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From Clinical Research and Development, Pfizer Global Research and Development, New London, Connecticut (Dr Harty and Dr Power) and Clinical Research and Development, Pfizer Global Research and Development, Ann Arbor, Michigan (Dr Johnson).
Address for reprints: Aidan Power, MB, BCh, MRCPsych, Pfizer Global Research and Development, 50 Pequot Avenue, New London, CT 06320; e-mail: aidan.c.power{at}pfizer.com.
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Key Words: Pharmacogenomics • race • ethnicity • genetics
The isosorbide dinitrate/hydralazine formulation is a combination of 2 older generic drugs and has been approved for the treatment of heart failure in self-identified black patients, a move the FDA press release hailed as a "step toward personalized medicine."2 The approval for this indication was based, in part, on the African American Heart Failure (A-HeFT) trial, which showed a 43% reduction in death compared to placebo,3 a significant improvement over previous trials in unselected groups of patients.4 A prospectively designed genetic analysis is being performed in a subset of patients who participated in A-HeFT focusing on endothelial nitric oxide synthase (NOS3).5 This analysis represents an attempt to understand whether there is an underlying genetic reason for the difference in response to this therapy, possibly leading to the identification of responders by genetic variation that would cut across racial and ethnic categories. This finding could result in a drug whose use in a subpopulation is defined by genotype rather than by ethnicity. This development would be logical, given that 80% or more of genetic variation occurs among persons compared to the variation among populations.6,7 The consequence could be that, ultimately, ethnicity or race would not be a very useful guide to the use of drug therapies.8
Yet it is clear that significant disparities exist in health status, health care utilization, and outcomes among different racial and ethnic groups.9,10 There is considerable debate about the value of race and ethnicity in the prediction of disease, response to treatment, and health care outcomes, arguing for either the continued use of racial or ethnic classification or abandoning it altogether.11-15 The use of race and ethnicity as descriptors to segregate populations and evaluate contributions to drug response may appear to have some face validity at present. However, although genetic clustering may reveal population substructures for racial self-descriptors, these are not highly accurate because of population admixture, are subject to change over time and place, and may be more accurately assessed by taking into account other environmental and cultural factors that can be specifically measured.16,17 It has been argued that race is a fluid, social construct and a poor proxy for measures of social class, culture, and genes.18,19 There is thus a need to understand the context in which data concerning race were collected and to gather more specifically measurable data (ancestry, income status, neighborhood characteristics, etc) that will give more concrete meaning to the reality of the environmental and genetic circumstances.16 Indeed, use of these terms (race and ethnicity) without the accurate evaluation of these measurable contributing factors has been seen as a tendency to reify "race," hence raising the danger of reinforcing and maintaining inequities in health care.16,20
With regard to the extent to which race or ethnicity are satisfactory proxies for genetic factors, evidence is accumulating that, in fact, causative genetic variation will have the same effects across different populations. It is true that allelic variation contributes across populations to risk of disease and that the magnitude of risk may also vary among populations. For example, the odds ratios for risk of Alzheimer's disease associated with the APOE4 allele differ among white, African American, and Japanese populations.21 However, a recent analysis of genetic association studies in 43 diseases showed that the biologic impact of genetic variation is usually consistent across racial groupings.22
Likewise, ethnic variation in drug response has been shown to occur relatively frequently.23-25 It has been shown that in the case of abacavir, the effect of genetic variation in predicting risk of hypersensitivity differs among populations.26 However, the nature of the contribution of the HLA variation in increasing risk of adverse reactions has not been fully explained. By contrast, when functional variation in drug-metabolizing enzymes is evaluated for contributions to drug response, the effect appears to be consistent across different populations.24,27
The goals of the Human Genome Project and now the HapMap Project are to provide the tools that will enhance our understanding of the genetic contributions to disease and diversity.28 As the sciences of genetics and epidemiology develop during the next few years, we will gain improved understanding of the specific genetic and environmental contributions to disease. Likewise, as the science of pharmacogenomics develops more accurate tools to identify the molecular underpinnings of drug response, the need for classification by race will be replaced by more accurate and specific identification of each individual person's likelihood of responding to a particular drug therapy.
This is not to say that there are not significant challenges ahead for pharmacogenomics. Specific pharmacogenomics studies are reliant on adequate numbers of samples collected from appropriate clinical trials. The power of analyses is limited by the numbers of markers needed to test assumptions and the variation in linkage disequilibrium blocks across populations, limitations that HapMap will help to address.29
It is likely that for the foreseeable future, racial and ethnic descriptors will continue to be used in medical and scientific research, at least until the specific determinants can be identified and measured. We should not hold on to race or ethnicity as though it captures something mysterious and predictive, but rather we should seek to define and measure what it is capturing in broad strokes and strive to define it more precisely. Genomics illustrates the progress that has been made in identifying genetic variation and, in some cases, the functional significance of these variants. However, much more work is yet to be done to capture all the genetic and environmental factors relevant to drug response and then to derive clear-cut treatment guidelines from them.
The goal of pharmacogenomics is to develop more precisely defined therapies for patients and to individualize treatment as far as possible. Population descriptors (racial, ethnic, or otherwise), while having some value in initial categorization, are relatively crude measures that rarely have useful predictive value at the level of the individual patient. The future state of pharmacogenomics may not require these descriptors at all.
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 R. Temple and N. L. Stockbridge BiDil for Heart Failure in Black Patients: The U.S. Food and Drug Administration Perspective Ann Intern Med, January 2, 2007; 146(1): 57 - 62. [Abstract] [Full Text] [PDF]
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