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Research that aims to uncover risk factors and biomarkers for severe mental illness in young people, in order to improve detection and prevention
Identification of the Neural Circuitry of Persistent Negative Symptoms in First Episode Schizophrenia
Effective treatments for persistent negative symptoms in patients who have experienced their first episode of schizophrenia are a major unmet need, and the neural circuitry of these symptoms remains unknown. This study, led by Dr. Aristotle Voineskos, aims to identify neural circuitry biomarkers of persistent negative symptoms in this patient group. Identifying biomarkers can provide essential neurobiological information to accelerate intervention efforts for negative symptoms early in the disease progression. As a secondary aim, the study will use neuroimaging data to predict longitudinal persistent negative symptom status; this innovative approach would rapidly identify patients earlier who might suffer from these symptoms and will serve as an important step in providing a more personalized approach to care, thus optimizing the outcomes for patients suffering from these debilitating symptoms.
Uncovering Pathways to Psychosis to Enhance Early Identification and Prevention Efforts: Characterizing Psychosis Risk After Antecedent Disorders
Psychotic disorders such as schizophrenia cause major impairments throughout life. The sooner effective treatment is initiated after the onset of this illness, the better the outcome and prognosis for the patient. However, timely treatment is only possible if the psychosis is recognized at the beginning. Affiliate Scientist Dr. Wanda Tempelaar is working with the Institute for Clinical Evaluative Sciences (ICES) to use routinely collected health data to investigate trajectories of psychiatric disorders. ICES is a publicly funded, not-for-profit research institute and its research is highly regarded in Canada and abroad. ICES data is widely used by governments, hospitals, planners and practitioners to make decisions about care delivery and to develop policy. This study aims to investigate trajectories of mental health disorders preceding the onset of psychotic disorder in youth. Findings from this work will significantly advance our understanding of risk trajectories, to improve early detection and intervention.
Using Electrophysiological Indices of Auditory Processing to Estimate Psychosis Risk in Clinical High Risk Youth
Efforts to identify people at high risk of developing schizophrenia, and prevent its disability, are crucial. High-risk patients, who have milder forms of schizophrenia symptoms, have 400 times the normal risk of developing the disorder. Yet, the majority of high-risk patients will not develop the illness. Providing them with unnecessary psychiatric treatments may expose them to unnecessary risks — including side effects and stigma — and is costly and time-consuming. To target treatment to those most in need, new tests are needed to predict which patients are most likely to develop schizophrenia and/or have long-term persistent symptoms. This study, led by Dr. Michael Kiang, and funded by the Miner’s Lamp Innovation Fund in Prevention and Early Detection of Severe Mental Illness, aims to examine the use of electroencephalographic (EEG or “brainwave”) biomarkers to further predict individual disease trajectories within high-risk groups, narrowing down the relatively large group of people considered at high risk for developing psychosis.
To date, this study has detected a number of brainwave abnormalities in patients at high risk for psychosis, and has found that the severity of some of these abnormalities predicts future disability versus recovery. The results could lay the groundwork for a practical prognostic test, enabling researchers to target treatment trials toward those at greatest risk of developing psychosis. Data collection is ongoing and has resulted in several peer-reviewed journal publications so far.
Synaptic density as a trait marker of Clinical High Risk (CHR) for Psychosis: an [18F]SynVesT-1 positron emission tomography (PET) study
Young people categorised as Clinical High Risk (CHR) are considered particularly vulnerable to developing psychosis. The CHR phase is an important juncture in an individual’s mental health because preventative interventions may reduce the risk of progression to a number of negative outcomes, including the development of schizophrenia. Prediction-oriented research is needed to identify markers of psychosis risk and pave the way for preventative interventions. This study, led by Dr. Omair Husain, utilizes a novel PET approach to examine the change over time in synaptic density in individuals with CHR. Findings from this study aim to shed light on the neurobiology of psychosis risk states, and potential quantifiable biomarkers to inform the development of targeted interventions at the earliest stages in the development of psychosis.
Gut Microbiome and Metabolic Dysfunction in Antipsychotic Naïve Patients (AP GUT)
This study, led by Drs. Margaret Hahn and Mahavir Agarwal, in collaboration with McMaster University, will examine the effects of antipsychotic medications in young adults who are starting them for the first time. Specifically, the study will measure changes in the gut microbiome and metabolic measures (i.e., weight, insulin sensitivity, glucose tolerance, lipids) in the first 12 weeks of antipsychotic use in antipsychotic-naïve individuals compared to matched healthy controls.
Early Detection of Aggression in First Episode Psychosis: A Structural and Functional Magnetic Resonance Imaging Study
Using functional magnetic resonance imaging (fMRI), Dr. Nathan Kolla’s study is aimed at providing neuroscience evidence that brain structure and function can undergo positive adaptations following a psychosocial treatment designed to reduce impulsivity and conduct-disordered behaviour known as Stop, Now and Plan (SNAP). The results of this study will have important implications for the treatment of justice-involved youth and could also lead to the development of simple biological tests that might help determine who is most likely to benefit from SNAP.
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