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Vanderbilt University
1.
Jeff, Janina Maria.
Admixture mapping and subsequent finemapping suggests novel loci for type 2 diabetes in African Americans.
Degree: MS, Interdisciplinary Studies: Applied Statistics, 2012, Vanderbilt University
URL: http://hdl.handle.net/1803/15329 
► Type 2 diabetes (T2D) is a complex metabolic disease that disproportionately affects African Americans. Obesity is a major risk factor for T2D, and it is…
(more)
▼ Type 2 diabetes (T2D) is a complex metabolic disease that disproportionately affects African Americans. Obesity is a major risk factor for T2D, and it is postulated that chronic inflammation possibly stemming from adipose tissue macrophages and T cells plays a key role. Genome-wide association studies (GWAS) have identified over 20 disease loci that contribute to T2D in European Americans but few studies have been performed in admixed populations.
We first performed a GWAS of 1,563 African Americans from the
Vanderbilt Genome-Electronic Records Project and Northwestern
University NUgene Project as part of the electronic Medical Records and Genomics (eMERGE) network. We successfully replicate an association in TCF7L2, previously identified by GWAS in our African American dataset. We were unable to identify novel associations at p<5.0x10-8 by GWAS. Admixture mapping disease loci in recently admixed populations is a powerful method used to identify disease loci in African Americans. Using admixture mapping, we sought to identify novel disease loci in the genome with T2D. Our admixture scan revealed multiple candidate genes with T2D, including TCIRG1, a T-cell immune regulator expressed in the pancreas and liver and not previously implicated in T2D. We performed a subsequent fine-mapping analysis to further assess the association with TCIRG1 and T2D in >5,000 African Americans. We successfully identified 13 independent associations in TCIRG1, CHKA, and ALDH3B1 genes on chromosome 11. Our results suggest a novel region on chromosome 11 identified by admixture mapping associated with T2D in African Americans and warrants additional replication and validation in this region.
Advisors/Committee Members: Jonathan Haines (committee member), Dana Crawford (committee member).
Subjects/Keywords: admixture mapping; statistics; human genetics; type 2 diabetes
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APA (6th Edition):
Jeff, J. M. (2012). Admixture mapping and subsequent finemapping suggests novel loci for type 2 diabetes in African Americans. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/15329
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Jeff, Janina Maria. “Admixture mapping and subsequent finemapping suggests novel loci for type 2 diabetes in African Americans.” 2012. Thesis, Vanderbilt University. Accessed March 08, 2021.
http://hdl.handle.net/1803/15329.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Jeff, Janina Maria. “Admixture mapping and subsequent finemapping suggests novel loci for type 2 diabetes in African Americans.” 2012. Web. 08 Mar 2021.
Vancouver:
Jeff JM. Admixture mapping and subsequent finemapping suggests novel loci for type 2 diabetes in African Americans. [Internet] [Thesis]. Vanderbilt University; 2012. [cited 2021 Mar 08].
Available from: http://hdl.handle.net/1803/15329.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Jeff JM. Admixture mapping and subsequent finemapping suggests novel loci for type 2 diabetes in African Americans. [Thesis]. Vanderbilt University; 2012. Available from: http://hdl.handle.net/1803/15329
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Vanderbilt University
2.
Dumitrescu, Logan Caneel.
Identificatiion and Characterization of Genetic Variants Associated with Lipid and Lipoprotein Levels.
Degree: PhD, Human Genetics, 2011, Vanderbilt University
URL: http://hdl.handle.net/1803/11282
► Low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels are well known independent risk factors for cardiovascular disease. Other lipoproteins, such as…
(more)
▼ Low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels are well known independent risk factors for cardiovascular disease. Other lipoproteins, such as Lp(a), are also emerging, independent risk factors as increasing epidemiologic evidence suggests. Lipid-associated single-nucleotide polymorphisms (SNPs) are being discovered in genome-wide association studies (GWAS) in samples of European descent, but little data exist in other populations. Therefore, there is a strong need to characterize the effect sizes and allele frequencies of these GWAS-identified variants in a diverse, population-based cohort. Also, despite the ever-growing number of loci detected by GWAS, the proportion of trait variation explained is collectively small. To investigate this missing heritability, it is important to continue to identify novel variants that are associated with lipid levels and to explore gene-environment interactions, which may also contribute to trait variation.
The primary objective of this work was to identify and characterize common genetic variants that explain a proportion of the inter-individual variability in lipids levels, including LDL-C, HDL-C, TG, and Lp(a) levels. To achieve this goal, I selected a set of SNPs associated with lipid levels from the literature and demonstrated that the majority of associations replicate and generalize in a diverse, independent cohort. An additional GWAS of children was used to discover a novel variants associated with LDL-C, HDL-C, and TG. I also performed a candidate gene study and determined that common variants in LPA were associated with Lp(a) levels. Lastly, I identified several environmental modifiers of replicated variants associated with LDL-C, HDL-C, and TG.
Advisors/Committee Members: Dana Crawford (committee member), Jonathan Haines (committee member), Mary Relling (committee member), Jay Fowke (committee member), Marylyn Ritchie (Committee Chair).
Subjects/Keywords: genetics; epidemiology; gwas; candidate gene study; lipids; lipoproteins; cardiovascular disease
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APA (6th Edition):
Dumitrescu, L. C. (2011). Identificatiion and Characterization of Genetic Variants Associated with Lipid and Lipoprotein Levels. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/11282
Chicago Manual of Style (16th Edition):
Dumitrescu, Logan Caneel. “Identificatiion and Characterization of Genetic Variants Associated with Lipid and Lipoprotein Levels.” 2011. Doctoral Dissertation, Vanderbilt University. Accessed March 08, 2021.
http://hdl.handle.net/1803/11282.
MLA Handbook (7th Edition):
Dumitrescu, Logan Caneel. “Identificatiion and Characterization of Genetic Variants Associated with Lipid and Lipoprotein Levels.” 2011. Web. 08 Mar 2021.
Vancouver:
Dumitrescu LC. Identificatiion and Characterization of Genetic Variants Associated with Lipid and Lipoprotein Levels. [Internet] [Doctoral dissertation]. Vanderbilt University; 2011. [cited 2021 Mar 08].
Available from: http://hdl.handle.net/1803/11282.
Council of Science Editors:
Dumitrescu LC. Identificatiion and Characterization of Genetic Variants Associated with Lipid and Lipoprotein Levels. [Doctoral Dissertation]. Vanderbilt University; 2011. Available from: http://hdl.handle.net/1803/11282
Vanderbilt University
3.
Koran, Mary Ellen Irene.
Imaging and Genetics of Two Amyloid Related Diseases: Alzheimer’s Disease and Down Syndrome.
Degree: PhD, Human Genetics, 2014, Vanderbilt University
URL: http://hdl.handle.net/1803/10539
► Alzheimer’s Disease is an irreversible, degenerative disease of the brain that accounts for a majority of dementia cases each year, in both the general population…
(more)
▼ Alzheimer’s Disease is an irreversible, degenerative disease of the brain that accounts for a majority of dementia cases each year, in both the general population and in patients with Down Syndrome. The advancement of in vivo imaging modalities that detect the neuropathologies associated with both Down Syndrome and Alzheimer’s Disease present new opportunities to explore these diseases in living human subjects. Imaging biomarkers not only permit earlier, more accurate patient diagnosis, but quantitative, neuropathology-based traits derived from imaging modalities offer increased power to detect associations with large-scale genetic data. This field of investigation has been termed “imaging genetics”. Imaging genetics studies aim to identify novel risk genes and elucidate gene function and novel mechanisms of disease pathology and etiology. In this dissertation, I have conducted imaging genetics studies of the neuropathologies of Alzheimer’s Disease and Down Syndrome in order to increase our understanding of the genetic etiology underlying these pathologies. Furthermore, new biomarkers of these pathologies are still needed. Thus, a magnetic resonance imaging sequence which has been shown to detect amyloid beta plaque in mice is explored in human studies in this dissertation. This work contributes novel findings to the body of research aimed at early identification of patients at risk of Alzheimer’s Disease.
Advisors/Committee Members: Chun Li (committee member), Tricia Thornton-Wells (committee member), Dana Crawford (committee member), Brian Welch (committee member), Jonathan Haines (Committee Chair).
Subjects/Keywords: imaging; genetics; amyloid; alzheimers; aging; down; downs; MRI; PET
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APA (6th Edition):
Koran, M. E. I. (2014). Imaging and Genetics of Two Amyloid Related Diseases: Alzheimer’s Disease and Down Syndrome. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/10539
Chicago Manual of Style (16th Edition):
Koran, Mary Ellen Irene. “Imaging and Genetics of Two Amyloid Related Diseases: Alzheimer’s Disease and Down Syndrome.” 2014. Doctoral Dissertation, Vanderbilt University. Accessed March 08, 2021.
http://hdl.handle.net/1803/10539.
MLA Handbook (7th Edition):
Koran, Mary Ellen Irene. “Imaging and Genetics of Two Amyloid Related Diseases: Alzheimer’s Disease and Down Syndrome.” 2014. Web. 08 Mar 2021.
Vancouver:
Koran MEI. Imaging and Genetics of Two Amyloid Related Diseases: Alzheimer’s Disease and Down Syndrome. [Internet] [Doctoral dissertation]. Vanderbilt University; 2014. [cited 2021 Mar 08].
Available from: http://hdl.handle.net/1803/10539.
Council of Science Editors:
Koran MEI. Imaging and Genetics of Two Amyloid Related Diseases: Alzheimer’s Disease and Down Syndrome. [Doctoral Dissertation]. Vanderbilt University; 2014. Available from: http://hdl.handle.net/1803/10539
Vanderbilt University
4.
Zuvich, Rebecca Lynn.
Identification of Additional Independent Loci in the Major Histocompatibility Complex in Multiple Sclerosis Susceptibility.
Degree: MS, Interdisciplinary Studies: Applied Statistics, 2010, Vanderbilt University
URL: http://hdl.handle.net/1803/13435
► Multiple sclerosis (MS) is characterized as an autoimmune neurodegenerative disease. The disease manifests as demyelination or degradation of the myelin sheath in the central nervous…
(more)
▼ Multiple sclerosis (MS) is characterized as an autoimmune neurodegenerative disease. The disease manifests as demyelination or degradation of the myelin sheath in the central nervous system. The Major Histocompatibility Complex (MHC) was associated with MS in the mid-1970’s; the association was later refined to the HLA-DRB1*1501-DQB*0602 haplotype. The MHC region is riddled with complicating factors including high gene content, extreme levels of polymorphism, and a dense pattern of linkage disequilibrium (LD). These characteristics make this region difficult for differentiating whether a single allele or an entire haplotype contributes to disease association. Despite these challenges it is clear that the MHC region harbors MS susceptibility loci in addition to the HLA-DRB1*1501 region. Using the strong LD in this region we can test a model that predicts residual odds ratios (ORs) for a marker in LD with a disease allele such as HLA-DRB1*1501. Comparing the correlation between the observed OR and the calculated OR for multiple SNPs in the MHC region, we hypothesize those SNPs that appear as outliers are suggestive of additional effects independent from the HLA-DRB1*1501 region. We examined ~2,300 SNPs in 1,479 cases and 1,482 controls in the 28 Mb to 36 Mb region on chromosome 6 containing the MHC. The ORs for the SNPs were grouped based on the amount of LD with the HLA-DRB1 surrogate SNP (rs3135388). We identified nine outlying SNPs, which had observed ORs much larger than the calculated OR. These nine SNPs are in six different genes that suggest susceptibility to MS independent of HLA-DRB1*1501.
Advisors/Committee Members: Marylyn Ritchie (committee member), Chun Li (committee member), Jonathan Haines (committee member).
Subjects/Keywords: multiple sclerosis; statistics
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APA (6th Edition):
Zuvich, R. L. (2010). Identification of Additional Independent Loci in the Major Histocompatibility Complex in Multiple Sclerosis Susceptibility. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/13435
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Zuvich, Rebecca Lynn. “Identification of Additional Independent Loci in the Major Histocompatibility Complex in Multiple Sclerosis Susceptibility.” 2010. Thesis, Vanderbilt University. Accessed March 08, 2021.
http://hdl.handle.net/1803/13435.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Zuvich, Rebecca Lynn. “Identification of Additional Independent Loci in the Major Histocompatibility Complex in Multiple Sclerosis Susceptibility.” 2010. Web. 08 Mar 2021.
Vancouver:
Zuvich RL. Identification of Additional Independent Loci in the Major Histocompatibility Complex in Multiple Sclerosis Susceptibility. [Internet] [Thesis]. Vanderbilt University; 2010. [cited 2021 Mar 08].
Available from: http://hdl.handle.net/1803/13435.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Zuvich RL. Identification of Additional Independent Loci in the Major Histocompatibility Complex in Multiple Sclerosis Susceptibility. [Thesis]. Vanderbilt University; 2010. Available from: http://hdl.handle.net/1803/13435
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Vanderbilt University
5.
Zuvich, Rebecca Lynn.
Pathway Approach to Decoding Multiple Sclerosis.
Degree: PhD, Human Genetics, 2009, Vanderbilt University
URL: http://hdl.handle.net/1803/15066
► Multiple sclerosis (MS) is characterized as a neurodegenerative autoimmune disease. This clinically complex disease has provided great challenges for geneticists over the years. With the…
(more)
▼ Multiple sclerosis (MS) is characterized as a neurodegenerative autoimmune disease. This clinically complex disease has provided great challenges for geneticists over the years. With the advent of genome-wide association studies (GWAS), the strong genetic component associated with MS is finally beginning to be characterized. One of the first discoveries to emerge in this new era was the association with rs6897932 in the interleukin-7 receptor alpha chain (IL7RA) gene. The goal of the work presented in this dissertation was to identify additional genes that increase one’s susceptibility to MS. Our studies involved examining genes in the extended biological pathway related to IL7RA to identify novel associations. Through this approach, we identified two additional novel gene regions that are likely associated with MS. These results help to further delineate the genetic architecture of MS and validate our pathway approach as an effective method to identify novel associations associated in a complex disease.
We began our investigation with a discovery screen containing SNPs from 73 genes with putative functional relationships to IL7RA and subsequently genotyped 7,865 single nucleotide polymorphism (SNPs) in and around these genes. Two of the gene regions examined, IL7 and SOCS1, had significantly associated SNPs that further replicated in an independent case-control dataset with joint p-values reaching 8.29x10-5 and 3.48x10-7, respectively, exceeding the threshold for experiment-wide significance. Our results also implicated two additional novel gene regions that are likely to be associated with MS: PRKCE with p-values reaching 3.47x10-4 and BCL2 with p-values reaching 4.32x10-4. The TYK2 gene, which emerged in our analysis, also has recently been associated with MS in other studies.
The work presented in this dissertation confirmed two novel regions and implicated several others that need further examination as MS disease loci. Thus, using the pathway approach in conjunction with large datasets and dense genotyping, the etiology of MS is finally starting to be dissected. By building on the knowledge of these gene effects, these studies will hopefully result in further understanding of the pathogenesis of MS.
Advisors/Committee Members: Subramanian Sriram (committee member), Dana Crawford (committee member), Michael Rock (committee member), Jonathan Haines (committee member), Marylyn Ritchie (Committee Chair).
Subjects/Keywords: autoimmune; susceptibility
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APA ·
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APA (6th Edition):
Zuvich, R. L. (2009). Pathway Approach to Decoding Multiple Sclerosis. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/15066
Chicago Manual of Style (16th Edition):
Zuvich, Rebecca Lynn. “Pathway Approach to Decoding Multiple Sclerosis.” 2009. Doctoral Dissertation, Vanderbilt University. Accessed March 08, 2021.
http://hdl.handle.net/1803/15066.
MLA Handbook (7th Edition):
Zuvich, Rebecca Lynn. “Pathway Approach to Decoding Multiple Sclerosis.” 2009. Web. 08 Mar 2021.
Vancouver:
Zuvich RL. Pathway Approach to Decoding Multiple Sclerosis. [Internet] [Doctoral dissertation]. Vanderbilt University; 2009. [cited 2021 Mar 08].
Available from: http://hdl.handle.net/1803/15066.
Council of Science Editors:
Zuvich RL. Pathway Approach to Decoding Multiple Sclerosis. [Doctoral Dissertation]. Vanderbilt University; 2009. Available from: http://hdl.handle.net/1803/15066
Vanderbilt University
6.
Edwards, Todd L.
An Extension to and Application of the Multifactor Dimensionality Reduction Pedigree Disequilibrium Test.
Degree: PhD, Human Genetics, 2008, Vanderbilt University
URL: http://hdl.handle.net/1803/10658
► As the field of genetics explores beyond mapping single-site disease susceptibility loci, epistasis between genes is being considered in disease models. These hypotheses present new…
(more)
▼ As the field of genetics explores beyond mapping single-site disease susceptibility loci, epistasis between genes is being considered in disease models. These hypotheses present new problems for investigators as they search through ever more complex data structures. The dimensionality and size of a search space, the types and strengths of disease associations in data, and the quality of inference allowed given a result are all challenges when testing for putative epistatic disease models.
Method development to analyze family data for epistatic interactions is in a preliminary stage. The multifactor dimensionality reduction pedigree disequilibrium test (MDR-PDT) is one technique for assessing epistatic models in family data. The objective of this proposal is to refine, test, and apply this method to real data.
MDR-PDT is a method that implements the genoPDT statistic within the framework of the MDR algorithm. We hypothesize that at the conclusion of my aims, the MDR-PDT algorithm’s utility and power will be improved. In the following dissertation we developed a cross validation algorithm for pedigree data, and an omnibus model selection method. We also implemented an extension to MDR-PDT that includes a likelihood ratio test for the statistical significance of an interaction found by the MDR-PDT search using logistic regression. Finally, MDR-PDT was applied to Alzheimer’s candidate gene datasets and revealed a multilocus model involving several genes that are functional candidates.
Advisors/Committee Members: Dana Crawford (committee member), Eden Martin (committee member), Charles Matthews (committee member), Marylyn Ritchie (committee member), Jonathan Haines (Committee Chair).
Subjects/Keywords: Association; Epistasis; Interaction; Genetics; Epidemiology
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APA (6th Edition):
Edwards, T. L. (2008). An Extension to and Application of the Multifactor Dimensionality Reduction Pedigree Disequilibrium Test. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/10658
Chicago Manual of Style (16th Edition):
Edwards, Todd L. “An Extension to and Application of the Multifactor Dimensionality Reduction Pedigree Disequilibrium Test.” 2008. Doctoral Dissertation, Vanderbilt University. Accessed March 08, 2021.
http://hdl.handle.net/1803/10658.
MLA Handbook (7th Edition):
Edwards, Todd L. “An Extension to and Application of the Multifactor Dimensionality Reduction Pedigree Disequilibrium Test.” 2008. Web. 08 Mar 2021.
Vancouver:
Edwards TL. An Extension to and Application of the Multifactor Dimensionality Reduction Pedigree Disequilibrium Test. [Internet] [Doctoral dissertation]. Vanderbilt University; 2008. [cited 2021 Mar 08].
Available from: http://hdl.handle.net/1803/10658.
Council of Science Editors:
Edwards TL. An Extension to and Application of the Multifactor Dimensionality Reduction Pedigree Disequilibrium Test. [Doctoral Dissertation]. Vanderbilt University; 2008. Available from: http://hdl.handle.net/1803/10658
Vanderbilt University
7.
Reif, David Michael.
Integrated Analysis of Genetic and Proteomic Data.
Degree: PhD, Human Genetics, 2006, Vanderbilt University
URL: http://hdl.handle.net/1803/14337
► Biological organisms are complex systems that dynamically integrate inputs from a multitude of physiological and environmental factors. Complex clinical outcomes arise from the concerted interactions…
(more)
▼ Biological organisms are complex systems that dynamically integrate inputs from a multitude of physiological and environmental factors. Complex clinical outcomes arise from the concerted interactions among the myriad components of a biological system. Therefore, in addressing questions concerning the etiology of phenotypes as complex as common human disease or adverse reaction to vaccination, it is essential that the systemic nature of biology be taken into account. Analysis methods must integrate the information provided by each data type in a manner analogous to the operation of the body itself. It is hypothesized that such integrated approaches will provide a more comprehensive portrayal of the mechanisms underlying complex phenotypes and lend confidence to the biological interpretation of analytical conclusions.This dissertation concerns the development of a comprehensive analysis paradigm wherein experimental data of multiple types were analyzed jointly in the study of complex phenotypes. Flexible machine learning methods were used to integrate information that is insensitive to spatial and temporal flux (genetic polymorphisms) with information subject to dynamic changes (protein concentrations measured at multiple time points). This strategy was applied to genetic and proteomic data in both simulated and real analysis situations. Results of studies using simulated data indicated that utilizing multiple data types is beneficial when the disease model is complex and the phenotypic outcome-associated data type is unknown. The successful application to combined genetic and proteomic data from smallpox vaccine studies supported the hypothesis that such integrated approaches are analytically beneficial.
Considering the rapid progress in experimental technologies able to reliably generate vast quantities of data, as well as continual improvements in cost efficiency, it is expected that datasets including multiple types of experimental information will become commonplace in the near future. It is hoped that the positive conclusions from this dissertation will help spur the adoption of an analytical approach that rightfully takes the broader physiological context of complex biological systems into account.
Advisors/Committee Members: James Crowe, Jr. (committee member), Douglas Fisher (committee member), Jonathan Haines (committee member), Jason Moore (committee member), Scott Williams (Committee Chair).
Subjects/Keywords: machine learning; statistics; Systems biology; immunology; Genetic polymorphisms; Smallpox – Vaccination – Complications; Proteomics
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APA (6th Edition):
Reif, D. M. (2006). Integrated Analysis of Genetic and Proteomic Data. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14337
Chicago Manual of Style (16th Edition):
Reif, David Michael. “Integrated Analysis of Genetic and Proteomic Data.” 2006. Doctoral Dissertation, Vanderbilt University. Accessed March 08, 2021.
http://hdl.handle.net/1803/14337.
MLA Handbook (7th Edition):
Reif, David Michael. “Integrated Analysis of Genetic and Proteomic Data.” 2006. Web. 08 Mar 2021.
Vancouver:
Reif DM. Integrated Analysis of Genetic and Proteomic Data. [Internet] [Doctoral dissertation]. Vanderbilt University; 2006. [cited 2021 Mar 08].
Available from: http://hdl.handle.net/1803/14337.
Council of Science Editors:
Reif DM. Integrated Analysis of Genetic and Proteomic Data. [Doctoral Dissertation]. Vanderbilt University; 2006. Available from: http://hdl.handle.net/1803/14337
Vanderbilt University
8.
Velez, Digna Rosa.
Investigations into the genetic susceptibility to preterm birth.
Degree: PhD, Human Genetics, 2008, Vanderbilt University
URL: http://hdl.handle.net/1803/10496
► Spontaneous preterm birth (PTB), gestational age less than 37 weeks, is a major public health problem worldwide. Almost 500,000 preterm births occur annually in the…
(more)
▼ Spontaneous preterm birth (PTB), gestational age less than 37 weeks, is a major public health problem worldwide. Almost 500,000 preterm births occur annually in the United States (U.S.), accounting for ~12% of deliveries. The outcomes associated with PTB include increased risk of infant morbidity and mortality.
In addition to the effects on the health of the child, there is a significant disparity in incidence and clinical correlates of PTB between ethnic groups in the U.S. PTB, for example, among African Americans is ~18% compared to ~12% in Caucasians. Also, African American women who experience PTB are also more likely to have future PTB and early PTB associated with infection (less than 32 weeks gestation) than Caucasian women. Both the disparity in PTB rates and clinical correlates between ethnic groups in the U.S. may be explained by genetic causes.
An important aspect of PTB that distinguishes it from other phenotypes is that both maternal and fetal genes can affect pregnancy outcome. Because of the complex relationship between mother and fetus, the numerous factors affecting pregnancy and substantial selection for term delivery to ensure survival, it is unlikely that any single factor will be sufficient to explain PTB.
To better understand the genetic contribution to PTB and the rate disparity between ethnic groups, we performed a comprehensive genetic analysis. A high-throughput candidate gene screen and an analysis of amniotic fluid (AF) cytokine protein levels were performed to identify PTB risk factors. We selected candidate genes based on genes showing positive results in previous studies and/or being involved in hypothesized pathophysiological pathways. We selected 130 genes and 1536 single nucleotide polymorphisms (SNPs) from the nuclear genome and three candidate genes from the mitochondrial genome. We also examined AF protein concentration of seven well-established biomarkers of PTB for association with PTB. Our study indicates that several common risk factors in the infection and inflammatory response pathways may explain a portion of the risk in both Caucasians and African Americans; however, different genes lead to increased risk in Caucasians and African Americans, with the maternal influence being greater in Caucasians than in African Americans.
Advisors/Committee Members: Jonathan Haines (committee member), Jeffrey Canter (committee member), John Jeffery Reese (committee member), Scott M. Williams (committee member), Marylyn D. Ritchie (Committee Chair).
Subjects/Keywords: genetic epidemiology; genetics; preterm birth
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APA (6th Edition):
Velez, D. R. (2008). Investigations into the genetic susceptibility to preterm birth. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/10496
Chicago Manual of Style (16th Edition):
Velez, Digna Rosa. “Investigations into the genetic susceptibility to preterm birth.” 2008. Doctoral Dissertation, Vanderbilt University. Accessed March 08, 2021.
http://hdl.handle.net/1803/10496.
MLA Handbook (7th Edition):
Velez, Digna Rosa. “Investigations into the genetic susceptibility to preterm birth.” 2008. Web. 08 Mar 2021.
Vancouver:
Velez DR. Investigations into the genetic susceptibility to preterm birth. [Internet] [Doctoral dissertation]. Vanderbilt University; 2008. [cited 2021 Mar 08].
Available from: http://hdl.handle.net/1803/10496.
Council of Science Editors:
Velez DR. Investigations into the genetic susceptibility to preterm birth. [Doctoral Dissertation]. Vanderbilt University; 2008. Available from: http://hdl.handle.net/1803/10496
Vanderbilt University
9.
Turner, Stephen Dale.
Knowledge-Driven Genome-Wide Analysis of Multigenic Interactions Impacting HDL Cholesterol Level.
Degree: PhD, Human Genetics, 2010, Vanderbilt University
URL: http://hdl.handle.net/1803/15293
► Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last…
(more)
▼ Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. I begin this dissertation with a review of study designs and analytical methods for genetic association studies. Next, I characterize and present a series of improvements in using grammatical evolution to train neural networks for discovering gene-gene interactions in disease gene association studies. I then present an analysis of cis-epistasis - nonadditive multi-SNP interactions that influence gene expression. Next, I present a cohesive set of quality control procedures to be used for genome-wide association studies. Finally, I conclude by presenting results from a knowledge-driven gene-gene interaction analysis of HDL level in two clinical practice-based population biobanks.
Advisors/Committee Members: Yu Shyr (committee member), Marylyn D. Ritchie (committee member), Jonathan Haines (committee member), Erik Boczko (committee member), Dana Crawford (Committee Chair).
Subjects/Keywords: Human genetics; bioinformatics; machine learning; neural networks; cardiovascular disease; complex disease
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Manager
APA (6th Edition):
Turner, S. D. (2010). Knowledge-Driven Genome-Wide Analysis of Multigenic Interactions Impacting HDL Cholesterol Level. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/15293
Chicago Manual of Style (16th Edition):
Turner, Stephen Dale. “Knowledge-Driven Genome-Wide Analysis of Multigenic Interactions Impacting HDL Cholesterol Level.” 2010. Doctoral Dissertation, Vanderbilt University. Accessed March 08, 2021.
http://hdl.handle.net/1803/15293.
MLA Handbook (7th Edition):
Turner, Stephen Dale. “Knowledge-Driven Genome-Wide Analysis of Multigenic Interactions Impacting HDL Cholesterol Level.” 2010. Web. 08 Mar 2021.
Vancouver:
Turner SD. Knowledge-Driven Genome-Wide Analysis of Multigenic Interactions Impacting HDL Cholesterol Level. [Internet] [Doctoral dissertation]. Vanderbilt University; 2010. [cited 2021 Mar 08].
Available from: http://hdl.handle.net/1803/15293.
Council of Science Editors:
Turner SD. Knowledge-Driven Genome-Wide Analysis of Multigenic Interactions Impacting HDL Cholesterol Level. [Doctoral Dissertation]. Vanderbilt University; 2010. Available from: http://hdl.handle.net/1803/15293
. 
Open Access Theses and Dissertations