The familial risk and heritability of multiple sclerosis and its onset phenotypes: A case-control study.

BACKGROUND: The two main phenotypes of multiple sclerosis (MS), primary progressive (PPMS) and relapsing Onset (ROMS), show clinical and demographic differences suggesting possible differential risk mechanisms. Understanding the heritable features of these phenotypes could provide aetiological insight. OBJECTIVES: To evaluate the magnitude of familial components in PPMS and ROMS and to estimate the heritability of disease phenotypes. METHODS: We used data from 25,186 MS patients of Nordic ancestry from the Swedish MS Registry between 1987 and 2019 with known disease phenotype (1593 PPMS and 16,718 ROMS) and 251,881 matched population-based controls and 3,364,646 relatives of cases and controls. Heritability was calculated using threshold-liability models. For familial odds ratios (ORs), logistic regression with robust sandwich estimator was utilized. RESULTS: The OR of MS diagnosis in those with a first-degree family member with ROMS was 7.00 and 8.06 in those with PPMS. The corresponding ORs for having a second-degree family member with ROMS was 2.16 and 2.18 in PPMS. The additive genetic effect in ROMS was 0.54 and 0.22 in PPMS. CONCLUSION: Risk of MS increases by several folds in those with a relative with MS. The likelihood of developing either disease phenotype appears independent of genetic predisposition.

A multiple sclerosis disease progression measure based on cumulative disability.

BACKGROUND: Existing severity measurements in multiple sclerosis (MS) are often cross-sectional, making longitudinal comparisons of disease course between individuals difficult. OBJECTIVE: The objective of this study is to create a severity metric that can reliably summarize a patient's disease course. METHODS: We developed the nARMSS - normalized ARMSS (age-related MS severity score) over follow-up, using the deviation of individual ARMSS scores from the expected value and integrated over the corresponding time period. The nARMSS scales from -5 to +5; a positive value indicates a more severe disease course for a patient when compared to other patients with similar disease timings. RESULTS: Using Swedish MS registry data, the nARMSS was tested using data at 2 and 4 years of follow-up to predict the most severe quartile during the subsequent period up to 10 years total follow-up. The metric used was area under the curve of the receiver operating characteristic (AUC-ROC). This resulted in measurements of 0.929 and 0.941. In an external Canadian validation cohort, the equivalent AUC-ROCs were 0.901 and 0.908. CONCLUSION: The nARMSS provides a reliable, generalizable and easily measurable metric which makes longitudinal comparison of disease course between individuals feasible.

Accurate classification of secondary progression in multiple sclerosis using a decision tree.

BACKGROUND: The absence of reliable imaging or biological markers of phenotype transition in multiple sclerosis (MS) makes assignment of current phenotype status difficult. OBJECTIVE: The authors sought to determine whether clinical information can be used to accurately assign current disease phenotypes. METHODS: Data from the clinical visits of 14,387 MS patients in Sweden were collected. Classifying algorithms based on several demographic and clinical factors were examined. Results obtained from the best classifier when predicting neurologist recorded disease classification were replicated in an independent cohort from British Columbia and were compared to a previously published algorithm and clinical judgment of three neurologists. RESULTS: A decision tree (the classifier) containing only most recently available expanded disability scale status score and age obtained 89.3% (95% confidence intervals (CIs): 88.8-89.8) classification accuracy, defined as concordance with the latest reported status. Validation in the independent cohort resulted in 82.0% (95% CI: 81.0-83.1) accuracy. A previously published classification algorithm with slight modifications achieved 77.8% (95% CI: 77.1-78.4) accuracy. With complete patient history of 100 patients, three neurologists obtained 84.3% accuracy compared with 85% for the classifier using the same data. CONCLUSION: The classifier can be used to standardize definitions of disease phenotype across different cohorts. Clinically, this model could assist neurologists by providing additional information.

A topological data analysis based classification method for multiple measurements.

BACKGROUND: Machine learning models for repeated measurements are limited. Using topological data analysis (TDA), we present a classifier for repeated measurements which samples from the data space and builds a network graph based on the data topology. A machine learning model with cross-validation is then applied for classification. When test this on three case studies, accuracy exceeds an alternative support vector machine (SVM) voting model in most situations tested, with additional benefits such as reporting data subsets with high purity along with feature values. RESULTS: For 100 examples of 3 different tree species, the model reached 80% classification accuracy after 30 datapoints, which was improved to 90% after increased sampling to 400 datapoints. The alternative SVM classifier achieved a maximum accuracy of 68.7%. Using data from 100 examples from each class of 6 different random point processes, the classifier achieved 96.8% accuracy, vastly outperforming the SVM. Using two outcomes in neuron spiking data, the TDA classifier was similarly accurate to the SVM in one case (both converged to 97.8% accuracy), but was outperformed in the other (relative accuracies 79.8% and 92.2%, respectively). CONCLUSIONS: This algorithm and software can be beneficial for repeated measurement data common in biological sciences, as both an accurate classifier and a feature selection tool.

Factors associated with and long-term outcome of benign multiple sclerosis: a nationwide cohort study.

OBJECTIVE: Benign multiple sclerosis (BMS) is often defined by the Expanded Disability Status Scale (EDSS) score of ≤3.0 after ≥15 years of disease duration. This classification's clinical relevance remains unclear as benign patients may suffer other impairments and advance towards a progressive course, prompting our objective to holistically investigate factors associated with BMS and its long-term prognosis. METHODS: Benign cases were identified in the Swedish Multiple Sclerosis registry. Baseline clinical data, demographic features and influence of multiple sclerosis (MS) major risk alleles on likelihood of benign course were investigated. Physical disability (EDSS), cognitive function (Symbol Digit Modalities Test; SDMT) and self-reported and socioeconomic differences between benign and non-benign patients were evaluated using generalised estimation equations models. RESULTS: 11222 patients (2420 benign/8802 non-benign) were included. Benign patients were more likely to be female and younger at MS onset, have fewer relapses within the first two and 5 years from onset and fully recover from the first relapse (p<0.001). No association between human leucocyte antigen (HLA) DRB1*15:01 carriership (OR: 0.97, 95% CI: 0.86 to 1.09) or HLA-A*02:01 lacking (OR: 0.99, 95% CI: 0.87 to 1.11) and benign/non-benign was found. Non-benign patients accumulated an extra 0.04 (95% CI 0.03 to 0.04, p<0.001) EDSS score/year, lost an extra 0.3 (95% CI - 0.39 to - 0.18, p<0.001) SDMT score/year and deteriorated faster in self-reported impact and socioeconomic measures (p<0.001). CONCLUSION: Patients with BMS have a better disease course as they progress more slowly at the group level in all respects. Lack of an association with major genetic risk factors indicates that MS course is most likely influenced by either environmental factor(s) or genetic factors outside the HLA region.

Importance of early treatment initiation in the clinical course of multiple sclerosis.

OBJECTIVES: The aim of this study was to identify factors influencing the long-term clinical progression of multiple sclerosis (MS). A special objective was to investigate whether early treatment decisions influence outcome. METHODS: We included 639 patients diagnosed with MS from 2001 to 2007. The median follow-up time was 99 months (8.25 years). Cox regression models were applied to identify factors correlating with the outcome variable defined as time from treatment start to irreversible score 4 of the Expanded Disability Status Scale (EDSS). RESULTS: Patients initiated on treatment later had a greater risk of reaching EDSS 4 (hazard ratio of 1.074 (95% confidence interval (CI), 1.048-1.101)), increased by 7.4% for every year of delay in treatment start after MS onset. Patients who started treatment after 3 years from MS onset reached the outcome sooner with hazard ratio of 2.64 (95% CI, 1.71-4.08) compared with the patients who started treatment within 1 year from MS onset. Baseline EDSS and age at onset were found to be predictive factors of disability progression. CONCLUSION: Early treatment initiation was associated with a better clinical outcome. In addition, we confirmed the well-established prognostic factors of late age at onset and early disability.

Age Related Multiple Sclerosis Severity Score: Disability ranked by age.

BACKGROUND: The Multiple Sclerosis Severity Score (MSSS) is obtained by normalising the Expanded Disability Status Scale (EDSS) score for disease duration and has been a valuable tool in cross-sectional studies. OBJECTIVE: To assess whether use of age rather than the inherently ambiguous disease duration was a feasible approach. METHOD: We pooled disability data from three population-based cohorts and developed an Age Related Multiple Sclerosis Severity (ARMSS) score by ranking EDSS scores based on the patient's age at the time of assessment. We established the power to detect a difference between groups afforded by the ARMSS score and assessed its relative consistency over time. RESULTS: The study population included 26058 patients from Sweden ( n = 11846), Canada ( n = 6179) and the United Kingdom ( n = 8033). There was a moderate correlation between EDSS and disease duration ( r = 0.46, 95% confidence interval (CI): 0.45-0.47) and between EDSS and age ( r = 0.44, 95% CI: 0.43-0.45). The ARMSS scores showed comparable power to detect disability differences between groups to the updated and original MSSS. CONCLUSION: Since age is typically unbiased and readily obtained, and the ARMSS and MSSS were comparable, the ARMSS may provide a more versatile tool and could minimise study biases and loss of statistical power caused by inaccurate or missing onset dates.

Modest familial risks for multiple sclerosis: a registry-based study of the population of Sweden.

Data on familial recurrence rates of complex diseases such as multiple sclerosis give important hints to aetiological factors such as the importance of genes and environment. By linking national registries, we sought to avoid common limitations of clinic-based studies such as low numbers, poor representation of the population and selection bias. Through the Swedish Multiple Sclerosis Registry and a nationwide hospital registry, a total of 28 396 patients with multiple sclerosis were identified. We used the national Multi-Generation Registry to identify first and second degree relatives as well as cousins, and the Swedish Twin Registry to identify twins of patients with multiple sclerosis. Crude and age corrected familial risks were estimated for cases and found to be in the same range as previously published figures. Matched population-based controls were used to calculate relative risks, revealing lower estimates of familial multiple sclerosis risks than previously reported, with a sibling recurrence risk (λs = 7.1; 95% confidence interval: 6.42-7.86). Surprisingly, despite a well-established lower prevalence of multiple sclerosis amongst males, the relative risks were equal among maternal and paternal relations. A previously reported increased risk in maternal relations could thus not be replicated. An observed higher transmission rate from fathers to sons compared with mothers to sons suggested a higher transmission to offspring from the less prevalent sex; therefore, presence of the so-called 'Carter effect' could not be excluded. We estimated the heritability of multiple sclerosis using 74 757 twin pairs with known zygosity, of which 315 were affected with multiple sclerosis, and added information from 2.5 million sibling pairs to increase power. The heritability was estimated to be 0.64 (0.36-0.76), whereas the shared environmental component was estimated to be 0.01 (0.00-0.18). In summary, whereas multiple sclerosis is to a great extent an inherited trait, the familial relative risks may be lower than usually reported.

Changes to anti-JCV antibody levels in a Swedish national MS cohort.

BACKGROUND: The anti-JC virus (JCV) antibody status has been introduced to stratify patients with multiple sclerosis (MS) for higher or lower risk of progressive multifocal leukoencephalopathy (PML). OBJECTIVE: To assess the potential utility of anti-JCV antibody levels for earlier diagnosis or prediction of PML. METHODS: An analytically validated antibody assay was used to determine serological status, normalised optical density values, and dilution titres for anti-JCV antibodies. The method was applied to stored sera of 1157 patients with MS including five cases of PML, all enrolled in the Swedish pharmacovigilance study for natalizumab (NAT). Anticytomegalovirus (CMV) and antivaricella-zoster (VZV) antibody levels served as controls. RESULTS: Prior to treatment with NAT, anti-JCV antibody levels were stable in the anti-JCV positive patients. During therapy, a slight decrease in anti-JCV and anti-VZV antibody levels, but not anti-CMV antibody levels, was observed. All five patients who developed PML showed a mild to moderate increase in anti-JCV antibody levels at time of PML diagnosis; pre-PML samples suggested that this increase might start already prior to diagnosis of PML. CONCLUSIONS: Treatment initiation with NAT may lead to a slight decrease in anti-JCV and anti-VZV antibody levels, suggestive of a mild suppressive effect of NAT on antibody levels. Our findings in five cases of PML demonstrate that the onset of PML can be accompanied by increasing anti-JCV antibodies in serum. Monitoring of anti-JCV antibody levels could potentially be used as a tool for prediction or earlier diagnosis of PML during NAT treatment for MS. Further studies are warranted.

The impact of healthcare systems on the clinical diagnosis and disease-modifying treatment usage in relapse-onset multiple sclerosis: a real-world perspective in five registries across Europe.

Introduction: Prescribing guidance for disease-modifying treatment (DMT) in multiple sclerosis (MS) is centred on a clinical diagnosis of relapsing-remitting MS (RRMS). DMT prescription guidelines and monitoring vary across countries. Standardising the approach to diagnosis of disease course, for example, assigning RRMS or secondary progressive MS (SPMS) diagnoses, allows examination of the impact of health system characteristics on the stated clinical diagnosis and treatment access. Methods: We analysed registry data from six cohorts in five countries (Czech Republic, Denmark, Germany, Sweden and United Kingdom) on patients with an initial diagnosis of RRMS. We standardised our approach utilising a pre-existing algorithm (DecisionTree, DT) to determine patient diagnoses of RRMS or secondary progressive MS (SPMS). We identified five global drivers of DMT prescribing: Provision, Availability, Funding, Monitoring and Audit, data were analysed against these concepts using meta-analysis and univariate meta-regression. Results: In 64,235 patients, we found variations in DMT use between countries, with higher usage in RRMS and lower usage in SPMS, with correspondingly lower usage in the UK compared to other registers. Factors such as female gender (p = 0.041), increasing disability via Expanded Disability Status Scale (EDSS) score (p = 0.004), and the presence of monitoring (p = 0.029) in SPMS influenced the likelihood of receiving DMTs. Standardising the diagnosis revealed differences in reclassification rates from clinical RRMS to DT-SPMS, with Sweden having the lowest rate Sweden (Sweden 0.009, range: Denmark 0.103 - UK portal 0.311). Those with higher EDSS at index (p < 0.03) and female gender (p < 0.049) were more likely to be reclassified from RRMS to DT-SPMS. The study also explored the impact of diagnosis on DMT usage in clinical SPMS, finding that the prescribing environment and auditing practices affected access to treatment. Discussion: This highlights the importance of a healthcare system's approach to verifying the clinical label of MS course in facilitating appropriate prescribing, with some flexibility allowed in uncertain cases to ensure continued access to treatment.