Abstract
Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy regulation in youth. Recent studies indicate that machine learning techniques can help elucidate the role of neuroimaging measures in classifying individual subjects by specific symptom trajectory. Cortical thickness measures were extracted in sixty-eight anatomical regions covering the entire brain in 115 participants from the Longitudinal Assessment of Manic Symptoms (LAMS) study and 31 healthy comparison youth (12.5 y/o;-Male/Female = 15/16;-IQ = 104;-Right/Left handedness = 24/5). Using a combination of trajectories analyses, surface reconstruction, and machine learning techniques, the present study aims to identify the extent to which measures of cortical thickness can accurately distinguish youth with higher (n = 18) from those with lower (n = 34) trajectories of manic-like behaviors in a large sample of LAMS youth (n = 115; 13.6 y/o; M/F = 68/47, IQ = 100.1, R/L = 108/7). Machine learning analyses revealed that widespread cortical thickening in portions of the left dorsolateral prefrontal cortex, right inferior and middle temporal gyrus, bilateral precuneus, and bilateral paracentral gyri and cortical thinning in portions of the right dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, and right parahippocampal gyrus accurately differentiate (Area Under Curve = 0.89;p = 0.03) youth with different (higher vs lower) trajectories of positive mood and energy dysregulation over a period up to 5years, as measured by the Parent General Behavior Inventory-10 Item Mania Scale. Our findings suggest that specific patterns of cortical thickness may reflect transdiagnostic neural mechanisms associated with different temporal trajectories of positive mood and energy dysregulation in youth. This approach has potential to identify patterns of neural markers of future clinical course.
Highlights
A Longitudinal Assessment of Manic Symptoms (LAMS) study cortex(including the caudal middle frontal gyrus), left ventrolateral prefrontal cortex and right parahippocampal gyrus accurately distinguished LAMS youth with higher, from those with lower, PGBI-10M trajectories
In the present study we did not focus on single diagnoses, but rather looked at different trajectories of positive mood and energy dysregulation up to five years that cut across diagnoses
This might in part explain the differences in findings of the present study with those observed in Gogtay et al Decreases in frontal cortical thickness in adolescents with bipolar spectrum disorders (BPSD) relative to healthy control youth were reported,[51] but only generic measures of cortical thickness for frontal, temporal and parietal lobes were provided in this latter study
Summary
Difficulty regulating positive mood and energy is a feature of pediatric bipolar spectrum disorders (BPSD),[1,2,3] and of other psychiatric disorders in youth, including other mood disorders,[2, 4,5,6] attention deficit hyperactivity disorder (ADHD)[4, 7,8,9,10] and oppositional defiant disorders (ODD).[4, 11] It is present in youth without a psychiatric diagnosis.[12,13,14] Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy regulation over time, and how these trajectories predispose youth to specific future psychiatric disorders. In LAMS youth, having a higher PGBI-10M score (!12) at study entry was associated with high risk of developing BPSD,[21] as well as other severe psychopathology[2, 22] and disorders[15, 16] in the future
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