Subcortical volumetric abnormalities in bipolar disorder

Lithium and valproate affect subcortical brain volumes in individuals with bipolar disorder: Mega-analysis of 235 individuals

INTRODUCTION

The mega-analysis conducted by the ENIGMA Bipolar Disorder Working Group revealed significant volume increment effects of lithium on the hippocampus in individual with bipolar disorder. However, the study did not assess other medications and other subcortical regions.

METHODS

Data of 235 individuals with bipolar disorder were taken from a mega-analysis conducted by the COCORO consortium in Japan. The effects of psychotropic prescriptions (lithium, valproate, antipsychotics, antidepressants, benzodiazepines) were assessed using a linear mixed-effects model with volumes of subcortical structures as dependent variables, and age, sex, intracranial volume, duration of illness, and psychotropic prescriptions as independent variables; the type of protocol was incorporated as a random effect.

RESULTS

Prescriptions of lithium was associated with larger left amygdala volume (Effect size (ES, Cohen's d) = 0.36, p = 0.001). Prescriptions of valproate was associated with smaller left amygdala volume (ES = -0.45, p = 0.001), and larger bilateral ventricle volumes (ES = 0.68, p < 0.001 (left), ES = 0.70, p < 0.001 (right)). Prescriptions of antipsychotics were associated with larger left globus pallidus volume (ES = 0.33, p = 0.014) and smaller left hippocampus volume (ES = -0.33, p = 0.024). Prescriptions of benzodiazepines were associated with smaller left lateral ventricle (ES = -0.40, p = 0.029). Prescriptions of antidepressants were associated with smaller right accumbens volume (ES = -0.22, p = 0.043), bilateral caudate volumes (ES = -0.38, p = 0.013 (left), ES = -0.25, p = 0.050 (right)) and right putamen volume (ES = -0.23, p = 0.024).

CONCLUSION

We confirmed the association between prescription of valproate and smaller amygdala and larger lateral ventricle volumes in a large sample for the first time. Large sample size, uniform data collection methodology, and robust statistical analysis are strengths of the current study.

Synaptic protein expression in bipolar disorder patient-derived neurons implicates PSD-95 as a marker of lithium response

Bipolar disorder (BD) is a severe mental illness characterized by recurrent episodes of depression and mania. Lithium is the gold standard pharmacotherapy for BD, but outcomes are variable, and the relevant therapeutic mechanisms underlying successful treatment response remain uncertain. To identify synaptic markers of BD and lithium response, we measured the effects of lithium on induced pluripotent stem cell-derived neurons from BD patients and controls. We determined that baseline expression of synapsin I (SYN1) and PSD-95 is reduced in BD neurons compared to controls. In control neurons, lithium treatment had modest, transient effects increasing SYN1 and PSD-95 expression. In BD neurons, lithium increased SYN1 expression regardless of lithium response history. However, lithium only increased PSD-95 expression selectively in neurons from lithium-responders and not in neurons from lithium non-responders, leading to group differences in the colocalization of SYN1 and PSD-95. In conclusion, this preliminary work indicates synaptic protein markers are associated with BD pathology and correction of post-synaptic protein expression may be an important mechanism underlying lithium response.

Altered Brain Functional Networks in Patients With Breast Cancer After Different Cycles of Neoadjuvant Chemotherapy

BACKGROUND

Cancer-related cognitive impairment (CRCI) impacts breast cancer (BC) patients' quality of life after chemotherapy. While recent studies have explored its neural correlates, single time-point designs cannot capture how these changes evolve over time.

PURPOSE

To investigate changes in the brain connectome of BC patients at several time points during neoadjuvant chemotherapy (NAC).

STUDY TYPE

Longitudinal.

SUBJECTS

55 participants with BC underwent clinical assessments and fMRI at baseline (TP1), the first cycle of NAC (TP2, 30 days later), and the end (TP3, 140 days later). Two matched female healthy control (HCs, n = 20 and n = 18) groups received the same assessments. FIELD STRENGTH/SEQUENCE: rs-fMRI (gradient-echo EPI) and 3D T1-weighted magnetization-prepared rapid gradient echo sequence at 3.0 T.

ASSESSMENT

Brain functional networks were analyzed using graph theory approaches. We analyzed changes in brain connectome metrics and explored the relationship between these changes and clinical scales (including emotion and cognitive test). Patients were divided into subgroups according to clinical classification, chemotherapy regimen, and menopausal status. Longitudinal analysis was performed at three time points for each subgroup.

STATISTICAL TESTS

An independent sample t-test for patient-HC comparison at TP1. Analysis of variance and paired t-test for longitudinal changes. Regression analysis for relations between network measurements changes and clinical symptom scores changes. Significance was defined as p < 0.05.

RESULTS

Post-NAC, BC patients showed increased global efficiency (TP2-TP1 = 0.087, TP3-TP1 = 0.078), decreased characteristic path length (TP2-TP1 = -0.413, TP3-TP1 = -0.312), and altered nodal centralities mainly in the frontal-limbic system and cerebellar cortex. These abnormalities expanded with chemotherapy progression significantly (TP2 vs. TP3). Topological parameters changes were also correlated with clinical scales changes significantly. No differences were found within or between HC groups (p = 0.490-0.989) or BC subgroups (p = 0.053-0.988) at TP1.

DATA CONCLUSIONS

NAC affects the brain functional connectome of BC patients at TP2, and these changes persist and further intensify at TP3.

LEVEL OF EVIDENCE: 2

TECHNICAL EFFICACY

Stage 5.

Biomarker identification in bipolar disorder

Bipolar disorder (BD) is a severe psychiatric condition whose pathophysiology is complex and multifactorial. Genetic, environmental and social risk factors play a role in its development as well as in its progressive course. Research is currently focusing on the identification of the biological basis underlying these processes in order to suggest novel biomarkers capable to predict BD etiopathogenesis and staging. Staging has been recognized as of great value for the treatment and management of many illnesses and might also be suitable for mental health issues, particularly in disorders like BD, which progress from an initial mild phase to a more severe and thus difficult-to-treat situation. Thus, it would be of great help the characterization of to suggest better treatment requirements and improve prognosis across the different stages of the illness. Here, we summarize current research on the biological hypotheses of BD and the biomarkers associated with its progression, reviewing clinical studies available in the literature.

Novel multimodal precision medicine approaches and the relevance of developmental trajectories in bipolar disorder

There is a pressing need to establish objective measures to improve diagnosis, prediction, prevention and treatment of bipolar disorder (BD). Multimodal artificial intelligence (AI) tools could provide these means by incorporating various layers of data orthogonally related to BD, including genomics and other omics, environmental exposures, imaging measures, electronic health records, cognition, sensing devices and clinical variables. These rapidly evolving AI models hold promise to capture the multidimensional complexity of BD and delineate clinically relevant developmental trajectories that could guide clinical care and therapeutic strategies. In this review, we describe the potential of mapping developmental trajectories underlying BD, outline how novel multimodal models could improve the prediction of BD and related outcomes, and discuss specific clinical use cases and key ethical and practical challenges regarding the development and potential implementation of these multimodal AI solutions to advance precision medicine approaches in BD.

Alterations of subcortical structural volume in pediatric bipolar disorder patients with and without psychotic symptoms

BACKGROUND

Pediatric bipolar disorder (PBD) with psychotic symptoms may predict more severe impairment in social functioning, but the underlying biological mechanisms remain unclear. The aim of this study was to investigate alterations in subcortical structural volume in PBD with and without psychotic symptoms.

METHODS

We recruited 24 psychotic PBD (P-PBD) patients, 24 non-psychotic PBD (NP-PBD) patients, and 18 healthy controls (HCs). All participants underwent scanning with a 3.0 T Siemens Trio scanner. The FreeSurfer 7.4.0 software was employed to calculate the volume of each subcortical structure. An analysis of covariance (ANCOVA) was performed to identify brain regions with significant volume differences among the three groups, and then the inter-group comparisons were calculated. Partial correlation analyses were conducted to identify relationships between subcortical structural volumes and clinical features. Finally, receiver operating characteristic curve (ROC) analysis was employed to verify the capacity to distinguish between P-PBD and NP-PBD, P-PBD and HCs, and NP-PBD and HCs.

RESULTS

ANCOVA revealed significant differences in the volumes of bilateral lateral ventricles, third ventricle, left thalamus, and right pallidum among three groups. Compared with HC, the third ventricle volume was increased in both groups of PBD patients, whereas the left thalamus and right pallidum volumes were decreased, and the bilateral lateral ventricles were enlarged in P-PBD patients. In contrast, only the third ventricle showed further enlargement in the group of P-PBD patients compared with NP-PBD patients. Partial correlation analyses revealed that episode times were associated with the third ventricle volume in P-PBD patients. Furthermore, ROC analyses indicated that volume in the left lateral ventricle exhibited the greatest capacity to distinguish between the P-PBD and NP-PBD, and the third ventricle performed best in distinguishing both the P-PBD group from HCs and the NP-PBD group from HCs. The combined metrics demonstrated greater diagnostic value in two-by-two comparisons.

CONCLUSION

Current research suggests that PBD with psychotic symptoms may have more extensive lateral and third ventricular volume enlargement. Bilateral lateral ventricles may serve as potential neurobiomarkers to distinguish P- PBD patients from NP-PBD patients.

Family study of bipolar disorder with comorbid anxiety disorder points to THSD7A with possible role of parent-of-origin effect

Aim

The aim of this study was to provide new insights into the genetics of bipolar disorder (BD) by analyzing BD comorbid with anxiety disorders.

Methods

Structured interviews were conducted with BD patients and their parents. Cases were classified into those with comorbid anxiety spectrum (AS) and those without. The family history of patients with BD with comorbid AS was assessed. Focusing on parent-of-origin effects and genomic imprinting from the results, imprinted genes and tested single nucleotide polymorphisms (SNPs) in the identified genes were investigated for an association with BD by transmission disequilibrium test (TDT) using published whole-exome sequencing data.

Results

The incidence of comorbid AS among all the patients with BD analyzed in this study was 39.6%. Patients with BD whose fathers had AS or mood disorders exhibited a significantly higher rate of AS. Among the known imprinted genes, two were associated with BD: THSD7A and CACNA1C. By pruning SNPs, six variants of the THSD7A exons and four variants of the CACNA1C exons were included in the analysis. Among these, one variant of THSD7A, rs2074603, showed over-transmission from parents to patients with BD. Furthermore, it was nominally significant only for fathers when TDT was performed separately for fathers and mothers.

Conclusion

THSD7A may play a role in BD with parent-of-origin effects. Further research is necessary to explore the mechanisms by which genomic imprinting is associated with BD. Clinical Trial Registration: N/A.

Lateral Ventricular Enlargement and Asymmetry and Myelin Content Imbalance in Individuals With Bipolar and Depressive Disorders: Clinical and Research Implications

BACKGROUND

The link between ventricular enlargement and asymmetry with other indices of brain structure remains underexplored in individuals with bipolar (BD) and depressive (DD) disorders. Our study compared the lateral ventricular size, ventricular asymmetry, and cortical myelin content in individuals with BD versus those with DD versus healthy controls (HC).

METHODS

We obtained T1w and T2w images from 149 individuals (age = 27.7 (SD = 6.1) years, 78% female, BD = 38, DD = 57, HC = 54) using Magnetic Resonance Imaging (MRI). The BD group consisted of individuals with BD Type I (n = 11) and BD Type II (n = 27), while the DD group consisted of individuals with major depressive disorder (MDD, n = 38) and persistent depressive disorder (PDD, n = 19) Cortical myelin content was calculated using the T1w/T2w ratio. Elastic net regularized regression identified brain regions whose myelin content was associated with ventricular size and asymmetry. A post hoc linear regression examined how participants' diagnosis, illness duration, and current level of depression moderated the relationship between the size and asymmetry of the lateral ventricles and levels of cortical myelin in the selected brain regions.

RESULTS

Individuals with BD and DD had larger lateral ventricles than HC. Larger ventricles and lower asymmetry were observed in individuals with BD who had longer lifetime illness duration and more severe current depressive symptoms. A greater left asymmetry was observed in participants with DD than in those with BD (p < 0.01). Elastic net revealed that both ventricular enlargement and asymmetry were associated with altered myelin content in cingulate, frontal, and sensorimotor cortices. In BD, but not in other groups, ventricular enlargement was related to altered myelin content in the right insular regions.

CONCLUSIONS

Lateral ventricular enlargement and asymmetry are linked to myelin content imbalance, thus potentially leading to emotional and cognitive dysfunction in mood disorders.

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.

Abnormal choroid plexus, hippocampus, and lateral ventricles volumes as markers of treatment-resistant major depressive disorder

AIM

One-third of patients with major depressive disorder (MDD) do not achieve full remission and have high relapse rates even after treatment, leading to increased medical costs and reduced quality of life and health status. The possible specificity of treatment-resistant depression (TRD) neurobiology is still under investigation, with risk factors such as higher inflammatory markers being identified. Given recent findings on the role of choroid plexus (ChP) in neuroinflammation and hippocampus in treatment response, the aim of the present study was to evaluate inflammatory- and trophic-related differences in these regions along with ventricular volumes among patients with treatment-sensitive depression (TSD), TRD, and healthy controls (HCs).

METHODS

ChP, hippocampal, and ventricular volumes were assessed in 197 patients with MDD and 58 age- and sex-matched HCs. Volumes were estimated using FreeSurfer 7.2. Treatment resistance status was defined as failure to respond to at least two separate antidepressant treatments. Region of interest volumes were then compared among groups.

RESULTS

We found higher ChP volumes in patients with TRD compared with patients with TSD and HCs. Our results also showed lower hippocampal volumes and higher lateral ventricular volumes in TRD compared with both patients without TRD and HCs.

CONCLUSIONS

These findings corroborate the link between TRD and neuroinflammation, as ChP volume could be considered a putative marker of central immune activity. The lack of significant differences in all of the region of interest volumes between patients with TSD and HCs may highlight the specificity of these features to TRD, possibly providing new insights into the specific neurobiological underpinnings of this condition.

Dissecting depression symptoms: Multi-omics clustering uncovers immune-related subgroups and cell-type specific dysregulation

In a subset of patients with mental disorders, such as depression, low-grade inflammation and altered immune marker concentrations are observed. However, these immune alterations are often assessed by only one data type and small marker panels. Here, we used a transdiagnostic approach and combined data from two cohorts to define subgroups of depression symptoms across the diagnostic spectrum through a large-scale multi-omics clustering approach in 237 individuals. The method incorporated age, body mass index (BMI), 43 plasma immune markers and RNA-seq data from peripheral mononuclear blood cells (PBMCs). Our initial clustering revealed four clusters, including two immune-related depression symptom clusters characterized by elevated BMI, higher depression severity and elevated levels of immune markers such as interleukin-1 receptor antagonist (IL-1RA), C-reactive protein (CRP) and C-C motif chemokine 2 (CCL2 or MCP-1). In contrast, the RNA-seq data mostly differentiated a cluster with low depression severity, enriched in brain related gene sets. This cluster was also distinguished by electrocardiography data, while structural imaging data revealed differences in ventricle volumes across the clusters. Incorporating predicted cell type proportions into the clustering resulted in three clusters, with one showing elevated immune marker concentrations. The cell type proportion and genes related to cell types were most pronounced in an intermediate depression symptoms cluster, suggesting that RNA-seq and immune markers measure different aspects of immune dysregulation. Lastly, we found a dysregulation of the SERPINF1/VEGF-A pathway that was specific to dendritic cells by integrating immune marker and RNA-seq data. This shows the advantages of combining different data modalities and highlights possible markers for further stratification research of depression symptoms.

[Long-term courses of bipolar disorders]

BACKGROUND

Bipolar disorder (short: BD) is a severe illness with very heterogeneous trajectories. While some of the patients show no or hardly any long-term impairments, other affected individuals show substantial neurocognitive deficits with a clear decline in psychosocial functioning. Which factors influence the course of the disease is the subject of current research efforts.

OBJECTIVE

This review presents the long-term course of bipolar disease and the factors influencing it. In particular, differential trajectory types are discussed. The cognitive and psychosocial functional level as well as the psychopathological characteristics of the disease are elucidated. In addition, biological factors and treatment approaches influencing the course and prognosis are identified.

MATERIAL AND METHODS

Literature search using PubMed focusing on longitudinal studies over several years (see online supplement).

RESULTS

To date, there are only a few predictors and biomarkers that allow prediction of long-term progression. None have been sufficiently studied to enable clinical use. Appropriate pharmacological and psychotherapeutic treatment of those affected is essential to avoid renewed episodes of the disease.

DISCUSSION

The long-term course of bipolar disorder is highly heterogeneous and multifaceted. Despite intensive research efforts, no predictors have yet been identified that reliably predict the clinical course. This makes further research all the more important in order to offer individualized therapy options, develop new therapies and positively influence the course of the disease at an early stage.

Machine learning with multiple modalities of brain magnetic resonance imaging data to identify the presence of bipolar disorder

BACKGROUND

Bipolar disorder (BD) is a chronic psychiatric mood disorder that is solely diagnosed based on clinical symptoms. These symptoms often overlap with other psychiatric disorders. Efforts to use machine learning (ML) to create predictive models for BD based on data from brain imaging are expanding but have often been limited using only a single modality and the exclusion of the cerebellum, which may be relevant in BD.

METHODS

In this study, we sought to improve ML classification of BD by combining information from structural, functional, and diffusion-weighted imaging. Participants (108 BD I, 78 control) with BD type I and matched controls were recruited into an imaging study. This dataset was randomly divided into training and testing sets. For each of the three modalities, a separate ML model was selected, trained, and then used to generate a prediction of the class of each test subject. Majority voting was used to combine results from the three models to make a final prediction of whether a subject had BD. An independent replication sample was used to evaluate the ability of the ML classification to generalize to data collected at other sites.

RESULTS

Combining the three machine learning models through majority voting resulted in an accuracy of 89.5 % for classification of the test subjects as being in the BD or control group. Bootstrapping resulted in a 95 % confidence interval of 78.9 %-97.4 % for test accuracy. Performance was reduced when only using 2 of the 3 modalities. Analysis of feature importance revealed that the cerebellum and nodes of the emotional control network were among the most important regions for classification. The machine learning model performed at chance on the independent replication sample.

CONCLUSION

BD I could be identified with high accuracy in our relatively small sample by combining structural, functional, and diffusion-weighted imaging data within a single site but not generalize well to an independent replication sample. Future studies using harmonized imaging protocols may facilitate generalization of ML models.

Cerebrospinal Fluid Biomarkers of Central Nervous System Inflammation Predict Cortical Decline in Bipolar Disorder and Ventricular Enlargement in Healthy Controls

INTRODUCTION

Bipolar disorder has been associated with significant structural brain changes, potentially driven by central nervous system (CNS) inflammation. This study aimed to investigate the relationship between inflammation biomarkers in cerebrospinal fluid (CSF) and longitudinal structural brain changes.

METHODS

We included 29 individuals with bipolar disorder and 34 healthy controls, analyzing three selected inflammation-related biomarkers - interleukin-6 (IL-6), interleukin-8 (IL-8), and chitinase-3-like protein 1 (YKL-40) - in both blood serum and CSF. Structural brain changes were assessed through magnetic resonance imaging at two timepoints, focusing on cortical thickness of the middle temporal cortex and inferior frontal gyrus, as well as ventricular volume.

RESULTS

In healthy controls, baseline CSF levels of YKL-40 predicted ventricular enlargement in both hemispheres. Among individuals with bipolar disorder, higher baseline levels of IL-8 were associated with a decline in cortical thickness in the right and left middle temporal cortex, as well as the right inferior frontal gyrus. No significant associations were observed with serum biomarkers.

CONCLUSIONS

These findings suggest that CSF IL-8 may contribute to cortical decline in bipolar disorder. The lack of association between serum biomarkers and brain changes highlights the specificity of CNS inflammation in these processes. Additionally, the observed link between CSF YKL-40 and ventricular enlargement in healthy controls may indicate a role of CNS inflammation processes in normal brain aging.

INTRODUCTION

Bipolar disorder has been associated with significant structural brain changes, potentially driven by central nervous system (CNS) inflammation. This study aimed to investigate the relationship between inflammation biomarkers in cerebrospinal fluid (CSF) and longitudinal structural brain changes.

METHODS

We included 29 individuals with bipolar disorder and 34 healthy controls, analyzing three selected inflammation-related biomarkers - interleukin-6 (IL-6), interleukin-8 (IL-8), and chitinase-3-like protein 1 (YKL-40) - in both blood serum and CSF. Structural brain changes were assessed through magnetic resonance imaging at two timepoints, focusing on cortical thickness of the middle temporal cortex and inferior frontal gyrus, as well as ventricular volume.

RESULTS

In healthy controls, baseline CSF levels of YKL-40 predicted ventricular enlargement in both hemispheres. Among individuals with bipolar disorder, higher baseline levels of IL-8 were associated with a decline in cortical thickness in the right and left middle temporal cortex, as well as the right inferior frontal gyrus. No significant associations were observed with serum biomarkers.

CONCLUSIONS

These findings suggest that CSF IL-8 may contribute to cortical decline in bipolar disorder. The lack of association between serum biomarkers and brain changes highlights the specificity of CNS inflammation in these processes. Additionally, the observed link between CSF YKL-40 and ventricular enlargement in healthy controls may indicate a role of CNS inflammation processes in normal brain aging.

Disorganized thalamic subregional functional connectivity in bipolar I disorder

Thalamus plays a pivotal role in the pathophysiology of neuropsychiatric conditions due to its strategic position and intricate connectivity with the cerebral cortex, limbic system, and other subcortical structures. In the present study, the potential involvement of the thalamus and subregions of the thalamus are explored in bipolar disorder (BD). In particular, functional and structural magnetic resonance imaging was performed on 73 adult patients with BD-I and 78 healthy controls (HCs). Seed-based thalamus and thalamic subregional functional connectivity (FC) were compared between the BD-I patients and HCs. Compared to HCs, patients with BD-I showed higher FC between the left thalamus and right lingual gyrus and altered FC between the dorsal thalamus and the default mode network and prefrontal regions, which may be correlated with mania symptomatology. In patients with BD-I, the anterior subregions of the thalamus had higher FC than the posterior subregions. No significant difference in gray matter volume or local functional activity was found in the thalamus and thalamic subregions between BD-I and HC. These findings provide evidence of disorganized thalamocortical FC in BD-I, suggesting that the thalamus and its subregions may play important and specific roles in the neural circuitry of BD.

Alterations of subcortical structure volume in pediatric bipolar disorder patients with manic or depressive first-episode

BACKGROUND

Bipolar disorder may begin as depression or mania, which can affect the treatment and prognosis. The physiological and pathological differences among pediatric bipolar disorder (PBD) patients with different onset symptoms are not clear. The aims of the present study were to investigate subcortical structural alterations in PBD patients with first-episode depressive (PBD-FED) and first-episode manic (PBD-FEM).

METHODS

A total of 59 individuals including 28 PBD-FED, 13 PBD-FEM, and 18 healthy controls (HCs) underwent high-resolution structural magnetic resonance scans. FreeSurfer 7.2 was used to detect changes in subcortical volumes. Simultaneously, thalamic, hippocampal, and amygdala subregion volumes were compared between the three groups.

RESULTS

Analysis of covariance controlling for age, sex, education, and estimated intracranial volume shows third and fourth ventricle enlargement in patients with PBD. Compared with the PBD-FED and HCs, the PBD-FEM group had reduced gray matter volume in the left thalamus, bilateral hippocampus, and right amygdala. Subsequent subregion analyses showed right cortico-amygdaloid transient, bilateral accessory-basal nucleus, left hippocampal tail, right hippocampal head, and body volume reduction in the PBD-FEM group.

CONCLUSIONS

The present findings provided evidence of decreased subcortical structure in PBD-FEM patients, which might present its trait feature.

Genetic architectures of the human hippocampus and those involved in neuropsychiatric traits

BACKGROUND

The hippocampus, with its complex subfields, is linked to numerous neuropsychiatric traits. While most research has focused on its global structure or a few specific subfields, a comprehensive analysis of hippocampal substructures and their genetic correlations across a wide range of neuropsychiatric traits remains underexplored. Given the hippocampus's high heritability, considering hippocampal and subfield volumes (HASV) as endophenotypes for neuropsychiatric conditions is essential.

METHODS

We analyzed MRI-derived volumetric data of hippocampal and subfield structures from 41,525 UK Biobank participants. Genome-wide association studies (GWAS) on 24 HASV traits were conducted, followed by genetic correlation, overlap, and Mendelian randomization (MR) analyses with 10 common neuropsychiatric traits. Polygenic risk scores (PRS) based on HASV traits were also evaluated for predicting these traits.

RESULTS

Our analysis identified 352 independent genetic variants surpassing a significance threshold of 2.1 × 10-9 within the 24 HASV traits, located across 93 chromosomal regions. Notably, the regions 12q14.3, 17q21.31, 12q24.22, 6q21, 9q33.1, 6q25.1, and 2q24.2 were found to influence multiple HASVs. Gene set analysis revealed enrichment of neural differentiation and signaling pathways, as well as protein binding and degradation. Of 240 HASV-neuropsychiatric trait pairs, 75 demonstrated significant genetic correlations (P < 0.05/240), revealing 433 pleiotropic loci. Particularly, genes like ACBD4, ARHGAP27, KANSL1, MAPT, ARL17A, and ARL17B were involved in over 50 HASV-neuropsychiatric pairs. Leveraging Mendelian randomization analysis, we further confirmed that atrophy in the left hippocampus, right hippocampus, right hippocampal body, and right CA1-3 region were associated with an increased risk of developing Parkinson's disease (PD). Furthermore, PRS for all four HASVs were significantly linked to a higher risk of Parkinson's disease (PD), with the highest hazard ratio (HR) of 1.30 (95% CI 1.18-1.43, P = 6.15 × 10⁻⁸) for right hippocampal volume.

CONCLUSIONS

These findings highlight the extensive distribution of pleiotropic genetic determinants between HASVs and neuropsychiatric traits. Moreover, they suggest a significant potential for effectively managing and intervening in these diseases during their early stages.

Larger putamen in individuals at risk and with manifest bipolar disorder

BACKGROUND

Individuals at risk for bipolar disorder (BD) have a wide range of genetic and non-genetic risk factors, like a positive family history of BD or (sub)threshold affective symptoms. Yet, it is unclear whether these individuals at risk and those diagnosed with BD share similar gray matter brain alterations.

METHODS

In 410 male and female participants aged 17-35 years, we compared gray matter volume (3T MRI) between individuals at risk for BD (as assessed using the EPIbipolar scale; n = 208), patients with a DSM-IV-TR diagnosis of BD (n = 87), and healthy controls (n = 115) using voxel-based morphometry in SPM12/CAT12. We applied conjunction analyses to identify similarities in gray matter volume alterations in individuals at risk and BD patients, relative to healthy controls. We also performed exploratory whole-brain analyses to identify differences in gray matter volume among groups. ComBat was used to harmonize imaging data from seven sites.

RESULTS

Both individuals at risk and BD patients showed larger volumes in the right putamen than healthy controls. Furthermore, individuals at risk had smaller volumes in the right inferior occipital gyrus, and BD patients had larger volumes in the left precuneus, compared to healthy controls. These findings were independent of course of illness (number of lifetime manic and depressive episodes, number of hospitalizations), comorbid diagnoses (major depressive disorder, attention-deficit hyperactivity disorder, anxiety disorder, eating disorder), familial risk, current disease severity (global functioning, remission status), and current medication intake.

CONCLUSIONS

Our findings indicate that alterations in the right putamen might constitute a vulnerability marker for BD.

Increased grey matter volumes in the temporal lobe and its relationship with cognitive functioning in euthymic patients with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is characterized by episodic mood dysregulation, although a significant portion of patients suffer persistent cognitive impairment during euthymia. Previous magnetic resonance imaging (MRI) research suggests BD patients may have accelerated brain aging, observed as lower grey matter volumes. How these neurostructural alterations are related to the cognitive profile of BD is unclear.

METHODS

We aim to explore this relationship in euthymic BD patients with multimodal structural neuroimaging. A sample of 27 euthymic BD patients and 24 healthy controls (HC) underwent structural grey matter MRI and diffusion-weighted imaging (DWI). BD patient's cognition was also assessed. FreeSurfer algorithms were used to obtain estimations of regional grey matter volumes. White matter pathways were reconstructed using TRACULA, and four diffusion metrics were extracted. ANCOVA models were performed to compare BD patients and HC values of regional grey matter volume and diffusion metrics. Global brain measures were also compared. Bivariate Pearson correlations were explored between significant brain results and five cognitive domains.

RESULTS

Euthymic BD patients showed higher ventricular volume (F(1, 46) = 6.04; p = 0.018) and regional grey matter volumes in the left fusiform (F(1, 46) = 15.03; pFDR = 0.015) and bilateral parahippocampal gyri compared to HC (L: F(1, 46) = 12.79, pFDR = 0.025/ R: F(1, 46) = 15.25, pFDR = 0.015). Higher grey matter volumes were correlated with greater executive function (r = 0.53, p = 0.008).

LIMITATIONS

We evaluated a modest sample size with concurrent pharmacological treatment.

CONCLUSIONS

Higher medial temporal volumes in euthymic BD patients may be a potential signature of brain resilience and cognitive adaptation to a putative illness neuroprogression. This knowledge should be integrated into further efforts to implement imaging into BD clinical management.

Factor analysis of lifetime psychopathology and its brain morphometric and genetic correlates in a transdiagnostic sample

There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.

Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

New Advances in the Pharmacology and Toxicology of Lithium: A Neurobiologically Oriented Overview

Over the last six decades, lithium has been considered the gold standard treatment for the long-term management of bipolar disorder due to its efficacy in preventing both manic and depressive episodes as well as suicidal behaviors. Nevertheless, despite numerous observed effects on various cellular pathways and biologic systems, the precise mechanism through which lithium stabilizes mood remains elusive. Furthermore, there is recent support for the therapeutic potential of lithium in other brain diseases. This review offers a comprehensive examination of contemporary understanding and predominant theories concerning the diverse mechanisms underlying lithium's effects. These findings are based on investigations utilizing cellular and animal models of neurodegenerative and psychiatric disorders. Recent studies have provided additional support for the significance of glycogen synthase kinase-3 (GSK3) inhibition as a crucial mechanism. Furthermore, research has shed more light on the interconnections between GSK3-mediated neuroprotective, antioxidant, and neuroplasticity processes. Moreover, recent advancements in animal and human models have provided valuable insights into how lithium-induced modifications at the homeostatic synaptic plasticity level may play a pivotal role in its clinical effectiveness. We focused on findings from translational studies suggesting that lithium may interface with microRNA expression. Finally, we are exploring the repurposing potential of lithium beyond bipolar disorder. These recent findings on the therapeutic mechanisms of lithium have provided important clues toward developing predictive models of response to lithium treatment and identifying new biologic targets. SIGNIFICANCE STATEMENT: Lithium is the drug of choice for the treatment of bipolar disorder, but its mechanism of action in stabilizing mood remains elusive. This review presents the latest evidence on lithium's various mechanisms of action. Recent evidence has strengthened glycogen synthase kinase-3 (GSK3) inhibition, changes at the level of homeostatic synaptic plasticity, and regulation of microRNA expression as key mechanisms, providing an intriguing perspective that may help bridge the mechanistic gap between molecular functions and its clinical efficacy as a mood stabilizer.

Noninvasive intervention by transcranial ultrasound stimulation: Modulation of neural circuits and its clinical perspectives

Low-intensity focused transcranial ultrasound stimulation (TUS) is an emerging noninvasive technique capable of stimulating both the cerebral cortex and deep brain structures with high spatial precision. This method is recognized for its potential to comprehensively perturb various brain regions, enabling the modulation of neural circuits, in a manner not achievable through conventional magnetic or electrical brain stimulation techniques. The underlying mechanisms of neuromodulation are based on a phenomenon where mechanical waves of ultrasound kinetically interact with neurons, specifically affecting neuronal membranes and mechanosensitive channels. This interaction induces alterations in the excitability of neurons within the stimulated region. In this review, we briefly present the fundamental principles of ultrasound physics and the physiological mechanisms of TUS neuromodulation. We explain the experimental apparatus and procedures for TUS in humans. Due to the focality, the integration of various methods, including magnetic resonance imaging and magnetic resonance-guided neuronavigation systems, is important to perform TUS experiments for precise targeting. We then review the current state of the literature on TUS neuromodulation, with a particular focus on human subjects, targeting both the cerebral cortex and deep subcortical structures. Finally, we outline future perspectives of TUS in clinical applications in psychiatric and neurological fields.

The relationship between the size and asymmetry of the lateral ventricles and cortical myelin content in individuals with mood disorders

Background

Although enlargement of the lateral ventricles was previously observed in individuals with mood disorders, the link between ventricular size and asymmetry with other indices of brain structure remains underexplored. In this study, we examined the association of lateral ventricular size and asymmetry with cortical myelin content in individuals with bipolar (BD) and depressive (DD) disorders compared to healthy controls (HC).

Methods

Magnetic resonance imaging (MRI) was used to obtain T1w and T2w images from 149 individuals (age=27.7 (SD=6.1) years, 78% female, BD=38, DD=57, HC=54). Cortical myelin content was calculated using the T1w/T2w ratio. Elastic net regularized regression identified brain regions whose myelin content was associated with ventricular size and asymmetry. A post-hoc linear regression examined how participants' diagnosis, illness duration, and current level of depression moderated the relationship between the size and asymmetry of the lateral ventricles and levels of cortical myelin in the selected brain regions.

Results

Individuals with mood disorders had larger lateral ventricles than HC. Larger ventricles and lower asymmetry were observed in individuals with BD who had longer lifetime illness duration and more severe current depressive symptoms. A greater left asymmetry was observed in participants with DD than in those with BD (p<0.01). Elastic net revealed that both ventricular enlargement and asymmetry were associated with altered myelin content in cingulate, frontal, and sensorimotor cortices. In BD, but not other groups, ventricular enlargement was related to altered myelin content in the right insular regions.

Conclusions

Lateral ventricular enlargement and asymmetry are linked to myelin content imbalance, thus, potentially leading to emotional and cognitive dysfunction in mood disorders.

Bipolar disorders and schizophrenia: discrete disorders?

BACKGROUND

With similarities in heritability, neurobiology and symptomatology, the question has been raised whether schizophrenia and bipolar disorder are truly distinctive disorders or belong to a continuum. This narrative review summarizes common and distinctive findings from genetics, neuroimaging, cognition and clinical course that may help to solve this ethiopathogenetic puzzle.

METHODS

The authors conducted a literature search for papers listed in PubMed and Google Scholar, using the search terms "schizophrenia" and "bipolar disorder" combined with different terms such as "genes", "neuroimaging studies", "phenomenology differences", "cognition", "epidemiology". Articles were considered for inclusion if they were written in English or Spanish, published as full articles, if they compared subjects with schizophrenia and bipolar disorder, or subjects with either disorder with healthy controls, addressing differences between groups.

RESULTS

Several findings support the hypothesis that schizophrenia and bipolar disorder are discrete disorders, yet some overlapping of findings exists. The evidence for heritability of both SZ and BD is obvious, as well as the environmental impact on individual manifestations of both disorders. Neuroimaging studies support subtle differences between disorders, it appears to be rather a pattern of irregularities than an unequivocally unique finding distinguishing schizophrenia from bipolar disorder. The cognitive profile displays differences between disorders in certain domains, such as premorbid intellectual functioning and executive functions. Finally, the timing and trajectory of cognitive impairment in both disorders also differs.

CONCLUSION

The question whether SZ and BD belong to a continuum or are separate disorders remains a challenge for further research. Currently, our research tools may be not precise enough to carve out distinctive, unique and undisputable differences between SZ and BD, but current evidence favors separate disorders. Given that differences are subtle, a way to overcome diagnostic uncertainties in the future could be the application of artificial intelligence based on BigData.

LIMITATIONS

Despite the detailed search, this article is not a full and complete review of all available studies on the topic. The search and selection of papers was also limited to articles in English and Spanish. Selection of papers and conclusions may be biased by the personal view and clinical experience of the authors.

White and gray matter alterations in bipolar I and bipolar II disorder subtypes compared with healthy controls - exploring associations with disease course and polygenic risk

Patients with bipolar disorder (BD) show alterations in both gray matter volume (GMV) and white matter (WM) integrity compared with healthy controls (HC). However, it remains unclear whether the phenotypically distinct BD subtypes (BD-I and BD-II) also exhibit brain structural differences. This study investigated GMV and WM differences between HC, BD-I, and BD-II, along with clinical and genetic associations. N = 73 BD-I, n = 63 BD-II patients and n = 136 matched HC were included. Using voxel-based morphometry and tract-based spatial statistics, main effects of group in GMV and fractional anisotropy (FA) were analyzed. Associations between clinical and genetic features and GMV or FA were calculated using regression models. For FA but not GMV, we found significant differences between groups. BD-I patients showed lower FA compared with BD-II patients (ptfce-FWE = 0.006), primarily in the anterior corpus callosum. Compared with HC, BD-I patients exhibited lower FA in widespread clusters (ptfce-FWE < 0.001), including almost all major projection, association, and commissural fiber tracts. BD-II patients also demonstrated lower FA compared with HC, although less pronounced (ptfce-FWE = 0.049). The results remained unchanged after controlling for clinical and genetic features, for which no independent associations with FA or GMV emerged. Our findings suggest that, at a neurobiological level, BD subtypes may reflect distinct degrees of disease expression, with increasing WM microstructure disruption from BD-II to BD-I. This differential magnitude of microstructural alterations was not clearly linked to clinical and genetic variables. These findings should be considered when discussing the classification of BD subtypes within the spectrum of affective disorders.

Accelerated brain aging as a biomarker for staging in bipolar disorder: an exploratory study

BACKGROUND

Two established staging models outline the longitudinal progression in bipolar disorder (BD) based on episode recurrence or inter-episodic functioning. However, underlying neurobiological mechanisms and corresponding biomarkers remain unexplored. This study aimed to investigate if global and (sub)cortical brain structures, along with brain-predicted age difference (brain-PAD) reflect illness progression as conceptualized in these staging models, potentially identifying brain-PAD as a biomarker for BD staging.

METHODS

In total, 199 subjects with bipolar-I-disorder and 226 control subjects from the Dutch Bipolar Cohort with a high-quality T1-weighted magnetic resonance imaging scan were analyzed. Global and (sub)cortical brain measures and brain-PAD (the difference between biological and chronological age) were estimated. Associations between individual brain measures and the stages of both staging models were explored.

RESULTS

A higher brain-PAD (higher biological age than chronological age) correlated with an increased likelihood of being in a higher stage of the inter-episodic functioning model, but not in the model based on number of mood episodes. However, after correcting for the confounding factors lithium-use and comorbid anxiety, the association lost significance. Global and (sub)cortical brain measures showed no significant association with the stages.

CONCLUSIONS

These results suggest that brain-PAD may be associated with illness progression as defined by impaired inter-episodic functioning. Nevertheless, the significance of this association changed after considering lithium-use and comorbid anxiety disorders. Further research is required to disentangle the intricate relationship between brain-PAD, illness stages, and lithium intake or anxiety disorders. This study provides a foundation for potentially using brain-PAD as a biomarker for illness progression.

Network dysfunction of sadness facial expression processing and morphometry in euthymic bipolar disorder

Facial emotion recognition (FER), including sadness, is altered in bipolar disorder (BD). However, the relationship between this impairment and the brain structure in BD is relatively unexplored. Furthermore, its association with clinical variables and with the subtypes of BD remains to be clarified. Twenty euthymic patients with BD type I (BD-I), 28 BD type II (BD-II), and 45 healthy controls completed a FER test and a 3D-T1-weighted magnetic resonance imaging. Gray matter volume (GMV) of the cortico-limbic regions implicated in emotional processing was estimated and their relationship with FER performance was investigated using network analysis. Patients with BD-I had worse total and sadness-related FER performance relative to the other groups. Total FER performance was significantly negatively associated with illness duration and positively associated with global functioning in patients with BD-I. Sadness-related FER performance was also significantly negatively associated with the number of previous manic episodes. Network analysis showed a reduced association of the GMV of the frontal-insular-occipital areas in patients with BD-I, with a greater edge strength between sadness-related FER performance and amygdala GMV relative to controls. Our results suggest that FER performance, particularly for facial sadness, may be distinctively impaired in patients with BD-I. The pattern of reduced interrelationship in the frontal-insular-occipital regions and a stronger positive relationship between facial sadness recognition and the amygdala GMV in BD may reflect altered cortical modulation of limbic structures that ultimately predisposes to emotional dysregulation. Future longitudinal studies investigating the effect of mood state on FER performance in BD are warranted.

Verbal memory impairments in mood disorders and psychotic disorders: A systematic review of comparative studies

BACKGROUND

Mood and psychotic disorders are both associated with verbal memory impairments. Verbal memory represents an important treatment target for both disorders. However, whether the neurocognitive and neurophysiological profiles of verbal memory impairments differ between specific disorders within these two diagnostic categories and healthy controls remains unclear. The current systematic review synthesized findings from comparative studies which used behavioural and neuroimaging tasks to investigate verbal memory impairments between: (1) mood disorder, psychotic disorder, and healthy control groups; and (2) mood disorder without psychotic features, mood disorder with psychotic features, and healthy control groups.

METHODS

The search strategy combined terms related to three main concepts: 'mood disorders', 'psychotic disorders', and 'verbal memory'. Searches were executed in Embase, MEDLINE, PsycInfo, and PubMed databases. A total of 38 articles met the full eligibility criteria and were included in the final narrative synthesis. Findings were stratified by memory domain (overall composite score, verbal working memory, immediate recall, delayed recall, and recognition memory) and by illness phase (acute and non-acute).

RESULTS

Mood and psychotic disorders displayed consistent verbal memory impairments compared to healthy controls during the acute and non-acute phases. Few significant differences were identified in the literature between mood and psychotic disorders, and between mood disorders with and without psychotic features. Individuals with schizophrenia were found to have decreased immediate and delayed verbal recall performance compared to bipolar disorder groups during the acute phase. Major depressive disorder groups with psychotic features were also found to have decreased delayed verbal recall performance compared to those without psychosis during the acute phase. No consistent differences were identified between mood and psychotic disorders during the non-acute phase. Finally, preliminary evidence suggests there may be functional abnormalities in important frontal and temporal brain regions related to verbal memory difficulties in both mood and psychotic disorders.

DISCUSSION

The current findings have potential implications for the diagnosis and treatment of cognitive impairments in mood and psychotic disorders. Verbal recall memory may serve as a sensitive tool in the risk stratification of cognitive impairments for certain mood and psychotic disorders. Moreover, since no widespread differences between clinical groups were identified, the evidence supports providing targeted interventions for verbal memory, such as pharmacological and non-pharmacological interventions, through a trans-diagnostic approach in mood and psychotic disorders.

White matter integrity in bipolar disorder investigated with diffusion tensor magnetic resonance imaging and fractal geometry

BACKGROUND

Growing evidence suggests the presence of white matter (WM) alterations in bipolar disorder (BD). In this study we aimed to investigate the state of WM structures, in terms of tissue integrity and morphological complexity, in BD patients compared to healthy controls (HC), in an attempt to better elucidate the microstructural changes associated with BD.

METHODS

We collected a dataset of 399 Diffusion Tensor Magnetic Resonance Imaging (167 BD and 232 healthy controls) images, acquired at five different sites, which was processed with Tract-Based Spatial Statistics (TBSS) and fractal analysis.

RESULTS

The TBSS analysis demonstrated significantly lower FA values in the BD group. Diffusion abnormalities were primarily located in the temporo-parietal network. The Fractal Dimension (FD) analysis did not reveal consistent significant differences in the morphological complexity of WM structures between the groups. When the FD values of patients were considered individually, it is possible to notice some localized significant deviations from the healthy population.

LIMITATIONS

DTI sequences have not been harmonized before acquisition, samples' sizes are heterogeneous.

CONCLUSIONS

This study, by applying both TBSS and FD analyses, allows to evaluate diffusion and structural alterations of WM at the same time. The evaluation of WM integrity from these two different perspectives could be useful to better understand the pathophysiological and morphological changes underpinning bipolar disorder.

Involvement of the ipsilateral-to-the-pain anterior-superior hypothalamic subunit in chronic cluster headache

BACKGROUND

Despite hypothalamus has long being considered to be involved in the pathophysiology of cluster headache, the inconsistencies of previous neuroimaging studies and a limited understanding of the hypothalamic areas involved, impede a comprehensive interpretation of its involvement in this condition.

METHODS

We used an automated algorithm to extract hypothalamic subunit volumes from 105 cluster headache patients (57 chronic and 48 episodic) and 59 healthy individuals; after correcting the measures for the respective intracranial volumes, we performed the relevant comparisons employing logist regression models. Only for subunits that emerged as abnormal, we calculated their correlation with the years of illness and the number of headache attacks per day, and the effects of lithium treatment. As a post-hoc approach, using the 7 T resting-state fMRI dataset from the Human Connectome Project, we investigated whether the observed abnormal subunit, comprising the paraventricular nucleus and preoptic area, shows robust functional connectivity with the mesocorticolimbic system, which is known to be modulated by oxytocin neurons in the paraventricular nucleus and that is is abnormal in chronic cluster headache patients.

RESULTS

Patients with chronic (but not episodic) cluster headache, compared to control participants, present an increased volume of the anterior-superior hypothalamic subunit ipsilateral to the pain, which, remarkably, also correlates significantly with the number of daily attacks. The post-hoc approach showed that this hypothalamic area presents robust functional connectivity with the mesocorticolimbic system under physiological conditions. No evidence of the effects of lithium treatment on this abnormal subunit was found.

CONCLUSIONS

We identified the ipsilateral-to-the-pain antero-superior subunit, where the paraventricular nucleus and preoptic area are located, as the key hypothalamic region of the pathophysiology of chronic cluster headache. The significant correlation between the volume of this area and the number of daily attacks crucially reinforces this interpretation. The well-known roles of the paraventricular nucleus in coordinating autonomic and neuroendocrine flow in stress adaptation and modulation of trigeminovascular mechanisms offer important insights into the understanding of the pathophysiology of cluster headache.

The Genetic Architecture of Amygdala Nuclei

BACKGROUND

Whereas genetic variants influencing total amygdala volume have been identified, the genetic architecture of its distinct nuclei has yet to be explored. We aimed to investigate whether increased phenotypic specificity through nuclei segmentation aids genetic discoverability and elucidates the extent of shared genetic architecture and biological pathways with related disorders.

METHODS

T1-weighted brain magnetic resonance imaging scans (N = 36,352, 52% female) from the UK Biobank were segmented into 9 amygdala nuclei with FreeSurfer (version 6.1). Genome-wide association analyses were performed on the entire sample, a European-only subset (n = 31,690), and a generalization (transancestry) subset (n = 4662). We estimated single nucleotide polymorphism-based heritability; derived polygenicity, discoverability, and power estimates; and investigated genetic correlations and shared loci with psychiatric disorders.

RESULTS

The heritability of the nuclei ranged from 0.17 to 0.33. Across the whole amygdala and the nuclei volumes, we identified 28 novel genome-wide significant (padj < 5 × 10-9) loci in the European analysis, with significant en masse replication for the whole amygdala and central nucleus volumes in the generalization analysis, and we identified 10 additional candidate loci in the combined analysis. The central nucleus had the highest statistical power for discovery. The significantly associated genes and pathways showed unique and shared effects across the nuclei, including immune-related pathways. Shared variants were identified between specific nuclei and autism spectrum disorder, Alzheimer's disease, Parkinson's disease, bipolar disorder, and schizophrenia.

CONCLUSIONS

Through investigation of amygdala nuclei volumes, we have identified novel candidate loci in the neurobiology of amygdala volume. These nuclei volumes have unique associations with biological pathways and genetic overlap with psychiatric disorders.

Impaired neural stress resistance and loss of REST in bipolar disorder

Neurodevelopmental changes and impaired stress resistance have been implicated in the pathogenesis of bipolar disorder (BD), but the underlying regulatory mechanisms are unresolved. Here we describe a human cerebral organoid model of BD that exhibits altered neural development, elevated neural network activity, and a major shift in the transcriptome. These phenotypic changes were reproduced in cerebral organoids generated from iPS cell lines derived in different laboratories. The BD cerebral organoid transcriptome showed highly significant enrichment for gene targets of the transcriptional repressor REST. This was associated with reduced nuclear REST and REST binding to target gene recognition sites. Reducing the oxygen concentration in organoid cultures to a physiological range ameliorated the developmental phenotype and restored REST expression. These effects were mimicked by treatment with lithium. Reduced nuclear REST and derepression of REST targets genes were also observed in the prefrontal cortex of BD patients. Thus, an impaired cellular stress response in BD cerebral organoids leads to altered neural development and transcriptional dysregulation associated with downregulation of REST. These findings provide a new model and conceptual framework for exploring the molecular basis of BD.

Large-Scale Neuroimaging of Mental Illness

Neuroimaging has provided important insights into the brain variations related to mental illness. Inconsistencies in prior studies, however, call for methods that lead to more replicable and generalizable brain markers that can reliably predict illness severity, treatment course, and prognosis. A paradigm shift is underway with large-scale international research teams actively pooling data and resources to drive consensus findings and test emerging methods aimed at achieving the goals of precision psychiatry. In parallel with large-scale psychiatric genomics studies, international consortia combining neuroimaging data are mapping the transdiagnostic brain signatures of mental illness on an unprecedented scale. This chapter discusses the major challenges, recent findings, and a roadmap for developing better neuroimaging-based tools and markers for mental illness.

State- and trait-related dysfunctions in bipolar disorder across different mood states: a graph theory study

BACKGROUND

The interplay between state- and trait-related disruptions in structural networks remains unclear in bipolar disorder (BD), but graph theory can offer insights into global and local network changes. We sought to use diffusion-tensor imaging (DTI) and graph theory approaches to analyze structural topological properties across distinct mood states and identify high-risk individuals by examining state- and trait-related impairments in BD.

METHODS

We studied changes in white matter network among patients with BD and healthy controls, exploring relationships with clinical variables. Secondary analysis involved comparing patients with BD with unaffected people at high genetic risk for BD.

RESULTS

We included 152 patients with BD, including 52 with depressive BD (DBD), 64 with euthymic BD (EBD) and 36 with manic BD (MBD); we also included 75 healthy controls. Secondary analyses involved 27 unaffected people at high genetic risk for BD. Patients with DBD and MBD exhibited significantly lower global efficiencies than those with EBD and healthy controls, with patients with DBD showing the lowest global efficiencies. In addition, patients with DBD displayed impaired local efficiency and normalized clustering coefficient (γ). At a global level, γ correlated negatively with depression and anxiety. Compared with healthy controls, and across mood states, patients with BD showed abnormal shortest path lengths in the frontolimbic circuit, a trend mirrored among those at high genetic risk for BD.

LIMITATIONS

Considerations include medication effects, absence of recorded BD episode counts and the cross-sectional nature of the study.

CONCLUSION

Mood-specific whole-brain network metrics could serve as potential biomarkers in BD for transitions between mood states. Moreover, these findings contribute to evidence of trait-related frontolimbic circuit irregularities, shedding light on underlying pathophysiological mechanisms in BD.

Altered Sex Differences in Hippocampal Subfield Volumes in Schizophrenia

BACKGROUND AND HYPOTHESIS

The hippocampus is a heterogenous brain structure that differs between the sexes and has been implicated in the pathophysiology of psychiatric illnesses. Here, we explored sex and diagnostic group differences in hippocampal subfield volumes, in individuals with schizophrenia spectrum disorder (SZ), bipolar disorders (BD), and healthy controls (CTL).

STUDY DESIGN

One thousand and five hundred and twenty-one participants underwent T1-weighted magnetic resonance imaging (SZ, n = 452, mean age 30.7 ± 9.2 [SD] years, males 59.1%; BD, n = 316, 33.7 ± 11.4, 41.5%; CTL, n = 753, 34.1 ± 9.1, 55.6%). Total hippocampal, subfield, and intracranial volumes were estimated with Freesurfer (v6.0.0). Analysis of covariance and multiple regression models were fitted to examine sex-by-diagnostic (sub)group interactions in volume. In SZ and BD, separately, associations between volumes and clinical as well as cognitive measures were examined between the sexes using regression models.

STUDY RESULTS

Significant sex-by-group interactions were found for the total hippocampus, dentate gyrus, molecular layer, presubiculum, fimbria, hippocampal-amygdaloid transition area, and CA4, indicating a larger volumetric deficit in male patients relative to female patients when compared with same-sex CTL. Subgroup analyses revealed that this interaction was driven by males with schizophrenia. Effect sizes were overall small (partial η < 0.02). We found no significant sex differences in the associations between hippocampal volumes and clinical or cognitive measures in SZ and BD.

CONCLUSIONS

Using a well-powered sample, our findings indicate that the pattern of morphological sex differences in hippocampal subfields is altered in individuals with schizophrenia relative to CTL, due to higher volumetric deficits in males.

Predictive modelling of brain disorders with magnetic resonance imaging: A systematic review of modelling practices, transparency, and interpretability in the use of convolutional neural networks

Brain disorders comprise several psychiatric and neurological disorders which can be characterized by impaired cognition, mood alteration, psychosis, depressive episodes, and neurodegeneration. Clinical diagnoses primarily rely on a combination of life history information and questionnaires, with a distinct lack of discriminative biomarkers in use for psychiatric disorders. Symptoms across brain conditions are associated with functional alterations of cognitive and emotional processes, which can correlate with anatomical variation; structural magnetic resonance imaging (MRI) data of the brain are therefore an important focus of research, particularly for predictive modelling. With the advent of large MRI data consortia (such as the Alzheimer's Disease Neuroimaging Initiative) facilitating a greater number of MRI-based classification studies, convolutional neural networks (CNNs)-deep learning models well suited to image processing tasks-have become increasingly popular for research into brain conditions. This has resulted in a myriad of studies reporting impressive predictive performances, demonstrating the potential clinical value of deep learning systems. However, methodologies can vary widely across studies, making them difficult to compare and/or reproduce, potentially limiting their clinical application. Here, we conduct a qualitative systematic literature review of 55 studies carrying out CNN-based predictive modelling of brain disorders using MRI data and evaluate them based on three principles-modelling practices, transparency, and interpretability. We propose several recommendations to enhance the potential for the integration of CNNs into clinical care.

Subcortical volumetric alterations in four major psychiatric disorders: a mega-analysis study of 5604 subjects and a volumetric data-driven approach for classification

Differential diagnosis is sometimes difficult in practical psychiatric settings, in terms of using the current diagnostic system based on presenting symptoms and signs. The creation of a novel diagnostic system using objective biomarkers is expected to take place. Neuroimaging studies and others reported that subcortical brain structures are the hubs for various psycho-behavioral functions, while there are so far no neuroimaging data-driven clinical criteria overcoming limitations of the current diagnostic system, which would reflect cognitive/social functioning. Prior to the main analysis, we conducted a large-scale multisite study of subcortical volumetric and lateralization alterations in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder using T1-weighted images of 5604 subjects (3078 controls and 2526 patients). We demonstrated larger lateral ventricles volume in schizophrenia, bipolar disorder, and major depressive disorder, smaller hippocampus volume in schizophrenia and bipolar disorder, and schizophrenia-specific smaller amygdala, thalamus, and accumbens volumes and larger caudate, putamen, and pallidum volumes. In addition, we observed a leftward alteration of lateralization for pallidum volume specifically in schizophrenia. Moreover, as our main objective, we clustered the 5,604 subjects based on subcortical volumes, and explored whether data-driven clustering results can explain cognitive/social functioning in the subcohorts. We showed a four-biotype classification, namely extremely (Brain Biotype [BB] 1) and moderately smaller limbic regions (BB2), larger basal ganglia (BB3), and normal volumes (BB4), being associated with cognitive/social functioning. Specifically, BB1 and BB2-3 were associated with severe and mild cognitive/social impairment, respectively, while BB4 was characterized by normal cognitive/social functioning. Our results may lead to the future creation of novel biological data-driven psychiatric diagnostic criteria, which may be expected to be useful for prediction or therapeutic selection.

Factors that can influence neurocognitive performance: a case study in a controlled environment

This is a case study of a patient in her 50s who presents with severe malnutrition, alcohol dependence, and untreated Bipolar Affective Disorder. She was hospitalized multiple times and placed in a group home 1 year after symptom onset. Cognitive and functional improvements are observed over a 6-year period, as demonstrated by 3 comprehensive neuropsychological evaluations. Residing in a monitored and structured environment for 6 years, with stability in psychiatric medications, monitored nutrition and abstinence from alcohol are attributed to this improvement. This study provides unique evidence of the impact of balanced nutrition and improvements in psychiatric symptoms on cognition.

Effect of lithium in pyramidal neurons of Cornu Ammonis in an animal model

Bipolar disorder has been associated with a decrease in hippocampal size, and lithium appears to reverse this neuroanatomical abnormality. The objective of this work was to evaluate, at a cellular level, the size of both cell body and nucleus of pyramidal neurons located throughout the Cornu Ammonis (CA1 to CA4 regions). To perform this duty, we used 16 rats that were randomized into two groups: control and dietary lithium-treated. After one month, they were sacrificed and their brains removed for histopathological analysis. Serial photos of the entire Cornu Ammonis were taken and, after dividing them into 4 regions of interest, we measured the cell body and nucleus on each pyramidal neuron belonging to the first 5 photos of each region of interest. As a result of this histological analysis, cell body area and nuclear area were significantly larger in the experimental group in a specific area of the Cornu Ammonis that could correspond to CA2 or the transition between CA1 and CA2. These results suggest that the effect of lithium is not homogeneous throughout the hippocampus and allows directing future studies to a specific area of this structure.

Borderline shades: Morphometric features predict borderline personality traits but not histrionic traits

Borderline personality disorder (BPD) is one of the most diagnosed disorders in clinical settings. Besides the fully diagnosed disorder, borderline personality traits (BPT) are quite common in the general population. Prior studies have investigated the neural correlates of BPD but not of BPT. This paper investigates the neural correlates of BPT in a subclinical population using a supervised machine learning method known as Kernel Ridge Regression (KRR) to build predictive models. Additionally, we want to determine whether the same brain areas involved in BPD are also involved in subclinical BPT. Recent attempts to characterize the specific role of resting state-derived macro networks in BPD have highlighted the role of the default mode network. However, it is not known if this extends to the subclinical population. Finally, we wanted to test the hypothesis that the same circuitry that predicts BPT can also predict histrionic personality traits. Histrionic personality is sometimes considered a milder form of BPD, and making a differential diagnosis between the two may be difficult. For the first time KRR was applied to structural images of 135 individuals to predict BPT, based on the whole brain, on a circuit previously found to correctly classify BPD, and on the five macro-networks. At a whole brain level, results show that frontal and parietal regions, as well as the Heschl's area, the thalamus, the cingulum, and the insula, are able to predict borderline traits. BPT predictions increase when considering only the regions limited to the brain circuit derived from a study on BPD, confirming a certain overlap in brain structure between subclinical and clinical samples. Of all the five macro networks, only the DMN successfully predicts BPD, confirming previous observations on its role in the BPD. Histrionic traits could not be predicted by the BPT circuit. The results have implications for the diagnosis of BPD and a dimensional model of personality.

The effect of chronic lithium treatment on hippocampal progenitor cells: Transcriptomic analysis and systems pharmacology

OBJECTIVE

To identify the genomics underpinning the increased volume of the hippocampus after long-term administration of lithium (Li) in bipolar disorder patients, hypothesizing the possible contribution of cell growth and differentiation pathways to this complication.

METHODS

RNA-seq profiles of four samples of hippocampal progenitor cells chronically treated with a high dose of Li and three samples chronically treated with the therapeutic dose were retrieved from NCBI-GEO. The raw data underwent filtration, quality control, expression fold change, adjusted significance, functional enrichment, and pharmacogenomic analyses.

RESULTS

CCND1, LOXL2, and PRNP were identified as the genes involved in the drug response and the chronic effects of Li in the hippocampal cells. GSK-3β was also a hub in the pharmacogenomic network of Li. In addition, ZMPSTE24 and DHX35 were identified as the important genes in lithium therapy.

CONCLUSIONS

As shown by gene ontology results, these findings conclude that lithium may increase the size of the hippocampus in bipolar patients by stimulating the generation of new neurons and promoting their differentiation into neuroblasts, neurons, or microglia.

Morphological abnormalities in youth with bipolar disorder and their relationship to clinical characteristics

OBJECTIVES

To characterize the neuroanatomy of BD in youth and its correlation to clinical characteristics.

METHODS

The current study includes a sample of 105 unmedicated youth with first-episode BD, aged between 10.1 and 17.9 years, and 61 healthy comparison adolescents, aged between 10.1 and 17.7 years, who were matched for age, race, sex, socioeconomic status, intelligence quotient (IQ), and education level. T1-weighted magnetic resonance imaging (MRI) images were obtained using a 4 T MRI scanner. Freesurfer (V6.0) was used to preprocess and parcellate the structural data, and 68 cortical and 12 subcortical regions were considered for statistical comparisons. The relationship between morphological deficits and clinical and demographic characteristics were evaluated using linear models.

RESULTS

Compared with healthy youth, youth with BD had decreased cortical thickness in frontal, parietal, and anterior cingulate regions. These youth also showed decreased gray matter volumes in 6 of the 12 subcortical regions examined including thalamus, putamen, amygdala and caudate. In further subgroup analyses, we found that youth with BD with comorbid attention-deficit hyperactivity disorder (ADHD) or with psychotic symptoms had more significant deficits in subcortical gray matter volume.

LIMITATIONS

We cannot provide information about the course of structural changes and impact of treatment and illness progression.

CONCLUSIONS

Our findings indicate that youth with BD have significant neurostructural deficits in both cortical and subcortical regions mainly located in the regions related to emotion processing and regulation. Variability in clinical characteristics and comorbidities may contribute to the severity of anatomic alterations in this disorder.

Supra-second interval timing in bipolar disorder: examining the role of disorder sub-type, mood, and medication status

BACKGROUND

Widely reported by bipolar disorder (BD) patients, cognitive symptoms, including deficits in executive function, memory, attention, and timing are under-studied. Work suggests that individuals with BD show impairments in interval timing tasks, including supra-second, sub-second, and implicit motor timing compared to the neuronormative population. However, how time perception differs within individuals with BD based on disorder sub-type (BDI vs II), depressed mood, or antipsychotic medication-use has not been thoroughly investigated. The present work administered a supra-second interval timing task concurrent with electroencephalography (EEG) to patients with BD and a neuronormative comparison group. As this task is known to elicit frontal theta oscillations, signal from the frontal (Fz) lead was analyzed at rest and during the task.

RESULTS

Results suggest that individuals with BD show impairments in supra-second interval timing and reduced frontal theta power during the task compared to neuronormative controls. However, within BD sub-groups, neither time perception nor frontal theta differed in accordance with BD sub-type, depressed mood, or antipsychotic medication use.

CONCLUSIONS

This work suggests that BD sub-type, depressed mood status or antipsychotic medication use does not alter timing profile or frontal theta activity. Together with previous work, these findings point to timing impairments in BD patients across a wide range of modalities and durations indicating that an altered ability to assess the passage of time may be a fundamental cognitive abnormality in BD.

Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants

BACKGROUND

Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

METHODS

We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.

RESULTS

BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.

CONCLUSIONS

We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Antidepressant emergent mood switch in major depressive disorder: onset, clinical correlates and impact on suicidality

Antidepressant (AD)- emergent mood switch (AEMS) is a common complication of bipolar depression. This study aimed to investigate the prevalence and clinical correlates of subthreshold AEMS (i.e. not fulfilling DSM criteria for hypomanic episodes) in major depressive disorder (MDD) and, prognostically, its impact on AD treatment outcome and suicidality. The study involved 425 outpatients with MDD followed during the acute phase (12 weeks) and continuation (weeks 13-28) AD treatment. AEMS was assessed through the Altman Self-Rating Mania scale (ASRM ≥ 6). Several clinical features differentiated individuals with or without subthreshold AEMS (n = 204 vs. 221): negative self-perception [odds ratio (OR) 1.017-1.565]; panic disorder (OR 1.000-1.091); subthreshold hypomanic episodes (OR 1.466-13.352); childhood emotional abuse (OR 1.053-2.447); lifetime suicidal behaviour (OR 1.027-1.236); AD-related remission (χ 2  = 22.903 P  < 0.0001) and suicide ideation (χ 2  = 16.701 P  < 0.0001). In AEMS earlier onset showed a strong correlation with bipolar spectrum disorder (overall score: P  = 0.0053; mixed depression: P  = 0.0154; subthreshold hypomania: P  = 0.0150) whereas late-onset was associated with more severe suicidal behaviour ( P  < 0.001). In conclusion, our results demonstrate that subthreshold mood switches occur frequently in unipolar depression during acute AD treatment as well as in continuation phase. Time of switch onset seems to have the greatest diagnostic and prognostic value.

Subcortical Brain Alterations in Carriers of Genomic Copy Number Variants

OBJECTIVE

Copy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disorders (NPDs), including autism (ASD) and schizophrenia. Little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, the authors investigated gross volume, vertex-level thickness, and surface maps of subcortical structures in 11 CNVs and six NPDs.

METHODS

Subcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (CNVs at 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2; age range, 6-80 years; 340 males) and 782 control subjects (age range, 6-80 years; 387 males) as well as ENIGMA summary statistics for ASD, schizophrenia, attention deficit hyperactivity disorder, obsessive-compulsive disorder, bipolar disorder, and major depression.

RESULTS

All CNVs showed alterations in at least one subcortical measure. Each structure was affected by at least two CNVs, and the hippocampus and amygdala were affected by five. Shape analyses detected subregional alterations that were averaged out in volume analyses. A common latent dimension was identified, characterized by opposing effects on the hippocampus/amygdala and putamen/pallidum, across CNVs and across NPDs. Effect sizes of CNVs on subcortical volume, thickness, and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and schizophrenia.

CONCLUSIONS

The findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions, as well distinct effects, with some CNVs clustering with adult-onset conditions and others with ASD. These findings provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD and why a single CNV increases the risk for a diverse set of NPDs.

Progressive grey matter alterations in bipolar disorder across the life span - A systematic review

OBJECTIVES

To elucidate the relationship between the course of bipolar disorder (BD) and structural brain changes across the life span, we conducted a systematic review of longitudinal imaging studies in adolescent and adult BD patients.

METHODS

Eleven studies with 329 BD patients and 277 controls met our PICOS criteria (participants, intervention, comparison, outcome and study design): BD diagnosis based on DSM criteria, natural course of disease, comparison of grey matter changes in BD individuals over ≥1-year interval between scans.

RESULTS

The selected studies yielded heterogeneous findings, partly due to varying patient characteristics, data acquisition and statistical models. Mood episodes were associated with greater grey matter loss in frontal brain regions over time. Brain volume decreased or remained stable in adolescent patients, whereas it increased in healthy adolescents. Adult BD patients showed increased cortical thinning and brain structural decline. In particular, disease onset in adolescence was associated with amygdala volume reduction, which was not reported in adult BD.

CONCLUSIONS

The evidence collected suggests that the progression of BD impairs adolescent brain development and accelerates structural brain decline across the lifespan. Age-specific changes in amygdala volume in adolescent BD suggest that reduced amygdala volume is a correlate of early onset BD. Clarifying the role of BD in brain development across the lifespan promises a deeper understanding of the progression of BD patients through different developmental episodes.

Contributions of circadian clock genes to cell survival in fibroblast models of lithium-responsive bipolar disorder

Bipolar disorder (BD) is characterized by mood episodes, disrupted circadian rhythms and gray matter reduction in the brain. Lithium is an effective pharmacotherapy for BD, but not all patients respond to treatment. Lithium has neuroprotective properties and beneficial effects on circadian rhythms that may distinguish lithium responders (Li-R) from non-responders (Li-NR). The circadian clock regulates molecular pathways involved in apoptosis and cell survival, but how this overlap impacts BD and/or lithium responsiveness is unknown. In primary fibroblasts from Li-R/Li-NR BD patients and controls, we found patterns of co-expression among circadian clock and cell survival genes that distinguished BD vs. control, and Li-R vs. Li-NR cells. In cellular models of apoptosis using staurosporine (STS), lithium preferentially protected fibroblasts against apoptosis in BD vs. control samples, regardless of Li-R/Li-NR status. When examining the effects of lithium treatment of cells in vitro, caspase activation by lithium correlated with period alteration, but the relationship differed in control, Li-R and Li-NR samples. Knockdown of Per1 and Per3 in mouse fibroblasts altered caspase activity, cell death and circadian rhythms in an opposite manner. In BD cells, genetic variation in PER1 and PER3 predicted sensitivity to apoptosis in a manner consistent with knockdown studies. We conclude that distinct patterns of coordination between circadian clock and cell survival genes in BD may help predict lithium response.