Multiple biomarkers improve the prediction of multiple sclerosis in clinically isolated syndromes

Association between clinical characteristics, acute steroid treatment and oligoclonal bands result in multiple sclerosis: A retrospective study

BACKGROUND

Detection of oligoclonal bands (OCBs) in the cerebrospinal fluid (CSF) is important for diagnosis of multiple sclerosis (MS). Previous studies reported that treatment with intravenous methylprednisolone (IVMP) before lumber puncture (LP) could suppress OCBs production. The aim of this study was to assess whether IVMP initiation prior to CSF collection affects OCBs results in patients with an acute demyelinating event. Additionally, we examined which clinical characteristics are associated with the presence of OCBs in the CSF.

METHODS

We retrospectively evaluated patients admitted to the neurology department at rabin medical center (RMC) between 2010 and 2022 who underwent LP with OCBs analysis as part of their demyelinating attack workup. Patients were divided into OCB-positive and OCB-negative groups and demographical and clinical characteristics (including timing and duration of acute steroid treatment and history of prior demyelinating attacks) were analyzed for association with OCBs results.

RESULTS

A total of 342 patients were included with a median age of 35 years (IQR, 27-46). Two hundred thirty-eight (69.6 %) were OCB-positive. Initiation of IVMP before LP was not associated with negative OCBs (11.8 % Vs. 13.5 %, P = 0.721), nor was it correlated with OCBs positivity (OR=0.86, P = 0.66). CSF cell count was higher in OCB-positive patients (5 Vs. 3, P = 0.001), and a history of prior demyelinating attacks was associated with- (33.6 % Vs. 20.2 %, P = 0.014) and predictive of OCBs positivity (OR=2, P = 0.013).

CONCLUSIONS

Timing of steroids was not associated with OCB positivity. However, pleocytosis and a prior attack were associated with OCB positivity in this cohort. Our results suggest that steroid treatment is unlikely to affect OCBs results. Ideally, larger prospective studies would be needed to confirm our observations.

Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system that affects millions of people worldwide. The disease course varies greatly across individuals and many disease-modifying treatments with different safety and efficacy profiles have been developed recently. Prognostic models evaluated and shown to be valid in different settings have the potential to support people with MS and their physicians during the decision-making process for treatment or disease/life management, allow stratified and more precise interpretation of interventional trials, and provide insights into disease mechanisms. Many researchers have turned to prognostic models to help predict clinical outcomes in people with MS; however, to our knowledge, no widely accepted prognostic model for MS is being used in clinical practice yet.

OBJECTIVES

To identify and summarise multivariable prognostic models, and their validation studies for quantifying the risk of clinical disease progression, worsening, and activity in adults with MS.

SEARCH METHODS

We searched MEDLINE, Embase, and the Cochrane Database of Systematic Reviews from January 1996 until July 2021. We also screened the reference lists of included studies and relevant reviews, and references citing the included studies.

SELECTION CRITERIA

We included all statistically developed multivariable prognostic models aiming to predict clinical disease progression, worsening, and activity, as measured by disability, relapse, conversion to definite MS, conversion to progressive MS, or a composite of these in adult individuals with MS. We also included any studies evaluating the performance of (i.e. validating) these models. There were no restrictions based on language, data source, timing of prognostication, or timing of outcome.

DATA COLLECTION AND ANALYSIS

Pairs of review authors independently screened titles/abstracts and full texts, extracted data using a piloted form based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS), assessed risk of bias using the Prediction Model Risk Of Bias Assessment Tool (PROBAST), and assessed reporting deficiencies based on the checklist items in Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD). The characteristics of the included models and their validations are described narratively. We planned to meta-analyse the discrimination and calibration of models with at least three external validations outside the model development study but no model met this criterion. We summarised between-study heterogeneity narratively but again could not perform the planned meta-regression.

MAIN RESULTS

We included 57 studies, from which we identified 75 model developments, 15 external validations corresponding to only 12 (16%) of the models, and six author-reported validations. Only two models were externally validated multiple times. None of the identified external validations were performed by researchers independent of those that developed the model. The outcome was related to disease progression in 39 (41%), relapses in 8 (8%), conversion to definite MS in 17 (18%), and conversion to progressive MS in 27 (28%) of the 96 models or validations. The disease and treatment-related characteristics of included participants, and definitions of considered predictors and outcome, were highly heterogeneous amongst the studies. Based on the publication year, we observed an increase in the percent of participants on treatment, diversification of the diagnostic criteria used, an increase in consideration of biomarkers or treatment as predictors, and increased use of machine learning methods over time. Usability and reproducibility All identified models contained at least one predictor requiring the skills of a medical specialist for measurement or assessment. Most of the models (44; 59%) contained predictors that require specialist equipment likely to be absent from primary care or standard hospital settings. Over half (52%) of the developed models were not accompanied by model coefficients, tools, or instructions, which hinders their application, independent validation or reproduction. The data used in model developments were made publicly available or reported to be available on request only in a few studies (two and six, respectively). Risk of bias We rated all but one of the model developments or validations as having high overall risk of bias. The main reason for this was the statistical methods used for the development or evaluation of prognostic models; we rated all but two of the included model developments or validations as having high risk of bias in the analysis domain. None of the model developments that were externally validated or these models' external validations had low risk of bias. There were concerns related to applicability of the models to our research question in over one-third (38%) of the models or their validations. Reporting deficiencies Reporting was poor overall and there was no observable increase in the quality of reporting over time. The items that were unclearly reported or not reported at all for most of the included models or validations were related to sample size justification, blinding of outcome assessors, details of the full model or how to obtain predictions from it, amount of missing data, and treatments received by the participants. Reporting of preferred model performance measures of discrimination and calibration was suboptimal.

AUTHORS' CONCLUSIONS

The current evidence is not sufficient for recommending the use of any of the published prognostic prediction models for people with MS in clinical routine today due to lack of independent external validations. The MS prognostic research community should adhere to the current reporting and methodological guidelines and conduct many more state-of-the-art external validation studies for the existing or newly developed models.

VEP Score of a Left Eye Had Predictive Values for Achieving NEDA-3 over Ten Years in Patients with Multiple Sclerosis

BACKGROUND

The aim of this study was to determine the predictive value of visual evoked potentials (VEPs) in patients with relapsing-remitting multiple sclerosis (RRMS) in achieving no evidence of disease activity-3 (NEDA-3) during up to 10 years of first-line immunomodulatory therapy and to determine whether the lateralization of optic nerve damage may have prognostic significance concerning clinical disability and response to therapy.

METHODS

In a retrospective study, a total of 83 patients (53 female and 30 male) with RRMS participated. The average age of patients was 38.31 ± 9.01. Patients were followed for 2, 5 or 10 years. VEPs were measured at the beginning of the follow-up and after many years of monitoring. Data on optical neuritis (ON) were obtained from medical history. The degree of disability was estimated by the neurologist (independent rater), and magnetic resonance (MR) imaging of the endocranium was performed with gadolinium contrasts. Achieving NEDA-3 is considered a favorable outcome of treatments.

RESULTS

Among those treated, 19 (22.9%) reached NEDA-3, while 64 (77.1%) did not reach NEDA-3. The values of the evoked potential (EP) score for the left eye (r = 0.008, odds ratio (OR) = 0.344 (0.156-0.757)) and latency for the left eye (r = 0.042, OR = 0.966 (0.934-0.999)) at the onset of disease were predictive factors for achieving NEDA-3.

CONCLUSIONS

A normal VEP at the beginning of RRMS increases the chance of reaching NEDA-3 by about six times.

Multimodal Evoked Potentials as Potential Biomarkers of Disease Activity in Patients With Clinically Isolated Syndrome

Objective

There is an ongoing search for markers useful in monitoring and predicting disease activity at the early stage of multiple sclerosis (MS). The goals of this study were to prospectively evaluate the changes in parameters of multimodal evoked potentials (EP) and cognition within a 3-year follow-up period in patients with clinically isolated syndrome (CIS), and to assess the prognostic value of baseline findings with regard to the disease outcomes.

Methods

In 29 patients (20 women, nine men, mean age 31.1) multimodal (visual, brainstem auditory, somatosensory, event-related) EP and neuropsychological tests (NT) were performed at baseline (T0) and after 1 (T1) and 3 (T3) years. Their results were compared longitudinally between baseline, T1, and T3. Baseline results confirmed conversion of CIS into multiple sclerosis (MS) and disability level at T1 and T3 using multiple comparisons and a logistic regression model.

Results

Apart from mean N13/P16 SEP (somatosensory evoked potentials) amplitude (lower at T1 and T3 than at baseline (T0 1.02 ± 0.37 μV, T1 0.90 ± 0.26 μV, T3 0.74 ± 0.32 μV, p < 0.05 for both comparisons), no significant changes of EP or NT parameters were found in longitudinal assessment. Baseline P300 Pz latency was longer for the patients with MS than for those with CIS at T1 (352.69 vs. 325.56 ms). No predictive value was shown for any of the analyzed baseline variables with regard to conversion from CIS into MS.

Significance

Baseline ERP abnormalities were associated with their short-term conversion into MS. ERP are worth considering in multimodal EP evaluation at the early stage of MS.

Systems analysis of miRNA biomarkers to inform drug safety

microRNAs (miRNAs or miRs) are short non-coding RNA molecules which have been shown to be dysregulated and released into the extracellular milieu as a result of many drug and non-drug-induced pathologies in different organ systems. Consequently, circulating miRs have been proposed as useful biomarkers of many disease states, including drug-induced tissue injury. miRs have shown potential to support or even replace the existing traditional biomarkers of drug-induced toxicity in terms of sensitivity and specificity, and there is some evidence for their improved diagnostic and prognostic value. However, several pre-analytical and analytical challenges, mainly associated with assay standardization, require solutions before circulating miRs can be successfully translated into the clinic. This review will consider the value and potential for the use of circulating miRs in drug-safety assessment and describe a systems approach to the analysis of the miRNAome in the discovery setting, as well as highlighting standardization issues that at this stage prevent their clinical use as biomarkers. Highlighting these challenges will hopefully drive future research into finding appropriate solutions, and eventually circulating miRs may be translated to the clinic where their undoubted biomarker potential can be used to benefit patients in rapid, easy to use, point-of-care test systems.

Optic Nerve Topography in Multiple Sclerosis Diagnosis: The Utility of Visual Evoked Potentials

Objective

To assess the added value of the optic nerve region (by using visual evoked potentials [VEPs]) to the current diagnostic criteria.

Methods

From the Barcelona clinically isolated syndrome (CIS) cohort, patients with complete information to assess dissemination in space (DIS), the optic nerve region, and dissemination in time at baseline (n = 388) were selected. Modified DIS (modDIS) criteria were constructed by adding the optic nerve to the current DIS regions. The DIS and modDIS criteria were evaluated with univariable Cox proportional hazard regression analyses with the time to the second attack as the outcome. A subset of these patients who had at least 10 years of follow-up or a second attack occurring within 10 years (n = 151) were selected to assess the diagnostic performance. The analyses were also performed according to CIS topography (optic neuritis vs non–optic neuritis).

Results

The addition of the optic nerve as a fifth region improved the diagnostic performance by slightly increasing the accuracy (2017 DIS 75.5%, modDIS 78.1%) and the sensitivity (2017 DIS 79.2%, modDIS 82.3%) without lowering the specificity (2017 DIS 52.4%, modDIS 52.4%). When the analysis was conducted according to CIS topography, the modDIS criteria performed similarly in both optic neuritis and non–optic neuritis CIS.

Conclusion

The addition of the optic nerve, assessed by VEP, as a fifth region in the current DIS criteria slightly improves the diagnostic performance because it increases sensitivity without losing specificity.

Visual Evoked Potentials as a Biomarker in Multiple Sclerosis and Associated Optic Neuritis

: ABSTRACT:: Multiple sclerosis (MS) is an inflammatory, degenerative disease of the central nervous system (CNS) characterized by progressive neurological decline over time. The need for better "biomarkers" to more precisely capture and track the effects of demyelination, remyelination, and associated neuroaxonal injury is a well-recognized challenge in the field of MS. To this end, visual evoked potentials (VEPs) have a role in assessing the extent of demyelination along the optic nerve, as a functionally eloquent CNS region. Moreover, VEPs testing can be used to predict the extent of recovery after optic neuritis (ON) and capture disabling effects of clinical and subclinical demyelination events in the afferent visual pathway. In this review, the evolving role of VEPs in the diagnosis of patients with ON and MS and the utility of VEPs testing in determining therapeutic benefits of emerging MS treatments is discussed.

Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis

Background

Evoked potentials (EPs) are a measure of the conductivity of the central nervous system. They are used to monitor disease progression of multiple sclerosis patients. Previous studies only extracted a few variables from the EPs, which are often further condensed into a single variable: the EP score. We perform a machine learning analysis of motor EP that uses the whole time series, instead of a few variables, to predict disability progression after two years. Obtaining realistic performance estimates of this task has been difficult because of small data set sizes. We recently extracted a dataset of EPs from the Rehabiliation & MS Center in Overpelt, Belgium. Our data set is large enough to obtain, for the first time, a performance estimate on an independent test set containing different patients.

Methods

We extracted a large number of time series features from the motor EPs with the highly comparative time series analysis software package. Mutual information with the target and the Boruta method are used to find features which contain information not included in the features studied in the literature. We use random forests (RF) and logistic regression (LR) classifiers to predict disability progression after two years. Statistical significance of the performance increase when adding extra features is checked.

Results

Including extra time series features in motor EPs leads to a statistically significant improvement compared to using only the known features, although the effect is limited in magnitude (ΔAUC = 0.02 for RF and ΔAUC = 0.05 for LR). RF with extra time series features obtains the best performance (AUC = 0.75±0.07 (mean and standard deviation)), which is good considering the limited number of biomarkers in the model. RF (a nonlinear classifier) outperforms LR (a linear classifier).

Conclusions

Using machine learning methods on EPs shows promising predictive performance. Using additional EP time series features beyond those already in use leads to a modest increase in performance. Larger datasets, preferably multi-center, are needed for further research. Given a large enough dataset, these models may be used to support clinicians in their decision making process regarding future treatment.

Disease Pathway Cut for Multi-Target drugs

Background

Biomarker discovery studies have been moving the focus from a single target gene to a set of target genes. However, the number of target genes in a drug should be minimum to avoid drug side-effect or toxicity. But still, the set of target genes should effectively block all possible paths of disease progression.

Methods

In this article, we propose a network based computational analysis for target gene identification for multi-target drugs. The min-cut algorithm is employed to cut all the paths from onset genes to apoptotic genes on a disease pathway. If the pathway network is completely disconnected, development of disease will not further go on. The genes corresponding to the end points of the cutting edges are identified as candidate target genes for a multi-target drug.

Results and conclusions

The proposed method was applied to 10 disease pathways. In total, thirty candidate genes were suggested. The result was validated with gene set enrichment analysis software, PubMed literature review and de facto drug targets.

Prognostic value of serum neurofilaments in patients with clinically isolated syndromes

Objective

To assess the prognostic role of serum neurofilament light chains (NfL) for clinically defined multiple sclerosis (CDMS) and McDonald 2017 multiple sclerosis (MS) in patients with clinically isolated syndromes (CIS).

Methods

We retrospectively analyzed data of patients admitted to our neurologic department between 2000 and 2015 for a first demyelinating event. We evaluated baseline serum NfL in addition to CSF, MRI, and clinical data.

Results

Among 222 patients who were enrolled (mean follow-up 100.6 months), 45 patients (20%) developed CDMS and 141 patients (63.5%) developed 2017 MS at 2 years. Serum NfL (median 22.0, interquartile range 11.6–40.4 pg/mL) was noticeably increased in patients with a recent relapse, with a high number of T2 and gadolinium-enhancing lesions at baseline MRI. Serum NfL was prognostic for both CDMS and McDonald 2017 MS, with a threefold and a twofold respective reduction in CDMS and 2017 MS risk in those patients with low and extremely low levels of NfL. The results remained unchanged subsequent to adjustment for such established MS prognostic factors as oligoclonal bands, Gd-enhancing lesions, and a high T2 lesion load at baseline MRI. NfL was associated with disability at baseline but not at follow-up.

Conclusions

Serum NfL have a prognostic value for CIS patient conversion to MS. NfL might play a twin role as biomarker in MS as peak level measurements can act as a quantitative marker of serious inflammatory activity, while steady-state levels can be a reflection of neurodegenerative and chronic inflammatory processes.

Oligoclonal bands increase the specificity of MRI criteria to predict multiple sclerosis in children with radiologically isolated syndrome

BACKGROUND

Steps towards the development of diagnostic criteria are needed for children with the radiologically isolated syndrome to identify children at risk of clinical demyelination.

OBJECTIVES

To evaluate the 2005 and 2016 MAGNIMS magnetic resonance imaging criteria for dissemination in space for multiple sclerosis, both alone and with oligoclonal bands in cerebrospinal fluid added, as predictors of a first clinical event consistent with central nervous system demyelination in children with radiologically isolated syndrome.

METHODS

We analysed an international historical cohort of 61 children with radiologically isolated syndrome (≤18 years), defined using the 2010 magnetic resonance imaging dissemination in space criteria (Ped-RIS) who were followed longitudinally (mean 4.2 ± 4.7 years). All index scans also met the 2017 magnetic resonance imaging dissemination in space criteria.

RESULTS

Diagnostic indices (95% confidence intervals) for the 2005 dissemination in space criteria, with and without oligoclonal bands, were: sensitivity 66.7% (38.4-88.2%) versus 72.7% (49.8-89.3%); specificity 83.3% (58.6-96.4%) versus 53.9% (37.2-69.9%). For the 2016 MAGNIMS dissemination in space criteria diagnostic indices were: sensitivity 76.5% (50.1-93.2%) versus 100% (84.6-100%); specificity 72.7% (49.8-89.3%) versus 25.6% (13.0-42.1%).

CONCLUSIONS

Oligoclonal bands increased the specificity of magnetic resonance imaging criteria in children with Ped-RIS. Clinicians should consider testing cerebrospinal fluid to improve diagnostic certainty. There is rationale to include cerebrospinal fluid analysis for biomarkers including oligoclonal bands in planned prospective studies to develop optimal diagnostic criteria for radiologically isolated syndrome in children.

Evaluation of serum miR-191-5p, miR-24-3p, miR-128-3p, and miR-376c-3 in multiple sclerosis patients

BACKGROUND

Biomarkers that could be used in early diagnosis of multiple sclerosis (MS), segregation of disease subtypes, and discrimination of the aggressive disease course from the benign one are urgently needed.

OBJECTIVE

The aim of this study was to investigate the specificity of circulating microRNAs: miR-191-5p, miR-128-3p, miR-24-3p, and miR-376c-3p in MS and evaluate their association with disease activity and disability progression.

METHODS

The expressions of circulating miRNAs were studied in serum of 100 subjects (53 relapsing-remitting (RRMS), 20 primary progressive (PPMS), and 27 controls), using miScript serum miRNA RT-PCR assay techniques.

RESULTS

In comparison with controls, miR-191-5p and miR-24-3p were overexpressed in RRMS and PPMS, with no differences between the subtypes. miR-24-3p correlated positively with the disability progression index in the combined group of all patients with MS. miR-128-3p showed tendency toward the predominant expression in PPMS and correlated positively with the annual relapse rate in RRMS. miR-376c-3p expression levels did not differ between the groups, and no associations were found to clinical parameters.

CONCLUSION

This study highlighted the connection of circulating miRNAs to MS. miR-24-3p and miR-128-3p showed a tendency of association with disability accumulation and disease activity, respectively. Further studies should evaluate their suitability for clinical use.

Clinical Application of 2017 McDonald Diagnostic Criteria for Multiple Sclerosis

BACKGROUND AND PURPOSE

McDonald criteria for multiple sclerosis diagnosis have been revised over the years, diagnostic procedures have been simplified and earlier diagnosis facilitated. The new 2017 revision introduces other important changes, with a further simplification for the diagnosis. Oligoclonal bands reassume a more relevant role in the workup.

METHODS

We describe 3 typical cases of patients admitted for clinically isolated syndrome and illustrate how the application of the new criteria can change the diagnostic approach with respect to the previous criteria.

RESULTS

In two of the three cases a diagnosis of multiple sclerosis is now possible.

CONCLUSIONS

The new 2017 Multiple Sclerosis criteria may have an important impact in clinical practice with an earlier treatment to avoid the risk of disease dissemination. Their application requires a careful assessment to avoid misdiagnosis and mistreatments.

Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria

The 2010 McDonald criteria for the diagnosis of multiple sclerosis are widely used in research and clinical practice. Scientific advances in the past 7 years suggest that they might no longer provide the most up-to-date guidance for clinicians and researchers. The International Panel on Diagnosis of Multiple Sclerosis reviewed the 2010 McDonald criteria and recommended revisions. The 2017 McDonald criteria continue to apply primarily to patients experiencing a typical clinically isolated syndrome, define what is needed to fulfil dissemination in time and space of lesions in the CNS, and stress the need for no better explanation for the presentation. The following changes were made: in patients with a typical clinically isolated syndrome and clinical or MRI demonstration of dissemination in space, the presence of CSF-specific oligoclonal bands allows a diagnosis of multiple sclerosis; symptomatic lesions can be used to demonstrate dissemination in space or time in patients with supratentorial, infratentorial, or spinal cord syndrome; and cortical lesions can be used to demonstrate dissemination in space. Research to further refine the criteria should focus on optic nerve involvement, validation in diverse populations, and incorporation of advanced imaging, neurophysiological, and body fluid markers.