**3. Response to the diet therapy**

Although dietary recommendations have been implemented to improve health and diminish the risk of CVD, type 2 diabetes and obesity, these recommendations have been established based on populations and not the individual. On the other hand the approach has been surprisingly unsuccessful in reducing CVD risk and the drastically different inter individual responses to a diet (Ordovas & Corella., 2004).

So this clearly highlights the limitations of population-based nutritional recommendations and suggests that our understanding of the mechanisms responsible for inter-individual differences are far from being understood (Much et al., 2005).

Recent clinical evidence suggests dramatic inter-individual differences and existence of consistent hypo- and hyperresponders in response of plasma lipids to dietary manipulations, ranging from reduced LDL-C levels and TGs in some, to decreased HDL-C levels to elevated TGs. So in some, a low-fat diet has caused a shift to a lipid pattern that is more atherogenic than the original one. This supports the hypothesis that responsiveness is related to genetic variation and existence of nutrient–gene interactions or personۥs genotype (defined by the term 'nutrigenetics') (DeBusk, 2008; Perez-Martinez et al., 2011; Masson et al., 2003; Rideout., 2011; Ordovas et al., 2007).

A classic example of this is the large variation in the concentration of serum low-density lipoprotein-cholesterol (LDL-C) in response to fish oil supplementation. The cardio protective effects of the fatty acids in fish oil, Eicosapentaenoic Acid (EPA) and Docosahexaenoic Acid (DHA) are well recognized. However, a potentially deleterious increase in LDL-C (5–10%) has been consistently reported after moderate to high doses of fish oil (>2 g day−1 EPA + DHA) (Lovegrove & Gitau., 2008).

Despite this small, but significant increase in LDL-C, closer examination of the responses revealed a noticeable inter-individual variation. There was a mean increase in LDL-C of 4. 1%, yet the spread of individual responses was substantial, with 33 of the 74 subjects demonstrating a lower serum LDL-C and the remaining 41 demonstrating a higher LDL-C (range −40 to +113%) following fish oil intervention. This heterogeneous response to a change in dietary fat, may be attributed to a number of factors; including age, gender,

The link between serum cholesterol and the development of atherosclerosis was established a few decades ago and is now widely accepted. The National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) publishes updated guidelines for treating lipid disorders. The latest version is the ATP III (Ordovas & Corella., 2004; Debra., 2008). The current recommendations aim to reduce the classical modifiable risk factors, and much emphasis has been placed on controlling high-plasma cholesterol levels (Ordovas &

Physicians are encouraged to refer patients to Registered Dietitians (RDs) to help patients meet goals for therapy (NCEP) based on LDL cholesterol levels. So the ATP III recommended the therapeutic lifestyle change (TLC) dietary pattern as the cornerstone for primary and secondary prevention of CHD. These guidelines consider dietary modification of treatment with emphasis on reducing the high saturated fat atherogenic diet and increased content of polyunsaturated fatty acid (PUFA) as well as controlling other behavioral factors. These therapies are used primarily to lower elevated blood levels of LDL-C, raise HDL –C and lower triglycerides (TGs) (Rubin & Berglund., 2002; Debra., 2008;

Although dietary recommendations have been implemented to improve health and diminish the risk of CVD, type 2 diabetes and obesity, these recommendations have been established based on populations and not the individual. On the other hand the approach has been surprisingly unsuccessful in reducing CVD risk and the drastically different inter

So this clearly highlights the limitations of population-based nutritional recommendations and suggests that our understanding of the mechanisms responsible for inter-individual

Recent clinical evidence suggests dramatic inter-individual differences and existence of consistent hypo- and hyperresponders in response of plasma lipids to dietary manipulations, ranging from reduced LDL-C levels and TGs in some, to decreased HDL-C levels to elevated TGs. So in some, a low-fat diet has caused a shift to a lipid pattern that is more atherogenic than the original one. This supports the hypothesis that responsiveness is related to genetic variation and existence of nutrient–gene interactions or personۥs genotype (defined by the term 'nutrigenetics') (DeBusk, 2008; Perez-Martinez et al., 2011; Masson et

A classic example of this is the large variation in the concentration of serum low-density lipoprotein-cholesterol (LDL-C) in response to fish oil supplementation. The cardio protective effects of the fatty acids in fish oil, Eicosapentaenoic Acid (EPA) and Docosahexaenoic Acid (DHA) are well recognized. However, a potentially deleterious increase in LDL-C (5–10%) has been consistently reported after moderate to high doses of

Despite this small, but significant increase in LDL-C, closer examination of the responses revealed a noticeable inter-individual variation. There was a mean increase in LDL-C of 4. 1%, yet the spread of individual responses was substantial, with 33 of the 74 subjects demonstrating a lower serum LDL-C and the remaining 41 demonstrating a higher LDL-C (range −40 to +113%) following fish oil intervention. This heterogeneous response to a change in dietary fat, may be attributed to a number of factors; including age, gender,

Corella., 004).

Ordovas & Orella., 2004).

**3. Response to the diet therapy** 

individual responses to a diet (Ordovas & Corella., 2004).

al., 2003; Rideout., 2011; Ordovas et al., 2007).

differences are far from being understood (Much et al., 2005).

fish oil (>2 g day−1 EPA + DHA) (Lovegrove & Gitau., 2008).

baseline LDL-C levels, disease status and drug use. However, recent evidence strongly suggests that variations in a number of key genes may also be important (Lovegrove & Gitau., 2008). For example, individuals with specific of genetic variants in a gene may experience different type of lipoprotein changes when placed on a particular diet, whereas individuals with other variants in the gene may be resistant to the effects of the same diet. Although data is sparse in regard to whether such interactions exist, some limited work suggests that interactions may play an important role in determining lipoprotein profiles and may thus be informative for CVD risk prediction. For example, knowledge of a patient's genetic information may allow medical providers and nutritional counselors to predict what lipoprotein changes are likely to occur if the patient starts a particular dietary intervention and, thus, better advise the patient regarding lifestyle changes (Musunuru., 2010; Ordovas & Corella., 2004).

Lipoproteins are macromolecular complexes of lipids and proteins that originate mainly in the liver and intestine and are involved in transporting and redistributing lipids in the body. Lipid homeostasis is achieved by the coordinated action of numerous nuclear factors, enzymes, apolipoproteins, binding proteins, and receptors. Lipid metabolism is also linked with energy metabolism and is subject to many hormonal controls essential for adjusting to environmental and internal conditions. Genetic variability exists in humans for most of these components, and some of these mutations result in abnormal lipid metabolism and plasma lipoprotein profiles that may contribute to the pathogenesis of atherosclerosis. Many of these genes have been explored in terms of gene-diet interactions (Ordovas & Corella., 2004).

So the shift towards personalized nutritional advice is a very attractive proposition, where, in principle, an individual can be given dietary advice specifically tailored to their genotype. However, the evidence-base for the impact of interactions between nutrients and fixed genetic variants on biomarkers of CVD risk is still very limited (Lovegrove & Gitau., 2008; Ordovas., 2006; Masson et al., 2003; Masson & Mc Neil., 2005; Fisler & Warden., 2005).

With the advent of nutritional genomics, it's becoming clear that an individual's genetic makeup (genotype) is an important factor in this response and that dietary interventions must be matched to genotypes to effect the intended lipid-lowering responses (DeBusk., 2008).

A number of such genes have already been identified and include those involved with postprandial lipoprotein and triglyceride responses, homocysteine metabolism, hypertension, blood-clotting, and inflammation (Ordovas & Corella., 2004; DeBusk., 2008).

Genetic polymorphism in human populations is part of the evolutionary process that results from the interaction between the environment and the human genome. Recent changes in diet have upset this equilibrium, potentially influencing the risk of most common morbidities such as cardiovascular diseases, diabetes, and cancer. Reduction of these conditions is a major public health concern, and such a reduction could be achieved by improving our ability to detect disease predisposition early in life and by providing more personalized behavioral recommendations for successful primary prevention. In terms of cardiovascular diseases, polymorphisms at multiple genes have been associated with differential effects in terms of lipid metabolism. The integration of genetic and environmental complexity into current and future research will drive the field toward the implementation of clinical tools aimed at providing dietary advice optimized for the individual's genome (Ordovas., 2009; Engler., 2009).

Nutrigenetics and Dyslipidemia 45

variants associated with differential responses to nutrients or dietary pattern, functional food or supplement on a specific health outcome, and relating this variation to disease states (Much et al., 2005; Michael., 2008). The particular gene variants a person has to determine the nutritional requirements for that person and the gene-based differences in response to dietary components and developing nutraceuticals that are most compatible with health based on individual genetic makeup (DeBusk., 2009; Subbiah., 2007). Nutrigenetics will assist clinicians in identifying the optimal diet for a given individual, i. e., personalized

Furthermore, the concept is that if an individual is genotyped at various genes for diseaseassociated risk alleles, a genotype-based diet or nutritional supplement regimen may be useful to overcome the genetic variation and reduce risk or prevent the disease altogether

Nutrigenomics, is concerned with how bioactive components within food affect genes. The field of nutritional genomics is still evolving, and it is common to see "nutrigenomics" used as a shorthand version of "nutritional genomics ". However, keeping the concepts separate can be helpful when sorting out the underlying mechanisms involved (DeBusk., 2009). Nutrigenomics will unravel the optimal diet from within a series of nutritional alternatives, whereas nutrigenetics will help clinicians in identifying the optimal diet for a given

Although these two concepts are intimately associated, they take a fundamentally different approach to understanding the relationship between genes and diet. Despite the immediate goals differing, the long-term goal of improving health and preventing disease with

Nutrigenetics is the more familiar of the two subtypes of nutritional genomics (DeBusk., 2009) At one end of the spectrum of nutritional genomics are the highly penetrant monogenic disorders that give rise to inborn errors of metabolism such as phenylketonuria (DeBusk., 2009). More recently less penetrant, more subtle variations have been identified that also affect the gene-encoded protein's function. However, such variations do not in themselves cause disease. Instead, they alter a person's susceptibility for developing a disease. Depending on the specific gene variant, the person's likelihood of developing a disorder may be increased or reduced. These genes are the primary focus of nutritional genomics, because they are common within the global population, they affect dietary recommendations about the types and amounts of food that best fit a person, and practical interventions are possible. These interventions can potentially improve the health potential of individual people and, by extrapolation, the populations in which they

Current nutrition recommendations, directed towards populations, are based on estimated average nutrient requirements for a target population and intend to meet the needs of most individuals within that population. They also aim at preventing common diseases such as obesity, diabetes and cardiovascular disease. So diet has been reported as a major contributor to alarming prevalence of obesity (Shalileh et al, 2010). For infants with specific genetic polymorphisms, e. g. some inborn errors of metabolism such as phenylketonuria, adherence to current recommendations will cause disease symptoms and they need personalized nutrition recommendations (Hernell & West., 2008; Farhud & Shalileh., 2008).

nutrition (Much et al., 2005; Svacina., 2007; Zak & Slaby., 2007; Gillies., 2003).

(Wood., 2008; Xacur-GarcAa et al., 2008; Kussmann & Fay., 2008).

individual, i. e., personalized nutrition (Much et al., 2005)**.** 

nutrition requires the amalgamation of both disciplines (Much et al., 2005)

**4.2 Nutrigenomics** 

live (DeBusk., 2009).

The recognition that nutrients have the ability to interact and modulate molecular mechanisms underlying an organism's physiological functions has prompted a revolution in the field of nutrition (Much et al., 2005).

For the field of nutrition, this would encompass the ongoing efforts to understand the relationships between the genome and diet, currently termed nutrigenomics and nutrigenetics (Much et al., 2005; Ommen., 2004)
