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Using whole genome sequencing to identify risk alleles for susceptibility to schizophrenia

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TitleInfo
Title
Using whole genome sequencing to identify risk alleles for susceptibility to schizophrenia
Name (type = personal)
NamePart (type = family)
Davis
NamePart (type = given)
Gillian K.
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Gillian K. Davis
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author
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Matise
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Tara
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Tara Matise
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Advisory Committee
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chair
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Firestein
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Bonnie
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Bonnie Firestein
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Advisory Committee
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internal member
Name (type = personal)
NamePart (type = family)
Brzustowicz
NamePart (type = given)
Linda
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Linda Brzustowicz
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Advisory Committee
Role
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internal member
Name (type = personal)
NamePart (type = family)
Bartlett
NamePart (type = given)
Christopher
DisplayForm
Christopher Bartlett
Affiliation
Advisory Committee
Role
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outside member
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NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Graduate Studies
Role
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school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2017
DateOther (qualifier = exact); (type = degree)
2017-10
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2017
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Schizophrenia is a complex idiopathic neuropsychiatric illness that affects approximately 1% of the general population. Family, twin, and adoption studies indicate a high heritability and strong genetic element to the disease with first degree relatives demonstrating an increased risk of about 10% and monozygotic concordance rates as high as 50%. These values represent the probability of developing schizophrenia based on the presence of genetic components. The high heritability has led to individual studies and meta-analyses being able to produce significant evidence of linkage to specific locations, but studies that used large number of pedigrees have failed to produce statistically significant linkage results. Genome Wide Association Studies of schizophrenia have also produced similarly mixed results. One interpretation of these mixed linkage and association results is that factors such as small effect size and uncontrolled phenotypic variation require very large samples to overcome. This thesis focuses on a different interpretation: genuine genetic differences between definable subsets can mask both linkage and association, and that this problem is worsened in studies that use large samples where the entire sample is analyzed as if it were a genetically homogenous group. The work presented herein begins with linkage studies performed on 22 medium- sized Canadian pedigrees (n=304 individuals) of German or Celtic descent initially recruited if at least three subjects with schizophrenia were available for study. Association studies were conducted on an expanded sample of 30 pedigrees (n=573). Subjects in this sample have been followed for up to 20 years allowing for continued observation of diagnostic stability. We have identified linkage disequilibrium between schizophrenia and single nucleotide polymorphisms (SNPs) from six discrete genomic regions located under linkage peaks within this sample. We hypothesize that SNPs that generated compelling evidence of association (PPLD|L >= 0.2) produce these scores because they either are, or are in, high LD (r 2 >= 0.8) with functional variants that increase susceptibility to schizophrenia. To that end, whole genome sequencing data from ten individuals within this study (n=10) was analyzed to generate a list of variants within 500 kb upstream and downstream of each risk SNP. A pipeline was created to determine whether or not each SNP in this list was a candidate for further analysis by assessing its LD to the risk SNPs identified by the association studies described above. SNPs determined to be candidates were then genotyped in the entire sample (n=378) so that association could be accurately assessed. Finally, association scores were compared between risk SNPs and candidate SNPs, with variants having higher PPLD|L scores than the referring SNP identified as potential functional candidates. Six SNPs from one genomic region produced higher PPLD|L scores than the referring SNP and so will replace the referring SNP as candidates for further functional analysis. These six SNPs first will be evaluated for additional candidate SNPs 500 kb up- and down-stream in order to determine the best SNP in the region according to the PPLD|L. Additional SNPs have also been identified in some of the other genomic regions that need to be assessed for LD in the full sample. The SNP or SNPs producing the strongest LD signal in each region will need to be further assessed by functional assays to determine their potential role in schizophrenia susceptibility.
Subject (authority = RUETD)
Topic
Microbiology and Molecular Genetics
Subject (authority = ETD-LCSH)
Topic
Schizophrenia--Diagnosis
RelatedItem (type = host)
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Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_8482
PhysicalDescription
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electronic resource
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application/pdf
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text/xml
Extent
1 online resource (xi, 113 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Gillian K. Davis
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3TT4V31
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

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The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Davis
GivenName
Gillian
MiddleName
K.
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-10-02 11:08:20
AssociatedEntity
Name
Gillian Davis
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Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
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Author Agreement License
Detail
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.
RightsEvent
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-10-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2019-10-31
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after October 31st, 2019.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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2017-10-02T13:25:27
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2017-10-02T13:25:27
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