Literature DB >> 12115594

Covariates and confounding in epidemiologic studies using metabolic gene polymorphisms.

Emanuela Taioli1, Seymour Garte.   

Abstract

The relationship between exposure and disease when biomarkers are introduced in an epidemiologic study is explored and summarized. In molecular epidemiologic studies, biologic measurements play a major role as markers of exposure, disease or susceptibility to disease and/or exposure. In this scenario, the definition and management of confounding factors may change. Sometimes the presence or activation of the biomarker is partially caused by the relevant environmental exposure, and therefore the 2 variables (exposure and biomarker) should not be always treated as confounders of each other. Models of exposure-disease association in the presence of biologic markers are presented. The concept of confounders is reviewed in light of the role of biomarkers in the pathway between exposure and disease. Copyright 2002 Wiley-Liss, Inc.

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Year:  2002        PMID: 12115594     DOI: 10.1002/ijc.10448

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  2 in total

1.  A model of gene-gene and gene-environment interactions and its implications for targeting environmental interventions by genotype.

Authors:  Helen M Wallace
Journal:  Theor Biol Med Model       Date:  2006-10-09       Impact factor: 2.432

2.  Application of two machine learning algorithms to genetic association studies in the presence of covariates.

Authors:  Bareng A S Nonyane; Andrea S Foulkes
Journal:  BMC Genet       Date:  2008-11-14       Impact factor: 2.797

  2 in total

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