Hospital Clinic Barcelona, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona
Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases

Author Of 3 Presentations

Biomarkers and Bioinformatics Poster Presentation

P0027 - Are we ready for precision medicine in Multiple Sclerosis? A web-based survey across Europe   (ID 1411)

Presentation Number
P0027
Presentation Topic
Biomarkers and Bioinformatics

Abstract

Background

We designed a web-based survey to assess the willingness and interest of European neurologists working with MS to implement precision medicine in their routine clinical practice. This study is a part of the EU-funded MULTIPLEMS grant.

Objectives

1) To assess how neurologists across European countries view the role of body-fluid biomarkers in clinical practice; 2) To survey clinical practices of diagnostic work up, therapy selection and monitoring, and frequency of data collection and clinical and paraclinical measurements.

Methods

The survey had three parts: a) demographics of respondents; b) opinion of the role of predictive, diagnostic, disease-activity biomarkers and treatment-response body-fluid biomarkers in clinical practice; c) survey of clinical practice and management of MS cases (including therapy choice and use of biomarkers) by evaluating 5 clinical cases with different characteristics (therapeutic management in drug naive patients and in patients displaying different forms of remaining disease activity, as well as stopping threapy in stable diasease since long).

Results

194 neurologists across 11 European countries responded to the survey, with a mean response rate of 45%. 57.7% were male and the mean age was 49.8 years. The importance of biomarkers in clinical practice was rated from 1 (low) to 7 (high), and it was generally high: 4.1 for predictive and disease-activity biomarkers, 5.2 for treatment-response and 5.7 for diagnostic biomarkers, with neurologists in Belgium, Denmark, Spain, Sweden and UK being the most positive. Determination of cerebrospinal fluid (CSF) oligoclonal bands was considered the most established biomarker for diagnosis (98.5% of neurologists), prediction (56.7%) and disease activity (36.5%), trailed by anti-aquaporin 4 (90.7%) and anti-myelin oligodendrocyte antibodies (85.1%) for diagnosis. Anti-JC (93.8%) and varicella virus (61.9%) and anti-drug (natalizumab (74.7%) and interferon-beta (68.6%)) were considered useful in context of therapy selection and monitoring by most neurologists, while neurofilament levels in CSF and serum and vitamin D levels were less established. Therapeutic management in the five case examples varied widely, likely as a result of differences in local and national guidelines.

Conclusions

European MS neurologists express a positive opinion on the role of body-fluid biomarkers to manage MS in clinical practice, however, these seem still to have had a limited impact on therapeutic management and selection, which also varied markedly across countries. This underscores the need for further research in this area.

Collapse
Imaging Poster Presentation

P0567 - Diffusion-based Structural connectivity abnormalities in MS phenotypes. (ID 1271)

Abstract

Background

People with MS present disruption of structural brain networks, but the differential characteristics of such changes among MS phenotypes and their clinical impact are not well elucidated.

Objectives

To characterize diffusion-based brain connectivity abnormalities in different MS phenotypes and their relation with disability in a large cohort of patients.

Methods

In this multicenter, retrospective, cross-sectional study, we collected clinical and brain MRI data from 344 patients with MS [median Expanded Disability Status Scale, EDSS 2.0 (range 0-7.0)] and 91 healthy volunteers (HV) from four MAGNIMS centers. Cognition was assessed with the Paced Auditory Serial Addition Test (PASAT) and Symbol Digits Modalities Test (SDMT) in 298 patients. We collected 3D-T1, FLAIR, diffusion-weighted images (DWI) and T2 or field maps acquisitions. FSL and ANTs packages were used to carry out DWI preprocessing and MRtrix software to generate connectivity matrices based on fractional anisotropy values. We computed six network measures (strength, global and local efficiency, clustering coefficient, assortativity and transitivity), and applied the ComBat tool to reduce inter-site variability. We calculated age-adjusted differences in graphs between groups using Mann-Whitney with FDR correction or Kruskal-Wallis with Dunn’s Test when necessary. Associations with clinical features were explored with Spearman’s rank correlation.

Results

Thirty-eight (11%) patients presented a clinically isolated syndrome (CIS), 262 (76%) had relapsing-remitting (RR) and 44 (13%) secondary progressive (SP) MS. CIS patients showed reduced global and local efficiency, clustering coefficient and transitivity compared to HV (corrected p<0.001), whilst RRMS did not differ from CIS patients. Compared with CIS and RRMS, patients with SPMS showed larger changes for the same previous graphs measures (corrected p<0.05), and lower strength than RRMS (corrected p=0.019).

In patients, reduced measures of strength, global and local efficiency, clustering and transitivity correlated with higher EDSS (rho:-0.12–-0.16, corrected p<0.034), lower PASAT (rho:0.26–0.30, corrected p<0.001) and worse SDMT scores (rho:0.28–0.32, corrected p<0.001).

Conclusions

Structural network integrity at the whole brain level is already widely reduced in people with MS from the earliest phases of the disease and becomes more abnormal in SPMS. Network modifications may contribute to the clinical manifestations of the disease.

Collapse
Neuropsychology and Cognition Poster Presentation

P0805 - Dynamics of cognitive decline along the disease course in multiple sclerosis (ID 897)

Abstract

Background

Cognitive decline is frequent in patients with multiple sclerosis (MS). The cognitive trajectory is not well understood and a global overview throughout the disease course needs to be elucidated. Besides, predictors of future cognitive decline are still needed.

Objectives

We aim to (a) assess the temporal dynamics of cognitive function through disease course, and (b) explore different clinical and MRI predictors of cognitive decline in a large cohort of patients with MS.

Methods

Longitudinal study with 212 MS patients who performed a total of 605 neurological, cognitive and MRI examinations at different times of the disease [examinations per patient: 3 (IQR:2-3); baseline age: 40.2 (IQR:34.5-47.6) years; baseline disease duration: 8.2 (IQR:2.3-13.9) years]. A z-score for global cognition (z-BRB) and for each cognitive domain was obtained from the Rao's Battery, and a 3D-structural MRI was acquired to calculate regional gray matter (GM) volumes. We modelled the dynamics of cognition throughout the MS course using age at MS onset, education and sex adjusted mixed-effects linear spline models with knots at 5 and 15 years. An age and sex adjusted multivariate regression model was performed to determine which factors at the first examination best predict cognitive performance at last follow-up in the entire sample.

Results

In the first 5 years of MS, we detected an increase in z-BRB (β=0.050, p=0.004) and z-attention (β=0.048, p=0.013), followed by a decline in z-BRB (β=-0.029, p=0.005) and z-verbal memory (β=-0.049, p=0.001) between the 5-15 years of the disease. During the 15-30 years of MS course, the cognitive decline was maintained, but also involved z-attention (β=-0.035, p=0.012). Lower education, higher EDSS and volumetric changes at right parahippocampus, left parsorbitalis, left superior, left middle and right inferior temporal, and right superior parietal areas at the first examination were associated with worse z-BRB at the last follow-up (adjR2=0.48, β=-0.652–0.863, p=<0.001–0.024).

Conclusions

In MS, cognition deteriorates after the first 5 years of the disease, with a steady decline over the next 25 years. The verbal memory is affected earlier and more markedly, followed by involvement of attention and information processing speed. Moreover, education, clinical disability and GM volume at baseline are associated with future cognitive outcomes.

Collapse