UNDERSTANDING MECHANISMS OF RISK AND RESILIENCE THROUGHOUT BRAIN & BEHAVIOR DEVELOPMENT
THE CHALLENGES THAT DRIVE OUR WORK
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To understand why some youths who grow up with developmental stress become suicidal, while others do not (resilient).
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To timely identify those at risk for serious psychopathology and divert the developmental trajectory from risk to resilience.
THE QUESTIONS WE ASK
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What are the mechanisms that drive variability in the development of brain and behavior?
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How do environmental (E) exposures (e.g., trauma, neighborhood environment) interact among themselves (E X E), and with biological (e.g., genetic (G)) factors (G X E), to shape developmental trajectories of youth?
OUR VISION
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Promote resilience and prevent suicide and serious psychiatric outcomes in youths.
OUR MISSION
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Conduct impactful translational science aimed at reducing youth mental health burden.
OUR RESEARCH
In the BarziLab, we use multiple methods to understand variability in the development of brain and behavior.
We study how a myriad of environmental exposures (such as trauma and socioeconomic factors) dynamically interact among themselves, and with biological factors (such as genetic and epigenetic) to shape the development of brain and behavior.
OUR VALUES
We collect and analyze large human datasets.
We do collaborative interdisciplinary science.
We work with basic scientists to inform mechanistic gaps that can only be investigated in animal models.
OUR APPROACH
CONDUCT LONGITUDINAL STUDIES
BarziLab studies at-risk youths throughout development in attempt to elucidate the immune mechanisms associated with risk and resilience to developmental stress.
ANALYSE EXISTING LARGE-SCALE INFORMATIVE DATASETS
BarziLab uses available human datasets that can inform on the factors (features) that drive risk and resilience. We are specifically interested in integrating data from multiple levels of environmental exposures (exposome) with large scale biological data (e.g., genomics, imaging) and other available data sources (such as electronic health records) in order to better understand complex mechanisms of development and to allow prediction of adverse behavioural outcomes such as suicidal behavior.
RECENT PUBLICATIONS
COLLABORATORS
We aim to solve complicated challenges that require a multidisciplinary team of clinicians,
data scientists, geneticists, immunologists, developmental psychologists, basic neuroscientists and computational biologists.
SELECTED PROJECTS
Allostatic load in early adolescence: gene - environment contributions and relevance for mental health