Nutritional genomics

DR.

CHIARA MURGIA: The way we respond to food depends on our genetic background. And this is something that, as a professional, I’ve seen in practise for a long time. For example, some metabolic conditions depend on genetic mutations that affect the ability to utilise certain nutrients of food. One well-described example is the metabolic genetic condition phenylketonuria, a metabolic disease that is caused by a genetic mutation in the gene that codes for the enzyme phenylalanine hydroxylase. The carrier of this mutation are unable to metabolise the essential amino acid phenylalanine. So this is a case in which a perfectly good and essential component of our diet become a poisoning component for the carrier of this genetic mutation.

Another well-described example of this is lactose intolerance, the inability to digest the sugar contained in milk, the lactose. It is what is more frequent in the human population. Now we know that this is a situation that’s far more common than we used to think, and that the majority of the human population hasn’t got the ability to digest lactose past infancy. And this is caused by polymorphism in the regulatory region of the gene that codes for the enzyme lactase. What we have now with the completion of the Human Genome Project is the improvement of the technology that allow the sequencing of nucleic acids, DNA and RNA, and the computational technology to analyse the big data that come from the sequencing.

And now we are in a position to identify gene variants that are linked to chronic conditions associated with diet and lifestyle. In particular, technologies that led to identifying a large number of gene variants associated with chronic conditions are called genome-wide association studies. These types of studies, genome-wide association studies, compare two groups of population, the one with a condition, chronic disease type 2 diabetes, obesity, cardiovascular condition, and a group of healthy population, and investigate what gene variants are associated with the disease group. And so we now have a very large number of loci that are associated with those chronic conditions.

It’s also important to consider that genome-wide association study, that by definition association studies do not identify the causal link between the gene variant and the disease. The way the experiment is done doesn’t calculate the contribution that each polymorphism provides to the disease. Very often, the contribution of each of these polymorphism, what we call effect size, can be quite small. A good example of this is the identification of a few polymorphs in the gene FTO associated with obesity. FTo increases the risk of developing obesity of 1.7 times. So it’s still a very small contribution that needs to be put into the context of all the other polymorphs of that particular individual, together with lifestyle, including diet and exercise.

So while doctors and dietitians have seen the effect of genetic background on the response of food and dietetic pattern, now we are in the position of understanding the mechanism behind this response. And we can foresee that in the near future we’ll be able to apply this knowledge and translate it into practice, allowing a more targeted and personalised approach to the advice by a health professional.