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and treatment of mental illnesses.

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From Genes to Biology: Scalable Approaches for Biological Characterization of Mental Illness Risk Genes


Rebecca Beer, Ph.D.
Division of Neuroscience and Basic Behavioral Science


The current understanding of the relationship between genetic and phenotypic variation across biological scales is limited. One of the main bottlenecks in translating from genes associated with mental illnesses to disease biology lies in the lack of scalable experimental platforms that can extend the unbiased nature of gene discovery to the discovery of biological mechanisms. This initiative aims to fill that gap by optimizing and implementing new scalable technologies for functionally characterizing many genes in parallel to reveal mechanisms underlying disorders such as autism and schizophrenia. Such approaches would assay a variety of neurobiological processes (gene regulation, cellular signaling, synaptic transmission, development) across biological scales (cells, circuits, tissues, organisms) in multiple systems with introduced mutations in a rigorously selected, large set of genes. The data resulting from the effort would be integrated with existing datasets to create a comprehensive database of harmonized functional characterization of many risk-associated genes at multiple biological scales.

This initiative would aim to support research to:

  1. Develop a systematic and scalable approach for broadly characterizing the developmental, molecular, cellular, and systems-level function of genes and support optimization of innovative assays of central nervous system function.
  2. Leverage or develop novel, statistical, and computational methods to integrate data across modalities, levels of organization, and genes to make robust causal inferences into shared and unique disease mechanisms.
  3. Enable innovation in high-throughput biology by centralizing and harmonizing data, metadata, and tools to support the integration of diverse datasets across scales and experimental systems. Data created using these resources should be made openly available alongside bioinformatic, statistical, and computational tools.

This initiative will be informed by ongoing NIH/NIMH efforts, including large-scale human genetic studies, functional genomic studies, and cell atlas studies, and will foster the large-scale implementation of transformative tools and technologies emerging from the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative .


Most attempts to evaluate the impact of mental illness-associated genes or variants on brain function have been limited in scale to one or a few genes against a relatively narrow range of biological endpoints. Systematic efforts are hindered by our ability to fully capture the spectrum of potential disease-relevant biological phenotypes across a sufficiently large number of genes or variants in a cost-efficient and comprehensive way. New scalable technologies are emerging that address these limitations, offering the opportunity to probe the role of genetic variation in neurodevelopmental and psychiatric disorders with systematic and coordinated assays that more thoroughly capture the genetic and phenotypic space at a scale and breadth not currently covered by existing NIMH efforts.