Powerful new tool could provide personalized medicine Closer

Oct 2, 2016 | | Say something

A powerful tool is being developed by scientists at EPFL ETHZ to explore and determine the biological differences between individuals, overcoming an obstacle important for personalized medicine.

 New Powerful Tool May Help Bring Personalized Medicine Closer
effective new tool could help bring personalized medicine Closer

One of the biggest obstacles to successful treatment metabolic disorders such as diabetes, obesity, fatty liver, etc., is the variation in how patients respond to medication. The key to this variation is in the inherent biological differences between individuals, which can not be genetically explained. At the same time, this variation makes it very difficult to develop “standard” treatments for certain diseases. In an unprecedented move, EPFL and ETHZ scientists have developed a strategy that can define and explain the metabolic differences between individuals, paving the way for essentially medical precision. The work, which also highlights significant problems with case studies based on animal drugs, has been published in Science .

“In an unprecedented move, scientists have developed a strategy that can define and explain the metabolic differences between individuals, essentially paving the way for precision medicine. “


We are learning more and more that medical interventions may be more successful when tailored specific profile of each patient. The problem is that the definition of that profile is extremely difficult, as it involves information on the genome, protein, fat person, and all kinds of other layers of biology that make up the tissues and body. And so far, the only differences that have been taking serious account are those found among genes.

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This is what Johan Auwerx laboratories at EPFL and Ruedi Aebersold at ETH Zurich set out to solve with his recently published study. Looking at 40 different strains of mice, researchers successfully connected the variation between genomes of individuals to the variation between their proteomes – all whole protein. Thus, there was a big jump in the profile of the biology of an individual.

“There is a black box between the genome of a patient and their disease,” says Johan Auwerx, whose laboratory the study of the genome is handled. “What we have done here is to find a way to fill the black box by obtaining information about the proteome of the patient.”

“It’s much more complex to measure the set of proteins that sequenced the entire genome,” says Wu Yibo, principal co-author of the study. Scientists used data mouse proteins, obtained from a new technique of mass spectrometry Aebersold group developed, known as SWATH-MS. This is a technique that combines the advantages of mass spectrometry high performance with high reproducibility and consistency. In short, it is able to identify thousands of different proteins in hundreds of samples much faster and more accurately than conventional techniques, allowing researchers to measure the concentrations of a broad spectrum of liver proteins in mice.

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The researchers measured a total of 2,600 different proteins from tissue samples of 40 strains of mice, all of which came from the same two predecessors, meaning they were genetically related. “We wanted to keep the simple genetics in order to observe differences in the impact of the environment (diet) on the proteome, other layers of biology, and predisposition to diseases,” says Auwerx.

The mice were divided into groups representing each of the 40 strains, and the groups were fed a high-fat diet – essentially junk food – or a healthy, low fat diet. For a couple of weeks, scientists charted the physiological data from mice, and tested how fast they could gain weight in junk food diet and lose weight through exercise. Despite its genetic resemblance, mice with high-fat diet showed varied responses to diet and exercise. For example, some developed metabolic disorders such as fatty liver, while others did not.

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The researchers then combined the physiological data with data from genome, proteome and transcriptome her, which is essentially its full set of RNA – another biological “layer” in the black box. Through this combination, the scientists were able to better understand the role several proteins play when metabolize fat and energy production from it.

“Like mouse strains in this study, each patient with a disease is genetically different,” says Ruedi Aebersold. “The approach used in the cohort mouse can now be applied one by one in the research of human diseases, particularly for personalized medicine”. The SWATH-MS approach is now ready for use in human cohort studies, as researchers in his group have produces a corresponding database for thousands of human proteins.

“The goal here is to be able to customize medical intervention for each patient based on individual biological composition, the ‘black box’,” says Auwerx. In this vein, the group is specific drugs that can be used more efficiently with this approach for the treatment of metabolic disorders now.

Source: Eurekalert

This article was originally published on medindia.net

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