Our understanding of the genetics of bipolar disorder (BD) is advancing at a rapid pace. An increasing number of risk-associated polymorphisms and variants are being found, many of which reside in intergenic, intronic and other non-coding sequences. A major challenge lies in designing testable hypotheses to elucidate the potential function of disease-associated non-coding DNA. Many of these sequences are thought to exert regulatory functions, including long-range enhancer elements physically interacting with transcription start sites separated along the linear genome, sometimes by many kilobases of DNA. This proposal aims to generate a high- resolution quantitative trait loci (QTL) map of open chromatin in discrete cellular populations (neurons and glia) derived from two human cortical brain regions relevant to the pathophysiology of BD. We will then leverage high resolution expression quantitative trait loci (eQTLs), mapped in the same samples and brain regions, to identify BD associated noncoding regions that are simultaneously associated with differential exposure of regulatory regions (open chromatin) and gene expression of nearby genes (eQTLs). Long-range enhancer- promoter interactions of genes potentially regulated by open chromatin sequences will be mapped in human postmortem brain tissue using chromosome conformation capture, an innovative approach in neuroepigenetics. Multiscale network models causally linked to BD will be developed based on existing BD- related large-scale molecular data and the high-impact, high-resolution, complementary datasets generated through the proposed studies. Using iPS-cell-derived cultures of human neuronal cell systems, we will employ high-throughput molecular and cellular screening assays to not only validate the actions of individual genes on molecular and cellular BD-associated processes, but also to validate the molecular networks identified in our studies. The multidimensional approach presented here provides a roadmap to place BD genetic risk variants in molecular contexts to help identify the underlying regulatory and expression mechanisms through which they act. As a service to the BD research community, we will provide dramatically improved general access to large- scale, multidimensional datasets, together with systems level analyses of these datasets.

Public Health Relevance

Bipolar disorder (BD) is a common, chronic, and often disabling disorder that affects 1-4% of the US population. Multiscale network models causally linked to BD will be developed based on existing BD-related large-scale molecular data and the high-resolution complementary epigenome datasets generated through the proposed work. We will explore functional chromatin loopings at risk-associated DNA variants and polymorphisms in brain tissue and use neuronal cells grown in culture from reprogrammed skin cells to validate the molecular networks predicted to drive BD.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Genetics of Health and Disease Study Section (GHD)
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Arguello, Alexander
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Icahn School of Medicine at Mount Sinai
Schools of Medicine
New York
United States
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