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12 results on '"Mccombe P."'

1. Delay from treatment start to full effect of immunotherapies for multiple sclerosis.

Author

Roos I, Leray E, Frascoli F, Casey R, Brown JWL, Horakova D, Havrdova EK, Trojano M, Patti F, Izquierdo G, Eichau S, Onofrj M, Lugaresi A, Prat A, Girard M, Grammond P, Sola P, Ferraro D, Ozakbas S, Bergamaschi R, Sá MJ, Cartechini E, Boz C, Granella F, Hupperts R, Terzi M, Lechner-Scott J, Spitaleri D, Van Pesch V, Soysal A, Olascoaga J, Prevost J, Aguera-Morales E, Slee M, Csepany T, Turkoglu R, Sidhom Y, Gouider R, Van Wijmeersch B, McCombe P, Macdonell R, Coles A, Malpas CB, Butzkueven H, Vukusic S, and Kalincik T

Subjects
Adult, Cohort Studies, Female, Follow-Up Studies, Humans, Male, Middle Aged, Multiple Sclerosis diagnostic imaging, Natalizumab administration & dosage, Prospective Studies, Registries, Time Factors, Treatment Outcome, Disease Progression, Immunologic Factors administration & dosage, Immunosuppressive Agents administration & dosage, Multiple Sclerosis drug therapy, Multiple Sclerosis physiopathology
Abstract

In multiple sclerosis, treatment start or switch is prompted by evidence of disease activity. Whilst immunomodulatory therapies reduce disease activity, the time required to attain maximal effect is unclear. In this study we aimed to develop a method that allows identification of the time to manifest fully and clinically the effect of multiple sclerosis treatments ('therapeutic lag') on clinical disease activity represented by relapses and progression-of-disability events. Data from two multiple sclerosis registries, MSBase (multinational) and OFSEP (French), were used. Patients diagnosed with multiple sclerosis, minimum 1-year exposure to treatment, minimum 3-year pretreatment follow-up and yearly review were included in the analysis. For analysis of disability progression, all events in the subsequent 5-year period were included. Density curves, representing incidence of relapses and 6-month confirmed progression events, were separately constructed for each sufficiently represented therapy. Monte Carlo simulations were performed to identify the first local minimum of the first derivative after treatment start; this point represented the point of stabilization of treatment effect, after the maximum treatment effect was observed. The method was developed in a discovery cohort (MSBase), and externally validated in a separate, non-overlapping cohort (OFSEP). A merged MSBase-OFSEP cohort was used for all subsequent analyses. Annualized relapse rates were compared in the time before treatment start and after the stabilization of treatment effect following commencement of each therapy. We identified 11 180 eligible treatment epochs for analysis of relapses and 4088 treatment epochs for disability progression. External validation was performed in four therapies, with no significant difference in the bootstrapped mean differences in therapeutic lag duration between registries. The duration of therapeutic lag for relapses was calculated for 10 therapies and ranged between 12 and 30 weeks. The duration of therapeutic lag for disability progression was calculated for seven therapies and ranged between 30 and 70 weeks. Significant differences in the pre- versus post-treatment annualized relapse rate were present for all therapies apart from intramuscular interferon beta-1a. In conclusion we have developed, and externally validated, a method to objectively quantify the duration of therapeutic lag on relapses and disability progression in different therapies in patients more than 3 years from multiple sclerosis onset. Objectively defined periods of expected therapeutic lag allows insights into the evaluation of treatment response in randomized clinical trials and may guide clinical decision-making in patients who experience early on-treatment disease activity. This method will subsequently be applied in studies that evaluate the effect of patient and disease characteristics on therapeutic lag., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Published
2020
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2. Early clinical markers of aggressive multiple sclerosis.

Author

Malpas CB, Manouchehrinia A, Sharmin S, Roos I, Horakova D, Havrdova EK, Trojano M, Izquierdo G, Eichau S, Bergamaschi R, Sola P, Ferraro D, Lugaresi A, Prat A, Girard M, Duquette P, Grammond P, Grand'Maison F, Ozakbas S, Van Pesch V, Granella F, Hupperts R, Pucci E, Boz C, Sidhom Y, Gouider R, Spitaleri D, Soysal A, Petersen T, Verheul F, Karabudak R, Turkoglu R, Ramo-Tello C, Terzi M, Cristiano E, Slee M, McCombe P, Macdonell R, Fragoso Y, Olascoaga J, Altintas A, Olsson T, Butzkueven H, Hillert J, and Kalincik T

Subjects
Adult, Age of Onset, Disability Evaluation, Female, Humans, Male, Sensitivity and Specificity, Disease Progression, Multiple Sclerosis, Severity of Illness Index
Abstract

Patients with the 'aggressive' form of multiple sclerosis accrue disability at an accelerated rate, typically reaching Expanded Disability Status Score (EDSS) ≥ 6 within 10 years of symptom onset. Several clinicodemographic factors have been associated with aggressive multiple sclerosis, but less research has focused on clinical markers that are present in the first year of disease. The development of early predictive models of aggressive multiple sclerosis is essential to optimize treatment in this multiple sclerosis subtype. We evaluated whether patients who will develop aggressive multiple sclerosis can be identified based on early clinical markers. We then replicated this analysis in an independent cohort. Patient data were obtained from the MSBase observational study. Inclusion criteria were (i) first recorded disability score (EDSS) within 12 months of symptom onset; (ii) at least two recorded EDSS scores; and (iii) at least 10 years of observation time, based on time of last recorded EDSS score. Patients were classified as having 'aggressive multiple sclerosis' if all of the following criteria were met: (i) EDSS ≥ 6 reached within 10 years of symptom onset; (ii) EDSS ≥ 6 confirmed and sustained over ≥6 months; and (iii) EDSS ≥ 6 sustained until the end of follow-up. Clinical predictors included patient variables (sex, age at onset, baseline EDSS, disease duration at first visit) and recorded relapses in the first 12 months since disease onset (count, pyramidal signs, bowel-bladder symptoms, cerebellar signs, incomplete relapse recovery, steroid administration, hospitalization). Predictors were evaluated using Bayesian model averaging. Independent validation was performed using data from the Swedish Multiple Sclerosis Registry. Of the 2403 patients identified, 145 were classified as having aggressive multiple sclerosis (6%). Bayesian model averaging identified three statistical predictors: age > 35 at symptom onset, EDSS ≥ 3 in the first year, and the presence of pyramidal signs in the first year. This model significantly predicted aggressive multiple sclerosis [area under the curve (AUC) = 0.80, 95% confidence intervals (CIs): 0.75, 0.84, positive predictive value = 0.15, negative predictive value = 0.98]. The presence of all three signs was strongly predictive, with 32% of such patients meeting aggressive disease criteria. The absence of all three signs was associated with a 1.4% risk. Of the 556 eligible patients in the Swedish Multiple Sclerosis Registry cohort, 34 (6%) met criteria for aggressive multiple sclerosis. The combination of all three signs was also predictive in this cohort (AUC = 0.75, 95% CIs: 0.66, 0.84, positive predictive value = 0.15, negative predictive value = 0.97). Taken together, these findings suggest that older age at symptom onset, greater disability during the first year, and pyramidal signs in the first year are early indicators of aggressive multiple sclerosis., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Published
2020
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3. Clinical and therapeutic predictors of disease outcomes in AQP4-IgG+ neuromyelitis optica spectrum disorder.

Author

Kunchok A, Malpas C, Nytrova P, Havrdova EK, Alroughani R, Terzi M, Yamout B, Hor JY, Karabudak R, Boz C, Ozakbas S, Olascoaga J, Simo M, Granella F, Patti F, McCombe P, Csepany T, Singhal B, Bergamaschi R, Fragoso Y, Al-Harbi T, Turkoglu R, Lechner-Scott J, Laureys G, Oreja-Guevara C, Pucci E, Sola P, Ferraro D, Altintas A, Soysal A, Vucic S, Grand'Maison F, Izquierdo G, Eichau S, Lugaresi A, Onofrj M, Trojano M, Marriott M, Butzkueven H, Kister I, and Kalincik T

Subjects
Adult, Age Factors, Azathioprine pharmacology, Female, Follow-Up Studies, Humans, Immunoglobulin G, Male, Middle Aged, Mycophenolic Acid pharmacology, Recurrence, Rituximab pharmacology, Time Factors, Aquaporin 4 immunology, Disease Progression, Immunologic Factors pharmacology, Neuromyelitis Optica drug therapy, Neuromyelitis Optica immunology, Neuromyelitis Optica physiopathology, Outcome Assessment, Health Care, Registries, Severity of Illness Index
Abstract

Background: Aquaporin-4-IgG positive (AQP4-IgG+) Neuromyelitis Optica Spectrum Disorder (NMOSD) is an uncommon central nervous system autoimmune disorder. Disease outcomes in AQP4-IgG+NMOSD are typically measured by relapse rate and disability. Using the MSBase, a multi-centre international registry, we aimed to examine the impact immunosuppressive therapies and patient characteristics as predictors of disease outcome measures in AQP4-IgG+NMOSD., Method: This MSBase cohort study of AQP4-IgG+NMOSD patients examined modifiers of relapse in a multivariable proportional hazards model and expanded disability status score (EDSS) using a mixed effects model., Results: 206 AQP4-IgG+ patients were included (median follow-up 3.7 years). Age (hazard ratio [HR] = 0.82 per decade, p = 0.001), brainstem onset (HR = 0.45, p = 0.009), azathioprine (HR = 0.46, p<0.001) and mycophenolate mofetil (HR = 0.09, p = 0.012) were associated with a reduced risk of relapse. A greater EDSS was associated with age (β = 0.45 (per decade), p<0.001) and disease duration (β = 0.07 per year, p<0.001). A slower increase in EDSS was associated with azathioprine (β = -0.48, p<0.001), mycophenolate mofetil (β = -0.69, p = 0.04) and rituximab (β = -0.35, p = 0.024)., Interpretation: This study has demonstrated that azathioprine and mycophenolate mofetil reduce the risk of relapses and disability progression is modified by azathioprine, mycophenolate mofetil and rituximab. Age and disease duration were the only patient characteristics that modified the risk of relapse and disability in our cohort., Competing Interests: Declaration of Competing Interest The authors declare no competing interests directly related to the presented work., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Published
2020
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4. Risk of secondary progressive multiple sclerosis: A longitudinal study.

Author

Fambiatos A, Jokubaitis V, Horakova D, Kubala Havrdova E, Trojano M, Prat A, Girard M, Duquette P, Lugaresi A, Izquierdo G, Grand'Maison F, Grammond P, Sola P, Ferraro D, Alroughani R, Terzi M, Hupperts R, Boz C, Lechner-Scott J, Pucci E, Bergamaschi R, Van Pesch V, Ozakbas S, Granella F, Turkoglu R, Iuliano G, Spitaleri D, McCombe P, Solaro C, Slee M, Ampapa R, Soysal A, Petersen T, Sanchez-Menoyo JL, Verheul F, Prevost J, Sidhom Y, Van Wijmeersch B, Vucic S, Cristiano E, Saladino ML, Deri N, Barnett M, Olascoaga J, Moore F, Skibina O, Gray O, Fragoso Y, Yamout B, Shaw C, Singhal B, Shuey N, Hodgkinson S, Altintas A, Al-Harbi T, Csepany T, Taylor B, Hughes J, Jun JK, van der Walt A, Spelman T, Butzkueven H, and Kalincik T

Subjects
Adult, Female, Humans, Longitudinal Studies, Male, Multiple Sclerosis, Chronic Progressive drug therapy, Multiple Sclerosis, Chronic Progressive physiopathology, Multiple Sclerosis, Relapsing-Remitting drug therapy, Multiple Sclerosis, Relapsing-Remitting physiopathology, Risk, Disease Progression, Immunologic Factors pharmacology, Multiple Sclerosis, Chronic Progressive epidemiology, Multiple Sclerosis, Relapsing-Remitting epidemiology, Severity of Illness Index
Abstract

Background: The risk factors for conversion from relapsing-remitting to secondary progressive multiple sclerosis remain highly contested., Objective: The aim of this study was to determine the demographic, clinical and paraclinical features that influence the risk of conversion to secondary progressive multiple sclerosis., Methods: Patients with adult-onset relapsing-remitting multiple sclerosis and at least four recorded disability scores were selected from MSBase, a global observational cohort. The risk of conversion to objectively defined secondary progressive multiple sclerosis was evaluated at multiple time points per patient using multivariable marginal Cox regression models. Sensitivity analyses were performed., Results: A total of 15,717 patients were included in the primary analysis. Older age (hazard ratio (HR) = 1.02, p  < 0.001), longer disease duration (HR = 1.01, p  = 0.038), a higher Expanded Disability Status Scale score (HR = 1.30, p  < 0.001), more rapid disability trajectory (HR = 2.82, p  < 0.001) and greater number of relapses in the previous year (HR = 1.07, p  = 0.010) were independently associated with an increased risk of secondary progressive multiple sclerosis. Improving disability (HR = 0.62, p  = 0.039) and disease-modifying therapy exposure (HR = 0.71, p  = 0.007) were associated with a lower risk. Recent cerebral magnetic resonance imaging activity, evidence of spinal cord lesions and oligoclonal bands in the cerebrospinal fluid were not associated with the risk of conversion., Conclusion: Risk of secondary progressive multiple sclerosis increases with age, duration of illness and worsening disability and decreases with improving disability. Therapy may delay the onset of secondary progression.

Published
2020
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5. Identification and outcomes of clinical phenotypes in amyotrophic lateral sclerosis/motor neuron disease: Australian National Motor Neuron Disease observational cohort.

Author

Talman P, Duong T, Vucic S, Mathers S, Venkatesh S, Henderson R, Rowe D, Schultz D, Edis R, Needham M, Macdonnell R, McCombe P, Birks C, and Kiernan M

Subjects
Amyotrophic Lateral Sclerosis classification, Australia, Female, Gastrostomy statistics & numerical data, Humans, Kaplan-Meier Estimate, Male, Middle Aged, Neuroprotective Agents therapeutic use, Noninvasive Ventilation statistics & numerical data, Phenotype, Prospective Studies, Registries, Riluzole therapeutic use, Time Factors, Amyotrophic Lateral Sclerosis mortality, Amyotrophic Lateral Sclerosis therapy, Disease Progression
Abstract

Objective: To capture the clinical patterns, timing of key milestones and survival of patients presenting with amyotrophic lateral sclerosis/motor neuron disease (ALS/MND) within Australia., Methods: Data were prospectively collected and were timed to normal clinical assessments. An initial registration clinical report form (CRF) and subsequent ongoing assessment CRFs were submitted with a completion CRF at the time of death., Design: Prospective observational cohort study., Participants: 1834 patients with a diagnosis of ALS/MND were registered and followed in ALS/MND clinics between 2005 and 2015., Results: 5 major clinical phenotypes were determined and included ALS bulbar onset, ALS cervical onset and ALS lumbar onset, flail arm and leg and primary lateral sclerosis (PLS). Of the 1834 registered patients, 1677 (90%) could be allocated a clinical phenotype. ALS bulbar onset had a significantly lower length of survival when compared with all other clinical phenotypes (p<0.004). There were delays in the median time to diagnosis of up to 12 months for the ALS phenotypes, 18 months for the flail limb phenotypes and 19 months for PLS. Riluzole treatment was started in 78-85% of cases. The median delays in initiating riluzole therapy, from symptom onset, varied from 10 to 12 months in the ALS phenotypes and 15-18 months in the flail limb phenotypes. Percutaneous endoscopic gastrostomy was implemented in 8-36% of ALS phenotypes and 2-9% of the flail phenotypes. Non-invasive ventilation was started in 16-22% of ALS phenotypes and 21-29% of flail phenotypes., Conclusions: The establishment of a cohort registry for ALS/MND is able to determine clinical phenotypes, survival and monitor time to key milestones in disease progression. It is intended to expand the cohort to a more population-based registry using opt-out methodology and facilitate data linkage to other national registries., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Published
2016
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6. Defining secondary progressive multiple sclerosis.

Author

Lorscheider J, Buzzard K, Jokubaitis V, Spelman T, Havrdova E, Horakova D, Trojano M, Izquierdo G, Girard M, Duquette P, Prat A, Lugaresi A, Grand'Maison F, Grammond P, Hupperts R, Alroughani R, Sola P, Boz C, Pucci E, Lechner-Scott J, Bergamaschi R, Oreja-Guevara C, Iuliano G, Van Pesch V, Granella F, Ramo-Tello C, Spitaleri D, Petersen T, Slee M, Verheul F, Ampapa R, Amato MP, McCombe P, Vucic S, Sánchez Menoyo JL, Cristiano E, Barnett MH, Hodgkinson S, Olascoaga J, Saladino ML, Gray O, Shaw C, Moore F, Butzkueven H, and Kalincik T

Subjects
Adult, Cohort Studies, Consensus, Female, Humans, Male, Middle Aged, Multiple Sclerosis, Chronic Progressive physiopathology, Disease Progression, Multiple Sclerosis, Chronic Progressive diagnosis, Severity of Illness Index
Abstract

A number of studies have been conducted with the onset of secondary progressive multiple sclerosis as an inclusion criterion or an outcome of interest. However, a standardized objective definition of secondary progressive multiple sclerosis has been lacking. The aim of this work was to evaluate the accuracy and feasibility of an objective definition for secondary progressive multiple sclerosis, to enable comparability of future research studies. Using MSBase, a large, prospectively acquired, global cohort study, we analysed the accuracy of 576 data-derived onset definitions for secondary progressive multiple sclerosis and first compared these to a consensus opinion of three neurologists. All definitions were then evaluated against 5-year disease outcomes post-assignment of secondary progressive multiple sclerosis: sustained disability, subsequent sustained progression, positive disability trajectory, and accumulation of severe disability. The five best performing definitions were further investigated for their timeliness and overall disability burden. A total of 17 356 patients were analysed. The best definition included a 3-strata progression magnitude in the absence of a relapse, confirmed after 3 months within the leading Functional System and required an Expanded Disability Status Scale step ≥4 and pyramidal score ≥2. It reached an accuracy of 87% compared to the consensus diagnosis. Seventy-eight per cent of the identified patients showed a positive disability trajectory and 70% reached significant disability after 5 years. The time until half of all patients were diagnosed was 32.6 years (95% confidence interval 32-33.6) after disease onset compared with the physicians' diagnosis at 36 (35-39) years. The identified patients experienced a greater disease burden [median annualized area under the disability-time curve 4.7 (quartiles 3.6, 6.0)] versus non-progressive patients [1.8 (1.2, 1.9)]. This objective definition of secondary progressive multiple sclerosis based on the Expanded Disability Status Scale and information about preceding relapses provides a tool for a reproducible, accurate and timely diagnosis that requires a very short confirmation period. If applied broadly, the definition has the potential to strengthen the design and improve comparability of clinical trials and observational studies in secondary progressive multiple sclerosis., (© The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Published
2016
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7. Functional characterisation of the amyotrophic lateral sclerosis risk locus GPX3/TNIP1

Author

Restuadi, Restuadi, Steyn, Frederik J, Kabashi, Edor, Ngo, Shyuan T, Cheng, Fei-Fei, Nabais, Marta F, Thompson, Mike J, Qi, Ting, Wu, Yang, Henders, Anjali K, Wallace, Leanne, Bye, Chris R, Turner, Bradley J, Ziser, Laura, Mathers, Susan, McCombe, Pamela A, Needham, Merrilee, Schultz, David, Kiernan, Matthew C, van Rheenen, Wouter, van den Berg, Leonard H, Veldink, Jan H, Ophoff, Roel, Gusev, Alexander, Zaitlen, Noah, McRae, Allan F, Henderson, Robert D, Wray, Naomi R, Giacomotto, Jean, and Garton, Fleur C

Subjects
Biological Sciences, Genetics, ALS, Neurodegenerative, Human Genome, Neurosciences, Rare Diseases, Brain Disorders, 2.1 Biological and endogenous factors, Neurological, Amyotrophic Lateral Sclerosis, Animals, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Neurodegenerative Diseases, Polymorphism, Single Nucleotide, Zebrafish, Motor neurone disease, MND, Genome-wide association study, Computational biology, Neurodegenerative diseases, Quantitative trait loci, Genes, Regulator, Disease progression, Clinical Sciences
Abstract

BackgroundAmyotrophic lateral sclerosis (ALS) is a complex, late-onset, neurodegenerative disease with a genetic contribution to disease liability. Genome-wide association studies (GWAS) have identified ten risk loci to date, including the TNIP1/GPX3 locus on chromosome five. Given association analysis data alone cannot determine the most plausible risk gene for this locus, we undertook a comprehensive suite of in silico, in vivo and in vitro studies to address this.MethodsThe Functional Mapping and Annotation (FUMA) pipeline and five tools (conditional and joint analysis (GCTA-COJO), Stratified Linkage Disequilibrium Score Regression (S-LDSC), Polygenic Priority Scoring (PoPS), Summary-based Mendelian Randomisation (SMR-HEIDI) and transcriptome-wide association study (TWAS) analyses) were used to perform bioinformatic integration of GWAS data (Ncases = 20,806, Ncontrols = 59,804) with 'omics reference datasets including the blood (eQTLgen consortium N = 31,684) and brain (N = 2581). This was followed up by specific expression studies in ALS case-control cohorts (microarray Ntotal = 942, protein Ntotal = 300) and gene knockdown (KD) studies of human neuronal iPSC cells and zebrafish-morpholinos (MO).ResultsSMR analyses implicated both TNIP1 and GPX3 (p < 1.15 × 10-6), but there was no simple SNP/expression relationship. Integrating multiple datasets using PoPS supported GPX3 but not TNIP1. In vivo expression analyses from blood in ALS cases identified that lower GPX3 expression correlated with a more progressed disease (ALS functional rating score, p = 5.5 × 10-3, adjusted R2 = 0.042, Beffect = 27.4 ± 13.3 ng/ml/ALSFRS unit) with microarray and protein data suggesting lower expression with risk allele (recessive model p = 0.06, p = 0.02 respectively). Validation in vivo indicated gpx3 KD caused significant motor deficits in zebrafish-MO (mean difference vs. control ± 95% CI, vs. control, swim distance = 112 ± 28 mm, time = 1.29 ± 0.59 s, speed = 32.0 ± 2.53 mm/s, respectively, p for all

Published
2022

8. Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Author

Rheenen, Wouter van, Spek, Rick A. A. van der, Bakker, Mark K., Vugt, Joke J. F. A. van, Hop, Paul J., Zwamborn, Ramona A. J., Klein, Niek de, Westra, Harm Jan, Bakker, Olivier B., Deelen, Patrick, Shireby, Gemma, Needham, Merrilee, Ceroni, Mauro, Simoncini, Costanza, Gagliardi, Stella, Corrado, Lucia, Garton, Fleur C., Mazzini, Letizia, Westeneng, Henk Jan, Ross, Jay P., Valluzzi, Francesco, Aguggia, Marco, Raggi, Flavia, Rini, Augusto, Traynor, Bryan J., Singleton, Andrew B., Ngo, Shyuan T., Corcia, Philippe, Olsen, Catherine M., Hofman, Albert, Van Eijk, Kristel R., Pasterkamp, R. Jeroen, Tittmann, Lukas, Iacoangeli, Alfredo, Mitne Neto, Miguel, Sproviero, Daisy, Cauchi, Ruben J., Ophoff, Roel A., Wiedau Pazos, Martina, Lomen-Hoerth, Catherine, Deerlin, Vivianna M. van, Nicholson, Garth A., Brylev, Lev, Whiteman, David C., Grosskreutz, Julian, Fan, Dongsheng, Couratier, Philippe, Roediger, Annekathrin, Gaur, Nayana, D’alfonso, Sandra, Uitterlinden, André G., Pamphlett, Roger, Fominykh, Vera, Byrne, Ross P., Lieb, Wolfgang, Iazzolino, Barbara, Dekker, Annelot M., Slap Consortium, Demeshonok, Vera, Millecamps, Stéphanie, Ataulina, Anastasia, Rogelj, Boris, Koritnik, Blaž, Zidar, Janez, Ravnik-Glavač, Metka, Franke, Andre, Mcrae, Allan F., Rowe, Dominic B., Peotta, Laura, Cooper-Knock, Johnathan, Glavač, Damjan, Doherty, Mark, Rietschel, Marcella, Stević, Zorica, Drory, Vivian, Meininger, Vincent, Zarrelli, Michele, Povedano, Monica, Gaunt, Tom R., Steyn, Frederik J., Williams, Kelly L., Smith, Bradley N., Cugnasco, Paolo, Papurello, Diego Maria, Nozzoli, Cecilia, Sorarù, Gianni, Mather, Karen A., Ripke, Stephan, Nöthen, Markus M., Sachdev, Perminder S., Henders, Anjali K., Wallace, Leanne, Carvalho, Mamede de, Gromicho, Marta, Pinto, Susana, Marco, Giovanni de, Al Khleifat, Ahmad, Eberle, Michael A., Braun, Alice, Gusmaroli, Graziano, Siciliano, Gabriele, Petri, Susanne, Breen, Gerome, Weber, Markus, Rouleau, Guy A., Rojas García, Ricardo, Silani, Vincenzo, Amouyel, Philippe, Ghiglione, Paolo, Davey Smith, George, Curtis, Charles J., Shatunov, Aleksey, Mill, Jonathan, Mclaughlin, Russell L., Filosto, Massimiliano, Comi, Cristoforo, Gerfo, Annalisa lo, Ferlini, Alessandra, Riva, Nilo, Mora Pardina, Jesus S., Chiveri, Luca, Hardiman, Orla, Torrieri, Maria Claudia, Kenna, Kevin P., Wray, Naomi R., Tsai, Ellen, Runz, Heiko, Franke, Lude, Padovani, Alessandro, Chandran, Siddharthan, Al Chalabi, Ammar, Assialioui, Abdelilah, Labate, Carmelo, Damme, Philip van, Ticozzi, Nicola, Palumbo, Francesca, Inghilleri, Maurizio, Chiò, Adriano, Pal, Suvankar, Lunetta, Christian, Jörk, Alexander, Cichon, Sven, Kraft, Julia, Morrison, Karen E., Ruiz, Luigi, Shaw, Pamela J., Hardy, John, Orrell, Richard W., Sendtner, Michael, Meyer, Thomas, Dion, Patrick A., Calvo, Andrea, Kooyman, Maarten, Başak, Nazli, Gerardi, Francesca, Simone, Isabella L., Kooi, Anneke J. van der, Ratti, Antonia, Ferrandi, Delfina, Fogh, Isabella, Ludolph, Albert C., Moglia, Cristina, Brunetti, Maura, Diamanti, Luca, Barthel, Tabea, Blair, Ian P., Es, Michael A. van, Gallone, Salvatore, Canosa, Antonio, Guerra, Vito, Grassano, Maurizio, Beghi, Ettore, Pupillo, Elisabetta, Logroscino, Giancarlo, Ferrarese, Carlo, Nefussy, Beatrice, Theele, Erik, Rinaldi, Fabrizio, Weishaupt, Jochen H., Kiernan, Matthew C., Barberis, Marco, Osmanovic, Alma, Baloh, Robert H., Nordin, Angelica, Lerner, Yossef, Vito, Nicoletta di, Zabari, Michal, Zoccolella, Stefano, Heverin, Mark, Gotkine, Marc, Guaita, Maria Cristina, Brenner, David, Freischmidt, Axel, Sbaiz, Luca, Benyamin, Beben, Glass, Jonathan D., Landers, John E., Tazelaar, Gijs H. P., Rota, Eugenia, Bensimon, Gilbert, Ilse, Benjamin, Brice, Alexis, Durr, Alexandra, Payan, Christine A. M., Saker-Delye, Safa, Wood, Nicholas W., Gentile, Salvatore, Moisse, Matthieu, Topp, Simon, Henderson, Robert D., Rademakers, Rosa, Perrone, Patrizia, Stubendorff, Beatrice, Brown, Robert H., Restuadi, Restuadi, Tremolizzo, Lucio, Mundi, Ciro, Berg, Leonard H. van den, Passarella, Bruno, Delodovici, Maria Luisa, Furlong, Sarah, Bono, Giorgio, Manera, Umberto, Vasta, Rosario, Bombaci, Alessandro, Meineri, Piero, Mauro, Alessandro, Hannon, Eilis, Casale, Federico, Leone, Maurizio, Shaw, Christopher E., Fuda, Giuseppe, Salamone, Paolina, Mathers, Susan, Baird, Denis, Launaro, Nicola, Marchi, Fabiola de, Veldink, Jan H., Gellera, Cinzia, Salachas, François, Witte, Otto W., Andersen, Peter M., Bertolotto, Antonio, Gionco, Maurizio, Leotta, Daniela, Odddenino, Enrico, Slalom Consortium, Tamma, Filippo, Dotta, Michele, Lauria, Giuseppe, Steinbach, Robert, Imperiale, Daniele, Geda, Claudio, Dolzhenko, Egor, Cavallo, Roberto, Pignatta, Pietro, Groen, Ewout J. N., Cotelli, Maria Sofia, Mattei, Marco de, Calabrese, Gianluigi, Sapio, Alessia di, Giardini, Guido, Hübner, Christian A., Corti, Stefania, Bell, Shaughn, Comi, Giancarlo, Mccombe, Pamela A., Tiloca, Cinzia, Parals Consortium, Gawor, Klara, Peverelli, Silvia, Taroni, Franco, Pensato, Viviana, Castellotti, Barbara, Graff, Caroline, Comi, Giacomo P., Cereda, Cristina, Bo, Roberto del, Boero, Giovanni, Slagen Consortium, Vourc’h, Patrick, Stem Cell Aging Leukemia and Lymphoma (SALL), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), van Rheenen, Wouter, van der Spek, Rick AA, Bakker, Mark K, van Vugt, Joke JFA, Benyamin, Beben, Veldink, Jan H, SLALOM Consortium, PARALS Consortium, SLAGEN Consortium, SLAP Consortium, van Rheenen, W, van der Spek, R, Bakker, M, van Vugt, J, Hop, P, Zwamborn, R, de Klein, N, Westra, H, Bakker, O, Deelen, P, Shireby, G, Hannon, E, Moisse, M, Baird, D, Restuadi, R, Dolzhenko, E, Dekker, A, Gawor, K, Westeneng, H, Tazelaar, G, van Eijk, K, Kooyman, M, Byrne, R, Doherty, M, Heverin, M, Al Khleifat, A, Iacoangeli, A, Shatunov, A, Ticozzi, N, Cooper-Knock, J, Smith, B, Gromicho, M, Chandran, S, Pal, S, Morrison, K, Shaw, P, Hardy, J, Orrell, R, Sendtner, M, Meyer, T, Basak, N, van der Kooi, A, Ratti, A, Fogh, I, Gellera, C, Lauria, G, Corti, S, Cereda, C, Sproviero, D, D'Alfonso, S, Soraru, G, Siciliano, G, Filosto, M, Padovani, A, Chio, A, Calvo, A, Moglia, C, Brunetti, M, Canosa, A, Grassano, M, Beghi, E, Pupillo, E, Logroscino, G, Nefussy, B, Osmanovic, A, Nordin, A, Lerner, Y, Zabari, M, Gotkine, M, Baloh, R, Bell, S, Vourc'H, P, Corcia, P, Couratier, P, Millecamps, S, Meininger, V, Salachas, F, Mora Pardina, J, Assialioui, A, Rojas-Garcia, R, Dion, P, Ross, J, Ludolph, A, Weishaupt, J, Brenner, D, Freischmidt, A, Bensimon, G, Brice, A, Durr, A, Payan, C, Saker-Delye, S, Wood, N, Topp, S, Rademakers, R, Tittmann, L, Lieb, W, Franke, A, Ripke, S, Braun, A, Kraft, J, Whiteman, D, Olsen, C, Uitterlinden, A, Hofman, A, Rietschel, M, Cichon, S, Nothen, M, Amouyel, P, Traynor, B, Singleton, A, Mitne Neto, M, Cauchi, R, Ophoff, R, Wiedau-Pazos, M, Lomen-Hoerth, C, van Deerlin, V, Grosskreutz, J, Roediger, A, Gaur, N, Jork, A, Barthel, T, Theele, E, Ilse, B, Stubendorff, B, Witte, O, Steinbach, R, Hubner, C, Graff, C, Brylev, L, Fominykh, V, Demeshonok, V, Ataulina, A, Rogelj, B, Koritnik, B, Zidar, J, Ravnik-Glavac, M, Glavac, D, Stevic, Z, Drory, V, Povedano, M, Blair, I, Kiernan, M, Benyamin, B, Henderson, R, Furlong, S, Mathers, S, Mccombe, P, Needham, M, Ngo, S, Nicholson, G, Pamphlett, R, Rowe, D, Steyn, F, Williams, K, Mather, K, Sachdev, P, Henders, A, Wallace, L, de Carvalho, M, Pinto, S, Petri, S, Weber, M, Rouleau, G, Silani, V, Curtis, C, Breen, G, Glass, J, Brown, R, Landers, J, Shaw, C, Andersen, P, Groen, E, van Es, M, Pasterkamp, R, Fan, D, Garton, F, Mcrae, A, Davey Smith, G, Gaunt, T, Eberle, M, Mill, J, Mclaughlin, R, Hardiman, O, Kenna, K, Wray, N, Tsai, E, Runz, H, Franke, L, Al-Chalabi, A, Van Damme, P, van den Berg, L, Veldink, J, Ferrarese, C, Neurology, ANS - Neuroinfection & -inflammation, APH - Methodology, APH - Quality of Care, EURO-NMD, Internal Medicine, Epidemiology, Başak, Ayşe Nazlı (ORCID 0000-0001-9257-3540 & YÖK ID 1512), van Rheenen, W., Van der Spek, R.A.A., Bakker, M.K., van Vugt, J.J.F.A., Hop, P.J., Zwamborn, R.A.J., de Klein, N., Westra, H.J., Bakker, O.B., Deelen, P., Shireby, G., Hannon, E., Moisse, M., Baird, D., Restuadi, R., Dolzhenko, E., Dekker, A.M., Gawor, K., Westeneng, H.J., Tazelaar, G.H.P., van Eijk, K.R., Kooyman, M., Byrne, R.P., Doherty, M., Heverin, M., Al Khleifat, A., Iacoangeli, A., Shatunov, A., Ticozzi, N., Cooper-Knock, J., Smith, B.N., Gromicho, M., Chandran, S., Pal, S., Morrison, K.E., Shaw, P.J., Hardy, J., Orrell, R.W., Sendtner, M., Meyer, T., van der Kooi, A.J., Ratti, A., Fogh, I., Gellera, C., Lauria, G., Corti, S., Cereda, C., Sproviero, D., D'Alfonso, S., Sorarù, G., Siciliano, G., Filosto, M., Padovani, A., Chiò, A., Calvo, A., Moglia, C., Brunetti, M., Canosa, A., Grassano, M., Beghi, E., Pupillo, E., Logroscino, G., Nefussy, B., Osmanovic, A., Nordin, A., Lerner, Y., Zabari, M., Gotkine, M., Baloh, R.H., Bell, S., Vourc'h, P., Corcia, P., Couratier, P., Millecamps, S., Meininger, V., Salachas, F., Mora Pardina, J.S., Assialioui, A., Rojas-García, R., Dion, P.A., Ross, J.P., Ludolph, A.C., Weishaupt, J.H., Brenner, D., Freischmidt, A., Bensimon, G., Brice, A., Durr, A., Payan, C.A.M., Saker-Delye, S., Wood, N.W., Topp, S., Rademakers, R., Tittmann, L., Lieb, W., Franke, A., Ripke, S., Kraft, J.,Whiteman, David C., Olsen, Catherine M., Uitterlinden, A.G., Hofman, A., Rietschel, M., Cichon, S., Nothen, M.M., Amouyel, P., Comi, G., Riva, N., Lunetta, C., Gerardi, F., Cotelli, M.S., Rinaldi, F., Chiveri, L., Guaita, M.C., Perrone, P., Ceroni, M., Diamanti, L., Ferrarese, C., Tremolizzo, L., Delodovici, M.L., Bono, G., Manera, U., Vasta, R., Bombaci, A., Casale, F., Fuda, G., Salamone, P., Iazzolino, B., Peotta, L., Cugnasco, P., De Marco, G., Torrieri, M.C., Palumbo, F., Gallone, S., Barberis, M., Sbaiz, L., Gentile, S., Mauro, A., Mazzini, L., De Marchi, F., Corrado, L., Bertolotto, A., Gionco, M., Leotta, D., Odddenino, E., Imperiale, D., Cavallo, R., Pignatta, P., De Mattei, M., Geda, C., Papurello, D.M., Gusmaroli, G., Comi, C., Labate, C., Ruiz, L., Ferrandi, D., Rota, E., Aguggia, M., Di Vito, N., Meineri, P., Ghiglione, P., Launaro, N., Dotta, M., Di Sapio, A., Giardini, G., Tiloca, C., Peverelli, S., Taroni, F., Pensato, V., Castellotti, B., Comi, G.P., Del Bo, R., Gagliardi, S., Raggi, F., Simoncini, C., Lo Gerfo, A., Inghilleri, M., Ferlini, A., Simone, I.L., Passarella, B., Guerra, V., Zoccolella, S., Nozzoli, C., Mundi, C., Leone, M., Zarrelli, M., Tamma, F., Valluzzi, F., Calabrese, G., Boero, G., Rini, A., Traynor, B.J., Singleton, A.B., Neto, M.M., Cauchi, R.J., Ophoff, R.A., Wiedau-Pazos, M., Lomen-Hoerth, C., van Deerlin, V.M., Grosskreutz, J., Roediger, A., Gaur, N., Jork, A., Barthel, T., Theele, E., Ilse, B., Stubendorff, B., Witte, O.W., Steinbach, R., Hubner, C.A., Graff, C., Brylev, L., Fominykh, V., Demeshonok, V., Ataulina, A., Rogelj, B., Koritnik, B., Zidar, J., Ravnik-Glavac, M., Glavac, D., Stevic, Z., Drory, V., Povedano, M., Blair, I.P., Kiernan, M.C., Benyamin, B., Henderson, R.D., Furlong, S., Mathers, S., McCombe, P.A, Needham, M., Ngo, S.T., Nicholson, G.A., Pamphlett, R., Rowe, D.B., Steyn, F.J., Williams, K.L., Mather, K.A., Sachdev, P.S., Henders, A.K., Wallace, L., de Carvalho, M., Pinto, S., Petri, S., Weber, M., Rouleau, G.A., Silani, V., Curtis, C.J., Breen, G., Glass, J.D., Brown, R.H., Landers, J.E., Shaw, C.E., Andersen, P.M., Groen, E.J.N, van Es, M.A., Pasterkamp, R.J., Fan, D.S., Garton, F.C., McRae, A.F., Smith, G.D., Gaunt, T.R., Eberle, M.A., Mill, J., McLaughlin, R.L., Hardiman, O., Kenna, K.P., Wray, N.R., Tsai, E.L., Runz, H., Franke, L., Al-Chalabi, A., Van Damme, P., van den Berg, L.H., Veldink, J.H., Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM), and School of Medicine

Subjects
Male, Genetics and heredity, amyotrophic lateral sclerosis, Neurologi, Glutamine, Medizin, Genome-wide association study, Disease, SUSCEPTIBILITY, Genome-wide association studies, DISEASE, Genètica mèdica, 0302 clinical medicine, neurodegenerative disease, genome-wide association study, ALS, gene, autophagy, Risk Factors, amyotrophic lateral sclerosi, RNA-Seq, Amyotrophic lateral sclerosis, disease-modifying therapies, blood [Cholesterol], Genetics, Genetics & Heredity, Neurons, 0303 health sciences, Medical genetics, Neurodegenerative diseases, Genome-wide association, Mendelian randomization, Frontotemporal dementia, Hexanucleotide repeat, Mutant SOD1, Metaanalysis, ALS, Susceptibility, Identification, Brain, Amyotrophic Lateral Sclerosis, Cholesterol, Disease Progression, Female, Humans, Mendelian Randomization Analysis, Microsatellite Repeats, Neurodegenerative Diseases, Quantitative Trait Loci, Genome-Wide Association Study, Mutation, MUTANT SOD1, genetics [Amyotrophic Lateral Sclerosis], medicine.anatomical_structure, Neurology, risk factor, metabolism [Neurons], MENDELIAN RANDOMIZATION, nerve cell, Life Sciences & Biomedicine, quantitative trait locu, Biology, 03 medical and health sciences, Amyotrophic lateral sclerosis -- Diagnosis, blood, ddc:570, medicine, degenerative disease, Motor neuron disease, human, Genomes, GENOME-WIDE ASSOCIATION, gene, Gene, metabolism [Glutamine], METAANALYSIS, 030304 developmental biology, Mendelian randomization analysi, Science & Technology, HEXANUCLEOTIDE REPEAT, meta analysi, IDENTIFICATION, metabolism [Amyotrophic Lateral Sclerosis], FRONTOTEMPORAL DEMENTIA, medicine.disease, metabolism [Brain], genetics [Neurodegenerative Diseases], Expression quantitative trait loci, disease exacerbation, Neuron, gemone, genetic, Vesicle-mediated transport, metabolism, Nervous system -- Degeneration, Esclerosi lateral amiotròfica, 030217 neurology & neurosurgery
Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons., Dutch Research Council (NWO); VENI Scheme Grant; VIDI Grant; Prinses Beatrix Spierfonds; Neuromuscular Fellowship Grant; Medical Research Council (MRC); Clinical Infrastructure Award; Epidemiology Unit; Integrative Epidemiology Unit; Canadian Institutes of Health Research; IWT; National Institute on Aging; National Health and Medical Research Council (NHMRC); Enabling Grant; NHMRC/Australian Research Council Strategic Award; NHMRC; NHMRC Centre of Research Excellence Grant; National Health and Medical Research Council of Australia (NHMRC) Research Fellowship; United Kingdom, Medical Research Council; Economic and Social Research Council; European Union (EU); Horizon 2020; European Community's Health Seventh Framework Programme; EuroMOTOR; European Research Council (ERC); Research and Innovation Programme; EScORIAL; ALS Foundation Netherlands; Alzheimer’s Society PhD Studentship; ARSla Funding; Biogen; University of Bristol; Motor Neurone Disease Association (MNDA); NIHR Maudsley Biomedical Research Centre; Dutch Ministry of Education, Culture, and Science; Netherlands Organization for Scientific Research (NWO; BRAINSCAPES); Gravitation Program; ALS Liga België; National Lottery of Belgium; KU Leuven Opening the Future Fund; KU Leuven Funds, “Een Hart voor ALS”, “Laeversfonds voor ALS Onderzoek” and the “Valéry Perrier Race against ALS Fund”; E. von Behring Chair for Neuromuscular and Neurodegenerative Disorders; ALS Liga België; “Live now” Charity Foundation; Moscow ALS palliative Care Service; Canadian Institutes of Health; Research Australia; Ice Bucket Challenge Grant; NIH Intramural Research Programs; FightMND Mid-Career Fellowship; NIHR Senior Investigator; Sheffield NIHR Biomedical Research Centre; Motor Neurone Disease Association; National Institute for Health Research (NIHR) Biomedical Research Centre; Maudsley NHS Foundation Trust; King’s College London; NIHR Senior Investigator Award; Netherlands Organization for Health Research and Development; Vici Scheme; Netherlands Organization for Health Research and Development STRENGTH Project; PPP Allowance

Published
2021
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9. Determinants of therapeutic lag in multiple sclerosis

Author

Tomas Kalincik, Marc Girard, Corinne Pottier, Murat Terzi, Jean Pelletier, Oliver Gerlach, Julie Prevost, Dana Horakova, Francois Grand'Maison, Raed Alroughani, Guillermo Izquierdo, Francesco Patti, Federico Frascoli, Maria Trojano, Franco Granella, Pamela A. McCombe, Charles B Malpas, Recai Turkoglu, Aurélie Ruet, Jonathan Ciron, Tünde Csépány, Nicolas Maubeuge, Helmut Butzkueven, Pierre Clavelou, Tamara Castillo Trivino, Marco Onofrj, Jean Philippe Camdessanche, Pierre Labauge, Vincent Van Pesch, Pierre Grammond, Abir Wahab, Roberto Bergamaschi, Aysun Soysal, Diana Ferraro, Bertrand Bourre, Olivier Gout, Jeannette Lechner-Scott, Sara Eichau, Emmanuelle Leray, Alexis Montcuquet, Pierre Duquette, Olivier Casez, Youssef Sidhom, Patrizia Sola, Bart Van Wijmeersch, Izanne Roos, Gilles Edan, Serkan Ozakbas, David Laplaud, Sandra Vukusic, Abdullatif Al Khedr, Céline Labeyrie, Philippe Cabre, Eric Thouvenot, Céline Louapre, Romain Casey, Alessandra Lugaresi, Riadh Gouider, Alasdair Coles, Eric Berger, Ivania Patry, Gerardo Iuliano, Elisabetta Cartechini, Cavit Boz, Karolina Hankiewicz, Eva Havrdova, Eduardo Aguera-Morales, J William L Brown, Jérôme De Seze, Bruno Stankoff, Olivier Heinzlef, Gilles Defer, Alexandre Prat, Chantal Nifle, Maria José Sá, Marc Debouverie, Daniele Spitaleri, Aude Maurousset, Thibault Moreau, Christine Lebrun-Frenay, Hélène Zéphir, University of Melbourne, Recherche en Pharmaco-épidémiologie et Recours aux Soins (REPERES), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP), École des Hautes Études en Santé Publique [EHESP] (EHESP), Département Méthodes quantitatives en santé publique (METIS), Collectif de recherche handicap, autonomie et société inclusive (CoRHASI), Swinburne University of Technology [Melbourne], Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Centre de recherche en neurosciences de Lyon (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Hospices Civils de Lyon (HCL), Charles University [Prague], Università degli studi di Catania [Catania], Università degli studi 'G. d'Annunzio' Chieti-Pescara [Chieti-Pescara] (Ud'A), Università degli Studi di Modena e Reggio Emilia (UNIMORE), University of Queensland [Brisbane], Monash University [Clayton], UCL - SSS/IONS/CEMO - Pôle Cellulaire et moléculaire, UCL - (SLuc) Service de biochimie médicale, UCL - (SLuc) Service de neurologie, Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Pontchaillou [Rennes], Charles University [Prague] (CU), Adaptation, mesure et évaluation en santé. Approches interdisciplinaires (APEMAC), Université de Lorraine (UL), Service de neurologie [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), University of Bari Aldo Moro (UNIBA), University of Catania [Italy], Hospital Virgen Macarena, Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal (UdeM), CHU Toulouse [Toulouse], INSERM, Neurocentre Magendie, U1215, Physiopathologie de la Plasticité Neuronale, F-33000 Bordeaux, France, CIC Bordeaux, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Dokuz Eylül Üniversitesi = Dokuz Eylül University [Izmir] (DEÜ), CIC Strasbourg (Centre d’Investigation Clinique Plurithématique (CIC - P) ), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Strasbourg (UNISTRA)-Hôpital de Hautepierre [Strasbourg]-Nouvel Hôpital Civil de Strasbourg, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CHU Lille, Fernando Pessoa University, Azienda Ospedaleria Universitaria di Modena, CHU Montpellier, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), Centre Hospitalier Universitaire de Nice (CHU Nice), Karadeniz Technical University (KTU), Università degli Studi di Macerata = University of Macerata (UNIMC), CHU Dijon, Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Centre hospitalier universitaire de Nantes (CHU Nantes), University of Newcastle [Australia] (UoN), Zuyderland Hospital [Heerlen, The Netherlands], Ondokuz Mayis University, University of Parma = Università degli studi di Parma [Parme, Italie], Amiri hospital, University of Salerno (UNISA), Université Catholique de Louvain = Catholic University of Louvain (UCL), Hasselt University (UHasselt), San Giuseppe Moscati Hospital [Avellino, Italie], Bakirkoy Matern & Childrens State Hosp, Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon), Universidad de Córdoba [Cordoba], Hospital Donostia, CHU Clermont-Ferrand, Hôpital de la Timone [CHU - APHM] (TIMONE), Fondation Ophtalmologique Adolphe de Rothschild [Paris], Centre Hospitalier Universitaire de Nîmes (CHU Nîmes), CHI Poissy-Saint-Germain, Université de la Manouba [Tunisie] (UMA), University of Debrecen, Hôpital Charles Nicolle [Rouen], CHU Amiens-Picardie, CHU de la Martinique [Fort de France], CHU Limoges, CHU Henri Mondor, Centre Hospitalier Universitaire de Saint-Etienne (CHU de Saint-Etienne), Centre Hospitalier Régional Universitaire de Tours (CHRU TOURS), Centre Hospitalier Sud Francilien, CH Evry-Corbeil, Centre Hospitalier de Saint-Denis [Ile-de-France], Centre Hospitalier René Dubos [Pontoise], This study was supported by the EDMUS Foundation and NHMRC [1140766,1129189, 1157717]. IR is supported by a MSIF-ARSEP McDonald fellowship grantand a Melbourne Research Scholarship. The MSBase Foundation is a not-for-profitorganization that receives support from Biogen, Novartis, Merck, Roche, Teva andSanofi Genzyme. The study was conducted separately and apart from the guidanceof the sponsors. The Observatoire Français de la Sclérose en Plaques (OFSEP) issupported by a grant provided by the French State and handled by the 'AgenceNationale de la Recherche,' within the framework of the 'Investments for the Future'program, under the reference ANR-10-COHO-002, by the Eugène Devic EDMUSFoundation against multiple sclerosis and by the ARSEP Foundation., ANR-10-COHO-0002,OFSEP,Observatoire Français de la Sclérose en Plaques(2010), Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), Roos I., Leray E., Frascoli F., Casey R., Brown J.W.L., Horakova D., Havrdova E.K., Debouverie M., Trojano M., Patti F., Izquierdo G., Eichau S., Edan G., Prat A., Girard M., Duquette P., Onofrj M., Lugaresi A., Grammond P., Ciron J., Ruet A., Ozakbas S., De Seze J., Louapre C., Zephir H., Sa M.J., Sola P., Ferraro D., Labauge P., Defer G., Bergamaschi R., Lebrun-Frenay C., Boz C., Cartechini E., Moreau T., Laplaud D., Lechner-Scott J., Grand'Maison F., Gerlach O., Terzi M., Granella F., Alroughani R., Iuliano G., Van Pesch V., Van Wijmeersch B., Spitaleri D.L.A., Soysal A., Berger E., Prevost J., Aguera-Morales E., McCombe P., Castillo Trivino T., Clavelou P., Pelletier J., Turkoglu R., Stankoff B., Gout O., Thouvenot E., Heinzlef O., Sidhom Y., Gouider R., Csepany T., Bourre B., Al Khedr A., Casez O., Cabre P., Montcuquet A., Wahab A., Camdessanche J.-P., Maurousset A., Patry I., Hankiewicz K., Pottier C., Maubeuge N., Labeyrie C., Nifle C., Coles A., Malpas C.B., Vukusic S., Butzkueven H., Kalincik T., Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA), Università degli studi di Catania = University of Catania (Unict), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Neurocentre Magendie : Physiopathologie de la Plasticité Neuronale (U1215 Inserm - UB), Université de Bordeaux (UB)-Institut François Magendie-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Nouvel Hôpital Civil de Strasbourg-Hôpital de Hautepierre [Strasbourg], Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Modena e Reggio Emilia = University of Modena and Reggio Emilia (UNIMORE), University of Newcastle [Callaghan, Australia] (UoN), Ondokuz Mayis University (OMU), Università degli studi di Parma = University of Parma (UNIPR), Universidad de Córdoba = University of Córdoba [Córdoba], University of Debrecen Egyetem [Debrecen], CHU Rouen, Normandie Université (NU)-Normandie Université (NU), CHU Henri Mondor [Créteil], Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Registrie, Male, medicine.medical_specialty, Treatment response, Pediatrics, Neurology, Lag, [SDV]Life Sciences [q-bio], Aucun, multiple sclerosis, 03 medical and health sciences, Disability Evaluation, 0302 clinical medicine, Multiple Sclerosis, Relapsing-Remitting, Recurrence, medicine, Humans, Treatment effect, Disabled Persons, Registries, 030304 developmental biology, 0303 health sciences, business.industry, Multiple sclerosis, Delayed onset, medicine.disease, 3. Good health, Clinical neurology, therapeutic lag, multiple sclerosi, Disease Progression, Disabled Person, Observational study, Female, observational study, Neurology (clinical), business, 030217 neurology & neurosurgery, Human
Abstract

International audience; Objective: To explore the associations of patient and disease characteristics with the duration of therapeutic lag for relapses and disability progression.Background: Therapeutic lag represents the delay from initiation of therapy to attainment of full treatment effect. Understanding the determinants of therapeutic lag provides valuable information for personalised choice of therapy in multiple sclerosis (MS).Design/Methods: Data from MSBase, a multinational MS registry, and OFSEP, the French national registry, were used. Patients diagnosed with MS, minimum 1-year exposure to MS treatment, minimum 3-year pre-treatment follow up and yearly review were included in the analysis. By studying incidence of relapses and 6-month confirmed disability progression, the duration of therapeutic lag was calculated by identifying the first local minimum of the first derivative after treatment start in subgroups stratified by patient and disease characteristics. Pairwise analyses of univariate predictors were performed. Combinations of determinants that consistently drove differences in therapeutic lag in pair by pair analyses were included in the final model.Results: Baseline EDSS, ARR and sex were associated with duration of therapeutic lag on disability progression in univariate and pairwise bivariable analyses. In the final model, therapeutic lag was 27.8 weeks shorter in females with ARR6 compared to those with EDSS>=6 (26.6, 18.2–34.9 vs 54.3, 47.2–61.5). Baseline EDSS, ARR, sex and MS phenotype were associated with duration of therapeutic lag on relapses in univariate analyses. Pairwise bivariable analyses of the pairs of determinants suggested ependently associated with therapeutic lag. In the final model, therapeutic lag was shortest in those with RRMS and EDSS

Published
2021
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10. Clinical and therapeutic predictors of disease outcomes in AQP4-IgG+ neuromyelitis optica spectrum disorder

Author

Guillermo Izquierdo, Ayse Altintas, Tomas Kalincik, Petra Nytrova, Charles B Malpas, Roberto Bergamaschi, Ilya Kister, Diana Ferraro, Aysun Soysal, Helmut Butzkueven, Sara Eichau, Francois Grand'Maison, Guy Laureys, Jeannette Lechner-Scott, Jyh Yung Hor, Pamela A. McCombe, Yara Dadalti Fragoso, Steve Vucic, Rana Karabudak, Raed Alroughani, Cavit Boz, Celia Oreja-Guevara, Eugenio Pucci, Tünde Csépány, Patrizia Sola, Serkan Ozakbas, Bhim Singhal, Francesco Patti, Maria Trojano, Franco Granella, Marco Onofrj, Alessandra Lugaresi, Recai Turkoglu, Mark Marriott, Murat Terzi, Amy Kunchok, Talal Al-Harbi, Magdolna Simó, Javier Olascoaga, Eva Havrdova, Bassem Yamout, Kunchok A., Malpas C., Nytrova P., Havrdova E.K., Alroughani R., Terzi M., Yamout B., Hor J.Y., Karabudak R., Boz C., Ozakbas S., Olascoaga J., Simo M., Granella F., Patti F., McCombe P., Csepany T., Singhal B., Bergamaschi R., Fragoso Y., Al-Harbi T., Turkoglu R., Lechner-Scott J., Laureys G., Oreja-Guevara C., Pucci E., Sola P., Ferraro D., Altintas A., Soysal A., Vucic S., Grand'Maison F., Izquierdo G., Eichau S., Lugaresi A., Onofrj M., Trojano M., Marriott M., Butzkueven H., Kister I., Kalincik T., and Ondokuz Mayıs Üniversitesi

Subjects
Male, Time Factors, Azathioprine, Severity of Illness Index, 0302 clinical medicine, Natalizumab, Recurrence, Outcome Assessment, Health Care, Disability, Immunosuppression, Neuromyelitis optica spectrum disorder, Predictors, Relapses, Therapy, 030212 general & internal medicine, Registries, Relapse, Hazard ratio, Neuromyelitis Optica, Age Factors, General Medicine, Middle Aged, Neurology, Cohort, Disease Progression, Female, Rituximab, medicine.drug, Cohort study, Adult, medicine.medical_specialty, 03 medical and health sciences, Internal medicine, medicine, Humans, Immunologic Factors, Aquaporin 4, Neuromyelitis optica, Expanded Disability Status Scale, Proportional hazards model, business.industry, Mycophenolic Acid, medicine.disease, Immunoglobulin G, Neurology (clinical), business, 030217 neurology & neurosurgery, Follow-Up Studies, Predictor
Abstract

Altintas, Ayse/0000-0002-8524-5087; Laureys, Guy/0000-0002-1708-4373; Vucic, Steve/0000-0002-8323-873X; patti, francesco/0000-0002-6923-0846; Kister, Ilya/0000-0003-3549-949X; Lugaresi, Alessandra/0000-0003-2902-5589 WOS: 000521648000049 PubMed: 31877445 Background: Aquaporin-4-IgG positive (AQP4-IgG(+)) Neuromyelitis Optica Spectrum Disorder (NMOSD) is an uncommon central nervous system autoimmune disorder. Disease outcomes in AQP4-IgG + NMOSD are typically measured by relapse rate and disability. Using the MSBase, a multi-centre international registry, we aimed to examine the impact immunosuppressive therapies and patient characteristics as predictors of disease outcome measures in AQP4-IgG + NMOSD. Method: This MSBase cohort study of AQP4-IgG + NMOSD patients examined modifiers of relapse in a multivariable proportional hazards model and expanded disability status score (EDSS) using a mixed effects model. Results: 206 AQP4-IgG + patients were included (median follow-up 3.7 years). Age (hazard ratio [HR] = 0.82 per decade, p = 0.001), brainstem onset (HR = 0.45, p = 0.009), azathioprine (HR = 0.46, p < 0.001) and mycophenolate mofetil (HR = 0.09, p = 0.012) were associated with a reduced risk of relapse. A greater EDSS was associated with age (beta = 0.45 (per decade), p < 0.001) and disease duration (beta = 0.07 per year, p < 0.001). A slower increase in EDSS was associated with azathioprine (beta = -0.48, p < 0.001), mycophenolate mofetil (beta = -0.69, p = 0.04) and rituximab (beta = -0.35, p = 0.024). Interpretation: This study has demonstrated that azathioprine and mycophenolate mofetil reduce the risk of relapses and disability progression is modified by azathioprine, mycophenolate mofetil and rituximab. Age and disease duration were the only patient characteristics that modified the risk of relapse and disability in our cohort. National Health and Medical Research Council of AustraliaNational Health and Medical Research Council of Australia [1083539, 1129189, 1140766, 1080518]; MerckMerck & Company; BiogenBiogen; NovartisNovartis; Bayer-ScheringBayer AG; Sanofi-Genzyme; Teva This study was financially supported by National Health and Medical Research Council of Australia [project grants 1083539 and 1129189, and fellowships 1140766 and 1080518]. The MSBase Foundation is a not-for-profit organization that receives support from Merck, Biogen, Novartis, Bayer-Schering, Sanofi-Genzyme and Teva. The study was conducted separately and apart from the guidance of the sponsors.

Published
2020

11. Prediction of on-treatment disability worsening in RRMS with the MAGNIMS score

Author

Jeannette Lechner-Scott, Patrizia Sola, Pierre Grammond, Daniele Spitaleri, Jose Luis Sanchez-Menoyo, Raed Alroughani, Maria Trojano, Franco Granella, Tomas Kalincik, Cavit Boz, Diana Ferraro, Pamela A. McCombe, Bart Van Wijmeersch, Serkan Ozakbas, Alessandra Lugaresi, Raymond Hupperts, Guillermo Izquierdo, Francois Grand'Maison, Maria Pia Sormani, Vilija Jokubaitis, Steve Vucic, Eugenio Pucci, Marco Onofrj, Helmut Butzkueven, Amy Kunchok, Kunchok A., Lechner-Scott J., Granella F., Trojano M., Alroughani R., Sola P., Ferraro D., Lugaresi A., Onofrj M., Ozakbas S., Izquierdo G., Grammond P., Luis Sanchez-Menoyo J., Van Wijmeersch B., Boz C., Pucci E., McCombe P., Grand'Maison F., Spitaleri D., Vucic S., Hupperts R., Jokubaitis V., Sormani M.P., Butzkueven H., and Kalincik T.

Subjects
medicine.medical_specialty, outcomes, Cohort Studies, Multiple sclerosis, Neoplasm Recurrence, Multiple Sclerosis, Relapsing-Remitting, medicine, Humans, magnetic resonance imaging, Multiple sclerosi, therapy, medicine.diagnostic_test, Interferon beta, business.industry, Disease progression, Magnetic resonance imaging, prediction, medicine.disease, Clinical neurology, Neurology, Relapsing remitting, prognosis, outcome, Disease Progression, Neurology (clinical), Radiology, Neoplasm Recurrence, Local, business, prognosi, Cohort study
Abstract

Background: The magnetic resonance imaging in multiple sclerosis (MAGNIMS) score combines relapses and magnetic resonance imaging (MRI) lesions to predict disability outcomes in relapsing–remitting multiple sclerosis (RRMS) treated with interferon-β. Objective: To validate the MAGNIMS score and extend to other disease-modifying therapies (DMTs). To examine the prognostic value of gadolinium contrast-enhancing (Gd+) lesions. Methods: This RRMS MSBase cohort study ( n = 2293) used a Cox model to examine the prognostic value of relapses, MRI activity and the MAGNIMS score for disability worsening during treatment with interferon-β and three other DMTs. Results: Three new T2 lesions (hazard ratio (HR) = 1.60, p = 0.028) or two relapses (HR = 2.24, p = 0.002) on interferon-β (for 12 months) were predictive of disability worsening over 4 years. MAGNIMS score = 2 (1 relapse and ⩾3 T2 lesions or ⩾2 relapses) was associated with a greater risk of disability worsening on interferon-β (HR = 2.0, p = 0.001). In pooled cohort of four DMTs, similar associations were seen (MAGNIMS score = 2: HR = 1.72, p = 0.001). Secondary analyses demonstrated that the addition of Gd+ to the MAGNIMS did not materially improve its prediction of disability worsening. Conclusion: We have validated the MAGNIMS score in RRMS and extended its application to three other DMTs: 1 relapse and ⩾3 T2 lesions or ⩾2 relapses predicted worsening of disability. Contrast-enhancing lesions did not substantially improve the prognostic score.

Published
2020

12. Delay from treatment start to full effect of immunotherapies for multiple sclerosis

Author

Roos, Izanne, Leray, Emmanuelle, Frascoli, Federico, Casey, Romain, Brown, J William L, Horakova, Dana, Havrdova, Eva, Trojano, Maria, Patti, Francesco, Izquierdo, Guillermo, Eichau, Sara, Onofrj, Marco, Lugaresi, Alessandra, Prat, Alexandre, Girard, Marc, Grammond, Pierre, Sola, Patrizia, Ferraro, Diana, Ozakbas, Serkan, Bergamaschi, Roberto, Sá, Maria José, Cartechini, Elisabetta, Boz, Cavit, Granella, Franco, Hupperts, Raymond, Terzi, Murat, Lechner-Scott, Jeannette, Spitaleri, Daniele, Van Pesch, Vincent, Soysal, Aysun, Olascoaga, Javier, Prevost, Julie, Aguera-Morales, Eduardo, Slee, Mark, Csepany, Tunde, Turkoglu, Recai, Sidhom, Youssef, Gouider, Riadh, Van Wijmeersch, Bart, McCombe, Pamela, Macdonell, Richard, Coles, Alasdair, Malpas, Charles, Butzkueven, Helmut, Vukusic, Sandra, Kalincik, Tomas, Duquette, Pierre, Grand'Maison, Francois, Iuliano, Gerardo, Ramo-Tello, Cristina, Solaro, Claudio, Cabrera-Gomez, Jose Antonio, Rio, Maria Edite, Bolaños, Ricardo Fernandez, Shaygannejad, Vahid, Oreja-Guevara, Celia, Sanchez-Menoyo, Jose Luis, Petersen, Thor, Altintas, Ayse, Barnett, Michael, Flechter, Shlomo, Fragoso, Yara, Amato, Maria Pia, Moore, Fraser, Ampapa, Radek, Verheul, Freek, Hodgkinson, Suzanne, Cristiano, Edgardo, Yamout, Bassem, Laureys, Guy, Dominguez, Jose Andres, Zwanikken, Cees, Deri, Norma, Dobos, Eniko, Vrech, Carlos, Butler, Ernest, Rozsa, Csilla, Petkovska-Boskova, Tatjana, Karabudak, Rana, Rajda, Cecilia, Alkhaboori, Jabir, Saladino, Maria Laura, Shaw, Cameron, Shuey, Neil, Vucic, Steve, Sempere, Angel Perez, Campbell, Jamie, Piroska, Imre, Taylor, Bruce, van der Walt, Anneke, Kappos, Ludwig, Roullet, Etienne, Gray, Orla, Simo, Magdolna, Sirbu, Carmen-Adella, Brochet, Bruno, Cotton, François, De Sèze, Jérôme, Dion, Armelle, Douek, Pascal, Guillemin, Francis, Laplaud, David, Lebrun-Frenay, Christine, Moreau, Thibault, Olaiz, Javier, Pelletier, Jean, Rigaud-Bully, Claire, Stankoff, Bruno, Marignier, Romain, Debouverie, Marc, Edan, Gilles, Ciron, Jonathan, Ruet, Aurélie, Collongues, Nicolas, Lubetzki, Catherine, Vermersch, Patrick, Labauge, Pierre, Defer, Gilles, Cohen, Mikaël, Fromont, Agnès, Wiertlewsky, Sandrine, Berger, Eric, Clavelou, Pierre, Audoin, Bertrand, Giannesini, Claire, Gout, Olivier, Thouvenot, Eric, Heinzlef, Olivier, Al-Khedr, Abdullatif, Bourre, Bertrand, Casez, Olivier, Cabre, Philippe, Montcuquet, Alexis, Créange, Alain, Camdessanché, Jean-Philippe, Faure, Justine, Maurousset, Aude, Patry, Ivania, Hankiewicz, Karolina, Pottier, Corinne, Maubeuge, Nicolas, Labeyrie, Céline, Nifle, Chantal, University of Melbourne, The Royal Melbourne Hospital, Recherche en Pharmaco-épidémiologie et Recours aux Soins (REPERES), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP), École des Hautes Études en Santé Publique [EHESP] (EHESP), Département Méthodes quantitatives en santé publique (METIS), Swinburne University of Technology [Melbourne], Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, University of Cambridge [UK] (CAM), Medicine Charles University and General Faculty Hospital in Prague, University of Bari Aldo Moro (UNIBA), University of Catania [Italy], Hospital Universitario Virgen Macarena [Seville, Spain], University 'G. d'Annunzio' of Chieti-Pescara [Chieti], Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Université de Montréal (UdeM), University of Modena and Reggio Emilia, Partenaires INRAE, Dokuz Eylül Üniversitesi = Dokuz Eylül University [Izmir] (DEÜ), IRCCS Mondino Foundation, Universidade Fernando Pessoa, KTU Medical Faculty Farabi Hospital, University of Parma = Università degli studi di Parma [Parme, Italie], Zuyderland Ziekenhuis, Medical Faculty [Samsun, Turkey], University of Newcastle [Australia] (UoN), Université Catholique de Louvain = Catholic University of Louvain (UCL), Bakirkoy Education and Research Hospital for Psychiatric and Neurological Diseases, Hospital Universitario Donostia, Hospital Universitario Reina Sofía de Córdoba, Instituto Maimonides de Investigación Biomédica de Córdoba (IMIBIC), Haydarpasa Numune Training and Research Hospital, Hasselt University (UHasselt), University of Queensland [Brisbane], Hitachi Cambridge Laboratory [University of Cambridge], Hitachi, Ltd-University of Cambridge [UK] (CAM), Monash University [Melbourne], Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CR CHUM), Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal (UdeM)-Université de Montréal (UdeM), Ospedali Riuniti di Salerno, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Université de Montpellier (UM), Centre hospitalier universitaire de Poitiers (CHU Poitiers), AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), 1157717, National Health and Medical Research Council, Biogen, MSIF-ARSEP McDonald, Melbourne Research Scholarship, French State, ‘Agence Nationale de la Recherche,’, ANR-10-COHO-002, ‘Investments for the Future’, Eugène Devic EDMUS Foundation, ARSEP Foundation, Novartis, Merck, Roche, Teva Pharmaceutical Industries, Sanofi Genzyme, EDMUS Foundation, UCL - SSS/IONS/CEMO - Pôle Cellulaire et moléculaire, UCL - (SLuc) Service de neurologie, Roos I., Leray E., Frascoli F., Casey R., Brown W.J.L., Horakova D., Havrdova E.K., Trojano M., Patti F., Izquierdo G., Eichau S., Onofrj M., Lugaresi A., Prat A., Girard M., Grammond P., Sola P., Ferraro D., Ozakbas S., Bergamaschi R., Sa M.J., Cartechini E., Boz C., Granella F., Hupperts R., Terzi M., Lechner-Scott J., Spitaleri D., van Pesch V., Soysal A., Olascoaga J., Prevost J., Aguera-Morales E., Slee M., Csepany T., Turkoglu R., Sidhom Y., Gouider R., van Wijmeersch B., McCombe P., Macdonell R., Coles A., Malpas C.B., Butzkueven H., Vukusic S., Kalincik T., Duquette P., Grand'Maison F., Iuliano G., Ramo-Tello C., Solaro C., Cabrera-Gomez J.A., Rio M.E., Bolanos R.F., Shaygannejad V., Oreja-Guevara C., Sanchez-Menoyo J.L., Petersen T., Altintas A., Barnett M., Flechter S., Fragoso Y., Amato M.P., Moore F., Ampapa R., Verheul F., Hodgkinson S., Cristiano E., Yamout B., Laureys G., Dominguez J.A., Zwanikken C., Deri N., Dobos E., Vrech C., Butler E., Rozsa C., Petkovska-Boskova T., Karabudak R., Rajda C., Alkhaboori J., Saladino M.L., Shaw C., Shuey N., Vucic S., Sempere A.P., Campbell J., Piroska I., Taylor B., van der Walt A., Kappos L., Roullet E., Gray O., Simo M., Sirbu C.-A., Brochet B., Cotton F., de Seze J., Dion A., Douek P., Guillemin F., Laplaud D., Lebrun-Frenay C., Moreau T., Olaiz J., Pelletier J., Rigaud-Bully C., Stankoff B., Marignier R., Debouverie M., Edan G., Ciron J., Ruet A., Collongues N., Lubetzki C., Vermersch P., Labauge P., Defer G., Cohen M., Fromont A., Wiertlewsky S., Berger E., Clavelou P., Audoin B., Giannesini C., Gout O., Thouvenot E., Heinzlef O., Al-Khedr A., Bourre B., Casez O., Cabre P., Montcuquet A., Creange A., Camdessanche J.-P., Faure J., Maurousset A., Patry I., Hankiewicz K., Pottier C., Maubeuge N., Labeyrie C., Nifle C., Brown, Will [0000-0002-7737-5834], Coles, Alasdair [0000-0003-4738-0760], Apollo - University of Cambridge Repository, McCombe, Pamela/0000-0003-2704-8517, Slee, Mark/0000-0003-4323-2453, Brown, William/0000-0002-7737-5834, Laplaud, David/0000-0001-6113-6938, Ciron, Jonathan/0000-0002-3386-6308, Roos, Izanne/0000-0003-0371-3666, Lugaresi, Alessandra/0000-0003-2902-5589, Aguera-Morales, Eduardo/0000-0002-8604-2054, Kalincik, Tomas, Girard, Marc, Patti, Francesco, Horakova, Dana, Malpas, Charles B., Olascoaga, Javier, Prevost, Julie, Roos, Izanne, Hupperts, Raymond, Csepany, Tunde, VAN WIJMEERSCH, Bart, Ferraro, Diana, Aguera-Morales, Eduardo, Cartechini, Elisabetta, Vukusic, Sandra, Frascoli, Federico, Lugaresi, Alessandra, Sa, Maria Jose, Butzkueven, Helmut, Spitaleri, Daniele, Macdonell, Richard, Coles, Alasdair, Havrdova, Eva K., Granella, Franco, Turkoglu, Recai, Trojano, Maria, Sola, Patrizia, Van Pesch, Vincent, Onofrj, Marco, Grammond, Pierre, Bergamaschi, Roberto, Izquierdo, Guillermo, McCombe, Pamela, Slee, Mark, Eichau, Sara, Prat, Alexandre, Leray, Emmanuelle, Soysal, Aysun, Terzi, Murat, Brown, J. William L., Boz, Cavit, Sidhom, Youssef, Gouider, Riadh, Ozakbas, Serkan, Casey, Romain, Lechner-Scott, Jeannette, Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP), Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA), Hospital Universitario Virgen Macarena [Séville], Università degli studi di Parma = University of Parma (UNIPR), University of Newcastle [Callaghan, Australia] (UoN), University of Cambridge [UK] (CAM)-Hitachi, Ltd, and ANR-10-COHO-0002,OFSEP,Observatoire Français de la Sclérose en Plaques(2010)

Subjects
Adult, Male, medicine.medical_specialty, Multiple Sclerosis, Time Factors, multiple sclerosis, law.invention, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Natalizumab, Randomized controlled trial, law, Internal medicine, medicine, Humans, Immunologic Factors, Multiple sclerosi, 030212 general & internal medicine, Prospective Studies, Registries, Prospective cohort study, therapeutic lag, business.industry, Multiple sclerosis, Interferon beta-1a, Middle Aged, medicine.disease, Fingolimod, 3. Good health, Treatment Outcome, Cohort, Disease Progression, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Female, Neurology (clinical), business, Immunotherapies, 030217 neurology & neurosurgery, Immunosuppressive Agents, Therapeutic lag, prognosis, treatment, medicine.drug, Cohort study, Follow-Up Studies
Abstract

In multiple sclerosis, treatment start or switch is prompted by evidence of disease activity. Whilst immunomodulatory therapies reduce disease activity, the time required to attain maximal effect is unclear. In this study we aimed to develop a method that allows identification of the time to manifest fully and clinically the effect of multiple sclerosis treatments ('therapeutic lag') on clinical disease activity represented by relapses and progression-of-disability events. Data from two multiple sclerosis registries, MSBase (multinational) and OFSEP (French), were used. Patients diagnosed with multiple sclerosis, minimum 1-year exposure to treatment, minimum 3-year pretreatment follow-up and yearly review were included in the analysis. For analysis of disability progression, all events in the subsequent 5-year period were included. Density curves, representing incidence of relapses and 6-month confirmed progression events, were separately constructed for each sufficiently represented therapy. Monte Carlo simulations were performed to identify the first local minimum of the first derivative after treatment start; this point represented the point of stabilization of treatment effect, after the maximum treatment effect was observed. The method was developed in a discovery cohort (MSBase), and externally validated in a separate, non-overlapping cohort (OFSEP). A merged MSBase-OFSEP cohort was used for all subsequent analyses. Annualized relapse rates were compared in the time before treatment start and after the stabilization of treatment effect following commencement of each therapy. We identified 11 180 eligible treatment epochs for analysis of relapses and 4088 treatment epochs for disability progression. External validation was performed in four therapies, with no significant difference in the bootstrapped mean differences in therapeutic lag duration between registries. The duration of therapeutic lag for relapses was calculated for 10 therapies and ranged between 12 and 30 weeks. The duration of therapeutic lag for disability progression was calculated for seven therapies and ranged between 30 and 70 weeks. Significant differences in the pre- versus post-treatment annualized relapse rate were present for all therapies apart from intramuscular interferon beta-1a. In conclusion we have developed, and externally validated, a method to objectively quantify the duration of therapeutic lag on relapses and disability progression in different therapies in patients more than 3 years from multiple sclerosis onset. Objectively defined periods of expected therapeutic lag allows insights into the evaluation of treatment response in randomized clinical trials and may guide clinical decision-making in patients who experience early on-treatment disease activity. This method will subsequently be applied in studies that evaluate the effect of patient and disease characteristics on therapeutic lag. This study was supported by the EDMUS Foundation, Biogen and NHMRC (1140766, 1129189, 1157717). I.R. is supported by a MSIF-ARSEP McDonald fellowship grant and a Melbourne Research Scholarship. The MSBase Foundation is a not-for-profit organization that receives support from Biogen, Novartis, Merck, Roche, Teva and Sanofi Genzyme. The Observatoire Francais de la Sclerose en Plaques (OFSEP) is supported by a grant provided by the French State and handled by the 'Agence Nationale de la Recherche,' within the framework of the 'Investments for the Future' program, under the reference ANR-10-COHO-002, by the Eugene Devic EDMUS Foundation against multiple sclerosis and by the ARSEP Foundation. The study was conducted separately and apart from the guidance of the sponsors. Kalincik, T (corresponding author), Univ Melbourne, Dept Med, CORe, 300 Grattan St, Melbourne, Vic 3050, Australia. tomas.kalincik@unimelb.edu.au

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