The MoxFo initiative-Mechanisms of action: Biomarkers in multiple sclerosis exercise studies

background: as exercise exerts neurobiological and immunomodulatory effects, it might also act as a disease-modifying intervention in MS. however, a clear mechanistic link between exercise and disease-modifying effects in MS has yet to be established.objective: establish recommendations for future mechanistic exercise studies in MS.Methods: In regular meetings, members of the mechanisms of action group within the MoXFo (Moving eXercise research Forward in MS) initiative evaluated gaps of knowledge and discussed unmet needs in mechanistic MS research.results: we concluded that biomarkers assessed in translational studies in humans and animals are essential to decipher the underlying mechanisms of exercise in MS. consequently, we defined clear definitions of different types of biomarkers examined in MS exercise studies and operationalized their use to align with the research question and optimal testing time points. Furthermore, we provide key considerations to improve the rigor of translational studies and defined minimal reporting criteria for animal studies.conclusion: the resulting recommendations are intended to improve the quality of future mechanistic exercise studies in MS and consequently lead to a better understanding of therapeutic approaches

Cognitive-motor interference in multiple sclerosis and healthy controls: results from single, dual, and triple task posturography

Aim: This article is based on our previous research, which was presented as a poster at the ECTRIMS Congress 2018 and published as a conference abstract (https://www.professionalabstracts.com/ectrims2018/iplanner/#/presentation/1698). Cognitive-motor interference (CMI) has been observed in both healthy controls (HC) and persons with multiple sclerosis (pwMS), but limited and contradictory data is making it difficult to assess the impact of motor and cognitive functioning levels on CMI. The aim of this study was to investigate CMI in pwMS and HC by means of a dual task postural paradigm, to compare them between groups and to analyse the influence of motor and cognitive functioning levels assessed with complementary instruments on observed CMI. Methods: The dual task posturography paradigm serves to quantify the impact of a cognitive (i.e., performing serial subtractions), a motor challenge (closing eyes), or both challenges combined (triple task) on body sway during standing in an upright position feet closed. The data analysed were acquired in one interventional and four observational studies and selected based on predefined criteria and by systematic quality control. A total of 113 pwMS and 42 HC were selected for analysis. Results: Comparable changes in motor and cognitive performance due to cognitive or combined cognitive-motor challenges were observed in both HC and pwMS. Combining both tasks did not result in further changes in motor performance but resulted in a decrease in cognitive performance. This reduction in cognitive performance with an additional motor challenge correlated with lower levels of cognitive and motor functioning in pwMS. Unexpectedly, an increase in body sway due to a cognitive or combined cognitive-motor challenges was primarily observed in pwMS and HC with better cognitive and motor functioning. Conclusions: The results suggest that dual-task effects are not disease-specific but rather reflect individually different adaptation strategies depending on the specific motor and cognitive functioning levels

The MoxFo initiative—Mechanisms of action: Biomarkers in multiple sclerosis exercise studies

Background: As exercise exerts neurobiological and immunomodulatory effects, it might also act as a disease-modifying intervention in MS. However, a clear mechanistic link between exercise and diseasemodifying effects in MS has yet to be established. Objective: Establish recommendations for future mechanistic exercise studies in MS. Methods: In regular meetings, members of the mechanisms of action group within the MoXFo (Moving eXercise research Forward in MS) initiative evaluated gaps of knowledge and discussed unmet needs in mechanistic MS research. Results: We concluded that biomarkers assessed in translational studies in humans and animals are essential to decipher the underlying mechanisms of exercise in MS. Consequently, we defined clear definitions of different types of biomarkers examined in MS exercise studies and operationalized their use to align with the research question and optimal testing time points. Furthermore, we provide key considerations to improve the rigor of translational studies and defined minimal reporting criteria for animal studies. Conclusion: The resulting recommendations are intended to improve the quality of future mechanistic exercise studies in MS and consequently lead to a better understanding of therapeutic approaches.Advanced Clinician-Scientist Fellowship from the BMBF (iSTAR, 01EO2106)Hertie Network of Excellence in Clinical Neuroscience of the Gemeinnützige Hertie- StiftungUniversity Medical Center Hamburg-Eppendorf, Deutsche Forschungsgemeinschaft (SFB1328, SPP1738, KFO296, FOR2289, FOR2879, FOR5068, and FR1720/11-2)Gemeinnützige Hertie-Stiftung, Deutsche Multiple Sklerose Gesellschaft (DMSG; V6.2)Bundesministerium für Bildung und Forschung (Target validation, 16GW0308K

Validation of Computer-Adaptive Contrast Sensitivity as a Tool to Assess Visual Impairment in Multiple Sclerosis Patients

International audienceBackground: Impairment of visual function is one of the major symptoms of people with multiple sclerosis (pwMS). A multitude of disease effects including inflammation and neurodegeneration lead to structural impairment in the visual system. However, the gold standard of disability quantification, the expanded disability status scale (EDSS), relies on visual assessment charts. A more comprehensive assessment of visual function is the full contrast sensitivity function (CSF), but most tools are time consuming and not feasible in clinical routine. The quantitative CSF (qCSF) test is a computerized test to assess the full CSF. We have already shown a better correlation with visual quality of life (QoL) than for classical high and low contrast charts in multiple sclerosis (MS).Objective: To study the precision, test duration, and repeatability of the qCSF in pwMS. In order to evaluate the discrimination ability, we compared the data of pwMS to healthy controls.Methods: We recruited two independent cohorts of MS patients. Within the precision cohort (n = 54), we analyzed the benefit of running 50 instead of 25 qCSF trials. The repeatability cohort (n = 44) was assessed by high contrast vision charts and qCSF assessments twice and we computed repeatability metrics. For the discrimination ability we used the data from all pwMS without any previous optic neuritis and compared the area under the log CSF (AULCSF) to an age-matched healthy control data set.Results: We identified 25 trials of the qCSF algorithm as a sufficient amount for a precise estimate of the CSF. The median test duration for one eye was 185 s (range 129–373 s). The AULCSF had better test–retest repeatability (Mean Average Precision, MAP) than visual acuity measured by standard high contrast visual acuity charts or CSF acuity measured with the qCSF (0.18 vs. 0.11 and 0.17, respectively). Even better repeatability (MAP = 0.19) was demonstrated by a CSF-derived feature that was inspired by low-contrast acuity charts, i.e., the highest spatial frequency at 25% contrast. When compared to healthy controls, the MS patients showed reduced CSF (average AULCSF 1.21 vs. 1.42, p < 0.01).Conclusion: High precision, usability, repeatability, and discrimination support the qCSF as a tool to assess contrast vision in pwMS

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

Enhancing mitochondrial activity in neurons protects against neurodegeneration in a mouse model of multiple sclerosis

While transcripts of neuronal mitochondrial genes are strongly suppressed in central nervous system inflammation, it is unknown whether this results in mitochondrial dysfunction and whether an increase of mitochondrial function can rescue neurodegeneration. Here we show that predominantly genes of the electron transport chain are suppressed in inflamed mouse neurons resulting in impaired mitochondrial complex IV activity. This was associated with posttranslational inactivation of the transcriptional co-regulator PGC-1α. In mice, neuronal overexpression of Ppargc1a, which encodes for PGC-1α, led to increased numbers of mitochondria, complex IV activity and maximum respiratory capacity. Moreover, Ppargc1a overexpressing neurons showed a higher mitochondrial membrane potential that related to an improved calcium buffering capacity. Accordingly, neuronal deletion of Ppargc1a aggravated neurodegeneration during experimental autoimmune encephalomyelitis (EAE), while neuronal overexpression of Ppargc1a ameliorated it. Our study provides systemic insights into mitochondrial dysfunction in neurons during inflammation and commends elevation of mitochondrial activity as a promising neuroprotective strategy

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

Bassoon proteinopathy drives neurodegeneration in multiple sclerosis

Multiple sclerosis (MS) is characterized by inflammatory insults that drive neuroaxonal injury. However, knowledge about neuron-intrinsic responses to inflammation is limited. By leveraging neuron-specific messenger RNA profiling, we found that neuroinflammation leads to induction and toxic accumulation of the synaptic protein bassoon (Bsn) in the neuronal somata of mice and patients with MS. Neuronal overexpression of Bsn in flies resulted in reduction of lifespan, while genetic disruption of Bsn protected mice from inflammation-induced neuroaxonal injury. Notably, pharmacological proteasome activation boosted the clearance of accumulated Bsn and enhanced neuronal survival. Our study demonstrates that neuroinflammation initiates toxic protein accumulation in neuronal somata and advocates proteasome activation as a potential remedy

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