Ourunderstandingofthegeneticsofschizophreniaisadvancingatarapidpaceandanincreasingnumberof risk-associated polymorphisms and variants have been discovered. Because the majority of these variants reside in intergenic, intronic and other non-coding sequences, a precise variant or target gene for schizophrenia has not been identified. Therefore, a major challenge lies in designing testable hypotheses to elucidatethepotentialfunctionofdisease-associatednon-codingDNA.Manyoftheriskvariantsarethoughtto affect gene expression through alterations of regulatory elements, including long-range enhancer sequences physicallyinteractingwithtranscriptionstartsitesseparatedalongthelineargenomeofDNA.
The aim ofthis proposalistomaptheregulatorysequences(oropenchromatin)indiscretecellularpopulations(neuronsand glia)derivedfromtwohumancorticalbrainregionsinalargecohortofcaseswithschizophreniaandcontrols, followed by generation of a high-resolution quantitative trait loci (QTL) map of regulatory sequences. In addition, high resolution expression quantitative trait loci (eQTLs), mapped in the same samples and brain regions, will be leveraged to identify schizophrenia associated non-coding regions that are simultaneously associated with differential exposure of regulatory regions (open chromatin) and gene expression of nearby genes(eQTLs).Long-rangeenhancer-promoterinteractionsofgenespotentiallyregulatedbyopenchromatin sequenceswillbemappedinhumanpostmortembraintissueusingchromosomeconformationcapture.Using the existing schizophrenia-related large-scale molecular data and the high-impact, high-resolution, complementarydatasetsgeneratedthroughtheproposedstudies,wewilldevelopmultiscalenetworkmodels causally linked to schizophrenia. The action of individual genes on molecular and cellular schizophrenia- associated processes and the molecular networks identified in our studies will be validated using iPS-cell- derived cultures of human neuronal cell systems. The multidimensional approach presented here provides a roadmap to place schizophrenia genetic risk variants in molecular contexts to help identify the underlying regulatoryandexpressionmechanismsthroughwhichtheyact.
The VHA Independent Budget Report for FY2003 listed 104,593 Veterans being treated for schizophrenia, accounting for nearly 12% of the VA?s total healthcare costs. Multiscale network models causally linked to schizophrenia will be developed based on existing schizophrenia-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 schizophrenia. This holds the potential for direct translational and clinical applications of which may reinvigorate stalled drug development that can improve the mental health of our Veterans.
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