New research has developed a computational biology tool, based on multi-level network analysis, to achieve an integrated vision of multiple sclerosis. It is one of the first studies to date that employs multiomics – the simultaneous analysis of data from very different scales, covering everything from genes to the whole organism.

MS symptoms vary among patients, but the most common range from vision problems, asthenia, difficulty walking and keeping balance, to numbness or weakness in the arms and legs. All of them can appear and disappear, or last over time. 

A study by an international research team, led by the Department of Medicine and Life Sciences at Pompeu Fabra University, in collaboration with Hospital del Mar, Hospital Clínic, Charité – Medical University of Berlin, and the universities of Oslo and Genoahas, conducted a multilevel network analysis of multiomic data (genomic, phosphoproteomic, and cytomic), brain and retinal images, and clinical data of 328 patients with MS and 90 healthy subjects. 

The findings revealed a correlation between the protein MK03 – previously linked to MS – with the total count of T cells, the thickness of the layer of retinal nerve fibers, and the timed gait test, which measures the time it takes a patient to walk 7.5 meters as quickly as possible. 

Although the size of the study has not allowed validating the use of this correlation as a biomarker to diagnose and possibly treat MS, it has provided an integrated view of this complex system and revealed the relationship between four biological scales: proteins, cells, tissues, and behavior.

The study was published in the journal PLOS Computational Biology.