Development of Cortical Surface Area and Gyrification in Attention-Deficit/Hyperactivity Disorder

Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland 20892, USA.
Biological psychiatry (Impact Factor: 10.26). 03/2012; 72(3):191-7. DOI: 10.1016/j.biopsych.2012.01.031
Source: PubMed


Delineation of the cortical anomalies underpinning attention-deficit/hyperactivity disorder (ADHD) can powerfully inform pathophysiological models. We previously found that ADHD is characterized by a delayed maturation of prefrontal cortical thickness. We now ask if this extends to the maturation of cortical surface area and gyrification.
Two hundred thirty-four children with ADHD and 231 typically developing children participated in the study, with 837 neuroanatomic magnetic resonance images acquired longitudinally. We defined the developmental trajectories of cortical surfaces and gyrification and the sequence of cortical maturation, as indexed by the age at which each cortical vertex attained its peak surface area.
In both groups, the maturation of cortical surface area progressed in centripetal waves, both lateral (starting at the central sulcus and frontopolar regions, sweeping toward the mid and superior frontal gyrus) and medial (descending down the medial prefrontal cortex, toward the cingulate gyrus). However, the surface area developmental trajectory was delayed in ADHD. For the right prefrontal cortex, the median age by which 50% of cortical vertices attained peak area was 14.6 years (SE = .03) in ADHD, significantly later than in typically developing group at 12.7 years (SE = .03) [log-rank test χ(¹)² = 1300, p < .00001]. Similar, but less pronounced, delay was found in the left hemispheric lobes. There were no such diagnostic differences in the developmental trajectories of cortical gyrification.
The congruent delay in cortical thickness and surface area direct attention away from processes that selectively affect one cortical component toward mechanisms controlling the maturation of multiple cortical dimensions.

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Available from: Alan Charles Evans, Dec 27, 2013
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    • "Delayed cortical maturation is common to several developmental disorders (Shaw et al. 2010). However, developmental trajectories may look different at later points in the lifespan; for example in children with ADHD, (Shaw et al. 2012) found a delay in the age at which childhood increase in cortical thickness gives way to cortical thinning, similar to the delayed reduction in GM concentration seen in De Brito et al. (2009). However, a longitudinal study including adults with ADHD symptoms found that by adulthood , symptom severity was associated with reduced GM thickness (Shaw et al. 2013). "
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    ABSTRACT: Genetic, behavioural and functional neuroimaging studies have revealed that different vulnerabilities characterise children with conduct problems and high levels of callous-unemotional traits (CP/HCU) compared with children with conduct problems and low callous-unemotional traits (CP/LCU). We used voxel-based morphometry to study grey matter volume (GMV) in 89 male participants (aged 10-16), 60 of whom exhibited CP. The CP group was subdivided into CP/HCU (n = 29) and CP/LCU (n = 31). Whole-brain and regional GMV were compared across groups (CP vs. typically developing (TD) controls (n = 29); and CP/HCU vs. CP/LCU vs. TD). Whole-brain analyses showed reduced GMV in left middle frontal gyrus in the CP/HCU group compared with TD controls. Region-of-interest analyses showed reduced volume in bilateral orbitofrontal cortex (OFC) in the CP group as a whole compared with TD controls. Reduced volume in left OFC was found to be driven by the CP/HCU group only, with significant reductions relative to both TD controls and the CP/LCU group, and no difference between these latter two groups. Within the CP group left OFC volume was significantly predicted by CU traits, but not conduct disorder symptoms. Reduced right anterior cingulate cortex volume was also found in CP/HCU compared with TD controls. Our results support previous findings indicating that GMV differences in brain regions central to decision-making and empathy are implicated in CP. However, they extend these data to suggest that some of these differences might specifically characterise the subgroup with CP/HCU, with GMV reduction in left OFC differentiating children with CP/HCU from those with CP/LCU.
    Journal of Abnormal Child Psychology 09/2015; DOI:10.1007/s10802-015-0073-0 · 3.09 Impact Factor
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    • "c o m / l o c a t e / y n i m g developing youths as compared to 10.5 years in attention deficit hyperactivity disorder (ADHD)—indicating a cortical maturation delay (Shaw et al., 2007). The delay was also observed with cortical surface area and gyrification (Shaw et al., 2012). Douaud and colleagues reported delayed gray and white-matter neurodevelopment in patients with schizophrenia as compared to healthy controls (Douaud et al., 2009). "
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    ABSTRACT: Background: Major psychiatric disorders are increasingly being conceptualized as 'neurodevelopmental', because they are associated with aberrant brain maturation. Several studies have hypothesized that a brain maturation index integrating patterns of neuroanatomical measurements may reliably identify individual subjects deviating from a normative neurodevelopmental trajectory. However, while recent studies have shown great promise in developing accurate brain maturation indices using neuroimaging data and multivariate machine learning techniques, this approach has not been validated using a large sample of longitudinal data from children and adolescents. Methods: T1-weighted scans from 303 healthy subjects aged 4.88 to 18.35years were acquired from the National Institute of Health (NIH) pediatric repository ( Out of the 303 subjects, 115 subjects were re-scanned after 2years. The least absolute shrinkage and selection operator algorithm (LASSO) was 'trained' to integrate neuroanatomical changes across chronological age and predict each individual's brain maturity. The resulting brain maturation index was developed using first-visit scans only, and was validated using second-visit scans. Results: We report a high correlation between the first-visit chronological age and brain maturation index (r=0.82, mean absolute error or MAE=1.69years), and a high correlation between the second-visit chronological age and brain maturation index (r=0.83, MAE=1.71years). The brain maturation index captured neuroanatomical volume changes between the first and second visits with an MAE of 0.27years. Conclusions: The brain maturation index developed in this study accurately predicted individual subjects' brain maturation longitudinally. Due to its strong clinical potentials in identifying individuals with an abnormal brain maturation trajectory, the brain maturation index may allow timely clinical interventions for individuals at risk for psychiatric disorders.
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    • "Emerging literature suggests an important role of FPCN in the pathophysiology of ADHD. Previous structural imaging studies consistently report abnormal morphometry (Nakao, Radua, Rubia, & Mataix-Cols, 2011) and developmental trajectories (Shaw et al., 2012) in the prefrontal, cingulate and parietal structures in ADHD. Both qualitative review (Rubia, 2011) and meta-analyses (Cortese et al., 2012; Hart, Radua, Nakao, Mataix-Cols, Rubia, 2013) on task-fMRI document hypoactivation of the components within the FPCN in ADHD across tasks. "
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