Beyond the questions of whether to employ direct or indirect measures of insulin resistance and whether to model simple or composite phenotypes, there is the matter of genotyping strategies. The study of candidate genes has proven to be a popular approach. A candidate gene is usually defined as a gene whose protein product, based on its biological activity, can plausibly be assumed to influence the trait under consideration. The main problem with this approach is that the number of such proteins is legion. In the case of insulin resistance the list would presumably include proteins that influence insulin binding to its receptor, those involved in the insulin signaling pathway, those influencing glucose uptake and cell metabolism, and no doubt countless others, both known and unknown. Variation in any one of these proteins could potentially affect insulin sensitivity. Moreover, as more is learned about these pathways, the list of potential candidate genes, already dauntingly large, grows seemingly without limit. The chances of a “lucky hit” would seem to be remote, and indeed, studies with candidate genes have thus far proved to be disappointing.
Before investing major resources in studying a potential candidate gene, it would seem that a stronger prior hypothesis implicating the proposed candidate is needed, rather than just a general sense that, based on its biology, it could influence insulin action. Efforts to implicate candidate genes often take the form of association studies, which can be performed in either related or unrelated individuals. Population stratification — that is, the existence of more than one ancestral source of a population’s gene pool — represents a major limitation of this study design. If, as is likely, the various ancestral sources differ both in their susceptibility to various diseases and in the frequency of various genetic markers, spurious associations may be observed between genetic markers and various phenotypes. In some cases, the existence of population stratification is well appreciated, as in the case of Mexican-Americans, whose gene pool derives from both European and Native American sources. In other cases, the basis of population stratification is more obscure. This problem can be ameliorated to some extent by selecting appropriate controls, especially family-based controls, which help assure that whatever population stratification affects the cases also affects the controls. Still, it is likely that population stratification is at least partly responsible for the large number of reports of association between candidate gene polymorphisms and diseases or conditions that have later proven to be nonreplicable.
With the increasing availability of large numbers of highly informative genetic markers, particularly microsatellite markers that now span the entire genome, the strategy of whole-genome scanning for linkage to phenotypes of interest has become feasible. Controversy still exists over what lod scores should be taken as evidence of linkage, but, based on simulation studies, widely accepted criteria for “suggestive” and “significant” linkage are lod scores above 2.0 and above 3.0, respectively (21
). A candidate gene located in a chromosomal region that has been found to be linked to a phenotype of interest is referred to as a “positional” candidate. Sometimes a gene whose protein product might not otherwise strongly recommend itself as a candidate by virtue of its biological activity may suddenly be considered a plausible candidate by virtue of its presence in a linked region. One should be cautious, however, since linkages detected in whole-genome scans with microsatellite markers typically implicate relatively large chromosomal regions extending over perhaps 20–30 centimorgans (approximately 20–30 megabases). Such regions typically harbor hundreds of genes.
If a genetic variant in a positional candidate is later found to be associated with a phenotype, the prior evidence of linkage provides at least some degree of reassurance that the association is not an artifact of population stratification. For example, the gene for membrane glycoprotein PC-1 is considered to be a candidate for insulin resistance, since this protein has been shown to inhibit insulin receptor tyrosine kinase activity in cultured fibroblasts (22
). We have recently reported genetic linkage between the chromosomal region where this gene is located and fasting serum insulin concentration (lod = 3.9) in nondiabetic San Antonio Family Diabetes Study participants (23
). Clearly, this evidence of linkage enhances this gene’s status as a candidate gene. On the other hand, given the relatively broad chromosomal region implicated in the linkage analysis, it is important not to become overly enamored of this or any other positional candidate merely because, of all the genes in the linked region, its function happens to be known.
Just as the presence of detectable linkage does not anoint a positional candidate, neither does the absence of linkage exclude a candidate’s possible significance. Even if a given candidate gene does not play a major role in the overall distribution of insulin sensitivity, it may still be responsible for minor variations in the phenotype in the general population, or it may exert major effects on a small number of individuals in the population. Thus, mutations in the Insulin Receptor
gene clearly produce insulin resistance in various relatively rare conditions (3
), but linkage studies indicate that variation in this gene accounts for, at most, a minor proportion of the variation in insulin sensitivity in the general population.