People used to be satisfi ed to live in a black and white world. TV was in black and white, so were photographs. But when color exploded off the screen and off the Kodachromes for the fi rst time, that’s when the revolution started. And so goes the story of genomics and proteomics, which were once the black and white species, respectively, in the world of omics. Then, somehow, these omics got manufactured wrong, at least in a few batches. Other components seemed to have accidentally fallen into the batch mixture, and what came out was something with more vivid colors. The result: other, more exotic omics like nutrigenomics, toxicogenomics, and metabolomics were born. And life was never thesame again in the world of omics.
Picture yourself in this world, where integration of diverse scientifi c disciplines is key, and applications of such integrations seem limitless. So whether you want to study how nutrients impact gene expression, how genes can help to customize diet, or you just want to know how a chemical will impact human health or the environment, genomic and proteomic tools willbe your friends. So what color is your omic?
Nutrigenomics
We have all had a cholesterol test. If the results are less than desirable, say 250 mg/dL (average normal max. 200 mg/dL), the doctor will usually tell the patient to lose weight, just cut down the fat or cholesterol in their diet, or prescribe some a cholesterol- or fat-lowering drug. But there might come a day when a doctor might say that a “250” cholesterol reading is healthy for some, but not for others. Welcome to the land of nutrigenomics, where researchers who choose this color hope one day that doctors will tailor diet to an individual’s genetic profi leand maybe, just maybe, prolong human life.
For a more exact defi nition...“What they call nutrigenomics is how nutrients interact with the genome and how an individual responds to certain nutrients based on their genetic profi le,” says Ravi Subbiah, PhD, professor of internal medicine at the University of Cincinnati, Cincinnati, Ohio. Nutrigenomics has offi cially been around since 2003 when researchers coined the term todistinguish it from pharmacogenomics.
Nutrigenomics is not as a clear-cut a fi eld as pharmacogenomics, says Subbiah, because the diet–genome interactions are still too complicated for people to learn readily. But it’s getting there, thanks to some purposeful genomics research. “I would say in the last fi ve years people have begun to discover genetic mutations that are amenable to dietary manipulation.” For example, he says, some people absorb more cholesterol in their gutthan others. The extent of cholesterol absorptionis genetically determined–polymorphic variation in regulatory genes controls the amount of cholesterol absorbed. It follows then that individuals with polymorphisms causing increased absorption must watch their dietary intake of cholesterol. This has led to a trend in which nutrigenomic researchers are beginning to identify a number of signifi cant mutationsrelated to dietary absorption.
But nutrigenomics is not just all about genes. “I don’t consider nutrigenomics strictly DNA despite the fact the name implies that it is just DNA work,” says Jim Kaput, PhD, assistant professor at the University of Illinois, Chicago. “A number of us in the fi eld have broadened the definition of nutrigenomics to consider any nutrient omic technology.” Because using any one omic (genomics, proteomics, or metabolomics) does not give the complete picture of nutrient–genome interaction, nutrigenomics integrates multiple omics approaches, including nutrigenetics (to understand how genetic polymorphisms affect an individual’s response to dietary components); transcriptomics (to understand how dietary components induce changes in gene expression);proteomics; and metabolomics.
“I think there are a lot of labs that use this integrative approach and try to put all of these different omics together,” says Cindy Davis, PhD, program director of the Nutritional Science Research Group at the National Cancer Institute, Rockville, Md. In her position, Davis reviews many grants for nutrigenomics research, and is, therefore, in charge of allocating National Institutes of Health (NIH) funding for such research. The reason to fund nutrigenomics research, she says, is that there have been a lot of inconsistencies in the epidemiologic studies linking diet and cancer, with some showing protective effects, some showing no effect, and still others showing detrimental effects. “What we are trying to understand is how an individual’s genetic background may determine whether or not they may benefi t from certain dietary modifi cations for cancer prevention.” NIH considers nutrigenomics an evolving area of research, providing funding to academic labs since the science’s inception in 2002-2003.
And the work is slowly moving into humans. For example, most of Kaput’s work has relied on studies in experimental animal strains, but he recently started work in humans. The human studies involve taking blood samples, looking at SNPs, transcriptomes, proteomes, and metabolites, and then matching those data to answers on a standard food frequency questionnaire corresponding to that sample. But until he can get the funding to put all of thisinformation together, the project is on hold.
Once researchers fi nd mutations that affect dietary absorption, the next obvious question is: What can an individual do about it? says Subbiah.“Can you go to the dietician or nutritionist in theclinic and have them tell you what to eat basedon your genomic profile?”
Nutrigenomics is already being applied in the nutriceuticals industry, which produces dietary products customized to fi t the needs of specifi c human populations based on race, gender, or a specific genetic polymorphism. And nutrigenomics is not just being applied to human health. Just ask Karl Dawson, PhD, director of worldwide research at Alltech Biotechnology Nicholasville, Ky. People are interested in how to best feed livestock animals (poultry, cattle, and swine) because they are grown for human consumption, says Dawson.“The idea is to look at gene expression patternsand use them to evaluate nutritional status,with the overall goal of evaluating nutritionalstrategies. In our case, we are interested inlooking at various supplementation feed andhow we might infl uence animal health at thegene expression level.”
Alltech has made a lot of startling discoveries about animal health. For example, they have discovered through DNA microarraydriven transcriptomics that selenium is a very important nutrient in the animal diet. “We are really looking to develop some specifi c tools that allow us to gauge nutritional status....it’s something we talk about a lot but don’t reallyunderstand yet.”
A greater understanding of the mission of nutrigenomics is sure to occur in the future. Kaput predicts nutrigenomics will roll through the clinic. “There are companies that are offering genetic tests that say: ‘here are your SNPs for 19 genes, now go eat more broccoli and you’ll be healthy.’ But what’s healthy for you may not be what’s healthy for me,” he says, “and I think most people in the fi eld would say the same because we just don’t have the data yet tosay this is how you should stay healthy.”
Metabolomics/lipidomics
As much as nutrigenomicians like to claim that diet directly impacts the behavior of the genome (and consequently health), the real impact of diet on overall health comes from the genome’s control over metabolism. Metabolites–the end-products of the activity of metabolic enzyme cascades–come in all shapes and sizes, and include everything from small basic precursors, such as diacyl glycerol, to largermolecules, such as hormones.
A subset of the metabolome is the lipidome, which is composed of the lipids found in a given biological fl uid, such as plasma. Basically, metabolomics and lipidomics use two core methods: mass spectrometry (MS)–which measures all ionizable, low-abundance metabolites in a sample–and nuclear magnetic resonance spectroscopy (NMR)–which can quantify allionizable, high-abundance metabolites.
“We use whatever will give us the qualitative and quantitative accuracy we need with a reasonable throughput,” says Bruce German, PhD, professor at the University of California, Davis. For fatty acids and triglycerides, German uses gas chromatography (GC) combined with fl ame ionization detection (FID). This method is more quantitatively accurate than mass spectrometry, he says. “The problem is you cannot identify every molecule in a sample.”
Although the idea of measuring all of the lipids in a biological sample, i.e., lipidomics, is not a new idea, it is a new idea to incorporate lipidomics into metabolomics–but still about five to six years old. In that time, however, there have been two schools of thought: the MS school and the NMR school. As divergent as they may seem, these two schools do have the same ultimate goal in mind, says German. That is, to be able to identify and quantify every singlemetabolite in a sample with absolute accuracy.
Metabolomics is still in the early stages of development, as are most of the omics technologies discussed in this article. “We are still in this phase of biomarker discovery, trying to fi nd proteins that are predictive of disease in the most complex proteome there is: human plasma,” says German, “and many studies don’t produce very much [conclusive] information because,simply, the technology is not there yet.”
Toxicogenomics Omics technologies are also helping researchers measure the toxic effects of chemicals on animal and humans. This is happening at the US Environmental Protection Agency (EPA). And a lot of it started with the introduction of The National Center of Computational Toxicology in Research Triangle Park, N.C. The center uses a whole variety of modern molecular tools including genomics, proteomics, and metabolomics, combined with computer processing power to understand how chemicals in the environment cause their effects in animaland humans.
“When the EPA protects human health based upon animal studies, what we look for in those studies are adverse events,” says Robert Kavlock, PhD, director of the center. “So if something causes cancer, that is obviously an adverse effect; but if something just causes a single gene to get turned on, then that’s not so clear.” According to Kavlock, the EPA is using gene expression data to set regulations on the use of certain chemicals in the workplace and in the environment. However, the EPA would not necessarily set a regulation on a chemical if only a single gene were turned on in response to exposure to that chemical, unless, of course, that the effects of turning it on are birth defects, or nervous system disorders, or cancer or whatever, he says.
Another researcher using toxicogenomics is Lyle Burgoon, PhD, visiting research associate at Michigan State University, East Lansing, Mich., and CEO of Toxicogenomic Informatics and Solutions, LLC, Lansing, Mich. Burgoon uses toxicogenomics to identify cross-species differences in toxicity following exposure to the same chemical. “We are looking for genes that are the same or different following exposure to a chemical and the kinetics of those changes,” says Burgoon.
Like the aforementioned omics technologies, toxicogenomics is an integrated approach. “One of the keys to toxicogenomics is to try to integrate data from previous work: cell-based assays, pathological specimens, and clinical chemistry,” says Burgoon. The fi eld has been growing since the term, toxicogenomics, was coined in 2001, albeit mostly in academia. “Industry does not know how to deal with the data coming from toxicogenomics.” So there is a movement now to determine whether toxicogenomics can identify toxicity of newly-developed drug compounds. “If you can kill a compound sooner in the development cycle though toxicogenomics, you can potentially save a company millions of dollars by allowing them to avoid wasteful clinical trials,” says Burgoon.
So whether you are a toxicologist, a nutritionist, or a biochemist, omics technologies have pervaded your world. Those who have embraced the technologies have taken full advantage of their high-throughput nature and bio-informational richness, and created small niches and subcategories of already exotic integrations. However, most of these integrations are only in their infancy and, thus, have a long way to go before the ambitions of their creators are fully realized. PA
Lipid Profile
