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Integrating Multi-Dimensional Data to Explore Mechanisms Underlying Psychiatric Phenotypes

NAMHC Concept Clearance

Presenter

Linda Brady, Ph.D.
Director, Division of Neuroscience and Basic Behavioral Science (DNBBS)

Goal

This initiative will support development of advanced bioinformatics and statistical tools to integrate genomic, environmental, and phenomic data to link various complex phenotypes leading to novel diagnostic tools, clinical trials, and potential targets for intervention in mental disorders.

Rationale

Recent NIMH investments have led to an enormous depth of genomic data, extensive brain imaging data, and new clinical assessments to define the etiology, pathophysiology, and trajectories of mental disorders. Although many bioinformatics tools are available, existing tools do not offer effective means to integrate the breadth of data types collected across these studies, which may include neuroimaging data, physiological data, clinical data, and genomic data. Neither are the available tools capable of offering efficient statistical analyses of multi-dimensional data for diagnostic or outcomes research. Therefore, a biologically grounded approach is needed to reduce the plausible combination of genomic regions and various types of phenotypes in order to effect a drastic reduction in the number of statistical tests needed to reach meaningful conclusions.

This initiative will support development of holistic analytical approaches to model biological systems accurately, using data from various platforms. NIMH expects newly developed analytical tools will help to establish links between biological networks, environmental factors, and downstream psychiatric phenotypes, which will ultimately provide a foundation for identifying new diagnostic tools and personalized therapeutic methods.

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