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No head-to-head clinical trials have been published comparing guanfacine extended release (GXR) and atomoxetine (ATX): two nonstimulants approved for the treatment of attention-deficit/hyperactivity disorder (ADHD). However, other study designs or methods could be used to indirectly compare these two medications. Matching-adjusted indirect comparison (MAIC) is a recent methodology that utilizes individual patient data (IPD) from clinical trials for one treatment and published aggregate data from another treatment to estimate the relative efficacy of both, providing rapid, reliable comparative efficacy results.
We aimed to identify markers of future affective lability in youth at bipolar disorder risk from the Pittsburgh Bipolar Offspring Study (BIOS) (n = 41, age = 14, SD = 2.30), and validate these predictors in an independent sample from the Longitudinal Assessment of Manic Symptoms study (LAMS) (n = 55, age = 13.7, SD = 1.9). We included factors of mixed/mania, irritability, and anxiety/depression (29 months post MRI scan) in regularized regression models. Clinical and demographic variables, along with neural activity during reward and emotion processing and gray matter structure in all cortical regions at baseline, were used to predict future affective lability factor scores, using regularized regression. Future affective lability factor scores were predicted in both samples by unique combinations of baseline neural structure, function, and clinical characteristics. Lower bilateral parietal cortical thickness, greater left ventrolateral prefrontal cortex thickness, lower right transverse temporal cortex thickness, greater self-reported depression, mania severity, and age at scan predicted greater future mixed/mania factor score. Lower bilateral parietal cortical thickness, greater right entorhinal cortical thickness, greater right fusiform gyral activity during emotional face processing, diagnosis of major depressive disorder, and greater self-reported depression severity predicted greater irritability factor score. Greater self-reported depression severity predicted greater anxiety/depression factor score. Elucidating unique clinical and neural predictors of future-specific affective lability factors is a step toward identifying objective markers of bipolar disorder risk, to provide neural targets to better guide and monitor early interventions in bipolar disorder at-risk youth.
Polypharmacy (the concurrent use of more than one psychoactive drug) and other combination interventions are increasingly common for treatment of severe psychiatric problems only partly responsive to monotherapy. This practice and research on it raise scientific, clinical, and ethical issues such as additive side effects, interactions, threshold for adding second drug, appropriate target measures, and (for studies) timing of randomization. One challenging area for treatment is severe child aggression. Commonly-used medications, often in combination, include psychostimulants, antipsychotics, mood stabilizers, and alpha-2 agonists, which vary considerably in terms of perceived safety and efficacy.
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.
In this study, we investigated whether intrinsic glial dysfunction contributes to the pathogenesis of schizophrenia (SCZ). Our approach was to establish humanized glial chimeric mice using glial progenitor cells (GPCs) produced from induced pluripotent stem cells derived from patients with childhood-onset SCZ. After neonatal implantation into myelin-deficient shiverer mice, SCZ GPCs showed premature migration into the cortex, leading to reduced white matter expansion and hypomyelination relative to controls. The SCZ glial chimeras also showed delayed astrocytic differentiation and abnormal astrocytic morphologies. When established in myelin wild-type hosts, SCZ glial mice showed reduced prepulse inhibition and abnormal behavior, including excessive anxiety, antisocial traits, and disturbed sleep. RNA-seq of cultured SCZ human glial progenitor cells (hGPCs) revealed disrupted glial differentiation-associated and synaptic gene expression, indicating that glial pathology was cell autonomous. Our data therefore suggest a causal role for impaired glial maturation in the development of schizophrenia and provide a humanized model for its in vivo assessment.
Astrocytic differentiation is developmentally impaired in patients with childhood-onset schizophrenia (SCZ). To determine why, we used genetic gain- and loss-of-function studies to establish the contributions of differentially expressed transcriptional regulators to the defective differentiation of glial progenitor cells (GPCs) produced from SCZ patient-derived induced pluripotent cells (iPSCs). Negative regulators of the bone morphogenetic protein (BMP) pathway were upregulated in SCZ GPCs, including BAMBI, FST, and GREM1, whose overexpression retained SCZ GPCs at the progenitor stage. SMAD4 knockdown (KD) suppressed the production of these BMP inhibitors by SCZ GPCs and rescued normal astrocytic differentiation. In addition, the BMP-regulated transcriptional repressor REST was upregulated in SCZ GPCs, and its KD similarly restored normal glial differentiation. REST KD also rescued potassium-transport-associated gene expression and K+ uptake, which were otherwise deficient in SCZ glia. These data suggest that the glial differentiation defect in childhood-onset SCZ, and its attendant disruption in K+ homeostasis, may be rescued by targeting BMP/SMAD4- and REST-dependent transcription.
High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points.
The DSM-5 separates the diagnostic criteria for mood and behavioral disorders. Both types of disorders share neurocognitive deficits of executive function and reading difficulties in childhood. Children with dyslexia also have executive function deficits, revealing a role of executive function circuitry in reading. The aim of the current study is to determine whether there is a significant relationship of functional connectivity within the fronto-parietal and cingulo-opercular cognitive control networks to reading measures for children with mood disorders, behavioral disorders, dyslexia, and healthy controls (HC).
A new multilayer-bead formulation of extended-release methylphenidate hydrochloride (MPH-MLR) has been evaluated in pharmacokinetic studies in healthy adults and in Phase III efficacy/safety studies in children and adolescents with attention deficit hyperactivity disorder (ADHD). Using available data in healthy adults, a two-input, one-compartment, first-order elimination population pharmacokinetic model was developed using nonlinear mixed-effect modeling. The model was then extended to pediatric subjects, and was found to adequately describe plasma concentration-time data for this population. A pharmacokinetic/pharmacodynamic model was also developed using change from baseline in the ADHD Rating Scale (ADHD-RS)-IV total scores from a pediatric Phase III trial and simulated plasma concentration-time data. During simulations for each MPH-MLR dose level (10-80 mg), increased body weight resulted in decreased maximum concentration. Additionally, as maximum concentration increased, ADHD-RS-IV total score improved (decreased). Knowledge of the relationship between dose, body weight, and clinical response following the administration of MPH-MLR in children and adolescents may be useful for clinicians selecting initial dosing of MPH-MLR. Additional study is needed to confirm these results.
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