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Application of association and linka...

Fingerlin, Tasha Elizabeth.

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Application of association and linkage methods in studies of complex traits.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Application of association and linkage methods in studies of complex traits./
作者:	Fingerlin, Tasha Elizabeth.
面頁冊數:	100 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-06, Section: B, page: 2471.
Contained By:	Dissertation Abstracts International64-06B.
標題:	Biology, Biostatistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3096092

Application of association and linkage methods in studies of complex traits.
Fingerlin, Tasha Elizabeth.

Application of association and linkage methods in studies of complex traits. - 100 p.

Source: Dissertation Abstracts International, Volume: 64-06, Section: B, page: 2471.

Thesis (Ph.D.)--University of Michigan, 2003.

Complex diseases like type 2 diabetes, heart disease and cancer have a tremendous impact on the worldwide public health. The inherent complexity of the pathogenesis of these diseases due to genetic and environmental factors dictate that efforts to map and identify variants that confer risk to these diseases are often met with difficulty. I begin this dissertation with a brief introduction to complex genetic diseases and the strategies used to map susceptibility variants.Subjects--Topical Terms:

1018416
Biology, Biostatistics.

Application of association and linkage methods in studies of complex traits.
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245 1 0 $a Application of association and linkage methods in studies of complex traits.
300 $a 100 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-06, Section: B, page: 2471.
500 $a Chairs: Michael Boehnke; Sharon L. R. Kardia.
502 $a Thesis (Ph.D.)--University of Michigan, 2003.
520 $a Complex diseases like type 2 diabetes, heart disease and cancer have a tremendous impact on the worldwide public health. The inherent complexity of the pathogenesis of these diseases due to genetic and environmental factors dictate that efforts to map and identify variants that confer risk to these diseases are often met with difficulty. I begin this dissertation with a brief introduction to complex genetic diseases and the strategies used to map susceptibility variants.
520 $a In the first paper of this dissertation, I investigated the role of variation in the calpain-10 gene in conferring risk to type 2 diabetes in a large sample of Finnish affected sibling pairs from the Finland United States Investigation of NIDDM Genetics (FUSION) study. I did not reproduce the association between a haplotype combination and diabetes status that was first reported in Mexican Americans. Hence, the calpain-10 gene does not appear to either confer susceptibility to type 2 diabetes or strongly influence diabetes-related traits in the FUSION sample.
520 $a In the second paper, I investigated the impact of using sex-averaged genetic maps in place of sex-specific maps in multipoint linkage analysis when identity by descent status is incompletely known. Via simulation, I compared the power, false-positive rates, and disease-location estimates of analyses that used both maps when the female:male map distance ratio was different from one. Unless the proportion of informative male and female meioses differed, I found no differences in the two types of analyses for maker densities of l, 5 and 10 cM.
520 $a In the third paper, I investigated case-selection strategies for disease-marker case control association studies when affected sibships are available. I compared three case-selection strategies that use allele-sharing information to one that randomly selects a single individual from each sibship. When individuals carrying alleles that are present in multiple affected individuals in an affected sibship are chosen, the frequency of the disease-associated variant can be increased in the case sample. As such, using allele-sharing information to select cases can increase the efficiency of disease-marker association studies.
520 $a I conclude with a brief summary of the dissertation and discussion of future work.
590 $a School code: 0127.
650 4 $a Biology, Biostatistics. $3 1018416
650 4 $a Biology, Genetics. $3 1017730
650 4 $a Health Sciences, Public Health. $3 1017659
650 4 $a Health Sciences, Pathology. $3 1017854
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710 2 0 $a University of Michigan. $3 777416
773 0 $t Dissertation Abstracts International $g 64-06B.
790 1 0 $a Boehnke, Michael, $e advisor
790 1 0 $a Kardia, Sharon L. R., $e advisor
790 $a 0127
791 $a Ph.D.
792 $a 2003
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