In a recent review of 38 clinical studies on polyphenols and the gut microbiome, my CSU colleagues and I found that researchers often did a good job measuring changes in the gut microbiome, blood chemistry and health outcomes for humans, but paid far less attention to confounding variation that might derive from the foods themselves. None of the studies used untargeted methods that capture a broader range of food chemicals, and less than half used targeted approaches that measure a handful of known compounds. When studying the health parameters of humans, researchers relied on more advanced tools, yet the findings were inconsistent. One likely reason is that the variability of the foods—the apples, teas or berries used in these studies—wasn’t fully captured. Without that information, it’s hard to explain why results differ from one study to another.
These differences matter. Nutrition science is moving toward precision nutrition, tailoring dietary recommendations to individuals or groups based on their unique biology. But if we don’t know the detailed chemical composition of the foods we study, our conclusions about diet and health risk being incomplete or misleading. The possible solution to this is called foodomics – the comprehensive chemical profiling of foods. Much of this research fits under the umbrella of what has come to be called the Periodic Table of Food. The findings from foodomics research can be included in clinical trials to control for hidden variability, discover new bioactive compounds and make nutrition research more reproducible. Right now, clinical trials are good at analyzing people, but incomplete because they do not analyze foods.
