Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology

G Davey Smith, D Lawlor, RM Harbord, NJ Timpson, INM Day, S Ebrahim

Research output: Contribution to journalArticle (Academic Journal)peer-review

288 Citations (Scopus)

Abstract

In conventional epidemiology confounding of the exposure of interest with lifestyle or socioeconomic factors, and reverse causation whereby disease status influences exposure rather than vice versa, may invalidate causal interpretations of observed associations. Conversely, genetic variants should not be related to the confounding factors that distort associations in conventional observational epidemiological studies. Furthermore, disease onset will not influence genotype. Therefore, it has been suggested that genetic variants that are known to be associated with a modifiable (nongenetic) risk factor can be used to help determine the causal effect of this modifiable risk factor on disease outcomes. This approach, mendelian randomization, is increasingly being applied within epidemiological studies. However, there is debate about the underlying premise that associations between genotypes and disease outcomes are not confounded by other risk factors. We examined the extent to which genetic variants, on the one hand, and nongenetic environmental exposures or phenotypic characteristics on the other, tend to be associated with each other, to assess the degree of confounding that would exist in conventional epidemiological studies compared with mendelian randomization studies.
Translated title of the contributionClustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology
Original languageEnglish
Pages (from-to)e352
Number of pages8
JournalPLoS Medicine
Volume4
Issue number12
DOIs
Publication statusPublished - Dec 2007

Keywords

  • Environment
  • Genetic Variation
  • Polymorphism, Single Nucleotide
  • Heart Diseases
  • Reproducibility of Results
  • Epidemiologic Methods
  • Humans
  • Aged
  • Great Britain
  • Risk Assessment
  • Socioeconomic Factors
  • Phenotype
  • Life Style
  • Genotype
  • Cross-Sectional Studies
  • Risk Factors
  • Confounding Factors (Epidemiology)
  • Health Behavior
  • Middle Aged
  • Genetic Predisposition to Disease
  • Cluster Analysis
  • Female

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