The factors that determine whether remyelination fails or succeeds in multiple sclerosis remain unknown. By grafting lymphocytes from patients into demyelinated lesions in mice, El Behi, Sanson et al. show that lymphocytes differ in their ability to induce remyelination. Unravelling the basis of this heterogeneity reveals prerequisites for efficient myelin repair.

Multiple sclerosis (MS) is a neuro-inflammatory disease for which the pathogenesis remains largely unclear. Lysophosphatidic acid (LPA) is an endogenous phospholipid that is involved in multiple immune cell functions and is dysregulated in MS. Its receptor LPA1 is expressed in macrophages and regulates their activation, which is of interest due to the role of macrophage activation in MS in both destruction and repair.In this study, we studied the viable Malaga variant of LPA1-null mutation as well as pharmaceutical inhibition of LPA1 in mice with experimental autoimmune encephalomyelitis (EAE), a model of MS. LPA1 expression was also analyzed in both wild-type EAE mice and MS patient immune cells. The effect of LPA and LPA1 on macrophage activation was studied in human monocyte-derived macrophages.We show that lack of LPA1 activity induces a milder clinical course in EAE, and that Lpar1 expression in peripheral blood mononuclear cells (PBMCs) correlates with onset of relapses and severity in wild-type EAE mice. We see the same over-expression in PBMCs from MS patients during relapse compared to progressive forms of the disease, and in monocyte-derived macrophages after exposure to pro-inflammatory stimuli. In addition, LPA induced a proinflammatory-like response in macrophages through LPA1, providing a plausible way in which LPA and LPA1 dysregulation can lead to the inflammation seen in MS.These data show a new mechanism of LPA signaling in the pathogenesis of MS, prompting further research into its use as a therapeutic target biomarker.

Identifying the nodes able to drive the state of a network is crucial to understand, and eventually control, biological systems. Despite recent advances, such identification remains difficult because of the huge number of equivalent controllable configurations, even in relatively simple networks. Based on the evidence that in many applications it is essential to test the ability of individual nodes to control a specific target subset, we develop a fast and principled method to identify controllable driver-target configurations in sparse and directed networks. We demonstrate our approach on simulated networks and experimental gene networks to characterize macrophage dysregulation in human subjects with multiple sclerosis.

In multiple sclerosis (MS), immune cells invade the central nervous system and destroy myelin. Macrophages contribute to demyelination and myelin repair, and their role in each process depends on their ability to acquire specific phenotypes in response to external signals. Here, we assess whether defects in MS patient macrophage responses may lead to increased inflammation or lack of neuro-regenerative effects.To test this hypothesis, CD14+CD16- monocytes from MS patients and healthy controls were activated in vitro to obtain homeostatic-like, pro-inflammatory and pro-regenerative macrophages. Myelin phagocytic capacity and surface molecule expression of CD14, CD16 and HLA-DR were evaluated with flow cytometry. In parallel, macrophages were assessed through RNA sequencing and metabolomics.We observed that MS patient monocytes ex vivo recapitulate their preferential activation toward a CD16+ phenotype, a subset of pro-inflammatory cells present in MS lesions. Even in the absence of pro-inflammatory stimuli, MS patient macrophages exhibit a pro-inflammatory transcriptomic profile with higher levels of cytokine/chemokine suggesting increased recruitment capacities. Interestingly, MS patient macrophages exhibit a specific metabolic signature with a mitochondrial energy metabolism blockage resulting in a shift from oxidative phosphorylation to glycolysis. Furthermore, we observe a failure to up-regulate apoptosis effector genes in the pro inflammatory state suggesting a longer-lived pro-inflammatory macrophage population.Our results highlight an intrinsic defect of MS patient macrophages that provide evidence of innate immune cell memory in MS.

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Multiple sclerosis (MS) is a neuro-inflammatory disease for which the pathogenesis remains largely unclear. Lysophosphatidic acid (LPA) is an endogenous phospholipid that is involved in multiple immune cell functions and is dysregulated in MS. Its receptor LPA1 is expressed in macrophages and regulates their activation, which is of interest due to the role of macrophage activation in MS in both destruction and repair.In this study, we studied the viable Malaga variant of LPA1-null mutation as well as pharmaceutical inhibition of LPA1 in mice with experimental autoimmune encephalomyelitis (EAE), a model of MS. LPA1 expression was also analyzed in both wild-type EAE mice and MS patient immune cells. The effect of LPA and LPA1 on macrophage activation was studied in human monocyte-derived macrophages.We show that lack of LPA1 activity induces a milder clinical course in EAE, and that Lpar1 expression in peripheral blood mononuclear cells (PBMCs) correlates with onset of relapses and severity in wild-type EAE mice. We see the same over-expression in PBMCs from MS patients during relapse compared to progressive forms of the disease, and in monocyte-derived macrophages after exposure to pro-inflammatory stimuli. In addition, LPA induced a proinflammatory-like response in macrophages through LPA1, providing a plausible way in which LPA and LPA1 dysregulation can lead to the inflammation seen in MS.These data show a new mechanism of LPA signaling in the pathogenesis of MS, prompting further research into its use as a therapeutic target biomarker.

The polygenic and multi-cellular nature of multiple sclerosis (MS) pathology necessitates cell-type-specific molecular studies in order to improve our understanding of the mechanisms underlying immune cell dysfunction in MS. Here, using a large dataset of 1075 transcriptomes from 209 MS and healthy individuals, we assessed MS-associated transcriptional changes in 6 cell-type-states implicated in MS: naive and memory CD4+ T cells and CD14+ monocytes purified from peripheral blood, each in primary (unstimulated) and in vitro stimulated states. Our analyses identified shared and distinct changes in individual genes, biological pathways, and co-expressed gene modules in MS T cells and monocytes. We found evidence of replication for the association between MS and three (two T cell and one monocyte) co-expressed gene modules in independent data from peripheral blood mononuclear cells (PBMC) and monocyte-derived macrophages. Our computational drug screen identified glucocorticoid receptor agonists as the top therapeutic compounds for reversing the replicated MS-associated T cell modules. This finding was further supported by the significant enrichment of these modules for literature-driven glucocorticoid response gene sets, in addition to results from our in vitro experiment on gene expression effects of the glucocorticoid receptor agonist dexamethasone in MS PBMC. In summary, our study provides cell-type-specific information on genes and pathways perturbed in MS T cells and monocytes, and suggests a novel explanation for the therapeutic effects of glucocorticoids in relation to MS T cell pathology.

Identifying the nodes that have the potential to influence the state of a network is a relevant question for many complex interconnected systems.Despite recent advances in network controllability, the univocal identification of the driver nodes remains difficult in practice because of the combinatorial and numerical complexity associated with existence of a huge number of equivalent controllable walks, even in relatively small networks. However, in many applications it is often essential to test the ability of an individual node to control a specific target subset of the network. In biological networks, this might provide precious information on how single genes regulate the expression of specific groups of molecules in the cell.Taking into account these constraints, we propose an optimized heuristic based on the Kalman rank condition to quantify the centrality of a node as the number of target nodes it can control. By introducing a hierarchy among the nodes in the target set, and performing a step-wise research, we ensure for sparse and directed networks the identification of a controllable driver-target configuration in a significantly reduced space and time complexity.We show how the method works for simple network configurations, then we use it to characterize the inflammatory pathways in molecular gene networks associated with macrophage dysfunction in patients with multiple sclerosis. Results indicate that the targeted secreted molecules can in general be controlled by a large number of driver nodes (51%) involved in different cell functions, i.e. sensing, signaling and transcription.However, during the inflammatory response only a moderate fraction of all the possible driver-target pairs are significantly coactivated, as measured by gene expression data obtained from human blood samples. Notably, they differ between multiple sclerosis patients and healthy controls, and we find that this is related to the presence of dysregulated genes along the controllable walks.Our method, that we name step-wise target controllability, represents a practical solution to identify controllable driver-target configurations in directed complex networks and test their relevance from a functional perspective.