Network analysis provides an integrated view of multiple sclerosis

An international research team has developed a computational biology tool, based on multi-level network analysis, to achieve an integrated vision of multiple sclerosis. This tool could be used to study other complex diseases such as types of dementia.

Multiple sclerosis is an autoimmune disease of unknown cause that occurs when the immune system attacks the brain and spinal cord. It is a complex disease, not always easy to diagnose, which covers a wide range of biological scales, ranging from genes and proteins to cells and tissues, including the entire organism.

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

The study was led by the Department of Medicine and Life Sciences (MELIS) ​​at Pompeu Fabra University, in collaboration with Hospital del Mar, Hospital Clínic, Charité-Medical University of Berlin and the universities of Oslo and Genoa. The study is published in PLoS Computational Biology.

Researchers conducted a multilevel network analysis of multiomics (genomic, phosphoproteomic, and cytomic), brain and retinal images, and clinical data from 328 multiple sclerosis patients and 90 healthy subjects. This is one of the first studies to date that simultaneously analyzes data from very different scales, covering everything from genes to the organism as a whole. Thus, the new tool allows researchers to understand the complexity of chronic diseases.

“In this study, we analyzed five levels at once: genes, proteins, cells, parts of the brain and behavior. The proximity of the elements of each level in each person determined the connection between the elements within of each level and between levels and “, thanks to Boolean dynamics, considering each element as active or inactive, and the introduction of disturbances in the system, we made the elements of the network oscillate”, explains Jordi Garcia- Ojalvo, professor of systems biology and director of the Dynamic Systems Department, Biology Laboratory of the Department of Medicine and Life Sciences of the UPF.

“Thus, we managed to identify which elements of the different levels are related to the biological level.”

“In complex diseases, as in society, many things are happening at the same time, and on several scales and over time. So, for humans, researchers and doctors, it is difficult to visualize them if “it is only by using these types of diseases. tools that allow us to discern and identify the linked elements”, explains Pablo Villoslada, associate professor at the Department of Medicine and Life Sciences of the UPF, director of the Neuroscience Program at the Hospital del Mar Research Institute and head of the Neurology Department at Hospital del Mar, who co-led the study with Garcia-Ojalvo.

Thanks to the enormous capacity of networks to simplify complex data, they managed to reveal the correlation between the MK03 protein, previously associated with multiple sclerosis, with the total number of T lymphocytes, cells of the immune system that help fight infections, the thickness of the retinal nerve fiber layer and the timed walk test, which measures the time it takes a patient to walk 7.5 meters as quickly as possible.

Although the scale of the study did not allow validation of the use of this correlation as a biomarker to diagnose and potentially treat multiple sclerosis, it provided an integrated view of this complex system and revealed the relationship between four biological scales: proteins, cells, tissues and behavior.

“In complex diseases, it is very difficult to have genetic biomarkers. They are often determined by several genes and there is a lot of “background noise”. And here we study sets of genes, proteins and phenotypes, and if they are related to each other, we have an indication of the existence of the disease,” adds Garcia-Ojalvo.

“With multiple sclerosis, we have to construct a puzzle whose appearance we can more or less guess. We are not completely in the dark, which is why we use systems biology, which tells us the relevant relationships between elements for the puzzle to be solved. coherent, adapted and we learn. And once we know how the disease works, we can figure out how to deal with it,” concludes Villoslada.

This tool based on the relationship between fundamental biology and applied medicine could be applied to the study of other complex diseases such as Alzheimer’s disease and other types of dementia.