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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Brain structural damage networks at different stages of schizophrenia

BACKGROUND

Neuroimaging studies have documented brain structural changes in schizophrenia at different stages of the illness, including clinical high-risk (cHR), genetic high-risk (gHR), first-episode schizophrenia (FES), and chronic schizophrenia (ChS). There is growing awareness that neuropathological processes associated with a disease fail to map to a specific brain region but do map to a specific brain network. We sought to investigate brain structural damage networks across different stages of schizophrenia.

METHODS

We initially identified gray matter alterations in 523 cHR, 855 gHR, 2162 FES, and 2640 ChS individuals relative to 6963 healthy controls. By applying novel functional connectivity network mapping to large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to four specific networks.

RESULTS

Brain structural damage networks of cHR and gHR had limited and non-overlapping spatial distributions, with the former mainly involving the frontoparietal network and the latter principally implicating the subcortical network, indicative of distinct neuropathological mechanisms underlying cHR and gHR. By contrast, brain structural damage networks of FES and ChS manifested as similar patterns of widespread brain areas predominantly involving the somatomotor, ventral attention, and subcortical networks, suggesting an emergence of more prominent brain structural abnormalities with illness onset that have trait-like stability over time.

CONCLUSIONS

Our findings may not only provide a refined picture of schizophrenia neuropathology from a network perspective, but also potentially contribute to more targeted and effective intervention strategies for individuals at different schizophrenia stages.

Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness

Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one's children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and resilience strengthening. Prior twin, family, and adoption studies suggest that the aetiology of mental illness is governed by a complex interplay of genetic and environmental factors, potentially mediated by changes in epigenetic programming and brain development. However, how these factors ultimately materialise into mental disorders remains unclear. Here, we present the FAMILY consortium, an interdisciplinary, multimodal (e.g., (epi)genetics, neuroimaging, environment, behaviour), multilevel (e.g., individual-level, family-level), and multisite study funded by a European Union Horizon-Staying-Healthy-2021 grant. FAMILY focuses on understanding and prediction of intergenerational transmission of mental illness, using genetically informed causal inference, multimodal normative prediction, and animal modelling. Moreover, FAMILY applies methods from social sciences to map social and ethical consequences of risk prediction to prepare clinical practice for future implementation. FAMILY aims to deliver: (i) new discoveries clarifying the aetiology of mental illness and the process of resilience, thereby providing new targets for prevention and intervention studies; (ii) a risk prediction model within a normative modelling framework to predict who is at risk for developing mental illness; and (iii) insight into social and ethical issues related to risk prediction to inform clinical guidelines.

Putative Risk Biomarkers of Bipolar Disorder in At-risk Youth

Bipolar disorder is a highly heritable and functionally impairing disease. The recognition and intervention of BD especially that characterized by early onset remains challenging. Risk biomarkers for predicting BD transition among at-risk youth may improve disease prognosis. We reviewed the more recent clinical studies to find possible pre-diagnostic biomarkers in youth at familial or (and) clinical risk of BD. Here we found that putative biomarkers for predicting conversion to BD include findings from multiple sample sources based on different hypotheses. Putative risk biomarkers shown by perspective studies are higher bipolar polygenetic risk scores, epigenetic alterations, elevated immune parameters, front-limbic system deficits, and brain circuit dysfunction associated with emotion and reward processing. Future studies need to enhance machine learning integration, make clinical detection methods more objective, and improve the quality of cohort studies.

Non-linear development of brain morphometry in child and adolescent offspring of individuals with bipolar disorder or schizophrenia

Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at increased risk of developing psychopathology. Structural brain alterations have been found in child and adolescent offspring of patients with bipolar disorder and schizophrenia, but the developmental trajectories of brain anatomy in this high-familial-risk population are still unclear. 300 T1-weighted scans were obtained of 187 offspring of at least one parent diagnosed with bipolar disorder (n=80) or schizophrenia (n=53) and offspring of parents without severe mental illness (n=54). The age range was 8 to 23 years old; 113 offspring underwent two scans. Global brain measures and regional cortical thickness and surface area were computed. A generalized additive mixed model was used to capture non-linear age trajectories. Offspring of parents with schizophrenia had smaller total brain volume than offspring of parents with bipolar disorder (d=-0.20, p=0.004) and control offspring (d=-0.22, p=0.005) and lower mean cortical thickness than control offspring (d=-0.23, p<0.001). Offspring of parents with schizophrenia showed differential age trajectories of mean cortical thickness and cerebral white matter volume compared with control offspring (both p's=0.003). Regionally, offspring of parents with schizophrenia had a significantly different trajectory of cortical thickness in the middle temporal gyrus versus control offspring (p<0.001) and bipolar disorder offspring (p=0.001), which was no longer significant after correcting for mean cortical thickness. These findings suggest that particularly familial high risk of schizophrenia is related to reductions and deviating developmental trajectories of global brain structure measures, which were not driven by specific regions.

Enhancing Early Diagnosis of Bipolar Disorder in Adolescents Through Multimodal Neuroimaging

BACKGROUND

Bipolar disorder (BD), a severe neuropsychiatric condition, often appears during adolescence. Traditional diagnostic methods, which primarily rely on clinical interviews and single-modal magnetic resonance imaging (MRI) techniques, may have limitations in accuracy. This study aimed to improve adolescent BD diagnosis by integrating behavioral assessments with multimodal MRI. We hypothesized that this combination would enhance diagnostic accuracy for at-risk adolescents.

METHODS

A retrospective cohort of 309 participants, including patients with BD, offspring of patients with BD (with and without subthreshold symptoms), non-BD offspring with subthreshold symptoms, and healthy control participants, was analyzed. Behavioral attributes were integrated with MRI features from T1-weighted, resting-state functional MRI, and diffusion tensor imaging. Three diagnostic models were developed using GLMNET multinomial regression: a clinical diagnosis model based on behavioral attributes, an MRI-based model, and a comprehensive model integrating both datasets.

RESULTS

The comprehensive model achieved a prediction accuracy of 0.83 (95% CI, 0.72-0.92), significantly higher than the clinical (0.75) and MRI-based (0.65) models. Validation with an external cohort showed high accuracy (0.89, area under the curve = 0.95). Structural equation modeling revealed that clinical diagnosis (β = 0.487, p < .0001), parental BD history (β = -0.380, p < .0001), and global function (β = 0.578, p < .0001) significantly affected brain health, while psychiatric symptoms showed only a marginal influence (β = -0.112, p = .056).

CONCLUSIONS

This study highlights the value of integrating multimodal MRI with behavioral assessments for early diagnosis in at-risk adolescents. Combining neuroimaging enables more accurate patient subgroup distinctions, facilitating timely interventions and improving health outcomes. Our findings suggest a paradigm shift in BD diagnostics, advocating for incorporating advanced imaging techniques in routine evaluations.

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC

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.

CSMD1 regulates brain complement activity and circuit development

Complement proteins facilitate synaptic elimination during neurodevelopmental pruning, but neural complement regulation is not well understood. CUB and Sushi Multiple Domains 1 (CSMD1) can regulate complement activity in vitro, is expressed in the brain, and is associated with increased schizophrenia risk. Beyond this, little is known about CSMD1 including whether it regulates complement activity in the brain or otherwise plays a role in neurodevelopment. We used biochemical, immunohistochemical, and proteomic techniques to examine the regional, cellular, and subcellular distribution as well as protein interactions of CSMD1 in the brain. To evaluate whether CSMD1 is involved in complement-mediated synapse elimination, we examined Csmd1-knockout mice and CSMD1-knockout human stem cell-derived neurons. We interrogated synapse and circuit development of the mouse visual thalamus, a process that involves complement pathway activity. We also quantified complement deposition on synapses in mouse visual thalamus and on cultured human neurons. Finally, we assessed uptake of synaptosomes by cultured microglia. We found that CSMD1 is present at synapses and interacts with complement proteins in the brain. Mice lacking Csmd1 displayed increased levels of complement component C3, an increased colocalization of C3 with presynaptic terminals, fewer retinogeniculate synapses, and aberrant segregation of eye-specific retinal inputs to the visual thalamus during the critical period of complement-dependent refinement of this circuit. Loss of CSMD1 in vivo enhanced synaptosome engulfment by microglia in vitro, and this effect was dependent on activity of the microglial complement receptor, CR3. Finally, human stem cell-derived neurons lacking CSMD1 were more vulnerable to complement deposition. These data suggest that CSMD1 can function as a regulator of complement-mediated synapse elimination in the brain during development.

The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Schizophrenia: from neurochemistry to circuits, symptoms and treatments

Schizophrenia is a leading cause of global disability. Current pharmacotherapy for the disease predominantly uses one mechanism - dopamine D2 receptor blockade - but often shows limited efficacy and poor tolerability. These limitations highlight the need to better understand the aetiology of the disease to aid the development of alternative therapeutic approaches. Here, we review the latest meta-analyses and other findings on the neurobiology of prodromal, first-episode and chronic schizophrenia, and the link to psychotic symptoms, focusing on imaging evidence from people with the disorder. This evidence demonstrates regionally specific neurotransmitter alterations, including higher glutamate and dopamine measures in the basal ganglia, and lower glutamate, dopamine and γ-aminobutyric acid (GABA) levels in cortical regions, particularly the frontal cortex, relative to healthy individuals. We consider how dysfunction in cortico-thalamo-striatal-midbrain circuits might alter brain information processing to underlie psychotic symptoms. Finally, we discuss the implications of these findings for developing new, mechanistically based treatments and precision medicine for psychotic symptoms, as well as negative and cognitive symptoms.

Large-Scale Neuroimaging of Mental Illness

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

Functional Alterations in Patients with Bipolar Disorder and Their Unaffected First-Degree Relatives: Insight from Genetic, Epidemiological, and Neuroimaging Data

Bipolar disorder (BD) profoundly affects cognitive and psychosocial functioning, leading to a significant illness burden on patients and their families. Genetic factors are predominant in the onset of bipolar disorder and functional impairments. This disorder exhibits a strong family aggregation, with heritability estimates reaching up to 80%. Individuals with BD often experience impaired functioning, especially in significant areas such as physical performance, sleep, cognition, interpersonal interactions, socioeconomic status, family and marital relationships, work and school performance, well-being, and life expectancy. However, patients with different subtypes exhibit significant heterogeneity in social functioning, cognition, and creativity levels. There are notable differences in psychosocial and cognitive function in their unaffected first-degree relatives (UFR) who do not suffer but may carry susceptibility genes compared to healthy control (HC) without a family history. The observations indicate common genetic structures between BD patients and their UFR, which results in varying degrees of functional abnormalities. Therefore, this article mainly provides evidence on cognition, creativity, and psychosocial functioning in patients with BD and their UFR to provide a more comprehensive understanding of this critical topic in the field of BD. By integrating various findings, including clinical data and neuroimaging studies, our article aims to provide insights and valuable information for a deeper exploration of the pathogenesis of BD and the development of more targeted therapeutic strategies in the future.

Cortical and subcortical structural differences in psychostimulant-free ADHD youth with and without a family history of bipolar I disorder: a cross-sectional morphometric comparison

Although attention-deficit/hyperactivity disorder (ADHD) and a family history of bipolar I disorder (BD) are associated with increased risk for developing BD, their neuroanatomical substrates remain poorly understood. This study compared cortical and subcortical gray matter morphology in psychostimulant-free ADHD youth with and without a first-degree relative with BD and typically developing healthy controls. ADHD youth (ages 10-18 years) with ('high-risk', HR) or without ('low-risk', LR) a first-degree relative with BD and healthy comparison youth (HC) were enrolled. High-resolution 3D T1-weighted images were acquired using a Philips 3.0 T MR scanner. The FreeSurfer image analysis suite was used to measure cortical thickness, surface area, and subcortical volumes. A general linear model evaluated group differences in MRI features with age and sex as covariates, and exploratory correlational analyses evaluated associations with symptom ratings. A total of n = 142 youth (mean age: 14.16 ± 2.54 years, 35.9% female) were included in the analysis (HC, n = 48; LR, n = 49; HR, n = 45). The HR group exhibited a more severe symptom profile, including higher mania and dysregulation scores, compared to the LR group. For subcortical volumes, the HR group exhibited smaller bilateral thalamic, hippocampal, and left caudate nucleus volumes compared to both LR and HC, and smaller right caudate nucleus compared with LR. No differences were found between LR and HC groups. For cortical surface area, the HR group exhibited lower parietal and temporal surface area compared with HC and LR, and lower orbitofrontal and superior frontal surface area compared to LR. The HR group exhibited lower left anterior cingulate surface area compared with HC. LR participants exhibited greater right pars opercularis surface area compared with the HC. Some cortical alterations correlated with symptom severity ratings. These findings suggest that ADHD in youth with a BD family history is associated with a more a severe symptom profile and a neuroanatomical phenotype that distinguishes it from ADHD without a BD family history.

Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis

BACKGROUND AND HYPOTHESIS

Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes.

STUDY DESIGN

We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score.

STUDY RESULTS

After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores.

CONCLUSIONS

Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.

Cerebellar morphological differences and associations with extrinsic factors in bipolar disorder type I

BACKGROUND

The neural underpinnings of bipolar disorder (BD) remain poorly understood. The cerebellum is ideally positioned to modulate emotional regulation circuitry yet has been understudied in BD. Literature suggests differences in cerebellar activity and metabolism in BD, however findings on structural differences remain contradictory. Potential reasons include combining BD subtypes, small sample sizes, and potential moderators such as genetics, adverse childhood experiences (ACEs), and pharmacotherapy.

METHODS

We collected 3 T MRI scans from participants with (N = 131) and without (N = 81) BD type I, as well as blood and questionnaires. We assessed differences in cerebellar volumes and explored potentially influential factors.

RESULTS

The cerebellar cortex was smaller bilaterally in participants with BD. Polygenic propensity score did not predict any cerebellar volumes, suggesting that non-genetic factors may have greater influence on the cerebellar volume difference we observed in BD. Proportionate cerebellar white matter volumes appeared larger with more ACEs, but this may result from reduced ICV. Time from onset and symptom burden were not associated with cerebellar volumes. Finally, taking sedatives was associated with larger cerebellar white matter and non-significantly larger cortical volume.

LIMITATIONS

This study was cross-sectional, limiting interpretation of possible mechanisms. Most of our participants were White, which could limit the generalizability. Additionally, we did not account for potential polypharmacy interactions.

CONCLUSIONS

These findings suggest that external factors, such as sedatives and childhood experiences, may influence cerebellum structure in BD and may mask underlying differences. Accounting for such variables may be critical for consistent findings in future studies.

Specificity of associations between parental psychopathology and offspring brain structure

Multiple forms of parental psychopathology have been associated with differences in subcortical brain volume. However, few studies have considered the role of comorbidity. Here, we examine if alterations in child subcortical brain structure are specific to parental depression, anxiety, mania, or alcohol/substance use parental psychopathology, common across these disorders, or altered by a history of multiple disorders. We examined 6581 children aged 9 to 10 years old from the ABCD study with no history of mental disorders. We found several significant interactions such that the effects of a parental history of depression, anxiety, and substance use problems on amygdala and striatal volumes were moderated by comorbid parental history of another disorder. Interactions tended to suggest smaller volumes in the presence of a comorbid disorder. However, effect sizes were small, and no associations remained significant after correcting for multiple comparisons. Results suggest that associations between familial risk for psychopathology and offspring brain structure in 9-10-year-olds are modest, and relationships that do exist tend to implicate the amygdala and striatal regions and are moderated by a comorbid parental psychopathology history. Several methodological factors, including controlling for intracranial volume and other forms of parental psychopathology and excluding child psychopathology, likely contribute to inconsistencies in the literature.

The Risk for Schizophrenia-Bipolar Spectrum: Does the Apple Fall Close to the Tree? A Narrative Review

Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric disorders that share clinical features and several risk genes. Important information about their genetic underpinnings arises from intermediate phenotypes (IPs), quantifiable biological traits that are more prevalent in unaffected relatives (RELs) of patients compared to the general population and co-segregate with the disorders. Within IPs, neuropsychological functions and neuroimaging measures have the potential to provide useful insight into the pathophysiology of SCZ and BD. In this context, the present narrative review provides a comprehensive overview of the available evidence on deficits in neuropsychological functions and neuroimaging alterations in unaffected relatives of SCZ (SCZ-RELs) and BD (BD-RELs). Overall, deficits in cognitive functions including intelligence, memory, attention, executive functions, and social cognition could be considered IPs for SCZ. Although the picture for cognitive alterations in BD-RELs is less defined, BD-RELs seem to present worse performances compared to controls in executive functioning, including adaptable thinking, planning, self-monitoring, self-control, and working memory. Among neuroimaging markers, SCZ-RELs appear to be characterized by structural and functional alterations in the cortico-striatal-thalamic network, while BD risk seems to be associated with abnormalities in the prefrontal, temporal, thalamic, and limbic regions. In conclusion, SCZ-RELs and BD-RELs present a pattern of cognitive and neuroimaging alterations that lie between patients and healthy individuals. Similar abnormalities in SCZ-RELs and BD-RELs may be the phenotypic expression of the shared genetic mechanisms underlying both disorders, while the specificities in neuropsychological and neuroimaging profiles may be associated with the differential symptom expression in the two disorders.

A Review of Potential Neuroimaging Biomarkers of Schizophrenia-Risk

The risk for developing schizophrenia is increased among first-degree relatives of those with psychotic disorders, but the risk is even higher in those meeting established criteria for clinical high risk (CHR), a clinical construct most often comprising of attenuated psychotic experiences. Conversion to psychosis among CHR youth has been reported to be about 15-35% over three years. Accurately identifying individuals whose psychotic symptoms will worsen would facilitate earlier intervention, but this has been difficult to do using behavior measures alone. Brain-based risk markers have the potential to improve the accuracy of predicting outcomes in CHR youth. This narrative review provides an overview of neuroimaging studies used to investigate psychosis risk, including studies involving structural, functional, and diffusion imaging, functional connectivity, positron emission tomography, arterial spin labeling, magnetic resonance spectroscopy, and multi-modality approaches. We present findings separately in those observed in the CHR state and those associated with psychosis progression or resilience. Finally, we discuss future research directions that could improve clinical care for those at high risk for developing psychotic disorders.

Associations between N-Acetylaspartate and white matter integrity in individuals with schizophrenia and unaffected relatives

Compromised white matter has been reported in schizophrenia; however, few studies have investigated neurochemical abnormalities underlying microstructural differences. N-acetylaspartate (NAA) is used to synthesize myelin and is often reduced in persons with schizophrenia (PSZ) and their unaffected first-degree relatives (REL). Low levels of NAA could affect white matter by preventing the synthesis or repair of myelin. We used magnetic resonance spectroscopy and diffusion tensor imaging to investigate the relationship between NAA and white matter integrity in PSZ. REL were included to examine whether putative relationships are associated with symptom expression or illness liability. 52 controls, 23 REL and 25 PSZ underwent 7T proton magnetic resonance spectroscopy and/or 3T diffusion tensor imaging. NAA in the visual cortex and basal ganglia were measured and compared across groups. Diffusivity measures were compared across groups using tract-based spatial statistics and related to NAA concentrations. Visual cortex NAA was significantly reduced in PSZ compared to controls. White matter integrity did not differ between groups. Reduced cortical and subcortical NAA were associated with diffusivity measures of poor white matter microstructure. These data suggest that levels of neural NAA may be related to white matter integrity similarly across individuals with schizophrenia, those at genetic risk, and controls.

Genetic associations between bipolar disorder and brain structural phenotypes

Patients with bipolar disorder (BD) and their first-degree relatives exhibit alterations in brain volume and cortical structure, whereas the underlying genetic mechanisms remain unclear. In this study, based on the published genome-wide association studies (GWAS), the extent of polygenic overlap between BD and 15 brain structural phenotypes was investigated using linkage disequilibrium score regression and MiXeR tool, and the shared genomic loci were discovered by conjunctional false discovery rate (conjFDR) and expression quantitative trait loci (eQTL) analyses. MiXeR estimated the overall measure of polygenic overlap between BD and brain structural phenotypes as 4-53% on a 0-100% scale (as quantified by the Dice coefficient). Subsequent conjFDR analyses identified 54 independent loci (71 risk single-nucleotide polymorphisms) jointly associated with BD and brain structural phenotypes with a conjFDR < 0.05, among which 33 were novel that had not been reported in the previous BD GWAS. Follow-up eQTL analyses in respective brain regions both confirmed well-known risk genes (e.g. CACNA1C, NEK4, GNL3, MAPK3) and discovered novel risk genes (e.g. LIMK2 and CAMK2N2). This study indicates a substantial shared genetic basis between BD and brain structural phenotypes, and provides novel insights into the developmental origin of BD and related biological mechanisms.

Accuracy of the Arabic HCL - 32 and MDQ in detecting patients with bipolar disorder

BACKGROUND

Studies about the two most used and validated instruments for the early detection of Bipolar Disorder (BD), the 32 - item Hypomania Checklist (HCL - 32) and the Mood Disorder Questionnaire (MDQ), are scarce in non-Western countries. This study aimed to explore the reliability, factor structure, and criterion validity of their Arabic versions in a sample of Tunisian patients diagnosed with mood disorders.

METHODS

The sample included 59 patients with BD, 86 with unipolar Major Depressive Disorder (MDD) and 281 controls. Confirmatory factor analysis was applied to show that a single global score was an appropriate summary measure of the screeners in the sample. Receiver Operating Characteristic analysis was used to assess the capacity of the translated screeners to distinguish patients with BD from those with MDD and controls.

RESULTS

Reliability was good for both tools in all samples. The bifactor implementation of the most reported two-factor model had the best fit for both screeners. Both were able to distinguish patients diagnosed with BD from putatively healthy controls, and equally able to distinguish patients diagnosed with BD from patients with MDD.

CONCLUSION

Both screeners work best in excluding the presence of BD in patients with MDD, which is an advantage in deciding whether or not to prescribe an antidepressant.

Neuroimaging in schizophrenia: an overview of findings and their implications for synaptic changes

Over the last five decades, a large body of evidence has accrued for structural and metabolic brain alterations in schizophrenia. Here we provide an overview of these findings, focusing on measures that have traditionally been thought to reflect synaptic spine density or synaptic activity and that are relevant for understanding if there is lower synaptic density in the disorder. We conducted literature searches to identify meta-analyses or other relevant studies in patients with chronic or first-episode schizophrenia, or in people at high genetic or clinical risk for psychosis. We identified 18 meta-analyses including over 50,000 subjects in total, covering: structural MRI measures of gyrification index, grey matter volume, grey matter density and cortical thickness, neurite orientation dispersion and density imaging, PET imaging of regional glucose metabolism and magnetic resonance spectroscopy measures of N-acetylaspartate. We also review preclinical evidence on the relationship between ex vivo synaptic measures and structural MRI imaging, and PET imaging of synaptic protein 2A (SV2A). These studies show that schizophrenia is associated with lower grey matter volumes and cortical thickness, accelerated grey matter loss over time, abnormal gyrification patterns, and lower regional SV2A levels and metabolic markers in comparison to controls (effect sizes from ~ -0.11 to -1.0). Key regions affected include frontal, anterior cingulate and temporal cortices and the hippocampi. We identify several limitations for the interpretation of these findings in terms of understanding synaptic alterations. Nevertheless, taken with post-mortem findings, they suggest that schizophrenia is associated with lower synaptic density in some brain regions. However, there are several gaps in evidence, in particular whether SV2A findings generalise to other cohorts.

Neurocognitive Correlates of Cerebellar Volumetric Alterations in Youth with Pediatric Bipolar Spectrum Disorders and Bipolar Offspring

BACKGROUND

Emerging evidence points towards the involvement of the cerebellum in the processing of emotions and pathophysiology of mood disorders. However, cerebellar and related cognitive alterations in youth with pediatric bipolar disorder (PBD) and those at high risk to develop the disorder, such as bipolar offspring (BD-OFF) are not clearly defined.

OBJECTIVE

To investigate cerebellar gray and white matter volumes, cognition, and their relationship in youth with PBD and BD-OFF.

METHODS

Thirty youth (7 to 17 years, inclusive) with PBD, 30 BD-OFF and 40 healthy controls (HC) were recruited. Study participants underwent a computer-based cognitive battery assessing affective processing, executive function, attention, psychomotor speed, and learning. Three-tesla MRI scan was performed to assess cerebellar white and gray matter volumes. Cerebellar segmentation was performed with FreeSurfer. Statistical analyses include between-group differences in cognitive domains, cerebellar gray, and white matter volumes. Relationships between cerebellar volumes and cognitive domains were examined.

RESULTS

Youth with PBD showed greater cerebellar gray matter volumes than both BD-OFF and HC, whereas no differences were present between BD-OFF and HC. Both youth with PBD and BD-OFF showed altered processing of negative emotions and a bias towards positive emotions. In youth with PBD and BD-OFF, greater impairment in the processing of emotions correlated with greater cerebellar gray matter volumes.

CONCLUSION

The present findings corroborate hypotheses on cerebellar involvement in the processing of emotions and the pathophysiology of PBD. The presence of cerebellar dysfunction in BD-OFF is unclear.

Clinical and cortical similarities identified between bipolar disorder I and schizophrenia: A multivariate approach

BACKGROUND

Structural neuroimaging studies have identified similarities in the brains of individuals diagnosed with schizophrenia (SZ) and bipolar I disorder (BP), with overlap in regions of gray matter (GM) deficits between the two disorders. Recent studies have also shown that the symptom phenotypes associated with SZ and BP may allow for a more precise categorization than the current diagnostic criteria. In this study, we sought to identify GM alterations that were unique to each disorder and whether those alterations were also related to unique symptom profiles.

MATERIALS AND METHODS

We analyzed the GM patterns and clinical symptom presentations using independent component analysis (ICA), hierarchical clustering, and n-way biclustering in a large (N ∼ 3,000), merged dataset of neuroimaging data from healthy volunteers (HV), and individuals with either SZ or BP.

RESULTS

Component A showed a SZ and BP < HV GM pattern in the bilateral insula and cingulate gyrus. Component B showed a SZ and BP < HV GM pattern in the cerebellum and vermis. There were no significant differences between diagnostic groups in these components. Component C showed a SZ < HV and BP GM pattern bilaterally in the temporal poles. Hierarchical clustering of the PANSS scores and the ICA components did not yield new subgroups. N-way biclustering identified three unique subgroups of individuals within the sample that mapped onto different combinations of ICA components and symptom profiles categorized by the PANSS but no distinct diagnostic group differences.

CONCLUSION

These multivariate results show that diagnostic boundaries are not clearly related to structural differences or distinct symptom profiles. Our findings add support that (1) BP tend to have less severe symptom profiles when compared to SZ on the PANSS without a clear distinction, and (2) all the gray matter alterations follow the pattern of SZ < BP < HV without a clear distinction between SZ and BP.

Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders

Observational studies have reported the correlations between brain imaging-derived phenotypes (IDPs) and psychiatric disorders; however, whether the relationships are causal is uncertain. We conducted bidirectional two-sample Mendelian randomization (MR) analyses to explore the causalities between 587 reliable IDPs (N = 33,224 individuals) and 10 psychiatric disorders (N = 9,725 to 161,405). We identified nine IDPs for which there was evidence of a causal influence on risk of schizophrenia, anorexia nervosa and bipolar disorder. For example, 1 s.d. increase in the orientation dispersion index of the forceps major was associated with 32% lower odds of schizophrenia risk. Reverse MR indicated that only genetically predicted schizophrenia was positively associated with two IDPs, the cortical surface area and the volume of the right pars orbitalis. We established the BrainMR database ( http://www.bigc.online/BrainMR/ ) to share our results. Our findings provide potential strategies for the prediction and intervention for psychiatric disorder risk at the brain-imaging level.

Neural Correlates of the Risk for Schizophrenia and Bipolar Disorder: A Meta-analysis of Structural and Functional Neuroimaging Studies

BACKGROUND

Clinical features and genetics overlap in schizophrenia (SCZ) and bipolar disorder (BD). Identifying brain alterations associated with genetic vulnerability for SCZ and BD could help to discover intermediate phenotypes, quantifiable biological traits with greater prevalence in unaffected relatives (RELs), and early recognition biomarkers in ultrahigh risk populations. However, a comprehensive meta-analysis of structural and functional magnetic resonance imaging (MRI) studies examining relatives of patients with SCZ and BD has not been performed yet.

METHODS

We systematically searched PubMed, Scopus, and Web of Science for structural and functional MRI studies investigating relatives and healthy control subjects. A total of 230 eligible neuroimaging studies (6274 SCZ-RELs, 1900 BD-RELs, 10,789 healthy control subjects) were identified. We conducted coordinate-based activation likelihood estimation meta-analyses on 26 structural MRI and 81 functional MRI investigations, including stratification by task type. We also meta-analyzed regional and global volumetric changes. Finally, we performed a meta-analysis of all MRI studies combined.

RESULTS

Reduced thalamic volume was present in both SCZ and BD RELs. Moreover, SCZ-RELs showed alterations in corticostriatal-thalamic networks, spanning the dorsolateral prefrontal cortex and temporal regions, while BD-RELs showed altered thalamocortical and limbic regions, including the ventrolateral prefrontal, superior parietal, and medial temporal cortices, with frontoparietal alterations in RELs of BD type I.

CONCLUSIONS

Familiarity for SCZ and BD is associated with alterations in the thalamocortical circuits, which may be the expression of the shared genetic mechanism underlying both disorders. Furthermore, the involvement of different prefrontocortical and temporal nodes may be associated with a differential symptom expression in the two disorders.

Mismatch negativity and P3a amplitude in children with familial high risk of schizophrenia or bipolar disorder - A Danish register-based EEG study

BACKGROUND

Infrequent deviants in a rapid sequence of sounds elicit a negative cortical potential over the frontocentral midline (mismatch negativity, MMN) followed by a positive deflection (P3a). Both cortical potentials are consistently attenuated in patients with schizophrenia (SZ), and, to a lesser degree, in patients with bipolar disorder (BP).

OBJECTIVE

Since it is unclear when MMN and P3a deficits arise relative to the emergence of symptoms, we examined whether MMN and P3a alterations are already detectable in children with familial high risk.

METHODS

Using 128-channel electroencephalography, we recorded auditory MMN and P3a evoked by a deviation in sound duration, frequency, or both in 51 children with familial high-risk for SZ (FHR-SZ), 41 children with familial high-risk for BP (FHR-BP), and 39 population-based children (PBC) at a mean age of 12.10.

RESULTS

MMN amplitude evoked by a duration deviant was larger in children with FHR-BP compared to PBC and FHR-SZ. P3a amplitude in response to a duration ∗ frequency deviant was larger in children with FHR-BP compared to children with FHR-SZ, but not compared to PBC. MMN- and P3a-peak latency did not differ between groups.

CONCLUSIONS

At an age of around 12 years, children with FHR-BP display enhanced neural sensitivity to change detection of duration deviants, while FHR-SZ showed a normal response pattern. Longitudinal recordings in high-risk children during adolescence are required to elucidate the temporal trajectories of MMN and P3a responses and how they relate to the emergence of first clinical symptoms in SZ and BP.

A systematic review and meta-analysis of structural and functional brain alterations in individuals with genetic and clinical high-risk for psychosis and bipolar disorder

Neuroimaging findings in people at either genetic risk or at clinical high-risk for psychosis (CHR-P) or bipolar disorder (CHR-B) remain unclear. A meta-analytic review of whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies in individuals with genetic risk or CHR-P or CHR-B and controls identified 94 datasets (N = 7942). Notwithstanding no significant findings were observed following adjustment for multiple comparisons, several findings were noted at a more liberal threshold. Subjects at genetic risk for schizophrenia or bipolar disorder or at CHR-P exhibited lower gray matter (GM) volumes in the gyrus rectus (Hedges' g = -0.19). Genetic risk for psychosis was associated with GM reductions in the right cerebellum and left amygdala. CHR-P was associated with decreased GM volumes in the frontal superior gyrus and hypoactivation in the right precuneus, the superior frontal gyrus and the right inferior frontal gyrus. Genetic and CHR-P were associated with small structural and functional alterations involving regions implicated in psychosis. Further neuroimaging studies in individuals with genetic or CHR-B are warranted.

Retinal changes in bipolar disorder as an endophenotype candidate: Comparison of OCT-detected retinal changes in patients, siblings, and healthy controls

Optical coherence tomography (OCT) is a non-invasive imaging technique that detects retinal changes reflecting neurodegeneration. In recent studies in patients with bipolar disorder (BD) abnormal OCT findings have shown. In this study, we aimed to investigate the retinal changes in BD patients and their healthy siblings (HS) by comparing them with the healthy control (HC) group and to explore these findings as potential endophenotype candidates. 31 patients with BD, 31 age-matched HSs and 46 HCs were included and peripapillary retinal nerve fiber layer (RNFL), ganglion cell layer (GCL)+inner plexiform layer (IPL) and macular volume (MV) thicknesses were measured by OCT. The relationship between disease severity parameters, functionality and OCT measurements in the patient group was also investigated. In results, the mean RNFL thicknesses did not differ between groups. All GCL+IPL thicknesses were found to be significantly lower in the patient and sibling groups compared to the HCs. GCL+IPL thicknesses were significantly correlated with functionality of patients and severity of the disorder. Our findings suggest that analysis of retinal layers with OCT may be a beneficial indicator to show neuronal changes in BD and GCL+IPL may be a suitable endophenotype candidate.

Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings

This review compares the main brain abnormalities in schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and 22q11.2 Deletion Syndrome (22q11DS) determined by ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium investigations. We obtained ranked effect sizes for subcortical volumes, regional cortical thickness, cortical surface area, and diffusion tensor imaging abnormalities, comparing each of these disorders relative to healthy controls. In addition, the studies report on significant associations between brain imaging metrics and disorder-related factors such as symptom severity and treatments. Visual comparison of effect size profiles shows that effect sizes are generally in the same direction and scale in severity with the disorders (in the order SZ > BD > MDD). The effect sizes for 22q11DS, a rare genetic syndrome that increases the risk for psychiatric disorders, appear to be much larger than for either of the complex psychiatric disorders. This is consistent with the idea of generally larger effects on the brain of rare compared to common genetic variants. Cortical thickness and surface area effect sizes for 22q11DS with psychosis compared to 22q11DS without psychosis are more similar to those of SZ and BD than those of MDD; a pattern not observed for subcortical brain structures and fractional anisotropy effect sizes. The observed similarities in effect size profiles for cortical measures across the psychiatric disorders mimic those observed for shared genetic variance between these disorders reported based on family and genetic studies and are consistent with shared genetic risk for SZ and BD and structural brain phenotypes.

Schizophrenia and Bipolar Polygenic Risk Scores in Relation to Intracranial Volume

Schizophrenia and bipolar disorder are neurodevelopmental disorders with overlapping symptoms and a shared genetic background. Deviations in intracranial volume (ICV)—a marker for neurodevelopment—differ between schizophrenia and bipolar disorder. Here, we investigated whether genetic risk for schizophrenia and bipolar disorder is related to ICV in the general population by using the UK Biobank data (n = 20,196). Polygenic risk scores for schizophrenia (SZ-PRS) and bipolar disorder (BD-PRS) were computed for 12 genome wide association study P-value thresholds (PT) for each individual and correlations with ICV were investigated. Partial correlations were performed at each PT to investigate whether disease specific genetic risk variants for schizophrenia and bipolar disorder show different relationships with ICV. ICV showed a negative correlation with SZ-PRS at PT ≥ 0.005 (r < −0.02, p < 0.005). ICV was not associated with BD-PRS; however, a positive correlation between BD-PRS and ICV at PT = 0.2 and PT = 0.4 (r = +0.02, p < 0.005) appeared when the genetic overlap between schizophrenia and bipolar disorder was accounted for. Despite small effect sizes, a higher load of schizophrenia risk genes is associated with a smaller ICV in the general population, while risk genes specific for bipolar disorder are correlated with a larger ICV. These findings suggest that schizophrenia and bipolar disorder risk genes, when accounting for the genetic overlap between both disorders, have opposite effects on early brain development.

Genetic and environment effects on structural neuroimaging endophenotype for bipolar disorder: a novel molecular approach

We investigated gene-environment effects on structural brain endophenotype in bipolar disorder (BD) using a novel method of combining polygenic risk scores with epigenetic signatures since traditional methods of examining the family history and trauma effects have significant limitations. The study enrolled 119 subjects, including 55 BD spectrum (BDS) subjects diagnosed with BD or major depressive disorder (MDD) with subthreshold BD symptoms and 64 non-BDS subjects comprising 32 MDD subjects without BD symptoms and 32 healthy subjects. The blood samples underwent genome-wide genotyping and methylation quantification. We derived polygenic risk score (PRS) and methylation profile score (MPS) as weighted summations of risk single nucleotide polymorphisms and methylation probes, respectively, which were considered as molecular measures of genetic and environmental risks for BD. Linear regression was used to relate PRS, MPS, and their interaction to 44 brain structure measures quantified from magnetic resonance imaging (MRI) on 47 BDS subjects, and the results were compared with those based on family history and childhood trauma. After multiplicity corrections using false discovery rate (FDR), MPS was found to be negatively associated with the volume of the medial geniculate thalamus (FDR = 0.059, partial R² = 0.208). Family history, trauma scale, and PRS were not associated with any brain measures. PRS and MPS show significant interactions on whole putamen (FDR = 0.09, partial R² = 0.337). No significant gene-environment interactions were identified for the family history and trauma scale. PRS and MPS generally explained greater proportions of variances of the brain measures (range of partial R² = [0.008, 0.337]) than the clinical risk factors (range = [0.004, 0.228]).

Asphyxia at birth affects brain structure in patients on the schizophrenia-bipolar disorder spectrum and healthy participants

BACKGROUND

Uncertainty exists about what causes brain structure alterations associated with schizophrenia (SZ) and bipolar disorder (BD). Whether a history of asphyxia-related obstetric complication (ASP) - a common but harmful condition for neural tissue - contributes to variations in adult brain structure is unclear. We investigated ASP and its relationship to intracranial (ICV), global brain volumes and regional cortical and subcortical structures.

METHODS

A total of 311 patients on the SZ - BD spectrum and 218 healthy control (HC) participants underwent structural magnetic resonance imaging. They were evaluated for ASP using prospective information obtained from the Medical Birth Registry of Norway.

RESULTS

In all groups, ASP was related to smaller ICV, total brain, white and gray matter volumes and total surface area, but not to cortical thickness. Smaller cortical surface areas were found across frontal, parietal, occipital, temporal and insular regions. Smaller hippocampal, amygdala, thalamus, caudate and putamen volumes were reported for all ASP subgroups. ASP effects did not survive ICV correction, except in the caudate, which remained significantly smaller in both patient ASP subgroups, but not in the HC.

CONCLUSIONS

Since ASP was associated with smaller brain volumes in all groups, the genetic risk of developing a severe mental illness, alone, cannot easily explain the smaller ICV. Only the smaller caudate volumes of ASP patients specifically suggest that injury from ASP can be related to disease development. Our findings give support for the ICV as a marker of aberrant neurodevelopment and ASP in the etiology of brain development in BD and SZ.

Differences in subcortical brain volumes among patients with schizophrenia and bipolar disorder and healthy controls

BACKGROUND

Patients with schizophrenia and bipolar disorder have an overlapping polygenic architecture and clinical similarities, although the 2 disorders are distinct diagnoses with clinical dissimilarities. It remains unclear whether there are specific differences in subcortical volumes between schizophrenia and bipolar disorder, and whether the subcortical differences are affected by any clinical characteristics. We investigated differences in subcortical volumes bilaterally among patients with schizophrenia, patients with bipolar disorder and healthy controls. We also investigated the influences of clinical characteristics on specific subcortical volumes in these patient groups.

METHODS

We collected 3 T T ₁-weighted MRI brain scans from 413 participants (157 with schizophrenia, 51 with bipolar disorder and 205 controls) with a single scanner at a single institute. We used FreeSurfer version 6.0 for processing the T ₁-weighted images to segment the following subcortical brain volumes: thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala and nucleus accumbens. Differences in the 7 subcortical volumes were investigated among the groups. We also evaluated correlations between subcortical volumes and clinical variables in these patient groups.

RESULTS

Of 7 subcortical regions, patients with schizophrenia had significantly smaller volumes in the left thalamus (Cohen d = -0.29, p = 5.83 × 10^-3), bilateral hippocampi (left, d = -0.36, p = 8.85 × 10^-4; right, d = -0.41, p = 1.15 × 10^-4) and left amygdala (d = -0.31, p = 4.02 × 10^-3) than controls. Compared with controls, patients with bipolar disorder had bilateral reductions only in the hippocampal volumes (left, d = -0.52, p = 1.12 × 10^-3; right, d = -0.58, p = 0.30 × 10^-4). We also found that patients with schizophrenia had significantly smaller volumes in the bilateral amygdalae (left, d = -0.43, p = 4.22 × 10^-3; right, d = -0.45, p = 4.56 × 10^-3) than patients with bipolar disorder. We did not find any significant volumetric differences in the other 6 subcortical structures between patient groups (p > 0.05). Smaller left amygdalar volumes were significantly correlated with younger onset age only in patients with schizophrenia (r = 0.22, p = 5.78 × 10^-3).

LIMITATIONS

We did not evaluate the differences in subcortical volumes between patients stratified based on clinical bipolar disorder subtype and a history of psychotic episodes because our sample size of patients with bipolar disorder was limited.

CONCLUSION

Our findings suggest that volumetric differences in the amygdala between patients with schizophrenia and those with bipolar disorder may be a putative biomarker for distinguishing 2 clinically similar diagnoses.

Genomic and neuroimaging approaches to bipolar disorder

BACKGROUND

To date, besides genome-wide association studies, a variety of other genetic analyses (e.g. polygenic risk scores, whole-exome sequencing and whole-genome sequencing) have been conducted, and a large amount of data has been gathered for investigating the involvement of common, rare and very rare types of DNA sequence variants in bipolar disorder. Also, non-invasive neuroimaging methods can be used to quantify changes in brain structure and function in patients with bipolar disorder.

AIMS

To provide a comprehensive assessment of genetic findings associated with bipolar disorder, based on the evaluation of different genomic approaches and neuroimaging studies.

METHOD

We conducted a PubMed search of all relevant literatures from the beginning to the present, by querying related search strings.

RESULTS

ANK3, CACNA1C, SYNE1, ODZ4 and TRANK1 are five genes that have been replicated as key gene candidates in bipolar disorder pathophysiology, through the investigated studies. The percentage of phenotypic variance explained by the identified variants is small (approximately 4.7%). Bipolar disorder polygenic risk scores are associated with other psychiatric phenotypes. The ENIGMA-BD studies show a replicable pattern of lower cortical thickness, altered white matter integrity and smaller subcortical volumes in bipolar disorder.

CONCLUSIONS

The low amount of explained phenotypic variance highlights the need for further large-scale investigations, especially among non-European populations, to achieve a more complete understanding of the genetic architecture of bipolar disorder and the missing heritability. Combining neuroimaging data with genetic data in large-scale studies might help researchers acquire a better knowledge of the engaged brain regions in bipolar disorder.

Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, p_FDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, p_spin = 0.024), but not BD (r = 0.166, p_spin = 0.205) or MDD (r = -0.274, p_spin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, p_spin = 0.006), BD (rho = -0.672, p_spin = 0.009), and MDD (rho = -0.692, p_spin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

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.

ENIGMA brain injury: Framework, challenges, and opportunities

Traumatic brain injury (TBI) is a major cause of disability worldwide, but the heterogeneous nature of TBI with respect to injury severity and health comorbidities make patient outcome difficult to predict. Injury severity accounts for only some of this variance, and a wide range of preinjury, injury-related, and postinjury factors may influence outcome, such as sex, socioeconomic status, injury mechanism, and social support. Neuroimaging research in this area has generally been limited by insufficient sample sizes. Additionally, development of reliable biomarkers of mild TBI or repeated subconcussive impacts has been slow, likely due, in part, to subtle effects of injury and the aforementioned variability. The ENIGMA Consortium has established a framework for global collaboration that has resulted in the largest-ever neuroimaging studies of multiple psychiatric and neurological disorders. Here we describe the organization, recent progress, and future goals of the Brain Injury working group.

A Possible White Matter Compensating Mechanism in the Brain of Relatives of People Affected by Psychosis Inferred from Repeated Long-Term DTI Scans

Background and Hypothesis

An existing model suggests that some brain features of relatives of people affected by psychosis can be distinguished from both the probands and a control group.  Such findings can be interpreted as representing a compensating mechanism.

Study Design

We studied white matter features using diffusion tensor imaging in a cohort of 82 people affected by psychosis, 122 of their first-degree relatives, and 89 control subjects that were scanned between two to three times with an interval of approximately 3 years between consecutive scans. We measured both fractional anisotropy and other standard diffusivity measures such as axial diffusivity. Additionally, we calculated standard connectivity measures such as path length based on probabilistic or deterministic tractography. Finally, by averaging the values of the different measures over the two or three consecutive scans, we studied epoch-averagely the difference between these three groups.

Study Results

For several tracts and several connectivity measures, the relatives showed distinct features from both the probands and the control groups. In those cases, the relatives did not necessarily score between the probands and the control group. An aggregate analysis in the form of a group-dependent score for the different modes of the analysis (e.g., for fractional anisotropy) supported this observation.

Conclusions

We interpret these results as evidence supporting a compensation mechanism in the brain of relatives that may be related to resilience that some of them exhibit in the face of the genetic risk they have for being affected by psychosis.

A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium

Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.

ENIGMA + COINSTAC: Improving Findability, Accessibility, Interoperability, and Re-usability

The FAIR principles, as applied to clinical and neuroimaging data, reflect the goal of making research products Findable, Accessible, Interoperable, and Reusable. The use of the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymized Computation (COINSTAC) platform in the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium combines the technological approach of decentralized analyses with the sociological approach of sharing data. In addition, ENIGMA + COINSTAC provides a platform to facilitate the use of machine-actionable data objects. We first present how ENIGMA and COINSTAC support the FAIR principles, and then showcase their integration with a decentralized meta-analysis of sex differences in negative symptom severity in schizophrenia, and finally present ongoing activities and plans to advance FAIR principles in ENIGMA + COINSTAC. ENIGMA and COINSTAC currently represent efforts toward improved Access, Interoperability, and Reusability. We highlight additional improvements needed in these areas, as well as future connections to other resources for expanded Findability.

Plasma fatty acid-binding protein 7 concentration correlates with depression/anxiety, cognition, and positive symptom in patients with schizophrenia

Because of the involvement of the brain in the pathophysiology of psychiatric disorders, obtaining information on the biochemical features that directly contribute to symptoms is challenging. The present study aimed to assess fatty acid-binding protein 7 (FABP7) expressed specifically in the brain and detectable in the peripheral blood and to investigate the correlation between blood FABP7 concentration and symptoms. We recruited 30, 29, and 35 patients with schizophrenia, bipolar disorder, and depression and evaluated using the Positive and Negative Syndrome Scale (PANSS), Young Mania Rating Scale (YMRS), and Hamilton Depression Rating Scale (HAMD-21), respectively. Plasma FABP7 concentrations correlated with PANSS scores (R² = 0.3305, p < 0.001) but not with other scales. In the analysis of the relationship between five dimensions of schizophrenia symptoms derived from the PANSS 5-factor model and measured plasma FABP7 concentrations, severities of depression/anxiety, cognition, and positive symptom were significantly correlated with plasma FABP7 concentrations. Further molecular investigation of the functional and kinetic analyses of FABP7 is necessary to understand the relationship of this protein with schizophrenia pathology. Nevertheless, the present study suggests that FABP7 can be a biological indicator reflecting the pathogenesis of schizophrenia and has potential applications as a biomarker for diagnosis and symptom assessment.

Effects of polygenic risk for suicide attempt and risky behavior on brain structure in young people with familial risk of bipolar disorder

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.

The psychosis human connectome project: An overview

Investigations within the Human Connectome Project have expanded to include studies focusing on brain disorders. This paper describes one of the investigations focused on psychotic psychopathology: The psychosis Human Connectome Project (P-HCP). The data collected as part of this project were multimodal and derived from clinical assessments of psychopathology, cognitive assessments, instrument-based motor assessments, blood specimens, and magnetic resonance imaging (MRI) data. The dataset will be made publicly available through the NIMH Data Archive. In this report we provide specific information on how the sample of participants was obtained and characterized and describe the experimental tasks and procedures used to probe neural functions involved in psychotic disorders that may also mark genetic liability for psychotic psychopathology. Our goal in this paper is to outline the data acquisition process so that researchers intending to use these publicly available data can plan their analyses. MRI data described in this paper are limited to data acquired at 3 Tesla. A companion paper describes the study's 7 Tesla image acquisition protocol in detail, which is focused on visual perceptual functions in psychotic psychopathology.

Morphometric Analysis of Structural MRI Using Schizophrenia Meta-analytic Priors Distinguish Patients from Controls in Two Independent Samples and in a Sample of Individuals With High Polygenic Risk

Schizophrenia (SCZ) is associated with structural brain changes, with considerable variation in the extent to which these cortical regions are influenced. We present a novel metric that summarises individual structural variation across the brain, while considering prior effect sizes, established via meta-analysis. We determine individual participant deviation from a within-sample-norm across structural MRI regions of interest (ROIs). For each participant, we weight the normalised deviation of each ROI by the effect size (Cohen's d) of the difference between SCZ/control for the corresponding ROI from the SCZ Enhancing Neuroimaging Genomics through Meta-Analysis working group. We generate a morphometric risk score (MRS) representing the average of these weighted deviations. We investigate if SCZ-MRS is elevated in a SCZ case/control sample (NCASE = 50; NCONTROL = 125), a replication sample (NCASE = 23; NCONTROL = 20) and a sample of asymptomatic young adults with extreme SCZ polygenic risk (NHIGH-SCZ-PRS = 95; NLOW-SCZ-PRS = 94). SCZ cases had higher SCZ-MRS than healthy controls in both samples (Study 1: β = 0.62, P < 0.001; Study 2: β = 0.81, P = 0.018). The high liability SCZ-PRS group also had a higher SCZ-MRS (Study 3: β = 0.29, P = 0.044). Furthermore, the SCZ-MRS was uniquely associated with SCZ status, but not attention-deficit hyperactivity disorder (ADHD), whereas an ADHD-MRS was linked to ADHD status, but not SCZ. This approach provides a promising solution when considering individual heterogeneity in SCZ-related brain alterations by identifying individual's patterns of structural brain-wide alterations.

Individuals at increased risk for development of bipolar disorder display structural alterations similar to people with manifest disease

In psychiatry, there has been a growing focus on identifying at-risk populations. For schizophrenia, these efforts have led to the development of early recognition and intervention measures. Despite a similar disease burden, the populations at risk of bipolar disorder have not been sufficiently characterized. Within the BipoLife consortium, we used magnetic resonance imaging (MRI) data from a multicenter study to assess structural gray matter alterations in N = 263 help-seeking individuals from seven study sites. We defined the risk using the EPIbipolar assessment tool as no-risk, low-risk, and high-risk and used a region-of-interest approach (ROI) based on the results of two large-scale multicenter studies of bipolar disorder by the ENIGMA working group. We detected significant differences in the thickness of the left pars opercularis (Cohen's d = 0.47, p = 0.024) between groups. The cortex was significantly thinner in high-risk individuals compared to those in the no-risk group (p = 0.011). We detected no differences in the hippocampal volume. Exploratory analyses revealed no significant differences in other cortical or subcortical regions. The thinner cortex in help-seeking individuals at risk of bipolar disorder is in line with previous findings in patients with the established disorder and corresponds to the region of the highest effect size in the ENIGMA study of cortical alterations. Structural alterations in prefrontal cortex might be a trait marker of bipolar risk. This is the largest structural MRI study of help-seeking individuals at increased risk of bipolar disorder.