Logic Regression for Analysis of the Association between Genetic Variation in the Renin-Angiotensin System and Myocardial Infarction or Stroke | Zendy

Charles Kooperberg | Zendy; Josh Bis | Zendy; Kristin D. Marciante | Zendy; Susan R. Heckbert | Zendy; Thomas Lumley | Zendy; Bruce M. Psaty | Zendy

Open Access

Logic Regression for Analysis of the Association between Genetic Variation in the Renin-Angiotensin System and Myocardial Infarction or Stroke

Author(s) -

Charles Kooperberg,

Josh Bis,

Kristin D. Marciante,

Susan R. Heckbert,

Thomas Lumley,

Bruce M. Psaty

Publication year - 2006

Publication title -

american journal of epidemiology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.33

H-Index - 256

eISSN - 1476-6256

pISSN - 0002-9262

DOI - 10.1093/aje/kwk006

Subject(s) - single nucleotide polymorphism , snp , myocardial infarction , stroke (engine) , genotype , genetic association , haplotype , observational study , medicine , genetic variants , genetic variation , renin–angiotensin system , bioinformatics , biology , genetics , gene , blood pressure , mechanical engineering , engineering

Recent developments in genetic sequencing technology now make it possible to genotype large numbers of single nucleotide polymorphisms (SNPs) in large samples. Many association studies using SNP data are now being carried out. Typically, these observational studies establish whether certain haplotypes or individual SNPs are associated with a health outcome. Few methods exist for finding interaction effects among multiple SNPs or between SNPs and environmental factors. In this paper, the authors describe logic regression, an exploratory method with which to identify interactions for further research. They illustrate this method using data from a US case-control study of myocardial infarction and stroke (1995-1999) carried out among 1,614 persons in Washington State who were genotyped for 32 SNPs on five genes in the renin-angiotensin system.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research