Perspectives in Nutrigenomics for human health Poonam C. Mittal, Biochemistry Department, Department, University of Allahabad, Allahabad, India.
“Nutrition has often been the subject of conjectures and ingenious hypotheses—but our actual knowledge is so insufficient that their only use is to try to satisfy our imagination. If we could arrive at some more exact facts they could well have applications in medicine.” Lavoisier (1743-1794).
Abstract:
The main concern of the science of human nutrition has been development of a dietary regime that promotes optimum health for most of the population. However, as data linking diet and disease accumulated, the response to dietary factors was found to be individualistic. The same dietary factors were found to produce disease in a person who had a genetic predisposition to that particular disease, but not in those, who seemingly had a more efficient metabolic machinery to handle the nutrient in question. This led to the discovery that nutrients can influence metabolic pathways through nutrient-gene interactions, and thereby influence homeostasis. As information from the human genome became available, rapid developments took place in this newly emerging science of Nutrigenomics. The study of nutrigenomics focuses on understanding the relationship between nutrition, genetics and health. This requires application of genomics, transcriptomics and metabolomics, which respectively help in understanding how dietary signals influence gene expression, protein expression and metabolite production. The final outcome is a pattern of these effects, which have been called the dietary signature of the metabolic process. This review will discuss the significance of studying these dietary signatures at the level of the cell, the tissue and the organism as a whole. The use of genomic tools in nutrition research, which can conduct millions of genetic screening tests, will be explained and the modes by which nutrients affect the genome, proteome and metabolome will be discussed.
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Nutrigenomics has attracted media attention as the technology to prescribe tailored dietary regimens specific to an individual’s genetic requirements. This is a distinct possibility, as rapid strides have been made is the application of nutrigenomics for disease management. A brief overview of these issues and what they mean for human h uman health will be provided in the present review.
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INTRODUCTION: The role of nutrition in human health: historical perspective
The earliest records linking the importance of specific substances in food to life can be traced to scholars such as Hippocrates and Charaka, who lived more than 2400 yrs back, even though, at that time, there was no knowledge of the chemical nature of foods. The beginnings of modern concepts of food chemistry can be traced to the mid-1700s, less than three centuries back, when Lavoisier discovered that oxidation of carbon is the source of food energy. Chemical methods of analysis developed rapidly during the ‘chemical revolution’ in France at the end of the eighteenth century and became the impetus for developments in food analysis and investigations linking con sequences of consuming various foods for human health and nutrition. Magendie and Liebig led research through the 19th century to characterize macronutrients such as carbohydrates, fat and protein. This was followed by b y characterization of more complex molecules such as the vitamins, which are present in foods in smaller amounts, and required more sophisticated techniques for determination. Developments in nutritional sciences were also guided by observations linking poor diets to diseases such as scurvy, beriberi, kwashiorkor, marasmus, anemia, n ight blindness etc. Since war, famine and drought were common, the study of the science of Human Nutrition concerned itself with the development of a dietary regime that promoted optimum health for the entire popu lation. The first recommended dietary allowances (RDA) were developed during World War II by the United States National Academy of Sciences (US-NAS) to provide populations with the knowh ow to eat right. Thereafter, many countries of the world developed their own RDA, based on data obtained on local populations. Throughout most of the twentieth century, the focus of research in nutritional science was mainly on preventing undernutrition for the entire population. There was no distinction between individual requirements: the approach was to treat everyone as genetically identical.
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The link between diet and disease
Towards the end of the twentieth century, data started accumulating to indicate the involvement of diet in the etiology of several diseases, not hitherto recognized as directly related to diet. Incidence of diseases d iseases such as cardiovascular disorders, diabetes mellitus type 2, hypertension, cancer etc was linked to consumption of certain foods by individuals or ethnic groups of distinct geographical regions. The issue received global impetus when, in 1990, the World Health Organization (WHO) published the report of an expert group appointed to look into the relationships between diet, nutrition and prevention of chronic diseases [1]. This resulted in a paradigm shift in thinking: food is not only about preventing undernutrition and deficiency diseases but also about optimum health and prevention of common non-communicable diseases. Research in nutritional science started getting focused on healthy diets for disease prevention [2], and in 2003, the WHO Expert Committee published its report recognizing the link between several chronic diseases and obesity, further emphasizing the link between diet, disease and optimum health [3] Scientific evidence mounted that chronic disease d isease could be modified, positively as well as negatively, by dietary adjustments, and that these must begin early in the life of an individual, because diet has a long-term bearing on later health.
Epidemiological as well as experimental approaches indicated that benefits of dietary choices differ among individuals and dietary requirements may be individualistic. Diet seemed to have a modifying effect on the genetics of a person which influenced the phenotype. Thus, the same dietary factors factors were found to produce disease in a person who had a genetic predisposition to that particular disease, but not in others with a different genetics. The individual’s response to a food or nutrient could be traced to differences in metabolic handling of a dietary component, involving complex interactions between genotypes, metabolic phenotypes, other dietary factors, lifestyle and environmental factors.
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Thus arose the possibility of developing personal diets for disease prevention for an individual. However, to unravel individual responses to food and diets, the requirement was for satisfactory molecular approaches to study how metabolism of food differs with regard to age, gender, lifestyle, phenotype such as body size, and genetics. This made the issue very complex. It was further complicated by developmen ts in epigenetics whereby changes in phenotype or genetic expression were traced to mechanisms other than changes in DNA sequence. Historically, Jacob and Monad, in 1961, described how lactose acts as a nutrient inducer and increases expression of three structural genes (lac operon) coding for lactose metabolizing enzymes. Other classical experiments also indicated nutritional influences on gene expression. For example, polyribosome formation was linked to the requirement of essential amino acids; synthesis of ferritin was found to be iron-induced and a high carbohydrate diet and fasting were found to regulate PEP carboxykinase. Indirect influences, for example through mediators such as hormones or signaling systems, were found to produce changes chang es in transcription of specific genes to yield proteins that define phenotypic expression [4]. Although it was clear that nutritional science cou ld establish personal diet-health relationships and predict disease in an individual, practical applications were limited due to methodological constraints, and followed developments in genetics. The evidence for nutrient-gene interactions: the birth of nutrigenomics
Genes are the segments of deoxyribonucleic acid (DNA) which code for a protein, and direct the development of an organism. They are inheritable; and different forms of a given gene, known as alleles, produce several characteristics: the phenotypes, of which eye color and hair color are examples. Genetic diseases, such as phenylketonuria, sickle cell anemia and scores of others, have traditionally been termed as those arising out o f effects in a single allele of a gene. 97 % of known genetic diseases are monogenic diseases. More recently, it has been recognized that several genetic disorders are multifactorial or polygenic in nature. Heart diseases and diabetes mellitus fall in this category. The interaction between environmental env ironmental factors such as nutrition and genes in
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the etiology of such diseases is also a subject of much recent study, involving scientists from several disciplines. The complete set of genes in an organism is known as its genome. The DNA in the nucleus of the human cell has about 3 billion base pairs. Developments in sequencing technologies and improved computing power led to the formal beginning, in October 1990, of the Human Genome Project (HGP) which was an international collaborative effort at sequencing all these 3 billion bases to identify all human genes and make them accessible for further biological study. It met its goal in April 2003 [5, 6]. Since the human body contains over a hundred thousand proteins, it was expected that the genome would comprise of a commensurate number of genes. However, , the HGP has placed the number of genes in according to estimates published in 2004 [7] , the human genome at about 20 000 to 25 000, much less than expected at its outset. The proteins coded by the genome determine the visible physical characteristics of the organism and direct the metabolism of food and ensure that the body recognizes foreign from self, thereby fighting the large variety of possible infecting agents. It also modulates levels of various molecules which control behav ior. The great complexity that is the hallmark of the living system results to a large extent from thousands of chemical modifications that these proteins undergo, and the regulatory processes that control them, which ultimately manage to maintain homeostasis, despite the complexity of the organism.
There has been a growing recognition that nutrients act as dietary signals in controlling homeostasis by influencing the metabolic programming of cells [8]. The establishment of this link between diet and gene interactions led to the shift in focus of nutrition research to molecular biology and genetics; and nutrigenomics was born. The aim of nutrigenomics is to regulate a person’s nutritional regime to suit his genotype, and achieve optimal health.
For this, the need arose to obtain a holistic picture of the interaction between genes and food, and consequent homeostatic state, which characterizes human health.
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Thus, nutrigenomics has emerged as a potential tool to develop tailored diets to recover the homeostatic state and prevent or control diseases [9]. The premise underlying nutrigenomics is that influence of diet on health depends on an individual’s genetic make-up. Nutrigenomics tries to define the cause-effect relationship between specific nutrients and diets on human health, leading to the idea of a personalized diet, based on genotype. It seeks to provide a molecular understanding of how common chemicals in the diet affect health by altering the expression exp ression of genes and the structure of an individual’s genome.
However, the study of nutrient action at the molecular and subcellular levels is a very complicated task. For the first time, due to emerging technologies associated with the HGP, tools became available which could lead to a deeper understanding of interactions among food, genes, protein structure, post-translational changes in protein structure and consequent effects on metabolism. Thus, relationships among nutrients and food components, genomic structure or function and molecular events have begun to be established [9], [10].
To appreciate advances in nutrigenomics, it is essential to have a preliminary understanding of the tools and techniques of molecular biology which are used to understand gene expression, protein synthesis and finally metabolite production, through the sciences of genomics, transcriptomics, proteomics and metabolomics.
Fundamental concepts in gene expression, protein synthesis and metabolite production – Genomics; Transcriptomics; Proteomics and Metabolomics
Gene expression is the process that is described by the central dogma of molecular biology. The information encoded in the strands of the DNA, in the sequence of nucleotides, is used for its replication into two copies. It is then transcribed into a complementary chain of messenger ribonucleic acid (mRNA), which is translated into protein. This requires the mRNA to get anchored an chored to another kind of RNA, the ribosomal RNA (rRNA). A third kind of RNA, the transfer RNA (tRNA) specifically picks up
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amino acids based on the information in the nucleotide sequence of the mRNA, as dictated by the genetic code. Amino acids are the building blocks of polypeptides which organize to finally form the proteins. Proteins have a characteristic shape (conformation) which determines their varied functions. For example, as biological catalysts, the enzymes, they direct all metabolic activities. Thus, the final function of a protein depends on the base sequence of the gene which directed its synthesis. Gene expression is an extremely specific process, and maintains a very high level of fidelity with the information coded by the nucleotide sequence in the parent DNA.
Genomics is the study of the genome of an organism, which is the sum total of all genes of any individual. Genomics requires the study of all of the nucleotide sequences, including structural genes, regulatory sequences, and non-coding DNA segments, in the chromosomes of an organism. It requires determination of the entire DNA sequence of an organism, which comprises of about 3 billion b illion nucleotides. The foundation for sequencing of nucleotides was laid by Fred Sanger [11], and by Allan Maxam and Walter Gilbert [12]. However, it became possible to consider large-scale sequencing only after the development of high-throughput sequencing technologies that were capable of producing millions of sequences at once, and formed the basis of the HGP. All cells in the human body contain identical DNA, which can be sequenced by these sequencing techniques. However, all genes are not expressed in every cell all the time, which is the basis of differentiation of cells, leading to the varied functions of different cells, which ultimately is responsible for the complexity of multicellular organisms. Hence Genomics requires tools to understand which genes are being read and to what extent, that is, the complete set of RNA transcripts produced by the g enome at any specific time in a cell type. This set of RNA is known as the transcriptome, and the study of the transcriptome is known as transcriptomics. The genome is static but the transcriptome is extremely dynamic and changing, due to varying patterns of gene expression. In any organism, the transcriptome of various cells is nev er identical.
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Hence there is a need to study which genes are active in a cell at any given time. This has become possible due to the availability of DNA microarray technology which has provided scientists with a powerful technique to obtain the transcriptome [13]. Unlike sequencing techniques which describe the entire genome, this technique is capable of determining which genes are turned on in a given cell by analyzing the mRNA in that cell and obtaining the transcriptome. For this the mRNA in the cell under study is first collected, then labeled by attaching a fluorescent dye and placed in a DNA array slide containing a large number of DNA probes. The mRNA will attach to its complementary DNA on the microarray and appear under a fluorescence scanner. Microarrays obtained from a normal cell and a corresponding cell of a person suffering from, say diabetes mellitus will appear different if there is a difference in the activities of a particular particular gene in the two cells. This technique is used frequently frequently to examine the activities of various genes at different times. The technique is powerful enough to examine how active thousands of genes are at any given time. Differences in gene expression are studied by the process called expression analysis or expression profiling. Thus, the science of transcriptomics is important for the identification of genes that are differentially expressed in distinct cell populations or subtypes, to obtain data on the likely proteins that will be found in a particular cell. However, mRNA is not always translated into protein [14], so it does not always correlate with the proteins produced in a cell [15, 16]. Translation, and the consequent set of proteins in the cell, depends on the physiological state of the cell. So, the analysis of relative mRNA expression levels can be complicated by the fact that relatively small changes in mRNA expression can produce large changes in the total amount of the corresponding protein present in the cell, and in any cell, the set of proteins actually present at any given time depends on distinct requirements and stresses. It is also important that the 25- 30 thousand or so genes code for at least 100,000 proteins, mainly due to a variety of post translational modifications such as phosphorylation, ubiquitination, methylation, acetylation, glycosylation, oxidation, nitrosylation etc. Thus, the set of proteins present in any cell at any given time can vary to a large extent and the utility of transcriptomics becomes limited. Genomics describes the blueprint, and
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transcriptomics tells us which part of the blue print is being transcribed. But both are insufficient to obtain the entire set of proteins that are actually synthesized in a cell type at any given time. Thus arose the need to obtain the entire complement of proteins produced by a cell or an organism, leading to a new area of study called proteomics. .
The term proteomics was coined to rhyme with genomics, and denoted the study
of proteins within a cell or organism at a specific stage of the cell cycle and within a given environment [17]. The entire complement of proteins in the cell at any given time is known as the proteome [18]. Since the polypeptide is synthesized under instructions of the genome, in conjunction with w ith the transcriptome and is subjected to varying posttranslational modifications, a large variety of particular sets of proteins are produced by the cell. This set, the proteome, will depend on the distinct requirements of the cell and the stresses that a cell or organism undergoes, because proteomics confirms the presence of the protein and provides a direct measure of the quantity present. Since proteins are involved in virtually every cellular function, control every regulatory mechanism, and are modified in disease (as the cause or the effect), the proteome dictates the phenotype of the cell and, collectively, of the tissue or organ that the cells comprise. This phenotype varies with physiological state, such as cell cycle stage, differentiation, function, and age. What is of relevance to nutrigenomics is that it can also be impacted by the onset of or interventions in response to acute insults or chronic diseases [19]. Proteomic research aims to develop markers of disease ex pression and find therapeutic solutions [17]. Proteomics also helps to obtain the changes in protein profile in response to specific dietary interventions [20, 21]. The study of proteomics is much more complicated than genomics because the proteome, but not the genome, varies with time and environment in the same cell line. The tools of proteomics include obtaining the spectrum of different proteins in the cell line, sequencing of amino acids a cids in the polypeptide chains of the protein, their separation using 2-D gel electrophoresis, detection by mass spectrometry, including matrix assisted laser desorption/ionization (MALDI) mass spectrometry, ELISA based techniques for antibody based detection and quantification q uantification etc. and informatics tools. Any proteomic analysis is very costly, laborious, and time consuming. It yields a very large a mount of
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data which is difficult to interpret. Hence the need is to design simple experiments with clear-cut questions to make sense of data obtained from proteomic tools [19]. Proteins are not the only biomolecules in the cell. The cell also contains several thousands of molecules of sugars, organic acids and amino acids. Most of these are the result of metabolic processes which are the result of reactions catalyzed by some of the cellular proteins, the enzymes [22], although some are externally acquired. The term metabolome, to rhyme with genome, transcriptome and proteome, has been coined to denote the complete set of metabolites in a cell or an organism. Metabolomics [23], speci specifi fica call lly y nutr nutrit itio iona nall meta metabol bolom omic ics, s, is conce concern rned ed with with meta metabol bolic ic pathw pathway ayss and and networks and includes regulation of metabolic pathways and networks by nutrients and othe otherr food food comp compon onent ents. s. It summ summat ates es all all the the meta metabo boli lite tess in body body flui fluids ds,, whic which h are are impacted by endogenous factors such as age, sex, body composition, genetics, underlying pathologies, circadian rhythms and resting metabolic rate and exogenous factors such as diet, including all known and hitherto unknown nutrients as well as non-nutrients such as dietary fiber, additives, pollutants, drugs etc., and the large number of signals from hundr hundred edss of inte intest stin inal al micr microf oflo lora ra.. A very very larg largee numb number er of comp compoun ounds ds make make the the metabolome, which can be likened to a metabolic fingerprint reflecting the balance of an individual’s metabolism.
An analysis of the metabolome can be expected to lead to an understanding of the dyna dynami micc beha behavi vior or of meta metabo boli lism sm and and conse consequ quen entt cellu cellula larr funct functio ion. n. For For this this,, the the compoun compounds ds compri comprisin sing g the metabol metabolome ome need to be identi identifi fied, ed, quantif quantified ied and their their relati relative ve propor proportio tions ns analyze analyzed d and interp interpret reted. ed. This This has led to the develop development ment of meta metabo bono nomi mics cs,, whic which h is conc concer erne ned d with with the the quan quanti tita tati tive ve meas measur urem emen entt of the the metabolome. [23]. [23].
However, the measurement of such a large number of metabolites requires advanced methodology such as nuclear magnetic resonance, functional magnetic resonance imaging and high performance liquid chromatography, and handling of a large amount of mathematical data. Since many metabolites are small, mass spectroscopy (MS)
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is found to be suitable to measure compounds with mol wt. 70-500. But Bu t this technique cannot distinguish compounds with similar molecular weights. Hence it needs to be combined with other techniques such as liquid chromatography (LC) and gas chromatography (GC), denoted as LC/MS and GC/MS. Analysis of data thus obtained requires sophisticated tools of information technology (IT) [24]. More recently, a new technique which combines capillary electrophoresis (CE) with MS, known as CE/MS has been found suitable for obtaining the metabolome. Metabolomes can be used to compare profiles of cancer cells or other diseased cells with a normal cell and study modifications by drugs and similar interventions. The major goal of metabolomics is to model intracellular metabolism in its entirety [24].
An important difference between data obtained from metabolomics and other molecular biology techniques is that the latter employs reductionist approaches, while the former focuses on understanding complex biological b iological systems from a holistic systems point of view [24]. Metabolomics amplifies changes in the proteome, and represents the phenotype of an organism more closely [25]. It includes both signaling and structural molecules [26]. However, metabolomics as a science is still in its infancy, while the fields of genomics and proteomics are relatively more advanced. The need is to integrate these areas of research and follow a systems approach to the understanding of health and disease.
Application of metabolomics in the fields of pharmacology and toxicology has led to some success. However, most research in these fields have been conducted on laboratory animals which are genetically and nutritionally more homogenous than humans. More recently, attempts are being made to study the impact of nutrients on the metabolome [27]. But such studies have to be performed on humans, which makes it more difficult to formulate an experimental design that yields meaningful data. Thus application of metabolomics to nutrition research is more complicated. The human nutritional metabolome is a sum of all endogeno us and exogenous metabolites [23], which depends on extrinsic factors such as all nutrient and non-nutrient constituents of diet, drugs, physical activity, colonic flora, stress and on intrinsic factors such as body
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composition, tissue turnover, resting metabolic rate, age, genotype, health status, reproductive status and diurnal cycles. Various biofluids used to obtain the human metabolome are blood, urine and saliva, of which urine appears to be a suitable because it is easily available [23]. Some compounds identified in spectra obtained by nuclear magnetic resonance spectrum of human urine are: lactate, alanine, citrate, dimethylamine, dimethylamine, creatinine, N -oxide, trimethylamine- N -oxide, glycine, hippurate, urea, etc. There are several other compounds that may be identifiable. So, the first priority for research in this area is consensus on the definition of the human metabolome. The metabolome will be a complex set of a large number of compounds, found in varying concentrations at different points of time due to variations in metabolic rates. Analysis of such a dynamic and large body of data da ta is another priority for research in this area. Techniques involving mathematical modeling and pattern recognition emphasize the multidisciplinary nature of this field. The foregoing provides preliminary insights into the utility of genomics, transcriptomics, proteomics and metabolomics for understanding basic genetic and cellular processes. They are the tools of nutrigenomics that allow study of the effects of nutrients as dietary signals on gene expression, which includes genomic structure, function and molecular events. Interplay between diet and gene expression: Some examples
High-throughput genomic tools and the HGP provided the theoretical framework required to compare the nucleotide sequences of the entire genome of individuals. But this is no mean task. The human DNA, which forms the basis of all gene expression, comprises of 3 billion base pairs. However, gene s comprise only about 2 per cent of these nucleotides, called the coding part or the exon. The remaining 98 per cent is the noncoding portion called the introns. Tools of molecular biology and genomics have identified genes responsible for production of nutritionally important proteins such as digestive enzymes, transport molecules responsible for ferrying nutrients and cofactors to
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their site of use, and numerous other molecules responsible for metabolism and utilization of our dietary components, including macronutrients, vitamins, minerals, and phytochemicals [28]. These tools have also enabled study of the ‘non-coding DNA’, the introns, also erroneously called ‘junk DNA’; and have assigned to them important uses such as regulation of gene expression, evolutionary importance [29] and manual dexterity [30].
99.9 per cent of the genes of any two individuals are the same. The tiny 0.1 percent difference, roughly one nucleotide in 1000, is what makes up all the diversity seen in the approximately 10 billion humans on earth. The most common individual genomic variations (alleles) in humans include single nucleotide polymorphisms (SNPs, pronounced ‘snip’), which is a single base b ase substitution of one nucleotide with another. SNPs make up about 90% of all human genetic variation, since SNPs are estimated to occur in about 1 of every 1000 nucleotides [10]. According to one estimate, a total of at least 1.42 million SNPs are found at a density of one SNP per 1.91 kilobases [31]. An SNP may be of two types: the Adenine (A) may be replaced by Guanine (G), or cytosine (C) may be replaced by thymine (T), so that the polymorphism is known as A/G or C/T respectively. C/T polymorphism is more common than the A/G polymorphism [32].
SNPs are more commonly found within the coding region of genes, but also may be found within the introns. They are evolutionarily stable, they do not change much from generation to generation; hence they can be followed in population po pulation studies. SNPs have been recognized as precise gene markers. Since they can be affected by specific nutritional factors, proper levels of nutrients can be worked out and supplied exogenously or withheld, to ensure adequate expression of the gene to prevent disease. Scientists believe SNP maps will help them identify the multiple genes associated with complex ailments such as cancer, diabetes, vascular disease, and some forms of mental illness. These associations are difficult to establish with conventional genehunting methods because a single altered gene may make only a small contribution to the disease. This has made SNPs an intensive area of study, and led to the establishment of
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The SNP Consortium (TSC) in 1999 as a collaboration co llaborationof of several companies and institutions to produce a public resource of single nucleotide polymorphisms po lymorphisms (SNPs) in the human genome [33 , 34]. However, mapping such a large number of SNPs is a difficult task. This became easier with the discovery that SNPs are not inherited independe ntly but sets of adjacent SNPs are present on alleles in a block pattern. They are called haplotype. Entire blocks o f SNPs are transmitted through generations. This makes it easier to identify them. So if about 10 million SNPs have been estimated in human populations, all of them need not be identified. Just a few from a block are sufficient to characterize the presence of the entire block. This discovery led to the formation of The International HapMap Consortium in Oct 2002 to create a haplotype map of the human genome. An important objective of this endeavor was to guide the design and analysis of medical genetic studies and create a resource that would accelerate the identification of genetic factors that influence medical traits and open a new area in population genetics [35]. The importance of SNPs for nutrigenomics is emerging. Individual response to dietary factors consequent to differences in metabolic imbalances have been traced to SNPs. An SNP in the gene coding for the enzyme, methylenetetrahydrofolate reductase (MTHFR) is an example of its application in nutrigenomics. MTHFR is a cytoplasmic enzyme involved in processing of amino acids. It is required for proper utilization of dietary folic acid, because it catalyzes the reduction of 5, 10-methylenetetrahydrofolate to 5-methyl tetrahydrofolate. This reaction is required for the multistep process that converts the amino acid homocysteine to another amino acid, methionine, which is used by the body to make proteins and other important compounds, including neurotransmitters.
An SNP occurs at base pair 677of the gene for MTHFR. It is a C/T polymorphism, designated as MTHFR677T. The versions with C (CC and CT) function normally while the TT version is thermolabile and its activity is reduced. People with this variant accumulate homocysteine so that their methionine levels are reduced, which leads to increased risk for vascular disease, coronary heart disease, stroke, preeclampsia, certain kinds of birth defects and cognitive decline. This can be reversed
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by supplementing their diet with folate. The TT variant is relatively common in many populations worldwide [36]. Thus the MTHFR SNP is an example to show how requirement of a dietary constituent, in this case folate, depends on the polymorphism. There are about 20 genes that have polymorphisms that appear to confer a significant disadvantage, which may be overcome with a specific dietary modification which may require modulation of just one single compound, compou nd, such as folate in the case of the MTFHR SNP. [37].
Similar mechanisms involving other SNPs form an intensive area of research. For example, an SNP in the gene for the polypeptide angiotensinogen has been found to be associated with essential hypertension and response to dietary modulations such as the Dietary Approaches to Stop Hypertension (DASH) trial [38].
Gene expression can also be affected by another type of nutrient-gene interaction that involves transcription factors. Genes are flanked by un transcribed regions called Promoters. These are DNA sequences near the beginning of genes that signal RNA polymerase where to begin transcription. Transcription is mediated through binding of transcription factors to response element sequences which can modulate gene expression. Transcription factors are one of the groups of o f proteins that read and interpret the genetic ge netic "blueprint" in the DNA. Nutrients DNA. Nutrients can bind to the transcription factors to further modulate this gene expression. Several macro- and micro-nutrients have been found to affect various transcription factors, thus mediating nutrient-gene interactions [39]. This is the main mode of nutrient influence on gene expression. There are approximately 2600 proteins in the human genome that contain DNA-binding domains and most of these are presumed to function as transcription factors [40].
The nuclear hormone receptor superfamily of transcription factors, with 48 members in the human genome, gen ome, is the most important group of nutrient sensors [8, 39, 41, 42
]. Numerous receptors in this superfamily bind nutrients and their metabolites. These
include retinoic acid (retinoic acid receptor (RAR) a nd retinoid X receptor (RXR)), fatty acids (peroxisome proliferator activated receptors (PPARs) and liver X receptor (LXR)),
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vitamin D (vitamin D receptor (VDR)), oxysterols (LXR), bile salts (farnesoid X receptor (FXR), also known as bile salt receptor) or other hydrophobic food ingredients (constitutively active receptor (CAR) and pregnane X receptor (PXR)) [8, 41, 42, 43].
To illustrate, the mode of action of one o ne such nutrient-gene interaction is detailed here. The PPARs are lipid-activated transcription factors, associated with expression of genes involved in fatty acid metabolism [44]. The gene transcription first requires the binding of the PPAR to ω-3 and ω-6 fatty acids, after which it must bind to another ligand activated transcription factor, the retinoid X-receptor (RXR). This complex of PPAR-fatty acid + RXR-retinoid binds to the receptor response element and alters gene expression such that fatty acid synthesis is reduced and fatty acid oxidation is increased, leading to a lowering of fat storage. The effect of ω-3 fatty acids on increasing fatty acid oxidation has been found to be more than that of ω-6 fatty acids. Hence nutritionists now advocate a high ω-3 fatty acid intake to improve lipid profile.
However, findings with regard to effects of transcription factors are based o n laboratory studies. Mutant mice, transgenic mice, knockout mice and cell cultures are generally used to study how a particular transcription factor mediates the effect of a particular nutrient. However, sometimes cell lines display large differences in the expression of important transcription factors compared with primary cells or in or in vivo [39].
Nutrient-gene interactions also lead to varying metabolomic patterns. Since metabolomics is the science that analyzes metabolites which are the end products that depend on the genomics, transcriptomics and proteomics of an individual, the metabolome represents the outcome of the nutrient-gene-environment interaction. However, the analysis of the small molecules that comprise a metabolome is no easy task. To make metabolomics work for nutrigenomics, there is a need to have a library of small molecules to enable their identification. identification. For example, in a detailed study study of deproteinized plasma, 38 compounds were identified with the use of 1H NMR but 14 (25%) could not be identified [45]. Newer methods are more sensitive, yielding a larger number of metabolites but their identification is even more difficult.
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To assist scientists in the analysis of the metabolome, the National Institutes of Health (NIH) has established a consortium of small molecule screening centers called the Molecular Libraries Probe Production Centers Network (MLPCN) which performs high throughput screening (HTS) to identify small compounds. The MLPCN has established a collection of 300,000 chemically diverse small molecules, generally with molecular weight of 500 or less [46]. The challenges for the nutritional n utritional sciences will be to create a consensus of small molecules that are important for the study of metabolomics and then to create the standards needed for their identification with MS, NMR, and other emerging technologies [23].
Epigenetics is another area of research which has recently found bearing on nutrigenomics [10]. Epigenetic modifications influence gene ex pression so that only genes useful to a given kind of cell are activated, and this information can be transmitted to daughter cells. Variable environmental conditions can influence epigenetics, through the selective use and silencing of genes as cells develop.
As is evident from the foregoing, most methodologies used in biological sciences, especi especiall ally y in the area area of nutri nutrigeno genomic mics, s, have adopte adopted d the reduct reduction ionist ist approa approach ch to knowledge. This has catalyzed large strides in our understanding of biology. However, when studying complex life forms, reductionist approaches have their limitations [47,
48
]
and the need is to apply methodologies which allow a holistic view of the biological system being studied.
Methodological challenges: the growth of Systems Biology and the dietary signature
Any system is likely to behave differently when impacted by diverse stimuli, than when it is in a controlled environment. One of the great current debates in biology concerns whether the observed behavior of a system can be accounted for in terms of the
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behaviors of its subcomponents, and it has been suggested that holistic approaches may be more predictive and make for better understanding of the functioning of the body.
Systems biology is the term that envelops the various ‘-omics’ technologies. It develops the concept of complexity and attempts to understand the integrated function of complex, multicomponent biological systems, ranging from interacting proteins that carry out specific tasks to whole organisms [48]. This requires the study of the entire system under defined conditions by defining all the constituents in the system and determining the interactions among them [49, 50].
The systems biology approach has reported a fair amount of success in the area of pharmacogenomics, which is the study of genetic g enetic variability with regard to response to a drug [10]. But the methodological challenges of nutrigenomics are much more demanding because food comprises several thousands of varying nutrient and nonnutrient substances that, individually and collectively, impact the final outcome of metabolic processes and consequent health. Food is hundreds of folds more complex than any drug, and is constantly varying. It is the only input into the body, apart from the respiratory gases, which is responsible for the growth of a 3 kg newborn to a 70 kg adult, yet foods with widely varying nutrient compositions produce comparable bod y composition and functioning. Moreover, the system being affected, that is the human body, is the sum total of about a hundred trillion cells working in unison to maintain a homeostatic (homeodynamic?) entity.
Food components interact with our body at system, organ, cellular, and molecular levels, depending on their absorption, bioavailability, metabolism and bioefficacy. Modern nutritional and health research focuses on promoting health, preventing or delaying the onset of disease, and optimizing performance. It is important that the beneficial action of a particular food component at the molecular level does not cause a deleterious effect at some other level. Deciphering the molecular interplay between food and health requires therefore holistic approaches beca use nutritional improvement of certain health aspects must not be compromised by deterioration of others. In other
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words, in nutrition, we have to get everything right. [21] Innumerable studies are . .
available which report the effect of various food components on health, yet consensus with regard to the beneficial or detrimental d etrimental effects of even a single component is elusive, for various reasons [47], mainly because they lack the systems biology approach.
Applying the systems biology approach, nutrigenomics seeks to establish dietary signatures which are characteristic outcome of a person’s nutrient-environment-gene interaction. Thus, diseases with a genetic predisposition can lead to varied types of dietary signatures, which can be examined at various levels, such as cell culture, tissue culture and whole organisms.
Diet, environment and habits influence the development of common chronic diseases such as coronary heart disease (CHD), diabetes, cancer, hypertension and obesity. As described earlier, SNPs have been reported to trigger or provide protection against these diseases. Thus SNPs can be used as biomarker for early disease diagnosis as well as for preventive medicine. One such application, through comparison of two microarrays signifying ‘healthy’ versus ‘stress’ signatures, describes how nutrigenomic experiments can be used to identify individuals with sensitive genotypes. Individuals showing a ‘stress signature’ in the microarray would be at higher risk for developing serious conditions such as cirrhosis or insulin resistance under sustained metabolic and pro-inflammatory stress. With enough early warning, dietary intervention might reverse this process, regain homeostatic control and prevent these conditions in at-risk groups [39, 51]. However, such studies must be conducted on non-human models, because it is not possible to obtain human tissue for such work.
Another ‘signature’, which is more holistic and can be obtained from humans, is the metabolome, which is characteristic of a person, and is the outcome of his genomics, transcriptomics and proteomics. The impact of a nutrient or any molecule on one’s genome and transcriptome can lead to a modified proteome which will impact utilization of nutrients due to alterations in metabolism and lead to characteristic metabolomes. The metabolome, thus is the dietary signature of the dietary signal.
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However, although metabolomics has been used successfully in pharmacology and toxicology, where the number of exogenous compounds are few and well characterized, the challenges of the metabolomic approach for nutrigenomics is much more complex and requires handling han dling of very large datasets, pattern analysis techniques, mathematical modeling and extensive interdisciplinary research [23].
There is a concerted effort to identify small molecules likely to be found in the metabolome and make the data available in the the public domain. The Human Metabolome Database (HMDB) is a freely available electronic database containing detailed information about small molecule metabolites found in the human body. It is intended to be used for applications in metabolomics, clinical chemistry, biomarker discovery and general education. The database (version 2.0) contains over 6500 metabolite entries including both water-soluble and lipid soluble metabolites as well as metabolites that would be regarded as either abundant (> 1 uM) or relatively rare (< 1 nM). Additionally, approximately 1500 protein (and DNA) sequences are linked to these metabolite entries. Each MetaboCard entry contains more than 100 data fields with 2/3 of the information being devoted to chemical/clinical data and the other 1/3 devoted to enzymatic or biochemical data. Many data fields are hyperlinked to other databases (KEGG, PubChem, MetaCyc, ChEBI, PDB, Swiss-Prot, and GenBank) and a variety of structure and pathway viewing applets. The HMDB database supports extensive text, sequence, chemical structure and relational query searches. Two additional databases, DrugBank and FooDB are also part of the HMDB suite of databases. DrugBank contains equivalent information on ~1500 drugs while FooDB contains equivalent information on ~2000 food components and food additives [52, 53].
Another methodological issue is that most nutrients may be weak but
chronic dietary signals, acting on polygenic diet related diseases. Their detection would poses problems which are distinct from those faced in pharmacogenomics.
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Thus, there are two main strategies of nutrigenomics. The first, molecular nutrition and genomics, allows study of how food can impact target genes, mechanisms and pathways, using a reductionist approach, requiring relatively affordable methodologies. The other, which entails development and study of dietary signatures, profiles and early biomarkers requires the more desirable holistic nutritional systems biology approach, but which is much more complex and requires much larger funding.
Tailor-made diets - Panacea or distant dream
From the foregoing, it can be said that nutrigenomic tools have been instrumental in establishing that gene-nutrient-environmental interactions exist and produce specific stress signals. The question is whether specific medical foods and supplements can be tailored for alleviating the stress, and for early detection and management of various diseases. Some success has been achieved with regard to understanding the genetic basis of many common polygenic diseases and the impact of isolated dietary components on their etiology at the molecular level, which is required to obtain an assessment of the feasibility of tailor-made diets.
Obesity is a major health problem which predisposes the bod y to several diseases. Living beings have evolved through food shortages, so genetically, we are predisposed to assimilate and store as much energy as possible in times of food surplus, but we are not genetically tuned to losing it, which complicates co mplicates body weight management. Overweight, obesity and related medical complications can occur as a result of genetic or acquired changes in a large number of processes, including, cardiac diseases, Diabetes mellitus, cancer [3, 54] etc. According to one estimate, food components may be acting on genetic variants in more than 400 genes, thereby the predisposition to develop several obesityassociated medical problems becomes a very complex issue [55]. Hence, though limited success has been achieved in understanding obesity at the molecular level, more in depth
22
studies are required to understand the nutrient-gene nu trient-gene interactions for various disorders before nutrigenomics provides a panacea for this problem.
There are many challenging issues concerning diet and genetic polymorphism in relation to cardiac diseases that need to be discussed. Single-nucleotide polymorphisms in several genes have been linked to differential effects in terms of lipid metabolism; however, even a simple model of benefit and risk is difficult to interpret in terms of dietary advice to carriers of the various alleles because of conflicting interactions between different genes. For example, the reported benefit of polyunsaturated fatty acids in studies of various polymorphisms may be due to the n-3 family of polyunsaturated fatty acids which is high in fish and is likely to have been high in primitive diets but is deficient in our modern diet [56]. Predisposition to cardiac diseases has been discussed earlier in relation to another SNP, the MTHFR677T SNP.
Osteoporosis is another widespread disease that has been found to have a genetic g enetic basis. Numerous candidate genes for osteoporosis susceptibility have been identified over the last two decades, and the effect of certain nutrients and dietary components on bone health-related parameters. The issue is very complex, and has not yet reached a stage where it is scientifically possible to advise people to alter their diet on the basis of their genotype (i.e. personalised nutrition for osteoporosis prevention) [57]. Another disease which seems to have a genetic basis and whose incidence and severity can be modulated by diet is Crohn’s disease, which is one of the causes of Inflammatory Bowel Disease (IBD). The Nutrigenomics NZ is attempting attempting to identify SNPs SNPs involved in the development of IBD as a first step on determining how food components can affect the disease at the molecular genetic level. [58].
These are just a few of the large quantum of research which have found links between various dietary components and most common health conditions such as obesity, o besity, cardiac diseases, hypertension, cancer, osteoporosis, IBD etc. Thus, the prospects appear to be good for nutrigenomics as the technology to prescribe tailored dietary regimens specific to an individual’s genetic requirements.
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This has attracted extensive media attention, and has triggered the introduction of large numbers of functional foods, which are claimed to have health-promoting / disease preventing properties. ‘Nutrigenetic services’ are also available over the internet without the involvement of a health care professional. Among the genetic variants most commonly assessed by these companies are those found in genes that influence cardiovascular disease risk [59]. Several commercial companies are already offering personalized nutrition services based on testing. Personalized foods are predicted to be launched on the market in 3 to 10 years. It is predicted that everyone would have the opportunity to choose, among a large set of recommended products, the foods that are best adapted to his/her personal metabolic profile, p rofile, as described by the metabolome.
However, caution is warranted in the interpretation of DNA-based data, which is very complex. There is need to carefully examine nutritional genomics as a potential tool for targeted medical nutrition therapy [59]. Clear-cut yes or no answers to whether personalized diets are ‘doable’ needs to be assessed at the level of the experiment, the laboratory and the relevant social worlds [60]. Attempts are being made to review nutritional genomics research and policy for nutrition practice and policy and for maximizing benefit and minimizing adverse outcomes w ithin genetically diverse human populations [61]. However, until the scientific evidence concerning diet-gene interactions is much more robust, the provision of personalized pe rsonalized dietary advice on the basis of specific genotype remains questionable [62].
Even if the applications of currently available information are useful for individualized dietary advice, there is a dearth of personnel who can educate the end-user of nutrigenomic technologies; about its benefits, utilizing social research and addressing consumers’ hopes and concerns [63], others who can provide genetic counseling [64]), yet others who can develop products, handle patenting issues, create regulations and conduct clinical trials, in a wide variety of industries such as the pharmaceutical industry, food industries and those involved in diagnostics [65].
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It is important that applications of findings in nutrigenomics are accompanied by appropriate information for the consumer, because scientific claims about the benefits of a food ingredient may be based on reductionist approaches where confounding variables are controlled [47]. Nutritional needs are complex, and apart from genetic make up, are also dependent on age, gender, lifestyle, exercise, phenotype, and epigenomic imprinting. What may work for one person may not work for another. The benefits be nefits are limited by laws of probability, and there are no universal magic bullets [66].
Another area that is very complex but equally important must deal with the ethical, legal and social implications (ELSI) of genomic research [10]. The bioethical issues concerning human nutrigenomics include issues of privacy, social stigmatization, despair in affected individuals and their family and friends, discriminatory practices by employers and insurance agencies, and several related problems [10, 62].
The question has been raised whether nutrigenomics can provide the panacea that it propounds to do [55], because living cells are complex, dynamic chemical plants with redundant pathways and feedback systems which respond to every change, and translating laboratory findings to practical diet plans is not a simple task. The diversity of dietary compounds is enormous; there are an estimated 5000 types of flavanoids alone 67, in addition to scores of other compounds. c ompounds. Moreover, there are difficulties associated with finding biomarkers that quantify health status. Health is more difficult to define than disease, so most biomarkers define disease rather than hea lth. Nutrients have relatively minor effects on health endpoints, as compared co mpared to those of drugs in pharmacodynamic ph armacodynamic studies, and there are large intra and an d inter individual variations not related to diet. Biological systems can be treated in isolated pieces on ly for purposes of study. However, they form a complex and delicate network of feedback loops and interplays that defies simplification [55], and ‘…one thing is clear: to understand the whole one must study the whole.’ [68]. CONCLUSION
The present and future of nutrigenomics:
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Less than two centuries after Magendie discovered the essentiality of dietary protein and his student, Claude Bernard gave the concept of homeostasis, and about half a century since Watson and Crick discovered the structure of DNA, incredibly rapid technological advances have led to in depth knowledge about the complexity that underlines the interactions among diet, genes, environment and the tools to study them. Scientists have unraveled the entire human genome of 3 billion base pairs, identified the 25 thousand genes among these base pairs, assessed the presence of about 100 thousand proteins in the human proteome, studied thousands of the approximately 10 million SNPs, and some HapMaps, that exist in human populations, identified about 2600 proteins which function as transcription factors and created a molecular library of about 300 thousand small molecules, most of which are metabolites. They have also identified about 5000 naturally occurring flavonoids in various plants used as food [67] and a large number of other nutrient and non nutrient compounds in foods. foods. Thus, an enormous amount of data has been generated and efforts continue to obtain meaningful information from it. However, given the complexity of both the systems involved, that is the human body and the dietary compounds, compounded by other variables, it is an enormous task to make sense of the data that will emerge from current technologies. Hence, it will be necessary to develop nutrigenomics on the lines of nutritional systems biology to address current challenges [69]. Data analysis by super computers, capable of complex mathematical modeling will be required, especially if the more favored holistic perspective is to be adopted.
Despite these complexities, nutrigenomics holds promise for improving the life of future generations; and personalized assessments based on metabolomics will, some day in the not too distant future, replace the traditional tools used to evaluate nutritional status. They will lead to the ability to make nutrition recommendations uniquely suited to the individual according to their genetic makeup and metabolic profile [70], thus making personalized, customized nutrition counseling a reality.
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However, new approaches to handle the complexities and social consequences of the emerging technologies will be required, and the major challenges for nutrigenomic research in the next decade will continue to be identification of cause/effect relationships among multiple genome variants, diet and other environmental factors, and the main chronic diseases. The technology is directionally correct but we still have a long way to go.
The future must also address the need to provide both specialized genomicsrelated education and training and general public information to enhance awareness, build competencies, make informed decisions, and ensure continuity of access to health services. The controversies related to personalized diets and benefits of functional foods must be presented to the public in their correct perspective. Scientists and the media must synergize to ensure that the issue is publicized in its correct perspective, without undue euphoria, nor unwarranted caution, because as a science, nutrigenomics is still in its infancy, but holds the promise to offer the panacea in times to come.
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