Editorial: Real Nutritional Genomics

By Len Monheit

For several years now, we’ve been hearing scientific visionaries tell us of the promise of nutritional genomics (nutrigenomics or nutragenomics) , explaining that we’ll be able to consume an individualized set of components, derived from an assessment of our genetic makeup, and designed to have maximum health benefit as these components interact with our bodies on a molecular level. In one person’s mind, this might involve a gene scanning device, a printout, an assessment against a nutrient bank, and an output that reads like a personalized diet. In another environment, one would get classified as a ‘nutritional ‘x’ where ‘x’ indicates, in grouped terms, the type of profile you might have, and hence the type of diet and supplementation regime recommended for ‘your’ optimal health. Both of these concepts have been discussed for years now, and the emerging science and understanding of both gene expression and the impact of nutrition at a molecular level, make these interesting approaches for further research.

The concept (and impact) of personalized nutrition was brought home to me a couple years ago, when a nutrigenomics researcher I was scheduled to introduce at a conference, described to me the fact that something in his genetic makeup meant that consuming omega-3’s, for him, seemed to correlate to a higher level of LDL, and so, again for him, avoiding omega-3s was a requirement for him effectively managing his cholesterol. He went on to predict that optimal research in the future should theoretically move to lowest possible significant sample size, as the variability in genetic makeup of the research population made any large number of subjects impossible to analyze in certain experiments as the variability would lead inevitably to inconclusive results. Theoretically, he suggested, ‘n’ should be ‘1’, since as soon as you got larger than ‘1’, your risk of variability would more than offset your ability to show significance.

Let’s take a step back for a second.

One of the hang-ups regarding any commercial discussion about nutrigenomics has always been the economic feasibility, and hence the business potential and fundamentally, business model to support such a program. Tied to this proposition was the ethical dialogue about genetic information and access to it, potential for misuse, and an attitude in many cases of “let the authorities worry about it and when the time comes, we’ll see what opportunities….” While many companies have been exploring nutritional genomics as a cornerstone of their value proposition, few, if any, (in a process akin to the frequent gap between science and marketing) have been successful, so far, in tying it to their balance sheet effectively. Perhaps there are signs that this is about to change.

Research that hit the headlines last week caught my eye. With a headline "Vitamin E Could Help 40% of Diabetics Ward off Heart Attacks…" the release went on to describe that 40 percent of individuals with diabetes carry a certain gene, and when these gene specific individuals were given 400 IU of Vitamin E daily, they had 50 percent fewer heart attacks, strokes and related deaths than a placebo group. Doing simple math, if the study had been performed on a general population (perhaps 40 percent with the gene), and in the general population, Vitamin E supplementation had no effect, we’d have 40% of the study group showing a 50 percent reduction, 60 percent of the study group showing no effect, overall, more than halving the study response and therefore limiting its potential significance. (I’m sure I’m restating the obvious here).

In effect, what has been determined, is that a genetic marker identifies a group predisposed genetically to benefit from the regime of supplementation, with an obvious impact on the success of the study. One wonders how much other ‘marginally’ successful (or even inconclusive) research in the past, might have been more conclusive if the subjects had a genetic predisposition to benefit from the study regime. Does the identification of such markers and their impact make research more viable?

The ability to optimize the success of a study program ultimately has significant consequences for the overall cost and ROI of research. Perhaps those companies involved in the supplements, functional food, medical food and related sectors, should be interacting with the biotech and genetics research communities (if they are not already doing so), looking for relationships that might enhance the viability of their research programs.

Perhaps this then, is where the potential of nutrigenomics will unfold and manifest, and deliver more efficacious products, not to a general population, but to a much more targeted group. And perhaps, in this environment, we can better understand the scientific inconsistencies when one study, perhaps in an unconscious skewing of genetic predisposition, shows significant results, and another shows marginal or non-significant benefit on a general population.

Fundamentally and frankly, anything that provides more value or a chance at higher ROI for each research dollar spent is a good thing for our industry. Also fundamentally, the more we understand about the behavior of our products in populations and population subgroups, the better we are able to handle the challenges not only of research inconsistencies, but also the queries of regulators – regulators who frequently track the science relating to nutrition, as well as developments in pharmaceuticals, biotechnology, genetics, and other areas.

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