At a seminar given on May 21th at the Center of Integrative Genomics of the University of Lausanne, Switzerland, James Kaput, Head of the Clinical Translation Unit at the Nestlé Institute of Health Sciences, talked about research strategies for personalized nutrition.
He said the basic assumptions for designing research strategies in the 20th century, particularly for studying genotype-environment interactions, are now obsolete and no longer adapted to systemic biology-oriented 21th century science. If we wish to account for individual genetic variations, the multi-factorial nature of most metabolic diseases, as well as the complexity of the “environment” (food, toxins, drugs, teratogens, etc.), we can no longer conduct population studies the way it has been done so far.
The “old” strategy assigned study subjects to pre-defined groups such as “normal weight” (BMI<25) and “overweight” (BMI>25)) and averaged measured responses as the group average. This, said the speaker, can no longer be done because it does not take into account individual variation. The measurements are only one frame of a movie, which cannot assess the dynamic nature of human physiology.
In his view of a “new” strategy, J. Kaput highlighted the importance of quantifying each individual before doing any classification, that is, tracking the individuals’ nutrition, health, genetics, economics, etc. Sorting individuals into response groups appears more complex that the usual randomization of individuals before quantification, but can be achieved with the help of bioinformatics using multi-platform analysis of the genome, transcriptome, protein, and metabolite profiles.
Although still underdeveloped due to genetic variability, food diversity, and inability to measure all aspects of individual physiology, the novel research strategy carries the advantage of providing population as well as individual level data and may lead to new insight into nutrition and health questions..
In an interview for ScienceWatch.com, he stated : “While nutrigenomic research provides the technologies and concepts, we need to develop novel research strategies for developing individual risk factors, while taking into account gene variants, epistatic interactions resulting from differing genetic ancestries, and influences of different environments—quite a challenging task“.