Tantalizing Data and Ample Buzz for Personalized Nutrition

Metabolomics ASN Title SlideIt was quite a splash. Near simultaneous presentations in Baltimore and San Francisco. For the last two days, Tim Spector and colleagues have been busy presenting data from an ambitious study of personalized nutrition. They had a late breaking poster at the American Diabetes Association meeting. Also, they made two presentations at American Society of Nutrition meeting.

But most important, the data was strong enough to create quite a buzz. Spector found tremendous variations between individuals in the metabolic response to identical meals. What’s more, genetics only explained about half of that variation. Identical twins had quite different responses.

These researchers and their startup – ZOE – are “stalking the dream of personalized nutrition,” said the New York Times.

Precision Nutrition

Ask any dietitian. Food and nutrition are intensely personal. People have their likes and dislikes, of course. Some people might do very well with a low-carb, high-fat diet. For others, it’s intolerable. But these differences are also biological.

Spector et al found a wide variation in how even identical twins responded to the very same foods. Blood sugar, insulin, and other responses were very different in different people. Genetics explained only 53 percent of the glycemic response. Spector explained:

The sheer scale and detail of our scientific project is such that for the first time we can explore tremendously rich nutrition data at the level of an individual. Our results surprisingly show that we are all different in our response to such a basic input as food. It was a real shock to see that even identical twins have such different responses.

Implications for Dietary Guidelines

Of course, this raises some important questions for people writing dietary guidelines. When individual needs can vary so greatly, what’s the best approach? Commenting on this work, Professor Jennie Brand-Miller said that one-size-fits-all guidelines are starting to look a bit antiquated. “I think the PREDICT study is led by a great team and will be a mine of valuable information,” she said.

Caution: Early Days

However, she and others also advised caution. Indiana University’s Andrew Brown told us:

This work is moving in the right direction of creating models to predict responses. Two challenges lie ahead. First, predictions are reflections of the past, and need to be validated again. Second, these are acute settings. As an analogy, it’s usually not appropriate to extrapolate obesity outcomes from single meal food challenges, so we should not make disease outcome conclusions about these data.

Bottom line, this work holds a lot of promise. But all this buzz sets up opportunities to exploit gullible people with a concept that sounds great without proven benefits. We’ve said it before. If you want precision, personalized nutrition, your best bet today is to see a skilled RDN.

Click here for the poster at the ADA meeting and here for Spector’s presentation at ASN. Click here for more from the New York Times. Finally, for more on applying multiple omics technologies, click here.

Buzz, photograph © Henry T. McLin / flickr

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June 11, 2019

One Response to “Tantalizing Data and Ample Buzz for Personalized Nutrition”

  1. June 12, 2019 at 7:36 am, Mary-Jo said:

    Thanks for all the links, Ted and also for the endorsement for RDNs. It’s interesting stuff going on, but even if we can streamline how people can get tested and informed of what diet combo and recommendations would work best for them, how much more likely would people follow the information, as Mr. Caulfield already pointed out re: following best diet recommendations already out there (general vs. precise, though). i would be curious to see the Predict researchers replicate their protocol for their same subjects with a time lapse to see if their responses were the same. My experience in providing individualized diet and nutrition plans for people is that even the same person has different effects of dietary modifications at different times in their lives — say, a low-fat diet working well in their 30s and a lower carb working better in their 50’s. I do like, however, that additional measures are being encouraged to evaluate a person’s metabolic and nutritional health, other than just weight on a scale or BMI.