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Although largely confined to the airways, SARS-CoV-2 infection has been associated with sensory abnormalities that manifest in both acute and chronic phenotypes. To gain insight on the molecular basis of these sensory abnormalities, we used the golden hamster model to characterize and compare the effects of infection with SARS-CoV-2 and influenza A virus (IAV) on the sensory nervous system. We detected SARS-CoV-2 transcripts but no infectious material in the cervical and thoracic spinal cord and dorsal root ganglia (DRGs) within the first 24 hours of intranasal virus infection. SARS-CoV-2–infected hamsters exhibited mechanical hypersensitivity that was milder but prolonged compared with that observed in IAV-infected hamsters. RNA sequencing analysis of thoracic DRGs 1 to 4 days after infection suggested perturbations in predominantly neuronal signaling in SARS-CoV-2–infected animals as opposed to type I interferon signaling in IAV-infected animals. Later, 31 days after infection, a neuropathic transcriptome emerged in thoracic DRGs from SARS-CoV-2–infected animals, which coincided with SARS-CoV-2–specific mechanical hypersensitivity. These data revealed potential targets for pain management, including the RNA binding protein ILF3, which was validated in murine pain models. This work elucidates transcriptomic signatures in the DRGs triggered by SARS-CoV-2 that may underlie both short- and long-term sensory abnormalities.

Background and ObjectivesTo report the clinical, biological, and imaging features and clinical course of a French cohort of patients with glial fibrillary acidic protein (GFAP) autoantibodies.MethodsWe retrospectively included all patients who tested positive for GFAP antibodies in the CSF by immunohistochemistry and confirmed by cell-based assay using cells expressing human GFAPα since 2017 from 2 French referral centers.ResultsWe identified 46 patients with GFAP antibodies. Median age at onset was 43 years, and 65% were men. Infectious prodromal symptoms were found in 82%. Other autoimmune diseases were found in 22% of patients, and coexisting neural autoantibodies in 11%. Tumors were present in 24%, and T-cell dysfunction in 23%. The most frequent presentation was subacute meningoencephalitis (85%), with cerebellar dysfunction in 57% of cases. Other clinical presentations included myelitis (30%) and visual (35%) and peripheral nervous system involvement (24%). MRI showed perivascular radial enhancement in 32%, periventricular T2 hyperintensity in 41%, brainstem involvement in 31%, leptomeningeal enhancement in 26%, and reversible splenial lesions in 4 cases. A total of 33 of 40 patients had a monophasic course, associated with a good outcome at last follow-up (Rankin Score ≤2: 89%), despite a severe clinical presentation. Adult and pediatric features are similar. Thirty-two patients were treated with immunotherapy. A total of 11/22 patients showed negative conversion of GFAP antibodies.DiscussionGFAP autoimmunity is mainly associated with acute/subacute meningoencephalomyelitis with prodromal symptoms, for which tumors and T-cell dysfunction are frequent triggers. The majority of patients followed a monophasic course with a good outcome.

Neuromyelitis optica (NMO) is an autoimmune demyelinating disease of the central nervous system characterized by the presence of autoantibodies (called NMO-IgG) targeting aquaporin-4. Aquaporin-4 is expressed at the perivascular foot processes of astrocytes, in the glia limitans, but also at the ependyma. Most studies have focused on studying the pathogenicity of NMO-IgG on astrocytes, and NMO is now considered an astrocytopathy. However, periependymal lesions are observed in NMO suggesting that ependymal cells could also be targeted by NMO-IgG. Ependymal cells regulate CSF-parenchyma molecular exchanges and CSF flow, and are a niche for sub-ventricular neural stem cells. Our aim was to examine the effect of antibodies from NMO patients on ependymal cells. We exposed two models, i.e. primary cultures of rat ependymal cells and explant cultures of rat lateral ventricular wall whole mounts, to purified IgG of NMO patients (NMO-IgG) for 24 hours. We then evaluated the treatment effect using immunolabelling, functional assays, ependymal flow analysis and bulk RNA sequencing. For each experiment, the effects were compared with those of purified IgG from a healthy donors and non-treated cells. We found that: (i) NMO-IgG induced aquaporin-4 agglomeration at the surface of ependymal cells and induced cell enlargement in comparison to controls. In parallel, it induced an increase in gap junction connexin-43 plaque size; (ii) NMO-IgG altered the orientation of ciliary basal bodies and functionally impaired cilia motility; (iii) NMO-IgG activated the proliferation of sub-ventricular neural stem cells; (iv) treatment with NMO-IgG up-regulated the expression of pro-inflammatory cytokines and chemokines in the transcriptomic analysis. Our study showed that NMO-IgG can trigger an early and specific reactive phenotype in ependymal cells, with functional alterations of intercellular communication and cilia, activation of sub-ventricular stem cell proliferation and the secretion of pro-inflammatory cytokines. These findings suggest a key role for ependymal cells in the early phase of NMO lesion formation.

Despite being largely confined to the airways, SARS-CoV-2 infection has been associated with sensory abnormalities that manifest in both acute and long-lasting phenotypes. To gain insight on the molecular basis of these sensory abnormalities, we used the golden hamster infection model to characterize the effects of SARS-CoV-2 versus Influenza A virus (IAV) infection on the sensory nervous system. Efforts to detect the presence of virus in the cervical/thoracic spinal cord and dorsal root ganglia (DRGs) demonstrated detectable levels of SARS-CoV-2 by quantitative PCR and RNAscope uniquely within the first 24 hours of infection. SARS-CoV-2-infected hamsters demonstrated mechanical hypersensitivity during acute infection; intriguingly, this hypersensitivity was milder, but prolonged when compared to IAV-infected hamsters. RNA sequencing (RNA-seq) of thoracic DRGs from acute infection revealed predominantly neuron-biased signaling perturbations in SARS-CoV-2-infected animals as opposed to type I interferon signaling in tissue derived from IAV-infected animals. RNA-seq of 31dpi thoracic DRGs from SARS-CoV-2-infected animals highlighted a uniquely neuropathic transcriptomic landscape, which was consistent with substantial SARS-CoV-2-specific mechanical hypersensitivity at 28dpi. Ontology analysis of 1, 4, and 30dpi RNA-seq revealed novel targets for pain management, such as ILF3. Meta-analysis of all SARS-CoV-2 RNA-seq timepoints against preclinical pain model datasets highlighted both conserved and unique pro-nociceptive gene expression changes following infection. Overall, this work elucidates novel transcriptomic signatures triggered by SARS-CoV-2 that may underlie both short- and long-term sensory abnormalities while also highlighting several therapeutic targets for alleviation of infection-induced hypersensitivity.One Sentence SummarySARS-CoV-2 infection results in an interferon-associated transcriptional response in sensory tissues underlying time-dependent hypersensitivity.

Opioid analgesics exert their therapeutic and adverse effects by activating

Multivariate functional anomaly detection has received a large amount of attention recently. Accounting both the time dimension and the correlations between variables is challenging due to the existence of different types of outliers and the dimension of the data. In the context of predictive maintenance and quality control, data sets often contain a large number of functional variables. However, most of the existing methods focus on a small number of functional variables. Moreover, in fields that have high reliability standards, detecting a small number of potential multivariate functional outliers with as few false positives as possible is crucial. In such a context, the adaptation of the Invariant Coordinate Selection (ICS) method from the multivariate to the multivariate functional case is of particular interest. Two extensions of ICS are proposed: point-wise and global. For both methods, the choice of the relevant components together with outlier identification and interpretation are discussed. A comparison is made on a predictive maintenance example from the avionics field and a quality control example from the microelectronics field. It appears that in such a context, point-wise and global ICS with a small number of selected components can be recommended.

SUMMARYSARS-CoV-2 has been found capable of inducing prolonged pathologies collectively referred to as Long-COVID. To better understand this biology, we compared the short- and long-term systemic responses in the golden hamster following either SARS-CoV-2 or influenza A virus (IAV) infection. While SARS-CoV-2 exceeded IAV in its capacity to cause injury to the lung and kidney, the most significant changes were observed in the olfactory bulb (OB) and olfactory epithelium (OE) where inflammation was visible beyond one month post SARS-CoV-2 infection. Despite a lack of detectable virus, OB/OE demonstrated microglial and T cell activation, proinflammatory cytokine production, and interferon responses that correlated with behavioral changes. These findings could be corroborated through sequencing of individuals who recovered from COVID-19, as sustained inflammation in OB/OE tissue remained evident months beyond disease resolution. These data highlight a molecular mechanism for persistent COVID-19 symptomology and characterize a small animal model to develop future therapeutics.

Scatter matrices generalize the covariance matrix and are useful in many multivariate data analysis methods, including well-known principal component analysis (PCA), which is based on the diagonalization of the covariance matrix. The simultaneous diagonalization of two or more scatter matrices goes beyond PCA and is used more and more often. In this paper, we offer an overview of many methods that are based on a joint diagonalization. These methods range from the unsupervised context with invariant coordinate selection and blind source separation, which includes independent component analysis, to the supervised context with discriminant analysis and sliced inverse regression. They also encompass methods that handle dependent data such as time series or spatial data. peerReviewed

The sizing of aircraft electrical generators mainly depends on the electrical loads installed in the aircraft. Currently, the generator capacity is estimated by summing the critical loads, but this method tends to overestimate the generator capacity. A new method to challenge this approach is to use the electrical consumption recorded during flights and study the distribution of operational ratios between the actual consumption and the theoretical maximum consumption then size the future aircraft generators by applying a ratio to the theoretical value. This paper focuses on the application of extreme value theory on these operational ratios to estimate the maximal capacity utilization of a generator. A real data example is provided to illustrate the approach and estimate extreme quantiles and the right endpoint of the distribution of the ratios together with their approximate confidence interval in the nominal configuration. In all situations the right endpoint is proven to be finite and does not depend on the use procedures. This approach shows that ELA overestimates the maximal permanent consumption by 20% with error level of $$10^{-3}$$ in the nominal configuration.

The etiology of the autoimmune disorder systemic lupus erythematosus (SLE) remains poorly understood. In neuropsychiatric SLE (NPSLE), autoimmune responses against neural self-antigens find expression in neurological and cognitive alterations. SLE autoantibodies often target nucleic acids, including RNAs and specifically RNA domains with higher-order structural content. We report that autoantibodies directed against neuronal regulatory brain cytoplasmic (BC) RNAs were generated in a subset of SLE patients. By contrast, anti-BC RNA autoantibodies (anti-BC abs) were not detected in sera from patients with autoimmune diseases other than SLE (e.g., rheumatoid arthritis or multiple sclerosis) or in sera from healthy subjects with no evidence of disease. SLE anti-BC abs belong to the IgG class of immunoglobulins and target both primate BC200 RNA and rodent BC1 RNA. They are specifically directed at architectural motifs in BC RNA 5′ stem–loop domains that serve as dendritic targeting elements (DTEs). SLE anti-BC abs effectively compete with RNA transport factor heterogeneous nuclear ribonucleoprotein A2 (hnRNP A2) for DTE access and significantly diminish BC RNA delivery to synapto-dendritic sites of function.In vivoexperiments with male BALB/c mice indicate that, upon lipopolysaccharide-induced opening of the blood–brain barrier, SLE anti-BC abs are taken up by CNS neurons where they significantly impede localization of endogenous BC1 RNA to synapto-dendritic domains. Lack of BC1 RNA causes phenotypic abnormalities including epileptogenic responses and cognitive dysfunction. The combined data indicate a role for anti-BC RNA autoimmunity in SLE and its neuropsychiatric manifestations.SIGNIFICANCE STATEMENTAlthough clinical manifestations of neuropsychiatric lupus are well recognized, the underlying molecular–cellular alterations have been difficult to determine. We report that sera of a subset of lupus patients contain autoantibodies directed at regulatory brain cytoplasmic (BC) RNAs. These antibodies, which we call anti-BC abs, target the BC RNA 5′ domain noncanonical motif structures that specify dendritic delivery. Lupus anti-BC abs effectively compete with RNA transport factor heterogeneous nuclear ribonucleoprotein A2 (hnRNP A2) for access to BC RNAs. As a result, hnRNP A2 is displaced, and BC RNAs are impaired in their ability to reach synapto-dendritic sites of function. The results reveal an unexpected link between BC RNA autoantibody recognition and dendritic RNA targeting. Cellular RNA dysregulation may thus be a contributing factor in the pathogenesis of neuropsychiatric lupus.

SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has been found capable of inducing long term effects commonly referred to as post-acute sequelae of SARS-CoV-2 (PASC) or long COVID. To define the molecular basis of this condition, we compared the short- and long-term responses to influenza A virus and SARSCoV-2 in the golden hamster model. These data demonstrated that SARS-CoV-2 resulted in sustained changes to lung, kidney, and brain. The most significant change in response to SARS-CoV-2 was observed in the olfactory bulb, where persistent inflammation was visible beyond one month post infection. This was characterized by microglial activation, pro-inflammatory cytokine production, and a Type I interferon (IFN-I) response in the absence of detectable virus. Given the connection between olfactory bulb injury and neurological disorders, we postulate that this prolonged inflammation is an underlying cause of long COVID. Funding Information: This work was funded by generous support from the Marc Haas Foundation, the National Institutes of Health (NCI (R01CA234614) and NIAID (2R01AI107301) and NIDDK (R01DK121072 and 1RO3DK117252) to Department of Medicine, Weill Cornell Medicine (R.E.S.)), and DARPA’s PREPARE Program (HR0011-20-2-0040). The work was further funded by NINDS (NS111251, NSO86444, NSO86444S1)(V.Z., R.A.S.). Ethics Approval Statement: The Tissue Procurement Facility operates under Institutional Review Board (IRB) approved protocol and follows guidelines set by Health Insurance Portability and Accountability Act (HIPAA). Experiments using samples from human subjects were conducted in accordance with local regulations and with the approval of the IRB at the Weill Cornell Medicine. The autopsy samples are considered human tissue research and were collected under IRB protocols 20-04021814 and 19-11021069. All autopsies have consent for research use from next of kin, and these studies were determined as exempt by IRB at Weill Cornell Medicine under those protocol numbers.

International audience; Econometric land use models study determinants of land use shares of different classes: “agriculture”, “forest”, “urban” and “other” for example. Land use shares have a compositional nature as well as an important spatial dimension. We compare two compositional regression models with a spatial autoregressive nature in the framework of land use. We study the impact of the choice of coordinate space and prove that a choice of coordinate representation does not have any impact on the parameters in the simplex as long as we do not impose further restrictions. We discuss parameters interpretation taking into account the non-linear structure as well as the spatial dimension. In order to assess the explanatory variables impact, we compute and interpret the semi-elasticities of the shares with respect to the explanatory variables and the spatial impact summary measures.; Les modèles économétriques d'utilisation des terres étudient les déterminants des parts d'utilisation des sols de différentes catégories : "agriculture", "forêt", "urbain" et "autre" par exemple. Les parts d'utilisation des terres ont ont une composition et une dimension spatiale importante.. Les auteurs comparent deux modèles de régression compositionnelle avec une nature spatiale autorégressive dans le cadre de l'utilisation des terres. Ils étudient l'impact du choix de l'espace de coordonnées et prouvent que le choix de la représentation des coordonnées n'a pas d'impact sur les paramètres dans le simplex tant que l'on n'impose pas de restrictions supplémentaires. Ils discutent de l'interprétation des paramètres en tenant compte de la structure non linéaire ainsi que de la dimension spatiale. Afin d'évaluer l'impact des variables explicatives, ils calculent et interprétent les semi-élasticités des actions par rapport aux variables explicatives et les mesures sommaires de l'impact spatial.

OBJECTIVE: The main objective was to compare clinical features, disease course, and myelin oligodendrocyte glycoprotein (MOG) antibody (Ab) dynamics between children and adults with MOG-Ab-associated disease (MOGAD). METHODS: This retrospective multicentric, national study included 98 children and 268 adults with MOGAD between January 2014 and September 2019. Cox regression model for recurrent time-to-event data and Kaplan-Meier curves for time to antibody negativity were performed for the objectives. RESULTS: Isolated optic neuritis was the most frequent clinical presentation in both children (40.8%) and adults (55.9%, p = 0.013), and acute disseminated encephalomyelitis syndrome was more frequent in children (36.7% vs 5.6%, p

International audience; To reduce the number of aircrafts on ground, the electrical design engineers are interested in predicting the oil temperature of the generator during a flight. Changes on the temperature value may indicate an incorrect functioning of the generator. An abnormal behavior can be identified by using machine learning algorithms trained on flights free from any anomalies to predict the generator oil temperature. These predictions can then be compared to the observed values, here the sensor data collected from the aircraft during flight. If the observed value is far from the predicted value, a failure warning is raised and a maintenance action shall be performed. In this paper, we build a digital twin of the electrical generator which predicts the oil generator temperature at a given time thanks to the history of features. We compare several machine learning algorithms and the most promising appears to be a neural network which was implemented as part of the electrical generator digital twin. The digital twin is tested by using real flight data containing generator failures and it is verified that the algorithm is able to detect an anomaly prior to the failure events (early failure detection).

OBJECTIVE: To analyze whether myelin oligodendrocyte glycoprotein antibody (MOG-Ab) titres at onset of the disease were different according to the clinical phenotype at presentation, and to investigate whether the titres were associated with risk of further relapses or predicted clinical outcome in adult patients. Finally, we assessed an alternative method to the classical measurement of MOG-Ab levels by serial dilutions. METHODS: This is a retrospective study including 79 MOG-Ab-positive adult patients, whose samples were obtained at first episode. MOG-Ab were tested by cell-based assay. HEK293 cells were transfected (tHEK293) with human-MOG plasmid. Non-tHEK293 cells were used as negative controls. Assessment of antibody titres was performed by serial dilution, and delta mean fluorescence intensity ratio signal (MOG-ratio MFI) by flow cytometry. MOG-ratio MFI was calculated as follows: (MFI tHEK293cells- MFI non-tHEK293cells)/MFI non-tHEK293cells. MOG-ratio MFI was calculated from the first serum dilution at 1:320. The association between MOG-Ab titres and risk of relapse was analyzed by Cox regression. The association between MOG-Ab titres and visual or motor disability at last follow-up was performed by binary logistic regression. Poor visual outcome was defined when patients displayed some degree of visual disability (visual acuity [VA] < 20/20) and poor motor outcome when patients displayed some degree of motor disability (Disability Status Scale [DSS] > 1). We also investigated correlations between MOG-Ab titres and MOG-ratio MFI. RESULTS: MOG-Ab titres were higher in Caucasians than in those with other ethnicities, and in patients with a more severe VA (VA = 20/100) or motor disability (DSS = 3.0) at onset (p = 0.006, 0.034, and 0.058, respectively). MOG-Ab titres were not associated with risk of relapses or with the final clinical outcome. MOG-ratio MFI correlated with MOG-Ab titres in the whole cohort (? = 0.90; p < 0.001), and when stratified by initial clinical phenotype. CONCLUSION: High MOG-Ab titres at onset are associated with a more severe presentation, but do not predict the future disease course. MOG-ratio MFI is an alternative and straightforward method to determine MOG-Ab levels.

Myelin oligodendrocyte glycoprotein antibodies (MOG-Ab) have been reported in acute demyelinating encephalomyelitis (ADEM), optic neuritis (ON), and neuromyelitis optica spectrum disorders (NMOSD) in adults and pediatrics. We aimed to delineate the common features of MOG-Ab-related disorders in children and adults, and report uncommon presentations. Twenty-seven consecutive pediatric and adult patients testing positive for MOG-Ab, with a minimum follow-up of 6 months, were included. Comprehensive epidemiological, clinical, radiological, and laboratory data were retrospectively analyzed. Additionally, we compared radiological features between ADEM MOG-Ab-positive patients, and a group of ADEM MOG-Ab-negative ones, recruited during the same period. Among the whole cohort, 13 (48.1%) were pediatric, and 14 (51.9%) were female. MOG-Ab-related disorders comprised eight ADEM, eight ON, five isolated myelitis, four with NMOSD and two patients with multiple sclerosis, at last follow-up. After a median follow-up of 17.8 months, 11 (40.7%) patients presented a relapse. The most frequent clinical phenotype at onset was encephalopathy in pediatrics (53.9%) and myelitis in adults (50%) (p = 0.013). There were no other differences between both groups. When comparing ADEM MOG-Ab positive and negative patients, bilateral thalamic lesions were more often found in the positive group (p = 0.010). Unusual presentations were identified in three patients: patchy spinal cord gadolinium-enhancing lesions, an associated teratoma, and one presented with status epilepticus. MOG-Ab-related disorders shared common clinical and prognostic features, but encompass a spectrum wider than recently reported.

Codes JEL : C21, C25, C38, Q15, R14; In this paper, we propose models that allow to predict land use (urban, agriculture, forests, natural grasslands and soil) at the points of the Teruti-Lucas survey from easily accessible covariates. Our approach involves two steps: first we model land use at the Teruti-Lucas point level and second, we propose a method to aggregate land use on regular meshes. The model of the first stage provides fine level predictions. The second step aggregates these predictions on the tiles of the mesh comparing several methods. We are considering various regular meshes of the territory to study the prediction quality depending on the resolution. We show that with easily accessible variables we have an acceptable prediction quality at the point level and that the quality of prediction is improved from the very first stage of aggregation.; Les auteurs évaluent dans quelle mesure ils peuvent prédire l’usage des sols (usage urbain, usage agricole, forêts, prairies et sols naturels) au niveau des points de l’enquête Teruti-Lucas à partir de covariables facilement accessibles. Leur approche comporte deux étapes : la première permet de modéliser l’usage du sol au niveau des points Teruti-Lucas et la deuxième propose une méthode pour en déduire l’utilisation des sols sur un maillage défini par des carreaux. Le modèle de la première étape fournit des prédictions à un niveau fin. La deuxième étape agrège ces prédictions sur les carreaux du maillage en comparant plusieurs méthodes. Sont envisagés différents maillages réguliers du territoire en carreaux pour étudier la qualité de restitution en fonction de la résolution. Les auteurs montrent qu’avec des variables facilement accessibles on obtient une qualité de prédiction acceptable au niveau point et que l’amélioration de la qualité est importante dès la première étape d’agrégation.

International audience; We prove that any implementation of pivotal sampling is more efficient than multinomial sampling. This yields the weak consistency of the Horvitz Thompson estimator and the existence of a conservative variance estimator. A small simulation study supports our findings.

Anti–Glial fibrillary acidic protein (GFAP) encephalomyelitis is a recently described entity and while the spectrum of this disease has been explored, further research is needed to fully describe its phenotype. Area postrema syndrome (APS) is usually associated with neuromyelitis optica spectrum disorders (NMOSDs), whereas no case of APS has been previously reported with anti-GFAP encephalomyelitis. In this article, we report a case of APS in a 41-year-old woman in the context of anti-GFAP encephalomyelitis. This case was not associated with additional anti-AQP4 IgG and therefore extends the clinico-radiological spectrum of anti-GFAP encephalomyelitis.

The original version of this article unfortunately contained a mistake.

Neuromyelitis optica, a rare neuroinflammatory demyelinating disease of the CNS, is characterized by the presence of specific pathogenic autoantibodies directed against the astrocytic water channel aquaporin 4 (AQP4) and is now considered as an astrocytopathy associated either with complement-dependent astrocyte death or with astrocyte dysfunction. However, the link between astrocyte dysfunction and demyelination remains unclear. We propose glial intercellular communication, supported by connexin hemichannels and gap junctions, to be involved in demyelination process in neuromyelitis optica. Using mature myelinated cultures, we demonstrate that a treatment of 1 h to 48 h with immunoglobulins purified from patients with neuromyelitis optica (NMO-IgG) is responsible for a complement independent demyelination, compared to healthy donors’ immunoglobulins (P

Summary Recently a blind source separation model was suggested for spatial data, along with an estimator based on the simultaneous diagonalization of two scatter matrices. The asymptotic properties of this estimator are derived here, and a new estimator based on the joint diagonalization of more than two scatter matrices is proposed. The asymptotic properties and merits of the novel estimator are verified in simulation studies. A real-data example illustrates application of the method.

The proportions of votes by party on a given subdivision of a territory form a vector called composition (mathematically, a vector belonging to a simplex). It is interesting to model these proportions and study the impact of the characteristics of the territorial units on the outcome of the elections. In the political economy literature, such regression models are generally restricted to the case of two political parties. In the statistical literature, there are regression models adapted to share vectors including CODA models (for COmpositional Data Analysis), but also Dirichlet models, Student models and others. Our goal is to use CODA regression models to generalize political economy models to more than two parties. The models are _tted on French electoral data of the 2015 departmental elections.

Objective: We aimed to investigate the frequency and clinical significance of antibodies to myelin oligodendrocyte glycoprotein (MOG-abs) in patients who presented with a first episode of seronegative aquaporin 4 antibody (AQP4-ab) longitudinally extensive transverse myelitis (LETM). Methods: Epidemiological, clinical, and paraclinical data of 56 patients from three European centres were analysed. Patients were retrospectively tested for MOG-abs and AQP4-abs, by cell-based assays. Findings: Thirteen (23.2%) patients were MOG-ab positive. Among the 56 patients, six (10.7%) converted to neuromyelitis optica (NMO), one (1.8%) to multiple sclerosis (MS), nine (16.1%) had recurrent LETM, and 40 (71.4%) remained as monophasic LETM. Compared with seronegative patients, those with MOG-abs were younger (median: 32.5 vs 44 years; p=0.007), had cerebrospinal fluid pleocytosis more frequently (94% vs 45%, p=0.003) and had better outcome (median Expanded Disability Status Scale (EDSS) 2.0 vs 3.0, p=0.027). MOG-ab positive patients also showed an increase risk of optic neuritis relapse and NMO conversion ( p=0.010). Conclusion: Patients with MOG-abs in AQP4-ab seronegative LETM have clinical distinctive features, higher risk of optic neuritis relapses, and better outcome than patients seronegative.