Literature DB >> 22997868

Analysis of epidemiologic studies of genetic effects and gene-environment interactions.

Montserrat García-Closas1, Kevin Jacobs, Peter Kraft, Nilanjan Chatterjee.   

Abstract

This chapter describes basic principles in study design, data analysis, and interpretation of epidemiological studies of genetic polymorphisms and disease risk, including the assessment of gene-environment interactions. The case-control design (hospital-based, population-based or nested within a prospective cohort) is frequently used to study common genetic variants and disease risk. Because of their widespread use, the analysis of case-control data will be the focus of this chapter. Two key considerations in the study design will be addressed: the selection of genetic markers to be evaluated, and sample size considerations to ensure adequate power to detect associations with disease risk. Single nucleotide polymorphisms (SNPs) are the most frequent form of common genetic variation, thus the discussion on data analysis will be based on the evaluation of associations between SNPs and disease risk. This chapter will begin with the evaluation of quality control of genotyping data, which is a critical first step in the analysis of genetic data. A description of statistical methods will follow, aimed at the discovery of genetic susceptibility loci, including analysis of candidate SNPs and genome-wide association studies, haplotype analyses, and the evaluation of gene-gene and gene-environment interactions.

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Year:  2011        PMID: 22997868

Source DB:  PubMed          Journal:  IARC Sci Publ        ISSN: 0300-5038


  5 in total

1.  Environmental confounding in gene-environment interaction studies.

Authors:  Tyler J Vanderweele; Yi-An Ko; Bhramar Mukherjee
Journal:  Am J Epidemiol       Date:  2013-05-21       Impact factor: 4.897

2.  "Drivers" of translational cancer epidemiology in the 21st century: needs and opportunities.

Authors:  Tram Kim Lam; Margaret Spitz; Sheri D Schully; Muin J Khoury
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-01-15       Impact factor: 4.254

3.  Common genetic polymorphisms modify the effect of smoking on absolute risk of bladder cancer.

Authors:  Montserrat Garcia-Closas; Nathaniel Rothman; Jonine D Figueroa; Ludmila Prokunina-Olsson; Summer S Han; Dalsu Baris; Eric J Jacobs; Nuria Malats; Immaculata De Vivo; Demetrius Albanes; Mark P Purdue; Sapna Sharma; Yi-Ping Fu; Manolis Kogevinas; Zhaoming Wang; Wei Tang; Adonina Tardón; Consol Serra; Alfredo Carrato; Reina García-Closas; Josep Lloreta; Alison Johnson; Molly Schwenn; Margaret R Karagas; Alan Schned; Gerald Andriole; Robert Grubb; Amanda Black; Susan M Gapstur; Michael Thun; William Ryan Diver; Stephanie J Weinstein; Jarmo Virtamo; David J Hunter; Neil Caporaso; Maria Teresa Landi; Amy Hutchinson; Laurie Burdett; Kevin B Jacobs; Meredith Yeager; Joseph F Fraumeni; Stephen J Chanock; Debra T Silverman; Nilanjan Chatterjee
Journal:  Cancer Res       Date:  2013-03-27       Impact factor: 12.701

Review 4.  Lessons Learned From Past Gene-Environment Interaction Successes.

Authors:  Beate R Ritz; Nilanjan Chatterjee; Montserrat Garcia-Closas; W James Gauderman; Brandon L Pierce; Peter Kraft; Caroline M Tanner; Leah E Mechanic; Kimberly McAllister
Journal:  Am J Epidemiol       Date:  2017-10-01       Impact factor: 5.363

5.  VDR Gene Polymorphisms in Healthy Individuals with Family History of Premature Coronary Artery Disease.

Authors:  Martyna Fronczek; Joanna Katarzyna Strzelczyk; Tadeusz Osadnik; Krzysztof Biernacki; Zofia Ostrowska
Journal:  Dis Markers       Date:  2021-01-29       Impact factor: 3.434

  5 in total

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