Multiscale networks in multiple sclerosis.
Keith E KennedyNicole Kerlero de RosboAntonio UccelliMaria CellerinoFederico IvaldiPaola ContiniRaffaele De PalmaHanne F HarboTone BergeSteffan D BosEinar August HøgestølSynne Brune-IngebretsenSigrid A de Rodez BenaventFriedemann PaulAlexander U BrandtPriscilla Bäcker-KoduahJanina BehrensJoseph KuchlingSusanna AsseyerMichael ScheelClaudia ChienHanna ZimmermannSeyedamirhosein MotamediJosef Kauer-BoninJulio Saez-RodriguezMelanie RinasLeonidas G AlexopoulosMagi AndorraSara LlufriuAlbert SaizYolanda BlancoEloy Martinez-HerasElisabeth SolanaIrene Pulido-ValdeolivasElena H Martinez-LapiscinaJordi García-OjalvoPablo VillosladaPublished in: PLoS computational biology (2024)
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.
Keyphrases
- multiple sclerosis
- single cell
- white matter
- optical coherence tomography
- flow cytometry
- network analysis
- diabetic retinopathy
- molecular dynamics
- end stage renal disease
- monte carlo
- signaling pathway
- rna seq
- wastewater treatment
- ejection fraction
- electronic health record
- mass spectrometry
- oxidative stress
- newly diagnosed
- big data
- high throughput
- chronic kidney disease
- high resolution
- pi k akt
- gene expression
- peritoneal dialysis
- cell cycle arrest
- health information
- ms ms
- protein protein
- prognostic factors
- squamous cell carcinoma
- radiation therapy
- artificial intelligence
- cell proliferation
- healthcare
- brain injury
- data analysis
- transcription factor
- photodynamic therapy
- spinal cord injury
- subarachnoid hemorrhage
- peripheral nerve
- lymph node
- sentinel lymph node
- small molecule
- deep learning
- stress induced
- protein kinase