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Altered microRNA regulatory networks in individuals with schizophrenia
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Altered microRNA regulatory networks in individuals with schizophrenia
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ETD_2030
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http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051882
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eng
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theses
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Microbiology and Molecular Genetics
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Topic
Schizophrenia--Genetic aspects
Abstract
MicroRNAs (miRNAs) are small, endogenous non-coding RNA molecules that interact with messenger RNAs to direct their post-transcriptional repression. Like messenger RNAs, miRNAs exhibit distinct spatiotemporal expression signatures. The human brain, marked by tremendous structural and functional complexity, has an especially diverse miRNA expression profile. Altered expression or function of miRNAs has been linked to several neuropsychiatric disorders, including Alzheimer’s disease, Tourette’s syndrome, and Schizophrenia.
Schizophrenia is a debilitating psychiatric disorder that affects 0.5-1% of the world’s population. Family and twin studies suggest a strong genetic component to the disease, but efforts to isolate causal variants have been hampered by genetic heterogeneity, as well as interacting environmental factors. The underlying goal of this dissertation research is to investigate altered miRNA regulatory networks in individuals with schizophrenia spectrum disorders.
The work presented herein begins with a miRNA expression atlas of the developing human brain. Tissue samples representing fetal, early postnatal, and adult time points (n = 48 total) were analyzed using microarrays, and 312 miRNAs were classified according to their temporal expression patterns. This work goes on to describe the development of a multiplexed, bead-based SNP genotyping assay which was applied in a family-based genetic association study of the miRNA processing gene DGCR8. Comprehensive miRNA expression analysis of post-mortem brain tissue samples from subjects with schizophrenia, subjects with bipolar disorder, and psychiatrically healthy controls (n = 35 each group) revealed significant under-expression of several miRNAs in individuals with major psychosis, substantiating a proposed defect in miRNA processing. A pattern-based algorithm called miRSNiPer was developed, and used to predict SNPs that alter miRNA binding sites. A panel of 48 putative “miRSNPs” were genotyped in 25 extended pedigrees, and a SNP in the 3’UTR of H3F3B showed evidence of association (PPLD = 17%) to schizophrenia and schizoaffective disorder. Finally, the miRSNiPer algorithm was used to identify enriched genes and pathways among the targets of mis-expressed miRNAs.
Schizophrenia is a debilitating psychiatric disorder that affects 0.5-1% of the world’s population. Family and twin studies suggest a strong genetic component to the disease, but efforts to isolate causal variants have been hampered by genetic heterogeneity, as well as interacting environmental factors. The underlying goal of this dissertation research is to investigate altered miRNA regulatory networks in individuals with schizophrenia spectrum disorders.
The work presented herein begins with a miRNA expression atlas of the developing human brain. Tissue samples representing fetal, early postnatal, and adult time points (n = 48 total) were analyzed using microarrays, and 312 miRNAs were classified according to their temporal expression patterns. This work goes on to describe the development of a multiplexed, bead-based SNP genotyping assay which was applied in a family-based genetic association study of the miRNA processing gene DGCR8. Comprehensive miRNA expression analysis of post-mortem brain tissue samples from subjects with schizophrenia, subjects with bipolar disorder, and psychiatrically healthy controls (n = 35 each group) revealed significant under-expression of several miRNAs in individuals with major psychosis, substantiating a proposed defect in miRNA processing. A pattern-based algorithm called miRSNiPer was developed, and used to predict SNPs that alter miRNA binding sites. A panel of 48 putative “miRSNPs” were genotyped in 25 extended pedigrees, and a SNP in the 3’UTR of H3F3B showed evidence of association (PPLD = 17%) to schizophrenia and schizoaffective disorder. Finally, the miRSNiPer algorithm was used to identify enriched genes and pathways among the targets of mis-expressed miRNAs.
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electronic resource
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xi, 211 p. : ill.
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Ph.D.
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Includes bibliographical references (p. 190-210)
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by Michael P. Moreau
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Moreau
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Michael P.
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1983-
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Michael P. Moreau
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Matise
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Tara
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Tara Matise
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Brzustowicz
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Linda
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Linda Brzustowicz
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Millonig
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James
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James Millonig
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Padgett
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Richard
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Richard Padgett
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Rutgers University
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Graduate School - New Brunswick
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2009
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2009-10
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xx
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Rutgers University Electronic Theses and Dissertations
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Graduate School - New Brunswick Electronic Theses and Dissertations
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doi:10.7282/T3891610
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ETD doctoral
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Copyright protected
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Open
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Moreau
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Michael
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Michael Moreau
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Rutgers University. Graduate School - New Brunswick
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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