The 'black box' of personalised medicine?

14 June 2016

Scientists based in Switzerland have developed a tool which they say can fill the ‘black box’ that lies between the genome and proteome, allowing them to understand better what role particular proteins play in disease.

Evidence that personalised medicine improves patient outcomes continues to grow, yet our ability to customise medical interventions for individuals suffering from metabolic disorders is still limited. Researchers working at EPFL and ETHZ have developed a tool which uses a transomics (more than one 'omics technology) approach to find results which could not be achieved through singular methods.

The study titled: Systems proteomics of liver mitochondria function details the process by which they developed their technique to characterise the individual metabolic differences between over 400 mice, all who shared the same two ancestors. 

By combining protein and metabolite data obtained through a new mass spectrometry technique with DNA and RNA sequencing, the team was able to construct “a comprehensive view on the overall variances induced by genetics and environment regarding metabolic activity”. In particular, they were able to establish multiple links between genotype and phenotype that could not be identified by an individual approach.

The authors believe that the future of personalised medicine lies in the combination of next generation omic data sets with genomic and transcriptomic data, rather than replacing them entirely. This combination “can fill in blind spots and assist in defining more detailed metabolic pathways”. The team is now looking at which drugs can be used to treat metabolic disorders through a personalised approach.

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