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All evidence so far appears to support a shared genetic and environmental (with diet and exercise being among the most important) contribution to disease predisposition, including obesity, metabolic syndrome, and type 2 diabetes. Nevertheless, the relative contribution of each of these two main parameters and the extent of their interaction are difficult to determine, and varies for each condition.
It is noteworthy, that although the human genome has not changed significantly over the last few decades, the prevalence of obesity, metabolic syndrome, and type 2 diabetes are increasing exponentially. Although the genetic and environmental factors have long been studied independently, an increasing effort is now placed on deciphering the gene–environment interaction. Obesity, metabolic syndrome, and type 2 diabetes are classic examples of such gene– environment interactions. For example, in a cohort of 287 monozygotic and 189 dizygotic young adult male twin pairs, it was shown that sedentary twins were more likely to develop high waist circumference if they were genetically susceptible to obesity than if they were not. The complexity, however, of these multi-factorial diseases has emphasized the call for development of more sophisticated statistical methods that would facilitate more accurate assessment of the interaction between complex combinations of multiple gene variants and environmental factors. A large set of common genetic variants are currently under study in the European programs Nutrient–Gene Interactions in Human Obesity (NUGENOB) ( http://www.nugenob.com) and Diet, Obesity and Genes (DIOGENES) ( http://www.diogenes-eu.org ). Such programs comprising both academic and industrial partners, aim to study gene–environment interactions and thus recognize genetic determinants liable to environmental stimuli that are capable of influencing obesity development. Within these programs, the use of comprehensive platforms coupled with clinical data will have a predominant role in elucidating the perturbed functions leading to obesity, and ultimately in developing better targeted therapies.
One of the rapidly expanding scientific fields that address the way genes and bioactive food components interact is nutrigenomics. It specifically focuses on understanding how diet affects the genome, directly (e.g. via methylation) or indirectly (e.g. at the gene expression level); (2) may compensate for or accentuate the effect of genetic polymorphisms; and (3) can alter the risk for disease progress by interfering with the molecular processes involved in disease onset, incidence, progression, and/or severity. The goal is the in-depth understanding of the genome–nutrient interaction, which will lead to carefully targeted dietary intervention strategies for restoring health and fitness and for preventing dietrelated disease. Many studies are beginning to address the interplay between genome and nutrition, such as in the case of type 2 diabetes. A characteristic example of the importance of nutrigenomic studies lies in the discovery of a polymorphism in the angiotensinogen gene, which alters the effect of dietary fiber on blood pressure. Specifically, individuals with the angiotensinogen TT genotype have decreased blood pressure, when provided with high insoluble fiber diets. In contrast, individuals with the TM or MM genotype do not experience a significant effect on their blood pressure in response to dietary fiber. Similarly, in individuals with a specific polymorphism in PPARgamma (Pro12Ala), a low polyunsaturatedto-saturated fat ratio is associated with an increase in body mass index and fasting insulin concentrations, signifying that when the dietary polyunsaturated-to-saturated fat ratio is low, the body mass index in Ala carriers is greater than that in Pro homozygotes (270) . When the dietary ratio is high, the opposite is seen. Analysis of 1,120 white subjects in the context of the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study demonstrated that common genetic variants at the IL1 b locus were associated with risk of metabolic syndrome and related phenotypes. Importantly, a significant interaction was identified between dietary polyunsaturated fatty acids, and specifically docosahexaenoic acids and eicosapentaenoic acids, intake and the IL1 b 6054G>A polymorphism, with AA subjects having significantly lower risk of metabolic syndrome. This suggests that the increasing genetic predisposition towards the development of metabolic syndrome in these individuals could be reduced by a diet rich in polyunsaturated fatty acids, supporting the notion that more tailored dietary recommendations could be successfully used to prevent chronic diseases. Furthermore, the Framingham Heart Study, involving 2,148 participants, identified an APOA5 polymorphism that was associated with polyunsaturated fatty acid intake in a dose-dependent manner thus determining fasting triglyceride levels.
Current technological advances are enabling an unprecedented width and speed of scientific discovery, thus increasing rapidly our understanding of the genetic etiology of obesity, metabolic syndrome, and diabetes. Although the number of disease-associated genes has recently risen sharply, many more yet-to-be-discovered genes are believed to be implicated in the above-mentioned complex diseases. Better designed, large-scale, multipopulation meta-analyses are starting to provide the necessary statistical power and biological breadth to uncover new genetic players in disease development. In parallel to causative gene mutations and single nucleotide polymorphisms (SNPs – the most common form of polymorphisms associated with obesity, metabolic syndrome, and diabetes), new forms of genome variation such as DNA copy number variants or novel mechanisms of genome/transcriptome regulation, such as microRNAs, are introducing an further level of complexity that needs to be considered. Advanced technological tools, together with cumulative biological knowledge, will allow us to answer the many open questions in disease pathophysiology such as, for example, the effect of type 1 diabetes genetic variants in immune response and tolerance or their role on insulin action and β -cell function in type 2 diabetes. In the meantime, the long-suspected gene–environment interplay will be molecularly deciphered through quickly evolving disciplines such as nutrigenomics. All this wealth of knowledge should translate in presymptomatic genetic diagnosis and effective preventive approaches, as well as improved clinical management when disease development is inevitable.
The human genome encodes >30,000 genes and is responsible for >100,000 functionally distinct proteins, which can initiate a host of cellular metabolic events. Understanding nutrigenomics and how foods and their components interact with the genome at many levels is undeniably essential to the identification of those individuals who will benefit most or be placed at risk by nutrition intervention strategies. The identification of individual differences in response to the same food components is the province of the field of nutrigenetics. Evidence is beginning to surface that genetic patterns can influence the response to foods and their components. Likewise, a number of bioactive food components can influence epigenomic, transcriptomic, proteomic, and metabolomic homeostasis. As with any new approach, these technologies should be viewed with cautious optimism. It is prudent for nutritionists and other health care professionals to recognize the merits and limitations of genomic technologies and to only allow this type of information to be utilized within a bioethical framework. Nutrigenomics is best described as the scientific study of the dynamic, yet regulated, manner in which bioactive food components interact with specific genes at multiple levels and vice versa. It is logical that as new information emerges within nutrigenomics, it will provide more specific information about the health consequences of changing eating behaviors at the level of the individual. The overall concept of nutrigenomics builds on the assumptions that dietary patterns or specific dietary components can influence cancer risk by modifying multiple cellular processes involved with the onset, incidence, progression, or severity of these diseases, bioactive food components can influence the human genome directly or indirectly and thereby influence the expression of genes and gene products, and the health consequences of a diet are dependent on the balance of health and disease states and on nutrigenetics (i.e., an individual’s genetic background) (Davis and Milner, 2004; Kaput and Rodriguez, 2004; Trujillo et al., 2005). The study of nutrigenomics and its associated changes in proteomics and metabolomics events should provide critical clues about molecular targets for bioactive food components and ultimately provide decisive information that can be used for a personalized or preemptive approach to nutrition that is based on predictive data about the likelihood that an individual will respond to a specific intervention. A host of dietary components likely influence genetic and epigenetic events and thereby influence cancer risk and tumor behavior. Both essential and nonessential nutrients have been found to modify multiple processes associated with cancer. This protection may arise from one or more changes in several cellular mechanisms, including those associated with carcinogen metabolism, hormonal homeostasis, cell signaling regulation, cell cycle controls, cell death, or apoptosis, and angiogenesis (Davis and Milner, 2004). More frequently than not, these bioactive food components modify several processes, and the determination of which is most important is an area of active scientific investigation. The quantity and duration of exposure to these bioactive components are generally the most important factors determining the degree and possibly the direction in which processes are modified. At least some evidence suggests detrimental consequences of consuming too little or too much of some essential nutrients on overall health (Combs, 2005; Miller et al., 2005). Whether this is true or not for nonessential nutrients remains an area of intense investigation. Thus, the intended use or the desired biological response must be considered when evaluating the health consequences associated with a change in the intake of a food or its active component(s). It is plausible that a change in a combination of processes determines the ultimate phenotypic response. Understanding which processes are altered and their interrelationships to the final outcome is fundamental to understanding the dynamic relationship between diet and cancer (Trujillo et al., 2005). Although advances have been made in understanding this interrelationship, the identification of those who will or will not benefit from dietary change remains an area of considerable controversy for the scientific community, as well as a source of bewilderment and frustration for the general public. The genetic revolution and the associated “omics” should provide valuable insights for explaining the inconsistencies in the nutrition and cancer literature. The study of gene–nutrient interactions is an expanding area of science and one that is becoming increasingly present in the scientific and public press. Discrepancies in the literature may arise from failing to recognize interindividual genetic differences in the response to foods or their components. One of the best examples reflecting how a false conclusion may arise comes from studies with colon cancer animal models. In studies by Yang et al. (2001), a decreased survival of mice was observed when mice were fed a Western-style diet (high in fat and phosphate and low in calcium and vitamin D) compared with an ideal semi-purified diet. However, the response was dependent on the frequency of mutated alleles in the p21 tumor suppressor gene. When this allelic variance was not considered, differences between diets were virtually impossible to detect. Wide variation in the response to a food component may occur not only because of genetic determinations of absorption and metabolism but also because of fluctuations in the molecular site of action. The angiotensinogen gene, which sets the tone for amount of angiotensinogen protein and thus vascular tone and sodium retention, appears to be influenced by several dietary components. A common polymorphism in the angiotensinogen gene encodes threonine (T) instead of methionine (M) at codon 235. Individuals with the angiotensinogen TT genotype appear to have a decrease in blood pressure (BP) when provided a diet with increased amounts (2.7–3.0 g/100 kcal of either insoluble or soluble fiber) of insoluble fiber compared with when increased amounts of soluble fiber are provided. In contrast, BP in individuals with a TM or MM genotype is not influenced by the type of fiber consumed (Hegele et al., 1997). These insights clarify why variations in BP responses to fiber supplementation have been observed in the literature. An association was also reported between angiotensinogen polymorphism (G6A) such that net systolic and diastolic BP response to the Dietary Approaches to Stop Hypertension (DASH) diet was greatest in individuals with the AA genotype (−6.93/−3.68mmHg) and least in those with the GG genotype (−2.80/0.20mmHg) (Svetkey et al., 2001).
Again, some of the reported discrepancies in the response of BP to dietary modification may reflect the populations examined and their genetic variations. Considerable evidence also points to the ability of dietary selenium to reduce the incidence of chemically induced cancer when provided at above required amounts within physiologically relevant ranges (Kim and Milner, 2001; Combs, 2005). A reduction in the incidence of liver, colon, prostate, and lung cancer has been reported with increasing dietary selenium exposure in humans (Clark et al., 1996). Nevertheless, it is clear from these studies that not all individuals responded equally to exaggerated intake, possibly reflecting genetic differences in the absorption, metabolism, or site of action for this trace element. Polymorphisms in glutathione peroxidase (GPx), a known selenium-dependent enzyme, at codon 198, which causes a substitution of leucine for proline, is associated with an increased risk of lung cancer (Hu and Diamond, 2003). Likewise, in a study nested within the α-Tocopherol, β-Carotene Cancer Prevention Study cohort, individuals with one copy of the allele for leucine (proline/leucine) were at 80% greater risk for lung cancer, and individuals with two copies of the allele for leucine (leucine/leucine) were at 130% greater risk compared with those with the proline genotype (proline/proline) (Ratnasinghe et al., 2000). Similar findings were reported for breast, head and neck, bladder, and skin cancer (Hu et al., 2004; Ichimura et al., 2004). It is conceivable that these relationships reflect cellular differences in the utilization or metabolism of selenium because the activity of GPx was not reported to differ. Support for this belief comes from differences in the ability of selenium to induce GPx activity in breast cancer cells transfected with the leucine or proline coding allele (Hu et al., 2004). Such data provide evidence that it is possible to use information about specific polymorphisms to gain insights into which individuals may need/require increased or decreased amounts of specific nutrients, as has been suggested by Ames et al. (2003). The utility of such information for health benefits comes from the ability of high doses of B vitamins to remedy or ameliorate 50 genetic neurological diseases in humans in which the binding affinity of coenzymes for critically important enzymatic binding sites is reduced, so a higher dose of B vitamin overcomes the effects of the reduced binding affinity normalizing enzymatic activity (Ames et al., 2002). Shifts in diet may also be needed to help counteract or offset conditions caused by various environmental factors. A study investigating the effect of caffeine on bone loss in elderly women found a positive association with a vitamin D receptor (VDR) (tt genotype) when intakes were > 300 mg/day, compared with those with the TT genotype (Rapuri et al., 2001). Because regular caffeine ingestion is such a common habit in our society, strategies other than recommending abstention from caffeine may be needed. Although it remains to be determined whether increasing the amount of calcium or vitamin D will influence the bone loss occurring in these individuals, this area deserves further consideration because evidence exists that the Fok1 polymorphism of the VDR can influence bone mineral accretion during pubertal growth through an effect on calcium absorption (Abrams et al., 2005). Many of the effects of vitamin D are likely mediated through changes in the VDR. Several polymorphisms, including Fok1, Bsm I, and poly-A, may influence the response to various dietary components and influence risk. The Fok1 VDR polymorphism, with the FF genotype, may be particularly important in determining the effect of dietary calcium on colon cancer risk. Although dietary calcium or fat did not influence colon cancer risk in individuals with an FF genotype, a decreased dietary calcium intake was accompanied by increased colon cancer risk with the f allele. Individuals with the ff genotype exhibited about a 2.5-fold increased colon cancer risk when low calcium was consumed compared with adequate intakes (Wong et al., 2003). Furthermore, high levels of dietary calcium and vitamin D reduced the risk of rectal cancer and provided support for a weak protective effect for the SS (poly-A) and BB (Bsm I) VDR genotypes (Slattery et al., 2004). Overall, the risk associated with VDR genotypes likely depends not only on the level of dietary calcium and vitamin D consumed but also on the tumor site (Slattery et al., 2004). Increased intake of some dietary components may lead to depressed health. Unquestionably, high energy intake resulting in obesity is a major public health concern and is associated with several chronic diseases including cancer (Calle et al., 2003). Imbalances in the homeostatic controls between genes and diet may explain the increased morbidity and mortality linked with obesity. It has been estimated that ~90,000 deaths/year from cancer might be avoided if the adult population could maintain a body mass index (BMI) of <25 throughout life (Calle et al., 2003). However, unraveling the relationships among factors influencing obesity, such as amount and type of fat consumed and genetic interactions, will likely be an extremely daunting task. For example, the nuclear receptor peroxisome proliferator-activated receptor-γ (PPARγ) is known to be involved in regulating insulin resistance and BP. In individuals with a Pro12Ala PPARγ polymorphism, the intake of a low polyunsaturated-tosaturated fat ratio is associated with an increased BMI and fasting insulin concentrations in those with multiple copies of the alanine allele. However, in the Pro carriers, increasing the dietary ratio of polyunsaturated (P) to saturated (S) fats to high amounts creates the opposite response (Luan et al., 2001). These data suggest that the dietary P : S ratio should not be set universally across all individuals and that some will likely benefit from a lower ratio, while others will benefit from a higher ratio. The interaction between type of dietary fat and PPARγ genotype illustrates the complexity found in examining gene–nutrient interactions and that blanket recommendations for intakes are likely to lead to unwanted results in subpopulations.
As more information surfaces about diet–gene interaction, we should be in a better position to explain the large heterogeneity in findings that has plagued clinical nutrition. Epigenetic events represent another controlling site for bioactive food components because they are critical for establishing which genes are and are not expressed. Results from numerous investigations provide evidence that tissue-specific differences in vertebrate DNA methylation help maintain patterns of gene expression or are involved in fine-tuning or establishing expression patterns. Various regulatory proteins including DNA methyltransferases, methylcytosine guanine dinucleotide binding proteins, histone-modifying enzymes, chromatin remodeling factors, and their multimolecular complexes are involved in the overall epigenetic process (Ross, 2003; Davis and Milner, 2004; Gallou-Kabani and Junien, 2005). Therefore, vertebrate DNA methylation is responsible for more than simply silencing transposable elements and foreign DNA sequences, as has been suggested. DNA hypomethylation is a nearly universal finding in cancer. These patterns are accompanied by site-specific hypermethylation sites. Hypermethylation of CpG-rich promoters of tumor suppressor genes in cancer has a critical role in downregulating expression of genes and, thus, participates in the cancer process. Nevertheless, evidence exists that creating DNA demethylation increases the formation of certain types of cancers in animal models, and paradoxically, DNA hypermethylation can cause carcinogenesis in other models. Therefore, factors that modify methylation patterns must be used with caution about their overall health consequences. Regardless, chronic administration of methionine- and choline-deficient diets results in global hypomethylation of hepatic DNA and leads to spontaneous liver tumor formation in rats (Poirier, 1986). Actually, several dietary factors may influence the supply of methyl groups and thereby influence the availability of Sadenosylmethionine (SAM) and therefore influence DNA methylation patterns (Ross, 2003). Evidence also exists that dietary factors may modify the utilization of methyl groups by processes including shifts in DNA methyltransferase (Dnmt) activity. A third plausible mechanism may relate to shifts in DNA demethylation activity caused by food components, although this process is not well understood.
Finally, DNA methylation patterns may influence the response to bioactive food components and thereby account for differences in response in normal and neoplastic cells. A series of studies have identified food components ranging from B vitamins to zinc as modifiers of that DNA methylation. The physiological relevance of epigenomic events in changing the neonate comes from studies with an Agouti mouse model. Providing supplemental choline, betaine, folic acid, vitamin B12, methionine, and zinc to the maternal diet was found to increase DNA methylation in the Agouti heterozygote mouse and to increase the proportion of offspring with brown compared with the yellow hair color characteristic of Agouti protein expression. This phenotypic change has been found to coincide with a lower susceptibility to obesity, diabetes, and cancer (Cooney, 1993; Cooney et al., 2002). Although the agouti gene does not exist in humans, these types of studies suggest that in principal maternal exposure to some dietary factors may influence lifelong health of the offspring, as has been suggested by others (Brakefield et al., 2005; Hunter, 2005). Global loss of monoacetylation and trimethylation of histone H4 is also a common occurrence in human tumors (Fraga et al., 2005). Histones are the proteins that form a scaffold around which a cell’s DNA is wrapped. Histone deacetylases (HDACs) are a family of 11 enzymes that remove an acetyl group from histones, which allows histones to bind DNA and inhibit gene transcription. Several studies suggest that butyrate, sulforaphane, resveratrol, and diallyl disulfide are dietary modifiers of HDAC (Druesne et al., 2004; Klampfer et al., 2004; Myzak et al., 2004; Galfi et al., 2005). Although much more research is needed to determine how these food components modify histones and ultimately gene expression, the emerging data are very tantalizing. It is certainly conceivable that prolonged exposure to one or more of these may influence the onset and severity of a number of disease conditions, including cancer.
To conclude, the listed studies and mentioned mechanisms further strengthen the notion that nutrition might be much more important for our health that we were initially aware of. Therefore, diet is pivotal is maintaining long-term health in more than one way.
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