Efforts to identify structural brain correlates of attention-deficit/hyperactivity disorder (ADHD) have yielded inconsistent results, with no common structural biomarker emerging across studies. Methodological factors may obscure underlying brain–behavior relations in the study of ADHD symptomatology, including the use of categorical diagnoses [1], relying on behavioral ratings from a single informant, and small sample sizes. Indeed, empirically based assessment of psychopathology has revealed aspects of dimensionality with regard to many psychiatric conditions, including ADHD [2]. Further, recent reports suggest that information from multiple informants increases the validity of ADHD assessment [3]. Population-based neuroimaging studies provide the opportunity to more rigorously characterize the neurobiological underpinnings of ADHD symptomatology by using dimensional, multi-informant behavioral ratings, and by examining convergence across multiple assessment modalities—including genetic and neurocognitive domains.
Studying a population-based sample of adolescents (N = 1538; 785 females) (M = 14.53 years old, SD = 0.41), we investigated the relationship between dimensional measures of ADHD symptomatology, brain structure, and reaction time variability (RTV)—an objective index of attentional lapses [4]. Parent ratings of ADHD symptoms, adolescent self-reports of ADHD symptoms, and RTV were each negatively associated with gray matter volume (GMV) in an overlapping region of the ventromedial prefrontal cortex (vmPFC). To our knowledge, this study represents the largest voxel-based morphometry (VBM) study to date on adolescent ADHD symptomatology. Despite modest correlations between multi-informant behavioral ratings (r = 0.36–0.66), we observed striking convergence in the vmPFC with regard to the anatomical correlates of each behavioral measure. Similarly, while RTV was weakly correlated with behavioral ratings of ADHD symptomatology (r = 0.11–0.14), there was considerable overlap with regard to anatomical correlates. Given convergence across dimensional, multi-informant behavioral ratings, and a measure of neurocognitive functioning that has been previously tied to ADHD, our findings indicate that vmPFC structure is a brain-based marker for inattention in adolescents.
Utilizing gene expression data collected as part of the Allen Human Brain Atlas [5], we found that the statistical map representing the relationship between GMV and ADHD symptomatology was differentially correlated with patterns of DRD1 and DRD2 gene expression. Our results appear consistent with models of cognitive dysfunction that postulate relative imbalance between D1 and D2 systems; however, it is important to emphasize that these gene expression analyses were meant to be hypothesis-generating in nature. More comprehensive studies of gene expression represent a plausible direction for future research.
The National Institute of Mental Health has placed growing emphasis on the need to, “identify and validate biomarkers and novel treatment targets relevant to the prevention, treatment, and recovery of psychiatric disorders,” as evidenced by the new Computational Psychiatry Program (https://www.nimh.nih.gov/about/organization/dtr/adult-psychopathology-and-psychosocial-interventions-research-branch/computational-psychiatry-program.shtml). An exciting avenue of our research has been to examine the extent to which vmPFC structure during adolescence predicts subsequent symptom trajectories into adulthood. Using data from the 5-year follow-up wave of the IMAGEN study, we found that adolescent vmPFC volume predicts adult ADHD symptomatology while controlling for baseline symptomatology [6]. Intriguingly, these latter results suggest that early structural development of the vmPFC may be consequential for the subsequent expression of hyperactive/inattentive symptoms in adulthood.
Acknowledgements
This work received support from the following sources: the European Union-funded FP6 Integrated Project IMAGEN (Reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the FP7 projects IMAGEMEND (602450; IMAging GEnetics for MENtal Disorders), AGGRESSOTYPE (602805) and MATRICS (603016), the Innovative Medicine Initiative Project EU-AIMS (115300-2), the Medical Research Council Grants “Developmental pathways into adolescent substance abuse” (93558) and Consortium on Vulnerability to Externalizing Disorders and Addictions [c-VEDA] (MR/N000390/1), the Swedish funding agencies VR, FORTE, and FORMAS, the Medical Research Council and the Wellcome Trust (Behavioural and Clinical Neuroscience Institute, University of Cambridge), the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152; 01EV0711; eMED SysAlc01ZX1311A; Forschungsnetz AERIAL), the Deutsche Forschungsgemeinschaft (DFG grants SM 80/7-1, SM 80/7-2, SFB 940/1), the National Institutes of Health, USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1), and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. ASP is supported by P20GM103644 (PI: Stephen T. Higgins), Agency: NIGMS Vermont Center on Behavior and Health.
Competing interests
The authors declare no competing interests.
Footnotes
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