Table 2 Potential biases in gene-gene and gene-environment investigations of coronary artery disease (CAD)

Selection bias

Skew in the selection of study participants

Patients with strong family history may self-select for study participation; patients with strong family history may be more likely to be referred to tertiary care and research centers

Survivor bias (prevalence-incidence bias)

Selection of study participants may miss mild disease or severe fatal cases

Patients whose first myocardial infarction is fatal are less likely to be studied

Recall bias

Patients are more likely to recall an environmental exposure if it was linked to a negative outcome

Patients with CAD may be more likely to remember an environmental exposure because of its negative consequences

Respondent bias

Patients answer in the way they believe they should answer, not the true answer

Patients with CAD and knowledge of potential CAD risk factors will be more motivated to report those exposures

Family information bias

Individuals become more aware of exposure if it is prevalent in their family

Many CAD risk factors and environmental exposures cluster in families

Exposure suspicion bias

Disease status can affect the amount of environmental exposure history collected

If data collection is not standardized, investigators may more thoroughly query patients with CAD

Publication bias

Statistically significant findings are more likely to be published

Gene-gene and gene-environment interaction findings in CAD are more likely to be published if significant

Measurement bias

Systematic errors of measurement

Platform- or laboratory-dependent genotyping errors; errors of laboratory values; errors of environmental exposure measurement

Population stratification

Differences in allele frequencies between groups resulting from ancestry not outcome status

CAD prevalence varies between ethnicities; but this can be tested and corrected for using methodological and statistical techniques