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Multiscale networks in multiple sclerosis

Authors :
Keith E Kennedy
Nicole Kerlero de Rosbo
Antonio Uccelli
Maria Cellerino
Federico Ivaldi
Paola Contini
Raffaele De Palma
Hanne H Harbo
Tone Berge
Steffan D Bos
Einar A Høgestøl
Synne Brune-Ingebretsen
Sigrid de Rodez Benavent
Friedemann Paul
Alexander U Brandt
Priscilla Bäcker-Koduah
Janina Behrens
Joseph Kuchling
Susana E Asseyer
Michael Scheel
Claudia Chien
Hanna Zimmermann
Seyedamirhosein Motamedi
Josef Kauer-Bonin
Julio Saez-Rodriguez
Melani Rinas
Leonidas 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
Publication Year :
2023
Publisher :
Cold Spring Harbor Laboratory, 2023.

Abstract

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. 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, and Boolean simulations identified paths within and among all layers. The path more commonly found from the boolean simulations connects MP2K, with Th17 cells, the retinal nerve fiber layer (RNFL) thickness and the age related MS severity score (ARMSS). Combinations of several proteins (HSPB1, MP2K1, SR6, KS6B1, SRC, MK03, LCK and STAT6)) and immune cells (Th17, Th1 non-classic, CD8, CD8 Treg, CD56 neg, and B memory) were part of the paths explaining the clinical phenotype. Specific paths identified were subsequently analyzed by flow cytometry at the single-cell level.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........fcf3681416d1cefc941a19340fb82553