Now that the sequence of the human genome has been determined, we know that polymorphic sequence variations occur in every individual at a frequency of approximately one in 1000 base pairs (Venter et al., 2001
). Because mammalian genes generally contain thousands of base pairs, it is to be expected that genetic variability among individuals will occur at most, if not all, genes—and therefore in most, or all, molecular targets for toxicants. This suggests that genetic variation may to be found to be a major cause, or perhaps the major cause, for variation in susceptibility to toxicant exposure. This possibility is supported by the exponentially growing list of spontaneous pathologies (diseases) associated with genetic variants (Ashton et al., 2002; Balmain et al., 2003; Botstein and Risch, 2003) as such variants would be expected to be involved with both spontaneous and chemically induced pathologies.
Of course, the knowledge that genetic variation can influence sensitivity to toxicants is not new. Classic examples are the sensitivity to fava bean toxicity among Mediterranean populations with glucose-6-phosphate dehydrogenase deficiency (G6PD) and the sensitivity to isoniazide among subpopulations with N-acetylase variants (Kalow, 1965; Weber, 1999). Historically, the term "pharmacogenetics," and by extrapolation "toxicogenetics," was applied to the study of the influence of genetic variation on pharmacological or toxicological response (Kalow, 1968). However, advances in the technologies of sequencing and identification of sequence variants have resulted in a set of linkage markers that now make it possible to efficiently identify highly penetrant polymorphisms that modify biological outcomes (Roses, 2002). This was made possible because of the realization that sequence variations in the human are linked in chromosomal blocks that have not been fully randomized during the course of evolutionary crossing-over, a phenomenon known as linkage disequilibrium (Dawson et al., 2002; Goodman, 2002; Stumpf, 2002). Thus, a set of linkage markers covering the entire genome is now available (Roses, 2002). Because of this linkage, it is possible to first determine whether a biological outcome is associated with one of these blocks and then, knowing that the outcome has a genetic basis, to identify the specific sequence variations responsible for the observed effect (Fig. 3). This strategy, coupled with ever-improving technologies for efficient haplotype screening (see, e.g., Buetow et al., 2001; De La Vega et al., 2002), will greatly diminish the time and effort required to identify associations between specific genetic variations and biological outcomes. Thus, the traditional field of pharmacogenetics is now being transformed into pharmacogenomics—the study of the effects of genetic variants across the entire genome rather than one gene at a time (Cantor, 1999).
Examples are now known in which genetic polymorphisms, in addition to the classical metabolic polymorphisms, render individuals sensitive to specific forms of toxicity. For example, polymorphisms in the structural proteins of the cardiac potassium channels are known to render individuals sensitive to drugs that induce prolongation of the cardiac Q-T interval, with an attendant risk of fatal cardiac arrhythmia (Larsen et al., 2001; Weber, 2001). The ability to identify individuals with such polymorphisms opens the door to identifying the genetic factors that place individuals into high-risk categories. This has strong implications for designing drugs that minimize effects in sensitive individuals, individualizing treatment therapies, and designing initial clinical trials to include subjects with common (and less than common) polymorphisms that may influence the action of particular classes of drugs.
As genomic technologies become more available, it is not unrealistic to expect that an individual’s genotype for key genes associated with disease susceptibility, metabolic capacity, and drug sensitivity might become a routine part of one’s medical record and be used in diagnosis, selection of appropriate drugs, and adjustment of drug dosages on an individual basis. In recent editorials, Roses (2001) and Cantor (1999) speculate about the potential impact of such approaches on medical diagnosis and therapy, suggesting that genetically based medicine and pharmaceutical development may soon be commonplace.
In addition to providing a better understanding of the role of genetic variation in interindividual responses among humans, these same technologies will allow genetic characterization of laboratory animal model systems and their comparison with human systems. This should significantly improve our ability to extrapolate quantitatively across species. Further, genetic technologies have provided the capability of "humanizing" laboratory animal and cellular models. Thus, as important human targets for drug and toxicant interactions are identified and characterized, analogous laboratory models that allow these interactions to be studied in laboratory species can be constructed. Such models have already been created, demonstrating the feasibility of this approach. Examples include animal models of sickle-cell disease (Fabry, 1993), cell lines engineered to express the human cytochrome p450 drug-metabolizing enzymes (Crespi and Penman, 1997; Crespi et al., 1993), and animal and laboratory models containing human receptors or enzymes, and/or knockouts of specific genes of interest (Gonzalez, 2002; Nakazawa and Ohno, 1999).
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