ABSTRACT
INTRODUCTION: Youth with a family history of bipolar disorder (At-Risk) have a higher risk of developing psychiatric disorders and experiencing environmental stressors than youth without such family history (Control). We studied the differential associations of familial and environmental factors on developing psychiatric diagnoses and symptoms, in At-Risk and Control youth. METHODS: At-Risk and Control youth (N = 466, ages 9-22) were systematically assessed for severity of symptoms, psychiatric diagnoses, and self-reported measures of stress and social support. We tested the association of family history and measures of stress or support with symptom severity and diagnoses. RESULTS: At-Risk youth had higher symptom severity scores and were more frequently diagnosed with psychiatric disorders (all p values < 0.001). When predicting mood symptom severity, family history had an interaction effect with stressful life events (p < 0.001) and number of distinct traumatic events (p = 0.001). In multivariate models, At-Risk status predicted anxiety disorders (OR = 2.7, CI 1.3-5.4, p = 0.005) and anxiety severity (Coefficient = 0.4, CI 0.2-0.7, p < 0.001) but not mood or behavioral disorder diagnoses or severity. LIMITATIONS: Measures of stress and social support were based on self-report. Not all participants had passed through the period of risk for developing the outcomes under study and the follow up period was variable. We could not fully study the differential impact of physical or sexual abuse due to low frequency of occurrence in controls. CONCLUSION: At-Risk youth exhibit more severe mood symptoms compared to Controls when exposed to similar levels of stress or trauma. At-Risk youth are also more prone to develop anxiety which may be a precursor for bipolar disorder.
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Structural neuroimaging studies have identified a combination of shared and disorder-specific patterns of gray matter (GM) deficits across psychiatric disorders. Pooling large data allows for examination of a possible common neuroanatomical basis that may identify a certain vulnerability for mental illness. Large-scale collaborative research is already facilitated by data repositories, institutionally supported databases, and data archives. However, these data-sharing methodologies can suffer from significant barriers. Federated approaches augment these approaches by enabling access or more sophisticated, shareable and scaled-up analyses of large-scale data. We examined GM alterations using Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation, an open-source, decentralized analysis application. Through federated analysis of eight sites, we identified significant overlap in the GM patterns (n = 4,102) of individuals with schizophrenia, major depressive disorder, and autism spectrum disorder. These results show cortical and subcortical regions that may indicate a shared vulnerability to psychiatric disorders.
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OBJECTIVES: To understand treatment practices for bipolar disorders (BD), this study leveraged the Global Bipolar Cohort collaborative network to investigate pharmacotherapeutic treatment patterns in multiple cohorts of well-characterized individuals with BD in North America, Europe, and Australia. METHODS: Data on pharmacotherapy, demographics, diagnostic subtypes, and comorbidities were provided from each participating cohort. Individual site and regional pooled proportional meta-analyses with generalized linear mixed methods were conducted to identify prescription patterns. RESULTS: This study included 10,351 individuals from North America (n = 3985), Europe (n = 3822), and Australia (n = 2544). Overall, participants were predominantly female (60%) with BD-I (60%; vs. BD-II = 33%). Cross-sectionally, mood-stabilizing anticonvulsants (44%), second-generation antipsychotics (42%), and antidepressants (38%) were the most prescribed medications. Lithium was prescribed in 29% of patients, primarily in the Australian (31%) and European (36%) cohorts. First-generation antipsychotics were prescribed in 24% of the European versus 1% in the North American cohort. Antidepressant prescription rates were higher in BD-II (47%) compared to BD-I (35%). Major limitations were significant differences among cohorts based on inclusion/exclusion criteria, data source, and time/year of enrollment into cohort. CONCLUSIONS: Mood-stabilizing anticonvulsants, second-generation antipsychotics, and antidepressants were the most prescribed medications suggesting prescription patterns that are not necessarily guideline concordant. Significant differences exist in the prescription practices across different geographic regions, especially the underutilization of lithium in the North American cohorts and the higher utilization of first-generation antipsychotics in the European cohorts. There is a need to conduct future longitudinal studies to further explore these differences and their impact on outcomes, and to inform and implement evidence-based guidelines to help improve treatment practices in BD.
Subject(s)
Antipsychotic Agents , Bipolar Disorder , Humans , Female , Male , Bipolar Disorder/drug therapy , Bipolar Disorder/epidemiology , Bipolar Disorder/diagnosis , Lithium/therapeutic use , Anticonvulsants/therapeutic use , Australia/epidemiology , Antipsychotic Agents/therapeutic use , Antidepressive Agents/therapeutic useABSTRACT
Investigating alterations in brain circuitry associated with bipolar disorder (BD) may offer a valuable approach to discover brain biomarkers for genetic and interventional studies of the disorder and related mental illnesses. Some diffusion MRI studies report evidence of microstructural abnormalities in white matter regions of interest, but we lack a fine-scale spatial mapping of brain microstructural differences along tracts in BD. We also lack large-scale studies that integrate tractometry data from multiple sites, as larger datasets can greatly enhance power to detect subtle effects and assess whether effects replicate across larger international datasets. In this multisite diffusion MRI study, we used BUndle ANalytics (BUAN, Chandio 2020), a recently developed analytic approach for tractography, to extract, map, and visualize profiles of microstructural abnormalities on 3D models of fiber tracts in 148 participants with BD and 259 healthy controls from 6 independent scan sites. Modeling site differences as random effects, we investigated along-tract white matter (WM) microstructural differences between diagnostic groups. QQ plots showed that group differences were gradually enhanced as more sites were added. Using the BUAN pipeline, BD was associated with lower mean fractional anisotropy (FA) in fronto-limbic, interhemispheric, and posterior pathways; higher FA was also noted in posterior bundles, relative to controls. By integrating tractography and anatomical information, BUAN effectively captures unique effects along white matter (WM) tracts, providing valuable insights into anatomical variations that may assist in the classification of diseases.
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Background: The interaction of polygenic risk (PRS) and environmental effects on development of bipolar disorder (BD) is understudied, as are high-risk offspring perceptions of their family environment (FE). We tested the association of offspring-perceived FE in interaction with BD-PRS on liability for BD in offspring at high or low familial risk for BD. Methods: Offspring of a parent with BD (oBD; n = 266) or no psychiatric disorders (n = 174), aged 12-21 at recruitment, participated in the US and Australia. Empirically-derived profiles of FE classified offspring by their perceived levels of familial cohesion, flexibility, and conflict. Offspring BD-PRS were derived from Psychiatric Genomics Consortium BD-GWAS. Lifetime DSM-IV bipolar disorders were derived from the Schedule for Affective Disorders and Schizophrenia for School-Aged Children. We used a novel stepwise approach for latent class modeling with predictors and distal outcomes. Results: Fifty-two offspring were diagnosed with BD. For those with well-functioning FE (two-thirds of the sample), higher BD-PRS tracked positively with liability for BD. However, for those with high-conflict FEs, the relationship between BD-PRS and liability to BD was negative, with highest risk for BD observed with lower BD-PRS. In exploratory analyses, European-ancestry offspring with BD had elevated history of suicidal ideation in high-conflict FE compared to well-functioning-FE, and of suicide attempt with low-BD-PRS and high-conflict FE. Conclusions: The data suggest that the relationship of BD-PRS and offspring liability for BD differed between well-functioning versus high-conflict FE, potentially in line with a multifactorial liability threshold model and supporting future study of and interventions improving family dynamics.
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OBJECTIVE: Family history is an established risk factor for mental illness. The authors sought to investigate whether polygenic scores (PGSs) can complement family history to improve identification of risk for major mood and psychotic disorders. METHODS: Eight cohorts were combined to create a sample of 1,884 participants ages 2-36 years, including 1,339 offspring of parents with mood or psychotic disorders, who were prospectively assessed with diagnostic interviews over an average of 5.1 years. PGSs were constructed for depression, bipolar disorder, anxiety, attention deficit hyperactivity disorder (ADHD), schizophrenia, neuroticism, subjective well-being, p factor, and height (as a negative control). Cox regression was used to test associations between PGSs, family history of major mental illness, and onsets of major mood and psychotic disorders. RESULTS: There were 435 onsets of major mood and psychotic disorders across follow-up. PGSs for neuroticism (hazard ratio=1.23, 95% CI=1.12-1.36), schizophrenia (hazard ratio=1.15, 95% CI=1.04-1.26), depression (hazard ratio=1.11, 95% CI=1.01-1.22), ADHD (hazard ratio=1.10, 95% CI=1.00-1.21), subjective well-being (hazard ratio=0.90, 95% CI=0.82-0.99), and p factor (hazard ratio=1.14, 95% CI=1.04-1.26) were associated with onsets. After controlling for family history, neuroticism PGS remained significantly positively associated (hazard ratio=1.19, 95% CI=1.08-1.31) and subjective well-being PGS remained significantly negatively associated (hazard ratio=0.89, 95% CI=0.81-0.98) with onsets. CONCLUSIONS: Neuroticism and subjective well-being PGSs capture risk of major mood and psychotic disorders that is independent of family history, whereas PGSs for psychiatric illness provide limited predictive power when family history is known. Neuroticism and subjective well-being PGSs may complement family history in the early identification of persons at elevated risk.
Subject(s)
Bipolar Disorder , Psychotic Disorders , Schizophrenia , Humans , Child, Preschool , Child , Adolescent , Young Adult , Adult , Psychotic Disorders/diagnosis , Psychotic Disorders/genetics , Bipolar Disorder/diagnosis , Bipolar Disorder/genetics , Bipolar Disorder/psychology , Schizophrenia/diagnosis , Schizophrenia/genetics , Parents , Risk FactorsABSTRACT
Environmental factors contribute to risk of bipolar disorder (BD), but how environmental factors impact the development of psychopathology within the context of elevated genetic risk is unknown. We herein sought to identify epigenetic signatures operating in the context of polygenic risk for BD in young people at high familial risk (HR) of BD. Peripheral blood-derived DNA was assayed using Illumina PsychArray, and Methylation-450K or -EPIC BeadChips. Polygenic risk scores (PRS) were calculated using summary statistics from recent genome-wide association studies for BD, major depressive disorder (MDD) and cross-disorder (meta-analysis of eight psychiatric disorders). Unrelated HR participants of European ancestry (n = 103) were stratified based on their BD-PRS score within the HR-population distribution, and the top two quintiles (High-BD-PRS; n = 41) compared against the bottom two quintiles (Low-BD-PRS; n = 41). The High-BD-PRS stratum also had higher mean cross-disorder-PRS and MDD-PRS (ANCOVA p = 0.035 and p = 0.024, respectively). We evaluated DNA methylation differences between High-BD-PRS and Low-BD-PRS strata using linear models. One differentially methylated probe (DMP) (cg00933603; p = 3.54 × 10-7) in VARS2, a mitochondrial aminoacyl-tRNA synthetase, remained significantly hypomethylated after multiple-testing correction. Overall, BD-PRS appeared to broadly impact epigenetic processes, with 1,183 genes mapped to nominal DMPs (p < 0.05); these displayed convergence with genes previously associated with BD, schizophrenia, chronotype, and risk taking. We tested poly-methylomic epigenetic profiles derived from nominal DMPs in two independent samples (n = 54 and n = 82, respectively), and conducted an exploratory evaluation of the effects of family environment, indexing cohesion and flexibility. This study highlights an important interplay between heritable risk and epigenetic factors, which warrant further exploration.
Subject(s)
Bipolar Disorder , Depressive Disorder, Major , Adolescent , Bipolar Disorder/genetics , Bipolar Disorder/psychology , Depressive Disorder, Major/genetics , Epigenesis, Genetic , Genetic Predisposition to Disease , Genome-Wide Association Study , HLA Antigens , Humans , Multifactorial Inheritance , Valine-tRNA Ligase/geneticsABSTRACT
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.
Subject(s)
Bipolar Disorder , Adolescent , Adult , Bipolar Disorder/diagnostic imaging , Bipolar Disorder/genetics , Brain/diagnostic imaging , Child , Corpus Striatum , Diffusion Magnetic Resonance Imaging , Humans , Magnetic Resonance Imaging , Thalamus , Young AdultABSTRACT
Bipolar disorder (BD) is associated with a 20-30-fold increased suicide risk compared to the general population. First-degree relatives of BD patients show inflated rates of psychopathology including suicidal behaviors. As reliable biomarkers of suicide attempts (SA) are lacking, we examined associations between suicide-related polygenic risk scores (PRSs)-a quantitative index of genomic risk-and variability in brain structures implicated in SA. Participants (n = 206; aged 12-30 years) were unrelated individuals of European ancestry and comprised three groups: 41 BD cases, 96 BD relatives ("high risk"), and 69 controls. Genotyping employed PsychArray, followed by imputation. Three PRSs were computed using genome-wide association data for SA in BD (SA-in-BD), SA in major depressive disorder (SA-in-MDD) (Mullins et al., 2019, The American Journal of Psychiatry, 176(8), 651-660), and risky behavior (Karlsson Linnér et al., 2019, Nature Genetics, 51(2), 245-257). Structural magnetic resonance imaging processing employed FreeSurfer v5.3.0. General linear models were constructed using 32 regions-of-interest identified from suicide neuroimaging literature, with false-discovery-rate correction. SA-in-MDD and SA-in-BD PRSs negatively predicted parahippocampal thickness, with the latter association modified by group membership. SA-in-BD and Risky Behavior PRSs inversely predicted rostral and caudal anterior cingulate structure, respectively, with the latter effect driven by the "high risk" group. SA-in-MDD and SA-in-BD PRSs positively predicted cuneus structure, irrespective of group. This study demonstrated associations between PRSs for suicide-related phenotypes and structural variability in brain regions implicated in SA. Future exploration of extended PRSs, in conjunction with a range of biological, phenotypic, environmental, and experiential data in high risk populations, may inform predictive models for suicidal behaviors.
Subject(s)
Bipolar Disorder , Depressive Disorder, Major , Adolescent , Bipolar Disorder/genetics , Depressive Disorder, Major/genetics , Genetic Predisposition to Disease , Genome-Wide Association Study , Gyrus Cinguli , Humans , Suicide, AttemptedABSTRACT
Bipolar disorder is associated with cognitive deficits and cortical changes for which the developmental dynamics are not well understood. The dopamine D2 receptor (DRD2) gene has been associated with both psychiatric disorders and cognitive variability. Here we examined the mediating role of brain structure in the relationship between DRD2 genomic variation and cognitive performance, with target cortical regions selected based on evidence of association with DRD2, bipolar disorder and/or cognition from prior literature. Participants (n = 143) were aged 12-30 years and comprised 62 first-degree relatives of bipolar patients (deemed 'at-risk'), 55 controls, and 26 patients with established bipolar disorder; all were unrelated Caucasian individuals with complete data across the three required modalities (structural magnetic resonance imaging, neuropsychological and genetic data). A DRD2 haplotype was derived from three functional polymorphisms (rs1800497, rs1076560, rs2283265) associated with alternative splicing (i.e., D2-short/-long isoforms). Moderated mediation analyses explored group differences in relationships between this DRD2 haplotype, three structural brain networks which subsume the identified cortical regions of interest (frontoparietal, dorsal-attention, and ventral-attention), and three cognitive indices (intelligence, attention, and immediate memory). Controls who were homozygous for the DRD2 major haplotype demonstrated greater cognitive performance as a result of dorsal-attention network mediation. However, this association was absent in the 'at-risk' group. This study provides the first evidence of a functional DRD2-brain-cognition pathway. The absence of typical brain-cognition relationships in young 'at-risk' individuals may reflect biological differences that precede illness onset. Further insight into early pathogenic processes may facilitate targeted early interventions.
Subject(s)
Bipolar Disorder , Adolescent , Adult , Bipolar Disorder/diagnostic imaging , Bipolar Disorder/genetics , Brain/diagnostic imaging , Child , Cognition , Humans , Memory, Short-Term , Receptors, Dopamine D2/genetics , Young AdultABSTRACT
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
ABSTRACT
Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R2 = 0.041, Pcorr < 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.
Subject(s)
Bipolar Disorder/pathology , Brain/pathology , White Matter/pathology , Adult , Bipolar Disorder/diagnostic imaging , Brain/diagnostic imaging , Corpus Callosum/diagnostic imaging , Corpus Callosum/pathology , Diffusion Tensor Imaging , Female , Humans , Male , Neural Pathways/diagnostic imaging , Neural Pathways/pathology , White Matter/diagnostic imagingABSTRACT
Many studies have reported that heavy substance use is associated with impaired response inhibition. Studies typically focused on associations with a single substance, while polysubstance use is common. Further, most studies compared heavy users with light/non-users, though substance use occurs along a continuum. The current mega-analysis accounted for these issues by aggregating individual data from 43 studies (3610 adult participants) that used the Go/No-Go (GNG) or Stop-signal task (SST) to assess inhibition among mostly "recreational" substance users (i.e., the rate of substance use disorders was low). Main and interaction effects of substance use, demographics, and task-characteristics were entered in a linear mixed model. Contrary to many studies and reviews in the field, we found that only lifetime cannabis use was associated with impaired response inhibition in the SST. An interaction effect was also observed: the relationship between tobacco use and response inhibition (in the SST) differed between cannabis users and non-users, with a negative association between tobacco use and inhibition in the cannabis non-users. In addition, participants' age, education level, and some task characteristics influenced inhibition outcomes. Overall, we found limited support for impaired inhibition among substance users when controlling for demographics and task-characteristics.
Subject(s)
Executive Function/physiology , Inhibition, Psychological , Psychomotor Performance/physiology , Substance-Related Disorders/physiopathology , HumansABSTRACT
Children's perceptions are important to understanding family environment in the bipolar disorder (BD) high-risk context. Our objectives were to empirically derive patterns of offspring-perceived family environment, and to test the association of family environment with maternal or paternal BD accounting for offspring BD and demographic characteristics. Participants aged 12-21 years (266 offspring of a parent with BD, 175 offspring of a parent with no psychiatric history) were recruited in the US and Australia. We modeled family environment using latent profile analysis based on offspring reports on the Conflict Behavior Questionnaire, Family Adaptability and Cohesion Evaluation Scales, and Home Environment Interview for Children. Parent diagnoses were based on the Diagnostic Interview for Genetic Studies and offspring diagnoses were based on the Schedule for Affective Disorders and Schizophrenia for School-Aged Children. Latent class regression was used to test associations of diagnosis and family environment. Two-thirds of all offspring perceived well-functioning family environment, characterized by nurturance, flexibility, and low conflict. Two 'conflict classes' perceived family environments low in flexibility and cohesion, with substantial separation based on high conflict with the father (High Paternal Conflict), or very high conflict and rigidity and low warmth with the mother (High Maternal Conflict). Maternal BD was associated with offspring perceiving High Maternal Conflict (OR 2.8, pâ¯=â¯0.025). Clinical care and psychosocial supports for mothers with BD should address family functioning, with attention to offspring perceptions of their wellbeing. More research is needed on the effect of paternal BD on offspring and family dynamics.
Subject(s)
Bipolar Disorder/etiology , Family/psychology , Adolescent , Bipolar Disorder/genetics , Family Conflict/psychology , Female , Humans , Interview, Psychological , Male , Psychiatric Status Rating Scales , Risk Factors , Social Environment , Surveys and QuestionnairesABSTRACT
Traveling patterns of neuronal activity-brain waves-have been observed across a breadth of neuronal recordings, states of awareness, and species, but their emergence in the human brain lacks a firm understanding. Here we analyze the complex nonlinear dynamics that emerge from modeling large-scale spontaneous neural activity on a whole-brain network derived from human tractography. We find a rich array of three-dimensional wave patterns, including traveling waves, spiral waves, sources, and sinks. These patterns are metastable, such that multiple spatiotemporal wave patterns are visited in sequence. Transitions between states correspond to reconfigurations of underlying phase flows, characterized by nonlinear instabilities. These metastable dynamics accord with empirical data from multiple imaging modalities, including electrical waves in cortical tissue, sequential spatiotemporal patterns in resting-state MEG data, and large-scale waves in human electrocorticography. By moving the study of functional networks from a spatially static to an inherently dynamic (wave-like) frame, our work unifies apparently diverse phenomena across functional neuroimaging modalities and makes specific predictions for further experimentation.
Subject(s)
Brain Waves/physiology , Brain/physiology , Diffusion Tensor Imaging/methods , Models, Neurological , Adolescent , Adult , Brain/diagnostic imaging , Computer Simulation , Electrocorticography , Female , Healthy Volunteers , Humans , Male , Nerve Net , Neurons , Nonlinear Dynamics , Young AdultABSTRACT
Melatonin secretion and polysomnography (PSG) were compared among a group of healthy adolescents who were at high familial risk for bipolar disorder (HR) and a second group at low familial risk (LR). Adolescent participants (nâ¯=â¯12) were a mean age 14 ± 2.3 years and included 8 females and 4 males. Saliva samples were collected under standardized condition light (red light) and following a 200 lux light exposure over two consecutive nights in a sleep laboratory. Red Light Melatonin onset (RLMO) was defined as saliva melatonin level exceeding the mean of the first 3 readings plus 2 standard deviations. Polysomnography was also completed during each night. HR youth, relative to LR, experienced a significantly earlier melatonin onset following 200 lux light exposure. Polysomnography revealed that LR youth, relative to HR, spent significantly more time in combined stages 3 and 4 (deep sleep) following red light exposure. Additionally, regardless of the group status (HR or LR), there was no significant difference in Red Light Melatonin Onset recorded at home or in the laboratory, implying its feasibility and reliability.
Subject(s)
Bipolar Disorder/diagnosis , Bipolar Disorder/metabolism , Genetic Predisposition to Disease , Melatonin/metabolism , Photic Stimulation/methods , Saliva/metabolism , Adolescent , Adult , Biomarkers/chemistry , Biomarkers/metabolism , Bipolar Disorder/genetics , Child , Circadian Rhythm/physiology , Female , Genetic Predisposition to Disease/genetics , Humans , Male , Polysomnography/trends , Reproducibility of Results , Saliva/chemistry , Sleep/physiology , Sleep Disorders, Circadian Rhythm/diagnosis , Sleep Disorders, Circadian Rhythm/genetics , Sleep Disorders, Circadian Rhythm/metabolismABSTRACT
This Article was originally published under Nature Research's License to Publish, but has now been made available under a [CC BY 4.0] license. The PDF and HTML versions of the Article have been modified accordingly.
ABSTRACT
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".
Subject(s)
Bipolar Disorder/metabolism , Bipolar Disorder/physiopathology , Nerve Net/physiology , Bipolar Disorder/genetics , Brain/physiopathology , Cerebral Cortex/physiopathology , Cognition/physiology , Connectome/methods , Emotions/physiology , Female , Humans , Male , Prefrontal Cortex/physiopathology , Psychotic Disorders/physiopathology , Schizophrenia/physiopathologyABSTRACT
BACKGROUND: Increased white matter hyperintensities (WMHs) is one of the most consistent imaging findings amongst participants with bipolar disorder (BD). This study investigated WMHs in a young population at high genetic risk for bipolar disorder (HR). METHODS: MRI scans were conducted at baseline in HR individuals (nâ¯=â¯131), patients with BD (nâ¯=â¯47) and controls (CON) (nâ¯=â¯108). Most of the HR (nâ¯=â¯77) and CON (nâ¯=â¯74) group completed scans after two years. Scans were examined for the presence of WMHs. RESULTS: There were significantly more periventricular WMHs in the BD compared to the CON group at baseline (pâ¯=â¯.04). Although the prevalence of periventricular WMHs was intermediate in the HR group, there were no significant differences between the HR and CON or BD participants. Deep WMHs did not differ significantly between the groups. Over time, there was a significant increase in the prevalence of periventricular WMHs in both the HR and CON groups (pâ¯=â¯.02). LIMITATIONS: The use of a visual rating scale to examine WMHs is subjective. As the gradings were collapsed into 'present' or 'absent', we could not ascertain whether the severity of hyperintensities worsened over time. CONCLUSIONS: Periventricular WMHs are more prevalent in young individuals with BD than controls. As these are not more prevalent in HR individuals, it is possible that these are either secondary to the development of bipolar disorder, its treatment, or resulting changes in lifestyle. In a novel finding, there were similar increases in the prevalence of WMHs in controls and HR youth over the 2-year period.
Subject(s)
Bipolar Disorder/diagnostic imaging , Magnetic Resonance Imaging/statistics & numerical data , White Matter/diagnostic imaging , Adolescent , Adult , Bipolar Disorder/genetics , Bipolar Disorder/pathology , Child , Female , Genetic Predisposition to Disease , Humans , Magnetic Resonance Imaging/methods , Male , Organ Size , Prevalence , Risk Factors , White Matter/pathology , Young AdultABSTRACT
Recent investigations have used diffusion-weighted imaging to reveal disturbances in the neurocircuitry that underlie cognitive-emotional control in bipolar disorder (BD) and in unaffected siblings or children at high genetic risk (HR). It has been difficult to quantify the mechanism by which structural changes disrupt the superimposed brain dynamics, leading to the emotional lability that is characteristic of BD. Average controllability is a concept from network control theory that extends structural connectivity data to estimate the manner in which local neuronal fluctuations spread from a node or subnetwork to alter the state of the rest of the brain. We used this theory to ask whether structural connectivity deficits previously observed in HR individuals (nâ¯=â¯84, mean age 22.4), patients with BD (nâ¯=â¯38, mean age 23.9), and age- and gender-matched controls (nâ¯=â¯96, mean age 22.6) translate to differences in the ability of brain systems to be manipulated between states. Localized impairments in network controllability were seen in the left parahippocampal, left middle occipital, left superior frontal, right inferior frontal, and right precentral gyri in BD and HR groups. Subjects with BD had distributed deficits in a subnetwork containing the left superior and inferior frontal gyri, postcentral gyrus, and insula (pâ¯=â¯0.004). HR participants had controllability deficits in a right-lateralized subnetwork involving connections between the dorsomedial and ventrolateral prefrontal cortex, the superior temporal pole, putamen, and caudate nucleus (pâ¯=â¯0.008). Between-group controllability differences were attenuated after removal of topological factors by network randomization. Some previously reported differences in network connectivity were not associated with controllability-differences, likely reflecting the contribution of more complex brain network properties. These analyses highlight the potential functional consequences of altered brain networks in BD, and may guide future clinical interventions.