Test for interaction between two unlinked loci.

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Test for interaction between two unlinked loci. Abstract Text:

Jinying Zhao,Li Jin,Momiao Xiong,

Despite the growing consensus on the importance of testing gene-gene interactions in genetic studies of complex diseases, the effect of gene-gene interactions has often been defined as a deviance from genetic additive effects, which is essentially treated as a residual term in genetic analysis and leads to low power in detecting the presence of interacting effects. To what extent the definition of gene-gene interaction at population level reflects the genes' biochemical or physiological interaction remains a mystery. In this article, we introduce a novel definition and a new measure of gene-gene interaction between two unlinked loci (or genes). We developed a general theory for studying linkage disequilibrium (LD) patterns in disease population under two-locus disease models. The properties of using the LD measure in a disease population as a function of the measure of gene-gene interaction between two unlinked loci were also investigated. We examined how interaction between two loci creates LD in a disease population and showed that the mathematical formulation of the new definition for gene-gene interaction between two loci was similar to that of the LD between two loci. This finding motived us to develop an LD-based statistic to detect gene-gene interaction between two unlinked loci. The null distribution and type I error rates of the LD-based statistic for testing gene-gene interaction were validated using extensive simulation studies. We found that the new test statistic was more powerful than the traditional logistic regression under three two-locus disease models and demonstrated that the power of the test statistic depends on the measure of gene-gene interaction. We also investigated the impact of using tagging SNPs for testing interaction on the power to detect interaction between two unlinked loci. Finally, to evaluate the performance of our new method, we applied the LD-based statistic to two published data sets. Our results showed that the P values of the LD-based statistic were smaller than those obtained by other approaches, including logistic regression models.

Test for interaction between two unlinked loci. Publishing Authors By Initials

J Zhao,L Jin,M Xiong,

For similar hemic and lymphatic diseases: hematologic diseases: anemia: anemia, hemolytic: anemia, hemolytic, congenital: thalassemia: alpha-thalassemia research abstracts see: hemic and lymphatic diseases: hematologic diseases: anemia: anemia, hemolytic: anemia, hemolytic, congenital: thalassemia: alpha-thalassemia research

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Test for interaction between two unlinked loci. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: American journal of human genetics

VOLUME: 79

Page Numbers: 831-45

Journal Abbreviation: Am. J. Hum. Genet.

ISSN: 0002-9297

DAY: 21

MONTH: 09

YEAR: 2006

Test for interaction between two unlinked loci. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 370475

Test for interaction between two unlinked loci. Keywords Mesh Terms:

KEYWORDS: alpha-Thalassemia

MESH TERMS: genetics

Chemical & Substance for Abstract: Test for interaction between two unlinked loci. Information

Substance Name: Hemoglobin, Sickle

Registry Number: 0

Grant and Affiliation Information for Test for interaction between two unlinked loci.

AFFILIATION: Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77225, USA.

Country: United States

AGENCY: United States NIAMS

GRANT: P01 AR052915-01A1

ACRONYM: AR

MEDLINETA: Am J Hum Genet

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