Discrete patterns of cortical thickness in youth with bipolar disorder differentially predict treatment response to quetiapine but not lithium

Imaging Biomarker Studies of Antipsychotic-Naïve First-Episode Schizophrenia in China: Progress and Future Directions

BACKGROUND AND HYPOTHESIS

Identifying biomarkers at onset and specifying the progression over the early course of schizophrenia is critical for better understanding of illness pathophysiology and providing novel information relevant to illness prognosis and treatment selection. Studies of antipsychotic-naïve first-episode schizophrenia in China are making contributions to this goal.

STUDY DESIGN

A review was conducted for how antipsychotic-naïve first-episode patients were identified and studied, the investigated biological measures, with a focus on neuroimaging, and how they extend the understanding of schizophrenia regarding the illness-related brain abnormality, treatment effect characterization and outcome prediction, and subtype discovery and patient stratification, in comparison to findings from western populations. Finally, how biomarker studies should be conducted in the future was also discussed.

STUDY RESULTS

Gray matter reduction has been most robust within temporo-frontal regions and cerebellum, whereas altered brain function has been most pronounced in cerebello-cortical connections and default mode network, each might be related to long-standing illness alterations and acute physiological alterations at measurement. By studying untreated patients, the progressive alterations in temporal and frontal regions and enlargements in bilateral putamen were found more likely effects of illness, not just treatment. Some of these changes were found with potential to predict clinical outcomes and differentiate biologically patient subgroups.

CONCLUSIONS

Mostly with data-driven approaches, the studies from China are helping identify candidate imaging biomarkers in schizophrenia that are related to early-stage illness, treatment effects, and biological subgroup differentiation. Future work is needed to translate these biomarkers for clinical application.

Mapping Structural Neuroimaging Trajectories in Bipolar Disorder: Neurobiological and Clinical Implications

Neuroimaging is a powerful noninvasive method for studying brain alterations in bipolar disorder (BD). To date, most neuroimaging studies of BD have included smaller cross-sectional samples reporting case versus control comparisons, revealing small to moderate effect sizes. In this narrative review, we discuss the current state of structural neuroimaging studies using magnetic resonance imaging, which inform our understanding of altered brain trajectories in BD across the lifespan. Alternative methodologies such as those that model patient deviations from age-specific norms are discussed, which may help derive new markers of BD pathophysiology. We discuss evidence from neuroimaging genetics and transcriptomics studies, which attempt to bridge the gap between macroscale brain variations and underlying microscale neurodevelopmental mechanisms. We conclude with a look toward the future and how ambitious investments in longitudinal, deeply phenotyped, population-based cohorts can improve modeling of complex clinical factors and provide more clinically actionable brain markers for BD.

Understanding Pediatric Bipolar Disorder Through the Investigation of Clinical, Neuroanatomic, Neurophysiological and Neurocognitive Dimensions: A Pilot Study

Background: Pathophysiological models of pediatric bipolar disorder (PBD) are lacking. Multimodal approaches may provide a comprehensive description of the complex relationship between the brain and behavior. Aim: To assess behavioral, neuropsychological, neurophysiological, and neuroanatomical alterations in youth with PBD. Methods: Subjects with PBD (n = 23) and healthy controls (HCs, n = 23) underwent (a) clinical assessments encompassing the severity of psychiatric symptoms, (b) neuropsychological evaluation, (c) analyses of event-related potentials (related to the passive viewing of fearful, neutral, and happy faces during electroencephalography recording, and (d) cortical thickness and deep gray matter volume measurement using magnetic resonance imaging. Canonical correlation analyses were used to assess the relationships between these dimensions. Results: Youth with PBD had higher levels of anxiety (p < 0.001) and borderline personality features (p < 0.001), greater commission errors for negative stimuli (p = 0.003), delayed deliberation time (p < 0.001), and smaller risk adjustment scores (p = 0.002) than HCs. Furthermore, they showed cortical thinning in the frontal, parietal, and occipital areas (all p < 0.001) and greater P300 for happy faces (p = 0.29). In youth with PBD, cortical thickening and P300 amplitude positively correlated with more commission errors for negative stimuli, longer deliberation times, reduced risk adjustment, higher levels of panic and separation anxiety, and greater levels of negative relationships, whereas they negatively correlated with levels of depression (overall loadings > or <0.3). Limitations: Small sample size, cross-sectional design, and limited variables investigated. Conclusions: This preliminary work showed that multimodal assessment might be a viable tool for providing a pathophysiological model that unifies brain and behavioral alterations in youth with PBD.

A 10-Year Longitudinal Study of Brain Cortical Thickness in People with First-Episode Psychosis Using Normative Models

BACKGROUND

Clinical forecasting models have potential to optimize treatment and improve outcomes in psychosis, but predicting long-term outcomes is challenging and long-term follow-up data are scarce. In this 10-year longitudinal study, we aimed to characterize the temporal evolution of cortical correlates of psychosis and their associations with symptoms.

DESIGN

Structural magnetic resonance imaging (MRI) from people with first-episode psychosis and controls (n = 79 and 218) were obtained at enrollment, after 12 months (n = 67 and 197), and 10 years (n = 23 and 77), within the Thematically Organized Psychosis (TOP) study. Normative models for cortical thickness estimated on public MRI datasets (n = 42 983) were applied to TOP data to obtain deviation scores for each region and timepoint. Positive and Negative Syndrome Scale (PANSS) scores were acquired at each timepoint along with registry data. Linear mixed effects models assessed effects of diagnosis, time, and their interactions on cortical deviations plus associations with symptoms.

RESULTS

LMEs revealed conditional main effects of diagnosis and time × diagnosis interactions in a distributed cortical network, where negative deviations in patients attenuate over time. In patients, symptoms also attenuate over time. LMEs revealed effects of anterior cingulate on PANSS total, and insular and orbitofrontal regions on PANSS negative scores.

CONCLUSIONS

This long-term longitudinal study revealed a distributed pattern of cortical differences which attenuated over time together with a reduction in symptoms. These findings are not in line with a simple neurodegenerative account of schizophrenia, and deviations from normative models offer a promising avenue to develop biomarkers to track clinical trajectories over time.

Association of BDNF risk variant and dorsolateral cortical thickness with long-term treatment response to valproate in type I bipolar disorder: An exploratory study

Valproate is among the most prescribed drugs for bipolar disorder; however, 87% of patients do not report full long-term treatment response (LTTR) to this medication. One of valproate's suggested mechanisms of action involves the brain-derived neurotrophic factor (BDNF), expressed in the brain areas regulating emotions, such as the prefrontal cortex. Nonetheless, data about the role of BDNF in LTTR and its implications in the structure of the dorsolateral prefrontal cortex (dlPFC) is scarce. We explore the association of BDNF variants and dorsolateral cortical thickness (CT) with LTTR to valproate in bipolar disorder type I (BDI). Twenty-eight BDI patients were genotyped for BDNF polymorphisms rs1519480, rs6265, and rs7124442, and T1-weighted 3D brain scans were acquired. LTTR to valproate was evaluated with Alda's scale. A logistic regression analysis was conducted to evaluate LTTR according to BDNF genotypes and CT. We evaluated CT differences by genotypes with analysis of covariance. LTTR was associated with BDNF rs1519480 and right dlPFC thickness. Insufficient responders with the CC genotype had thicker right dlPFC than TC and TT genotypes. Full responders reported thicker right dlPFC in TC and TT genotypes. In conclusion, different patterns of CT related to BDNF genotypes were identified, suggesting a potential biomarker of LTTR to valproate in our population.

Brain morphometric features predict medication response in youth with bipolar disorder: a prospective randomized clinical trial

BACKGROUND

Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics.

METHODS

A total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets.

RESULTS

Pre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns.

CONCLUSIONS

These findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development.

Brain-gut microbiota multimodal predictive model in patients with bipolar depression

BACKGROUND

The "microbiota-gut-brain axis" which bridges the brain and gut microbiota is involved in the pathological mechanisms of bipolar disorder (BD), but rare is known about the exact association patterns and the potential for clinical diagnosis and treatment outcome prediction.

METHODS

At baseline, fecal samples and resting-state MRI data were collected from 103 BD depression patients and 39 healthy controls (HCs) for metagenomic sequencing and network-based functional connectivity (FC), grey matter volume (GMV) analyses. All patients then received 4-weeks quetiapine treatment and were further classified as responders and non-responders. Based on pre-treatment datasets, the correlation networks were established between gut microbiota and neuroimaging measures and the multimodal kernal combination support vector machine (SVM) classifiers were constructed to distinguish BD patients from HCs, and quetiapine responders from non-responders.

RESULTS

The multi-modal pre-treatment characteristics of quetiapine responders, were closer to the HCs compared to non-responders. And the correlation network analyses found the substantial correlations existed in HC between the Anaerotruncus_ unclassified，Porphyromonas_asaccharolytica，Actinomyces_graevenitzii et al. and the functional connectomes involved default mode network (DMN),somatomotor (SM), visual, limbic and basal ganglia networks were disrupted in BD. Moreover, in terms of the multimodal classifier, it reached optimized area under curve (AUC-ROC) at 0.9517 when classified BD from HC, and also acquired 0.8292 discriminating quetiapine responders from non-responders, which consistently better than even using the best unique modality.

LIMITATIONS

Lack post-treatment and external validation datasets; size of HCs is modest.

CONCLUSIONS

Multi-modalities of combining pre-treatment gut microbiota with neuroimaging endophenotypes might be a superior approach for accurate diagnosis and quetiapine efficacy prediction in BD.

Pretreatment Alterations and Acute Medication Treatment Effects on Brain Task-Related Functional Connectivity in Youth With Bipolar Disorder: A Neuroimaging Randomized Clinical Trial

OBJECTIVE

Disruptions in cognition are a clinically significant feature of bipolar disorder (BD). The effects of different treatments on these deficits and the brain systems that support them remain to be established.

METHOD

A continuous performance test was administered to 55 healthy controls and 71 acutely ill youths with mixed/manic BD to assess vigilance and working memory during task-based functional magnetic resonance imaging studies. Patients, who were untreated for at least 7 days at baseline, and controls were scanned at pretreatment baseline and at weeks 1 and 6. After baseline testing, patients (n = 71) were randomly assigned to 6-week double-blind treatment with lithium (n = 26; 1.0-1.2 mEq/L) or quetiapine (n = 45; 400-600 mg). Weighted seed-based connectivity (wSBC) was used to assess regional brain interactions during the attention task compared with the control condition.

RESULTS

At baseline, youths with BD showed reduced connectivity between bilateral anterior cingulate cortex and both left ventral lateral prefrontal cortex and left insula and increased connectivity between left ventral lateral prefrontal cortex and left temporal pole, left orbital frontal cortex and right postcentral gyrus, and right amygdala and right occipital pole compared with controls. At 1-week follow-up, quetiapine, but not lithium, treatment led to a significant shift of connectivity patterns toward those of the controls. At week 6, compared with baseline, there was no difference between treatment conditions, at which time both patient groups showed significant normalization of brain connectivity toward that of controls.

CONCLUSION

Functional alterations in several brain regions associated with cognitive processing and the integration of cognitive and affective processing were demonstrated in untreated youths with BD before treatment. Treatment reduced several of these alterations, with significant effects at week 1 only in the quetiapine treatment group. Normalization of functional connectivity might represent a promising biomarker for early target engagement in youth with BD.

CLINICAL TRIAL REGISTRATION INFORMATION

Multimodal Neuroimaging of Treatment Effects in Adolescent Mania; https://clinicaltrials.gov/; NCT00893581.

A Randomized, Double-Blind, Controlled Trial of Lithium Versus Quetiapine for the Treatment of Acute Mania in Youth with Early Course Bipolar Disorder

Objective: To compare the efficacy and tolerability of lithium versus quetiapine for the treatment of manic or mixed episodes in youths with early course bipolar I disorder. Methods: Six-week, randomized, double-blind clinical trial of lithium versus quetiapine for the treatment of adolescents with acute manic/mixed episode. Target dose of quetiapine dose was adjusted to a target dose of 400-600 mg and target serum level for lithium was 1.0-1.2 mEq/L. Primary outcome measure was baseline-to-endpoint change in the Young Mania Rating Scale (YMRS). Secondary outcomes were treatment response (50% or more decrease from baseline in YMRS score) and remission (YMRS score ≤12, Children's Depression Rating Scale-Revised [CDRS-R] total score ≤28 and Clinical Global Impression Bipolar Severity Scale [CGI-BP-S] overall score of ≤3, respectively). Results: A total of 109 patients were randomized (quetiapine = 58 and lithium = 51). Participants in the quetiapine treatment group showed a significantly greater reduction in YMRS score than those in the lithium group (-11.0 vs. -13.2; p < 0.001; effect size 0.39). Response rate was 72% in the quetiapine group and 49% in the lithium group (p = 0.012); no differences in remission rates between groups were observed. Most frequent side effects for lithium were headaches (60.8%), nausea (39.2%), somnolence (27.5%), and tremor (27.5%); for quetiapine somnolence (63.8%), headaches (55.2%), tremor (36.2%), and dizziness (36.2%) were evidenced. Participants receiving quetiapine experienced more somnolence (p < 0.001), dizziness (p < 0.05), and weight gain (p < 0.05). Conclusions: Treatment with both lithium and quetiapine led to clinical improvement. Most study participants in this study experienced a clinical response; however, less than half of the participants in this study achieved symptomatic remission. The head-to-head comparison of both treatment groups showed quetiapine was associated with a statistically significant greater rate of response and overall symptom reduction compared with lithium. Trial registration: clinicaltrials.gov NCT00893581.

BIOMARKERS AND NEUROBEHAVIORAL DIAGNOSIS

Our current diagnostic methods for treatment planning in Psychiatry and Neurodevelopmental Disabilities leave room for improvement, and null results in clinical trials in these fields may be a result of insufficient tools for patient stratification. Great hope has been placed in novel technologies to improve clinical and trial outcomes, but we have yet to see a substantial change in clinical practice. As we examine attempts at biomarker validation within these fields, we find that it may be the diagnoses themselves that fall short. We now need to improve neuropsychiatric nosologies with a focus on validity based not solely on behavioral features, but on a synthesis that includes genetic and biological data as well. The eventual goal is diagnostic biomarkers and diagnoses themselves based on distinct mechanisms, but such an understanding of the causal relationship across levels of analysis is likely to be elusive for some time. Rather, we propose an approach in the near-term that deconstructs diagnosis into a series of independent, empiric and clinically relevant associations among a single, defined patient group, a single biomarker, a single intervention and a single clinical outcome. Incremental study across patient groups, interventions, outcomes and modalities will lead to a more interdigitated network of knowledge, and correlations in metrics across levels of analysis will eventually give way to the causal understanding that will allow for mechanistically based diagnoses.

Changes in the brain structural connectome after a prospective randomized clinical trial of lithium and quetiapine treatment in youth with bipolar disorder

The goals of the current study were to determine whether topological organization of brain structural networks is altered in youth with bipolar disorder, whether such alterations predict treatment outcomes, and whether they are normalized by treatment. Youth with bipolar disorder were randomized to double-blind treatment with quetiapine or lithium and assessed weekly. High-resolution MRI images were collected from children and adolescents with bipolar disorder who were experiencing a mixed or manic episode (n = 100) and healthy youth (n = 63). Brain networks were constructed based on the similarity of morphological features across regions and analyzed using graph theory approaches. We tested for pretreatment anatomical differences between bipolar and healthy youth and for changes in neuroanatomic network metrics following treatment in the youth with bipolar disorder. Youth with bipolar disorder showed significantly increased clustering coefficient (Cp) (p = 0.009) and characteristic path length (Lp) (p = 0.04) at baseline, and altered nodal centralities in insula, inferior frontal gyrus, and supplementary motor area. Cp, Lp, and nodal centrality of the insula exhibited normalization in patients following treatment. Changes in these neuroanatomic parameters were correlated with improvement in manic symptoms but did not differ between the two drug therapies. Baseline structural network matrices significantly differentiated medication responders and non-responders with 80% accuracy. These findings demonstrate that both global and nodal structural network features are altered in early course bipolar disorder, and that pretreatment alterations in neuroanatomic features predicted treatment outcome and were reduced by treatment. Similar connectome normalization with lithium and quetiapine suggests that the connectome changes are a downstream effect of both therapies that is related to their clinical efficacy.

Left prefrontal transcranial magnetic stimulation for treatment-resistant depression in adolescents: a double-blind, randomized, sham-controlled trial

Treatment-resistant depression (TRD) is prevalent and associated with a substantial psychosocial burden and mortality. There are few prior studies of interventions for TRD in adolescents. This was the largest study to date examining the feasibility, safety, and efficacy of 10-Hz transcranial magnetic stimulation (TMS) for adolescents with TRD. Adolescents with TRD (aged 12-21 years) were enrolled in a randomized, sham-controlled trial of TMS across 13 sites. Treatment resistance was defined as an antidepressant treatment record level of 1 to 4 in a current episode of depression. Intention-to-treat patients (n = 103) included those randomly assigned to active NeuroStar TMS monotherapy (n = 48) or sham TMS (n = 55) for 30 daily treatments over 6 weeks. The primary outcome measure was change in the Hamilton Depression Rating Scale (HAM-D-24) score. After 6 weeks of blinded treatment, improvement in the least-squares mean (SE) HAM-D-24 scores were similar between the active (-11.1 [2.03]) and sham groups (-10.6 [2.00]; P = 0.8; difference [95% CI], - 0.5 [-4.2 to 3.3]). Response rates were 41.7% in the active group and 36.4% in the sham group (P = 0.6). Remission rates were 29.2% in the active group and 29.0% in the sham group (P = 0.95). There were no new tolerability or safety signals in adolescents. Although TMS treatment produced a clinically meaningful change in depressive symptom severity, this did not differ from sham treatment. Future studies should focus on strategies to reduce the placebo response and examine the optimal dosing of TMS for adolescents with TRD.

Neuroanatomic and Functional Neuroimaging Findings

The search for brain morphology findings that could explain behavioral disorders has gone through a long path in the history of psychiatry. With the advance of brain imaging technology, studies have been able to identify brain morphology and neural circuits associated with the pathophysiology of mental illnesses, such as bipolar disorders (BD). Promising results have also shown the potential of neuroimaging findings in the identification of outcome predictors and response to treatment among patients with BD. In this chapter, we present brain imaging structural and functional findings associated with BD, as well as their hypothesized relationship with the pathophysiological aspects of that condition and their potential clinical applications.

Imaging-Based Subtyping for Psychiatric Syndromes

Despite considerable research evidence demonstrating significant neurobiological alterations in psychiatric disorders, incorporating neuroimaging approaches into clinical practice remains challenging. There is an urgent need for biologically validated psychiatric disease constructs that can inform diagnostic algorithms and targeted treatment development. In this article, we present a conceptual review of the most robust and impactful findings from studies that use neuroimaging methods in efforts to define distinct disease subtypes, while emphasizing cross-diagnostic and dimensional approaches. In addition, we discuss current challenges in psychoradiology and outline potential future strategies for clinically applicable translation.

Progress in psychoradiology, the clinical application of psychiatric neuroimaging

Psychoradiology is an emerging field that applies radiological imaging technologies to psychiatric conditions. In the past three decades, brain imaging techniques have rapidly advanced understanding of illness and treatment effects in psychiatry. Based on these advances, radiologists have become increasingly interested in applying these advances for differential diagnosis and individualized patient care selection for common psychiatric illnesses. This shift from research to clinical practice represents the beginning evolution of psychoradiology. In this review, we provide a summary of recent progress relevant to this field based on their clinical functions, namely the (1) classification and subtyping; (2) prediction and monitoring of treatment outcomes; and (3) treatment selection. In addition, we provide guidelines for the practice of psychoradiology in clinical settings and suggestions for future research to validate broader clinical applications. Given the high prevalence of psychiatric disorders and the importance of increased participation of radiologists in this field, a guide regarding advances in this field and a description of relevant clinical work flow patterns help radiologists contribute to this fast-evolving field.

Preliminary analysis of resting state functional connectivity in young adults with subtypes of bipolar disorder

BACKGROUND

A precision medicine approach to bipolar disorder (BD) requires greater knowledge of neural mechanisms, especially within the BD phenotype. The present study evaluated differences in resting state functional connectivity (RSFC) between young adults followed longitudinally since childhood with full-threshold type I BD (BD-I)-characterized by distinct manic episodes-or a more sub-syndromal presentation of BD (BD Not Otherwise Specified [BD-NOS]), compared to one another and to healthy controls (HC). Independent Components Analysis (ICA), a multivariate data-driven method, and dual regression were used to explore whether connectivity within resting state networks (RSNs) differentiated the groups, especially for characteristic fronto-limbic alterations in BD.

METHODS

Young adults (ages 18-30) with BD-I (n = 28), BD-NOS (n = 14), and HCs (n = 52) underwent structural and RSFC neuroimaging. ICA derived 30 components from RSFC data; a subset of these components, representing well-characterized RSNs, was used for between-group analyses.

RESULTS

Participants with BD-I had significantly greater connectivity strength between the executive control network and right caudate vs. HCs. Participants with BD-NOS had significantly greater connectivity strength between the sensorimotor network and left precentral gyrus vs. HCs, which was significantly related to psychiatric symptoms.

LIMITATIONS

Limitations included small BD-NOS sample size and variation in BD mood state and medication status.

CONCLUSIONS

Results for BD-I participants support prior findings of fronto-limbic alterations characterizing BD. Alterations in the sensorimotor network for adults with BD-NOS aligns with the small but growing body of evidence that sensorimotor network alterations may represent a marker for vulnerability to BD. Further study is required to evaluate specificity.