regions.No changes were identified in controls. Relationships between regional cortical changes in the same morphological measure revealed coordinated patterns within participants, whereas correlations between regions with CT and CSA change yielded bi-directional relationships. This suggests that these measures may be differentially affected by neurodegenerative mechanisms such as transneuronal degeneration following TBI and that degeneration may be localized to the depths of cortical sulci.These findings emphasize the importance of dissecting morphometric contributions to cortical volume change.

HighlightsDeep and superficial white matter structure was altered in youths with mild TBI.Slower processing speed was associated with superficial white matter structure in TBI.Some abnormalities were more pronounced in superficial compared to deep white matter.

Structural and functional cortico-striatal-thalamic-cortical (CSTC) circuit abnormalities have been observed in schizophrenia and the clinical high-risk state. However, this circuit is sexually dimorphic and changes across neurodevelopment. We examined effects of sex and age on structural and functional properties of the CSTC circuit in a large sample of youth with and without psychosis spectrum symptoms (PSS) from the Philadelphia Neurodevelopmental Cohort. T1-weighted and resting-state functional MRI scans were collected on a 3T Siemens scanner, in addition to participants' cognitive and psychopathology data. After quality control, the total sample (aged 11-21) was n = 1095 (males = 485, females = 610). Structural subdivisions of the striatum and thalamus were identified using the MAGeT Brain segmentation tool. Functional seeds were segmented based on brain network connectivity. Interaction effects among PSS group, sex, and age on striatum, thalamus, and subdivision volumes were examined. A similar model was used to test effects on functional connectivity of the CSTC circuit. A sex by PSS group interaction was identified, whereby PSS males had higher volumes and PSS females had lower volumes in striatal and thalamic subdivisions. Reduced functional striatocortical connectivity was found in PSS youth, primarily driven by males, whereby younger male PSS youth also exhibited thalamocortical hypo-connectivity (compared to non-PSS youth), vs. striato-cortical hyper-connectivity in older male PSS youth (compared to non-PSS youth). Youth with PSS demonstrate sex and age-dependent differences in striatal and thalamic subdivision structure and functional connectivity. Further efforts at biomarker discovery and early therapeutic intervention targeting the CSTC circuit in psychosis should consider effects of sex and age.

Objective: To summarize existing knowledge about the characteristics of attention problems secondary to traumatic brain injuries (TBI) of all severities in children.Methods: Computerized databases PubMed and PsychINFO and gray literature sources were used to identify relevant studies. Search terms were selected to identify original research examining new ADHD diagnosis or attention problems after TBI in children. Studies were included if they investigated any severity of TBI, assessed attention or ADHD after brain injury, investigated children as a primary or sub-analysis, and controlled for or excluded participants with preinjury ADHD or attention problems.Results: Thirty-nine studies were included in the review. Studies examined the prevalence of and risk factors for new attention problems and ADHD following TBI in children as well as behavioral and neuropsychological factors associated with these attention problems. Studies report a wide range of prevalence rates of new ADHD diagnosis or attention problems after TBI. Evidence indicates that more severe injury, injury in early childhood, or preinjury adaptive functioning problems, increases the risk for new ADHD and attention problems after TBI and both sexes appear to be equally vulnerable. Further, literature suggests that cases of new ADHD often co-occurs with neuropsychiatric impairment in other domains. Identified gaps in our understanding of new attention problems and ADHD include if mild TBI, the most common type of injury, increases risk and what brain abnormalities are associated with the emergence of these problems.Conclusion: This scoping review describes existing studies of new attention problems and ADHD following TBI in children and highlights important risk factors and comorbidities. Important future research directions are identified that will inform the extent of this outcome across TBI severities, its neural basis and points of intervention to minimize its impact.

The heterogeneity of white matter damage and symptoms in concussions has been identified as a major obstacle to therapeutic innovation. In contrast, the vast majority of diffusion MRI studies on concussion have traditionally employed group-comparison approaches. Such studies do not consider heterogeneity of damage and symptoms in concussion. To parse concussion heterogeneity, the present study combines diffusion MRI (dMRI) and multivariate statistics to investigate multi-tract multi-symptom relationships. Using dMRI data from a sample of 306 children ages 9 and 10 with a history of concussion from the Adolescent Brain Cognitive Development Study (ABCD study), we built connectomes weighted by classical and emerging diffusion measures. These measures were combined into two informative indices, the first capturing a mixture of patterns suggestive of microstructural complexity, the second representing almost exclusively axonal density. We deployed pattern-learning algorithms to jointly decompose these connectivity features and 19 behavioural measures that capture well-known symptoms of concussions. We found idiosyncratic symptom-specific multi-tract connectivity features, which would not be captured in traditional univariate analyses. Multivariable connectome-symptom correspondences were stronger than all single-tract/single-symptom associations. Multi-tract connectivity features were also expressed equally across different sociodemographic strata and their expression was not accounted for by injury-related variables. In a replication dataset, the expression of multi-tract connectivity features predicted adverse psychiatric outcomes after accounting for other psychopathology-related variables. By defining cross-demographic multi-tract multi-symptom relationships to parse concussion heterogeneity, the present study can pave the way for the development of improved stratification strategies that may contribute to the success of future clinical trials and the improvement of concussion management.