What we learn about bipolar disorder from large-scale neuroimaging:Findings and future directions from the ENIGMA Bipolar Disorder Working Group

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness

Reproducibility in the absence of selective reporting: An illustration from large‐scale brain asymmetry research

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p‐hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left–right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta‐analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an “ideal publishing environment,” that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically‐used sample sizes

The Association Between Familial Risk and Brain Abnormalities Is Disease Specific: An ENIGMA-Relatives Study of Schizophrenia and Bipolar Disorder

Background: Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. Methods: We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. Results: FDRs-BD had significantly larger ICV (d = +0.16, q <.05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = −0.12, q <.05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < −0.09, q <.05 corrected); and third ventricle was larger (d = +0.15, q <.05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. Conclusions: Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct

Progression of neuroanatomical abnormalities in psychotic disorder and the effect of psychotropic medication

Introduction: Schizophrenia is a particularly severe and disabling mental disorder affecting 20 million people worldwide. The vast majority of structural and diffusion neuroimaging studies on neuroanatomy and cognition have been conducted cross-sectionally and it remains unclear whether risk factors, treatments or associated illness effects are driving changes. The overarching theme of this thesis is to longitudinally examine elements of neuroanatomical progression and its cognitive or clinical correlates in samples of patients across different phases of psychosis spanning first episode of illness and treatment refractory schizophrenia, using structural and diffusion MRI techniques. Specifically, Manuscript 1 aims to assess whether impaired executive functioning and emotional intelligence at first presentation of psychotic episode are associated with progressive prefrontal and orbitofrontal cortical thinning and whether negative symptom severity is linked to progressive prefrontal cortical thinning in the years following the first-episode of psychosis. Manuscript 2 and 3, using a unique sample of treatment-resistant clozapine-naïve schizophrenia patients, investigate whether subcortical structures, white matter microstructure and structural network organisation demonstrate any progressive changes after 6 months of clozapine treatment and whether any such changes are related to clinical variables including treatment response and amount of clozapine taken. Method: Manuscript 1. 1.5T structural MRI images were acquired at baseline and after 3.5 years for 20 individuals with first-episode psychosis (FEP) and 18 healthy volunteers (HC). At baseline and follow-up, the longitudinal pipeline of Freesurfer was employed to parcellate prefrontal cortex and the MATRICS Consensus Cognitive Battery (MCCB) was used to assess executive functioning and emotional intelligence. At both timepoints the severity of negative and positive symptoms was assessed using the Positive and Negative Syndrome Scale (PANSS). Baseline cognitive performance was compared between diagnostic groups using Multivariate Analysis of Covariance (MANCOVA). Partial correlations investigated relationships between cognition and negative symptoms at baseline and cortical thickness change over time. Manuscript 2 & 3. Thirty-three patients with treatment-resistant schizophrenia (TRS) and 31 healthy volunteers successfully participated at both baseline, prior to clozapine initiation in patients, and 6 months follow-up clinical assessments and structural MRI scanning (Manuscript 2). Of these 64 participants, diffusion MRI data were available at both time points for 22 patients and 23 healthy controls (Manuscript 3). The severity of positive and negative symptoms was assessed at both time points using the PANSS, the Scale for the Assessment of Positive Symptoms (SAPS) and the Scale for the Assessment of Negative Symptoms (SANS). Social, occupational and psychological functioning was assessed using a Global Assessment of Functioning Score. In Manuscript 2 the longitudinal pipeline of Freesurfer v.5.3.0 was employed to bilaterally segment eight subcortical regions-of-interest: lateral ventricle, thalamus, hippocampus, caudate, putamen, globus pallidus, amygdala and nucleus accumbens. Two-way repeated MANCOVA was used to assess group differences in subcortical volumes over time and partial correlations to determine association with clinical variables. In Manuscript 3 the Tract-based spatial statistics approach (TBSS) was used to compare changes over time between groups in fractional anisotropy (FA). Changes in structural network organisation and subnetwork connectivity weighted by FA and number of streamlines (NOS) were assessed using graph theory and network-based statistics. Results: In Manuscript 1 we demonstrated that patients in their first-episode of psychotic illness perform significantly worse on several tests assessing different aspects of executive functions compared to healthy controls, including category fluency, attention, working memory and reasoning & problem solving. The poorer performance at baseline in spatial working memory was a significant predictor of loss of total prefrontal cortical thickness in the initial years after illness onset. We also found that impairment of emotional intelligence at illness onset was significantly associated with a progressive reduction of orbitofrontal thickness in patients after their first-episode of psychosis. Finally, we demonstrated a correlation between neuroanatomical progression and clinical variables, specifically, worsening of negative symptoms was associated with prefrontal thickness reduction as the illness progresses. In Manuscript 2, in treatment-resistant schizophrenia patients we showed a substantial progressive volumetric reduction of the thalamus, hippocampus, caudate, putamen and enlargement of lateral ventricles over a 6-month period compared to controls. Furthermore, patients who had the greatest symptomatic and functional improvement displayed the largest thalamo-striatal reductions. We also found that patients who were exposed to higher amounts of clozapine displayed a greater reduction of thalamus volume. In Manuscript 3, treatment-resistant schizophrenia patients showed progressive focal FA abnormalities in the white matter of key anterior tracts, such as genu and body of the corpus callosum and bilaterally in the anterior and superior corona radiata compared to controls. The brain structural network organisation was preserved in patients compared to controls. The FA reduction was independent of any clinical measures or serum level of clozapine. Conclusion: Taken together our results indicate that at onset of psychosis working memory and emotional intelligence impairment represents a trait marker of progressive prefrontal thinning as the illness progresses, while worsening of negative symptoms is associated with prefrontal thickness reduction over time, indicating a functional consequence of anatomical progression in psychosis. In those with the chronic treatment-resistant stage of the illness, there is a consistent progressive volume reduction in several subcortical structures as well as progressive focal abnormalities in the white matter microstructure of key anterior tracts, but a preserved brain structural network. However, our findings suggest a divergence of neuroanatomical progression, where progressive atrophy in the thalamo-striatal circuits are linked to clinical and functional improvement, whereas no such association is found with longitudinal progression in lateral ventricles, hippocampus and white matter. This thesis confirms the importance of investigating the neurocognitive dimension at illness onset in order to enhance understanding of the functional consequences of illness progression as well as identifying potential markers at illness onset. It also highlights the potential role of the thalamo-striatal circuits in tracking recovery in treatment-resistant schizophrenia patients, suggesting that its investigation using large scale longitudinal design studies could significantly contribute to the identification of biomarkers in refractory schizophrenia

White matter microstructure and structural networks in treatment-resistant schizophrenia patients after commencing clozapine treatment: A longitudinal diffusion imaging study

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Neuroanatomical dysconnectivity underlying cognitive deficits in bipolar disorder

BACKGROUND: Graph theory applied to brain networks is an emerging approach to understanding the brain's topological associations with human cognitive ability. Despite well-documented cognitive impairments in bipolar disorder (BD) and recent reports of altered anatomical network organization, the association between connectivity and cognitive impairments in BD remains unclear.METHODS: We examined the role of anatomical network connectivity derived from Ti - and diffusion-weighted magnetic resonance imaging in impaired cognitive performance in individuals with BD (n = 32) compared with healthy control individuals (n = 38). Fractional anisotropy- and number of streamlines-weighted anatomical brain networks were generated by mapping constrained spherical deconvolution-reconstructed white matter among 86 cortical/subcortical bilateral brain regions delineated in the individual's own coordinate space. Intelligence and executive function were investigated as distributed functions using measures of global, rich-club, and interhemispheric connectivity, while memory and social cognition were examined in relation to subnetwork connectivity.RESULTS: Lower executive functioning related to higher global clustering coefficient in participants with BD, and lower IQ performance may present with a differential relationship between global and interhemispheric efficiency in individuals with BD relative to control individuals. Spatial recognition memory accuracy and response times were similar between diagnostic groups and associated with basal ganglia and thalamus interconnectivity and connectivity within extended anatomical subnetworks in all participants. No anatomical subnetworks related to episodic memory, short-term memory, or social cognition generally or differently in BD.CONCLUSIONS: Results demonstrate selective influence of subnetwork patterns of connectivity in underlying cognitive performance generally and abnormal global topology underlying discrete cognitive impairments in BD.We gratefully acknowledge the participants, the support of the Welcome-Trust HRB Clinical Research Facility, the Centre for Advanced Medical Imaging at St. James Hospital Dublin and funding support from the Irish Research Council Government of Ireland Postgraduate Scholarship. We would also like to thank Andrew Hoopes, Research Technician I, MGH/HST Martinos Center for Biomedical Imaging for Freesurfer software support, Christopher Grogan, MSc, for his contribution to data processing and Jenna Pittman, BSc and Fiona Martyn, BA for their contribution to data handling. This research was funded by the Health Research Board (HRA-POR324) awarded to Dara M. Cannon, PhD.peer-reviewed2020-09-1

Neuroanatomical dysconnectivity underlying cognitive deficits in bipolar disorder

BACKGROUND: Graph theory applied to brain networks is an emerging approach to understanding the brain\u27s topological associations with human cognitive ability. Despite well-documented cognitive impairments in bipolar disorder (BD) and recent reports of altered anatomical network organization, the association between connectivity and cognitive impairments in BD remains unclear.METHODS: We examined the role of anatomical network connectivity derived from Ti - and diffusion-weighted magnetic resonance imaging in impaired cognitive performance in individuals with BD (n = 32) compared with healthy control individuals (n = 38). Fractional anisotropy- and number of streamlines-weighted anatomical brain networks were generated by mapping constrained spherical deconvolution-reconstructed white matter among 86 cortical/subcortical bilateral brain regions delineated in the individual\u27s own coordinate space. Intelligence and executive function were investigated as distributed functions using measures of global, rich-club, and interhemispheric connectivity, while memory and social cognition were examined in relation to subnetwork connectivity.RESULTS: Lower executive functioning related to higher global clustering coefficient in participants with BD, and lower IQ performance may present with a differential relationship between global and interhemispheric efficiency in individuals with BD relative to control individuals. Spatial recognition memory accuracy and response times were similar between diagnostic groups and associated with basal ganglia and thalamus interconnectivity and connectivity within extended anatomical subnetworks in all participants. No anatomical subnetworks related to episodic memory, short-term memory, or social cognition generally or differently in BD.CONCLUSIONS: Results demonstrate selective influence of subnetwork patterns of connectivity in underlying cognitive performance generally and abnormal global topology underlying discrete cognitive impairments in BD.We gratefully acknowledge the participants, the support of the Welcome-Trust HRB Clinical Research Facility, the Centre for Advanced Medical Imaging at St. James Hospital Dublin and funding support from the Irish Research Council Government of Ireland Postgraduate Scholarship. We would also like to thank Andrew Hoopes, Research Technician I, MGH/HST Martinos Center for Biomedical Imaging for Freesurfer software support, Christopher Grogan, MSc, for his contribution to data processing and Jenna Pittman, BSc and Fiona Martyn, BA for their contribution to data handling. This research was funded by the Health Research Board (HRA-POR324) awarded to Dara M. Cannon, PhD.2020-09-1