Reporting, appraising, and integrating data on genotype prevalence and gene-disease associations

Julian Little, Linda Bradley, Molly S. Bray, Mindy Clyne, Janice Dorman, Darrell L. Ellsworth, James Hanson, Muin Khoury, Joseph Lau, Thomas R. O'Brien, Nat Rothman, Donna Stroup, Emanuela Taioli, Duncan Thomas, Harri Vainio, Sholom Wacholder, Clarice Weinberg

Research output: Contribution to journalArticlepeer-review

343 Scopus citations

Abstract

The recent completion of the first draft of the human genome sequence and advances in technologies for genomic analysis are generating tremendous opportunities for epidemiologic studies to evaluate the role of genetic variants in human disease. Many methodological issues apply to the investigation of variation in the frequency of allelic variants of human genes, of the possibility that these influence disease risk, and of assessment of the magnitude of the associated risk. Based on a Human Genome Epidemiology workshop, a checklist for reporting and appraising studies of genotype prevalence and studies of gene-disease associations was developed. This focuses on selection of study subjects, analytic validity of genotyping, population stratification, and statistical issues. Use of the checklist should facilitate the integration of evidence from these studies. The relation between the checklist and grading schemes that have been proposed for the evaluation of observational studies is discussed. Although the limitations of grading schemes are recognized, a robust approach is proposed. Other issues in the synthesis of evidence that are particularly relevant to studies of genotype prevalence and gene-disease association are discussed, notably identification of studies, publication bias, criteria for causal inference, and the appropriateness of quantitative synthesis.

Original languageEnglish
Pages (from-to)300-310
Number of pages11
JournalAmerican Journal of Epidemiology
Volume156
Issue number4
DOIs
StatePublished - 15 Aug 2002
Externally publishedYes

Keywords

  • Association
  • Case-control studies
  • Causality
  • Cohort studies
  • Epidemiologic methods
  • Gene frequency
  • Genetic techniques
  • Meta-analysis

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