When the Human Genome Project wrapped in 2003, we assumed this ginormous data set would provide the much needed parts-list to fill in the blanks of human health and disease. But in the last 10 years it’s become exceedingly clear that things are just not that simple. Yes, our genes are obviously more than a little important in determining who we are, but a lot of other factors are, too. You probably wouldn’t be surprised to hear that what we eat is a big one.
Health sciences professor Katherine Tucker has dedicated her life to understanding how nutrition affects us and, in particular, how our nutrition can be culturally determined based on our diets. Although indirectly, our genetics are connected to our culture as well. Now don’t get too worked up, I’m not saying there’s a gene for faith or anything like that. But there are plenty of examples of certain gene mutations being more prevalent among some populations than others. For example, a mutation to the BRCA1 gene, which is associated with increased risk for breast and ovarian cancers, is more common among white women than Asian women. A mutation to the ABCA7 gene seems to be more often associated with Alzheimer’s disease among older African-Americans than whites.
Tucker is part of a growing field called nutrigenomics, in which researchers are studying how the nutrients we consume affect gene expression. What does that mean exactly? Here’s one example: There are three possible variants of a gene called APOE, one is associated with higher levels of low-density lipoprotein cholesterol (LDL-C, the “bad” kind), one is associated with moderate levels of LDL-C, and one is associated with lower levels. But throw a bunch of high-fat food into the mix and the intermediate variant becomes a bigger predictor of high LDL-C. So, just because you have a gene associated with some physical characteristic, what you eat may change things completely.
It seems if we can nail down the sequence of the 3 billion nucleotides that make up the human genome, we should have no problem dealing with a little Vitamin A. But it turns out this is a ridiculously complex question to study. There’s a number of reasons for that, and one, as you may be guessing, is the great variability in the way we eat.
Say you want to figure out how zinc intake affects gene expression. You might first assume that the real hairiness of this challenge would be looking at zinc’s interaction with all 20K genes, but due to some serious technical advances, this is actually the “easy” part.
“Because of the specificity of most gene x nutrient interactions,” write Tucker and her colleagues in a recently published paper, “valid data are needed for nutrient intakes at the individual level.”
This basically means that the genetic effects of your zinc intake might not look the same as those of my zinc intake. In order to get meaningful information about how an individual’s diet affects his or her risk for different diseases, for example, you need to look at many, many, many….many different individuals.
Okay, sure fine. If we can look at 20K genes then 20K people should be easy enough. True…and, well, not true. You can ask as many people as you want how much rice they eat, knowing that the whole grain kind is high in zinc. But rice means different things in different cultures.
To some, rice means sticky white rice cooked with a little salt. Others eat a ton of butter or oil with their rice, so now you have to think about how fat will interact as well.
There are three main ways nutritional epidemiologists like Tucker ask people about their diets. They can ask what you ate yesterday, but that’s not usually a good indicator because you may have eaten a huge slice of cake yesterday, something you only do once a year on your birthday. They can ask people to keep a record for a week or more, but this is time consuming so people don’t love doing it, not to mention the fact that keeping a diet journal is known to affect the way one eats. The third way is to administer a “food frequency questionnaire,” wherein you answer a whole bunch of questions about how often you eat different foods. FFQs, as they’re called, have to be specifically tailored to different cultures in order to get accurate nutritional data, again: rice means different things in different cultures. So if you’re comparing a bunch of FFQ results across populations, the correlations with genetic factors and outcomes are probably very skewed.
So, as Tucker and her co-authors repeatedly point out, the need for better, more effective dietary assessment methods is critically needed before anyone can reliably consider how nutrition and genetics are connected. We know that they are, of course, but to do anything real with that knowledge there needs to be a heck of a lot more standardization among the protocols, which will require some creative thinking on the part of the people performing these studies.
Tucker has already begun collaborating with researchers in Northeastern’s Personal Health Informatics program to think about using technology to streamline the process. As becomes clearer every day, crowdsourcing data through the Internet and our smartphones is an incredibly efficient way of collecting data. You just have to ask the right questions.