Multiscale networks in multiple sclerosis

by Keith E. Kennedy, Nicole Kerlero de Rosbo, Antonio Uccelli, Maria Cellerino, Federico Ivaldi, Paola Contini, Raffaele De Palma, Hanne F. Harbo, Tone Berge, Steffan D. Bos, Einar A. H øgestøl, Synne Brune-Ingebretsen, Sigrid A. de Rodez Benavent, Friedemann Paul, Alexander U. Brandt, Priscilla Bäcker-Koduah, Janina Behrens, Joseph Kuchling, Susanna Asseyer, Michael Scheel, Claudia Chien, Hanna Zimmermann, Seyedamirhosein Motamedi, Josef Kauer-Bonin, Julio Saez-Rodriguez, Melan ie Rinas, Leonidas G. Alexopoulos, Magi Andorra, Sara Llufriu, Albert Saiz, Yolanda Blanco, Eloy Martinez-Heras, Elisabeth Solana, Irene Pulido-Valdeolivas, Elena H. Martinez-Lapiscina, Jordi Garcia-Ojalvo, Pablo Villoslada 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 prot...
Source: PLoS Computational Biology - Category: Biology Authors: Source Type: research