The AMP SCZ Data Repository houses all data generated by the Accelerating Medicines Partnership (AMP®) Schizophrenia (SCZ) research study. AMP SCZ was launched in 2020 to address the critical need for more effective treatments for people with schizophrenia and related mental health conditions. Visit the AMP SCZ website to learn more.

The AMP SCZ Data Repository serves as a collaborative platform for harmonizing these data and shares the data with qualified researchers. The AMP SCZ program is a public-private partnership between the National Institutes of Health (NIH), the U.S. Food and Drug Administration (FDA), the European Medicines Agency (EMA), industry partners, non-profit partners and other organizations. Learn more about the AMP SCZ partners.

The AMP SCZ data will be made available to the research community as the data are being collected.

• Data Release 1.0 is now available at DOI: 10.15154/18rd-ck75.
• Data Release 2.0 is now available at DOI: 10.15154/8ax0-e673.

Please refer to the Release Notes for important information on how to interpret and use the AMP SCZ Study data. Release Notes are updated throughout the year, and we encourage users to check for updates regularly. Publicly available release notes can be found here. Only researchers with an approved NDA Data Use Certification (DUC) may obtain AMP SCZ Study data. Click the button below to create an NDA account and apply for data access.

The AMP SCZ data repository contains several datasets. These include curated and tabulated behavioral and clinical measures, electroencephalography and imaging data (plain text, comma-separated values files) and associated data. Click the button below to learn more about what data is available and how you can download the data. The data dictionaries for all tabulated data can be accessed here.

The first AMP SCZ data release provides baseline data for a relatively small subset of clinical high-risk (CHR) and healthy control participants. The data release allows users to view the quality and multiple data types that are, and will be, available. However, the sample size is sufficiently small that researchers are not encouraged to test hypotheses related to biomarkers for CHR.

Schizophrenia is a serious mental illness and one of the top 15 leading causes of disability worldwide. The disorder is characterized by alterations to a person’s thoughts, feelings, and behaviors, which can include a loss of contact with reality known as psychosis. These symptoms typically emerge in adolescence or early adulthood and can be persistent and disabling when left untreated, interfering with a person’s ability to engage in typical school, work, and social activities. In addition, individuals with schizophrenia often experience a delay between diagnosis and the start of treatment — ranging from 1 to 3 years. Delaying the start of treatment is often associated with poorer response and significantly worse long-term outcomes. Detection and intervention before psychosis develops, when individuals are at clinical high risk (CHR) for psychosis, could attenuate, postpone, or even prevent the transition to psychosis, and improve individuals’ clinical and functional outcomes.

Although research has developed clinical and biological measures that can identify individuals who are at increased risk for developing psychosis, these findings have not yet translated into targeted interventions. AMP SCZ aims to develop measures that further define early stages of risk and predict the likelihood of progression to psychosis and other outcomes. Such tools will enable clinical trials to test new pharmacologic interventions that may prevent the onset of psychosis.

 

NIMH and AMP SCZ

NIMH is currently supporting three research projects as part of the AMP SCZ initiative:

Trajectories and Predictors in the Clinical High Risk for Psychosis Population: Australian Network of Clinics and International Partners (CHR-Aus) Barnaby Nelson, Ph.D., head of ultra-high risk for psychosis research at the Center for Youth Mental Health at the University of Melbourne and at Orygen, Melbourne, Australia, and Patrick McGorry, M.D., Ph.D., head of the Center for Youth Mental Health at the University of Melbourne and executive director of Orygen, are leading a multisite project focused on developing models that can predict a wide range of clinical outcomes in CHR individuals. As part of this project, Nelson and colleagues will collect a diverse set of biomarkers along with clinical data to develop CHR trajectory-prediction tools that can be used to facilitate the selection of CHR individuals to enroll in clinical trials and monitor disease progression and outcomes.

ProNET: Psychosis-Risk Outcomes Network Scott Woods. M.D., professor of psychiatry at Yale University, and co-principal investigators Carrie Bearden, Ph.D., professor of psychiatry and biobehavioral sciences and psychology at the University of California, Los Angeles, and John Kane, M.D., professor and chair of psychiatry at the Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, are leading a multisite project, including 26 international sites, mapping a wide range of biomarkers (including brain structure and function, psychopathology and cognition, genetics, behavior, and natural language and speech) onto a set of CHR trajectories and outcomes. Woods and colleagues will then test whether data-driven variation in these biomarkers can be used to predict individual clinical trajectories.

Psychosis Risk Evaluation, Data Integration and Computational Technologies (PREDICT): Data Processing, Analysis, and Coordination Center Martha Shenton, Ph.D., professor of psychiatry and radiology at Harvard Medical School and Brigham and Women's Hospital, and Rene Kahn, M.D., Ph.D., chair of the Department of Psychiatry and Behavioral Health at Icahn School of Medicine at Mount Sinai, are leading a project creating a data processing, analysis, and coordination center that will integrate and analyze CHR biomarker and clinical data generated by the two multisite research networks (listed above) as well as key existing CHR-related datasets. Using these data, the researchers plan to develop algorithms that can identify biomarkers predictive of CHR outcomes — biomarkers that can then be used to identify clinically useful subtypes of CHR.

 

Associated NDA Collections

NIMH is also supporting the following research projects that are closely aligned with the AMP-SCZ project:

Clinical and Biomarker-Based Trajectories of Psychosis-Risk Populations in Kenya

Daniel Mamah, associate professor at Washington University School of Medicine is leading a project that will be collecting data in a way that is similar to the AMP-SCZ initiative.

 

All of the data generated by the research networks will be archived and publicly available in the AMP SCZ Data Repository within the NIMH Data Archive.

AMP SCZ marks the first AMP initiative focused on a neuropsychiatric disorder and the fifth AMP initiative overall. Ongoing AMP projects are focused on improving the productivity of therapeutic development for Parkinson’s disease (PD), Alzheimer’s disease (AD), type 2 diabetes (T2D), and the autoimmune disorders rheumatoid arthritis and systemic lupus erythematosus (RA/Lupus).

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Acknowledgement statement for published research using data from the AMP-SCZ initiative: This paper uses data collected in the Accelerating Medicines Partnership in Schizophrenia (AMP SCZ) project. AMP SCZ is supported by NIMH grants U24MH124629, U01MH124631, U01MH124639. The research was also funded in part by the Welcome Trust (220664/Z/20/Z).

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About the National Institutes of Health (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov.

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