Multiscale networks in multiple sclerosis

PLoS Comput Biol. 2024 Feb 8;20(2):e1010980. doi: 10.1371/journal.pcbi.1010980. eCollection 2024 Feb.


Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. In fact, any phenotype for an organism is dictated by the interplay among these scales. We conducted a multilayer network analysis and deep phenotyping with multi-omics data (genomics, phosphoproteomics and cytomics), brain and retinal imaging, and clinical data, obtained from a multicenter prospective cohort of 328 patients and 90 healthy controls. Multilayer networks were constructed using mutual information for topological analysis, and Boolean simulations were constructed using Pearson correlation to identified paths within and among all layers. The path more commonly found from the Boolean simulations connects protein MK03, with total T cells, the thickness of the retinal nerve fiber layer (RNFL), and the walking speed. This path contains nodes involved in protein phosphorylation, glial cell differentiation, and regulation of stress-activated MAPK cascade, among others. Specific paths identified were subsequently analyzed by flow cytometry at the single-cell level. Combinations of several proteins (GSK3AB, HSBP1 or RS6) and immune cells (Th17, Th1 non-classic, CD8, CD8 Treg, CD56 neg, and B memory) were part of the paths explaining the clinical phenotype. The advantage of the path identified from the Boolean simulations is that it connects information about these known biological pathways with the layers at higher scales (retina damage and disability). Overall, the identified paths provide a means to connect the molecular aspects of MS with the overall phenotype.

Publication types

  • Multicenter Study

MeSH terms

  • Brain
  • Heat-Shock Proteins
  • Humans
  • Multiple Sclerosis*
  • Prospective Studies
  • Retina
  • Tomography, Optical Coherence / methods


  • HSBP1 protein, human
  • Heat-Shock Proteins

Grants and funding

This work was supported by the Spanish Ministry of Science and Innovation and FEDER, under project PID2021-127311NB-I00, the European Commission (Horizon 2020 Framework Programme, ERACOSYSMED ERA-Net program, Sys4MS project, id:43 to PV); Instituto de Salud Carlos III, Spain (AC1500052 to PV); the Italian Ministry of Health (WFR-PER-2013-02361136 to AU); the German Ministry of Science (Deutsches Teilprojekt B “Förderkennzeichen: 031L0083B to FP) and the Norwegian Research Council (project 257955 to HHH). J.G-O. was also supported by the Maria de Maeztu Programme for Units of Excellence in R&D (grant CEX2018-000792-M), and by the Generalitat de Catalunya (ICREA Academia programme). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.