The first release of imaging and behavioral data from a study of affective and non-affective psychosis participants and healthy controls ages 16-25.
The main goal of the Human Connectome Project for Early Psychosis is to acquire high quality imaging, behavioral, clinical, cognitive, and genetic data on an important cohort of early psychosis patients, in a manner consistent with the original Human Connectome Project, where data from this project will be made available to the research community for future studies.
We focus on early psychosis (both affective and non-affective psychosis), within the first 3 years of the onset of psychotic symptoms. This is a critical time period when there are fewer confounds such as prolonged medication exposure and chronicity, and when early intervention strategies will be most effective, prior to the progression that often leads to debilitating and chronic illnesses, to great suffering, and to an enormous public health problem and economic burden. The data acquired will make it possible to identify disruptions in neural connections in early psychosis that likely underlie both brain function and dysfunction, and these data can be linked to behavioral, cognitive, and other measures, consistent with the goals of this funding initiative. Such an approach will lead not only to a better understanding of neural network disruptions in psychotic illnesses but will also lead to more targeted treatment interventions early in the course of illness to prevent the cascade of progression to chronicity where changes in the brain are likely not reversible.
Project Timespan: August 5, 2016 – July 31, 2020
Beth Israel Deaconess- Massachusetts Mental Health Center (Site Co-PI)
Data being collected
Imaging is conducted at multiple sites in two cities. In Boston: Brigham and Women’s Hospital, Beth Israel Deaconess-Massachusetts Mental Health Center, McLean Hospital, and Massachusetts General Hospital. In Indianapolis, IN: Indiana University School of Medicine. All sites are using a 3T Siemens Prisma MR scanner.
The study includes 320 male or female outpatients, between the ages of 16 to 35 years of age, within 3 years of onset of initial psychotic symptoms, and 80 controls.
Data Release Plans
An early release is planned for Year 2 of the project. The other two releases will be in Years 3 and 4.
Early Psychosis; Schizophrenia; Bipolar Disorder; Affective Psychosis; Non-Affective Psychosis; Anxiety; Mental Depression; Mood Disorders; White Matter
HCP-Early Psychosis Release 1.0 data is now available in the NIMH Data Archive (NDA). HCP-EP is a study of subjects ages 16-35 focused specifically on early psychosis, both affective and non-affective, within the first five years of the initial onset of psychotic symptoms. This time period is important as it is when there are fewer confounds such as prolonged medication exposure and chronicity, and it is also a time period where early intervention strategies may be most effective, before irreversible brain alterations take place, which likely begin early in the course of illness.
The HCP-Early Psychosis Release 1.0 includes:
The full release dataset is available on the HCP Featured Datasets query page on NDA as a single shared package (1.3 TB, option one) or can be filtered by modality, processing level, and subject GUID to create a custom package of a subset of the data (option two).
Full details of the project and released data are available in the:
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Release Date: Sep 09, 2020
Psychotic disorders are severe, debilitating, and even fatal. The development of targeted and effective interventions for psychosis depends upon on clear understanding of the timing and nature of disease progression to target processes amenable to intervention. Strong evidence suggests early and ongoing neuroprogressive changes, but timing and inflection points remain unclear and likely differ across cognitive, clinical, and brain measures. Additionally, granular evidence across modalities is particularly sparse in the "bridging years" between first episode and established illness-years that may be especially critical for improving outcomes and during which interventions may be maximally effective. Our objective is the systematic, multimodal characterization of neuroprogression through the early course of illness in a cross-diagnostic sample of patients with psychosis. We aim to (1) interrogate neurocognition, structural brain measures, and network connectivity at multiple assessments over the first eight years of illness to map neuroprogressive trajectories, and (2) examine trajectories as predictors of clinical and functional outcomes. We will recruit 192 patients with psychosis and 36 healthy controls. Assessments will occur at baseline and 8- and 16-month follow ups using clinical, cognitive, and imaging measures. We will employ an accelerated longitudinal design (ALD), which permits ascertainment of data across a longer timeframe and at more frequent intervals than would be possible in a single cohort longitudinal study. Results from this study are expected to hasten identification of actionable treatment targets that are closely associated with clinical outcomes, and identify subgroups who share common neuroprogressive trajectories toward the development of individualized treatments.
Several prominent theories of schizophrenia suggest that structural white matter pathologies may follow a developmental, maturational, and/or degenerative process. However, a lack of lifespan studies has precluded verification of these theories. Here, we analyze the largest sample of carefully harmonized diffusion MRI data to comprehensively characterize age-related white matter trajectories, as measured by fractional anisotropy (FA), across the course of schizophrenia. Our analysis comprises diffusion scans of 600 schizophrenia patients and 492 healthy controls at different illness stages and ages (14-65 years), which were gathered from 13 sites. We determined the pattern of age-related FA changes by cross-sectionally assessing the timing of the structural neuropathology associated with schizophrenia. Quadratic curves were used to model between-group FA differences across whole-brain white matter and fiber tracts at each age; fiber tracts were then clustered according to both the effect-sizes and pattern of lifespan white matter FA differences. In whole-brain white matter, FA was significantly lower across the lifespan (up to 7%; p < 0.0033) and reached peak maturation younger in patients (27 years) compared to controls (33 years). Additionally, three distinct patterns of neuropathology emerged when investigating white matter fiber tracts in patients: (1) developmental abnormalities in limbic fibers, (2) accelerated aging and abnormal maturation in long-range association fibers, (3) severe developmental abnormalities and accelerated aging in callosal fibers. Our findings strongly suggest that white matter in schizophrenia is affected across entire stages of the disease. Perhaps most strikingly, we show that white matter changes in schizophrenia involve dynamic interactions between neuropathological processes in a tract-specific manner.
Understanding the neuropathological underpinnings of mental disorders such as schizophrenia, major depression, and bipolar disorder is an essential step towards the development of targeted treatments. Diffusion MRI studies utilizing the diffusion tensor imaging (DTI) model have been extremely successful to date in identifying microstructural brain abnormalities in individuals suffering from mental illness, especially in regions of white matter, although identified abnormalities have been biologically non-specific. Building on DTI's success, in recent years more advanced diffusion MRI methods have been developed and applied to the study of psychiatric populations, with the aim of offering increased sensitivity to subtle neurological abnormalities, as well as improved specificity to candidate pathologies such as demyelination and neuroinflammation. These advanced methods, however, usually come at the cost of prolonged imaging sequences or reduced signal to noise, and they are more difficult to evaluate compared with the more simplified approach taken by the now common DTI model. To date, a limited number of advanced diffusion MRI methods have been employed to study schizophrenia, major depression and bipolar disorder populations. In this review we survey these studies, compare findings across diverse methods, discuss the main benefits and limitations of the different methods, and assess the extent to which the application of more advanced diffusion imaging approaches has led to novel and transformative information with regards to our ability to better understand the etiology and pathology of mental disorders.
Brain energy metabolism is critical for supporting synaptic function and information processing. A growing body of evidence suggests abnormalities in brain bioenergetics in psychiatric disorders, including both bipolar disorder (BD) and schizophrenia. (31)P magnetic resonance spectroscopy provides a noninvasive window into these processes in vivo. Using this approach, we previously showed that patients with BD show normal adenosine triphosphate (ATP) and phosphocreatine levels at rest but cannot maintain normal ATP levels in the visual cortex during times of high energy demand (photic stimulation). Because ATP is replenished from phosphocreatine via the creatine kinase reaction, we have now measured the creatine kinase forward reaction rate constant in BD.
Neurocognition is a central characteristic of schizophrenia and other psychotic disorders. Identifying the pattern and severity of neurocognitive functioning during the "near-psychotic," clinical high-risk (CHR) state of psychosis is necessary to develop accurate risk factors for psychosis and more effective and potentially preventive treatments.
White matter abnormalities have been reported in schizophrenia and may indicate altered cortical network integrity and structural connectivity, which have been hypothesized as key pathophysiological components of this illness. In this study, we aimed to further characterize the nature and progression of white matter alterations during the early stages of the disorder.
Tractography is the most anatomically accurate method for delineating white matter tracts in the brain, yet few studies have examined multiple tracts using tractography in patients with schizophrenia (SCZ). We analyze 5 white matter connections important in the pathophysiology of SCZ: uncinate fasciculus, cingulum bundle (CB), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus, and arcuate fasciculus (AF). Additionally, we investigate the relationship between diffusion tensor imaging (DTI) markers and neuropsychological measures.
Volume deficits of the hippocampus in schizophrenia have been consistently reported. However, the hippocampus is anatomically heterogeneous; it remains unclear whether certain portions of the hippocampus are affected more than others in schizophrenia. In this study, we aimed to determine whether volume deficits in schizophrenia are confined to specific subfields of the hippocampus and to measure the subfield volume trajectories over the course of the illness. Magnetic resonance imaging scans were obtained from Data set 1: 155 patients with schizophrenia (mean duration of illness of 7 years) and 79 healthy controls, and Data set 2: an independent cohort of 46 schizophrenia patients (mean duration of illness of 18 years) and 46 healthy controls. In addition, follow-up scans were collected for a subset of Data set 1. A novel, automated method based on an atlas constructed from ultra-high resolution, post-mortem hippocampal tissue was used to label seven hippocampal subfields. Significant cross-sectional volume deficits in the CA1, but not of the other subfields, were found in the schizophrenia patients of Data set 1. However, diffuse cross-sectional volume deficits across all subfields were found in the more chronic and ill schizophrenia patients of Data set 2. Consistent with this pattern, the longitudinal analysis of Data set 1 revealed progressive illness-related volume loss (~2-6% per year) that extended beyond CA1 to all of the other subfields. This decline in volume correlated with symptomatic worsening. Overall, these findings provide converging evidence for early atrophy of CA1 in schizophrenia, with extension to other hippocampal subfields and accompanying clinical sequelae over time.
Most programs specializing in the treatment of first-episode psychosis in the United States focus on schizophrenia. However, many early psychosis patients do not fit into this diagnostic category. Here we describe McLean OnTrack, an intensive outpatient treatment program that accepts all comers with first-episode psychosis.
Studies have demonstrated that episodic memory (EM) is often preferentially disrupted in schizophrenia. The neural substrates that mediate EM impairment in this illness are not fully understood. Several functional magnetic resonance imaging (fMRI) studies have employed EM probe tasks to elucidate the neural underpinnings of impairment, though results have been inconsistent. The majority of EM imaging studies have been conducted in chronic forms of schizophrenia with relatively few studies in early phase patients. Early phase schizophrenia studies are important because they may provide information regarding when EM deficits occur and address potential confounds more frequently observed in chronic populations. In this study, we assessed brain activation during the performance of visual scene encoding and recognition fMRI tasks in patients with earlyphase psychosis (n = 35) and age, sex, and race matched healthy control subjects (n = 20). Patients demonstrated significantly lower activation than controls in the right hippocampus and left fusiform gyrus during scene encoding and lower activation in the posterior cingulate, precuneus, and left middle temporal cortex during recognition of target scenes. Symptom levels were not related to the imaging findings, though better cognitive performance in patients was associated with greater right hippocampal activation during encoding. These results provide evidence of altered function in neuroanatomical circuitry subserving EM early in the course of psychotic illness, which may have implications for pathophysiological models of this illness.
Diffusion MRI has been successful in identifying the existence of white matter abnormalities in schizophrenia in vivo. However, the role of these abnormalities in the etiology of schizophrenia is not well understood. Accumulating evidence from imaging, histological, genetic, and immunochemical studies support the involvement of axonal degeneration and neuroinflammation--ubiquitous components of neurodegenerative disorders--as the underlying pathologies of these abnormalities. Nevertheless, the current imaging modalities cannot distinguish neuroinflammation from axonal degeneration, and therefore provide little specificity with respect to the pathophysiology progression and whether it is related to a neurodegenerative process. Free-water imaging is a new methodology that is sensitive to water molecules diffusing in the extracellular space. Excessive extracellular volume is a surrogate biomarker for neuroinflammation and can be separated out to reveal abnormalities such as axonal degeneration that affect diffusion characteristics in the tissue. We applied free-water imaging on diffusion MRI data acquired from schizophrenia-diagnosed human subjects with a first psychotic episode. We found a significant increase in the extracellular volume in both white and gray matter. In contrast, significant signs of axonal degeneration were limited to focal areas in the frontal lobe white matter. Our findings demonstrate that neuroinflammation is more prominent than axonal degeneration in the early stage of schizophrenia, revealing a pattern shared by many neurodegenerative disorders, in which prolonged inflammation leads to axonal degeneration. These findings promote anti-inflammatory treatment for early diagnosed schizophrenia patients.
Current definitions of the prodromal (or at-risk mental state) phase of schizophrenia include attenuated and/or transient psychotic symptoms as well as a combination of different risk indicators and a recent significant deterioration in global functioning. Data accumulated to date suggest rates of conversion to frank psychosis within two years in 25 to 40% of cases supporting the validity of these criteria. However, at this late phase of illness, functional deterioration is often already pronounced, highlighting the need for earlier identification. Moreover, negative symptoms and social impairments, cognitive deficits, other non-psychotic psychopathology and/or functional decline and non-specific biological indicators, often can be detected well before the at-risk mental state as currently defined; indicating that a broad characterization of an earlier stage may be possible. Identifying specific criteria to define this group of individuals, starting from the framework of familial high-risk, can help define a broader group of people, including earlier at-risk mental states, for future research. The hope is that this research will help facilitate intervention at earlier stages that may in turn minimize functional deterioration, and delay, attenuate or even prevent transition to psychosis. The disadvantages as well as the potential benefits of this approach are discussed.
Patients who present with a first episode of psychosis pose many challenges to psychiatry. While some morbidity from schizophrenia is probably not modifiable once acute psychosis has occurred, the best management of this stage of illness nevertheless holds the promise of improving long-term outcomes. We review the clinical literature on first-episode psychosis to derive clinical guidance with regard to timely diagnosis and optimal pharmacological and nonpharmacological treatment. We describe the illness course and the prognosis for this acute phase of illness and the immediate, postpsychotic period.
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