Stepwise target controllability identifies dysregulations of macrophage networks in multiple sclerosis.
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ABSTRACT:
SUBMITTER: Bassignana G
PROVIDER: S-EPMC8233109 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Multiple sclerosis is an inflammatory neurodegenerative disease of the central nervous system (CNS) and the most frequent cause of non-traumatic disability in adults in the Western world. Currently, several drugs have been approved for the treatment of multiple sclerosis. While the newer drugs are more effective, they have less favourable safety profiles. Thus, there is a need to identify new targets for effective and safe therapies, particularly in patients with progressive disease for whom no treatments are available. One such target is granulocyte-macrophage colony-stimulating factor (GM-CSF) or its receptor. In this article we review data on the potential role of GM-CSF and GM-CSF inhibition in MS. We discuss the expression and function of GM-CSF and its receptor in the CNS, as well as data from animal studies and clinical trials in MS.
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Project description:Multiple sclerosis is an autoimmune disease of the CNS in which both genetic and environmental factors are involved. Genome-wide association studies revealed more than 200 risk loci, most of which harbour genes primarily expressed in immune cells. However, whether genetic differences are translated into cell-specific gene expression profiles and to what extent these are altered in patients with multiple sclerosis are still open questions in the field. To assess cell type-specific gene expression in a large cohort of patients with multiple sclerosis, we sequenced the whole transcriptome of fluorescence-activated cell sorted T cells (CD4+ and CD8+) and CD14+ monocytes from treatment-naive patients with multiple sclerosis (n = 106) and healthy subjects (n = 22). We identified 479 differentially expressed genes in CD4+ T cells, 435 in monocytes, and 54 in CD8+ T cells. Importantly, in CD4+ T cells, we discovered upregulated transcripts from the NAE1 gene, a critical subunit of the NEDD8 activating enzyme, which activates the neddylation pathway, a post-translational modification analogous to ubiquitination. Finally, we demonstrated that inhibition of NEDD8 activating enzyme using the specific inhibitor pevonedistat (MLN4924) significantly ameliorated disease severity in murine experimental autoimmune encephalomyelitis. Our findings provide novel insights into multiple sclerosis-associated gene regulation unravelling neddylation as a crucial pathway in multiple sclerosis pathogenesis with implications for the development of tailored disease-modifying agents.
| S-EPMC8491073 | biostudies-literature
Project description: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.
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Project description:Controlling complex networks is of paramount importance in science and engineering. Despite the recent development of structural controllability theory, we continue to lack a framework to control undirected complex networks, especially given link weights. Here we introduce an exact controllability paradigm based on the maximum multiplicity to identify the minimum set of driver nodes required to achieve full control of networks with arbitrary structures and link-weight distributions. The framework reproduces the structural controllability of directed networks characterized by structural matrices. We explore the controllability of a large number of real and model networks, finding that dense networks with identical weights are difficult to be controlled. An efficient and accurate tool is offered to assess the controllability of large sparse and dense networks. The exact controllability framework enables a comprehensive understanding of the impact of network properties on controllability, a fundamental problem towards our ultimate control of complex systems.
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Project description:Recently, the focus of network research shifted to network controllability, prompting us to determine proteins that are important for the control of the underlying interaction webs. In particular, we determined minimum dominating sets of proteins (MDSets) in human and yeast protein interaction networks. Such groups of proteins were defined as optimized subsets where each non-MDSet protein can be reached by an interaction from an MDSet protein. Notably, we found that MDSet proteins were enriched with essential, cancer-related, and virus-targeted genes. Their central position allowed MDSet proteins to connect protein complexes and to have a higher impact on network resilience than hub proteins. As for their involvement in regulatory functions, MDSet proteins were enriched with transcription factors and protein kinases and were significantly involved in bottleneck interactions, regulatory links, phosphorylation events, and genetic interactions.
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Project description:BACKGROUND:Multiple sclerosis (MS) is a chronic disease of the central nervous system (CNS). Myeloid lineage cells (microglia and macrophages) may participate in the pathogenic mechanisms leading to MS. CD33 is a transmembrane receptor, mainly expressed by myeloid lineage cells. CD33 rs3865444 is a promoter variant previously associated with Alzheimer's disease, whose role in MS remains obscure. OBJECTIVE:To assess the role of CD33 rs3865444 in MS risk. METHODS:We genotyped 1396 patients with MS and 400 healthy controls for the presence of the CD33 rs3865444 variant. Odds ratios (ORs) with the respective 95% confidence intervals (CIs), were calculated with the SNPStats software, assuming five genetic models (co-dominant, dominant, recessive, over-dominant, and log-additive), with the G allele as the reference allele. The value of 0.05 was set as the threshold for statistical significance. RESULTS:CD33 rs3865444 was associated with MS risk in the dominant (GG vs. GT + TT; OR (95% C.I.) = 0.79 (0.63-0.99), p = 0.041) and the over-dominant (GG + TT vs. GT; OR (95% C.I.) = 0.77 (0.61-0.97), p = 0.03) modes of inheritance. Given that the GG genotype was more frequent and the GT genotype was less frequent in MS patients compared to controls-while the observed frequency of the TT genotype did not differ between the two groups-the observed difference in MS risk may be stemming from either the GG (as a risk factor) or the GT (as a protective factor) genotype of CD33 rs3865444. CONCLUSIONS:Our preliminary results suggest a possible contribution of CD33 rs3865444 to MS. Therefore, larger multiethnic studies should be conducted, investigating the role of CD33 rs3865444 in MS.
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Project description:This study examined the roles of microglia and monocytes in myelin destruction in patients with early multiple sclerosis (MS). Twenty-two cases were studied; the clinical duration was <9 weeks in 10 cases. Twenty myeloid cell subtypes or categories were identified including 2 cell types not known previously to occur in demyelinating diseases. Commencing myelin breakdown in plaques and in perivascular and subpial tissues occurred in the immediate presence of infiltrating monocytes and was effected by a homogeneous population of IgG-positive Fc receptor-bearing early phagocytes interacting with abnormal myelin. Oligodendrocyte apoptosis was observed in intact myelinated tissue bordering areas of active demyelination. Capillaries in the cerebral cortex plugged by large numbers of monocytes were common in acute cases of MS and in a patient with a neuromyelitis optica variant and extreme systemic recruitment of monocytes. In an MS patient with progressive disease, microglial nodules centered on MHC-II-positive capillaries plugged by monocytes were present in the cerebral cortex. This constitutes a new gray matter lesion in MS.
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Project description:In this paper, we study the problem of controlling complex networks with unilateral controls, i.e., controls which can assume only positive or negative values, not both. Given a complex network represented by the adjacency matrix A, an algorithm is developed that constructs an input matrix B such that the resulting system (A, B) is controllable with a near minimal number of unilateral control inputs. This is made possible by a reformulation of classical conditions for controllability that casts the minimal unilateral input selection problem into well known optimization problems. We identify network properties that make unilateral controllability relatively easy to achieve as compared to unrestricted controllability. The analysis of the network topology for instance allows us to establish theoretical bounds on the minimal number of controls required. For various categories of random networks as well as for a number of real-world networks these lower bounds are often achieved by our heuristics.
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Project description:The Statistical Physics of Complex Networks has recently provided new theoretical tools for policy makers. Here we extend the notion of network controllability to detect the financial institutions, i.e. the drivers, that are most crucial to the functioning of an interbank market. The system we investigate is a paradigmatic case study for complex networks since it undergoes dramatic structural changes over time and links among nodes can be observed at several time scales. We find a scale-free decay of the fraction of drivers with increasing time resolution, implying that policies have to be adjusted to the time scales in order to be effective. Moreover, drivers are often not the most highly connected "hub" institutions, nor the largest lenders, contrary to the results of other studies. Our findings contribute quantitative indicators which can support regulators in developing more effective supervision and intervention policies.
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