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14 Nutrigenomics John Milner, Elaine B. Trujillo, Christine M. Kaefer, and Sharon Ross B elief in the preventable nature of many chronic diseases coupled with rising health care costs has propelled consumers to seek more information about the quality of their diet and how dietary change might influence their life. This increased interest in the medicinal uses of foods or their components is not a new concept but has been handed down for generations. In fact, Hippocrates is often quoted as suggesting almost 2,500 years ago âto let food be thy medicine and medicine be thy food.â In the United States, approximately 80 percent of adults ages 65 and older have at least one chronic health condition, and at least half of this population has two or more chronic health conditions that contribute to disability, decreased quality of life, and increases in health care costs (Goulding, 2003). Not surprisingly, the estimated health care costs for those ages 65 and older in developed countries typically range from three to five times greater than the health care costs associated with younger people. In addition, health care expenditures in the United States are almost double the amounts spent on health care in many other countries (Goulding, 2003; Organisation for Economic Co-operation and Develop- ment, 2005). Many consumers believe lifestyle, which includes dietary habits, must be a contributor to the higher health care expenditures in the United States. Since more than 75 percent of U.S. health care costs are linked with one or more chronic diseases, and diet is linked to 5 of the 10 major causes of death for Americans, there is ample justification for such widespread interest. The significance of dietary components to health is not limited to the 278
MILNER, TRUJILLO, KAEFER, and ROSS 279 United States, since nearly 60 percent of deaths worldwide are diet related, and there is increased recognition that inappropriate nutrition contributes to increasing health care costs in most settings (World Health Organiza- tion, 2004). Some of the most common causes of death both globally and domestically include cardiovascular disease, cancer, and diabetes, which are intimately linked to eating behaviors (Centers for Disease Control and Prevention, 2004; World Cancer Research Fund and American Institute for Cancer Research, 1997; World Health Organization, 2004, 2005). The 2003 report from a Joint World Health Organization/Food and Agriculture Organization Expert Consultation on Diet, Nutrition, and the Preven- tion of Chronic Diseases reviewed a large body of scientific evidence and found that up to 80 percent of coronary heart disease, 90 percent of type 2 diabetes, and one-third of cancers may be prevented by healthy eating practices, maintenance of a normal weight, and regular physical activity (Nishida, Uauy, Kumanyika, and Shetty, 2004). Public health messages have centered on optimizing health for popu- lations. The approach has considerable merit, although it is clear that not all individuals respond identically to treatment, whether by dietary change, lifestyle change, or drug therapy. There is much that needs to be learned regarding what accounts for individual differences, including the interactions occurring between genetics and the environment. As noted in a 2003 World Health Organization report on chronic diseases, genes help âdefine opportunities for health and susceptibility to disease, while envi- ronmental factors, including diet, determine which susceptible individu- als are most likely to develop illnessâ (World Health Organization, 2003). Each stage of life is influenced by manmade and environmental factors that affect chronic disease risk. The interaction of genes with environmen- tal influences throughout the life span creates multiple opportunities for tailored behavioral health interventions. âGenomeâ is a term that refers to the entire DNA sequence of an organism, and âgenomicsâ is the scientific discipline of mapping, sequenc- ing, and analyzing the genome (Mathers, 2004). The human genome is an undeniably amazing blueprint of information. While all DNA consists of four simple bases, their sequence has a pronounced effect on health. Advances in molecular biology have already begun to reveal a wealth of information about human growth and development. Fundamental to genomics is the transcription of DNA to RNA (transcriptomics), which is subsequently translated to proteins (proteomics). Proteins bring about changes in cellular structure and small molecular weight compounds (metabolomics), which can influence one or more biological processes that ultimately determine a personâs phenotype (Figure 14-1). It is important to note that the relationship between transcriptomics, proteomics, and metabolomics is not linear. That is to say, there is not
280 BIOSOCIAL SURVEYS DNA Transcription RNA Dietary Component Translation Protein Metabolism Metabolite FIGURE 14-1â Dietary components can modify DNA transcription, translation, and metabolism. necessarily a direct link between the amount of expression of a particular mRNA and the level of protein expressed. If the resulting protein is an enzyme, the resulting metabolite concentrations are not always propor- tional. Thus, complex and poorly understood regulatory processes exist that can influence overall phenotype. Regardless, it is safe to conclude that the more knowledge gained about the human genome, the more there will be to learn about the prevention and treatment of human disease. The discovery of about 3 billion chemical coding units in human DNA has already opened unexpected opportunities for understanding in greater Figure 14-1 detail what commonalities are shared among all humans and what con- stitutes individuality. Differences in gene pool may account for population differences in the risk of developing such diseases as diabetes, heart disease, and cancers. Single-nucleotide polymorphisms (SNPs) differ in a single base from the generally accepted sequence, which occurs in at least 1 percent of the
MILNER, TRUJILLO, KAEFER, and ROSS 281 general population. SNPs are the commonest form of genetic variability. Humans have about 30,000 genes and roughly 5 to 8 million SNPs (Har- land, 2005). Several gene polymorphisms have been identified as screen- ing tools for predicting disease risk, including the HFE gene for heredi- tary hemochromatosis and the E-4 allele of the apolipoprotein (ApoE) gene for hypercholesterolemia and Alzheimer disease (Motulsky, 1999). Recently, the Genetic Association Information Network (GAIN) was cre- ated to support a series of genome-wide association studies designed to identify specific points of DNA variation associated with the occurrence of common diseases (http://www.genome.gov/19518664). In addition, in 2006, the National Institutes of Health (NIH) established the Genes and Environment Initiative (GEI) to support research that will lead to the understanding of gene-environment interactions in common diseases (http://www.genome.gov/19518663). Nutrigenomics It has long been recognized that humans have an individual respon- siveness to the foods they consume. Phenotypic variation to foods can be as subtle as sensitivity to bitterness, as reflected by the response to com- pounds like phenylthiocarbamide, or as gross as obesity, as reflected by differences in energy utilization (Clement, 2005; Wooding et al., 2004). Col- lectively, the scientific study of the way foods or their components interact with genes to influence phenotype is referred to as ânutrigenomicsâ or ânutritional genomicsâ (Davis and Milner, 2004; Trujillo, Davis, and Milner, 2006). The science of nutrigenomics is starting to provide greater clarity to the genetic pathways and associated molecular targets that account for the ability of food components to result in a physiologically relevant response. Researchers are beginning to unravel the genetic factors that influence an individualâs eating behaviors. Although this area of research is still in its infancy, new analytical approaches, including genome-wide linkage scans and association studies with candidate gene markers and eating behav- ior are beginning to surface (Rankinen and Bouchard, 2006). This chapter focuses on the role of nutrigenomics in health and disease prevention and related insights on how nutrition-related biomarkers may assist in dissect- ing individual differences in populations. The use of genomic technologies in nutrition research is relatively new but can have profound scientific implications for the development of public health messages and policy. Public screening programs that cap- ture genetic information about an individual are already having an impact on nutritional intervention strategies. A perfect example is phenylketon- uria (PKU), a rare metabolic disease involving the absence or deficiency of an enzyme needed to process an essential amino acid, which leads to
282 BIOSOCIAL SURVEYS mental retardation without proper treatment. Newborn blood screening for PKU has been part of public health programs in many parts of the world for decades, and the use of a phenylalanine-restricted diet is the accepted standard of care for this disease (National Institutes of Health Consensus Panel, 2001). Nutrients and Single-Nucleotide Polymorphisms Vitamin D is a fat-soluble vitamin that is found in food and can be formed in a personâs skin in response to sunlight. In the presence of adequate ultraviolet light (UVB) in the wavelength range of 290-315 nm, a dietary intake of vitamin D may not be needed. Since adequate exposure to UVB is not always possible for a variety of reasons, a dietary source of vitamin D is needed to avoid skeletal diseases that weaken bones, such as rickets and osteomalacia. There is also evidence that vitamin D adequacy may play a role in immune function and the regulation of cell growth and differentiation, and therefore vitamin D may be a factor in the development of cancer (Holick, 2006). The vitamin D receptor (VDR), a nuclear hormone receptor, is known to mediate the biological actions of 1,25-dihydroxyvitamin D3 (1,25(OH)2 D3), which is the physiologically active form of vitamin D, by regulating a variety of target genes involved in cell proliferation and differentiation. There are several known VDR polymorphisms that may affect the response to various dietary components and disease risk. One particu- lar VDR polymorphism is FokI, which results in a VDR protein that is three amino acids longer than the protein produced from individuals carrying the nonvariant F codon. Individuals with the Ff or ff genotype were reported to have a 51 and 84 percent greater risk, respectively, of developing colorectal cancer (Wong et al., 2003). Those consuming a low- calcium or low-fat diet were found to have more than double the risk of colorectal cancer when they carried the ff compared with the FF genotype. Data (Wong et al., 2003) suggest that once the inadequacy of the diet is eliminated, the effect of genotype disappears. Thus, this polymorphism may serve as a predictive marker for those who will benefit most from adequate nutrient intakes. Two additional vitamin D receptor polymorphisms (Bsm1 and poly A) also have been linked to calcium and vitamin D intake. Interestingly, these polymorphisms were related to energy consumption and the risk for colorectal cancer (Slattery et al., 2004). The occurrence of multiple VDR gene polymorphisms raises questions about the importance of single SNPs in accounting for variation and which diet-allele interactions are the most important determinants of phenotype. At least some evidence
MILNER, TRUJILLO, KAEFER, and ROSS 283 suggests that racial differences may exist in regard to the type of variance that occurs and its relationship to disease (Kidd et al., 2005). Thus, multiple variables, including diet and race, can influence the relationship between VDR and disease risk (Slattery et al., 2004; Wong et al., 2003). Studies are needed to expand the understanding of the molecu- lar and cellular significance of various polymorphisms, copy number variations, and their utility in population studies to detect susceptibility under a variety of environmental conditions (Redon et al., 2006). In fact, large longitudinal cohorts to evaluate both genetic and environmental factors that contribute to disease have been proposed (Manolio, Bailey- Wilson, and Collins, 2006). A polymorphism in the angiotensinogen gene may determine how an individualâs blood pressure responds to dietary fiber (Hegele, Jugenberg, Connelly, and Jenkins, 1997). Angiotensinogen is a liver protein involved with increasing vascular tone and promoting sodium retention, and plasma levels correlate with blood pressure. Individuals with a particular angiotensinogen genotype (TT) had a decrease in blood pressure when provided a diet with increased amounts of insoluble fiber compared with increased amounts of soluble fiber. In contrast, blood pressure in individu- als with a different genotype (TM or MM) was not significantly influenced by the type of fiber consumed. Thus, some of the reported discrepancies in the response of blood pressure to dietary fiber may be related to inter- individual genetic differences in response to different types of fiber. The response to other dietary components, such as caffeine, may also depend on specific SNPs. A study investigating the role of caffeine as a risk factor for bone loss in elderly women found that those with a variant of the vitamin D receptor (tt genotype) and who had caffeine intakes of greater than 300 mg/day had significantly higher rates of bone loss than did women with a different genotype (TT) (Rapuri, Gallagher, Kinyamu, and Ryschon, 2001). Since some individuals will not be receptive to caf- feine avoidance, it may be wise to develop alternative strategies for mini- mizing risk, including providing additional calcium, vitamin D, or both. Some additional examples of the interrelationship between SNPs and food components illustrate how reported discrepancies in the response to disease may arise from failure to account for interindividual genetic dif- ferences. The ApoE polymorphism is probably the most common example of a genetic polymorphism directly affected by a nutrient. ApoE plays an important role in lipid metabolism and its relationship to health and disease. There are three common allele variants, ApoE-2, ApoE-3, and ApoE-4. The ApoE-4 variant is associated with increased levels of total cholesterol and low-density lipoprotein cholesterol, which may increase risk for cardiovascular disease, but the opposite association occurs for carriers of ApoE-2. Some studies report greater plasma lipid responses to
284 BIOSOCIAL SURVEYS dietary manipulation in subjects carrying the ApoE-4 allele, while others fail to do so. A meta-analysis showed that ApoE-4 carriers were hyper- responsive to a low-fat diet. However, it is also true that ApoE-4 carriers may be hyporesponders to other types of interventions, such as dietary fiber (Ordovas et al., 1995; Uusitupa et al., 1992). While there is evidence that some diseases are associated with a SNP, the majority of the chronic diseases are thought to have multigenic roots. Thus, examining a single SNP may not provide sufficient detail to predict risk or appropriate inter- vention strategies. Diet-gene interactions, including the impact of the ratios of nutri- ents consumed on a particular genotype, may be particularly important. Nuclear receptors, specifically peroxisome proliferator-activated receptors (PPARs), regulate the expression of genes involved in the storage and metabolism of fats. One particular PPAR, PPAR gamma, is recognized for its involvement in regulating insulin resistance and blood pressure. In individuals with a specific polymorphism in PPAR gamma, a low polyunsaturated-to-saturated fat ratio is associated with an increase in body mass index and fasting insulin concentrations. When the dietary ratio of polyunsaturated to saturated fats is high, the opposite is true (Luan et al., 2001). The interaction between ratio and type of dietary fat and PPAR gamma genotype is another example of the complexity found in examining diet-nutrient interactions in conjunction with a single polymorphism. While there is mounting evidence that the frequency of functional polymorphisms may influence the response to a variety of dietary com- ponents, we need to validate and verify these findings (Davis et al., 2004; Stover, 2006; Trujillo, Davis, and Milner, 2006). Most findings are associ- ated with single observations and therefore need to be substantiated for their relevance and physiological significance in other settings. In addi- tion, attention needs to be given to the interaction of multiple genes in order to understand what is occurring within cells and ultimately being expressed in terms of health outcomes. Because of cost restraints, molecu- lar epidemiological studies have considered only a limited number of polymorphisms that may confer disease susceptibility. The use of hap- lotypes, which are a set of closely linked genetic markers present on one chromosome that tend to be inherited together, may offer a cost-effective solution for screening large populations. Alternatively, the need for low- cost whole genome DNA sequencing is being encouraged by a recent initiative from the National Human Genome Research Institute of NIH in order to reduce costs for sequencing individual genomes (http://grants. nih.gov/grants/guide/rfa-files/RFA-HG-04-003.html).
MILNER, TRUJILLO, KAEFER, and ROSS 285 Nutritional Epigenomics Epigenetics is the study of heritable changes in gene expression that occur without a change in DNA sequence and provide an extra layer of control in gene expression regulation. These regulatory processes are criti- cal components for normal development and growth of cells. Evidence continues to support the hypothesis that epigenetic abnormalities are causative factors in cancer, genetic disorders, and pediatric syndromes as well as contributing factors in autoimmune diseases and aging. Three distinct mechanisms are intricately related to epigenetics: DNA methylation, histone modification, and RNA-associated silencing. Abnor- mal methylation patterns are a nearly universal finding in cancer, as changes in DNA methylation have been observed in many cancer tissues, specifically colon, stomach, uterine cervix, prostate, thyroid, and breast tissues (Ross, 2003). Site-specific alterations in DNA methylation have also been observed in cancer and are thought to play a significant role in gene regulation and tumor behavior. The relationship between aberrant hypermethylation and hypomethylation on the expression of genes and their relationship to disease risk remains an area of active investigation. Because epigenetic events can be changed, they offer another explana- tion for how environmental factors, including diet, can influence biologi- cal processes and phenotypes. Dietary components have been reported to influence DNA methylation patterns. Food components influence these events in at least four different ways (Ross, 2003). First, dietary factors are important in providing and regulating the supply of methyl groups available for the formation of S-adenosylmethionine (SAM), the univer- sal methyl donor. Second, dietary factors may modify the utilization of methyl groups by processes that include shifts in DNA methyltransferase activity. A third plausible mechanism relates to DNA demethylation activ- ity. Finally, the DNA methylation patterns may influence the response by regulating genes that influence absorption, metabolism, or the site of action for the bioactive food component. The effect of maternal diet on phenotypic outcome in offspring has been examined in a mouse model, which is important because of its similarity in many ways to humans. The agouti mouse indicates that supplementation of choline, betaine, folic acid, vitamin B12, methionine, and zinc to the maternal diet increases the level of DNA methylation in the promoter region of the agouti gene and causes a change in the color pattern of the hair coat in offspring (Cooney, Dave, and Wolff, 2002). This phenotypic change coincides with a lower susceptibility to obesity, diabe- tes, and cancer. More recently, dietary genistein supplementation during pregnancy has been found to change the coat color of the offspring and reduce body mass, which were again reported to be related to changes
286 BIOSOCIAL SURVEYS in DNA methylation (Dolinoy, Weidman, Waterland, and Jirtle, 2006). While humans do not have the long-term repeating unit found in these mice, these studies serve as a proof-of-principle that diet can influence epigenetic events and lead to phenotypic change. These types of studies also suggest that in utero exposure to dietary components may not only influence embryonic development but also have profound and long-term health consequences. DNA methylation patterns are being utilized more frequently as bio- markers in population and case-control studies to determine if differences exist between certain exposed groups or between cases and controls. In one such investigation in patients with alcohol dependence, the DNA methylation pattern in the HERP (homocysteine-induced endoplasmic reticulum protein) promoter region was found to be hypermethylated in patients with alcohol dependence when compared with healthy controls (Bleich et al., 2006). Interestingly, this aberrant hypermethylation was also significantly associated with diminished expression of HERP mRNA as well as elevated homocysteine levels. These findings assist in understand- ing the pathogenesis of a disorder as well as support the importance of epigenetic control on gene expression and the impact of dietary influences on epigenetic control. Nutritional Transcriptomics Genomic and epigenomic shifts do not entirely account for the influ- ence that dietary factors can have on a personâs phenotype, since changes in the rate of transcription of genes (transcriptomics) can also be exceed- ingly important (Feder and Walser, 2005). Several bioactive food compo- nents have been reported to be important regulators of gene expression patterns both in vitro and in vivo. Vitamins, minerals, and various phyto- chemicals have been reported to significantly influence gene transcription and translation in a dose- and time-dependent manner. These changes are likely to be key to the ability of food components to influence one or more biological processes, including cellular energetics, cell growth, apoptosis, and differentiation, all of which are important in regulating disease risk and consequences. Transcriptomics allows for a genome-wide monitoring of expression for the simultaneous assessment of tens of thousands of genes and their relative expression. While microarray technologies provide an important tool to discover expression changes that are linked to cell processes, it must be remembered that any response may be cellular dependent and may vary between healthy and diseased conditions. Studies using ani- mal models are beginning to identify specific sites of action of bioactive food components. For example, the nuclear factor E2 p45-related factor
MILNER, TRUJILLO, KAEFER, and ROSS 287 2 (Nrf2) and the Kelch domain-containing partner Keap1 are modified by sulforaphane and allyl sulfur (Chen et al., 2004; Gamet-Payrastre, 2006). Sulforaphane is primarily found in cruciferous vegetables, such as broccoli and cabbage. Gene expression profiles from wild-type and Nrf2- deficient mice fed sulforaphane have shown several novel downstream events and thus provide more clues about the true biological response to this food component. The up-regulation of glutathione s-transferase, nico- tinamide adenine dinucleotide phosphate:quinone reductase, gamma- glutamylcysteine synthetase, and epoxide hydrolase, occurring because of release of Nrf2 from its cytosolic complex, may explain the ability of sulforaphane to influence multiple processes, including those involving xenobiotic metabolizing enzymes, antioxidants, and biosynthetic enzymes of the glutathione and glucuronidation conjugation pathways. Mammals are known to adapt to excess exposure to foods and their components through shifts in absorption, metabolism, or excretion. Thus, the quantity and duration of exposure must be considered when evaluating the response in gene expression patterns. Since microarray technologies provide only a single snapshot, overinterpretation of their physiological significance is certainly possible. While mRNA microarray technology continues to provide a powerful tool for examining potential sites of action of food components, their usefulness for population stud- ies remains uncertain. Transcriptomic technologies have been used to examine the relationship between diet and prostate cancer among native Japanese and second-generation Japanese American men as a function of consumption of animal fat and soy (Marks et al., 2004). This technology was able to discriminate between men with cancer and those who were cancer free. Likewise, detectable changes associated with body mass and metabolism were observed (Marks et al., 2004). Weight loss caused by caloric restriction has been reported to be associated with changes in the expression of several inflammatory-related genes as discovered by tran- scriptomics (Clement et al., 2004; Viguerie et al., 2005). To date, relatively few human studies have used transcriptomics to characterize the response to specific dietary components, and thus it is hard to make firm conclusions about the utility of this technology. Nev- ertheless, a recent study demonstrates that dietary intervention with high protein or carbohydrate breakfast cereals can influence gene expression patterns within a few hours after food consumption (van Erk, Blom, van Ommen, and Hendriks, 2006). However, much of the current evidence suggests that mRNA abundance is not always proportional to protein activity and thus cannot substitute for functional and ecological analyses of candidate genes (Feder and Walser, 2005). While the transcriptional profile can be useful in predicting metabolic stress, simpler indicators may suffice. It is possible that more select arrays may be useful if targeted
288 BIOSOCIAL SURVEYS to some cellular process. At this point it seems wise to evaluate carefully the costs and benefits of transcriptomics before including this research approach into large population studies. Other Factors Determining Risk: Population Differences There are well-documented differences in health between various populations and geographic areas; however, there is debate over the extent to which health disparities are due to âinnate genetic differences,â the âbiological impactâ of racial discrimination and lack of economic resources, or both (Krieger, 2005). Historically and in current scientific literature, a personâs race or ethnic group has been used as a way to cat- egorize and compare individuals as well as populations and their risks for developing various health conditions. It has been suggested that many of these labels are quite arbitrary (Krieger, 2005) and that the self-report of a personâs race or ethnicity often fails to accurately identify the full range of their genetic makeup (Gonzalez et al., 2005). Ongoing projects are aimed at cataloguing the patterns of human genetic variation throughout popu- lations in Africa, Asia, and the United States to assist in the identification of genes that impact health (Couzin, 2004). Genetic comparisons provide important information about ancestral links, and geographic distances between various populations may be more closely related to the intermingling of populations from different geographical areas than to the racial or ethnic group to which an indi- vidual self-reports (Thomas, Irwin, Shaugnessy, Zuiker, and Millikan, 2005). Nevertheless, migration studies provide interesting clues about the importance of the environment, including diet, in changing the health risk of individuals. For instance, men moving from Japan and China to the United States adopt increased risks of prostate cancer (Brawley, Knopf, and Thompson, 1998). Likewise, women moving from Japan to the United States were found to exhibit an increased risk of breast cancer in their new location (Cole and Cramer, 1977). Today, the incidence of breast and colon cancers is similar in both Japan and the United States, suggesting that environmental factors such as diet are primary determinants of risk. Biomarkers The use of a biomarker to indicate a biological response to selected foods and food components is critical, since long-term intervention stud- ies are difficult to conduct for a variety of reasons, including cost. Almost any measure that reflects a change in a biochemical process, structure, or function can serve as a useful biomarker. Several biomarkers may be used successfully to distinguish between healthy and diseased states and,
MILNER, TRUJILLO, KAEFER, and ROSS 289 in some instances, to predict future susceptibility to disease. While risk factors, including diabetes mellitus, smoking, hypertension, and hyper- cholesterolemia, have been linked to the risk of developing symptom- atic atherosclerosis, more sensitive biomarkers may offer early signals of shifts in risk. For example, lipid metabolism-related biomarkers such as lipoprotein(a) and apolipoprotein A-1 are associated positively and nega- tively, respectively, with premature atherosclerotic disease; however, there may be even earlier signals that are predictive of disease (Ordovas, 2006; Scheuner, 2001). Inflammatory markers, such as C-reactive protein (CRP) and fibrinogen, as well as thrombotic markers, such as fibrin D-dimer (DD) and tissue plasminogen activator, are receiving increased attention for their predictive value. Even nutrition-related factors, such as elevated plasma homocysteine, have been associated with the presence of athero- sclerotic arterial disease and its progression. It is highly unlikely that one biomarker will be shown to adequately predict disease risk; therefore, several sensitive, reliable, and inexpensive biomarkers are needed to adequately assess the benefits and risks associ- ated with consumption of specific foods and their bioactive components. It is likely that intake, biological effect, and susceptibility biomarkers will be needed to adequately evaluate the effectiveness of foods and their bio- active components (Figure 14-2). Assessment of dietary intake, performed by using various techniques such as 24-hour dietary recalls and food frequency questionnaires, is Susceptibility Dietary Phenotypic Exposure Target Change Quantity and Duration FIGURE 14-2 The quantity and duration of dietary exposures may bring about changes in the target (or biomarker) and result in phenotypic outcomes. Suscep- tibility factors may influence this process. Figure 14-2
290 BIOSOCIAL SURVEYS central for studies of the relationship between diet and health, and thus it is important that these dietary methods give an adequate measure of dietary intake. Given the variation in the content of individual food components, biological intake indicators, as reflected by circulating con- centrations or perhaps other obtainable tissue, may be particularly use- ful for reflecting the amount of bioactive food component or metabolite present in cells, tissues, or body fluids. Assessment of intake indicators is relatively straightforward analytically, but their use is complicated by the need to know the optimal measurement period after consumption and by variability in rates of metabolism and accumulation across tissues and biological fluids (Kohlmeier, 1995). These and other measurement errors can have profound effects on how dietary data are interpreted (Paeratakul et al., 1998). An interesting example concerning the relationship between dietary questionnaire data and circulating concentrations is highlighted for lyco- pene, a bioactive food component, in the European Prospective Investi- gation into Cancer and Nutrition (EPIC) study (Jenab et al., 2005). Serum lycopene concentrations have been reported to be inversely related to prostate cancer risk. EPIC investigators measured the consumption of tomatoes (raw and cooked) and tomato products (sauces, pastes, ketchup) in 521,000 subjects with country-specific dietary questionnaires across 10 countries. Furthermore, these investigators obtained plasma lycopene concentrations in a subgroup of 3,089 subjects from 16 EPIC regions (100 men and 100 women per region). The overall correlation of the total toma- toes and the tomato product intake with plasma lycopene was .33; the within-region correlation coefficient was .23, whereas the among-region correlation was .53. These modest correlations between the dietary consumption of tomato and the lycopene concentration in blood may be due to the imprecision of dietary measurements as well as variations in the bioavailability and the absorption of lycopene. The cooking and seasoning methods of tomatoes and tomato products and the methods of consumption can affect the bio- availability of lycopene. In addition, these generally low correlations of tomatoes and tomato products with plasma lycopene may be related to the time span between the exposure and the blood sampling, especially in light of the strong seasonal variations in the intake of tomato and tomato products. This example illustrates the complexity of assessing dietary exposure and the need for new approaches. The National Heart, Lung, and Blood Institute, along with the National Cancer Institute and several other institutes and centers at NIH, and the National Science Foundation, recently released a request for applications to develop technologies or biomarkers to measure diet and physical activity in free-living, diverse
MILNER, TRUJILLO, KAEFER, and ROSS 291 populations (http://grants.nih.gov/grants/guide/rfa-files/rfa-ca-07-032. html). Although serum and blood cells have frequently been used to evalu- ate exposure to bioactive food components, evaluation of bioactive food components may not always be predictive of the target tissue. Surrogate samples, such as exfoliated cells, may offer a noninvasive opportunity to evaluate exposures and physiological responses in target tissues. A source of exfoliated cells for oral or esophageal tissue can presumably be found in saliva. Because of the possible application of tea in the pre- vention of oral and esophageal cancers, Yang and collaborators (Yang, Lee, and Chen, 1999) measured the salivary levels of tea catechins in six human volunteers after drinking tea. Although exfoliated cells from saliva were not isolated in this study, the results suggest that tea catechins were absorbed through the oral mucosa and that salivaâa source of exfoliated cellsâmay be another biological source material in which to evaluate dietary exposure of certain bioactive food components and their physi- ological effects. Recently serum biomarkers were examined in a randomized con- trolled trial using matrix-assisted laser desorption/ionization-time of flight mass spectrometry proteomic profiling (MALDI-TOF) and statisti- cal analysis (Mitchell, Yasui, Lampe, Gafken, and Lampe, 2005). In this study, 38 participants ate a diet devoid of fruits and vegetables and one supplemented with cruciferous (broccoli) family vegetables. Interestingly, two significant peaks were detected (m/z values of 2,740 and 1,847) that could classify participants based on diet (control vs. cruciferous) with 76 percent accuracy. The 2,740 m/z peak was identified as the B-chain of alpha 2-HS glycoprotein, a serum protein previously found to vary with diet and be involved in insulin resistance and immune function. Thus, the expanded use of proteomic technologies may provide some important clues not only about consumption patterns (exposure), but also about their biological consequences. Dietary components are known to have widespread âeffectsâ on vari- ous cellular processes associated with health and disease prevention, including carcinogen metabolism, hormonal balance, cell signaling, cell cycle control, apoptosis, and angiogenesis (Davis and Milner, 2004; Trujillo et al., 2006). In addition, the combination of foods or nutrients may incur favorable outcomes. Studies in men have found that soy combined with black or green tea has been reported to synergistically reduce serum pros- tate-specific antigen concentrations, which is a marker for prostate cancer (Zhou, Yu, Zhong, and Blackburn, 2003). Moreover, certain combinations of foods or nutrients may diminish the magnitude of the response com- pared to when those foods or nutrients are provided alone. For example, the impact of omega-3 fatty acids on gene expression was not observed
292 BIOSOCIAL SURVEYS when combined with the antioxidant vitamin E in a cell culture system (Aktas and Halperin, 2004). Whether this is true in vivo remains unre- solved, but if this blunting effect of vitamin E also occurs in vivo, it would explain some of the inconsistencies about the health benefits of fish that currently exist in the literature. Effect biomarkers are particularly useful if they can predict a poten- tially detrimental response long before it occurs. However, few biomark- ers are universally accepted as being reliable (Schatzkin and Gail, 2002). The most common biomarkers are body mass index, blood pressure, and cholesterol. However, more sensitive biomarkers are needed to detect subtle change long before disease complications arise. The range of effect biomarkers required is immense because of the need to detect a variety of metabolic events that alter cognitive and physical performance or change the risk of disease. Associating genetic polymorphisms with carcinogen- DNA adduct measurements shows promise for monitoring dietary expo- sure to cancer-causing agents (Kyrtopoulos, 2006; Warren and Shields, 1997). Many other biomarkers are beginning to emerge that might be used effectively to monitor the impact of dietary habits on growth and devel- opment, including platelet-derived growth factor, transforming growth factor, basic fibroblast growth factor, epidermal growth factor, insulin-like growth factor, and hepatocyte growth factor (Giovannucci, 1999; Fletcher et al., 2005). Additional research is needed to unravel the effects of dietary habits on these and other effect biomarkers. An example of an effect biomarker that is influenced by diet comes from studies on the ability of fish oil to suppress tumor necrosis factor (TNF-a) production and mediate the inflammatory response. It is well known that TNF-a mediates inflammation and that high TNF-a produc- tion has adverse effects during disease. However, the effect biomarker is also influenced by the genetics of the consumer, since the response is influenced by polymorphisms in the TNF-a genes. Grimble and col- leagues (Grimble et al., 2002) found that men with high inherent TNF-a production were more sensitive to the anti-inflammatory effects of fish oil compared with men with lower levels of TNF-a production. The biological response to a food component is probably not consis- tent across all tissues. For example, the effect of nutritional zinc-deficiency on the activities of O6-alkylguanine:DNA methyltransferase (AGT) in nine rat tissues, including liver, lung, kidney, spleen, brain, esophagus, forestomach, gastric stomach, and small intestine, was examined by two measures (Fong, Cheung, and Ho, 1988). In both measurements, the activ- ity of AGT was significantly reduced in the esophagus of zinc-deficient rats compared with zinc-sufficient controls, but the other tissues were less affected, suggesting sensitivity of this tissue to zinc deficiency. A human clinical example for this concept comes from a randomized controlled
MILNER, TRUJILLO, KAEFER, and ROSS 293 clinical study on the effect of selenium supplementation for prevention of skin carcinoma (Clark et al., 1996). It was found that selenium treatment did not protect against development of basal or squamous cell carcinomas of the skin, but results from secondary end-point analyses supported the hypothesis that supplemental selenium may reduce the incidence of, and mortality from, carcinomas of several sites, including lung, colon, and prostate. The complexity in understanding the biological consequences of a change in an effect marker is illustrated by studies with the isoflavone genistein, a bioactive compound found in soy and other legumes. Cir- culating concentrations of estradiol are strongly and positively related to bone health and breast cancer risk in women (Thomas, Gallo, and Thomas, 2004). At low exposures, genistein may reduce the influence of naturally occurring estrogen, but at higher concentrations it may promote estrogenic effects (Gikas and Mokbel, 2005; Reinwald and Weaver, 2006). This dose dependency may explain part of the confusion that exists in the literature (Cassidy, 2003). Likewise, variation in how estradiol is formed and metabolized may influence the response to genistein supplements or dietary soy products. A recent study investigated the relationship among dietary isofla- vone exposure, genotype, and plasma estradiol levels in postmenopausal women using three markers of isoflavone exposure: diet, urine, and serum. There was a strong correlation between isoflavone and plasma estradiol in women with a particular polymorphism in a gene involved in estrogen metabolism. For the women with that polymorphism, the data would translate into a 30 percent reduction in breast cancer risk (Low et al., 2005). These observations raise the interesting possibility of a diet-gene interaction in which the effect of isoflavone exposure may be exceptionally pronounced in women with a particular genotype but is attenuated when women of different genotypes are considered. Thus, to gain a greater understanding of the observations, a biological effect measure must consider genomics. A host of susceptibility biomarkers also will be critical for evaluating the merits of changing dietary habits. These biomarkers should allow the measurement of individual differences associated with genetic back- ground or variation associated with many environmental factors (Milner, 2003; Perera, 1994). The ability of genetic differences to activate or detoxify genotoxic agents is becoming increasingly recognized as an appropriate susceptibility biomarker. Many genes, associated products, or receptors are now under investigation as markers of susceptibility, including those associated with OB, UCP, erbB-2, ras, myc, p53, BCL-2, Ki-67, and HNF-1-a (Wiedmann and Caca, 2005). Although several single-gene mutations have been shown to cause problems in experimental animal models, such as
294 BIOSOCIAL SURVEYS those that occur in some animal models of obesity, the situation in humans is likely to be considered more complex. Interactions among several genes, environmental factors, and behavior make the search for appropriate gene markers especially challenging. Nevertheless, new markers are being developed that should offer exciting opportunities for clarification of the effect of genes and the environment. Recently, the drug herceptin received attention for its novel charac- teristics in blocking a specific target and thereby susceptibility associated with the increased risk of certain breast cancers (Flaherty and Brose, 2006). This drug has been showcased as an emerging new strategy for dealing with disease, namely a molecular medicine approach. Interestingly, it has been recognized that various dietary components can modify this same process and influence the risk of disease. Evidence, from a variety of sources, points to olive oil, an integral ingredient of the Mediterranean diet, as a deterrent to cancer. Recent evidence suggests the ability of its monounsaturated fatty acid oleic acid (18:1n-9) to specifically regulate overexpression of HER2 (Her2/neu, erbB-2), a well-characterized onco- gene that may account for at least part of the observed protection in popu- lation studies (Colomer and Menendez, 2006). Interestingly, the efficacy of trastuzumab, a humanized monoclonal antibody binding with high affin- ity to the ectodomain (ECD) of the Her2-coded p185 (HER2) oncoprotein, was found to be enhanced by oleic acid (Colomer et al., 2006). In addition to olive oil, experimental evidence suggests one of the active components in green tea, epigallocatechin-3-gallate, is effective in inhibiting Her-2/ neu expression and leads to a suppression in the downstream events that it typically would bring about (Masuda, Suzui, Lim, and Weinstein, 2003). Evidence also exists that n-3 fatty acids from fish, as well as flavonoids from various grains, can retard Her2/neu expression (Menendez, Lupu, and Colomer, 2005; Way, Kao, and Kin, 2004). The field of nutrigenomics and associated biomarkers is helping to illuminate how nutrients modulate processes within human tissues. How- ever, there are many unique challenges that must be faced when dealing with nutritional and genomic research. People generally do not eat one food at a time, and it is often difficult to ascertain how much is consumed, which dietary component(s) brings about a positive or negative health effect, and if food components are working alone or in combination. Information coming from the Womenâs Health Initiative also emphasizes the need to not only understand quantities of individual food components but also the duration of their intake (Prentice et al., 2006). This was par- ticularly true for the effects of reducing fat intake on breast cancer risk, which did not appear until four to five years after the intervention started. How the genetic background of an individual, as well as that personâs age, gender, and lifestyle affect response to nutrients are additional issues
MILNER, TRUJILLO, KAEFER, and ROSS 295 that need to be more adequately addressed in the future. Although the task of answering these questions seems daunting, progress is being made and may well continue as newer tools and biomarker research unfolds. Overall, a variety of biomarkers that can monitor the intake (expo- sure), molecular target (effect) and variation in response (susceptibility) will be needed to develop a profile for an individual that reflects the effect of diet on overall performance and health. To assess the benefits of foods or their components, additional attention must be paid to examining the variability in response among populations and individuals, the strengths of any association or correlation, the specificity of the relationship, the reversibility of the response, and the biological basis for any proposed benefits. Undeniably, the development and application of validated and sensitive biomarkers have enormous importance not only in improving health but also in assessing the importance of dietary change. While it is difficult to assess the significance of individual types of investigations, it would be wise to develop a model that incorporates various types of data before highlighting the particular benefits or risks of a functional food or bioactive component. While some may argue that a model including epidemiologic evidence (25 percent), intervention studies (35 percent), animal models (25 percent), and mechanism of action (15 percent) might be appropriate, others might shift the proportions markedly. This is in no way a novel approach; it was used in preparing six consensus statements about chronic disease, yet many scientific and lay publications do not use the same criteria when showcasing information about the merits or limitations of nutrition and health studies. Ethics Although many researchers are enthusiastic about the potential to tailor public health products and services for disease prevention and treatment based on an individualâs genetic profile, and many consumers are anxious to gain more personal control over their health by learning about their genetic susceptibility for various health concerns, there are risks and benefits that must be taken into consideration. Potential benefits from genetic testing include relief from anxiety, improved ability to plan for the future, and more informed decisions regarding measures that may or may not play a role in disease prevention or treatment. Potential risks include the cost of testing, psychological and emotional reactions to results, disruption to families, and potential for discrimination (Anderlik and Rothstein, 2001). In the realm of nutrigenomics, it is important for the public to under- stand that the companies currently in existence that tout âpersonalized nutritionâ tend to base their recommendations on a small number of
296 BIOSOCIAL SURVEYS genes for which there is currently inadequate information to predict an individualâs response to specific food components or eating habits (Check, 2003; Kaput et al., 2005). In addition, because of the often complex inter- actions between genes and environmental factors, it is challenging for researchers, clinicians, and counselors to determine an individualâs likeli- hood of developing a disease. In some cases, behavioral changes will not modify a personâs likelihood of developing a given disease. However, in many cases, behavioral changes will modify individual risk, even if it is higher based on their genetics, so it is important that the information is communicated in a manner that does not create deterministic attitudes that might reduce self-efficacy. The fact that some companies exist that provide results directly to individuals without any discussion with a physician or genetics counselor is troubling, since this information may be used incorrectly or inappropriately (Castle, 2003). Regardless of the current concerns related to the accuracy of health claims made by com- panies marketing personalized nutrition and the manner in which these results are delivered to individuals, it is likely that the future of nutri- tion includes the ability to create effective individual guidance based on genetic profiles. A concern regarding the future of nutrigenomics (and genomics in general) is whether the extremely large investments in research infrastruc- ture to support ___omics research will further widen the health disparities gap between the rich and the poor at the individual and population levels (Darnton-Hill, Margetts, and Deckelbaum, 2004; Cannon and Leitzmann, 2005). As described above, the public throughout the world, as well as policy makers, health care providers, and a wide range of researchers need to understand the concept of genomics and how it can have a posi- tive impact on lives in order to make informed decisions about whether or not it will be in their best interest to support the large investments needed for genomics research. When genomics is considered at the population level, the issue of individual health benefit versus the good of the overall community, population, or country comes into question, especially since there are a limited number of health care dollars to treat everyone with medical issues (Anderlik et al., 2001). In order for genomics to improve health in developing countries and wealthier developed countries, tech- nological capacity and training need to be increased regionally to address health concerns and reduce the belief that â90% of research expenditure is dedicated to the health problems of 10% of the worldâs populationâ (Singer and Daar, 2001). The application of nutrigenomics to the field of agriculture has been used already in several developing countries to address some of the regional concerns related to nutritional deficiencies through improve- ments to crop yield and enhancement of the nutritional profile of staple
MILNER, TRUJILLO, KAEFER, and ROSS 297 crops. There has been an ongoing debate for years regarding the safety of genetically modified foods, fueled primarily by issues of trust and public perceptions of risk (Anderlik et al., 2001), and several countries will not allow these products into their food supply. If genomics can be applied as part of the solution to a wide range of health concerns in developing countries, which rank as some of the most populous nations in the world, the return on investment and health benefits need to be carefully consid- ered, along with issues of trust and public understanding of genetics and risk. In order for nutrigenomics to be applied to disease prevention and treatment, the public must be able to trust those who collect DNA for individual analysis as well as for inclusion into larger research databases, and those who will be providing them with health education based on genetic information. For example, in 1999 and 2000, the National Bioeth- ics Advisory Committee commissioned studies on the ethical issues and policy guidance regarding research involving human biological materials. The reports noted that in the United States, certain population groups that have experienced research abuses in the past, such as African Ameri- cans and Jews, had the highest levels of concern related to privacy and trust issues (Anderlik et al., 2001). The 2002 World Health Organization report Genomics and Health reviewed how certain cultural practices may also affect confidentiality (World Health Organization, 2002). There are many people who fear there is insufficient security and protection of their personal health data. Some countries, including Iceland and Estonia, which have national projects containing genetic information, have laws to safeguard genetic information, who may use it, and in what man- ner. However, in the United States there are serious gaps in the areas of privacy protection, the degree of specificity needed in informed consent procedures for research, and in the laws governing privacy of health information and genetic discrimination (Anderlik et al., 2001). Conclusion Advances in nutrition must be consistent with meeting the needs of populations as well as individuals in subpopulations. Since nutrition is not a pure science, it is ideally suited to build on the social, behavioral, and biological domains (Cannon et al., 2005). Nevertheless, each of these domains introduces a variety of perspectives about what is important and what strategies are critical for bringing about a change in health and disease prevention. In order to determine whether personalized nutrition with tailored risk reduction strategies to improve health through eating behaviors will motivate individuals and populations to change, behav- ioral and social scientists need to partner with basic researchers in current
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