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Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Background: Environmental modification of genetic information (epigenetics) is often invoked to explain interindividual differences in the phenotype of schizophrenia. In clinical practice, such variability is most prominent in the symptom profile and the treatment response. Epigenetic regulation of immune function is of particular interest, given the therapeutic relevance of this mechanism in schizophrenia. Methods: We analyzed the DNA methylation data of immune-relevant genes in patients with schizophrenia whose disease duration was less than 3 years, with previous lifetime antipsychotic treatment of no more than 2 weeks total. Results: A total of 441 patients met the inclusion criteria. Core symptoms were consistently associated with 206 methylation positions, many of which had previously been implicated in inflammatory responses. Of these, 24 methylation positions were located either in regulatory regions or near the CpG islands of 20 genes, including the SRC gene, which is a key player in glutamatergic signalling. These symptom-associated immune genes were enriched in neuronal development functions, such as neuronal migration and glutamatergic synapse. Compared with using only clinical information (including scores on the Positive and Negative Syndrome Scale), integrating methylation data into the model significantly improved the predictive ability (as indicated by area under the curve) for response to 8 weeks of antipsychotic treatment. Limitations: We focused on a small number of methylation probes (immune-centred search) and lacked nutritional data and direct brain-based measures. Conclusion: Epigenetic modifications of the immune system are associated with symptom severity at onset and subsequent treatment response in schizophrenia., Introduction Schizophrenia is characterized by its heterogeneity in both clinical symptoms and treatment response. It affects 24 million individuals around the world, resulting in substantially reduced life expectancy and a [...]

Background: A growing body of neuroimaging studies has reported common neural abnormalities among mental disorders in adults. However, it is unclear whether the distinct disorder-specific mechanisms operate during adolescence despite the overlap among disorders. Methods: We studied a large cohort of more than 11 000 preadolescent (age 9-10 yr) children from the Adolescent Brain and Cognitive Development cohort. We adopted a regrouping approach to compare cortical thickness (CT) alterations and longitudinal changes between healthy controls (n = 4041) and externalizing (n = 1182), internalizing (n = 1959) and thought disorder (n = 347) groups. Genome-wide association study (GWAS) was performed on regional CT across 4468 unrelated European youth. Results: Youth with externalizing or internalizing disorders exhibited increased regional CT compared with controls. Externalizing (p = 8 x [10.sup.-4], Cohen d = 0.10) and internalizing disorders (p = 2 x [10.sup.-3], Cohen d = 0.08) shared thicker CT in the left pars opercularis. The somatosensory and the primary auditory cortex were uniquely affected in externalizing disorders, whereas the primary motor cortex and higher-order visual association areas were uniquely affected in internalizing disorders. Only youth with externalizing disorders showed decelerated cortical thinning from age 10-12 years. The GWAS found 59 genome-wide significant associated genetic variants across these regions. Cortical thickness in common regions was associated with glutamatergic neurons, while internalizing-specific regional CT was associated with astrocytes, oligodendrocyte progenitor cells and GABAergic neurons. Limitations: The sample size of the GWAS was relatively small. Conclusion: Our study provides strong evidence for the presence of specificity in CT, developmental trajectories and underlying genetic underpinnings among externalizing and internalizing disorders during early adolescence. Our results support the neurobiological validity of the regrouping approach that could supplement the use of a dimensional approach in future clinical practice., Introduction During the past 2 decades, long-standing diagnostic categories of mental disorders, based on the Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD), have [...]

It is an error to see only illness in abnormality.--Lev Vygotsky (1) Considerable variations exist in the clinical presentation of psychiatric disorders. For any given diagnostic construct, there are several [...]

Open science provides a compelling framework for accelerating global collaborations and enabling discoveries to understand and treat mental health disorders. Herein, we discuss the advantages and obstacles to adopting open science in mental health research, considering the particularities of sensitive and diverse data types, the potential of co-designing projects with research participants and the opportunity of amplifying open science by integration with mental health care. We present a practical example of how this landscape may be navigated to adopt open science across an entire research centre, in 5 steps, namely leadership committing to open science; finding models, resources and allies; identifying needs; defining open science principles; and putting principles into practice. We derive lessons learned that can be built upon by researchers and research organizations joining the open science movement in mental health., Introduction Mental health disorders present an incredibly complex set of unsolved issues, both in terms of understanding their underlying causes and in developing the appropriate interventions to benefit each health [...]

The information in this column is not intended as a definitive treatment strategy but as a suggested approach for clinicians treating patients with similar histories. Individual cases may vary and [...]

Background: Working-memory deficit is associated with aberrant degree distribution of the brain connectome in schizophrenia. However, the brain neural mechanism underlying the degree redistribution pattern in schizophrenia is still uncertain. Methods: We examined the functional degree distribution of the connectome in 81 patients with schizophrenia and 77 healthy controls across different working-memory loads during an n-back task. We tested the associations between altered degree distribution and clinical symptoms, and we conducted functional connectivity analyses to investigate the neural mechanism underlying altered degree distribution. We repeated these analyses in a second independent data set of 96 participants. In the second data set, we employed machine-learning analysis to study whether the degree distribution pattern of one data set could be used to discriminate between patients with schizophrenia and controls in the other data set. Results: Patients with schizophrenia showed decreased centrality in the dorsal posterior cingulate cortex (dPCC) for the '2-back versus 0-back' contrast compared to healthy controls. The dPCC centrality pattern across all working-memory loads was an inverted U shape, with a left shift of this pattern in patients with schizophrenia. This reduced centrality was correlated with the severity of delusions and related to reduced functional connectivity between the dPCC and the dorsal precuneus. We replicated these results with the second data set, and the machine-learning analyses achieved an accuracy level of 71%. Limitations: We used a limited n-back paradigm that precluded the examination of higher working-memory loads. Conclusion: Schizophrenia is characterized by a load-dependent reduction of centrality in the dPCC, related to the severity of delusions. We suggest that restoring dPCC centrality in the presence of cognitive demands might have a therapeutic effect on persistent delusions in people with schizophrenia., Introduction Working-memory deficit--the failure to represent, maintain and update information in a short period of time--is a key feature of neurocognitive deficit in schizophrenia. (1) It emerges in the prodromal [...]

Background: Major depressive disorder (MDD) is a debilitating mental illness that has been linked to increases in markers of inflammation, as well as to changes in brain functional and structural connectivity, particularly between the insula and the subgenual anterior cingulate cortex (sgACC). In this study, we directly related inflammation and dysconnectivity in treatment-resistant MDD by concurrently measuring the following: microglial activity with [[sup.18]F]N-2-(fluoroethoxyl)benzyl-N-(4phenoxypyridin-3-yl)acetamide ([[sup.18]F]FEPPA) positron emission tomography (PET); the severity of MDD; and functional or structural connectivity among insula or sgACC nodes. Methods: Twelve patients with treatment-resistant MDD (8 female, 4 male; mean age [+ or -] standard deviation 54.9 [+ or -] 4.5 years and 23 healthy controls (11 female, 12 male; 60.3 [+ or -] 8.5 years) completed a hybrid [[sup.18]F]FEPPA PET and MRI acquisition. From these, we extracted relative standardized uptake values for [[sup.18]F]FEPPA activity and Pearson r-to-z scores representing functional connectivity from our regions of interest. We extracted diffusion tensor imaging metrics from the cingulum bundle, a key white matter bundle in MDD. We performed regressions to relate microglial activity with functional connectivity, structural connectivity and scores on the 17-item Hamilton Depression Rating Scale. Results: We found significantly increased [[sup.18]F]FEPPA uptake in the left sgACC in patients with treatment-resistant MDD compared to healthy controls. Patients with MDD also had a reduction in connectivity between the sgACC and the insula. The [[sup.18]F]FEPPA uptake in the left sgACC was significantly related to functional connectivity with the insula, and to the structural connectivity of the cingulum bundle. [[sup.18]F]FEPPA uptake also predicted scores on the Hamilton Depression Rating Scale. Limitations: A relatively small sample size, lack of functional task data and concomitant medication use may have affected our findings. Conclusion: We present preliminary evidence linking a network-level dysfunction relevant to the pathophysiology of depression and related to increased microglial activity in MDD., Introduction Major depressive disorder (MDD), characterized by recurrent cognitive and emotional dysfunction, is one of the most prevalent psychiatric disorders and a major contributor toward reduced quality of life. (1) [...]

Background: Abnormalities of cortical morphology have been consistently reported in major depressive disorder (MDD), with widespread focal alterations in cortical thickness, surface area and gyrification. However, it is unclear whether these distributed focal changes disrupt the system-level architecture (topology) of brain morphology in MDD. If present, such a topological disruption might explain the mechanisms that underlie altered cortical morphology in MDD. Methods: Seventy-six patients with first-episode MDD (33 male, 43 female) and 66 healthy controls (32 male, 34 female) underwent structural MRI scans. We calculated cortical indices, including cortical thickness, surface area and local gyrification index, using FreeSurfer. We constructed morphological covariance networks using the 3 cortical indices separately, and we analyzed the topological properties of these group-level morphological covariance networks using graph theoretical approaches. Results: Topological differences between patients with first-episode MDD and healthy controls were restricted to the thickness-based network. We found a significant decrease in global efficiency but an increase in local efficiency of the left superior frontal gyrus and the right paracentral lobule in patients with first-episode MDD. When we simulated targeted lesions affecting the most highly connected nodes, the thickness-based networks in patients with first-episode MDD disintegrated more rapidly than those in healthy controls. Limitations: Our sample of patients with first-episode MDD has limited generalizability to patients with chronic and recurrent MDD. Conclusion: A systems-level disruption in cortical thickness (but not surface area or gyrification) occurs in patients with first-episode MDD., Introduction Major depressive disorder (MDD) is one of the most prevalent mental illnesses; it affects more than 264 million people worldwide and has an estimated lifetime prevalence of 16.2%. (1) [...]

The act of will and the action of the body are not two different states ...; they do not stand in the relation of cause and effect but are one [...]