Re: Population stratification in epidemiologic studies of common genetic variants and cancer: quantification of bias.

Epidemiologists have long suspected that, in populations with racial or ethnic subgroups, spurious associations may arise between genetic markers and disease (1). Incomplete mixing of subgroups, known as population stratification or admixture, can lead to bias if one more or subgroups carries both a higher prevalence of an allele and a higher risk of disease (2). The magnitude and direction of the resulting bias are not well understood. Recently, a variety of alternative study designs have been proposed to avoid the problem of population stratification, including case–parent and case–sibling methods (2). In a recent issue of the Journal, Wacholder et al. (3) provided evidence that population stratification leads to minimal bias in epidemiologic studies of non-Hispanic U. S. Caucasians of European origin. The authors calculated a confounding risk ratio (CRR), the ratio of the crude and race-adjusted relative risks for the effect of genotype on disease. With the use of empiric data as well as data simulations, the authors found that the range of CRRs for European-Americans was 0.78–1.22. The majority of CRR values centered around the null value of 1.00, indicating no confounding by race. I performed similar calculations using previously published data from the Carolina Breast Cancer Study, a population-based, case–control study of inasive breast cancer in North Carolina. The study was approved by the Institutional Review Board at the University of North Carolina School of Medicine, Chapel Hill, and written informed consent was obtained from all study participants. The study population is 41% African-American, 58% white, and 1% other groups. Data for glutathione S-transferase M1, T1, and P1 (4); N-acetyltransferase 1 and 2 (5); catechol-O-methyltransferase (6); and P57/KIP2 (7) genotypes were used. The previously reported odds ratios (ORs) for “at-risk” genotypes ranged from 0.7 to 1.4, and there was little evidence for interaction between genotype and environmental exposures. For each genetic locus, logistic regression (implemented in SAS; SAS Institute, Cary, NC) was used to calculate a confounding OR (COR), the OR adjusted for age divided by the OR adjusted for age and race (3). Self-reported race was coded as a dichotomous variable, African-American versus non-AfricanAmerican. Non-African-Americans included whites, as well as seven Native Americans, three Asian-Americans, and three women who listed their race as “multiracial. ” CORs were also calculated after stratifying on smoking and a variety of other environmental factors. The range of CORs for genotype was 0.94–1.12 (Table 1). CORs deviated farther from the null (1.0) as the difference in genotype frequencies between African-Americans and whites increased, but most values were close to 1.0. After stratifying on environmental factors (data not shown), the range of CORs was 0.84–1.34, but most values remained close to the null. These results are compatible with the predictions of Wacholder et al. (3) and extend their findings to African-Americans and to whites. The results suggest that, in studies of breast cancer, failure to adjust for race does not lead to appreciable bias when estimating ORs for the genetic markers shown here. However, this finding may not apply to other cancers or other genetic markers.