Relationship of persistent manic symptoms to the diagnosis of pediatric bipolar spectrum disorders

Neurobehavioral Reward and Sleep-Circadian Profiles Predict Present and Next-Year Mania/Hypomania Symptoms

BACKGROUND

Heightened reward sensitivity/impulsivity, related neural activity, and sleep-circadian disruption are important risk factors for bipolar spectrum disorders, the defining feature of which is mania/hypomania. Our goal was to identify neurobehavioral profiles based on reward and sleep-circadian features and examine their specificity to mania/hypomania versus depression vulnerability.

METHODS

At baseline, a transdiagnostic sample of 324 adults (18-25 years) completed trait measures of reward sensitivity (Behavioral Activation Scale), impulsivity (UPPS-P-Negative Urgency), and a functional magnetic resonance imaging card-guessing reward task (left ventrolateral prefrontal activity to reward expectancy, a neural correlate of reward motivation and impulsivity, was extracted). At baseline, 6-month follow-up, and 12-month follow-up, the Mood Spectrum Self-Report Measure - Lifetime Version assessed lifetime predisposition to subthreshold-syndromal mania/hypomania, depression, and sleep-circadian disturbances (insomnia, sleepiness, reduced sleep need, rhythm disruption). Mixture models derived profiles from baseline reward, impulsivity, and sleep-circadian variables.

RESULTS

Three profiles were identified: 1) healthy (no reward or sleep-circadian disruption; n = 162); 2) moderate-risk (moderate reward and sleep-circadian disruption; n = 109); and 3) high-risk (high impulsivity and sleep-circadian disruption; n = 53). At baseline, the high-risk group had significantly higher mania/hypomania scores than the other groups but did not differ from the moderate-risk group in depression scores. Over the follow-up period, the high-risk and moderate-risk groups exhibited elevated mania/hypomania scores, whereas depression scores increased at a faster rate in the healthy group than in the other groups.

CONCLUSIONS

Cross-sectional and next-year predisposition to mania/hypomania is associated with a combination of heightened reward sensitivity and impulsivity, related reward circuitry activity, and sleep-circadian disturbances. These measures can be used to detect mania/hypomania risk and provide targets to guide and monitor interventions.

Using machine learning and surface reconstruction to accurately differentiate different trajectories of mood and energy dysregulation in youth

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.

Evaluation of Bipolar Disorder in Children and Adolescents Referred to a Mood Service: Diagnostic Pathways and Manic Dimensions

OBJECTIVES

Few studies have examined pediatric mental health services for early-onset bipolar disorder (BD). The goal of this study was to describe diagnostic pathways and manic dimensions in BD among referred children and adolescents.

METHODS

Data were obtained from a review of the charts of 814 subjects, 2 to 17 years of age, with a complaint of mood disturbances who were referred between 2003 and 2012 to a university-based child and adolescent clinic that specializes in mood disorders. After screening, eligible participants (N=494) were systematically assessed and followed to determine diagnoses on the basis of criteria in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision in accordance with the best-estimate approach. Manic symptoms were subjected to principal component analysis to investigate the dimensional bipolar profile of the sample.

RESULTS

Among the total help-seeking sample, approximately one third of the participants dropped out at intake and, after an average follow-up of 1.7 years, one third had been determined to meet criteria for BD and one third did not fulfill operational criteria for BD. The diagnostic status was changed in 35% of patients: approximately 10% were false positive (going from any bipolar diagnosis to a nonbipolar diagnosis) and approximately 25% were false negative (going from a nonbipolar diagnosis to any bipolar diagnosis). Most patients who converted to a bipolar diagnosis were initially labeled with major depressive disorder or attention-deficit/hyperactivity disorder and had a longer follow-up period. Relevant manic dimensions were elation, grandiosity, and disruption, which explained 41.4% of total variance.

CONCLUSIONS

Regular reappraisal and follow-up of children and adolescents with mood disturbances provides a window for detection of BD (eg, of core manic dimensions). A coordinated and hierarchical connection among pediatric mental health services with different degrees of specialization is recommended.

Predicting clinical outcome from reward circuitry function and white matter structure in behaviorally and emotionally dysregulated youth

Behavioral and emotional dysregulation in childhood may be understood as prodromal to adult psychopathology. Additionally, there is a critical need to identify biomarkers reflecting underlying neuropathological processes that predict clinical/behavioral outcomes in youth. We aimed to identify such biomarkers in youth with behavioral and emotional dysregulation in the Longitudinal Assessment of Manic Symptoms (LAMS) study. We examined neuroimaging measures of function and white matter in the whole brain using 80 youth aged 14.0 (s.d.=2.0) from three clinical sites. Linear regression using the LASSO (Least Absolute Shrinkage and Selection Operator) method for variable selection was used to predict severity of future behavioral and emotional dysregulation measured by the Parent General Behavior Inventory-10 Item Mania Scale (PGBI-10M)) at a mean of 14.2 months follow-up after neuroimaging assessment. Neuroimaging measures, together with near-scan PGBI-10M, a score of manic behaviors, depressive behaviors and sex, explained 28% of the variance in follow-up PGBI-10M. Neuroimaging measures alone, after accounting for other identified predictors, explained ~1/3 of the explained variance, in follow-up PGBI-10M. Specifically, greater bilateral cingulum length predicted lower PGBI-10M at follow-up. Greater functional connectivity in parietal-subcortical reward circuitry predicted greater PGBI-10M at follow-up. For the first time, data suggest that multimodal neuroimaging measures of underlying neuropathologic processes account for over a third of the explained variance in clinical outcome in a large sample of behaviorally and emotionally dysregulated youth. This may be an important first step toward identifying neurobiological measures with the potential to act as novel targets for early detection and future therapeutic interventions.

Behavioral and emotional dysregulation trajectories marked by prefrontal-amygdala function in symptomatic youth

BACKGROUND

Neuroimaging measures of behavioral and emotional dysregulation can yield biomarkers denoting developmental trajectories of psychiatric pathology in youth. We aimed to identify functional abnormalities in emotion regulation (ER) neural circuitry associated with different behavioral and emotional dysregulation trajectories using latent class growth analysis (LCGA) and neuroimaging.

METHOD

A total of 61 youth (9-17 years) from the Longitudinal Assessment of Manic Symptoms study, and 24 healthy control youth, completed an emotional face n-back ER task during scanning. LCGA was performed on 12 biannual reports completed over 5 years of the Parent General Behavior Inventory 10-Item Mania Scale (PGBI-10M), a parental report of the child's difficulty regulating positive mood and energy.

RESULTS

There were two latent classes of PGBI-10M trajectories: high and decreasing (HighD; n=22) and low and decreasing (LowD; n=39) course of behavioral and emotional dysregulation over the 12 time points. Task performance was >89% in all youth, but more accurate in healthy controls and LowD versus HighD (p<0.001). During ER, LowD had greater activity than HighD and healthy controls in the dorsolateral prefrontal cortex, a key ER region, and greater functional connectivity than HighD between the amygdala and ventrolateral prefrontal cortex (p's<0.001, corrected).

CONCLUSIONS

Patterns of function in lateral prefrontal cortical-amygdala circuitry in youth denote the severity of the developmental trajectory of behavioral and emotional dysregulation over time, and may be biological targets to guide differential treatment and novel treatment development for different levels of behavioral and emotional dysregulation in youth.

Predicting bipolar disorder on the basis of phenomenology: implications for prevention and early intervention

OBJECTIVE

Bipolar disorder is a multifaceted illness and there is often a substantial delay between the first onset of symptoms and diagnosis. Early detection has the potential to curtail illness progression and disorder-associated burden but it requires a clear understanding of the initial bipolar prodrome. This article summarizes the phenomenology of bipolar disorder with an emphasis on the initial prodrome, the evolution of the illness, and the implications for prevention and early intervention.

METHODS

A literature review was undertaken using Medline, Web of Science, and a hand search of relevant literature using keywords (e.g., phenomenology, initial or early symptoms, risk factors, and predictors/prediction). Findings from the literature were reviewed and synthesized and have been put into a clinical context.

RESULTS

Bipolar disorder is a recurrent, persistent, and disabling illness that typically develops in adolescence or early adulthood. The literature search yielded 28 articles, in which mood lability, nonspecific, non-mood symptoms, and cyclothymic temperament were the most cited prodromal features.

CONCLUSIONS

A small number of key prospective studies have provided evidence in support of an initial bipolar prodrome; however, methodological differences across studies have prohibited its clear delineation. It is, therefore, not currently possible to anticipate those who will develop bipolar disorder solely on the basis of early phenomenology. Accurate characterization of the bipolar disorder prodrome through high-quality, prospective research studies with adequate control groups will ultimately facilitate prompt and accurate diagnosis.

Do sub-syndromal manic symptoms influence outcome in treatment resistant depression in adolescents? A latent class analysis from the TORDIA study

BACKGROUND

To identify distinct depressive symptom trajectories in the TORDIA study and determine their correlates.

METHODS

Latent Class Growth Analysis (LCGA) using the Children's Depression Rating Scale-Revised (CDRS-R) through 72 weeks from intake.

RESULTS

3 classes were identified: (1) little change in symptomatic status ("NO"), comprising 24.9% of participants, with a 72-week remission rate of 25.3%; (2) slow, steady improvement ("SLOW"), comprising 47.9% of participants, with a remission rate of 60.0%, and (3) rapid symptom response ("GO"), comprising 27.2% of participants, with a remission rate of 85.7%. Higher baseline CDRS-R (p<0.001) and poorer functioning (p=0.03) were the strongest discriminators between NO and GO. Higher baseline CDRS (p<0.001) and scores on the Mania Rating Scale (MRS) (p=0.01) were the strongest discriminators between SLOW and GO. Other variables differentiating GO from both NO and from SLOW, were better baseline functioning, lower hopelessness, and lower family conflict. Both NO and SLOW showed increases on the MRS over time compared to GO (ps ≤ 0.04), and increasing MRS was strongly associated with lack of remission by 72 weeks (p=0.02).

LIMITATIONS

High rate of open treatment by the end of the follow-up period creates difficulty in drawing clear inferences about the long-term impact of initial randomization.

CONCLUSION

Along with depressive severity, sub-syndromal manic symptoms, at baseline, and over time emerged as important predictors and correlates of poor outcome in this sample. Further research is needed on the treatment of severe depression, and on the assessment and management of sub-syndromal manic symptoms in treatment resistant depression.