Development of Cortical Lesion Volumes on Double Inversion Recovery MRI in Patients With Relapse-Onset Multiple Sclerosis

Background and Objective: In multiple sclerosis (MS) patients, Double Inversion Recovery (DIR) magnetic resonance imaging (MRI) can be used to detect cortical lesions (CL). While the quantity and distribution of CLs seems to be associated with patients' disease course, literature lacks frequent assessments of CL volumes (CL-V) in this context. We investigated the reliability of DIR for the longitudinal assessment of CL-V development with frequent follow-up MRIs and examined the course of CL-V progressions in relation to white-matter lesions (WML), contrast enhancing lesions (CEL) and clinical parameters in patients with Relapsing-Remitting Multiple Sclerosis (RRMS).Methods: In this post-hoc analysis, image- and clinical data of a subset of 24 subjects that were part of a phase IIa clinical trial on the “Safety, Tolerability and Mechanisms of Action of Boswellic Acids in Multiple Sclerosis (SABA)” (ClinicalTrials.gov, NCT01450124) were included. The study was divided in three phases (screening, treatment, study-end). All patients received 12 MRI follow-up-examinations (including DIR) during a 16-months period. CL-Vs were assessed for each patient on each follow-up MRI separately by two experienced neuroradiologists. Results of neurological screening tests, as well as other MRI parameters (WML number and volume and CELs) were included from the SABA investigation data.Results: Inter-rater agreement regarding CL-V assessment over time was good-to-excellent (κ = 0.89). Mean intraobserver variability was 1.1%. In all patients, a total number of 218 CLs was found. Total CL-Vs of all patients increased during the 4 months of baseline screening followed by a continuous and significant decrease from month 5 until study-end (p < 0.001, Kendall'W = 0.413). A positive association between WML volumes and CL-Vs was observed during baseline screening. Decreased CL-V were associated with lower EDSS and also with improvements of SDMT- and SCRIPPS scores.Conclusion: DIR MRI seems to be a reliable tool for the frequent assessment of CL-Vs. Overall CL-Vs decreased during the follow-up period and were associated with improvements of cognitive and disability status scores. Our results suggest the presence of short-term CL-V dynamics in RRMS patients and we presume that the laborious evaluation of lesion volumes may be worthwhile for future investigations.Clinical Trial Numbers:www.ClinicalTrials.gov, “The SABA trial”; number: NCT0145012

Postural Sway in Parkinson's Disease and Multiple Sclerosis Patients During Tasks With Different Complexity

Neurological diseases are associated with static postural instability. Differences in postural sway between neurological diseases could include “conceptual” information about how certain symptoms affect static postural stability. This information might have the potential to become a helpful aid during the process of finding the most appropriate treatment and training program. Therefore, this study investigated static postural sway performance of Parkinson's disease (PD) and multiple sclerosis (MS) patients, as well as of a cohort of healthy adults. Three increasingly difficult static postural tasks were performed, in order to determine whether the postural strategies of the two disease groups differ in response to the increased complexity of the balance task. Participants had to perform three stance tasks (side-by-side, semi-tandem and tandem stance) and maintain these positions for 10 s. Seven static sway parameters were extracted from an inertial measurement unit that participants wore on the lower back. Data of 47 healthy adults, 14 PD patients and 8 MS patients were analyzed. Both healthy adults and MS patients showed a substantial increase in several static sway parameters with increasingly complex stance tasks, whereas PD patients did not. In the MS patients, the observed substantial change was driven by large increases from semi-tandem and tandem stance. This study revealed differences in static sway adaptations between PD and MS patients to increasingly complex stance tasks. Therefore, PD and MS patients might require different training programs to improve their static postural stability. Moreover, this study indicates, at least indirectly, that rigidity/bradykinesia and spasticity lead to different adaptive processes in static sway

Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation.

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis

Is multiple sclerosis progression associated with the HLA-DR15 haplotype?

Background The prevalence of multiple sclerosis is associated with the major histocompatibility complex class II DR15 haplotype HLA-DRB1*15:01∼HLA-DRB5*01:01. Objective To assess whether multiple sclerosis progression is associated with the main susceptibility haplotype HLA-DRB1*15:01∼HLA-DRB5*01:01. Methods Patients (n = 1230) and healthy controls (n = 2110) were genotyped for HLA-DRB1 and HLA-DRB5. The baseline Expanded Disability Status Scale (EDSS) score was determined and patients were followed for at least 3 years. Results After follow-up of the consecutive cohort 349 patients were classified as having clinical isolated syndrome and 881 patients as having multiple sclerosis. The susceptibility allele HLA-DRB1*15:01 was more frequent in clinical isolated syndrome (odds ratio 1.56) and multiple sclerosis (odds ratio 3.17) compared to controls. HLA- DRB1*15:01 was the only enriched HLA-DRB1 allele in multiple sclerosis patients. Comparison of clinical characteristics between HLA-DRB1*15:01∼HLA-DRB5*01:01 negative and positive patients with multiple sclerosis showed that baseline EDSS score, disease duration and frequency of the category secondary progressive multiple sclerosis with relapse were increased in the HLA-DRB1*15:01∼HLA-DRB5*01:01 positive group. Conclusion The study confirmed HLA-DRB1*15:01 and HLA-DRB5*01:01 as the main susceptibility alleles and showed weak indirect evidence for a role in progression of the disease

Metabolomic Profiles for Primary Progressive Multiple Sclerosis Stratification and Disease Course Monitoring

Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing-remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies

Metabolomic Profiles for Primary Progressive Multiple Sclerosis Stratification and Disease Course Monitoring

Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing-remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies

Data_Sheet_1_Metabolomic Profiles for Primary Progressive Multiple Sclerosis Stratification and Disease Course Monitoring.docx

<p>Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing-remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.</p

Data_Sheet_6_Metabolomic Profiles for Primary Progressive Multiple Sclerosis Stratification and Disease Course Monitoring.xlsx

<p>Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing-remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.</p

Data_Sheet_4_Metabolomic Profiles for Primary Progressive Multiple Sclerosis Stratification and Disease Course Monitoring.xlsx

<p>Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing-remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.</p

Data_Sheet_3_Metabolomic Profiles for Primary Progressive Multiple Sclerosis Stratification and Disease Course Monitoring.xlsx

<p>Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing-remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.</p