Metabolomics, Metabonomics and Functional Nutrition: the next step in nutritional metabolism and biotherapeutics

Reviewer and Curator: Larry H. Bernstein, MD, FCAP 

The human genome is estimated to encode over 30,000 genes, and to be responsible for generating more than 100,000 functionally distinct proteins. Understanding the interrelationships among

1. genes,
2. gene products, and
3. dietary habits

is fundamental to identifying those who will benefit most from or be placed at risk by intervention strategies.

Unraveling the multitude of

• nutrigenomic,
• proteomic, and
• metabolomic patterns

that arise from the ingestion of foods or their

• bioactive food components

will not be simple but is likely to provide insights into a tailored approach to diet and health. The use of new and innovative technologies, such as

• microarrays,
• RNA interference, and
• nanotechnologies,

will provide needed insights into molecular targets for specific bioactive food components and

• how they harmonize to influence individual phenotypes(1).

Nutrigenetics asks the question how individual genetic disposition, manifesting as

• single nucleotide polymorphisms,
• copy-number polymorphisms and
• epigenetic phenomena,

affects susceptibility to diet.

Nutrigenomics addresses the inverse relationship, that is how diet influences

• gene transcription,
• protein expression and
• metabolism.

A major methodological challenge and first pre-requisite of nutrigenomics is integrating

• genomics (gene analysis),
• transcriptomics (gene expression analysis),
• proteomics (protein expression analysis) and
• metabonomics (metabolite profiling)

to define a “healthy” phenotype. The long-term deliverable of nutrigenomics is personalised nutrition (2).

Science is beginning to understand how genetic variation and epigenetic events

• alter requirements for, and responses to, nutrients (nutrigenomics).

At the same time, methods for profiling almost all of the products of metabolism in a single sample of blood or urine are being developed (metabolomics). Relations between

• diet and nutrigenomic and metabolomic profiles and
• between those profiles and health

have become important components of research that could change clinical practice in nutrition.

Most nutrition studies assume that all persons have average dietary requirements, and the studies often

• do not plan for a large subset of subjects who differ in requirements for a nutrient.

Large variances in responses that occur when such a population exists

• can result in statistical analyses that argue for a null effect.

If nutrition studies could better identify responders and differentiate them from nonresponders on the basis of nutrigenomic or metabolomic profiles,

• the sensitivity to detect differences between groups could be greatly increased, and
• the resulting dietary recommendations could be appropriately targeted (3).

In recent years, nutrition research has moved from classical epidemiology and physiology to molecular biology and genetics. Following this trend,

• Nutrigenomics has emerged as a novel and multidisciplinary research field in nutritional science that
• aims to elucidate how diet can influence human health.

It is already well known that bioactive food compounds can interact with genes affecting

• transcription factors,
• protein expression and
• metabolite production.

The study of these complex interactions requires the development of

• advanced analytical approaches combined with bioinformatics.

Thus, to carry out these studies

• Transcriptomics,
• Proteomics and
• Metabolomics

approaches are employed together with an adequate integration of the information that they provide(4).

Metabonomics is a diagnostic tool for metabolic classification of individuals with the asset of quantitative, non-invasive analysis of easily accessible human body fluids such as urine, blood and saliva. This feature also applies to some extent to Proteomics, with the constraint that

• the latter discipline is more complex in terms of composition and dynamic range of the sample.

Apart from addressing the most complex “Ome”, Proteomics represents

• the only platform that delivers not only markers for disposition and efficacy
• but also targets of intervention.

Application of integrated Omic technologies will drive the understanding of

• interrelated pathways in healthy and pathological conditions and
• will help to define molecular ‘switchboards’,
• necessary to develop disease related biomarkers.

This will contribute to the development of new preventive and therapeutic strategies for both pharmacological and nutritional interventions (5).

Human health is affected by many factors. Diet and inherited genes play an important role. Food constituents,

• including secondary metabolites of fruits and vegetables, may
• interact directly with DNA via methylation and changes in expression profiles (mRNA, proteins)
• which results in metabolite content changes.

Many studies have shown that

• food constituents may affect human health and
• the exact knowledge of genotypes and food constituent interactions with
• both genes and proteins may delay or prevent the onset of diseases.

Many high throughput methods have been employed to get some insight into the whole process and several examples of successful research, namely in the field of genomics and transcriptomics, exist. Studies on epigenetics and RNome significance have been launched. Proteomics and metabolomics need to encompass large numbers of experiments and linked data. Due to the nature of the proteins, as well as due to the properties of various metabolites, experimental approaches require the use of

• comprehensive high throughput methods and a sufficiency of analysed tissue or body fluids (6).

New experimental tools that investigate gene function at the subcellular, cellular, organ, organismal, and ecosystem level need to be developed. New bioinformatics tools to analyze and extract meaning

• from increasingly systems-based datasets will need to be developed.

These will require, in part, creation of entirely new tools. An important and revolutionary aspect of “The 2010 Project”  is that it implicitly endorses

• the allocation of resources to attempts to assign function to genes that have no known function.

This represents a significant departure from the common practice of defining and justifying a scientific goal based on the biological phenomena. The rationale for endorsing this radical change is that

• for the first time it is feasible to envision a whole-systems approach to gene and protein function.

This whole-systems approach promises to be orders of magnitude more efficient than the conventional approach (7).

The Institute of Medicine recently convened a workshop to review the state of the various domains of nutritional genomics research and policy and to provide guidance for further development and translation of this knowledge into nutrition practice and policy (8). Nutritional genomics holds the promise to revolutionize both clinical and public health nutrition practice and facilitate the establishment of

(a) genome-informed nutrient and food-based dietary guidelines for disease prevention and healthful aging,

(b) individualized medical nutrition therapy for disease management, and

(c) better targeted public health nutrition interventions (including micronutrient fortification and supplementation) that

• maximize benefit and minimize adverse outcomes within genetically diverse human populations.

As the field of nutritional genomics matures, which will include filling fundamental gaps in

• knowledge of nutrient-genome interactions in health and disease and
• demonstrating the potential benefits of customizing nutrition prescriptions based on genetics,
• registered dietitians will be faced with the opportunity of making genetically driven dietary recommendations aimed at improving human health.

The new era of nutrition research translates empirical knowledge to evidence-based molecular science (9). Modern nutrition research focuses on

• promoting health,
• preventing or delaying the onset of disease,
• optimizing performance, and
• assessing risk.

Personalized nutrition is a conceptual analogue to personalized medicine and means adapting food to individual needs. Nutrigenomics and nutrigenetics

• build the science foundation for understanding human variability in
• preferences, requirements, and responses to diet and
• may become the future tools for consumer assessment

motivated by personalized nutritional counseling for health maintenance and disease prevention.

The primary aim of ―omic‖ technologies is

• the non-targeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample.

By their nature, these technologies reveal unexpected properties of biological systems.

A second and more challenging aspect of ―omic‖ technologies is

• the refined analysis of quantitative dynamics in biological systems (10).

For metabolomics, gas and liquid chromatography coupled to mass spectrometry are well suited for coping with

• high sample numbers in reliable measurement times with respect to
• both technical accuracy and the identification and quantitation of small-molecular-weight metabolites.

This potential is a prerequisite for the analysis of dynamic systems. Thus, metabolomics is a key technology for systems biology.

In modern nutrition research, mass spectrometry has developed into a tool

• to assess health, sensory as well as quality and safety aspects of food.

In this review, we focus on health-related benefits of food components and, accordingly,

• on biomarkers of exposure (bioavailability) and bioefficacy.

Current nutrition research focuses on unraveling the link between

• dietary patterns,
• individual foods or
• food constituents and

the physiological effects at cellular, tissue and whole body level

• after acute and chronic uptake.

The bioavailability of bioactive food constituents as well as dose-effect correlations are key information to understand

• the impact of food on defined health outcomes.

Both strongly depend on appropriate analytical tools

• to identify and quantify minute amounts of individual compounds in highly complex matrices–food or biological fluids–and
• to monitor molecular changes in the body in a highly specific and sensitive manner.

Based on these requirements,

• mass spectrometry has become the analytical method of choice
• with broad applications throughout all areas of nutrition research (11).

Recent advances in high data-density analytical techniques offer unrivaled promise for improved medical diagnostics in the coming decade. Genomics, proteomics and metabonomics (as well as a whole slew of less well known ―omics‖ technologies) provide a detailed descriptor of each individual. Relating the large quantity of data on many different individuals to their current (and possibly even future) phenotype is a task not well suited to classical multivariate statistics. The datasets generated by ―omics‖ techniques very often violate the requirements for multiple regression. However, another statistical approach exists, which is already well established in areas such as medicinal chemistry and process control, but which is new to medical diagnostics, that can overcome these problems. This approach, called megavariate analysis (MVA),

• has the potential to revolutionise medical diagnostics in a broad range of diseases.

It opens up the possibility of expert systems that can diagnose the presence of many different diseases simultaneously, and

• even make exacting predictions about the future diseases an individual is likely to suffer from (12).

Cardiovascular diseases

Cardiovascular diseases are the leading cause of morbidity and mortality in Western countries. Although coronary thrombosis is the final event in acute coronary syndromes,

• there is increasing evidence that inflammation also plays a role in development of atherosclerosis and its clinical manifestations, such as
• myocardial infarction, stroke, and peripheral vascular disease.

The beneficial cardiovascular health effects of

• diets rich in fruits and vegetables are in part mediated by their flavanol content.

This concept is supported by findings from small-scale intervention studies with surrogate endpoints including

1. endothelium-dependent vasodilation,
2. blood pressure,
3. platelet function, and
4. glucose tolerance.

Mechanistically, short term effects on endothelium-dependent vasodilation

• following the consumption of flavanol-rich foods, as well as purified flavanols,
• have been linked to an increased nitric oxide bioactivity.

The critical biological target(s) for flavanols have yet to be identified (13), but we are beginning to see over the horizon.

Nutritional sciences

Nutrition sciences apply

1. transcriptomics,
2. proteomics and
3. metabolomics

to molecularly assess nutritional adaptations.

Transcriptomics can generate a

• holistic overview on molecular changes to dietary interventions.

Proteomics is most challenging because of the higher complexity of proteomes as compared to transcriptomes and metabolomes. However, it delivers

• not only markers but also
• targets of intervention, such as
• enzymes or transporters, and
• it is the platform of choice for discovering bioactive food proteins and peptides.

Metabolomics is a tool for metabolic characterization of individuals and

• can deliver metabolic endpoints possibly related to health or disease.

Omics in nutrition should be deployed in an integrated fashion to elucidate biomarkers

• for defining an individual’s susceptibility to diet in nutritional interventions and
• for assessing food ingredient efficacy (14).

The more elaborate tools offered by metabolomics opened the door to exploring an active role played by adipose tissue that is affected by diet, race, sex, and probably age and activity. When the multifactorial is brought into play, and the effect of changes in diet and activities studied we leave the study of metabolomics and enter the world of ―metabonomics‖. Adiponectin and adipokines arrive (15-22). We shall discuss ―adiposity‖ later.

Potential Applications of Metabolomics

Either individually or grouped as a profile, metabolites are detected by either

• nuclear magnetic resonance spectroscopy or mass spectrometry.

There is potential for a multitude of uses of metabolome research, including

1. the early detection and diagnosis of cancer and as
2. both a predictive and pharmacodynamic marker of drug effect.

However, the knowledge regarding metabolomics, its technical challenges, and clinical applications is unappreciated

• even though when used as a translational research tool,
• it can provide a link between the laboratory and clinic.

Precise numbers of human metabolites is unknown, with estimates ranging from the thousands to tens of thousands. Metabolomics is a term that encompasses several types of analyses, including

(a) metabolic fingerprinting, which measures a subset of the whole profile with little differentiation or quantitation of metabolites;

(b) metabolic profiling, the quantitative study of a group of metabolites, known or unknown, within or associated with a particular metabolic pathway; and

(c) target isotope-based analysis, which focuses on a particular segment of the metabolome by analyzing

• only a few selected metabolites that comprise a specific biochemical pathway.

Dynamic Construct of the –Omics

Dynamic Construct of the –Omics

Iron metabolism – Anemia

Hepcidin is a key hormone governing mammalian iron homeostasis and may be directly or indirectly involved in the development of most iron deficiency/overload and inflammation-induced anemia. The anemia of chronic disease (ACD) is characterized by macrophage iron retention induced by cytokines and hepcidin regulation. Hepcidin controls cellular iron efflux on binding to the iron export protein ferroportin. While patients present with both ACD and iron deficiency anemia (ACD/IDA), the latter results from chronic blood loss. Iron retention during inflammation occurs in macrophages and the spleen, but not in the liver. In ACD, serum hepcidin concentrations are elevated, which is related to reduced duodenal and macrophage expression of ferroportin. Individuals with ACD/IDA have significantly lower hepcidin levels than ACD subjects. ACD/IDA patients, in contrast to ACD subjects, were able to absorb dietary iron from the gut and to mobilize iron from macrophages. Hepcidin elevation may affect iron transport in ACD and ACD/IDA and it is more responsive to iron demand with IDA than to inflammation. Hepcidin determination may aid in selecting appropriate therapy for these patients (23).

There is correlation between serum hepcidin, iron and inflammatory indicators associated with anemia of chronic disease (ACD), ACD, ACD concomitant iron-deficiency anemia (ACD/IDA), pure IDA and acute inflammation (AcI) patients. Hepcidin levels in anemia types were statistically different, from high to low: ACD, AcI > ACD/IDA > the control > IDA. Serum ferritin levels were significantly increased in ACD and AcI patients but were decreased significantly in ACD/IDA and IDA. Elevated serum EPO concentrations were found in ACD, ACD/IDA and IDA patients but not in AcI patients and the controls. A positive correlation exists between hepcidin and IL-6 levels only in ACD/IDA, AcI and the control groups. A positive correlation between hepcidin and ferritin was marked in the control group, while a negative correlation between hepcidin and ferritin was noted in IDA. The significant negative correlation between hepcidin expression and reticulocyte count was marked in both ACD/IDA and IDA groups. If the hepcidin role in pathogenesis of ACD, ACD/IDA and IDA, it could be a potential marker for detection and differentiation of these anemias (24).

Cancer

Because cancer cells are known to possess a highly unique metabolic phenotype, development of specific biomarkers in oncology is possible and might be used in identifying fingerprints, profiles, or signatures to detect the presence of cancer, determine prognosis, and/or assess the pharmacodynamic effects of therapy (25).

HDM2, a negative regulator of the tumor suppressor p53, is over-expressed in many cancers that retain wild-type p53. Consequently, the effectiveness of chemotherapies that induce p53 might be limited, and inhibitors of the HDM2–p53 interaction are being sought as tumor-selective drugs. A binding site within HDM2 has been dentified which can be blocked with peptides inducing p53 transcriptional activity. A recent report demonstrates the principle using drug-like small molecules that target HDM2 (26).

Obesity, CRP, interleukins, and chronic inflammatory disease

Elevated CRP levels and clinically raised CRP levels were present in 27.6% and 6.7% of the population, respectively. Both overweight (body mass index [BMI], 25-29.9 kg/m2) and obese (BMI, 30 kg/m2) persons were more likely to have elevated CRP levels than their normal-weight counterparts (BMI, <25 kg/m2). After adjusting for potential confounders, the odds ratio (OR) for elevated CRP was 2.13 for obese men and 6.21 for obese women. In addition, BMI was associated with clinically raised CRP levels in women, with an OR of 4.76 (95% CI, 3.42-6.61) for obese women. Waist-to-hip ratio was positively associated with both elevated and clinically raised CRP levels, independent of BMI. Restricting the analyses to young adults (aged 17-39 years) and excluding smokers, persons with inflammatory disease, cardiovascular disease, or diabetes mellitus and estrogen users did not change the main findings (27).

A study of C-reactive protein and interleukin-6 with measures of obesity and of chronic infection as their putative determinants related levels of C-reactive protein and interleukin-6 to markers of the insulin resistance syndrome and of endothelial dysfunction. Levels of C-reactive protein were significantly related to those of interleukin-6 (r=0.37, P<0.0005) and tumor necrosis factor-a (r=0.46, P<0.0001), and concentrations of C-reactive protein were related to insulin resistance as calculated from the homoeostasis model and to markers of endothelial dysfunction (plasma levels of von Willebrand factor, tissue plasminogen activator, and cellular fibronectin). A mean standard deviation score of levels of acute phase markers correlated closely with a similar score of insulin resistance syndrome variables (r=0.59, P<0.00005) and the data suggested that adipose tissue is an important determinant of a low level, chronic inflammatory state as reflected by levels of interleukin-6, tumor necrosis factor-a, and C-reactive protein (28).

A number of other studies have indicated the inflammatory ties of visceral obesity to adipose tissue metabolic profiles, suggesting a role in ―metabolic syndrome‖. There is now a concept of altered liver metabolism in ―non-alcoholic‖ fatty liver disease (NAFLD) progressing from steatosis to steatohepatitis (NASH) (31,32).

These unifying concepts were incomprehensible 50 years ago. It was only known that insulin is anabolic and that insulin deficiency (or resistance) would have consequences in the point of entry into the citric acid cycle, which generates 16 ATPs. In fat catabolism, triglycerides are hydrolyzed to break them into fatty acids and glycerol. In the liver the glycerol can be converted into glucose via dihydroxyacetone phosphate and glyceraldehyde-3-phosphate by way of gluconeogenesis. In the case of this cycle there is a tie in with both catabolism and anabolism.

TCA_reactions

 http://www.newworldencyclopedia.org/entry/Image:TCA_reactions.gif

For bypass of the Pyruvate Kinase reaction of Glycolysis, cleavage of 2 ~P bonds is required. The free energy change associated with cleavage of one ~P bond of ATP is insufficient to drive synthesis of phosphoenolpyruvate (PEP), since PEP has a higher negative G of phosphate hydrolysis than ATP.

The two enzymes that catalyze the reactions for bypass of the Pyruvate Kinase reaction are the following:

(a) Pyruvate Carboxylase (Gluconeogenesis) catalyzes:

pyruvate + HCO3 + ATP — oxaloacetate + ADP + Pi

(b) PEP Carboxykinase (Gluconeogenesis) catalyzes:

oxaloacetate + GTP — phosphoenolpyruvate + GDP + CO2

The concept of anomalies in the pathways with respect to diabetes was sketchy then, and there was much to be filled in. This has been substantially done, and is by no means complete. However, one can see how this comes into play with diabetic ketoacidosis accompanied by gluconeogenesis and in severe injury or sepsis with peripheral proteolysis to provide gluconeogenic precursors. The reprioritization of liver synthetic processes is also brought into play with the conundrum of protein-energy malnutrition.

The picture began to be filled in with the improvements in technology that emerged at the end of the 1980s with the ability to profile tissue and body fluids by NMR and by MS. There was already a good inkling of a relationship of type 2 diabetes to major indicators of CVD (29,30). And a long suspected relationship between obesity and type 2 diabetes was evident. But how did it tie together?

End Stage Renal Disease and Cardiovascular Risk

Mortality is markedly elevated in patients with end-stage renal disease. The leading cause of death is cardiovascular disease.

As renal function declines,

• the prevalence of both malnutrition and cardiovascular disease increase.

Malnutrition and vascular disease correlate with the levels of

• markers of inflammation in patients treated with dialysis and in those not yet on dialysis.

The causes of inflammation are likely to be multifactorial. CRP levels are associated with cardio-vascular risk in the general population.

The changes in endothelial cell function,

• in plasma proteins, and
• in lpiids in inflammation

are likely to be atherogenic.

That cardiovascular risk is inversely correlated with serum cholesterol in dialysis patients, suggests that

• hyperlipidemia plays a minor role in the incidence of cardiovascular disease.

Hypoalbuminemia, ascribed to malnutrition, has been one of the most powerful risk factors that predict all-cause and cardiovascular mortality in dialysis patients. The presence of inflammation, as evidenced by increased levels of specific cytokines (interleukin-6 and tumor necrosis factor a) or acute-phase proteins (C-reactive protein and serum amyloid A), however, has been found to be associated with vascular disease in the general population as well as in dialysis patients. Patients have

• loss of muscle mass and changes in plasma composition—decreases in serum albumin, prealbumin, and transferrin levels, also associated with malnutrition.

Inflammation alters

• lipoprotein structure and function as well as
• endothelial structure and function

to favor atherogenesis and increases

• the concentration of atherogenic proteins in serum.

In addition, proinflammatory compounds, such as

• advanced glycation end products, accumulate in renal failure, and
• defense mechanisms against oxidative injury are reduced,

contributing to inflammation and to its effect on the vascular endothelium (33,34).

Endogenous copper can play an important role in postischemic reperfusion injury, a condition associated with endothelial cell activation and increased interleukin 8 (IL-8) production. Excessive endothelial IL-8 secreted during trauma, major surgery, and sepsis may contribute to the development of systemic inflammatory response syndrome (SIRS), adult respiratory distress syndrome (ARDS), and multiple organ failure (MOF). No previous reports have indicated that copper has a direct role in stimulating human endothelial IL-8 secretion. Copper did not stimulate secretion of other cytokines. Cu(II) appeared to be the primary copper ion responsible for the observed increase in IL-8 because a specific high-affinity Cu(II)-binding peptide, d-Asp-d-Ala-d-Hisd-Lys (d-DAHK), completely abolished this effect in a dose-dependent manner. These results suggest that Cu(II) may induce endothelial IL-8 by a mechanism independent of known Cu(I) generation of reactive oxygen species (35).

Blood coagulation plays a key role among numerous mediating systems that are activated in inflammation. Receptors of the PAR family serve as sensors of serine proteinases of the blood clotting system in the target cells involved in inflammation. Activation of PAR_1 by thrombin and of PAR_2 by factor Xa leads to a rapid expression and exposure on the membrane of endothelial cells of both adhesive proteins that mediate an acute inflammatory reaction and of the tissue factor that initiates the blood coagulation cascade. Other receptors that can modulate responses of the cells activated by proteinases through PAR receptors are also involved in the association of coagulation and inflammation together with the receptors of the PAR family. The presence of PAR receptors on mast cells is responsible for their reactivity to thrombin and factor Xa , essential to the inflammation and blood clotting processes (36).

The understanding of regulation of the inflammatory process in chronic inflammatory diseases is advancing.

Evidence consistently indicates that T-cells play a key role in initiating and perpetuating inflammation, not only via the production of soluble mediators but also via cell/cell contact interactions with a variety of cell types through membrane receptors and their ligands. Signalling through CD40 and CD40 ligand is a versatile pathway that is potently involved in all these processes. Many inflammatory genes relevant to atherosclerosis are influenced by the transcriptional regulator nuclear factor κ B (NFκB). In these events T-cells become activated by dendritic cells or inflammatory cytokines, and these T-cells activate, in turn, monocytes / macrophages, endothelial cells, smooth muscle cells and fibroblasts to produce pro-inflammatory cytokines, chemokines, the coagulation cascade in vivo, and finally matrix metalloproteinases, responsible for tissue destruction. Moreover, CD40 ligand at inflammatory sites stimulates fibroblasts and tissue monocyte/macrophage production of VEGF, leading to angiogenesis, which promotes and maintains the chronic inflammatory process.

NFκB plays a pivotal role in co-ordinating the expression of genes involved in the immune and inflammatory response, evoking tumor necrosis factor α (TNFα), chemokines such as monocyte chemoattractant protein-1 (MCP-1) and interleukin (IL)-8, matrix metalloproteinase enzymes (MMP), and genes involved in cell survival. A complex array of mechanisms, including T cell activation, leukocyte extravasation, tissue factor expression, MMP expression and activation, as well induction of cytokines and chemokines, implicated in atherosclerosis, are regulated by NFκB.

Expression of NFκB in the atherosclerotic milieu may have a number of potentially harmful consequences. IL-1 activates NFκB upregulating expression of MMP-1, -3, and -9. Oxidized LDL increases macrophage MMP-9, associated with increased nuclear binding of NFκB and AP-1. Expression of tissue factor, initiating the coagulation cascade, is regulated by NFκB. In atherosclerotic plaque cells, tissue factor antigen and activity were inhibited following over-expression of IκBα and dominant-negative IKK-2, but not by dominant negative IKK-1 or NIK. Tis supports the concept that activation of the ―canonical‖ pathway upregulates pro-thrombotic mediators involved in disease. Many of the cytokines and chemokines which have been detected in human atherosclerotic plaques are also regulated by NFκB. Over-expression of IκBα inhibits release of TNFα, IL-1, IL-6, and IL-8 in macrophages stimulated with LPS and CD40 ligand (CD40L). This report describes how NFκB activation upregulates major pro-inflammatory and pro-thrombotic mediators of atherosclerosis (37-41).

This review is both focused and comprehensive. The details of evolving methods are avoided in order to build the argument that a very rapid expansion of discovery has been evolving depicting disease, disease mechanisms, disease associations, metabolic biomarkers, study of effects of diet and diet modification, and opportunities for targeted drug development. The extent of future success will depend on the duration and strength of the developed interventions, and possibly the avoidance of dead end interventions that are unexpectedly bypassed. I anticipate the prospects for the interplay between genomics, metabolomics, metabonomics, and personalized medicine may be realized for several of the most common conditions worldwide within a few decades (42-44).

References

1. Trujillo E, Davis C, Milner J. Nutrigenomics, proteomics, metabolomics, and the practice of dietetics. J Am Diet Assoc. 2006;106(3):403-13.
2. Kussmann M, Raymond F, Affolter M. OMICS-driven biomarker discovery in nutrition and health. J Biotechnol. 2006;124(4):758-87.
3. (Zeisel SH. Nutrigenomics and metabolomics will change clinical nutrition and public health practice: insights from studies on dietary requirements for choline. Am J Clin Nutr. 2007;86(3):542-8.
4. García-Cañas V, Simó C, León C, Cifuentes A. Advances in Nutrigenomics research: novel and future analytical approaches to investigate the biological activity of natural compounds and food functions. J Pharm Biomed Anal. 2010;51(2):290-304.
5. Kussmann M, Blum S. OMICS-derived targets for inflammatory gut disorders: opportunities for the development of nutrition related biomarkers. Endocr Metab Immune Disord Drug Targets. 2007;7(4):271-87.
6. Ovesná J, Slabý O, Toussaint O, Kodícek M, et al. High throughput ‘omics’ approaches to assess the effects of phytochemicals in human health studies. Br J Nutr. 2008;99 E Suppl 1:ES127-34.
7. Workshop Report: ―The 2010 Project‖. Chory J, Ecker JR, Briggs S, et al. A Blueprint for Understanding How Plants Are Built and How to Improve Them. Plant Physiology 2000;123:423–425, http://www.plantphysiol.org.
8. Stover PJ, Caudill MA. Genetic and epigenetic contributions to human nutrition and health: managing genome-diet interactions. J Am Diet Assoc. 2008 Sep;108(9):1480-7.
9. Kussmann M, Panchaud A, Affolter M.. Proteomics in nutrition: status quo and outlook for biomarkers and bioactives. J Proteome Res. 201;9(10):4876-87.
10. Wolfram Weckwerth. Metabolomics in Systems Biology. Annual Review of Plant Biology 2003; 54: 669-689.
11. Kussmann M, Affolter M, Nagy K, Holst B, Fay LB. Mass spectrometry in nutrition: understanding dietary health effects at the molecular level. Mass Spectrom Rev. 2007;26(6):727-50.
12. Grainger DJ. Megavariate Statistics meets High Data-density Analytical Methods: The Future of Medical Diagnostics? IRTL Reviews 2003;1:1-6.
13. Heiss; C, Keen CL, Kelm M. Flavanols and Cardiovascular Disease Prevention. European Heart Journal 2010;31(21):2583-2592.
14. Kussmann M, Rezzi S, Daniel H. Profiling techniques in nutrition and health research. Curr Opin Biotechnol. 2008;19 (2):83-99.
15. Ohashi N, Ito C, Fujikawa R, Yamamoto H, et al. The impact of visceral adipose tissue and high-molecular weight adiponectin on cardia-ankle vascular index in asymptomatic Japanese subjects. Metabolism 2009; 58:1023-9. [CAVI and VAT and HMW adiponectin levels];

6. Zha JM, Di WJ, Zhu T, Xie T, et al. Comparison of gene transcription between subcutaneous and visceral adipose tissue in chinese adults. Endocr J 2009;56:934-44. [TLR4 signaling, 11 beta-HSD1 and GR levels in VAT];
7. Albert L, Girola A, Gilardini L, Conti A, et al. Type 2 diabetes and metabolic syndrome are associated with increased expression of 11 beta-hydroxysteroid dehydrogenase 1 in obese subjects. Int J Obesity (Lond) 2007;31:1826-31;
8. Fabbrini E, Markos F, Mohammed BS, Pietka T, et al. Intrahepatic fat, not visceral fat, is linked with metabolic complications of obesity. PNAS 2009;106:15430-5;
9. Tong J, Boyko EJ, Utzschneider KM, McNeely MJ, et al. Intraabdominal fat accumulation predicts the development of the metabolic syndrome in non-diabetic Japanese-Americans. Diabetologia 2007;50:1156-60;
10. Kim K, Valentine RJ, Shin Y, Gong K. Association of visceral adiposity and exercise participation with C- reactive protein, insulin resistance, and endothelial dysfunction in Korean healthy adults. Metabolism 2008;57:1181-9. [(VAT-EC exhibits a marked angiogenic and proinflammatory state];
11. Villaret A, Galitzky J, Decaunes P, Exteve D, et al. Adipose tisue endothelial cells from obese human subjects: differences among depots in angiogenic, metabolic, and inflammatory gene expression and cellular senescence. Diabetes 2010;59:2755-63;
12. van Dijk -, Feskens EJ, Bos MB, Hoelen DW, et al. A saturated fatty acid-rich diet induces an obesity-linked proinflammatory gene expression profile in adipose tissue of subjects at risk of metabolic syndrome. Am J Clin Nutr 2009;90:1656-64.[MUFA in LDL lowering].
13. Theurl I, Aigner E, Theurl M, Nairz M, et al. Regulation of iron homeostasis in anemia of chronic disease and iron deficiency anemia: diagnostic and therapeutic implications. Blood. 2009;113(21):5277-86
14. Cheng PP, Jiao XY, Wang XH, Lin JH, Cai YM. Hepcidin expression in anemia of chronic disease and concomitant iron-deficiency anemia. Clin Exp Med. 2010 May 25. [Epub ahead of print].
15. Spratlin JL, Serkova NJ, and Eckhardt SG. Clinical Applications of Metabolomics in Oncology: A Review. Clin Cancer Res. 2009 ;15; 15(2): 431–440.
16. Fischer PM, Lane DP. Small molecule inhibitors of thep53 suppressor HDM2: have protein-protein interactions come of age as drug targets? Trends in Pharm Sci 2004;25(7):343-346.
17. Visser M, Bouter LM, McQuillan GM, Wener HM. Elevated C-Reactive Protein Levels in Overweight and Obese Adults. JAMA. 1999;282:2131-2135.
18. Yudkin JS, Stehouwer CDA, Emeis JJ, Coppack SW. C-Reactive Protein in Healthy Subjects: Associations With Obesity, Insulin Resistance, and Endothelial Dysfunction : A Potential Role for Cytokines Originating From Adipose Tissue? Arterioscler. Thromb. Vasc. Biol. 1999; 19:972-978.
19. Visvikis-Siest S, Siest G. The STANISLAS cohort: a 10-year followup of supposed healthy families. Gene-environment interactions, reference values and evaluation of biomarkers in prevention of cardiovascular diseases. Clin Chem Lab Med 2008;46:733-47.
20. Schmidt MI, Duncan BB. Diabesity: an inflammatory metabolic condition. Clin Chem Lab Med 2003;41:1120-1130.
21. Fenkci S, Rota S, Sabir N, Akdag B. Ultrasonographic and biochemical evaluation of visceral obesity in obese women with non-alcoholic fatty liver disease. Eur J Med Res 2007;12:68-73. (VAT, HOMA)
22. Lee JW, Lee HR, Shim JY, Im JA, et al. Viscerally obese women with normal body weight have greater brachial-ankle pulse wave velocity than non viscerally obese women with excessive body weight. Clin Endocrinol (Oxf) 2007;66:572-8. [visceral obesity – high trigly, high baPWV, greater SFA and thigh SFA].
23. Kaysen GE. The Microinflammatory State in Uremia: Causes and Potential Consequences. J Am Soc Nephrol 2001;12:1549–1557.
24. Kaysen GE. Role of Inflammation and Its Treatment in ESRD Patients. Blood Purif 2002;20:70–80.
25. Bar-Or D, Thomas GW, Yukl RL, Rael LT, et al. Copper stimulates the synthesis and release of interleukin-8 in human endothelial cells: a possible early role in systemic inflammatory responses. Shock 2003;20(2):154–158.
26. Dugina TN, Kiseleva EV, Chistov IV, Umarova BA, and Strukova SM. Receptors of the PAR Family as a Link between Blood Coagulation and Inflammation. Biochemistry (Moscow), 2002; 67(1):65-74. [Translated from Biokhimiya 2002;67(1):77-87].
27. Monaco C, Andreakos E, Kiriakidis S, Feldmann M, and and Ewa Paleolog. T-Cell-Mediated Signalling in Immune, Inflammatory and Angiogenic Processes: The Cascade of Events Leading to Inflammatory Diseases. Current Drug Targets – Inflammation & Allergy, 2004, 3, 35-42.
28. Monaco C, Grosjean J, and Paleolog E. The role of the NFκB pathway in atherosclerosis. [E-mail: e.paleolog@imperial.ac.uk]
29. Libby P, Ridker PM, and Maseri A. Inflammation and atherosclerosis. Circulation 2002;105:1135-43.
30. Karin M, Yamamoto Y, Wang QM. The IKK NF-kappa B system: a treasure trove for drug development. Nat Rev Drug Discov 2004;3:17-26.
31. Karin M, Ben-Neriah Y. Phosphorylation meets ubiquitination: the control of NF-[kappa]B activity. Annu Rev Immunol 2000;18:621-63.
32. Lee DY, Bowen BP, and Northen TR. Mass spectrometry–based metabolomics, analysis of metabolite-protein interactions, and imaging. BioTechniques 2010;49:557-565.
33. Faca V, Krasnoselsky A, and Hanash S. Innovative proteomic approaches for cancer biomarker discove.
34. Sharp, P, and MIT faculty. ‘Convergence’ offers potential for revolutionary advance in biomedicine. The Third Revolution: Convergence of the Life Sciences, Physical Sciences and Engineering. White paper. Reported in Biotechnology Jan 5, 2011. [Convergence is a new paradigm that can yield critical advances in a broad array of sectors]

Read Full Post »