Structural brain network analysis in families multiply affected with bipolar I disorder

Reconfiguration of brain network dynamics in bipolar disorder: a hidden Markov model approach

Bipolar disorder (BD) is a neuropsychiatric disorder characterized by severe disturbance and fluctuation in mood. Dynamic functional connectivity (dFC) has the potential to more accurately capture the evolving processes of emotion and cognition in BD. Nevertheless, prior investigations of dFC typically centered on larger time scales, limiting the sensitivity to transient changes. This study employed hidden Markov model (HMM) analysis to delve deeper into the moment-to-moment temporal patterns of brain activity in BD. We utilized resting-state functional magnetic resonance imaging (rs-fMRI) data from 43 BD patients and 51 controls to evaluate the altered dynamic spatiotemporal architecture of the whole-brain network and identify unique activation patterns in BD. Additionally, we investigated the relationship between altered brain dynamics and structural disruption through the ridge regression (RR) algorithm. The results demonstrated that BD spent less time in a hyperconnected state with higher network efficiency and lower segregation. Conversely, BD spent more time in anticorrelated states featuring overall negative correlations, particularly among pairs of default mode network (DMN) and sensorimotor network (SMN), DMN and insular-opercular ventral attention networks (ION), subcortical network (SCN) and SMN, as well as SCN and ION. Interestingly, the hypoactivation of the cognitive control network in BD may be associated with the structural disruption primarily situated in the frontal and parietal lobes. This study investigated the dynamic mechanisms of brain network dysfunction in BD and offered fresh perspectives for exploring the physiological foundation of altered brain dynamics.

Age Trajectories of the Structural Connectome in Child and Adolescent Offspring of Individuals With Bipolar Disorder or Schizophrenia

Background

Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at elevated risk of developing psychiatric illness owing to both genetic predisposition and increased burden of environmental stress. Emerging evidence indicates a disruption of brain network connectivity in young offspring of patients with bipolar disorder and schizophrenia, but the age trajectories of these brain networks in this high-familial-risk population remain to be elucidated.

Methods

A total of 271 T1-weighted and diffusion-weighted scans were obtained from 174 offspring of at least 1 parent diagnosed with bipolar disorder (n = 74) or schizophrenia (n = 51) and offspring of parents without severe mental illness (n = 49). The age range was 8 to 23 years; 97 offspring underwent 2 scans. Anatomical brain networks were reconstructed into structural connectivity matrices. Network analysis was performed to investigate anatomical brain connectivity.

Results

Offspring of parents with schizophrenia had differential trajectories of connectivity strength and clustering compared with offspring of parents with bipolar disorder and parents without severe mental illness, of global efficiency compared with offspring of parents without severe mental illness, and of local connectivity compared with offspring of parents with bipolar disorder.

Conclusions

The findings of this study suggest that familial high risk of schizophrenia is related to deviations in age trajectories of global structural connectome properties and local connectivity strength.

Diagnostic value of structural, functional and effective connectivity in bipolar disorder

INTRODUCTION

The aim of this systematic review is to assess the functional magnetic resonance imaging (fMRI) studies of bipolar disorder (BD) patients that characterize differences in terms of structural, functional, and effective connectivity between the patients with BD, patients with other psychiatric disorders and healthy controls as possible biomarkers for diagnosing the disorder using neuroimaging.

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), guidelines a systematic search for recent (since 2015) original studies on connectivity in bipolar disorder was conducted in PUBMED and SCOPUS.

RESULTS

A total of 60 studies were included in this systematic review: 20 of the structural connectivity, 33 of the functional connectivity, and only 7 of the studies focused on effective connectivity complied with the inclusion and exclusion criteria.

DISCUSSION

Despite the great heterogeneity in the findings, there are several trends that emerge. In structural connectivity studies, the main abnormalities in bipolar disorder patients were in the frontal gyrus, anterior, as well as posterior cingulate cortex and differences in emotion and reward-related networks. Cerebellum (vermis) to cerebrum functional connectivity was found to be the most common finding in BD. Moreover, prefrontal cortex and amygdala connectivity as part of the rich-club hubs were often reported to be disrupted. The most common findings based on effective connectivity were alterations in salience network, default mode network and executive control network. Although more studies with larger sample sizes are needed to ascertain altered brain connectivity as diagnostic biomarker, there is a perspective that the method could be used as a single marker of diagnosis in the future, and the process of adoption could be accelerated by using approaches such as semiunsupervised machine learning.

Changes in the structural brain connectome over the course of a nonrandomized clinical trial for acute mania

Disrupted topological organization of brain functional networks has been widely reported in bipolar disorder. However, the potential clinical implications of structural connectome abnormalities have not been systematically investigated. The present study included 109 unmedicated subjects with acute mania who were assigned to 8 weeks of treatment with quetiapine or lithium and 60 healthy controls. High resolution 3D-T1 weighted magnetic resonance images (MRI) were collected from both groups at baseline, week 1 and week 8. Brain networks were constructed based on the similarity of morphological features across brain regions and analyzed using graph theory approaches. At baseline, individuals with bipolar disorder illness showed significantly lower clustering coefficient (Cp) (p = 0.012) and normalized characteristic path length (λ) (p = 0.004) compared to healthy individuals, as well as differences in nodal centralities across multiple brain regions. No baseline or post-treatment differences were identified between drug treatment conditions, so change after treatment were considered in the combined treatment groups. Relative to healthy individuals, differences in Cp, λ and cingulate gyrus nodal centrality were significantly reduced with treatment; changes in these parameters correlated with changes in Young Mania Rating Scale scores. Baseline structural connectome matrices significantly differentiated responder and non-responder groups at 8 weeks with 74% accuracy. Global and nodal network alterations evident at baseline were normalized with treatment and these changes associated with symptomatic improvement. Further, baseline structural connectome matrices predicted treatment response. These findings suggest that structural connectome abnormalities are clinically significant and may be useful for predicting clinical outcome of treatment and tracking drug effects on brain anatomy in bipolar disorder.

CLINICAL TRIALS REGISTRATION

Name: Functional and Neurochemical Brain Changes in First-episode Bipolar Mania Following Successful Treatment with Lithium or Quetiapine. URL: https://clinicaltrials.gov/ .

REGISTRATION NUMBER

NCT00609193. Name: Neurofunctional and Neurochemical Markers of Treatment Response in Bipolar Disorder. URL: https://clinicaltrials.gov/ .

REGISTRATION NUMBER

NCT00608075.

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.

Longitudinal Changes in Structural Connectivity in Young People at High Genetic Risk for Bipolar Disorder

OBJECTIVE

Recent studies of patients with bipolar disorder or at high genetic risk reveal structural dysconnections among key brain networks supporting cognitive and affective processes. Understanding the longitudinal trajectories of these networks across the peak age range of bipolar disorder onset could inform mechanisms of illness onset or resilience.

METHODS

Longitudinal diffusion-weighted MRI and phenotypic data were acquired at baseline and after 2 years in 183 individuals ages 12-30 years in two cohorts: 97 unaffected individuals with a first-degree relative with bipolar disorder (the high-risk group) and 86 individuals with no family history of mental illness (the control group). Whole-brain structural networks were derived using tractography, and longitudinal changes in these networks were studied using network-based statistics and mixed linear models.

RESULTS

Both groups showed widespread longitudinal changes, comprising both increases and decreases in structural connectivity, consistent with a shared neurodevelopmental process. On top of these shared changes, high-risk participants showed weakening of connectivity in a network encompassing the left inferior and middle frontal areas, left striatal and thalamic structures, the left fusiform, and right parietal and occipital regions. Connections among these regions strengthened in the control group, whereas they weakened in the high-risk group, shifting toward a cohort with established bipolar disorder. There was marginal evidence for even greater network weakening in those who had their first manic or hypomanic episode before follow-up.

CONCLUSIONS

Neurodevelopment from adolescence into early adulthood is associated with a substantial reorganization of structural brain networks. Differences in these maturational processes occur in a multisystem network in individuals at high genetic risk of bipolar disorder. This may represent a novel candidate to understand resilience and predict conversion to bipolar disorder.

Diffusion kurtosis imaging of white matter in bipolar disorder

White matter pathology likely contributes to the pathogenesis of bipolar disorder (BD). Most studies of white matter in BD have used diffusion tensor imaging (DTI), but the advent of more advanced multi-shell diffusion MRI imaging offers the possibility to investigate other aspects of white matter microstructure. Diffusion kurtosis imaging (DKI) extends the DTI model and provides additional measures related to diffusion restriction. Here, we investigated white matter in BD by applying whole-brain voxel-based analysis (VBA) and a network-based connectivity approach using constrained spherical deconvolution tractography to assess differences in DKI and DTI metrics between BD (n = 25) and controls (n = 24). The VBA showed lower mean kurtosis in the corona radiata and posterior association fibers in BD. Regional differences in connectivity were indicated by lower mean kurtosis and kurtosis anisotropy in streamlines traversing the temporal and occipital lobes, and lower mean axial kurtosis in the right cerebellar, thalamo-subcortical pathways in BD. Significant differences were not seen in DTI metrics following FDR-correction. The DKI findings indicate altered connectivity across cortical, subcortical and cerebellar areas in BD. DKI is sensitive to different microstructural properties and is a useful complementary technique to DTI to more fully investigate white matter in BD.

Aberrant Subnetwork and Hub Dysconnectivity in Adult Bipolar Disorder: A Multicenter Graph Theory Analysis

Neuroimaging evidence implicates structural network-level abnormalities in bipolar disorder (BD); however, there remain conflicting results in the current literature hampered by sample size limitations and clinical heterogeneity. Here, we set out to perform a multisite graph theory analysis to assess the extent of neuroanatomical dysconnectivity in a large representative study of individuals with BD. This cross-sectional multicenter international study assessed structural and diffusion-weighted magnetic resonance imaging data obtained from 109 subjects with BD type 1 and 103 psychiatrically healthy volunteers. Whole-brain metrics, permutation-based statistics, and connectivity of highly connected nodes were used to compare network-level connectivity patterns in individuals with BD compared with controls. The BD group displayed longer characteristic path length, a weakly connected left frontotemporal network, and increased rich-club dysconnectivity compared with healthy controls. Our multisite findings implicate emotion and reward networks dysconnectivity in bipolar illness and may guide larger scale global efforts in understanding how human brain architecture impacts mood regulation in BD.

Structural brain network differences in bipolar disorder using with similarity-based approach

Objective: Previous studies have shown differences in the regional brain structure and function between patients with bipolar disorder (BD) and healthy subjects, but little is known about the structural connectivity between BD patients and healthy subjects. In this study, we evaluated the disease-related changes in regional structural connectivity derived from gray matter magnetic resonance imaging (MRI) scans. Methods: The subjects were 73 patients with BD and 80 healthy volunteers who underwent 3-Tesla MRI. Network metrics, such as the small world properties, were computed. We also performed rendering of the network metric images such as the degree, betweenness centrality, and clustering coefficient, on individual brain image. Then, we estimated the differences between them, and evaluate the relationships between the clinical symptoms and the network metrics in the patients with BD. Results: BD patients showed a lower clustering coefficient in the right parietal region and left occipital region, compared with healthy subjects. A weak negative correlation between Young mania rating scale and clustering coefficient was found in left anterior cingulate cortex. Conclusions: We found differences in gray matter structural connectivity between BD patients and healthy subjects by a similarity-based approach. These points may provide objective biological information as an adjunct to the clinical diagnosis of BD.

Structural dysconnectivity in offspring of individuals with bipolar disorder: The effect of co-existing clinical-high-risk for bipolar disorder

BACKGROUND

Bipolar disorder (BD) might be associated in disturbances in brain networks. However, little is known about the abnormalities in structural brain connectivity which might be related to vulnerability to BD and predictive of the emergence of manic symptoms. No previous study has investigated the effect of subthreshold syndromes on structural dysconnectivity in offspring of parents with BD (BDoff).

METHODS

We investigated diffusion weighted images of 70 BDoff and 48 healthy controls (HC). Nineteen of the 70 BDoff had presented with subthreshold syndromes indicating a clinical high-risk (BDoff-CHR) and other 51 BDoff had no such history (BDoff-non-CHR). Global and regional network properties, rich club organization and inter-regional connectivity in BDoff and healthy controls were investigated using graph analytical methods and network-based-statistics (NBS).

RESULTS

Global properties of WM networks appeared to be intact in BDoff-CHR and BDoff-non-CHR. However, decreased regional connectivity in right occipito-parietal areas and cerebellum was a common feature of both BDoff groups. Importantly, decreased interregional connectivity between nodes in right and left prefrontal regions, nodes in right prefrontal lobe and right temporal lobe and nodes in left occipital area and left cerebellum were evident in BDoff-CHR but not BDoff-non-CHR.

LIMITATIONS

The cross-sectional nature of the study was the main consideration.

CONCLUSION

Decreased regional connectivity in right posterior brain regions might be related to vulnerability to BD. On the other hand, interregional dysconnectivity in anterior frontal and limbic regions and left posterior brain regions might be evident in individuals genetically at risk for developing BD who had experienced subthreshold mood symptoms.

Multimodal MRI of Conduction Tracts and Anatomy of the Cerebral Gray Matter in Familial Risk of Affective Disorders and Schizophrenia

The present study analyzed diffusion characteristics of white matter tracts and grey matter anatomy in 48 mentally healthy participants, including first-degree relatives of patients with schizophrenia (N=13) and affective spectrum disorders (N=13). The subgroup with familial risk of schizophrenia displayed abnormalities in the structural connectivity and increased cortical thickness in the superior frontal gyrus. No differences in the analyzed characteristics were revealed in the subgroup with familial risk for affective disorders. The results are discussed within the framework of the concepts of endophenotypes and processes reflecting compensatory and protective mechanisms.

Functional brain networks in the schizophrenia spectrum and bipolar disorder with psychosis

Psychotic experiences have been proposed to lie on a spectrum, ranging from subclinical experiences to treatment-resistant schizophrenia. We aimed to characterize functional connectivity and brain network characteristics in relation to the schizophrenia spectrum and bipolar disorder with psychosis to disentangle neural correlates to psychosis. Additionally, we studied antipsychotic medication and lithium effects on network characteristics. We analyzed functional connectivity strength and network topology in 487 resting-state functional MRI scans of individuals with schizophrenia spectrum disorder (SCZ), bipolar disorder with a history of psychotic experiences (BD), treatment-naïve subclinical psychosis (SCP), and healthy controls (HC). Since differences in connectivity strength may confound group comparisons of brain network topology, we analyzed characteristics of the minimum spanning tree (MST), a relatively unbiased backbone of the network. SCZ and SCP subjects had a lower connectivity strength than BD and HC individuals but showed no differences in network topology. In contrast, BD patients showed a less integrated network topology but no disturbances in connectivity strength. No differences in outcome measures were found between SCP and SCZ, or between BD patients that used antipsychotic medication or lithium and those that did not. We conclude that functional networks in patients prone to psychosis have different signatures for chronic SCZ patients and SCP compared to euthymic BD patients, with a limited role for medication. Connectivity strength effects may have confounded previous studies, as no functional network alterations were found in SCZ after strict correction for connectivity strength.

Disrupted Rich Club Organization of Hemispheric White Matter Networks in Bipolar Disorder

Neuroimaging studies suggest disrupted connections of the brain white matter (WM) network in bipolar disorder (BD). A group of highly interconnected high-density structures, termed the 'rich club,' represents an important network for brain functioning. Recent works have revealed abnormal rich club organization in brain networks in BD. However, little is known regarding changes in the rich club organization of the hemispheric WM network in BD. Forty-nine BD patients and fifty-five age- and sex-matched normal controls (NCs) underwent diffusion tensor imaging (DTI). Graph theory approaches were applied to quantify group-specific rich club organization and nodal degree of hemispheric WM networks. We demonstrated that rich club organization of hemispheric WM networks in BD was disrupted, with disrupted feeder and local connections among hub and peripheral regions located in the default mode network (DMN) and the control execution network (CEN). In addition, BD patients showed abnormal asymmetry in the feeder and local connections, involving the hub and peripheral regions associated with emotion regulation and visuospatial functions. Moreover, the clinical symptoms of BD showed a significant correlation with the aberrant asymmetry in the regional degree of peripheral regions. These findings reveal that BD is closely associated with disrupted feeder and local connections but no alteration in rich-club connections in the rich club organization of hemispheric WM networks and provide novel insight into the changes of brain functions in BD.

Amygdala subnuclei volume in bipolar spectrum disorders: Insights from diffusion-based subsegmentation and a high-risk design

Amygdala abnormalities are widely documented in bipolar spectrum disorders (BSD). Amygdala volume typically is measured after BSD onset; thus, it is not known whether amygdala abnormalities predict BSD risk or relate to the disorder. Additionally, past literature often treated the amygdala as a homogeneous structure, and did not consider its distinct subnuclei and their differential connectivity to other brain regions. To address these issues, we used a behavioral high‐risk design and diffusion‐based subsegmentation to examine amygdala subnuclei among medication‐free individuals with, and at risk for, BSD. The behavioral high‐risk design (N = 114) included low‐risk (N = 37), high‐risk (N = 47), and BSD groups (N = 30). Diffusion‐based subsegmentation of the amygdala was conducted to determine whether amygdala volume differences related to particular subnuclei. Individuals with a BSD diagnosis showed greater whole, bilateral amygdala volume compared to Low‐Risk individuals. Examination of subnuclei revealed that the BSD group had larger volumes compared to the High‐Risk group in both the left medial and central subnuclei, and showed larger volume in the right lateral subnucleus compared to the Low‐Risk group. Within the BSD group, specific amygdala subnuclei volumes related to time since first episode onset and number of lifetime episodes. Taken together, whole amygdala volume analyses replicated past findings of enlargement in BSD, but did not detect abnormalities in the high‐risk group. Examination of subnuclei volumes detected differences in volume between the high‐risk and BSD groups that were missed in the whole amygdala volume. Results have implications for understanding amygdala abnormalities among individuals with, and at risk for, a BSD.

Bipolar Disorder and Gender Are Associated with Frontolimbic and Basal Ganglia Dysconnectivity: A Study of Topological Variance Using Network Analysis

Well-established structural abnormalities, mostly involving the limbic system, have been associated with disorders of emotion regulation. Understanding the arrangement and connections of these regions with other functionally specialized cortico-subcortical subnetworks is key to understanding how the human brain's architecture underpins abnormalities of mood and emotion. We investigated topological patterns in bipolar disorder (BD) with the anatomically improved precision conferred by combining subject-specific parcellation/segmentation with nontensor-based tractograms derived using a high-angular resolution diffusion-weighted approach. Connectivity matrices were constructed using 34 cortical and 9 subcortical bilateral nodes (Desikan-Killiany), and edges that were weighted by fractional anisotropy and streamline count derived from deterministic tractography using constrained spherical deconvolution. Whole-brain and rich-club connectivity alongside a permutation-based statistical approach was used to investigate topological variance in predominantly euthymic BD relative to healthy volunteers. BP patients (n = 40) demonstrated impairments across whole-brain topological arrangements (density, degree, and efficiency), and a dysconnected subnetwork involving limbic and basal ganglia relative to controls (n = 45). Increased rich-club connectivity was most evident in females with BD, with frontolimbic and parieto-occipital nodes not members of BD rich-club. Increased centrality in females relative to males was driven by basal ganglia and fronto-temporo-limbic nodes. Our subject-specific cortico-subcortical nontensor-based connectome map presents a neuroanatomical model of BD dysconnectivity that differentially involves communication within and between emotion-regulatory and reward-related subsystems. Moreover, the female brain positions more dependence on nodes belonging to these two differently specialized subsystems for communication relative to males, which may confer increased susceptibility to processes dependent on integration of emotion and reward-related information.

Structural connectivity in schizophrenia and bipolar disorder: Effects of chronicity and antipsychotic treatment

Previous studies based on graph theory parameters applied to diffusion tensor imaging support an alteration of the global properties of structural connectivity network in schizophrenia. However, the specificity of this alteration and its possible relation with chronicity and treatment have received small attention. We have assessed small-world (SW) and connectivity strength indexes of the structural network built using fractional anisotropy values of the white matter tracts connecting 84 cortical and subcortical regions in 25 chronic and 18 first episode (FE) schizophrenia and 24 bipolar patients and 28 healthy controls. Chronic schizophrenia and bipolar patients showed significantly smaller SW and connectivity strength indexes in comparison with controls and FE patients. SW reduction was driven by increased averaged path-length (PL) values. Illness duration but not treatment doses were negatively associated with connectivity strength, SW and PL in patients. Bipolar patients exposed to antipsychotics did not differ in SW or connectivity strength from bipolar patients without such an exposure. Executive functions and social cognition were related to SW index in the schizophrenia group. Our results support a role for chronicity but not treatment in structural network alterations in major psychoses, which may not differ between schizophrenia and bipolar disorder, and may hamper cognition.

Aberrant brain structural-functional connectivity coupling in euthymic bipolar disorder

Aberrant structural (diffusion tensor imaging [DTI]) and resting-state functional magnetic resonance imagining connectivity are core features of bipolar disorder. However, few studies have explored the integrity agreement between structural and functional connectivity (SC-FC) in bipolar disorder. We examine SC connectivity coupling index whether could potentially provide additional clinical predictive value for bipolar disorder spectrum disorders besides the intramodality network measures. By examining the structural (DTI) and resting-state functional network properties, as well as their coupling index, among 57 euthymic bipolar disorder patients (age 13-28 years, 18 females) and 42 age- and gender-matched healthy controls (age 13-28 years, 16 females), we found that compared to controls, bipolar disorder patients showed increased structural rich-club connectivity as well as decreased functional modularity. Importantly, the coupling strength between structural and functional connectome was decreased in patients compared to controls, which emerged as the most powerful feature discriminating the two groups. Our findings suggest that structural-functional coupling strength could serve as a valuable biological trait-like feature for bipolar disorder over and above the intramodality network measures. Such measure can have important clinical implications for early identification of bipolar disorder individuals, and inform strategies for prevention of bipolar disorder onset and relapse.

Connectomics of bipolar disorder: a critical review, and evidence for dynamic instabilities within interoceptive networks

The notion that specific cognitive and emotional processes arise from functionally distinct brain regions has lately shifted toward a connectivity-based approach that emphasizes the role of network-mediated integration across regions. The clinical neurosciences have likewise shifted from a predominantly lesion-based approach to a connectomic paradigm-framing disorders as diverse as stroke, schizophrenia (SCZ), and dementia as "dysconnection syndromes". Here we position bipolar disorder (BD) within this paradigm. We first summarise the disruptions in structural, functional and effective connectivity that have been documented in BD. Not surprisingly, these disturbances show a preferential impact on circuits that support emotional processes, cognitive control and executive functions. Those at high risk (HR) for BD also show patterns of connectivity that differ from both matched control populations and those with BD, and which may thus speak to neurobiological markers of both risk and resilience. We highlight research fields that aim to link brain network disturbances to the phenotype of BD, including the study of large-scale brain dynamics, the principles of network stability and control, and the study of interoception (the perception of physiological states). Together, these findings suggest that the affective dysregulation of BD arises from dynamic instabilities in interoceptive circuits which subsequently impact on fear circuitry and cognitive control systems. We describe the resulting disturbance as a "psychosis of interoception".

Cortico-limbic connectivity as a possible biomarker for bipolar disorder: where are we now?

INTRODUCTION

The fronto-limbic network has been suggested as a key circuitry in the pathophysiology and maintenance of bipolar disorder. In the past decade, a disrupted connectivity within prefrontal-limbic structures was identified as a promising candidate biomarker for the disorder. Areas Covered: In this review, the authors examine current literature in terms of the structural, functional and effective connectivity in bipolar disorder, integrating recent findings of imaging genetics and machine learning. This paper profiles the current knowledge and identifies future perspectives to provide reliable and usable neuroimaging biomarkers for bipolar psychopathology in clinical practice. Expert Opinion: The replication and the translation of acquired knowledge into useful and usable tools represents one of the current greatest challenges in biomarker research applied to psychiatry.

The Abnormality of Topological Asymmetry in Hemispheric Brain Anatomical Networks in Bipolar Disorder

Convergent evidences have demonstrated a variety of regional abnormalities of asymmetry in bipolar disorder (BD). However, little is known about the alterations in hemispheric topological asymmetries. In this study, we used diffusion tensor imaging to construct the hemispheric brain anatomical network of 49 patients with BD and 61 matched normal controls. Graph theory was then applied to quantify topological properties of the hemispheric networks. Although small-world properties were preserved in the hemispheric networks of BD, the degrees of the asymmetry in global efficiency, characteristic path length, and small-world property were significantly decreased. More changes in topological properties of the right hemisphere than those of left hemisphere were found in patients compared with normal controls. Consistent with such changes, the nodal efficiency in patients with BD also showed less rightward asymmetry mainly in the frontal, occipital, parietal, and temporal lobes. In contrast to leftward asymmetry, significant rightward asymmetry was found in supplementary motor area of BD, and attributed to more deficits in nodal efficiency of the left hemisphere. Finally, these asymmetry score of nodal efficiency in the inferior parietal lobule and rolandic operculum were significantly associated with symptom severity of BD. Our results suggested that abnormal hemispheric asymmetries in brain anatomical networks were associated with aberrant neurodevelopment, and providing insights into the potential neural biomarkers of BD by measuring the topological asymmetry in hemispheric brain anatomical networks.

Structural dysconnectivity of key cognitive and emotional hubs in young people at high genetic risk for bipolar disorder

Emerging evidence suggests that psychiatric disorders are associated with disturbances in structural brain networks. Little is known, however, about brain networks in those at high risk (HR) of bipolar disorder (BD), with such disturbances carrying substantial predictive and etiological value. Whole-brain tractography was performed on diffusion-weighted images acquired from 84 unaffected HR individuals with at least one first-degree relative with BD, 38 young patients with BD and 96 matched controls (CNs) with no family history of mental illness. We studied structural connectivity differences between these groups, with a focus on highly connected hubs and networks involving emotional centres. HR participants showed lower structural connectivity in two lateralised sub-networks centred on bilateral inferior frontal gyri and left insular cortex, as well as increased connectivity in a right lateralised limbic sub-network compared with CN subjects. BD was associated with weaker connectivity in a small right-sided sub-network involving connections between fronto-temporal and temporal areas. Although these sub-networks preferentially involved structural hubs, the integrity of the highly connected structural backbone was preserved in both groups. Weaker structural brain networks involving key emotional centres occur in young people at genetic risk of BD and those with established BD. In contrast to other psychiatric disorders such as schizophrenia, the structural core of the brain remains intact, despite the local involvement of network hubs. These results add to our understanding of the neurobiological correlates of BD and provide predictions for outcomes in young people at high genetic risk for BD.

Affected Anatomical Rich Club and Structural-Functional Coupling in Young Offspring of Schizophrenia and Bipolar Disorder Patients

BACKGROUND

Emerging evidence suggests disruptions in the wiring organization of the brain's network in schizophrenia (SZ) and bipolar disorder (BD). As the importance of genetic predisposition has been firmly established in these illnesses, children (offspring) of patients constitute an at-risk population. This study examines connectome organization in children at familial high risk for psychosis.

METHODS

Diffusion-weighted magnetic resonance imaging scans were collected from 127 nonpsychotic offspring 8 to 18 years of age (average age = 13.5 years) of a parent diagnosed with SZ (SZ offspring; n = 28) or BD (BD offspring; N = 60) and community control subjects (n = 39). Resting-state functional magnetic resonance imaging scans were available for 82 subjects. Anatomical and functional brain networks were reconstructed and examined using graph theoretical analysis.

RESULTS

SZ offspring were found to show connectivity deficits of the brain's central rich club (RC) system relative to both control subjects and BD offspring. The disruption in anatomical RC connectivity in SZ offspring was associated with increased modularity of the functional connectome. In addition, increased coupling between structural and functional connectivity of long-distance connections was observed in both SZ offspring and BD offspring.

CONCLUSIONS

This study shows lower levels of anatomical RC connectivity in nonpsychotic young offspring of SZ patients. This finding suggests that the brain's anatomical RC system is affected in at-risk youths, reflecting a connectome signature of familial risk for psychotic illness. Moreover, finding no RC deficits in offspring of BD patients suggest a differential effect of genetic predisposition for SZ versus BD on the developmental formation of the connectome.

Anatomical integration and rich-club connectivity in euthymic bipolar disorder

BACKGROUND

Although repeatedly associated with white matter microstructural alterations, bipolar disorder (BD) has been relatively unexplored using complex network analysis. This method combines structural and diffusion magnetic resonance imaging (MRI) to model the brain as a network and evaluate its topological properties. A group of highly interconnected high-density structures, termed the 'rich-club', represents an important network for integration of brain functioning. This study aimed to assess structural and rich-club connectivity properties in BD through graph theory analyses.

METHOD

We obtained structural and diffusion MRI scans from 42 euthymic patients with BD type I and 43 age- and gender-matched healthy volunteers. Weighted fractional anisotropy connections mapped between cortical and subcortical structures defined the neuroanatomical networks. Next, we examined between-group differences in features of graph properties and sub-networks.

RESULTS

Patients exhibited significantly reduced clustering coefficient and global efficiency, compared with controls globally and regionally in frontal and occipital regions. Additionally, patients displayed weaker sub-network connectivity in distributed regions. Rich-club analysis revealed subtly reduced density in patients, which did not withstand multiple comparison correction. However, hub identification in most participants indicated differentially affected rich-club membership in the BD group, with two hubs absent when compared with controls, namely the superior frontal gyrus and thalamus.

CONCLUSIONS

This graph theory analysis presents a thorough investigation of topological features of connectivity in euthymic BD. Abnormalities of global and local measures and network components provide further neuroanatomically specific evidence for distributed dysconnectivity as a trait feature of BD.

Anatomical dysconnectivity in bipolar disorder compared with schizophrenia: A selective review of structural network analyses using diffusion MRI

BACKGROUND

The dysconnectivity hypothesis suggests that psychotic illnesses arise not from regionally specific focal pathophysiology, but rather from impaired neuroanatomical integration across networks of brain regions. Decreased white matter organization has been hypothesized to be a feature of psychotic illnesses in general, which is supported by meta-analyses of DTI studies in bipolar disorder and schizophrenia. Although many diffusion MRI studies investigate bipolar disorder and schizophrenia alone, relatively few studies directly compare structural features in these psychotic illnesses. Recently, the application of graph theory analyses to DTI data has supported the dysconnectivity hypothesis in bipolar disorder and schizophrenia, employing topological properties to assess neuroanatomical dysconnectivity.

METHODS

This selective review evaluates white matter alterations using Diffusion Tensor Imaging (DTI) in bipolar disorder and schizophrenia, with a focus upon direct comparison DTI studies in both psychotic illnesses. We then expand in more detail on the development of network analyses and the application of these techniques in bipolar disorder and schizophrenia.

RESULTS

Converging evidence indicates that frontal connectivity alterations are common to both disorders, with prominent fronto-temporal deficits identified in schizophrenia and inter-hemispheric and limbic alterations reported in bipolar disorder.

LIMITATIONS

In bipolar disorder, most connectome reports use cortical maps alone, which given the importance of the limbic system in emotional regulation may limit the scope of network approaches in mood disorders.

CONCLUSIONS

Further direct connectivity comparisons between these psychotic illnesses may assist in unravelling the neuroanatomical deviations underpinning the overlapping features of psychosis and cognitive impairment, and the more diagnostically distinctive features of affective disturbance in bipolar disorder and deficit syndrome in schizophrenia.