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Computational Methods and Epidemiolo...

Rhead, Brooke.

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Computational Methods and Epidemiologic Approaches for Revealing the Etiology of Autoimmune Diseases.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational Methods and Epidemiologic Approaches for Revealing the Etiology of Autoimmune Diseases./
作者:	Rhead, Brooke.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	109 p.
附註:	Source: Dissertations Abstracts International, Volume: 81-05, Section: B.
Contained By:	Dissertations Abstracts International81-05B.
標題:	Genetics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=22615797
ISBN:	9781392825402

Computational Methods and Epidemiologic Approaches for Revealing the Etiology of Autoimmune Diseases.
Rhead, Brooke.

Computational Methods and Epidemiologic Approaches for Revealing the Etiology of Autoimmune Diseases. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 109 p.

Source: Dissertations Abstracts International, Volume: 81-05, Section: B.

Thesis (Ph.D.)--University of California, Berkeley, 2019.

This item must not be sold to any third party vendors.

Autoimmune diseases, in which normal tissues are inappropriately attacked by the immune system, are complex diseases driven by a combination of genetic and environmental factors. Most are chronic inflammatory diseases with some treatments available but no known cures, and the disease mechanisms are not completely understood. Epigenetic factors, such as DNA methylation and microRNAs, are affected by genetic and environmental exposures and in turn affect gene expression and thus may play a role in autoimmune disease pathogenesis. In this dissertation, I employ a combination of computational, bioinformatic, statistical, and epidemiologic methods to study the role of epigenetics in autoimmune diseases in humans, and to characterize inflammatory changes in human cell lines.Chapter one introduces some complexities of studying autoimmune diseases in humans and introduces concepts of epigenetics. Chapter two shows that naive T cells from rheumatoid arthritis patients share DNA methylation sites with fibroblast-like synoviocytes, cells that line joints and are involved in joint inflammation. Chapter three shows that there are differences in DNA methylation in CD4+ and CD8+ T cells from multiple sclerosis patients compared to cells from healthy controls. Chapter four uses genome-wide association study results to implicate specific microRNAs and tissues in pediatric-onset multiple sclerosis. Chapter five shows that the inflammatory cytokine tumor necrosis factor alpha drives DNA methylation and transcriptional changes and activates autoimmune disease genes in endothelial cells. Chapter six is a summary of conclusions and key findings.

ISBN: 9781392825402Subjects--Topical Terms:

530508
Genetics.
Subjects--Index Terms:

Autoimmune disease

Computational Methods and Epidemiologic Approaches for Revealing the Etiology of Autoimmune Diseases.
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520 $a Autoimmune diseases, in which normal tissues are inappropriately attacked by the immune system, are complex diseases driven by a combination of genetic and environmental factors. Most are chronic inflammatory diseases with some treatments available but no known cures, and the disease mechanisms are not completely understood. Epigenetic factors, such as DNA methylation and microRNAs, are affected by genetic and environmental exposures and in turn affect gene expression and thus may play a role in autoimmune disease pathogenesis. In this dissertation, I employ a combination of computational, bioinformatic, statistical, and epidemiologic methods to study the role of epigenetics in autoimmune diseases in humans, and to characterize inflammatory changes in human cell lines.Chapter one introduces some complexities of studying autoimmune diseases in humans and introduces concepts of epigenetics. Chapter two shows that naive T cells from rheumatoid arthritis patients share DNA methylation sites with fibroblast-like synoviocytes, cells that line joints and are involved in joint inflammation. Chapter three shows that there are differences in DNA methylation in CD4+ and CD8+ T cells from multiple sclerosis patients compared to cells from healthy controls. Chapter four uses genome-wide association study results to implicate specific microRNAs and tissues in pediatric-onset multiple sclerosis. Chapter five shows that the inflammatory cytokine tumor necrosis factor alpha drives DNA methylation and transcriptional changes and activates autoimmune disease genes in endothelial cells. Chapter six is a summary of conclusions and key findings.
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