Scientists from EPFL and ETHZ have developed a powerful tool for exploring and determining the inherent biological differences between individuals, which overcomes a major hurdle for personalized medicine.
One of the biggest obstacles in successfully treating metabolic disorders such as diabetes, obesity, fatty liver etc, is the variation in the way patients respond to medication. The key to this variation lies in the inherent biological differences between individuals, which cannot all be explained genetically. At the same time, this variation makes it very difficult to develop “standard” treatments for certain diseases. In a groundbreaking initiative, EPFL and ETHZ scientists have developed a strategy that can define and explain metabolic differences between individuals, essentially paving the way for precision medicine. The work, which also highlights significant issues with animal-based drug studies, is published in Science.
We are increasingly learning that medical interventions can be more successful when they are tailored to the specific profile of the individual patient. The problem is that defining that profile is extremely difficult, as it involves information on the person’s genome, proteins, fats, and all sorts of other layers of biology that make up their tissues and body. And so far, the only differences that we have been seriously taking into account are those found between genes.
This is what the labs of Johan Auwerx at EPFL and Ruedi Aebersold at ETH Zurich set out to solve with their recently published study. Looking at 40 different mice strains, the researchers successfully connected the variation between individuals’ genomes to the variation between their proteomes — their full set of proteins. In this way, they took a giant leap in profiling the biology of a particular individual.
“There is a black box between a patient’s genome and their disease,” says Johan Auwerx, whose lab handled the genome side of the study. “What we have done here is find a way to fill the black box by obtaining information on the patient’s proteome.”