Croarkin, Paul E.

Background The treatment of depression in children and adolescents is a substantial public health challenge. This study examined artificial intelligence tools for the prediction of early outcomes in depressed children and adolescents treated with fluoxetine, duloxetine, or placebo. Methods The study samples included training datasets ( N = 271) from patients with major depressive disorder (MDD) treated with fluoxetine and testing datasets from patients with MDD treated with duloxetine ( N = 255) or placebo ( N = 265). Treatment trajectories were generated using probabilistic graphical models (PGMs). Unsupervised machine learning identified specific depressive symptom profiles and related thresholds of improvement during acute treatment. Results Variation in six depressive symptoms (difficulty having fun, social withdrawal, excessive fatigue, irritability, low self‐esteem, and depressed feelings) assessed with the Children’s Depression Rating Scale‐Revised at 4–6 weeks predicted treatment outcomes with fluoxetine at 10–12 weeks with an average accuracy of 73% in the training dataset. The same six symptoms predicted 10–12 week outcomes at 4–6 weeks in (a) duloxetine testing datasets with an average accuracy of 76% and (b) placebo‐treated patients with accuracies of 67%. In placebo‐treated patients, the accuracies of predicting response and remission were similar to antidepressants. Accuracies for predicting nonresponse to placebo treatment were significantly lower than antidepressants. Conclusions PGMs provided clinically meaningful predictions in samples of depressed children and adolescents treated with fluoxetine or duloxetine. Future work should augment PGMs with biological data for refined predictions to guide the selection of pharmacological and psychotherapeutic treatment in children and adolescents with depression.

Age at depressive onset (AAO) corresponds to unique symptomatology and clinical outcomes. Integration of genome-wide association study (GWAS) results with additional “omic” measures to evaluate AAO has not been reported and may reveal novel markers of susceptibility and/or resistance to major depressive disorder (MDD). To address this gap, we integrated genomics with metabolomics using data-driven network analysis to characterize and differentiate MDD based on AAO. This study first performed two GWAS for AAO as a continuous trait in (a) 486 adults from the Pharmacogenomic Research Network-Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS), and (b) 295 adults from the Combining Medications to Enhance Depression Outcomes (CO-MED) study. Variants from top signals were integrated with 153 p180-assayed metabolites to establish multi-omics network characterizations of early (<age 18) and adult-onset depression. The most significant variant (p = 8.77 × 10−8) localized to an intron of SAMD3. In silico functional annotation of top signals (p < 1 × 10−5) demonstrated gene expression enrichment in the brain and during embryonic development. Network analysis identified differential associations between four variants (in/near INTU, FAT1, CNTN6, and TM9SF2) and plasma metabolites (phosphatidylcholines, carnitines, biogenic amines, and amino acids) in early- compared with adult-onset MDD. Multi-omics integration identified differential biosignatures of early- and adult-onset MDD. These biosignatures call for future studies to follow participants from childhood through adulthood and collect repeated -omics and neuroimaging measures to validate and deeply characterize the biomarkers of susceptibility and/or resistance to MDD development.

Abstract Background Despite its morbidity and mortality, the neurobiology of treatment-resistant depression (TRD) in adolescents and the impact of treatment on this neurobiology is poorly understood. Methods Using automatic segmentation in FreeSurfer, we examined brain magnetic resonance imaging baseline volumetric differences among healthy adolescents (n = 30), adolescents with major depressive disorder (MDD) (n = 19), and adolescents with TRD (n = 34) based on objective antidepressant treatment rating criteria. A pooled subsample of adolescents with TRD were treated with 6 weeks of active (n = 18) or sham (n = 7) 10-Hz transcranial magnetic stimulation (TMS) applied to the left dorsolateral prefrontal cortex. Ten of the adolescents treated with active TMS were part of an open-label trial. The other adolescents treated with active (n = 8) or sham (n = 7) were participants from a randomized controlled trial. Results Adolescents with TRD and adolescents with MDD had decreased total amygdala (TRD and MDD: −5%, P = .032) and caudal anterior cingulate cortex volumes (TRD: −3%, P = .030; MDD: −.03%, P = .041) compared with healthy adolescents. Six weeks of active TMS increased total amygdala volumes (+4%, P &lt; .001) and the volume of the stimulated left dorsolateral prefrontal cortex (+.4%, P = .026) in adolescents with TRD. Conclusions Amygdala volumes were reduced in this sample of adolescents with MDD and TRD. TMS may normalize this volumetric finding, raising the possibility that TMS has neurostructural frontolimbic effects in adolescents with TRD. TMS also appears to have positive effects proximal to the site of stimulation.

Introduction Tourette’s syndrome (TS) affects approximately 1% of children. This study will determine the efficacy and safety of paired comprehensive behavioural intervention for tics (CBIT) plus repetitive transcranial magnetic stimulation (rTMS) treatment in children with Tourette’s syndrome. We hypothesise that CBIT and active rTMS to the supplementary motor area (SMA) will (1) decrease tic severity, and (2) be associated with changes indicative of enhanced neuroplasticity (eg, changes in in vivo metabolite concentrations and TMS neurophysiology measures). Methods and analysis This study will recruit 50 youth with TS, aged 6–18 for a phase II, double-blind, block randomised, sham-controlled trial comparing active rTMS plus CBIT to sham rTMS plus CBIT in a 1:1 ratio. The CBIT protocol is eight sessions over 10 weeks, once a week for 6 weeks and then biweekly. The rTMS protocol is 20 sessions of functional MRI-guided, low-frequency (1 Hz) rTMS targeted to the bilateral SMA over 5 weeks (weeks 2–6). MRI, clinical and motor assessments and neurophysiological evaluations including motor mapping will be performed 1 week before CBIT start, 1 week after rTMS treatment and 1 week after CBIT completion. The primary outcome measure is Tourette’s symptom change from baseline to post-CBIT treatment, as measured by the Yale Global Tic Severity Scale. Secondary outcomes include changes in imaging, neurophysiological and behavioural markers. Ethics and dissemination Ethical approval by the Conjoint Health Research Ethics Board (REB18-0220). The results of this study will be published in peer-reviewed scientific journals, on ClinicalTrials.gov and shared with the Tourette and OCD Alberta Network. The results will also be disseminated through the Alberta Addictions and Mental Health Research Hub. Trial registration NCT03844919 .

Abstract Introduction: This case illustrates the feasibility, benefit, and putative enhanced ecological validity of performing internet-parent–child interaction therapy (I-PCIT) in the parent–child dyad's home for the treatment of behavior problems in medically ill children in the context of a global pandemic. Patient concerns: Parents of a 5-year-old girl initially presented with concerns regarding inattentiveness, physical and verbal fighting with her siblings, and getting kicked out of daycare for hitting another child. Patient also had difficulties sleeping at night. Diagnoses: Patient was diagnosed with electrical status epilepticus in sleep, frontal lobe executive function deficit, and attention deficit hyperactivity disorder. Interventions: Patient received a course of I-PCIT. Equipment included a cell phone with video capabilities connected to a videotelephony software program and set-up in the child's home by the parents. The treatment course included 8, 1-hour, weekly teaching/coaching sessions (7 of which were performed using I-PCIT) plus 1 follow-up booster session 6 months later. Outcomes: Home-based I-PCIT implementation greatly improved disruptive behaviors in a young child with electrical status epilepticus in sleep and attention deficit hyperactivity disorder. Conclusion: A combination of I-PCIT and methylphenidate allowed her to be successful at home and in a school setting. More research is needed on PCIT adaptations, such as home-based and internet-based PCIT, for medically ill children as well as treatment protocols for combined therapies.

Abstract Background Anxiety disorders such as generalized anxiety disorder (GAD) impact 10% of the US population, and many patients do not completely respond to first-line treatments (e.g., selective serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors, and psychotherapy). Given the dearth of evidence for non-pharmacologic, non-psychotherapeutic interventions, we performed a systematic review and meta-analysis of repetitive transcranial magnetic stimulation (rTMS) in adults with GAD. Methods A systematic literature review using the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines was conducted. Pre- and post-treatment anxiety scores were extracted, and a random-effects meta-analysis was conducted to determine the magnitude of improvement (standardized mean difference). Standard assessments of heterogeneity (e.g., Q-statistic, I2, and τ 2) and publication bias were performed. Results The initial search resulted in 3194 citations, of which 6 studies were included in the meta-analysis. In total, 152 patients were studied, including 97 patients who received active treatment and 55 who received sham treatment, and heterogeneity was modest (I2 13.32, Q = 5.77). In patients with GAD, rTMS produced a standardized mean difference of −1.857 (confidence interval: −2.219 to −1.494; P &lt; .001) with a prediction interval of −2.55 to −1.16. Conclusions The results suggest a robust effect of rTMS in GAD in the context of limited, heterogenous studies. Rigorously designed, randomized controlled trials of rTMS for GAD and related anxiety disorders are urgently needed. These studies will provide opportunities for biomarker development and integration of concurrent evidence-based psychotherapy to maximize results.