東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Discovery and Functional Interpretat...

Hu, Xinli.

Linked to FindBook

Google Book

Amazon

博客來

Discovery and Functional Interpretation of Genetic Risk in Autoimmune Diseases.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Discovery and Functional Interpretation of Genetic Risk in Autoimmune Diseases./
Author:	Hu, Xinli.
Description:	233 p.
Notes:	Source: Dissertation Abstracts International, Volume: 77-04(E), Section: B.
Contained By:	Dissertation Abstracts International77-04B(E).
Subject:	Genetics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3738828
ISBN:	9781339293318

Discovery and Functional Interpretation of Genetic Risk in Autoimmune Diseases.
Hu, Xinli.

Discovery and Functional Interpretation of Genetic Risk in Autoimmune Diseases. - 233 p.

Source: Dissertation Abstracts International, Volume: 77-04(E), Section: B.

Thesis (Ph.D.)--Harvard University, 2015.

Autoimmune diseases are chronic and debilitating conditions arising from abnormal immune responses directed against normal body tissues; they collectively affect the lives of 5-10% of the world population. These diseases often show familial clustering, suggesting strong genetic heritability. For many of autoimmune diseases, variation in the human leukocyte antigen (HLA) genes is the primary modulator of genetic risk. Recently, genome-wide association studies (GWAS) identified hundreds of genomic regions outside the HLA that harbor additional risk-conferring variants. The ultimate goal is to identify the precise causal variants and understand the mechanisms by which they lead to autoimmunity, which is challenged by complexities of the genome and the immune system. In this work, my colleagues and I developed and applied experimental and computational tools to reveal critical clues from multiple genetic and biological data types. First, we devised a statistical algorithm to identify the critical cell types involved in different autoimmune diseases. Two strongly heritable and common diseases, rheumatoid arthritis (RA) and type 1 diabetes (T1D), both involve the adaptive immune system, specifically the CD4+ T cells. We then conducted focused studies in CD4+ T cells using high-throughput genomic and proteomic technologies, and showed that immunological phenotypes and functions varied with genetic differences across individuals. To facilitate this study, we developed an automated computational tool to efficiently and reliably analyze the large-scale data. Finally, the HLA genes, which encode a family of highly variable antigen-recognition proteins, are the longest-known and strongest modulators of genetic risk in T1D. However, the extraordinary level of polymorphism and complex structure in the HLA region largely hindered precise localization and functional investigation of the causal mutations. We used dense-genotyping and robust statistical analyses to pinpoint the amino acid residue changes at a few key amino acid positions that explained the majority of disease risk within the HLA. The work presented in this dissertation revealed the specific immune cell populations, genetic variants, and cellular functions that affect RA, T1D, and other autoimmune diseases. Furthermore, it offers a rational framework, as well as powerful open-source computational tools, that can be applied in future functional genomic studies.

ISBN: 9781339293318Subjects--Topical Terms:

530508
Genetics.

Discovery and Functional Interpretation of Genetic Risk in Autoimmune Diseases.
LDR:03356nmm a2200277 4500 001 2069386
005 20160513093631.5
008 170521s2015 ||||||||||||||||| ||eng d
020 $a 9781339293318
035 $a (MiAaPQ)AAI3738828
035 $a AAI3738828
040 $a MiAaPQ $c MiAaPQ
100 1 $a Hu, Xinli. $3 3184397
245 1 0 $a Discovery and Functional Interpretation of Genetic Risk in Autoimmune Diseases.
300 $a 233 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-04(E), Section: B.
500 $a Advisers: George Church; Joel Hirschhorn; Vijay Kuchroo.
502 $a Thesis (Ph.D.)--Harvard University, 2015.
520 $a Autoimmune diseases are chronic and debilitating conditions arising from abnormal immune responses directed against normal body tissues; they collectively affect the lives of 5-10% of the world population. These diseases often show familial clustering, suggesting strong genetic heritability. For many of autoimmune diseases, variation in the human leukocyte antigen (HLA) genes is the primary modulator of genetic risk. Recently, genome-wide association studies (GWAS) identified hundreds of genomic regions outside the HLA that harbor additional risk-conferring variants. The ultimate goal is to identify the precise causal variants and understand the mechanisms by which they lead to autoimmunity, which is challenged by complexities of the genome and the immune system. In this work, my colleagues and I developed and applied experimental and computational tools to reveal critical clues from multiple genetic and biological data types. First, we devised a statistical algorithm to identify the critical cell types involved in different autoimmune diseases. Two strongly heritable and common diseases, rheumatoid arthritis (RA) and type 1 diabetes (T1D), both involve the adaptive immune system, specifically the CD4+ T cells. We then conducted focused studies in CD4+ T cells using high-throughput genomic and proteomic technologies, and showed that immunological phenotypes and functions varied with genetic differences across individuals. To facilitate this study, we developed an automated computational tool to efficiently and reliably analyze the large-scale data. Finally, the HLA genes, which encode a family of highly variable antigen-recognition proteins, are the longest-known and strongest modulators of genetic risk in T1D. However, the extraordinary level of polymorphism and complex structure in the HLA region largely hindered precise localization and functional investigation of the causal mutations. We used dense-genotyping and robust statistical analyses to pinpoint the amino acid residue changes at a few key amino acid positions that explained the majority of disease risk within the HLA. The work presented in this dissertation revealed the specific immune cell populations, genetic variants, and cellular functions that affect RA, T1D, and other autoimmune diseases. Furthermore, it offers a rational framework, as well as powerful open-source computational tools, that can be applied in future functional genomic studies.
590 $a School code: 0084.
650 4 $a Genetics. $3 530508
650 4 $a Biostatistics. $3 1002712
690 $a 0369
690 $a 0308
710 2 $a Harvard University. $b Medical Sciences. $3 3181716
773 0 $t Dissertation Abstracts International $g 77-04B(E).
790 $a 0084
791 $a Ph.D.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3738828