Cerebrospinal fluid humoral immunity in the differential diagnosis of multiple sclerosis

Bernitsas, Evanthia; Khan, Omar; Razmjou, Sara; Tselis, Alexandros; Bao, Fen; Caon, Christina; Millis, Scott R.; Seraji‐Bozorgzad, Navid

doi:10.1371/journal.pone.0181431

Cited by 21 publications

(15 citation statements)

References 33 publications

(41 reference statements)

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“…4353, Sebia, France). As described in a previous publication [ 15 ], CSF-OCB pattern classification was based on two consensus report recommendations [ 16 , 17 ]. Five types of patterns were proposed with only patterns 2 and 3 representing an intrathecal synthesis of IgG: type 1: normal CSF, type 2: two or more CSF restricted OCB, type 3: CSF restricted OCB and additional, identical OCB in serum and CSF, type 4: identical OCB in CSF and serum, “mirror pattern”, type 5: monoclonal bands in CSF and serum.…”

Section: Methodsmentioning

confidence: 99%

Cerebrospinal fluid abnormalities in first- and multi-episode schizophrenia-spectrum disorders: impact of clinical and demographical variables

et al. 2021

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Multiple lines of evidence indicate that immunological and inflammatory alterations contribute at least in a subgroup to the pathophysiology of schizophrenia. In this retrospective chart review, we investigated whether clinical factors contribute to altered cerebrospinal fluid (CSF) findings in schizophrenia-spectrum disorders. Clinical data from electronic medical records of patients with psychotic disorders (ICD-10: F20-F29) who received routine CSF diagnostics at the Department of Psychiatry and Psychotherapy, LMU Munich, Germany, were included. Chi² tests for dichotomous outcomes and independent t tests for continuous outcomes were used to compare differences between groups. A total of 331 patients were included in the analyses (43.2% female and 56.8% male). The mean age was 37.67 years (±15.58). The mean duration of illness was 71.96 months (±102.59). In all, 40% (128/320) were first-episode psychosis (FEP) patients and 60% (192/320) were multi-episode psychosis (MEP) patients. Elevated CSF protein levels were found in 19.8% and elevated CSF/serum albumin ratios (QAlb) in 29.4% of the cases. Pleocytosis was found in 6.1% of patients. MEP patients showed significantly higher mean QAlb compared with FEP patients (t(304.57) = −2.75, p = 0.006), which did not remain significant after correcting for age. QAlb elevation occurred more frequently in men (X2(1) = 14.76, p = <0.001). For treatment resistance, family history, and cMRI alterations, no significant differences in CSF-related outcomes were detected. Our work extends other retrospective cohorts confirming a relevant degree of CSF alterations in schizophrenia-spectrum disorders and shows the difficulty to relate these alterations to clinical and disease course trajectories. More research is needed to develop treatment response predictors from CSF analyses.

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Section: Methodsmentioning

confidence: 99%

Cerebrospinal fluid abnormalities in first- and multi-episode schizophrenia-spectrum disorders: impact of clinical and demographical variables

et al. 2021

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“…The greater the lesion load at the onset, the higher is the probability for an oligodendrocyte to die by apoptosis. The presence of oligoclonal bands is a biomarker that is associated with a more aggressive prognosis of MS [52,53]. As the oligoclonal bands are made of immunoglobulins of class G and/or M, they can be translated, in the simulation model, into an augmented autoimmune response in patients suffering from MS. Then we associated the presence of oligoclonal bands with an impaired function of the regulatory system in the simulated patient.…”

Section: Simulation Of Real Patientsmentioning

confidence: 99%

The Potential of Computational Modeling to Predict Disease Course and Treatment Response in Patients with Relapsing Multiple Sclerosis

Pappalardo

Russo

Pennisi

et al. 2020

Cells

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As of today, 20 disease-modifying drugs (DMDs) have been approved for the treatment of relapsing multiple sclerosis (MS) and, based on their efficacy, they can be grouped into moderate-efficacy DMDs and high-efficacy DMDs. The choice of the drug mostly relies on the judgment and experience of neurologists and the evaluation of the therapeutic response can only be obtained by monitoring the clinical and magnetic resonance imaging (MRI) status during follow up. In an era where therapies are focused on personalization, this study aims to develop a modeling infrastructure to predict the evolution of relapsing MS and the response to treatments. We built a computational modeling infrastructure named Universal Immune System Simulator (UISS), which can simulate the main features and dynamics of the immune system activities. We extended UISS to simulate all the underlying MS pathogenesis and its interaction with the host immune system. This simulator is a multi-scale, multi-organ, agent-based simulator with an attached module capable of simulating the dynamics of specific biological pathways at the molecular level. We simulated six MS patients with different relapsing–remitting courses. These patients were characterized based on their age, sex, presence of oligoclonal bands, therapy, and MRI lesion load at the onset. The simulator framework is made freely available and can be used following the links provided in the availability section. Even though the model can be further personalized employing immunological parameters and genetic information, we generated a few simulation scenarios for each patient based on the available data. Among these simulations, it was possible to find the scenarios that realistically matched the real clinical and MRI history. Moreover, for two patients, the simulator anticipated the timing of subsequent relapses, which occurred, suggesting that UISS may have the potential to assist MS specialists in predicting the course of the disease and the response to treatment.

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“…The greater the lesion load at onset, the higher is the probability for an oligodendrocyte to die by apoptosis. The presence of oligoclonal bands is a biomarker that is associated with a more aggressive prognosis of MS [52,53]. As the oligoclonal bands are made of immunoglobulins of class G and/or M, they can be translated, in the simulation model, into an augmented autoimmune response in patients suffering of MS. Then we associated the presence of oligoclonal bands with an impaired function of the regulatory system in the simulated patient.…”

Section: Simulation Of Real Patientsmentioning

confidence: 99%

The Potential of Computational Modeling to Predict Disease Course and Treatment Response in Patients with Relapsing Multiple Sclerosis

Papparlardo¹,

Russo²,

Pennisi³

et al. 2020

Preprint

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As of today, 20 disease modifying drugs (DMD) have been approved for the treatment of relapsing multiple sclerosis (MS) and, based on their efficacy, they can be grouped into moderate-efficacy DMDs and high-efficacy DMDs. The choice of the drug mostly relies on the judgement and experience of neurologists and the evaluation of therapeutic response can only be obtained by monitoring clinical and magnetic resonance imaging (MRI) status during follow up. In an era where therapies are focused on personalization, the aim of this study is to develop a modeling infrastructure to predict the evolution of relapsing MS and the response to treatments. We built a computational modeling infrastructure named UISS (Universal Immune System Simulator) able to simulate the main features and dynamics of the immune system activities. We extended UISS to simulate all the underlying MS pathogenesis and its interaction with the host immune system. This simulator is a multi-scale, multi-organ, agent based simulator with an attached module capable of simulating the dynamics of specific biological pathways at the molecular level. We simulated six MS patients with different relapsing-remitting courses. These patients were characterized on the basis of their age, sex, presence of oligoclonal bands, therapy and MRI lesion load at onset. The simulator framework is made freely available and can be used following the links provided in the availability section. Even though the model can be further personalized employing immunological parameters and genetic information, based on the available data we generated a few simulation scenarios for each patient, including those who matched the real clinical and MRI history. Moreover, for two patients, the simulator anticipated the timing of subsequent relapses, which really occurred, suggesting that UISS may have the potential to assist MS specialists in predicting the course of the disease and the response to treatment.

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Cerebrospinal fluid humoral immunity in the differential diagnosis of multiple sclerosis

Cited by 21 publications

References 33 publications

Cerebrospinal fluid abnormalities in first- and multi-episode schizophrenia-spectrum disorders: impact of clinical and demographical variables

Cerebrospinal fluid abnormalities in first- and multi-episode schizophrenia-spectrum disorders: impact of clinical and demographical variables

The Potential of Computational Modeling to Predict Disease Course and Treatment Response in Patients with Relapsing Multiple Sclerosis

The Potential of Computational Modeling to Predict Disease Course and Treatment Response in Patients with Relapsing Multiple Sclerosis

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