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You searched for subject:(admixture mapping study). Showing records 1 – 2 of 2 total matches.

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Vanderbilt University

1. Bray, Michael Joseph. Evaluating Epidemiologic and Genetic Risk Factors for Uterine Fibroid Characteristics.

Degree: PhD, Human Genetics, 2018, Vanderbilt University

Uterine fibroids, benign tumors of the uterus, are the most common female pelvic tumor. Fibroids are highly heterogeneous, with some women developing a single small fibroid while other women develop multiple and/or large fibroids. In addition, racial disparities in fibroid size and number support that fibroid characteristics have a genetic component. For example, African American (AA) women have more numerous and larger fibroids than European American (EA) women. Furthermore, AAs are two times more likely than EAs to receive surgical treatments for fibroids such as a hysterectomy. Unfortunately, most research on fibroids to date has not evaluated risk factors for specific fibroid characteristics. The purpose of this thesis is to provide a deeper understanding on both epidemiology and genetic risk factors of fibroid characteristics, fibroid number (single vs. multiple), volume of largest fibroid, and largest dimension of all fibroid measurements. After identifying epidemiologic risk factors for fibroid characteristics, this study identified several novel genetic loci associating with either fibroid size or number by methods of genome-wide association studies (GWAS) and admixture mapping studies. Lastly, this study estimated heritability of fibroids and fibroid size. Advisors/Committee Members: Bingshan Li (committee member), Melissa F. Wellons (committee member), Todd L. Edwards (committee member), Nancy J. Cox (committee member), Digna R. Velez Edwards (committee member), David C. Samuels (Committee Chair).

Subjects/Keywords: admixture mapping study; genome-wide association study; uterine fibroids

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Bray, M. J. (2018). Evaluating Epidemiologic and Genetic Risk Factors for Uterine Fibroid Characteristics. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/10965

Chicago Manual of Style (16th Edition):

Bray, Michael Joseph. “Evaluating Epidemiologic and Genetic Risk Factors for Uterine Fibroid Characteristics.” 2018. Doctoral Dissertation, Vanderbilt University. Accessed March 07, 2021. http://hdl.handle.net/1803/10965.

MLA Handbook (7th Edition):

Bray, Michael Joseph. “Evaluating Epidemiologic and Genetic Risk Factors for Uterine Fibroid Characteristics.” 2018. Web. 07 Mar 2021.

Vancouver:

Bray MJ. Evaluating Epidemiologic and Genetic Risk Factors for Uterine Fibroid Characteristics. [Internet] [Doctoral dissertation]. Vanderbilt University; 2018. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1803/10965.

Council of Science Editors:

Bray MJ. Evaluating Epidemiologic and Genetic Risk Factors for Uterine Fibroid Characteristics. [Doctoral Dissertation]. Vanderbilt University; 2018. Available from: http://hdl.handle.net/1803/10965


University of Southern California

2. Liu, Jinghua. Population substructure and its impact on genome-wide association studies with admixed populations.

Degree: PhD, Statistical Genetics and Genetic Epidemiology, 2012, University of Southern California

Association studies among admixed populations pose many challenges. The purpose of this study is to compare the methods for ancestry estimation and to investigate the control for confounding and the capture of heterogeneity in SNP effect by the use of individual ancestries. In addition, a general regression framework is proposed to perform admixture mapping for both case-only and case-control study designs among admixed populations. For confounding and heterogeneity, simulation results indicate that 1) adjustment for global ancestry can control for confounding; 2) additional adjustment for local ancestry may increase power when the induced admixture LD is in the opposite direction as the LD in the ancestral populations; 3) the inclusion of a SNP by local ancestry interaction term can increase power when there is substantial differential LD between ancestry populations. Real data analysis in a genome-wide data using the University of Southern California's Children's Health Study of childhood asthma highlights rs10519951 (p=8.5E-7) from the model with the interaction term, a SNP lacking any evidence of association from the SNP association analysis (p=0.5). For the admixture mapping, simulation and real data analysis results among African Americans from the Multiethnic Cohort Study of prostate cancer indicate that 1) case-only analysis suffers from spurious results among the regions with biased local ancestry estimation; 2) our proposed regression model yield similar performance as the existing methods; 3) it is more powerful to incorporate genotype information for admixture mapping; 4) and it is more powerful to incorporate SNP by local ancestry interaction to capture the admixture signal and heterogeneity by local ancestry simultaneously. Advisors/Committee Members: Conti, David V. (Committee Chair), Gilliland, Frank D. (Committee Member), Gauderman, William James (Committee Member), Thomas, Duncan C. (Committee Member), Knowles, James (Committee Member).

Subjects/Keywords: genetic association study; GWAS; admixture mapping; population stratification; confounding; heterogeneity; admixed population

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Liu, J. (2012). Population substructure and its impact on genome-wide association studies with admixed populations. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/78608/rec/5120

Chicago Manual of Style (16th Edition):

Liu, Jinghua. “Population substructure and its impact on genome-wide association studies with admixed populations.” 2012. Doctoral Dissertation, University of Southern California. Accessed March 07, 2021. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/78608/rec/5120.

MLA Handbook (7th Edition):

Liu, Jinghua. “Population substructure and its impact on genome-wide association studies with admixed populations.” 2012. Web. 07 Mar 2021.

Vancouver:

Liu J. Population substructure and its impact on genome-wide association studies with admixed populations. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2021 Mar 07]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/78608/rec/5120.

Council of Science Editors:

Liu J. Population substructure and its impact on genome-wide association studies with admixed populations. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/78608/rec/5120

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