Disrupted brain structural connectivity in Pediatric Bipolar Disorder with psychosis

White matter changes in paediatric bipolar disorder: A systematic review of diffusion magnetic resonance imaging studiesA systematic review of diffusion magnetic resonance imaging studies

BACKGROUND

Paediatric bipolar disorder (PBD) is characterized by severe mood fluctuations that deviate from typical childhood emotional development. Despite the efforts, the pathophysiology of this disorder is not well understood yet. In this review, we aimed to synthesize existing diffusion magnetic resonance imaging (dMRI) research findings in PBD.

METHODS

A literature search was conducted using PubMed, Embase, Scopus, and Web of Science databases to identify relevant studies published before April 2024.

RESULTS

A total of 23 studies were included in the review. The findings showed variations of fractional anisotropy (FA), axial diffusivity, radial diffusivity, and apparent diffusion coefficient in PBD compared to healthy controls (HCs). Key findings included decreased FA in the anterior cingulate, anterior corona radiata, and corpus callosum, particularly the genu, which correlated with clinical symptoms. Furthermore, longitudinal studies emphasized the significance of the uncinate fasciculus as having atypical developmental trajectories in PBD compared to HCs. In addition, graph analysis revealed widespread changes in structural connectivity, especially affecting the orbitofrontal cortex, frontal gyrus, and basal ganglia. Lastly, machine learning models showed promising results in differentiating PBD from HCs.

LIMITATIONS

Cross-sectional design of the studies, small sample sizes, and different imaging protocols preclude integration of the findings.

CONCLUSION

PBD seems to be associated with widespread structural changes compared to HC. Understanding these changes, which might account for the clinical manifestations of this disorder, increase our knowledge of the neurobiological underpinnings of PBD. This, in turn, may help develop more effective treatments for this disorder.

Functional network characteristics in adolescent psychotic mood disorder: associations with symptom severity and treatment effects

Adolescent psychotic mood disorder (MDP) is a specific phenotype that characterized by more severe symptoms and prognosis compared to nonpsychotic mood disorder (MDNP). But the underlying neural mechanisms remain unknown, and graph theory analysis can help to understand possible mechanisms of psychotic symptoms from the perspective of functional networks. A total of 177 adolescent patients with mood disorders were recruited, including 61 MDP and 116 MDNP. Functional networks were constructed, and topological properties were compared between the two groups at baseline and after treatment, and the association between properties changes and symptom improvement was explored. Compared to the MDNP group, the MDP group exhibited higher small-world properties (FDR q = 0.003) and normalized clustering coefficients (FDR q = 0.008) but demonstrated decreased nodal properties in the superior temporal gyrus (STG), Heschl's gyrus, and medial cingulate gyrus (all FDR q < 0.05). These properties were found to be correlated with the severity of psychotic symptoms. Topological properties also changed with improvement of psychotic symptoms after treatment, and changes in degree centrality of STG in the MDP was significantly positive correlated with improvement of psychotic symptoms (r = 0.377, P = 0.031). This study indicated that functional networks are more severely impaired in patients with psychotic symptoms. Topological properties, particularly those associated with the STG, hold promise as emerging metrics for assessing symptoms and treatment efficacy in patients with psychotic symptoms.

The Different Impact of Depressive or Manic First-episode on Pediatric Bipolar Disorder Patients: Evidence From Resting-state fMRI

Bipolar disorder may begin as depression or mania, which can affect the treatment and prognosis of bipolar disorder. However, the physiological and pathological differences of pediatric bipolar disorder (PBD) patients with different onset symptoms are not clear. The purpose of this study was to investigate the differences of clinical, cognitive function and intrinsic brain networks in PBD patients with first-episode depression and first-episode mania. A total of 63 participants, including 43 patients and 20 healthy controls, underwent resting-state fMRI scans. PBD patients were classified as first-episode depressive and first-episode manic based on their first-episode symptoms. Cognitive tests were used to measure attention and memory of all participants. Independent component analysis (ICA) was used to extract the salience network (SN), default-mode network (DMN), central executive network (ECN) and limbic network (LN) for each participant. Spearman rank correlation analysis was performed between abnormal activation and clinical and cognitive measures. The results showed that there were differences in cognitive functions such as attention and visual memory between first-episode depression and mania, as well as differences activation in anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), precuneus, inferior parietal cortex and parahippocampus. And significant associations of brain activity with clinical assessments or cognition were found in different patients. In conclusion, we found differential impairments in cognitive and brain network activation in first-episode depressive and first-episode manic PBD patients, and correlations were found between these impairments. These evidences may shed light on the different developmental paths of bipolar disorder.

Does the Brain Matter? Cortical Alterations in Pediatric Bipolar Disorder: A Critical Review of Structural and Functional Magnetic Resonance Studies

Pediatric bipolar disorder (PBD) is associated with significant psychosocial impairment, high use of mental health services and a high number of relapses and hospitalization. Neuroimaging techniques provide the opportunity to study the neurodevelopmental processes underlying PBD, helping to identify the endophenotypic markers of illness and early biological markers of PBD. The aim of the study is to review available studies assessing structural and functional brain correlates associated with PBD. PubMed, ISI Web of Knowledge and PsychINFO databases have been searched. Studies were included if they enrolled patients aged 0-18 years with a main diagnosis of PBD according to ICD or DSM made by a mental health professional, adopted structural and/or functional magnetic resonance as the main neuroimaging method, were written in English and included a comparison with healthy subjects. Of the 400 identified articles, 46 papers were included. Patients with PBD present functional and anatomic alterations in structures normally affecting regulations and cognition. Structural neuroimaging revealed a significant reduction in gray matter, with cortical thinning in bilateral frontal, parietal and occipital cortices. Functional neuroimaging studies reported a reduced engagement of the frontolimbic and hyperactivation of the frontostriatal circuitry. Available studies on brain connectivity in PBD patients potentially indicate less efficient connections between regions involved in cognitive and emotional functions. A greater functional definition of alteration in brain functioning of PBD patients will be useful to set up a developmentally sensitive targeted pharmacological and nonpharmacological intervention.

Dynamic sensitivity analysis: Defining personalised strategies to drive brain state transitions via whole brain modelling

Traditionally, in neuroimaging, model-free analyses are used to find significant differences between brain states via signal detection theory. Depending on the a priori assumptions about the underlying data, different spatio-temporal features can be analysed. Alternatively, model-based techniques infer features from the data and compare significance from model parameters. However, to assess transitions from one brain state to another remains a challenge in current paradigms. Here, we introduce a "Dynamic Sensitivity Analysis" framework that quantifies transitions between brain states in terms of stimulation ability to rebalance spatio-temporal brain activity towards a target state such as healthy brain dynamics. In practice, it means building a whole-brain model fitted to the spatio-temporal description of brain dynamics, and applying systematic stimulations in-silico to assess the optimal strategy to drive brain dynamics towards a target state. Further, we show how Dynamic Sensitivity Analysis extends to various brain stimulation paradigms, ultimately contributing to improving the efficacy of personalised clinical interventions.

Reduced Modular Segregation of White Matter Brain Networks in Attention Deficit Hyperactivity Disorder

OBJECTIVE

Despite studies reporting alterations in the brain networks of patients with ADHD, alterations in the modularity of white matter (WM) networks are still unclear.

METHOD

Based on the results of module division by generalized Louvain algorithm, the modularity of ADHD was evaluated. The correlation between the modular changes of ADHD and its clinical characteristics was analyzed.

RESULTS

The participation coefficient and the connectivity between modules of ADHD increased, and the modularity coefficient decreased. Provincial hubs of ADHD did not change, and the number of connector hubs increased. All results showed that the modular segregation of WM networks of ADHD decreased. Modules with reduced modular segregation are mainly responsible for language and motor functions. Moreover, modularity showed evident correlation with the symptoms of ADHD.

CONCLUSION

The modularity changes in WM network provided a novel insight into the understanding of brain cognitive alterations in ADHD.

Development of Thalamocortical Structural Connectivity in Typically Developing and Psychosis Spectrum Youths

BACKGROUND

Thalamocortical white matter connectivity is disrupted in psychosis and is hypothesized to play a role in its etiology and associated cognitive impairment. Attenuated cognitive symptoms often begin in adolescence, during a critical phase of white matter and cognitive development. However, little is known about the development of thalamocortical white matter connectivity and its association with cognition.

METHODS

This study characterized effects of age, sex, psychosis symptomatology, and cognition in thalamocortical networks in a large sample of youths (N = 1144, ages 8-22 years, 46% male) from the Philadelphia Neurodevelopmental Cohort, which included 316 typically developing youths, 330 youths on the psychosis spectrum, and 498 youths with other psychopathology. Probabilistic tractography was used to quantify percent total connectivity between the thalamus and six cortical regions and assess microstructural properties (i.e., fractional anisotropy) of thalamocortical white matter tracts.

RESULTS

Overall, percent total connectivity of the thalamus was weakly associated with age and was not associated with psychopathology or cognition. In contrast, fractional anisotropy of all thalamocortical tracts increased significantly with age, was generally higher in males than females, and was lowest in youths on the psychosis spectrum. Fractional anisotropy of tracts linking the thalamus to prefrontal and posterior parietal cortices was related to better cognitive function across subjects.

CONCLUSIONS

By characterizing the pattern of typical development and alterations in those at risk for psychotic disorders, this study provides a foundation for further conceptualization of thalamocortical white matter microstructure as a marker of neurodevelopment supporting cognition and an important risk marker for psychosis.

Cell-type-specific genes associated with cortical structural abnormalities in pediatric bipolar disorder

Background

Pediatric bipolar disorder (PBD) has been proven to be related to abnormal brain structural connectivity, but how the abnormalities in PBD correlate with gene expression is debated.

Objective

This study aims at identification of cell-type-specific gene modules based on cortical structural differences in PBD.

Methods

Morphometric similarity networks (MSN) were computed as a marker of interareal cortical connectivity based on MRI data from 102 participants (59 patients and 43 controls). Partial least squares (PLS) regression was used to calculate MSN differences related to transcriptomic data in AHBA. The biological processes and cortical cell types associated with this gene expression profile were determined by gene enrichment tools.

Results

MSN analysis results demonstrated differences of cortical structure between individuals diagnosed with PBD and healthy control participants. MSN differences were spatially correlated with the PBD-related weighted genes. The weighted genes were enriched for "trans-synaptic signaling" and "regulation of ion transport", and showed significant specific expression in excitatory and inhibitory neurons.

Conclusions

This study identified the genes that contributed to structural network aberrations in PBD. It was found that transcriptional changes of excitatory and inhibitory neurons might be associated with abnormal brain structural connectivity in PBD.

Dissociated brain functional connectivity of fast versus slow frequencies underlying individual differences in fluid intelligence: a DTI and MEG study

Brain network analysis represents a powerful technique to gain insights into the connectivity profile characterizing individuals with different levels of fluid intelligence (Gf). Several studies have used diffusion tensor imaging (DTI) and slow-oscillatory resting-state fMRI (rs-fMRI) to examine the anatomical and functional aspects of human brain networks that support intelligence. In this study, we expand this line of research by investigating fast-oscillatory functional networks. We performed graph theory analyses on resting-state magnetoencephalographic (MEG) signal, in addition to structural brain networks from DTI data, comparing degree, modularity and segregation coefficient across the brain of individuals with high versus average Gf scores. Our results show that high Gf individuals have stronger degree and lower segregation coefficient than average Gf participants in a significantly higher number of brain areas with regards to structural connectivity and to the slower frequency bands of functional connectivity. The opposite result was observed for higher-frequency (gamma) functional networks, with higher Gf individuals showing lower degree and higher segregation across the brain. We suggest that gamma oscillations in more intelligent individuals might support higher local processing in segregated subnetworks, while slower frequency bands would allow a more effective information transfer between brain subnetworks, and stronger information integration.

A novel method for estimating connectivity-based parcellation of the human brain from diffusion MRI: Application to an aging cohort

Connectivity‐based parcellation (CBP) methods are used to define homogenous and biologically meaningful parcels or nodes—the foundations of brain network fingerprinting—by grouping voxels with similar patterns of brain connectivity. However, we still lack a gold standard method and the use of CBPs to study the aging brain remains scarce. Our study proposes a novel CBP method from diffusion MRI data and shows its potential to produce a more accurate characterization of the longitudinal alterations in brain network topology occurring in aging. For this, we constructed whole‐brain connectivity maps from diffusion MRI data of two datasets: an aging cohort evaluated at two timepoints (mean interval time: 52.8 ± 7.24 months) and a normative adult cohort—MGH‐HCP. State‐of‐the‐art clustering techniques were used to identify the best performing technique. Furthermore, we developed a new metric (connectivity homogeneity fingerprint [CHF]) to evaluate the success of the final CBP in improving regional/global structural connectivity homogeneity. Our results show that our method successfully generates highly homogeneous parcels, as described by the significantly larger CHF score of the resulting parcellation, when compared to the original. Additionally, we demonstrated that the developed parcellation provides a robust anatomical framework to assess longitudinal changes in the aging brain. Our results reveal that aging is characterized by a reorganization of the brain's structural network involving the decrease of intra‐hemispheric, increase of inter‐hemispheric connectivity, and topological rearrangement. Overall, this study proposes a new methodology to perform accurate and robust evaluations of CBP of the human brain.

Genetic risk for bipolar disorder and schizophrenia predicts structure and function of the ventromedial prefrontal cortex

BACKGROUND

Bipolar disorder is highly heritable and polygenic. The polygenic risk for bipolar disorder overlaps with that of schizophrenia, and polygenic scores are normally distributed in the population. Bipolar disorder has been associated with structural brain abnormalities, but it is unknown how these are linked to genetic risk factors for psychotic disorders.

METHODS

We tested whether polygenic risk scores for bipolar disorder and schizophrenia predict structural brain alterations in 98 patients with bipolar disorder and 81 healthy controls. We derived brain cortical thickness, surface area and volume from structural MRI scans. In post-hoc analyses, we correlated polygenic risk with functional hub strength, derived from resting-state functional MRI and brain connectomics.

RESULTS

Higher polygenic risk scores for both bipolar disorder and schizophrenia were associated with a thinner ventromedial prefrontal cortex (vmPFC). We found these associations in the combined group, and separately in patients and drug-naive controls. Polygenic risk for bipolar disorder was correlated with the functional hub strength of the vmPFC within the default mode network.

LIMITATIONS

Polygenic risk is a cumulative measure of genomic burden. Detailed genetic mechanisms underlying brain alterations and their cognitive consequences still need to be determined.

CONCLUSION

Our multimodal neuroimaging study linked genomic burden and brain endophenotype by demonstrating an association between polygenic risk scores for bipolar disorder and schizophrenia and the structure and function of the vmPFC. Our findings suggest that genetic factors might confer risk for psychotic disorders by influencing the integrity of the vmPFC, a brain region involved in self-referential processes and emotional regulation. Our study may also provide an imaging-genetics vulnerability marker that can be used to help identify individuals at risk for developing bipolar disorder.

Reorganization of brain structural networks in aging: A longitudinal study

Normal aging is characterized by structural and functional changes in the brain contributing to cognitive decline. Structural connectivity (SC) describes the anatomical backbone linking distinct functional subunits of the brain and disruption of this communication is thought to be one of the potential contributors for the age-related deterioration observed in cognition. Several studies already explored brain network's reorganization during aging, but most focused on average connectivity of the whole-brain or in specific networks, such as the resting-state networks. Here, we aimed to characterize longitudinal changes of white matter (WM) structural brain networks, through the identification of sub-networks with significantly altered connectivity along time. Then, we tested associations between longitudinal changes in network connectivity and cognition. We also assessed longitudinal changes in topological properties of the networks. For this, older adults were evaluated at two timepoints, with a mean interval time of 52.8 months (SD = 7.24). WM structural networks were derived from diffusion magnetic resonance imaging, and cognitive status from neurocognitive testing. Our results show age-related changes in brain SC, characterized by both decreases and increases in connectivity weight. Interestingly, decreases occur in intra-hemispheric connections formed mainly by association fibers, while increases occur mostly in inter-hemispheric connections and involve association, commissural, and projection fibers, supporting the last-in-first-out hypothesis. Regarding topology, two hubs were lost, alongside with a decrease in connector-hub inter-modular connectivity, reflecting reduced integration. Simultaneously, there was an increase in the number of provincial hubs, suggesting increased segregation. Overall, these results confirm that aging triggers a reorganization of the brain structural network.

Preserving Right Pre-motor and Posterior Prefrontal Cortices Contribute to Maintaining Overall Basic Emotion

Basic emotions such as happiness, sadness, and anger are universal, regardless of the human species, and are governed by specific brain regions. A recent report revealed that mentalizing, which is the ability to estimate other individuals’ emotional states via facial expressions, can be preserved with the help of awake surgery. However, it is still questionable whether we can maintain the ability to understand others’ emotions by preserving the positive mapping sites of intraoperative assessment. Here, we demonstrated the cortical regions related to basic emotions via awake surgery for patients with frontal glioma and investigated the usefulness of functional mapping in preserving basic emotion. Of the 56 consecutive patients with right cerebral hemispheric glioma who underwent awake surgery at our hospital, intraoperative assessment of basic emotion could be successfully performed in 22 patients with frontal glioma and were included in our study. During surgery, positive responses were found in 18 points in 12 patients (54.5%). Of these, 15 points from 11 patients were found at the cortical level, mainly the premotor and posterior part of the prefrontal cortices. Then, we focused on cortical 15 positive mappings with 40 stimulations and investigated the types of emotions that showed errors by every stimulation. There was no specific rule for the region-emotional type, which was beyond our expectations. In the postoperative acute phase, the test score of basic emotion declined in nine patients, and of these, it decreased under the cut-off value (Z-score ≤ −1.65) in three patients. Although the total score declined significantly just after surgery (p = 0.022), it recovered within 3 months postoperatively. Our study revealed that through direct electrical stimulation (DES), the premotor and posterior parts of the prefrontal cortices are related to various kinds of basic emotion, but not a single one. When the region with a positive mapping site is preserved during operation, basic emotion function might be maintained although it declines transiently after surgery.

Gray matter abnormalities follow non-random patterns of co-alteration in autism: Meta-connectomic evidence

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by atypical brain anatomy and connectivity. Graph-theoretical methods have mainly been applied to detect altered patterns of white matter tracts and functional brain activation in individuals with ASD. The network topology of gray matter (GM) abnormalities in ASD remains relatively unexplored.

METHODS

An innovative meta-connectomic analysis on voxel-based morphometry data (45 experiments, 1,786 subjects with ASD) was performed in order to investigate whether GM variations can develop in a distinct pattern of co-alteration across the brain. This pattern was then compared with normative profiles of structural and genetic co-expression maps. Graph measures of centrality and clustering were also applied to identify brain areas with the highest topological hierarchy and core sub-graph components within the co-alteration network observed in ASD.

RESULTS

Individuals with ASD exhibit a distinctive and topologically defined pattern of GM co-alteration that moderately follows the structural connectivity constraints. This was not observed with respect to the pattern of genetic co-expression. Hub regions of the co-alteration network were mainly left-lateralized, encompassing the precuneus, ventral anterior cingulate, and middle occipital gyrus. Regions of the default mode network appear to be central in the topology of co-alterations.

CONCLUSION

These findings shed new light on the pathobiology of ASD, suggesting a network-level dysfunction among spatially distributed GM regions. At the same time, this study supports pathoconnectomics as an insightful approach to better understand neuropsychiatric disorders.

Pediatric bipolar disorder: Executive, linguistic, mnemonic, and cognitive efficiency mapping

Neuropsychological assessment can enrich our understanding of Pediatric Bipolar Disorder (PB). This study aimed to: (1) analyze the occurrence of neuropsychological frequency of deficits and difficulties in children with PB; (2) verify whether there is a performance difference between PB type I (PB-I) and PB type II (PB-II)/unspecified, and between PB with and without ADHD; and (3) verify the cognitive efficiency differences within the PB group and control groups, and among clinical subgroups. Participants in the study were 16 children diagnosed with PB and 40 children with typical development (6-12 years old). The results indicated a high frequency of deficits/difficulties in verbal fluency, cognitive efficiency in performing basic abilities, inhibitory control, cognitive flexibility, and working memory, with emphasis on verbal and executive losses. There were indications that type PB-I and comorbidity with ADHD negatively impact a child's neuropsychological development. The clinical group showed more cognitive efficiency losses compared with the control group, and greater losses were observed in PB-I and in PB with ADHD. The role of neuropsychological evaluation in multidomain and nonlinear statistical analysis is critical to gaining an understanding of the clinical and cognitive heterogeneity of PB.

Structural and functional alterations in untreated patients with major depressive disorder and bipolar disorder experiencing first depressive episode: A magnetic resonance imaging study combined with follow-up

BACKGROUND

Magnetic resonance imaging (MRI) could assist in identifying objective biomarkers and follow-up study could effectively improve subjective diagnostic accuracy. By combining MRI with follow-up, this study aims to determine the shared and distinct alterations between major depressive disorder (MDD) and bipolar disorder (BD).

METHODS

Untreated patients with MDD experiencing the first episode were subjected to MRI and subsequent follow-up. Fifteen patients with mania or hypomania were regrouped into BD group. Twenty patients were still grouped as MDD after an average of 37.95 months follow-up. Thirty healthy controls (HCs) were recruited to match the patients. Gray matter volume (GMV) and amygdala-seed functional connectivity (FC) in the whole brain were detected and compared among the three groups.

RESULTS

GMV analysis revealed that the MDD and BD groups presented reduced GMV predominantly in the parietal, occipital, and frontal regions in the bilateral cerebrum compared with the HCs. The BD group had reduced GMV predominantly in the parietal, temporal, insular regions and the Rolandic operculum in the right-side cerebrum compared with MDD and HC groups. FC analysis revealed that the MDD and BD patients displayed increased FC values mainly in the bilateral parietal, and left occipital regions. Only the BD group displayed increased FC values in the temporal, occipital, parietal and limbic regions in the right-side cerebrum relative to HCs.

LIMITATIONS

The main limitation is the relatively small sample size.

CONCLUSIONS

Alterations in the cortical regions and cortico-limbic neural system may provide the scientific basis for differential diagnosis in affective disorders.

Altered Functional Hubs and Connectivity in Type 2 Diabetes Mellitus Without Mild Cognitive Impairment

Background: Type 2 diabetes mellitus (T2DM)-related cognitive decline is associated with neuroimaging changes. However, only a few studies have focused on early functional alteration in T2DM prior to mild cognitive impairment (MCI). This study aimed to investigate the early changes of global connectivity patterns in T2DM by using a resting-state functional magnetic resonance imaging (rs-fMRI) technique. Methods: Thirty-four T2DM subjects and 38 age-, sex-, and education-matched healthy controls (HCs) underwent rs-fMRI in a 3T MRI scanner. Degree centrality (DC) was used to identify the functional hubs of the whole brain in T2DM without MCI. Then the functional connectivity (FC) between hubs and the rest of the brain was assessed by using the hub-based approach. Results: Compared with HCs, T2DM subjects showed increased DC in the right cerebellum lobules III-V. Hub-based FC analysis found that the right cerebellum lobules III-V of T2DM subjects had increased FC with the right cerebellum crus II and lobule VI, the right temporal inferior/middle gyrus, and the right hippocampus. Conclusions: Increased DC in the right cerebellum regions III-V, as well as increased FC within cerebellar regions and ipsilateral cerebrocerebellar regions, may indicate an important pathophysiological mechanism for compensation in T2DM without MCI.