Baseline Clinical Characterization of Participants in the Accelerating Medicines Partnership Schizophrenia Program.

Background: This paper focuses on the baseline clinical characterization of the participants in the Accelerating Medicines Partnership Schizophrenia (AMP SCZ) program. The AMP SCZ program is designed to investigate a wide array of clinical variables and biomarkers in a total of 2040 clinical high-risk (CHR) participants and 652 community control (CC) participants.

Methods: The dataset analyzed includes 1642 individuals at clinical high risk for psychosis and 519 CCs.

Sample Ascertainment and Recruitment Sources in the Accelerating Medicines Partnership Schizophrenia Program.

Background: This paper presents the recruitment sources of clinical high-risk (CHR) and community controls (CC) from the Accelerating Medicines Partnership Schizophrenia (AMP SCZ) program, which aims to study various clinical variables and biomarkers in 2040 CHR and 652 CC participants.

Methods: A total of 1640 CHR and 514 CC had recruitment source data. The Positive Symptoms and Diagnostic Criteria for the Comprehensive Assessment of At-Risk Mental States Harmonized with the SIPS was utilized to assess CHR criteria and severity of attenuated psychotic symptoms (APSs), and the Global Functioning: Social Scale was used for social functioning.

Differentiating biomarker features and familial characteristics of B-SNIP psychosis Biotypes.

Idiopathic psychosis shows considerable biological heterogeneity across cases. The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) used psychosis-relevant biomarkers to identify psychosis Biotypes, which will aid etiological and targeted treatment investigations. Here, our previous approach (Clementz et al.

Exposotypes in psychotic disorders.

Psychiatry lags in adopting etiological approaches to diagnosis, prognosis, and outcome prediction compared to the rest of medicine. Etiological factors such as childhood trauma (CHT), substance use (SU), and socioeconomic status (SES) significantly affect psychotic disorder symptoms. This study applied an agnostic clustering approach to identify exposome clusters "Exposotypes (ETs)" and examine their relationship with clinical, cognitive, and functional outcomes.

Functional Brain Age Acceleration from Dynamic and Static Connectivity Predicts Working Memory and Attention Deficits in Schizophrenia.

Background: Schizophrenia is characterized by deficits in attention and working memory. In recent years, the brain age gap (BAG), defined as the difference between neuroimaging-predicted and chronological age, has emerged as a biomarker of brain dysfunction. Prior studies primarily use structural MRI or static functional network connectivity (sFNC), while the potential of dynamic functional network connectivity (dFNC) to quantify BAG in relationship with cognition remains underexplored.

A graph transformer-based foundation model for brain functional connectivity network.

Although foundation models have advanced many medical imaging fields, their absence in neuroimage analysis limits progress in neuroscience and clinical practice. Brain functional connectivity (FC) analysis is central to understanding brain function and widely used in neuroscience. We propose a foundation model tailored for brain functional connectivity networks (FCN).

Mutualistic Multi-Network Noisy Label Learning (MMNNLL) Method and Its Application to Transdiagnostic Classification of Bipolar Disorder and Schizophrenia.

The subjective nature of diagnosing mental disorders complicates achieving accurate diagnoses. The complex relationship among disorders further exacerbates this issue, particularly in clinical practice where conditions like bipolar disorder (BP) and schizophrenia (SZ) can present similar clinical symptoms and cognitive impairments. To address these challenges, this paper proposes a mutualistic multi-network noisy label learning (MMNNLL) method, which aims to enhance diagnostic accuracy by leveraging neuroimaging data under the presence of potential clinical diagnosis bias or errors.

Sharing Neuroimaging Data with Squirrel - A Relational Data Format to Store Raw to Analyzed Data and Everything in Between.

Reproducibility of neuroimaging analyses and aggregation of heterogenous datasets are significant challenges in human subjects imaging research. This stems in part from a lack of an easy to use and universal data format that encompasses all steps of neuroimaging. The BIDS format has become widely adopted, however it is increasingly complex to implement as features are added, with the documentation now exceeding 500 pages.

Neural fingerprints of data driven cognitive subtypes across the psychosis spectrum: a B-SNIP study.

Cognitive dysfunction is a prominent feature of psychotic spectrum disorders. Identifying neurocognitive subgroups and their neural underpinnings may help elucidate distinct pathophysiological mechanisms and inform targeted interventions. This study aimed to derive cognitive subtypes using latent profile analysis (LPA) of the Brief Assessment of Cognition in Schizophrenia (BACS) and investigate associated variations in resting-state functional connectivity among these cognitive profiles and biologically derived Biotypes.

Structural Brain Changes Associated With Risky Drinking in Late-Life Depression.

Objectives: As alcohol use is common among older depressives, we assessed structural brain changes over 2 years and examined their association with changes in alcohol consumption.

Design: Longitudinal cohort study.

Setting: Academic health center.

The electroencephalography protocol for the Accelerating Medicines Partnership® Schizophrenia Program: Reliability and stability of measures.

Individuals at clinical high risk for psychosis (CHR) have variable clinical outcomes and low conversion rates, limiting development of novel and personalized treatments. Moreover, given risks of antipsychotic drugs, safer effective medications for CHR individuals are needed. The Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ) Program was launched to address this need.

Digital health technologies in the accelerating medicines Partnership® Schizophrenia Program.

Although meta-analytic studies have shown that 25-33% of those at Clinical High Risk (CHR) for psychosis transition to a first episode of psychosis within three years, less is known about estimating the risk of transition at an individual level. Digital phenotyping offers a novel approach to explore the nature of CHR and may help to improve personalized risk prediction. Specifically, digital data enable detailed mapping of experiences, moods and behaviors during longer periods of time (e.

Brain Age Disparities in Psychosis Across DSM Diagnoses and B-SNIP Biotypes.

Background And Hypothesis: The brain age gap (BAG) quantifies the difference between predicted brain age and chronological age. Prior research implicates higher BAG in psychotic disorders, suggesting accelerated brain aging. We hypothesized distinct brain aging profiles among biological subtypes of psychosis and intermediate BAG in their relatives.

Impact of Polygenic Interactions With Anticholinergic Burden on Cognition and Brain Structure in Psychosis Spectrum Disorders.

Objective: The authors sought to determine whether genetic predispositions to cognitive ability or psychiatric conditions interact with anticholinergic burden (AChB) to impact cognition and brain structure in individuals with psychotic disorders.

Methods: Participants with psychosis spectrum disorders (N=1,704) from the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) consortium, 18-65 years of age and representing diverse ancestries, underwent cognitive assessments, structural neuroimaging, genotyping, and a comprehensive medication review. The primary cognitive outcome was the Brief Assessment of Cognition in Schizophrenia (BACS) composite score, and the primary brain structural phenotype was total gray matter volume.

Brain-wide connectivity changes due to social-emotional regulation during a naturalistic fMRI task.

Social-emotional (SE) regulation is necessary for successful social interactions. Such emotion regulation (ER), however, has been examined in only a few studies using naturalistic SE tasks during functional neuroimaging. We examined ER in typically developed young adults (n = 62) watching and listening to a video of a person telling an emotional (positive, negative) or neutral story during functional MRI.

Cerebral perfusion differences in the visual cortex and fusiform subregions across the psychosis spectrum.

Background: Approximately 50% of individuals with psychosis spectrum disorders (PSD) experience visual hallucinations and deficits in visual processing. Cerebral blood flow (CBF) alterations have been identified in the occipital lobe (OL) and fusiform gyrus (FG) in PSD. However, prior studies neither report on cytoarchitectonic subregions of the OL or FG, nor their correlations with cognition.

Cognitive performance and differentiation of B-SNIP psychosis Biotypes: Algorithmic Diagnostics for Efficient Prescription of Treatments (ADEPT) - 2.

Objective: The B-SNIP consortium validated neurobiologically defined psychosis Biotypes (BT1, BT2, BT3) using cognitive and psychophysiological measures. B-SNIP's biomarker panel is not practical for most settings. Previously, B-SNIP developed an efficient classifier of Biotypes using only clinical assessments (called ADEPT-CLIN) with acceptable accuracy (~.

Thalamocortical Structural Covariation Networks Are Related to Familial Risk for Schizophrenia in the Context of Lower Nuclei Volume Estimates in Patients: An ENIGMA Study.

Background: Structural brain differences in the thalamus and the cortex have been widely reported in schizophrenia (SCZ) relative to neurotypical control individuals (NCs). Most previous studies examined the thalamus as a whole as a single region of interest. In addition, findings in individuals at familial high risk for SCZ (FHRs) remain inconclusive.

Alterations in Gray Matter Structure Linked to Frequency-Specific Cortico-Subcortical Connectivity in Schizophrenia via Multimodal Data Fusion.

Schizophrenia (SZ) is a complex psychiatric disorder that is currently defined by symptomatic and behavioral, rather than biological, criteria. Neuroimaging is an appealing avenue for SZ biomarker development, as several neuroimaging-based studies have shown measurable group differences in brain structure, as well as functional brain alterations in both static and dynamic functional network connectivity (sFNC and dFNC, respectively), between SZ and controls. The recently proposed filter-banked connectivity (FBC) method extends the standard dFNC sliding-window approach to estimate FNC within an arbitrary number of distinct frequency bands.

Visualizing functional network connectivity differences using an explainable machine-learning method.

. Functional network connectivity (FNC) estimated from resting-state functional magnetic resonance imaging showed great information about the neural mechanism in different brain disorders. But previous research has mainly focused on standard statistical learning approaches to find FNC features separating patients from control.

Sample ascertainment and clinical outcome measures in the Accelerating Medicines Partnership® Schizophrenia Program.

Clinical ascertainment and clinical outcome are key features of any large multisite study. In the ProNET and PRESCIENT research networks, the Accelerating Medicines Partnership Schizophrenia (AMPSCZ) Clinical Ascertainment and Outcome Measures Team aimed to establish a harmonized clinical assessment protocol across these two research networks and to define ascertainment criteria and primary and secondary endpoints. In addition to developing the assessment protocol, the goals of this aspect of the AMP SCZ project were: (1) to implement and monitor clinical training, ascertainment of participants, and clinical assessments; (2) to provide expert clinical input to the Psychosis Risk Evaluation, Data Integration and Computational Technologies: Data Processing, Analysis, and Coordination Center (PREDICT-DPACC) for data collection, quality control, and preparation of data for the analysis of the clinical measures; and (3) to provide ongoing support to the collection, analysis, and reporting of clinical data.

The MR neuroimaging protocol for the Accelerating Medicines Partnership® Schizophrenia Program.

Neuroimaging with MRI has been a frequent component of studies of individuals at clinical high risk (CHR) for developing psychosis, with goals of understanding potential brain regions and systems impacted in the CHR state and identifying prognostic or predictive biomarkers that can enhance our ability to forecast clinical outcomes. To date, most studies involving MRI in CHR are likely not sufficiently powered to generate robust and generalizable neuroimaging results. Here, we describe the prospective, advanced, and modern neuroimaging protocol that was implemented in a complex multi-site, multi-vendor environment, as part of the large-scale Accelerating Medicines Partnership® Schizophrenia Program (AMP® SCZ), including the rationale for various choices.

Beyond Pairwise Connections in Complex Systems: Insights into the Human Multiscale Psychotic Brain.

Complex biological systems, like the brain, exhibit intricate multiway and multiscale interactions that drive emergent behaviors. In psychiatry, neural processes extend beyond pairwise connectivity, involving higher-order interactions critical for understanding mental disorders. Conventional brain network studies focus on pairwise links, offering insights into basic connectivity but failing to capture the complexity of neural dysfunction in psychiatric conditions.

Cognitive assessment in the Accelerating Medicines Partnership® Schizophrenia Program: harmonization priorities and strategies in a diverse international sample.

Cognitive impairment occurs at higher rates in individuals at clinical high risk (CHR) for psychosis relative to healthy peers, and it contributes unique variance to multivariate prediction models of transition to psychosis. Such impairment is considered a core biomarker of schizophrenia. Thus, cognition is a key domain measured in the Accelerating Medicines Partnership® program for Schizophrenia (AMP SCZ initiative).

White Matter, Cognition, and Electrophysiological Variables in Bipolar Disorder: Using Multimodal Integration of Biomarker Variables Associated With Bipolar Disorder to Elucidate Deficits.

Aim: This study aimed to evaluate associations in bipolar disorder (BD) across multimodal measures of white matter microstructure (using diffusion tensor imaging; DTI), cognitive, behavioral, and brain electrophysiological measures (using electroencephalography; EEG).

Methods: Subjects were recruited through the Psychosis and Affective Research Domains and Intermediate Phenotypes Consortium (n = 45 bipolar with psychosis, n = 40 bipolar without psychosis, n = 66 healthy subjects). DTI data were used to quantify the white matter variables, fractional anisotropy (FA) and radial diffusivity (RD).