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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects 6 Methods for Predicting and Assessing Unintended Effects on Human Health This chapter focuses on current and prospective approaches for predicting and assessing unintended effects on human health from genetically modified (GM) foods, including those that are genetically engineered (GE), both before and after commercialization. (For an explanation of the distinction between GM and GE foods, see Chapter 1.) BACKGROUND The major challenges to predicting and assessing unintended adverse consequences—such as toxicity, nutritional deficiency, and allergenicity—stem from limitations in available data as well as in current scientific knowledge. For example, information about the range of normal compositional variability, especially in plant-derived food, is very limited. This significantly constrains the ability to distinguish true compositional differences of a “new” food from the normal variation found among its antecedents. To the extent that it cannot be determined whether the composition of a food has changed, it also cannot be predicted whether such changes have either adverse or beneficial health consequences. Even in cases where food composition changes are known, current understanding of the potential biological activity in humans for most food constituents is very limited. This becomes most evident when considering mixtures or diets consumed by human populations and then attempting to predict adverse health consequences from chronic intake of specific foods. Thus the present state of knowledge requires relying on a range of toxicological, metabolic, and epidemiological sciences to assess the significance of un-
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects intended health effects, using both targeted and profiling approaches (see Chapter 4). Employing a combination of these approaches builds on what is known and will increase the ability to detect or even prevent unsuspected consequences. Current approaches likely will be limited when applied to new GE foods with substantially altered composition. Consequently, a conceptual approach is presented in this chapter, grounded in the biological basis of adverse effects on human health and relying significantly on robust information regarding exposure. Despite the power of methods suggested by this conceptual approach and their ability to identify GE foods likely to have adverse effects, it is impossible using any method to prove the lack of an unintended effect. This is particularly true given the current state of knowledge regarding the exposure patterns of U.S. populations and how single food and mixtures of food components affect health. Thus requiring proof that there is no possibility of an unintended effect is not realistic for an assessment standard. The general conceptual approach for predicting and detecting adverse health outcomes discussed in this chapter is based on a risk assessment strategy proposed by the National Research Council (NRC, 1983) and relies on “substantial equivalence” to illustrate distinctions that may exist between foods modified by genetic engineering and those modified through traditional (non-GE) methods. This approach rests on the likelihood and functional significance of adverse outcomes of unintended or intended modifications being determined by several factors. These factors relate to the nature of the modification, such as whether it is quantitatively large or small and whether it is novel, and the characteristics of the compositional changes in question, such as dose-response outcomes and the nature and extent of likely exposures. Additionally, it considers population characteristics related to susceptibility, such as age, genetics, and nutritional status. STAGES IN THE DEVLOPMENT OF GE FOODS The development of a GE food involves a complex process that can be viewed as occurring in three stages: gene discovery, selection, and product advancement to commercialization. The safety of GE food should be assessed at all stages of its development (Taylor, 2001). Starting with an initial product concept, the gene discovery stage involves screening genes from many sources and selecting those that might contribute to a marketable result. Ideally, safety assessment should begin during this early gene-selection phase by taking into account each gene’s source, previous consumer exposure to the source, and whether there is a history of safe use for source material, the gene, and its specific products. In the case of GE plants, animals, and microbes, the next stage of the developmental process is line selection. Plants, for example, progress through a variety of steps in the greenhouse and field during which the biological and agronomic equivalence of the GE crop should be compared with its traditional counterpart.
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects These evaluations do not specifically focus on safety assessment, but many potential products with unusual characteristics are eliminated during this stage. This elimination process enhances the likelihood that a safe product will be generated. Finally, in the precommercialization stage for both GE plants and animals, the GE product should go through a detailed and specific safety assessment process. This process should focus on the safety of the products associated with the introduced gene and any other likely toxicological or antinutritional factors associated with the source of the novel gene and the product to which it was introduced. The safety of the GE product for both human and animal feeding purposes must be considered. SUBSTANTIAL EQUIVALENCE AND ITS ROLE IN SAFETY ASSESSMENT Given the relative novelty of genetic engineering, few examples are available that involve safety assessments for GE food, especially those with substantially altered composition that are the focus of this report. The use of substantial equivalence is one approach used to illustrate distinctions that may exist between foods modified by genetic engineering compared with traditional (non-GE) methods for modifying food composition. The concept of substantial equivalence provides a basis to plan a safety assessment designed to determine if GE foods are as safe as their traditional counterparts (FAO/WHO, 1996; IFT, 2000; OECD, 1993). It was developed in part because traditional toxicological approaches for evaluating the safety of food additives, pesticide residues, and contaminants do not work well in evaluating the safety of whole food, including GE food, because of the difficulties encountered in exaggerating the dosages of whole food in the diets of experimental animals. The concept of substantial equivalence is frequently misinterpreted because of the mistaken perception that the determination of substantial equivalence is the end point of a safety assessment, rather than the starting point. From a safety assessment perspective, the concept of substantial equivalence merely provides a framework for focusing any safety studies on the areas of greatest potential concern. Current GE varieties of traditional crops, such as corn and soybeans, are altered very little from their traditional counterparts. Thus the safety evaluation focuses on how GE crops differ from their traditional counterparts and further assumes that the unchanged components are just as safe as the traditional counterparts (see Chapter 4). With the concept of substantial equivalence, the GE food, or food component, is compared with its traditional counterpart for such attributes as origins of genes, phenotypic characteristics, composition—including key nutrients, antinutrients, and allergens—and consumption patterns. More recently, the phrase “substantial equivalence” has evolved into “comparative safety assessment” to encompass a broader meaning that includes an analytical
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects comparative component and a safety testing component of identified differences (Kok and Kuiper, 2003). Three outcomes are possible from the substantial equivalence comparisons (FAO/WHO, 1996). The subsequent examples are intended to illustrate the types of adverse consequences that may occur and not to signal a “clear and inevitable danger” of food derived by deliberate genetic modifications of food by traditional or more contemporary technologies. One possible outcome is that a GE food could be judged to be substantially equivalent to its conventional counterpart. In this case, no further safety testing would be required. However, this possibility is rather unlikely to occur in cases of GE foods that have substantially altered compositional traits compared with their conventional counterparts. In other cases, GE foods may be judged to be substantially equivalent to their conventional counterparts except for specific differences, including the introduced traits. In this situation the safety testing likely would focus on the safety of these differences and primarily on the introduced trait or gene product. An example for this outcome would be Bt corn or Roundup Ready soybeans. These products are those with traits, such as enhanced nutrients or reduced toxins, that usually are expressed by single genes and that share commonality with the vast majority of currently commercialized GE plants. Finally, the GE food could be judged not to be substantially equivalent to the conventional food or food component. Examples would include products with dramatically altered food composition, such as those aimed at improved nutritional profiles. More extensive safety assessments would be required for such products, including a more rigorous nutritional and toxicological assessment. Few products from this final category have been released into the commercial marketplace, so the nature of the safety assessment process in such cases has not yet been addressed by domestic and worldwide regulatory agencies. These safety assessments would need to be conducted in a rigorous but flexible manner, depending on the nature of the novel food product. During the process of substantial equivalence comparisons, extensive compositional analyses are conducted on the GE crop to compare it with the conventional counterpart. The selection of an appropriate comparator or comparators is obviously a key factor in this process. Comparisons should be made to the near isogenic parental variety from which the GE food was derived, and ideally to major commercial varieties of the same food, including varieties that are important in certain parts of the world where the crop will be exported. As noted previously, safety assessments typically focus on novel gene products and proteins, as well as any components that might be created in a GE food as a result of an enzymatic protein activity, or if the food has an effect on the metabolism of the host organism. The approaches to evaluating the safety of novel gene products are discussed later in this chapter. Limitations to assessments based
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects on the comparisons that can be made and sampling strategies are discussed in Chapters 3 and 4. Evaluation of Substantial Equivalence with Other Predictable Changes Applying the concept of substantial equivalence makes it possible to focus on the intentionally introduced traits and the novel proteins produced from the inserted genes. However, other predictable differences also may be identified. The possibility of altered metabolic profiles from the introduction of novel proteins with enzymatic activity is predictable for some GE food. In the case of golden rice, enhanced levels of carotenoids are produced as a direct, intended consequence of the genetic modification (Beyer et al., 2002). While this compositional difference in golden rice is intended to be beneficial to health (Nestle, 2003), the presence of the altered levels of carotenoids must also be part of the safety assessment. Applicability to Plant, Animal, and Microbial Organisms The framework of substantial equivalence has also been applied to GE animals and microorganisms. Assessment of the safety of the introduced traits or novel proteins can be approached in a similar fashion, no matter what the source of the inserted gene. This approach could also be applied to the identification of compositional differences and the safety assessment of food produced by all means of genetic modification. CURRENT SAFETY STANDARDS FOR GE FOODS On a worldwide basis, several organizations, including the Food and Agriculture Organization of the United Nations (FAO), the World Health Organization (WHO), and the Organization for Economic Cooperation and Development, have established the background for the safety assessment of GE food (FAO/WHO, 2000; OECD, 2000). In general, these organizations have concluded that GE products are not inherently less safe than those developed by traditional breeding (IFT, 2000). Furthermore, food safety considerations are similar to those arising from the products of traditional breeding other than food additives, which are subject to different regulations and testing procedures than food products. In the United States, the accepted standard of safety for foods produced from GE crops is the same as that for other similar food products. Under U.S. law for food additives, there must be a reasonable certainty that no harm will result from intended uses under anticipated conditions of consumption (Federal Register, 1992). There is no burden on the food manufacturer to demonstrate the safety of food products that are not food additives. However, the Food and Drug Adminis-
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects tration (FDA) can take action against a food, including GE food, if the food presents a demonstrable safety risk. SAFETY ASSESSMENT PRIOR TO COMMERCIALIZATION Safety of Ingested DNA As described in Chapter 2, genetic transfer between species has been shown to occur naturally as well as through human intervention. The deoxyribonucleic acid (DNA) present in plants, microorganisms, and animals used as food is ingested in significant quantities. Further, consumption of DNA, typically 0.1 to 1.0 g per day from food sources, is not known to be toxic (Doerfler and Schubbert, 1997). Additionally, the amount of DNA from a given GM food would likely represent less than 1/250,000 of the total amount of DNA consumed from all food sources (FAO/WHO, 2000). However, the possibility of transferring and incorporating novel genes from GM foods into cells has been investigated in animal models, humans, and microorganisms (gut bacteria). In model experiments in which mice were orally administered high doses of bacterially derived DNA, test DNA fragments were apparently incorporated into bacterial and mouse cells (Schubbert et al., 1998). This report contrasts with others in which no transfer or only a low frequency of transfer was observed (Biosafety Clearinghouse, 2003). Furthermore, the significance of the observations of Schubbert and coworkers (1998) has been seriously questioned by others (Beever and Kemp, 2000). As pointed out previously (WHO, 2000), the transfer of DNA from GM plants into microbial or mammalian cells, under normal circumstances of dietary exposure, would require all of the following conditions to exist: Relevant (potentially hazardous) genetic material in the plant DNA would have to be released from the plant cells, presumably as linear fragments. The released genetic material would have to survive digestion by nucleases both in the plant and in the gastrointestinal tract. The genetic material, once exposed to the gut, would have to compete for uptake with DNA from conventional foods. The recipient cells would have to be competent for transformation (uptake of the DNA), and the genetic material would have to survive enzymatic degradation by normal cellular mechanisms. The genetic material would have to be incorporated into the host DNA by rare enzymatic events. The consequences of uptake of DNA by somatic mammalian cells differs from that of uptake of DNA by microorganisms, as DNA in mammalian somatic cells is not transmitted to subsequent generations, but in microbes it may be. The
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects vast majority of known bacteria are not naturally transformable. No evidence exists for the transfer to and expression of plant or animal genes in microorganisms under natural conditions. Nielsen and coworkers (1998) did observe that plant genes could be transferred to bacteria under laboratory conditions only if homologous recombination was possible. In summary, the safety of GE products should be predicated on the characteristics of the novel protein or other product expressed by the gene, rather than on the safety of ingesting DNA or the possibility of horizontal transfer of novel genetic material to humans or gastrointestinal microorganisms. Safety Evaluation of Marker Genes and Their Products Products of marker genes are obvious predictable differences that should be highlighted in initial substantial equivalence comparisons. In addition to principal gene products, GE foods often contain antibiotic resistance marker genes or other marker genes that remain from the product development process. The most common antibiotic resistance marker gene expresses an enzyme called neomycin phosphotransferase II. The safety of commonly used antibiotic resistance markers has been well-established (WHO, 1993, 2000). However, a concern exists that antibiotic resistance might be transferred from a GE plant cell to intestinal bacteria in humans. Expert groups (WHO, 1993, 2000) have concluded that there is no evidence to support that the antibiotic resistance markers currently in use pose a health risk to humans or domestic animals (WHO, 2000). Several reasons exist for the well-established safety of antibiotic marker genes in GE foods, including: the lack of any evidence for the transfer of antibiotic resistance to intestinal bacteria or dietary pathogens; the extremely low theoretical likelihood of such transfers; and the use of antibiotic resistance markers for antibiotics that have limited clinical applications, such as neomycin (WHO, 2000). While there has been an increase in the prevalence of antibiotic-resistant bacteria, it cannot be attributed to the use of antibiotic resistance markers in GE foods. Increasingly, other methods are being employed in agricultural biotechnology that avoid the incorporation of antibiotic resistance marker genes into the commercial product. These methods include removing the antibiotic resistance marker gene after successfully transferring the desired genetic trait, or using alternative marker genes in the genetic transformation. If alternative marker genes are used, the products of these genes would also need to be evaluated for safety. Since limited experience exists with such alternative marker genes, the safety of these gene products has not yet been well established.
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects As previously stated, the safety of GE products should be predicated on the characteristics of the novel protein or other product expressed by the gene, rather than on the safety of ingesting DNA or the possibility of horizontal transfer of novel genetic material to humans or gastrointestinal microorganisms. Safety Assessment of Novel Gene Products Assessing the Potential Toxicity of GE food Toxicological studies in animals are considered on a case-by-case basis as part of assessing the safety of GE food (Kuiper et al., 2001). The demonstration of a lack of an amino acid-sequence homology of a novel protein to known protein toxicants and rapid proteolytic degradation under simulated mammalian conditions of digestion are often deemed sufficient to presume the safety of a novel protein. However, subchronic animal toxicological studies have also been conducted on some of the novel proteins and on GE food. As noted previously, the design and interpretation of animal toxicological studies with whole food, including GE food, is challenging. Methods exist for detecting the toxicity of chemicals in premarket evaluations. FDA has compiled a set of guidelines for toxicity testing of proposed food additives (OFAS, 2001). Similarly, the U.S. Environmental Protection Agency (EPA) has developed a number of guidelines for the toxicology assessment of pesticides, including a number relevant to the health effects of pesticides in food (OPPTS, 1996). Present guidelines, with the exception of the oral acute toxicity test, have not been applied to the assessment of currently approved GE foods. The traditional toxicological tests may be more relevant to the next generation of GE foods that will be substantially different in composition from traditional counterparts. However, application of the tests to whole food is difficult with existing methodologies, so such testing could likely be applied only to specific unique components identified in the GE variety. Although much testing is done in vitro, most involves feeding studies with whole animals. These studies attempt to minimize the numbers of animals used because of animal welfare concerns and because of costs. Most strategies rely on high doses of the agent under study to compensate, in part, for these limitations. Generally toxicologists first determine the maximum tolerated dose (MTD) of a substance, that is, a sufficiently high dose to cause an adverse effect, but not death. Levels close to and below the MTD are tested. This procedure is designed to maximize the tests’ statistical power, but it is not without controversy since testing at the MTD induces toxic effects that can cause physiological alterations to the animals that are not relevant in the case of humans exposed at much lower levels. In a number of rare cases, animal models have produced results that are not biologically relevant to humans at all, but generally these models have been work-
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects able. However, this approach was designed to assess conventional food additives and pesticides—not the effects of macronutrients or other food components that are difficult to isolate from whole food. Feeding food at the MTD is not feasible due to the high mass and volume of intake required, which would confound the results because of excessive caloric intake and other probable dietary imbalances. Occasionally, subchronic toxicity tests are conducted on GE food (Kuiper et al., 2001), although such testing is not typically part of the safety assessment approach used by commercial seed companies. In these tests the GE food is fed generally to rats or mice for at least 28 days (Kuiper et al., 2001). Feed consumption, body weight, organ weights, blood chemistries, and his-topathology are among the parameters that can be assessed in such experiments. However, the complexities involved in the design of subchronic toxicity tests complicate the interpretation of the results (Kuiper et al., 2001). From a practical perspective, subchronic toxicity tests likely can only be performed with the whole GM food (or some significant component of it, such as the oil fraction) because purification of sufficient quantities of the novel protein would usually be extremely difficult. The difficulties involved in the extraction of specific components from food for testing is illustrated by the bacterially-produced Cry9C protein in StarLink corn mentioned earlier. Moreover, traditional toxicological approaches have never been proven to have utility for testing complex mixtures, including whole food. The design of tests for food components will need to be informed by the fact that food components always occur as part of a complex mixture (see Chapter 4). The toxicity of any individual compound in food could be offset by other factors that are protective, such as those that prevent exposure by binding to dietary fiber or natural antioxidants. Likewise, the toxicity could be enhanced, for example, by facilitating absorption or by inclusion of natural substances that act via the same mechanism. A large effort is under way to develop new microarray technologies (see Chapter 4) in order to examine patterns of DNA expression that are associated with various types of toxicity, such as immune system response, receptor biology, signal transduction, protein modification, membrane transport, growth and development, metabolism, oxidative stress, and regulation of the cell cytoskeleton (Pennie, 2002). Assessing the Potential Acute Toxicity of Novel Proteins Most proteins are unlikely to be acutely toxic, particularly when ingested. However, an assessment of the acute toxicity of the novel proteins introduced into GE food is one approach to preventing unintended health consequences. Nevertheless, evaluation of the acute oral toxicity of a GE food and the novel proteins it may contain should be considered. Additionally, a bioinformatics database containing the amino acid sequences of known protein toxins should be
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects developed and maintained. This database could then be used to screen novel proteins for a sequence similar to known protein toxins. Further research will be needed to develop appropriate searching strategies to use with the database. Currently the acute toxicities of novel proteins are evaluated as part of the overall safety assessment in certain circumstances. These experiments typically involve oral administration of high doses of the novel protein by stomach tube to either rats or mice. Because many proteins are not for the most part toxic, the evaluation of the acute toxicity of novel proteins has not been particularly revealing. Examples of this application can be found for 5-enolpyruvylshikimate-3-phosphate synthase (Harrison et al., 1996) and neomycin phosphotransferase II, a marker gene product (Fuchs et al., 1993). The assessment results from these two studies indicated that the products containing the marker genes were as safe and nutritious as their conventional counterparts. The likelihood of the unintentional introduction of a novel, toxic protein into a GE food is extremely low, simply because proteins are rarely toxic, with a few noteworthy exceptions, such as botulinum toxins and staphylococcal entertoxins. Appropriate methods exist to assess the acute toxicity of novel proteins, and they can be implemented on a case-by-case basis as necessary. The use of subchronic and chronic toxicity testing in animals is not currently recommended as part of the safety assessment approach. Subchronic testing may be considered in cases where the novel protein has no safe history of use (e.g., proteins with lectins that may have neurotoxic actions). The current need, however, for comparatively large quantities of material precludes the use of the purified novel protein in long-term animal toxicology studies. Thus such studies would involve the use of whole GE food, which presents challenges for experimental design and interpretation. Assessing the Possible Allergenicity of Novel Proteins The identification of an unanticipated allergic response to a newly introduced protein in the diet is expected to be a rare event. If such responses were not anticipated from the premarket testing phase, the identification of these rare events would depend upon medical diagnosis of the allergic response and proper attribution of this response to the GE food, as discussed in Chapter 5. However, clinical approaches to the detection of rare allergenic reactions are questionable, so the focus of current assessment approaches has been on premarket assessment. Premarket Allergenicity Assessment Virtually all known food allergens are proteins, so the allergenic potential of all novel proteins must be determined. In 1996 a decision-tree approach for assessing the potential allergenicity of GE food was developed that relied upon evaluating the source of the gene, the amino acid sequence homology of the newly
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects introduced protein, the immunoreactivity of the new protein with serum immunoglobuline-E (IgE) from individuals with known allergies to the source of the transferred genetic material (specific serum screening), and the various physicochemical properties of the newly introduced protein, such as heat stability and digestive stability (Metcalfe et al., 1996). This decision-tree approach, as modified by FAO/WHO (2000), is depicted in Figure 6-1. Additional criteria have been suggested to assess the allergenicity of GE food, including comparing the overall structural identity with known allergens, targeted serum screening, and animal models (FAO/WHO, 2001). The Codex Ad Hoc Intergovernmental Task Force on Safety Assessment of Genetically Modified Foods recommended using only information on the source of the gene, structural comparisons with known allergens (both overall structural identity of 35 percent or greater and amino acid sequence identity of eight contiguous amino acids or more), specific serum screening, and pepsin resistance because targeted serum screening and animal models have not yet been validated for use in such applications (Codex Alimentarius Commission, 2002). The Report of the Fourth Session of the Codex Ad Hoc Intergovernmental Task Force on Foods Derived from Biotechnology (FAO/WHO 2003) reviewed these assessment guidelines for inclusion in the Draft Guideline for the Conduct of Food Safety Assessment of Foods Produced Using Recombinant-DNA Microorganisms. As noted, the likelihood of the unintentional introduction of an allergen into a GE food is low, but it should be evaluated in every case. Although no single test can provide complete assurance that a novel protein from a source with no history of allergenicity will not act as an allergen, the combined application of all of the approaches discussed above can provide reasonable assurance that a novel protein has a low probability of acting as one. The various tests and criteria used to evaluate the potential allergenicity of GE food have been thoroughly discussed elsewhere (FAO/WHO, 2000, 2001; Metcalfe et al., 1996; Taylor, 2002; Taylor and Hefle, 2002). Several approaches should be considered to improve the assessment of the potential allergenicity of novel proteins. First, since structural comparison between novel proteins and known allergens are predicated on the availability of a sequence homology database of known allergens, a publicly available database, as mentioned above, should be created for use by researchers, regulators, and agricultural biotechnology companies. This database would ideally contain known allergens from all environmental sources, including food. A scientifically rigorous approach should be used to determine which proteins should be included in this database as known allergens. Research is recommended on searching strategies to develop sound, discriminating approaches that identify potential allergens. Because pepsin resistance seems to be a characteristic of many food allergens, a need exists to standardize methods for assessing this attribute. In those cases in which genes are obtained from known allergenic sources or the sequence comparison yields potentially significant similarities to known al-
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects tem involvement and of very uneven global distribution. Safety evaluations of products likely to be consumed by populations with high infection rates require deliberate considerations relevant to immunological, gastrointestinal, and other physiological functions. Economic constraints that impose overwhelming dependencies on specific food staples raise concerns related to the extent and duration of exposure. The majority of the world’s population depends daily on a limited number of foods. The most notable are corn, rice, wheat, and cassava. Changes in these products will impact total dietary intakes to a level proportionate to their dietary dominance. Under conditions of dietary monotony, three factors increase the possibility of adverse consequences and the likelihood of their functional significance: intakes of the modified product are high; exposure is prolonged and persists through most, if not all, of the life course; and the proportion of those exposed is nearly universal. The latter is particularly relevant if genetic variability significantly influences adverse responses to the agent’s consumption. Measurement Error and Confounders Considerable error may be associated with exposure assessments, resulting in exposure misclassification. Such misclassification usually results in an estimate of the association between exposure and outcome that is closer to the null than to the truth (Kelsey, 1996; also see Rothman and Greenland, 1998). In targeted studies at the individual level, the estimate can be improved with the use of a validation substudy that is internal to the main study (Spiegelman et al., 2001). In the validation substudy, a more detailed dietary intake assessment would be performed using repeat measures. For example, these might include multiple blood draws for biomarker assessments. When the validation study is large enough, with more than 340 participants, an internal estimate of the association of exposure with the outcome can be obtained and adjusted for misclassification (Spiegelman et al., 2001). A balanced design for the validation study in which an equal number of people are sampled in the four groups defined by the imperfect exposure measure and the outcome variable has been shown to perform well (Holcroft and Spiegelman, 1999). The consequences of exposure misclassification on exposure assessment are greater for exposures that are rare than for exposures that are common. Self-selection issues have plagued epidemiological investigations that rely on observational studies. Exposure to a factor might be higher or lower because of association with a personal characteristic that is also associated with the health outcome. Health-conscious people may be healthier than others and are likely to follow healthy behaviors. Associations between the exposure and health effect might then be due to the confounder, which may or may not be measured. This kind of pitfall is well known, and methods to minimize confounding in the study
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects design and cautions in inferences made from observational studies are standard practice (Kelsey, 1996; Lilienfeld, 1994). Health Monitoring In specifically designed epidemiological studies or in surveillance studies using routinely collected data, the health outcomes studied fall into four broad classes: mortality (disease specific), incidence (disease specific), integrated measures of health (e.g., health related quality of life or quality adjusted life years), and intermediate health outcomes (e.g., serum cholesterol and other lipid markers). In specific studies, due care is taken to obtain an unbiased assessment of health outcome that is complete and such that the health effects estimated are reproducible. Systems that are in place for routine surveillance include the national health surveys discussed earlier. A key factor in postmarket surveillance is the collection and analysis of adverse effects reports. Such reports usually come from health care providers and give an indication of possible adverse effects of an agent so that investigators can determine if there is a pattern of such effects that may be causal. This was done with birth defect diagnoses and exposure to clarithromycin in which pharmacy and hospital claims were monitored (Drinkard et al., 2000); with medical reports associated with aspartame use (Butchko et al., 1994; Tollefson and Barnard, 1992); and with adverse events monitoring with respect to Olestra (Slough et al., 2001). Birth defect monitoring systems are maintained by most states; the completeness of the registries varies. Detection of a change in frequency over time has led to specific epidemiological studies of birth defects (e.g., the Chernobyl accident, trisomy 21 in West Berlin, and neural tube defects in a small series in Turkey) that have not been replicated by other studies (Little, 1993). There are also several cancer registries as part of the Surveillance, Epidemiology, and End Results Program (NCI, 2001). A health monitoring system that links such registries to exposures of interest may enhance the ability to detect unsuspected outcomes. Longitudinal data on food consumption patterns can at times be linked with health data via the use of health plan databases and hospital admissions and discharge records. The observed and expected rates of birth defects or specific diagnoses can be compared. It often is noted that these data are subject to potential biases, such as uncontrolled confounding and ecological fallacy. However, such analyses, if well designed, can use more sophisticated statistical techniques that allow inferences to be drawn. Several authors have advocated the use of nonclassical model-based methods in this regard, including Bayesian methods, with applications to specific investigation of trends in breast cancer mortality (Bernardinelli et al.,1995), chronic myeloid leukemia (Chen, 1999), cancer of the oral cavity (Knorr-Held and Rasser,
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Safety of Genetically Engineered Foods: Approaches to Assessing Unintended Health Effects 2000), and particulate matter air pollution and premature mortality (Dominici et al., 2003). There are no routine systems of cardiovascular morbidity ascertainment, although there are several large epidemiological cohort studies that include the endpoints of stroke or myocardial infarction, such as the Framingham study, the Nurses Health Study, the Women’s Health Initiative, the Physicians Health Study, and the Cardiovascular Health Study (Abbott et al., 1988; Ma et al., 1999; Psaty et al., 1999; Rimm et al., 1998; Rossouw et al., 2002). Mortality data are collected routinely at the local level and aggregated into county and state statistics with associated age, gender, and other sociodemographic information. By extracting information from national surveys such as NHANES, it is possible to impute values for functional status or quality of life, such as the Health Utility Index, or the SF36. These in turn can be integrated with mortality information to calculate quality-adjusted life years. DISCUSSION The ability to evaluate the unintended health effects of a genetically engineered organism that expresses a significantly different phenotype than its conventional counterpart is problematic (Kuiper et al., 2001). As recognized by other expert panels, current risk-assessment paradigms and drug-safety evaluation programs are inappropriate methods to apply to the determination of the potential for unintended adverse health effects of GE food (Atherton, 2002; FAO/WHO, 2000). Unlike chemicals and drugs, a dose-response relationship cannot be established for food (i.e., it is not possible to dose an animal with 10, 1, and 0.1 times the volume of food). Foods also represent complex mixtures that must be tested as a whole to consider possible nonadditive interactions that can significantly impact toxicological outcome (Dybing et al., 2002). Consequently, even though these technologies may satisfy the hazard identification step of risk evaluation, there are no existing validated methods for dose-response characterization for a complex mixture such as food. New approaches should be based on a risk-assessment strategy proposed by the National Research Council (NRC, 1983) and rely on “substantial equivalence” to illustrate distinctions that may exist between foods modified by genetic engineering compared with those modified through traditional (non-GE) methods. Further, such evaluations would be expected at all stages of product development, including gene discovery, selection, and advancement to commercialization, and followed by postmarketing studies to further assess both intended and unintended effects. Epidemiological studies may be helpful in the postmarketing phase, provided they are conducted with the rigor that contemporary methods allow. The more definition that can be brought to bear with respect to defining exposure, the greater the inferential potential of these observational population-based methods.
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