It is easy to forget that these studies of associations between genes and diseases use the traditional epidemiologic tools of population studies. Investigators have the same concerns associated with any epidemiologic study: having appropriate design and analytic approaches, sufficient sample size and statistical power, and minimal bias and confounding. Despite hundreds of association studies and retrospective meta-analyses of polymorphisms in more than 30 genes that are associated with BMD and fractures, no convincing conclusions have emerged (13). The VDR gene is no exception. To try to address this issue, investigators have reported retrospective meta-analyses of published studies. For example, a recent meta-analysis by Fang and colleagues (14) has shown no relationship between the VDRBsmI or TaqI polymorphisms and fracture risk. However, these retrospective meta-analyses typically have significant between-study heterogeneity and biases. Between-study heterogeneity refers to dissimilarity, more than expected by chance, among the estimates of strength of association in the individual studies. Possible causes of dissimilarity include variation in allele frequencies, disease expression, effects of other genetic markers, or disease susceptibility across study samples. Genuine heterogeneity may be difficult to distinguish from the effects of publication or misclassification bias in meta-analyses (15). Lack of standardized genotyping methods and phenotype definitions across studies and publication bias, whereby positive associations are more likely to be published, are major contributing problems to heterogeneity, which in turn makes it difficult to draw conclusions from a body of research.