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BackgroundStructural 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 methodsWe 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.ResultsComponent 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.ConclusionThese 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.

The Research Domain Criteria (RDoC) initiative aims to organize research according to domains of brain function. Dysfunction within these domains leads to psychopathology that is classically measured with rating scales. Examining the correspondence between the specific measures assessed within rating scales and RDoC domains is necessary to assess the needs for new RDoC-focused scales. Such RDoC-focused scales have the potential of allowing translation of this work into the clinical domain of measuring psychopathology and designing treatment. Here, we describe an initial qualitative assessment by a group of 10 clinician-scientists of the alignment between RDoC domains and the items within five commonly used rating scales. In this commentary, we report limited correspondence and make recommendations for future work needed to address these limitations.

BackgroundElectroconvulsive therapy (ECT) is the most effective treatment for treatment-resistant depression (TRD), especially for acute suicidal ideation, but the associated cognitive adverse effects and negative stigma limit its use. Another seizure therapy under development is magnetic seizure therapy (MST), which could potentially overcome the restrictions associated with ECT with similar efficacy. The neurophysiological targets and mechanisms of seizure therapy, however, remain poorly understood.Methods/designThis neurophysiological study protocol is published as a companion to the overall Confirmatory Efficacy and Safety Trial of Magnetic Seizure Therapy for Depression (CREST-MST) protocol that describes our two-site, double-blind, randomized, non-inferiority clinical trial to develop MST as an effective and safe treatment for TRD. Our aim for the neurophysiological component of the study is to evaluate two biomarkers, one to predict remission of suicidal ideation (primary outcome) and the other to predict cognitive impairment (secondary outcome). Suicidal ideation will be assessed through cortical inhibition, which according to our preliminary studies, correlates with remission of suicidal ideation. Cortical inhibition will be measured with simultaneous transcranial magnetic stimulation (TMS) and electroencephalography (EEG), TMS-EEG, which measures TMS-evoked EEG activity. Cognitive adverse effects associated with seizure therapy, on the contrary, will be evaluated via multiscale entropy analysis reflecting the complexity of ongoing resting-state EEG activity.DiscussionECT and MST are known to influence cortical inhibition associated with depression, suicidal ideation severity, and clinical outcome. Therefore, evaluating cortical inhibition and brain temporal dynamics will help understand the pathophysiology of depression and suicidal ideation and define new biological targets that could aid clinicians in diagnosing and selecting treatments. Resting-state EEG complexity was previously associated with the degree of cognitive side effects after a seizure therapy. This neurophysiological metric may help clinicians assess the risk for adverse effects caused by these useful and effective treatments.Trial registrationClinicalTrials.gov NCT03191058 . Registered on June 19, 2017.

Elevations in peripheral inflammatory markers have been reported in patients with psychosis. Whether this represents an inflammatory process defined by individual or subgroups of markers is unclear. Further, relationships between peripheral inflammatory marker elevations and brain structure, cognition, and clinical features of psychosis remain unclear. We hypothesized that a pattern of plasma inflammatory markers, and an inflammatory subtype established from this pattern, would be elevated across the psychosis spectrum and associated with cognition and brain structural alterations. Clinically stable psychosis probands (Schizophrenia spectrum, n = 79; Psychotic Bipolar disorder, n = 61) and matched healthy controls (HC, n = 60) were assessed for 15 peripheral inflammatory markers, cortical thickness, subcortical volume, cognition, and symptoms. A combination of unsupervised exploratory factor analysis and hierarchical clustering was used to identify inflammation subtypes. Levels of IL6, TNFα, VEGF, and CRP were significantly higher in psychosis probands compared to HCs, and there were marker-specific differences when comparing diagnostic groups. Individual and/or inflammatory marker patterns were associated with neuroimaging, cognition, and symptom measures. A higher inflammation subgroup was defined by elevations in a group of 7 markers in 36% of Probands and 20% of HCs. Probands in the elevated inflammatory marker group performed significantly worse on cognitive measures of visuo-spatial working memory and response inhibition, displayed elevated hippocampal, amygdala, putamen and thalamus volumes, and evidence of gray matter thickening compared to the proband group with low inflammatory marker levels. These findings specify the nature of peripheral inflammatory marker alterations in psychotic disorders and establish clinical, neurocognitive and neuroanatomic associations with increased inflammatory activation in psychosis. The identification of a specific subgroup of patients with inflammatory alteration provides a potential means for targeting treatment with anti-inflammatory medications.

The National Institutes of Health has established the PhenX Toolkit as a web-based resource containing consensus measures freely available to the research community. The National Institute of Mental Health (NIMH) has introduced the Mental Health Research Core Collection as part of the PhenX Toolkit and recently convened the PhenX Early Psychosis Working Group to generate the PhenX Early Psychosis Specialty Collection. The Working Group consisted of two complementary panels for clinical and translational research. We review the process, deliberations, and products of the translational research panel. The Early Psychosis Specialty Collection rationale for measure selection as well as additional information and protocols for obtaining each measure are available on the PhenX website (https://www.phenxtoolkit.org). The NIMH strongly encourages investigators to use instruments from the PhenX Mental Health Research Collections in NIMH-funded studies and discourages use of alternative measures to collect similar data without justification. We also discuss some of the potential advances that can be achieved by collecting common data elements across large-scale longitudinal studies of early psychosis.

Genetic factors are known to influence both risk for schizophrenia (SZ) and variation in brain structure. A pressing question is whether the genetic underpinnings of brain phenotype and the disorder overlap. Using multivariate analytic methods and focusing on 1,402 common single-nucleotide polymorphisms (SNPs) mapped from the Psychiatric Genomics Consortium (PGC) 108 regions, in 777 discovery samples, we identified 39 SNPs to be significantly associated with SZ-discriminating gray matter volume (GMV) reduction in inferior parietal and superior temporal regions. The findings were replicated in 609 independent samples. These 39 SNPs in chr6:28308034-28684183 (6p22.1), the most significant SZ-risk region reported by PGC, showed regulatory effects on both DNA methylation and gene expression of postmortem brain tissue and saliva. Furthermore, the regulated methylation site and gene showed significantly different levels of methylation and expression in the prefrontal cortex between cases and controls. In addition, for one regulated methylation site we observed a significant in vivo methylation-GMV association in saliva, suggesting a potential SNP-methylation-GMV pathway. Notably, the risk alleles inferred for GMV reduction from in vivo imaging are all consistent with the risk alleles for SZ inferred from postmortem data. Collectively, we provide evidence for shared genetic risk of SZ and regional GMV reduction in 6p22.1 and demonstrate potential molecular mechanisms that may drive the observed in vivo associations. This study motivates dissecting SZ-risk variants to better understand their associations with focal brain phenotypes and the complex pathophysiology of the illness.

First, we describe the hallmark contributions of Irv Gottesman's pioneering scholarship for schizophrenia research including concepts of polygenicity, gene × environment interactions, epigenetics and the endophenotype concept. Gottesman and colleagues' twin studies showed that genes, not social factors, mediate schizophrenia risk. He then showed that schizophrenia is highly polygenic. Next, he introduced the concept of epigenetics into schizophrenia research. Gottesman then introduced the quantitative endophenotype concept. Endophenotypes are laboratory-based measures that show deficits in schizophrenia patients and lesser deficits in their first degree "unaffected" relatives and are viewed as being more proximal to genes and having a simpler genetic architecture than are "fuzzy" qualitative diagnostic disorders. Endophenotypes offer an exciting path to gene discovery, neural circuits, genetic architecture and new treatment pathways of schizophrenia and related psychotic disorders. Second, we were asked to discuss 2 of many endophenotype Consortia and related studies, in order to illustrate the impact of Gottesman's work. We describe the Consortium on the Genetics of Schizophrenia (COGS) exploring neurocognitive and neurophysiological endophenotypes in family and case-control studies. Association, linkage, sequencing and epigenetic studies are described. The Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP) uses an array of endophenotypes including brain imaging in studies across the psychosis dimension, allowing for dimensional analyses. BSNIP results have led to the concept of biotypes, advancing the field. Irv Gottesman was imaginatively prescient in generating novel insights and predicting many major issues which challenge schizophrenia researchers who still use his concepts to guide current research approaches.