Advanced Nutrition Nutrigenomics/ Nutrigenetics - Essay Example

Norena Laguerre Advanced Nutrition Nutrigenomics/ Nutrigenetics The Centers for Disease Control and Prevention defines Diabetes (CDC) as a “disease in which blood glucose levels are above normal. Most of the food we eat is turned into glucose, or sugar, for our bodies to use for energy. The pancreas, an organ that lies near the stomach, makes a hormone called insulin to help glucose get into the cells of our bodies. When you have diabetes, your body either doesnt make enough insulin or cant use its own insulin as well as it should. This causes sugar to build up in your blood. Diabetes can cause serious health complications including heart disease, blindness, kidney failure, and lower-extremity amputations”. The prevalence of the disease has a total of 18.2 million people, 6.3% of the population have diabetes. The number of people diagnosed is 13.0 million people, and the undiagnosed is 5.2 million people. Diabetes is the sixth leading cause of death in the United States. Recent progress in the areas of molecular and recombinant DNA technology has led to sophisticated research in genetics. DNA sequencing has made us acknowledge the uniqueness of individuals that come with genetic variation. Nutrigenomics encompasses a wide array of technologies that deal with how genetic programs present in cells and tissues may possibly be affected by diet. The following are three possible definitions of nutrigenomics: 1) “ … the application of high throughput genomics tools in nutrition research”; 2) “… seeks to examine ‘dietary signatures’ in cells, tissues and organisms and to understand how nutrition influences homeostasis”; and 3) “… the interface between the nutritional environment and cellular/ genetic processes”. All of these definitions have commonalities with other “omics” disciplines, specifically pharmacogenomics and pharmacogenetics. However stark differences are noted; for instance, nutrigenomics presents complications that the other two areas do not, particularly the length and the complexity of exposures. Research along this area has progressed in the past two decades, with physicians, geneticists, and nutritionists showing interest to the influences of genetic variation and gene-nutrient interactions in the management of diseases including coronary heart disease, hypertension, cancer, diabetes and obesity. Moreover, these have also investigated the roles of nutrients in gene expression. These have successfully paved the way for the discipline of nutrigenetics and nutrigenomics. The current paper seeks to investigate the influence of this new and promising discipline to the management of diabetes. These researches seek to demonstrate the benefits of this new science to the treatment of this debilitating disease. Wareham (in Burton & Stewart, 2004) asserts that most researches have held that diabetes and obesity are conditions that diet gene interaction does not influence. He depicted these as commendable areas for study, and reinforced that even in such common conditions, there will still be considerable research issues and challenges (Wareham in Burton & Stewart, 2004). He then suggested that the investigation of the relationship between genetic variation and diet in the management of diabetes be carefully tackled to avoid public confusion in the awareness campaigns about the disease. A substantial body of research evidence garnered from migration studies, cross section studies and temporal variation indicate that diabetes may be essentially an interaction between genes and the environment (Wareham in Burton & Stewart, 2004). These studies are relevant in so far as understanding the mechanisms of disease instead of modifying any existing public health advice (Burton & Stewart, 2004). In part, these studies have also suggested that diabetes can essentially be prevented by managing one’s diet and by encouraging exercise or physical activity. Issues about modern lifestyles being predisposing factors to the disease need to be discussed at his level instead of the individual level where it may just be futile, since some of them may have formed the perception that genetic differences ‘spare’ them from acquiring the disease. These make them complacent and free to exercise the lifestyles that they choose. Taking all these into account, these bring forth the question on how to get from the evidence that there really exists some interaction and its extent of certainty. Wareham (in Burton & Stewart, 2004) has suggested the nature of the evidence that is necessary to support this epidemiology, as follows: “1) a functional variant leading to a clinical outcome, and 2) an environmental or dietary factor predicting a clinical outcome. For either of these criteria, evidence of relationship to an intermediate quantitative trait would offer stronger support. Moreover, diabetes and obesity are conditions where diet gene interaction is considered as most probable. Wareham (in Burton & Stewart, 2004) have depicted these as effective models for investigation but have emphasized that even in these usual conditions, there are still grave obstacles that need to be hurdled. Moreover, he asserts that the position that the study of gene-diet interaction in diabetes should not be permitted to confuse present public health prevention messages. There has been proof from migration studies, cross sectional researchers of geographical variation and temporal variation all suggesting that the basis of diabetes is primarily a combination or an interaction between genes and the environment. This is of crucial importance in shedding light to the mechanisms of disease rather than in modifying any present public health advice. There is already relevant proof that diabetes can be essentially prevented by modifications in diet and increasing physical activity. Current lifestyles increasing the predisposition to diabetes are a societal problem and need to be discussed at this level rather than at the level of the individual and may be counter-productive if some individuals formed the perception that genetic differences might make them less prone to diabetes and thus not at risk from whatever lifestyles they chose. The concept of gene-nutrient interaction presents a truly interesting scientific question. Taken at the level of epidemiology, it raises the question: how do we get from evidence that there may be an interaction to a greater degree of certainty? The nature of epidemiological evidence is one of slow accumulation and will be hard to attain. The sort of evidence that is required is: 1) a functional variant leading to a clinical outcome; and an environmental or dietary factor predicting a clinical outcome. For either of these, proof of an association to an intermediate quantitative trait would lend more support. Study design problems indicate that the evidence for dietary factors relating to clinical results is inadequate. Wareham (in Burton &Stewart, 2004), for instance, assert that the relationship between diet and type II diabetes cannot be fully demonstrated because of study design issues. He says that the ideal study design is a nested control study – a case control study nested within a prospective study – because it makes possible avoiding recall bias. Moreover, studies need to employ significantly large sample sizes to achieve validity and precision. Currently, there are only several of these studies that may be gleaned from nutrigenomics literature. For instance, the Cambridge group (in Burton & Stewart, 2004) has investigated the relationship between polyunsaturated and saturated fats in the diet and incident diabetes. This study went on to add genetic factors that complicated it further. However, there have been developments in developing single-gene factors that cause obesity. For instance, mutations in the MC4 receptor gene are correlated with severe obesity in some families (Cambridge Group in Burton & Stewart, 2004). And yet, these mutations are uncommon and insignificant correlations with the more common polygenic forms of obesity have been shown. Research has progressed more along the underlying genetic factors of diabetes, with strong proof stemming from linkages studies and association studies (Muller & Kersten in Burton & Stewart, 2004). There are certain monogenic cases of diabetes, majority of which are maturity onset diabetes of the young (MODY), and genes related with such a condition have been successfully determined (Muller & Kersten in Burton & Stewart, 2004). Full genome scans have been carried out to demonstrate several regions that have a high probability of harboring genes that contribute to polygenic forms of diabetes. A handful of genes have been studied, including the PPARgamma and calpain genes. Although this area of research is promising, the evidence remains weak at this stage (Wareham in Burton & Stewart, 2003). Each of the genetic variations pointed out in Type II diabetes may seem neither required note adequate to exclusively cause the disease. Other options need to be examined, that is, other genetic mutations or environmental influences. For instance, the PPARgamma gene could be a key candidate for involvement in a gene-environment interaction. PPARgamma is a nuclear receptor that is dealt with in lipidogenesis and lipid metabolism. Some rare mutations in the gene encoding PPARgamma cause insulin resistance, and there are more usual or conventional polymorphisms that affect\insulin sensitivity. Empirical evidence is gradually being yielded from a clearer understanding of molecular mechanisms that PPARgamma might be relevant for gene-diet interaction. For example, the natural ligand of the receptor is a fatty acid, and the extent of affinity of the fatty acid for the receptor varies according to the length of the fatty acid and the degree of saturation. However, the epidemiological evidence for a correlation of this gene with diabetes is mixed. A meta- analysis accomplished by Altshuler (2000) illustrated that the common PPARgamma Pro12Ala polymorphism is related with a small degree of protection against the disease (OR=0.8). For detection of gene effects that interact with a dietary factor to cause a disease result, substantially large and longitudinal studies are necessary: probably more than half million people monitored for fifteen years or even beyond (Altshuler, 2000). The Altusher et al (2000) study further asserts that in the long run, proof for a gene-diet interaction will be gradually formed and developed from numerous and varied studies. In particular, quantitative trait studies can make notable contributions. For instance, there is evidence pointing out the fact that people with different genotypes for PPARgamma have different fasting insulin levels in response to dietary fat; however, it may be a bit difficult to move from such a quantitative approach to the distinct clinical results that appeal to both patients and clinicians. Moreover, evidence from observational researches such as those of Biobank and EPIC will not be sufficient to identify gene-environment interactions. It is imperative that these be supported by aetiological trials with corresponding analysis of differential responses to a changing environmental factors. These studies may offer more convincing causal inference than observational data. Certain studies of this nature have been conducted but on the whole have been too short-term in approach and have tended to study a general lifestyle intervention, whereas quite specific interventions will be necessary. Novel trials may require enrolling people on the basis of genotype; a critical factor in attaining the numbers necessary will be the allele frequencies for the genotypes of interest. The choice of participants based on the genotype may also raise ethical issues. Overall, more solid evidence supporting the indicated gene-diet interaction will require the following: a) an association of a functional variant and an environmental factor with outcome; b) an a priori biological hypothesis that supports the search for an interaction; c) functional studies in animals; d) evidence from linkage studies; e) aetiological trials; f) study replication; g) studies of adequate power Nick Wareham (in Burton & Stewart, 2004) concludes by considering whether studies of gene-environment interaction are timely and relevant for the moment. There are a few examples that may initially be encouraging. For example, there is evidence that the genotype at the GPR10 gene is at least partly accountable for distinctions in response to attempts to lower blood pressure by increasing physical exercise. Experimenting on the GPR10 genotype might aid the choice between drug intervention and lifestyle advice. Data from family history may also be utilized more proactively than at present. For instance, the combination of obesity and a family history of diabetes is known to be strongly predictive of diabetes; those with such a family history would benefit much from controlling their weight. This example raises important questions regarding behavior, motivation and risk perception. How does knowledge of a fixed risk associated to family history or genes influence people’s response to being advised to modify their behavior to lessen their risk of the disease? It is not known whether, and for whom, such information would serve as a motivator or for whom it would be considered counterproductive. In future studies, the value of nutrigenetics/nutrigenomics in the management of diabetes needs to be further leveraged on by addressing these issues on study design. Primarily, longitudinal, prospective studies must be carried out to increase the study’s odds ratios; to improve measurement errors for diet than what is generally estimated; and to be able to test a variety of genes and attain lower p values for statistical significance (Altshuler, 2000). References Altshuler, D., Hirschorn, J., Klannemark, M., Lindgren, C., Vohle, M., Nemesh, J., Lane, C., Schaffner, S., Bolk, S., Brewer, C., Tuomi, T., Gaudet, D., Hudson, T., Daly, M., Groop, L., & Lander, E. (2000). The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Natural Genetics. Sep, 26(1), 76-80. Retried from http://www.nature.com/cgi-taf/DynaPage.taf?file=/ng/journal/v26/n1/full/ng0900_76.html&filetype=pdf Burton, H. & Stewart, A. (2004). ‘Report of a workshop hosted by The Nuffield Trust and organized by the Public Health Genetics Unit.’ Retrieved from the http://66.102.7.104/search?q=cache:6daegmQgcaAJ:www.cgkp.org.uk/resources/pdf/nutrigenomics_report_2005.pdf+nutrigenetics+nutrigenomics+&hl=en Kaput J. & Rodriguez RL. (2004). Nutritional genomics: the next frontier in the postgenomic era. Physiology Genomics. Jan 15;16 (2), 166-77. Retrieved on October 2005 from http://physiolgenomics.physiology.org/cgi/reprint/16/2/166 Stewart, A. (2004). ‘You are what you eat.’ The promise of nutrigenetics and nutrigenomics. Retrieved from the Cambridge Knowledge Park http://www.cambridgenetwork.co.uk/POOLED/ARTICLES/BF_NEWSART/VIEW.ASP?Q=BF_NEWSART_92947 Read More