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Principal Investigator: MARIA JALBRZIKOWSKI
Organization: BOSTON CHILDREN'S HOSPITAL
Fiscal Year: 2024
Award: $773,425
Funding agency: National Institute of Mental Health
Project Summary/Abstract
Converging lines of evidence support the hypothesis that deviations from typical brain structure development
take place prior to psychosis onset, while ‘big data’ neuroimaging studies of adults with psychosis find subtle,
widespread gray matter disruptions in the brain. In this proposal, we will synergize knowledge about normative
structural neurodevelopment and findings of structural brain aberrations in adults with psychosis to develop
cost-effective brain-based markers of psychosis risk in youth. To improve identification of those at greatest risk,
we leverage results from large-scale structural neuroimaging studies of psychosis to create a ‘Psychosis
Neuroimaging Score’, a cumulative summary score that reflects one’s psychosis liability. We first aim to
transport the Psychosis Neuroimaging Score to youth by incorporating crucial aspects of structural brain
development. In Aim 1, we will characterize the normative developmental trajectory of the Psychosis
Neuroimaging Score by harmonizing many archival datasets of normative development (N>5,000, 2-30 years
old). We will then evaluate how greater age-associated deviation from the aggregate Psychosis Neuroimaging
Score differentiates youth with psychosis spectrum symptoms from typically developing youth in the
Philadelphia Neurodevelopmental Cohort (N=1209, 10-22 years old). In Aim 2, we plan to examine how
greater age-associated deviation from the aggregate Psychosis Neuroimaging Score predicts distinct
developmental trajectories associated with psychotic-like experiences in youth from the Adolescent Brain and
Cognitive Development Study (N=11,875). We will also assess the extent to which known psychosis risk
factors (e.g., family history of psychosis, obstetric complications, trauma) contribute to characterization of these
trajectories. Finally, in Aim 3, we propose to use measurement-in-error modeling to establish a functional
relationship between Psychosis Neuroimaging scores generated from 3T MRI scans and those generated
using low-field MRI scans in a community sample of youth. Results from this study will allow us to create more
affordable, clinically accessible biological indicators of severe psychopathology, ultimately improving
identification of young people at greatest risk and allowing earlier, more effective interventions.
Terms: <12-20 years old><20 year old><20 years of age><21+ years old><Adolescence><Adolescent><Adolescent Youth><Adult><Adult Human><Age><Approaches to prevention><Behavioral><Big Data><BigData><Biological><Biological Markers><Brain><Brain Nervous System><Brain region><Childhood><Classification><Clinical><Communities><Data><Data Set><Development><Diagnosis><Distress><Early Diagnosis><Early Intervention><Early identification><Encephalon><Family Medical History><Family Medical History Epidemiology><Family history of><Future><Generalized Growth><Genetic><Growth><Height><Heterogeneity><Image><Individual><Knowledge><MR Imaging><MR Tomography><MRI><MRI Scans><MRIs><Magnetic Resonance Imaging><Magnetic Resonance Imaging Scan><Maps><Measurement><Measures><Medical Imaging, Magnetic Resonance / Nuclear Magnetic Resonance><Mental disorders><Mental health disorders><Methodology><Methods><Modeling><NMR Imaging><NMR Tomography><Neural Development><Nuclear Magnetic Resonance Imaging><Performance><Persons><Philadelphia><Predicting Risk><Prevention approach><Primary Prevention><Proxy><Psychiatric Disease><Psychiatric Disorder><Psychopathology><Psychoses><Psychotic Disorders><Research><Risk><Risk Factors><Risk Marker><Sampling><Schizophrenia><Schizophrenic Disorders><Severities><Structure><Symptoms><Systematics><Testing><Time><Tissue Growth><Translating><Trauma><Weight><Youth><Youth 10-21><Zeugmatography><abnormal psychology><adolescence (12-20)><adulthood><age 20 years><age associated><age correlated><age dependent><age linked><age related><age specific><ages><archival data><archived data><bio-markers><biologic><biologic marker><biomarker><brain based><case control><case-controlled><child health care provider><child healthcare provider><cognitive development><cohort><community setting><cost effective><cost effectiveness><data archived><dementia praecox><developmental><early adulthood><early detection><effective intervention><emerging adult><forecasting risk><gray matter><imaging><improved><improved outcome><indexing><innovate><innovation><innovative><juvenile><juvenile human><mental illness><neural><neural imaging><neuro-imaging><neurodevelopment><neuroimaging><neurological imaging><novel><obstetrical complication><ontogeny><pediatric><pediatric care provider><pediatric health care provider><pediatric healthcare provider><pediatric provider><pediatrician><polygenic risk score><portability><predict risk><predict risks><predicted risk><predicted risks><predicting risks><predictive risk><predicts risk><prevent><preventing><psychiatric illness><psychological disorder><psychosis risk><psychotic illness><psychotic symptoms><psychotic-like experiences><risk prediction><risk predictions><risk predictor><risk predictors><schizophrenic><substantia grisea><synergism><twenty year old><twenty years of age><weights>