Perspectives in Nutrigenomics for human health

Poonam C. Mittal, Biochemistry 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

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 consequences 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 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, night

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 population. 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 knowhow 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 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 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 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 developments 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 in transcription of specific genes to yield proteins that define

phenotypic expression [4].

Although it was clear that nutritional science could 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 of

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 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,

according to estimates published in 2004 [7], the HGP has placed the number of genes in

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 behavior. 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.

6

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 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 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.

1 WHO Technical Report Series, No. 797. (1990). Diet, nutrition and the prevention of

chronic diseases. Report of a WHO Study Group. World Health Organization, Geneva.

2 The World Health Report (2002): Reducing risks, promoting healthy life. World Health

Organization, Geneva.

3 WHO Technical report Series 916. (2003). Diet, nutrition and the prevention of chronic

diseases. Report of a Joint WHO/FAO Expert consultation. Geneva.

4 Cousins, R. J. (1999). Nutritional regulation of gene expression. In: Shils, M.E., Olson,

J.A., Shike, M. & Ross, A.C. eds. Modern Nutrition in Health and Disease. Williams and

Wilkins Baltimore. 573-584.

5 US Department of Health and Human Services. International consortium completes

human genome project: all goals achieved; new vision for genome unveiled. NIH News.

Available from: http://www.nih.gov/news/pr/apr2003/nhgri-14.htm.

6 Human Genome Project Information System. Oakridge National Laboratory . Available

from: http://www.ornl.gov/sci/techresources/Human_Genome/project/about.shtml.

7 Stein, L. D. (2004). Human Genome: End of the Beginning, Nature, 431, 915-916.

8 Francis, G. A., Fayard, E., Picard, F. & Auwerx, J. (2002). Nuclear receptors and the

control of metabolism. Annu. Rev. Physiol. 65, 261–311.

9 Kaput, J. & Rodriguez, R. L. (2004). Nutritional genomics: the next frontier in the

postgenomic era. Physiol Genomics, 16,166–177.

10 Kauwell, G. P. A. (2005). Emerging Concepts in Nutrigenomics: A Preview of What Is

to Come. Nutrition in Clinical Practice, 20:75–87.

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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 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 genome 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 never identical.

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 11 Sanger, F., Nicklen, S. & Coulson, A. R. (1977). DNA sequencing with chain-

terminating inhibitors. Proc. Natl. Acad. Sci. U.S.A. 74 (12), 5463–7.

12 Maxam, A. M. & Gilbert, W. (1977). A new method for sequencing DNA. Proc. Natl.

Acad. Sci. U.S.A. 74, (2): 560–4.

13 DNA Microarray Fact Sheet. National Human Genome Research Institute, National

Institute of Health. Available from: http://www.genome.gov/10000533).

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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 gene in the two cells. This technique is used 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,

14 Buckingham, S. (2003). The major world of microRNAs. Available from:

http://www.nature.com/horizon/rna/background/micrornas.html.

15 Rogers, S., Girolami, M., Kolch, W., Waters, K. M., Liu, T, Thrall B., & Wiley, H. S.

(2008). Investigating the correspondence between transcriptomic and proteomic

expression profiles using coupled cluster models. Bioinformatics 24 (24): 2894–2900.

16 Dhingraa, V., Gupta, M., Andacht, T. & Fu, Z. F. (2005). New frontiers in proteomics

research: A perspective. International Journal of Pharmaceutics, 299 (1–2): 1–18.

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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

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 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].

17 Pardanani, A., Wieben, E. D., Spelsberg, T. C. & Tefferi, A. (2002). Primer on medical

genomics, part IV: expression proteomics. Mayo Clin Proc.; 77:1185–1196.

18 Wilkins M. R., Pasquali, C., Appel, R. D., Ou, K., Golaz, O., Jean-Charles Sanchez, J.,

Yan, J. X., Andrew. A. Gooley, A. A., Hughes, G., Humphery-Smith, I, Williams, K. L.

& Hochstrasser D.F. (1996). From Proteins to Proteomes: Large Scale Protein

Identification by Two-Dimensional Electrophoresis and Amino Acid Analysis. Nature

Biotechnology, 14 (1): 61–65.

19 Arrell, D. K., Neverova, I. & Van Eyk, J. E. (2001). Cardiovascular Proteomics:

Evolution and Potential. Circ Res.; 88:763-773.

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Proteomic research aims to develop markers of disease expression 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 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 etc. and informatics tools. Any proteomic

analysis is very costly, laborious, and time consuming. It yields a very large amount of

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],

20 Kvasni[caron]cka, F. (2003). Proteomics: general strategies and application to

nutritionally relevant proteins. J Chromatogr B Analyt Technol Biomed Life Sci, 787:77–

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21 Kussmann, M. & Affolter, M. (2009). Proteomics at the center of nutrigenomics:

Comprehensive molecular understanding of dietary health effects. Nutrition. 25, 11,

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22 Tomita, M. (2005). Chapter 1: Overview. In Metabolomics: the frontier of systems

biology. Ed. Tomita, M and Nishioka, T. Springer-Verlag, Tokyo. pp.1-5.

23 Gibney, M J; Walsh, M; Brennan, L; Roche, HM; German, B & van Ommen, B.

(2005). Metabolomics in human nutrition: opportunities and challenges. Am J Clin Nutr..

82: 497-503.

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specifically nutritional metabolomics, is concerned with metabolic pathways and

networks and includes regulation of metabolic pathways and networks by nutrients and

other food components. It summates all the metabolites in body fluids, which 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

hundreds of intestinal microflora. A very large number of compounds make 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

dynamic behavior of metabolism and consequent cellular function. For this, the

compounds comprising the metabolome need to be identified, quantified and their

relative proportions analyzed and interpreted. This has led to the development of

metabonomics, which is concerned with the quantitative measurement of the

metabolome. [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)

is found to be suitable to measure compounds with mol wt. 70-500. But 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

24 Kell, D. B., (2004). Metabolomics and systems biology: making sense of the soup.

Current Opinion in Microbiology, 7:296–307

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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 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 endogenous 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

25 Kell, D. B. (2006). Systems biology, metabolic modeling and metabolomics in drug

discovery and development. Drug Discov Today. 23-24:1085-92.

26 Saghatelian, A & Cravatt, B. F. (2005). Global strategies to integrate the proteome and

metabolome. Current Opinion in Chemical Biology, 9:62–68.

27 Whitfield, P. D., German, A. J. & Nobel, P. J. (2004). Metabolomics: an emerging

postgenomic tool for nutrition. Br J Nutr, 92, 549 –55.

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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, creatinine, 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 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, genes comprise only about 2 per cent of these

nucleotides, called the coding part or the exon. The remaining 98 per cent is the non-

coding 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

their site of use, and numerous other molecules responsible for metabolism and

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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 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].

28 Fogg-Johnson, N & Kaput, J. (2003). Nutrigenomics: An Emerging Scientific

Discipline. Food technology. 57, 4.

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Journal 14(2): 18-30.

30 Prabhakar, S., Visel, A., Akiyama, J.A., Shoukry, M., Lewis, K.D., Holt, A., Plajzer-

Frick, I., Morrison, H., FitzPatrick, D. R., Afzal, V., Pennacchio, L. A. Edward M.

Rubin, E. M. & Noonan, J. P. Human-Specific Gain of Function in a Developmental

Enhancer. (2008).Science, 321, 5894, 1346 – 1350.

31 Chakravarti, A. (2001) Single nucleotide polymorphisms …to a future of genetic

medicine. Nature, 409, 822-23.

32 Human Genome Project Information. Available from:

http://www.ornl.gov/sci/techresources/Human_Genome/project/about.shtml

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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 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 gene-

hunting 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

The SNP Consortium (TSC) in 1999 as a collaboration of several companies and

institutions to produce a public resource of single nucleotide polymorphisms (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 independently but sets of adjacent

SNPs are present on alleles in a block pattern. They are called haplotype. Entire blocks of

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

33 Sachidanandam,R., Weissman,D., Schmidt,S., Kakol,J., Stein,L., Marth,G., Sherry,S.,

Mullikin,J., Mortimore,B., Willey,D., Hunt,S., Cole,C., Coggill,P., Rice,C., Ning,Z.,

Rogers,J., Bentley,D., Kwok,P., Mardis,E., Yeh,R., Schultz,B., Cook,L., Davenport,R.,

Dante,M., Fulton,L., Hillier,L., Waterston,R., McPherson,J., Gilman,B., Schaffner,S.,

Van Etten,W., Reich,D., Higgins,J., Daly,M., Blumenstiel,B., Baldwin,J., Stange-

Thomann,N., Zody,M., Linton,L., Lander,E. and Altshuler, D. The International SNP

Map Working Group (2001). A map of human genome sequence variation containing

1.42 million single nucleotide polymorphisms; Nature, 409, 928–933.

34 Thorisson G. A. & Lincoln D. Stein, L. D. (2003) The SNP Consortium website: past,

present and future. Nucleic Acids Research, 31. , No. 1 124-127.

17

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

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

35 Gibbs R. A. et al., (2005) A haplotype map of the human genome: The International

HapMap Consortium. Nature, (2005) 437, 1299-1320.

18

require modulation of just one single compound, 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 untranscribed 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 proteins that read and interpret the genetic

"blueprint" in the 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, is the most important group of nutrient sensors [8, 39, 41, 42]. Numerous receptors in this superfamily bind nutrients and their metabolites. These

36 Genetics Home Reference: Available at: http://ghr.nlm.nih.gov/gene=mthfr

37 Schwahn, B. & Rozen, R. (2002). Polymorphisms in the methylenetetrahydrofolate

reductase gene: clinical consequences. Am J pharmacogenomics: genomics-related

research in drug development and clinical practice. 1 (3): 189–201.

38 Svetkey, L. P., Moore, T. J., Simons-Morton DG, et al. (2001). Angiotensinogen,

genotype and blood pressure response in the Dietary Approaches to Stop Hypertension

(DASH) study. J Hypertens;19:1949–1956.

19

include retinoic acid (retinoic acid receptor (RAR) and retinoid X receptor (RXR)), fatty

acids (peroxisome proliferator activated receptors (PPARs) and liver X receptor (LXR)),

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 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.

39 Müller, M. & Sander Kersten, S. (2003). Nutrigenomics: goals and strategies. Nature

Reviews Genetics. 4, 315- 322

40 Babu, M.M., Luscombe, N.M., Aravind, L., Gerstein, M. & Teichmann SA (2004).

Structure and evolution of transcriptional regulatory networks. Curr. Opin. Struct. Biol.

14 (3): 283–91.

41 Lu, T. T., Repa, J. J. & Mangelsdorf, D. J. (2001). Orphan nuclear receptors as eLiXiRs

and FiXeRs of sterol metabolism. J. Biol. Chem. 276, 37735–37738.

42 Mangelsdorf, D. J. et al. (1995). The nuclear receptor superfamily: the second decade.

Cell 83, 835–839.

43 Chawla, A., Repa, J. J., Evans, R. M. & Mangelsdorf, D. J. (2001). Nuclear receptors

and lipid physiology: opening the X-files. Science, 294, 1866–1870.

44 Clarke, S.D., Thuillier, P., Baillie, R. A. & Sha X. (1999). Peroxisome proliferator-

activated receptors: a family of lipid-activated transcription factors. Am J Clin

Nutr.;70:566–571.

20

However, findings with regard to effects of transcription factors are based on

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 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. For example, in a detailed 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.

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 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].

45 Ala-Korpela M. (1995). 1H NMR spectroscopy of human plasma. Prog Nucl Mag Res,

27:475–554.

46 NIH Roadmap for medical research. (2008). Available from:

http://nihroadmap.nih.gov/molecularlibraries

21

Epigenetics is another area of research which has recently found bearing on

nutrigenomics [10]. Epigenetic modifications influence gene expression 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,

especially in the area of nutrigenomics, have adopted the reductionist approach 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

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

47 Mittal, P. C. (2009). What should we eat: contradictory researches and the confused

consumer! In ‘New Research on Food Habits’ pp 17-34. Ed. F. Columbus. Nova Science

Publishers, New York.

48 Strange, K. (2005). The end of "naive reductionism": rise of systems biology or

renaissance of physiology? Am J Physiol Cell Physiol. 288:968-974.

22

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 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 non-

nutrient 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 body

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 because nutritional improvement of

certain health aspects must not be compromised by deterioration of others. In other

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

49 van Ommen, B. & Stierum, R. (2002) Nutrigenomics: exploiting systems biology in the

nutrition and health arena. Curr Opin Biotechnol.;13:517–521.

50 Ghazalpour, A., Doss, S., Yang, X., et al. (2004). Thematic review series: the

pathogenesis of atherosclerosis: toward a biological network for atherosclerosis. J Lipid

Res., 45: 1793–1805.

23

with regard to the beneficial or detrimental 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.

51 Whitney, A. R. et al. (2003). Individuality and variation in gene expression patterns in

human blood. Proc. Natl Acad.Sci. USA 100, 1896–1901.

24

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 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 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].

52 Human Metabolome Database. Available from:

http://www.chemaxon.com/forum/ftopic5363.html. Posted: Fri Oct 02, 2009 8:29 pm.

53 Wishart DS, Knox C, Guo AC, et al. (2009). HMDB: a knowledgebase for the human

metabolome. Nucleic Acids Res. 37(Database issue):D603-610.

25

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.

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 body 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 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,

26

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 obesity-

associated 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

studies are required to understand the nutrient-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

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

54 Calle, E.E. & Kaaks, R. (2004) Overweight, obesity and cancer: epidemiological

evidence and proposed mechanisms. Nature Rev. Cancer, 4: 579-589.

55 Palou, A. (2007). From nutrigenomics to personalised nutrition. Genes Nutr. 2:5–7

56 Ordovas, J.M. (2006). Genetic interactions with diet influence the risk of cardiovascular

disease. Am J Clin Nur.; 83(2):443S-446S.

57 Cashman, K.D., & Seamans, K. (2007). Bone health, genetics, and personalised

nutrition. Genes Nutr 2:47–51

27

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 to identify 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,

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.

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, 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

58 Ferguson, L. R., Peterman, I., Hu¨bner, C, Philpott, M. & Shelling, A.N. (2007).

Uncoupling gene–diet interactions in inflammatory bowel disease (IBD). Genes Nutr

2:71–73.

59 Vakil, S., Caudill, M.A. (2008). Personalized nutrition: nutritional genomics as a

potential tool for targeted medical nutrition therapy. Nutr. Rev. 65 (7): 301-15.

28

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 within genetically diverse human

populations [61]. However, until the scientific evidence concerning diet-gene interactions

is much more robust, the provision of personalized 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].

60 Penders, B. (2007). Personalised diet: is it doable? Individuality at different sites of

nutrigenomic practice. Genes Nutr 2:93–94.

61 Stover, P.J. & Caudill, M.A. (2008). Genetic and epigenetics contributions to human

nutrition and health: managing genome-diet interactions. J Am. Diet Assoc.. 198 (9):

1480-7.

62 Bergmann, M.M., Görman, U. & Mathers, J.C. (2008). Bioethical considerations for

human nutrigenomics. Ann Rev Nutr. 28: 447-67.

63 Ronteltap, A. & van Trijp, H. (2007). Consumer acceptance of personalized nutrition.

Genes Nutr. 2:85–87.

64 Ferguson L. R., Shelling, A. N., Lauren, D, McNabb W. (2007). Nutrigenomics and gut

health: meeting report from an international conference in Auckland, New Zealand, April

30, May 1–3, 2006. Genes Nutr 2:157–160.

65 Ruth L, Wrick KL (2005) Nutrigenomics: impact on diets, markets and health. Adv Life

Sci Rep 48: 1–261. Cambridge Healthtech Advisors, Waltham MA, USA.

http://www.chadvisors.com

29

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 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. 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 health. Nutrients have relatively

minor effects on health endpoints, as compared to those of drugs in pharmacodynamic

studies, and there are large intra and inter individual variations not related to diet.

66 Mittal, P. C. (2008). Modulating the aging process: A Biologist’s Perspective. pp 26-

29. In Population, Ageing and Development. Ed. Kapoor, R. N. Publ. Institute of Social

Development, Udaipur, India.

67 Nutrient Data Laboratory; Beltsville Human Nutrition Research Center, USDA. Nutrient database for standard reference, release. USDA Database; 2003. Available from: http://www.nal.usda.gov/fnic/foodcomp

30

Biological systems can be treated in isolated pieces only 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:

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.

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

68 Kacser,H. (1986) in The Organization of Cell Metabolism, ed., G.R. Welch and J.S.

Clegg, Plenum Press, New York, 327-3.

31

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.

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 genomics-

related 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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