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
- flow cytometry
- optical coherence tomography
- network analysis
- diabetic retinopathy
- molecular dynamics
- wastewater treatment
- end stage renal disease
- signaling pathway
- monte carlo
- high throughput
- optic nerve
- oxidative stress
- electronic health record
- induced apoptosis
- rna seq
- newly diagnosed
- mass spectrometry
- ejection fraction
- protein protein
- ms ms
- big data
- peritoneal dialysis
- prognostic factors
- binding protein
- health information
- squamous cell carcinoma
- healthcare
- cell cycle arrest
- clinical trial
- small molecule
- neuropathic pain
- working memory
- double blind
- single molecule
- cell death
- transcription factor
- patient reported outcomes
- sentinel lymph node
- data analysis
- artificial intelligence
- cross sectional
- brain injury
- patient reported
- nk cells
- locally advanced