Accelerating Medicines Partnership® SCHIZOPHRENIA
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Keep up with the latest news about the Accelerating Medicines Partnership (AMP®) SCZ program.

Past Annual Investigators Meetings (2023)


2024 Annual Investigators Meeting | 2023 | 2022

Welcoming Remarks

Joshua Gordon, MD, PhD; National Institute of Mental Health

Accelerating Medicines Partnership Schizophrenia (AMP® SCZ) is the single largest project in the National Institute of Mental Health (NIMH) and will likely reach over $118M in scope by the end of the program. This initiative brings together hundreds of scientists from across the world and partners in the public-private sector to combat mental illness. Years of research characterizing the state of Clinical High Risk (CHR) for psychosis and discovery of hundreds genetic clues form the underpinnings of this work. The integration of computational approaches in psychiatric research has accelerated tremendously to address the heterogeneity in schizophrenia. The scientific and clinical goal is to understand and intervene for individuals in the CHR state.

Challenges this group faces include: (1) the false trope that research does not lead to advanced mental health care; (2) the heterogeneity and complexity of understanding the brain and its biomarkers; and (3) skepticism from policy makers and the private sector that investments in mental health will pay off. This network needs to prove that it can identify individuals at risk, test treatments in that population, and analyze the results of those interventions. The results of this program will pave the way for investments in future mental health research.

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Presentations From AMP SCZ Junior Investigators

Exploring Alterations in Cerebellar and Thalamic Connectivity Systems in SchizophreniaM

Min Ji Ha, MSc, Ph.D candidate; Seoul National University

There is growing evidence that the thalamus and cerebellum play key roles in the coordination of information intake and cognition. The cortico-thalamo-cerebellar network has been studied in psychosis individually and in terms of network interaction. Only a few studies have analyzed these network properties in association with psychopathology. The research team at Seoul National University aimed to fill this gap. They found schizophrenia patients to have more difficulty understanding meanings of words. They leveraged magnetic resonance imaging (MRI) to conduct imaging analysis. They used the parcellation method to cluster the cortical network based on similarity. They merged cortical networks together to perform a network ROI analysis and perform cluster-level inference multivariate generalized linear model (GLM).

As a result, they found hypoconnectivity in schizophrenia participants compared to healthy controls in regions of interest (ROI)-to-ROI functional connectivity (FC) analysis and network dysconnectivity in psychosis. Cortico-thalamo-cerebellar Salience Network (SAL), Default Mode Network (DMN), and Central Executive Network (CEN) interactions decreased in schizophrenia patients. The triple network model of psychopathology may be expanded to a larger scale in future work. Understanding the mechanism within this system and network patterns across the psychosis risk continuum’s remain open questions.

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Enhancing CHR Recruitment With Digital Strategies

Michael Birnbaum, MD; Northwell Health

The internet has transformed how we share information, communicate, and learn. Young people are by far the highest users of the internet and social media and are also at the highest risk for emergence of psychosis disorders. 87% of young adults cite online resources for how they find and consume health information. This is particularly true for stigmatized illnesses. There are opportunities to improve how we engage help seekers and potential high-risk individuals online.

The research team built one of the first online tools to identify and engage individuals at risk for psychosis in New York state. They ran two campaigns in parallel, one was aimed toward youth at risk in New York state and the other aimed at their allies. Consistent with the literature, most people who engaged the campaign were interested in information alone. 12% were interested in a referral to care. In the 18-month study, there were 2.2 million ad impressions, 34,000 unique website visits, 11,000 quiz takers. They found that the campaign engaged younger teens than anticipated, including youth across the help-seeking continuum from initial information through referrals to care, and the importance of persistent outreach.

In the future, they aim to characterize help seeking and use that information to tailor communication strategies. They want to iteratively develop, test, and select advancement strategies using micro randomized trials. They would like to partner with AMP SCZ sites to refer individuals for continued research and clinical care.

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Towards Precision Psychiatry; The Discovery of New Psychosis Risk Stratification and Biotypes

Dominic Dwyer, PhD; Orygen; University of Melbourne

There is an increasing need for precision medicine and personalized characterization for consumers in clinical trials. One way to increase precision in AMP SCZ is by defining clinical endpoints (e.g., conversion to psychosis, non-conversion, remission of CHR state) and using machine learning to predict endpoints for individuals. Clustering was one of the first machine learning techniques to group patients and predict outcomes. Advanced machine learning techniques were adapted to psychiatry to find the most generalizable solutions that can provide useful information from patients across the world.

The research team looked at clinical stratification and brain bio-typing to predict patient outcomes. They found precise subgroups in large clinical databases including positive symptoms, negative symptoms, depression, and high functioning. The machine did not find a CHR group, but rather captured CHR individuals within each of the four subgroups. Precise premorbid functioning and illness courses can be stratified within each subgroup. Researchers and clinicians can use this information to target medicines to individuals, provide tailored information and psychoeducation, and try to improve personalized care. Historically, there have been biological subgroups in populations diagnosed with schizophrenia that have been misidentified and underdiagnosed. The research team hopes to leverage machine learning to identify biological subgroups and provide proper diagnosis and care.

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Leveraging Natural Language Processing and AI for Characterization of Clinical High Risk

Agrima Srivastava, PhD; Ichan School of Medicine at Mount Sinai

Previous studies have examined suicidal ideations in the CHR population. Research shows the prevalence of death by suicide is 1.25% higher in the CHR population compared to healthy controls, and suicidal behavior occurs in almost 20% of CHR individuals. Natural language processing (NLP) can be used to identify and interpret suicidal ideations in text.

The research team aimed to use NLP to identify linguistic correlates of suicidal ideation in CHR populations. Structured Interview for Psychosis-risk Syndromes (SIPS)/Scale of Prodromal Syndromes (SOPS) were used to characterize CHR. They used a human annotated training dataset with 58,000 Reddit comments to train the NLP model. The neural network model generates an output of probability distribution over emotions. They used this information to generate cumulative distribution function plots for emotions (e.g., anger, sadness, stress, loneliness). They examined the part of speech focused on first person pronouns by conducting a Part of Speech analysis to understand how “I” and “me” associated with suicidal ideation. They observed associations of anger with CHR individuals having recent suicidal ideation.

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Keynote

Developmental Pathways of Risk for Psychosis

Deanna Barch, PhD; Washington University in St. Louis

Dr. Barch and her research team are interested in studying early detection and treatment for individuals who may be at risk for developing psychosis. Large samples are needed from the general population since the prevalence risk is not high.

Dr. Barch presented findings from the Adolescent Brain and Cognitive Development (ABCD) study. The ABCD study enrolled 11,000+ youth ages 9-10 to be followed for 10+ years. There was nationwide enrollment. The study has many goals, including understanding normative developmental trajectories, developing national standards for normal brain development in youth, examining genetic vs. environmental factors, and studying the onset and progression of mental disorders. They are looking into suicidal ideation and attempts in young children, as well as psychosis risk and how that interacts with cannabis exposure. ABCD does not have great representation from rural communities since access to state-of-the art imaging at healthcare facilities is necessary.

The study is currently in year 5-6 depending on the age of the participant. Every year’s assessment includes a full imaging battery, mental and physical health report, and an assessment of related factors. They started using a modified Psychosis Questionnaire-Brief (PQ-B) tailored to young children. At ages 9-10, it can be hard to distinguish between psychotic experiences and typical imagination play. It was important to understand how distressing children found psychosis-like experiences. They created subgroups based on persistent or transient psychotic-like experiences (PLEs) and distressing or non-distressing reactions to them.

Social determinants of health were associated with the persistence of PLEs over time. Interaction between persistent and distressing PLEs were associated with lower cognition and higher anxiety and depression at baseline. They used a cortical parcellation to group networks into a variety of networks. Adults with clinically diagnosable psychotic disorders show increased connectivity in the whole brain, suggesting a lack of organization of networks, and cognitive impairments. Children with distressing PLEs show similar network activity to that of adults with psychosis. There are important differences in terms of location and size of cortical networks in the brain between individuals. The research team used an approach called Template Mapping that looks at an individual’s brain and identifies the unique representation of cortical networks.

The Regional Vulnerability Index looks at effect sizes for illnesses of interest (e.g., schizophrenia, bipolar disorder) to see patterns of effect sizes in different cortices and gyri. Regional Vulnerability Indices in children with persistent and distressing PLEs are most similar to that of adults with schizophrenia. Polygenic risk scores were analyzed for schizophrenia, educational attainment, PLEs, and cross disorders. The PRS for educational attainment seemed similar as that for PLEs. Both were associated with cortical volume and cognition changes which could account for these similarities.

ABCD is generating data that shows the relationship between increased psychotic-like experiences and environmental factors such as poverty, neighborhood depravation, neighbor safety, neighborhood drug offenses, and lead exposure risks. All these environmental were associated with increased risk of PLEs and reduced cortical brain matter, even when controlling for family income and medical history.

ABCD shows that we can identify psychotic-like symptoms in children. In the future, the study will examine interactions of PLEs with substance abuse as the children are getting older and starting to use alcohol and cannabis. The study hopes to identify early intervention, promote broader screening, and generate rich datasets to promote data-driven prediction of outcomes.

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Presentations from AMP SCZ Senior Investigators

CBD as a Novel Treatment for Psychosis

Philip McGuire, MD, PhD; University of Oxford

In the past 20 years our scientific understanding of the CHR population has increased rapidly, but there is a lack of effective treatments for symptoms and early intervention prevention. It is important to understand treatment reliability and acceptability in this diverse population. The cannabis plant contains several different compounds, most popularly tetrahydrocannabinol (THC) and cannabidiol (CBD). Pure cannabidiol can be extracted from the cannabis plant. The higher the THC content of cannabis and lower CBD content, the higher the likelihood of experiencing transient psychotic symptoms (e.g., paranoia). Illicit and recreational cannabis often has a high THC content and low CBD content, resulting in a perception of cannabis as an agent to introduce psychotogenic episodes.

One of the first studies looked at pure clinical-grade CBD and THC and their effects in schizophrenia symptoms. The research team found that cannabidiol does not cause psychotogenic episodes. If CBD is introduced to a participant followed by THC, the CBD seems to block the psychotogenic effect of THC. This led researchers to hypothesize that CBD can have antipsychotic effects. PET scans have looked at potential targets of CBD in the brain, one being the CB1 receptor. CB1 receptors are altered in individuals with a psychotic disorder.

Researchers in Brazil started introducing CBD to patients that were not responding well to antipsychotic medications and found CBD reduced psychotic symptoms. Clinical trials, including placebo-controlled trials, found that CBD improved symptoms in psychosis produced an additional benefit when administered in conjunction with antipsychotic medications. Other studies have found that CBD causes biological action in the hippocampal and striatum regions of the brain, two regions that are associated with the onset of psychosis.

One of the strengths of cannabidiol, especially compared to antipsychotic medications, is its limited known side effects. Some gastrointestinal issues have been noted but no other side effects. CBD has a high acceptability among patients. Antipsychotic medications, on the other hand, is often associated with weight gain, hypotension, sedation, involuntary muscle movements/contractions; stigmatized within the schizophrenia community; and met with resistance among patients.

The University of Oxford’s ongoing clinical trial studies the effects of cannabidiol on psychosis in CHR population at 12-35 years of age. They are investigating the mechanism of action through imaging, blood tests, and other measures before and after 4 weeks of treatment. The study does not plan to intervene with concurrent substance use among participants.

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New Directions in Early-Stage Mental Illness: New Diagnosis and Clinical Trial Innovation

Patrick McGorry, MD, PhD; Orygen; University of Melbourne

New approaches to diagnosis are needed in psychiatry. There is a split in the literature where some argue for a paradigm shift to diagnosis and others favor incremental improvements. Almost all treatments in psychiatry are cross-diagnostic and will have effects beyond the intended symptoms of that mental illness. When studying medications for psychosis, it is important to understand what other systems and functions in the brain they affect. The research team aimed to understand and predict later-stage symptoms of schizophrenia. The biomarkers of schizophrenia may change over time based on whether the individual is experiencing early-stage or late-stage symptoms. The stage of the illness is just as important as the diagnosis to determine the most appropriate and effective treatment path.

There is a global youth mental health crisis, as observed by the U.S. Surgeon General and others. In Australia, there has been a 50% increase in the prevalence of mental disorders in young people since 2007. One clinical study found that intervention in the CHR population improved outcomes, regardless of the selected treatment. Tremendous effects have been made to study the treatment of schizophrenia. A meta-analysis of these studies found that psychosis incidence could be reduced by 45% at 12 months with preventative treatment measures.

The Stepped Care for Youth at Risk of Psychosis (Stepped Care for Youth at Risk of Psychosis – Full Text View – ClinicalTrials.gov)study was a sequential adaptive trial to test a series of nested randomized trials. The trial design adapts to whether the patient is responding or not. Remission rates were lower than expected, while transition rates were slightly higher than expected. Even when remission was achieved, it was hard to maintain. The rate of treatment discontinuation was substantial, as it is in all schizophrenia trials that require follow-up visits. The results from STEP emphasize the need to improve adherence and fidelity of CHR research, improved treatments, and better definitions for the heterogeneity within CHR population to identify treatment-relevant subgroups.

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ERP and fMRI Biomarkers of NMDA-receptor Hypofunction in Schizophrenia and the CHR-P Syndrome: Evidence from Ketamine Challenge Studies

Daniel Mathalon, MD, PhD; University of California, San Francisco

Using pharmacological probes with specific neurotransmitter effects allows us to learn which receptors and systems contribute to psychiatric symptoms and effects. Neurophysiological biomarkers minimize the problems of blinding in research and potential demand characteristics that may blind a participant’s self-reporting. Many EEG biomarkers can be studied in animal models and build a case for testing that drug in humans. Novel drug development is promoted by targeting specific biomarkers and receptors. Ketamine is a rapid acting antidepressant that has taken the nation by storm. It is a dissociative anesthetic and non-competitive antagonist at the NMDA-receptor. Animal studies suggest that ketamine produces its psychotic-like effects by inducing excessive glutamate release.

Disruption of glutamate transmission at the NMDA-receptor by ketamine or another drug inhibits the normal feedback look, leading to an imbalance favoring excitation. Ketamine has been studied as a pharmacological model for NMDR hypofunction in schizophrenia for several decades. Ketamine has been studied alone in schizophrenia research and in conjunction with nicotine. The results show the effect of ketamine in intensity and frequency deviants. Schizophrenia produced a larger decrement in mismatched negativity (MMN) than ketamine across deviant types. Though ketamine was only studied at one dose. At higher doses, ketamine may provide to have a similar effect as schizophrenia on MMN. Ketamine and schizophrenia have similar effects on auditory P300.

Recent findings suggest the thalamus affects integration and coordination of cognitive information and is more than just a relay station as suggested in previous research. Thalamus connectivity was studied in healthy controls and schizophrenia patients. Schizophrenia showed less connectivity than healthy controls in regions in the cerebellum, pons, and thalamus and greater connectivity in the auditory complex, pre- and post-central gyrus, and occipital lobe. Hypoconnectivity of the thalamus has been associated with positive symptoms of schizophrenia. Ketamine induces thalamic hyperconnectivity with sensory motor regions, like schizophrenia. Ketamine may serve as a pharmacological model for some of schizophrenia’s effects on the brain, but not all.

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Wrap-Up

Brandon Staglin, MS; OneMind

Today, we have learned a lot about new directions for research and opportunities for improvements to diagnosis and treatment. Our society is facing a shadow crisis. People with schizophrenia are suffering throughout the world. Though schizophrenia is still stigmatized in our society. Lived experience with schizophrenia can feel like being trapped in the psychosis vortex. To those with schizophrenia, the path to treatment can feel like one step forward, two steps back. Participating in research and clinical trials can lead to breakthroughs for some participants.

OneMind aims to transforms the world’s mental health through science and media. 43 rising star awards have been funded to empower scientists to uncover advancements. If all young people experiencing mental illness can receive care through medicine, drive, love, community, and cause, they can drastically increase their chances to live a healthy life.

The mission to improve care through scientific research faces challenges. The capacity for treatment for those experiencing psychosis is far below demand as only 10% of those needing care have access. Increased understanding of the side effects of drugs and reduced trust in the medical system present growing challenges. Individuals need to be engaged earlier. Safer, more reliable, and more precise treatments need to be developed. Innovative and diverse treatment models must be tested at scale. The network must be grown to reach as many people as possible.

Members of AMP SCZ are encouraged to keep investigating, educate the public, advocate for policy improvements, and consider commercializing innovations produced. Together, this group can move mountains for those living with schizophrenia.

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Last Reviewed on February 14, 2024